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Printable Version 

Residential Central 

Air Conditioners and 

Heat Pumps 

Preliminary 

Technical Support 

Document 

The U.S. Department of Energy 

(DOE) prepared the preliminary 

technical support document 

(TSD) for the analyses 

conducted for its energy 

conservation standards 

rulemaking on residential 

central air conditioners and heat 

pumps to be published in 2011. 

The following documents are 

available as Adobe Acrobat 

PDFs. Download Adobe Reader. 

z Title Page (PDF 17 KB) 

z List of Acronyms and 

Abbreviations (PDF 15 

KB) 

z Executive Summary (PDF 

527 KB) 

Chapters 

z Chapter 1. Introduction 

(PDF 107 KB) 

z Chapter 2. Analytical 

Framework, Comments 

from Interested Parties, 

and DOE Responses (PDF 

401 KB) 

z Chapter 3. Market and 

Technology Assessment 

(PDF 612 KB) 

z Chapter 4. Screening 

EERE Information Center 

Programs and Offices 

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EERE-2008-BT-STD-0006 COMMENT 54
Analysis (PDF 52 KB) 

z Chapter 5. Engineering 

Analysis (PDF 863 KB) 

z Chapter 6. Markups to 

Determine Equipment 

Price (PDF 223 KB) 

z Chapter 7. Energy Use 

Characterization (PDF 848 

KB) 

z Chapter 8. Life-Cycle Cost 

and Payback Period 

Analysis (PDF 1.8 MB) 

z Chapter 9. Shipments 

Analysis (PDF 532 KB) 

z Chapter 10. National and 

Regional Impact Analysis 

(PDF 1.8 MB) 

z Chapter 11. Life-Cycle 

Cost Sub-group Analysis 

(PDF 29 KB) 

z Chapter 12. Preliminary 

Manufacturer Impact 

Analysis (PDF 123 KB) 

z Chapter 13. Utility Impact 

Analysis (PDF 27 KB) 

z Chapter 14. Employment 

Impact Analysis (PDF 28 

KB) 

z Chapter 15. 

Environmental 

Assessment (PDF 73 KB) 

z Chapter 16. Regulatory 

Impact Analysis (PDF 25 

KB) 

z Chapter 17. Regional 

Standards Impacts on 

Market Participants (PDF 

826 KB) 

Appendices 

z Appendix 3A. Utility 

Rebate Programs (PDF 

696 KB) 

z Appendix 6A. Detailed 

Data for Equipment Price 

Markups (PDF 286 KB) 

z Appendix 7A. Internal 

Loads Schedules and 

Part-Load Performance 

Curves (PDF 127 KB) 

z Appendix 7B. Typical 

Meteorological Year 

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EERE-2008-BT-STD-0006 COMMENT 54
(TMY2) Assignments (PDF 

1.1 MB) 

z Appendix 7C. Proposed 

Regions for Regional 

Standards and Mapping of 

RECS Observations (PDF 

440 KB) 

z Appendix 8A. User 

Instructions for Life-Cycle 

Cost Spreadsheet (PDF 58 

KB) 

z Appendix 8B. Technical 

Aspects of the TariffBased Approach (PDF 75 

KB) 

z Appendix 8C. Comparison 

of Marginal Prices for TOU 

and Default Tariffs (PDF 

70 KB) 

z Appendix 8D. 

Development of Monthly 

Allocation Factors for 

Residential Baseline 

Energy Use (PDF 53 KB) 

z Appendix 8E. Household 

Discount Rate 

Distributions (PDF 69 KB) 

z Appendix 8F. Detailed 

Life-Cycle Cost and 

Payback Period Results 

(PDF 391 KB) 

z Appendix 9A. Relative 

Price Elasticity of Demand 

for Appliances (PDF 137 

KB) 

z Appendix 10A. User 

Instructions for 

Shipments and NIA 

Spreadsheets (PDF 47 

KB) 

z Appendix 12A. Preliminary 

Manufacturer Interview 

Guides (PDF 122 KB) 

z Appendix 15A. Social Cost 

of Carbon for Regulatory 

Impact Analysis Under 

Executive Order 12866 

(PDF 752 KB) 

Contact Information 

Wes Anderson

Project Manager 

(202) 586-7335 

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EERE-2008-BT-STD-0006 COMMENT 54
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Content Last Updated: 04/02/2010 

Printable Version 

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EERE-2008-BT-STD-0006 COMMENT 54
 

PRELIMINARY TECHNICAL SUPPORT DOCUMENT (TSD): 

ENERGY EFFICIENCY PROGRAM FOR CONSUMER 

PRODUCTS AND INDUSTRIAL EQUIPMENT: 

Residential Central Air Conditioners and Heat Pumps 

March 2010 

U.S. Department of Energy 

Assistant Secretary 

Office of Energy Efficiency and Renewable Energy 

Building Technologies Program 

Appliances and Commercial Equipment Standards 

Washington, DC 20585 

EERE-2008-BT-STD-0006 COMMENT 54
This Document was prepared for the Department of Energy
 

by staff members of
 

Navigant Consulting, Inc., 

Lawrence Berkeley National Laboratory,
 

and 

Pacific Northwest National Laboratory
 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

ACRONYMS AND ABBREVIATIONS 

AEC Annual Energy Consumption 

AEO Annual Energy Outlook 

AHRI Air-Conditioning, Heating, and Refrigeration Institute 

ANSI American National Standards Institute 

ASHRAE American Society of Heating, Refrigeration and Air-Conditioning 

Engineers 

ASM Annual Survey of Manufacturers 

BOM bill of materials 

BT building technologies 

BTU British thermal units 

CAC Central air conditioners and heat pumps 

CBEC Commercial Building Energy Consumption Survey 

CEE Consortium for Energy Efficiency 

CFC chlorofluorocarbons 

CFR Code of Federal Regulations 

CIR Current Industry Reports 

COGS cost of goods sold 

CMER consumer marginal energy rates 

CSL candidate standard level 

DC direct current 

DOE U.S. Department of Energy 

DOJ U.S. Department of Justice 

ECM electronically commutated motors 

EER energy efficiency ratio 

EEV electronic expansion valve 

EIA Energy Information Administration 

EISA 2007 Energy Independence and Security Act of 2007 

EPA U.S. Environmental Protection Agency 

EPACT 2005 Energy Policy Act of 2005 

EPCA Energy Policy and Conservation Act of 1975 

°F degrees Fahrenheit 

FEMP Federal Energy Management Program 

FTC U.S. Federal Trade Commission 

GRIM Government Regulatory Impact Model 

HCFC hydrocholorofluorcarbon 

HFC hydrofluorocarbon 

HSPF heating seasonal performance factor 

HVAC heating, ventilation, and air conditioning 

ImSET Impact of Sector Energy Technologies 

kWh kilowatt hours 

LCC life-cycle cost 

LSHX liquid-suction heat exchangers 

MPC manufacturing production cost 

MIA manufacturer impact analysis 

AA-i 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

MLP manufacturer list price 

MPC manufacturer production cost 

MSP manufacturer selling price 

MTA market and technology assessment 

NAECA National Energy Conservation Act of 1987 

NAICS North American Industry Classification System 

NEMS National Energy Modeling System 

NES national energy savings 

NIA national impact analysis 

NPV net present value 

NOPR Notice of Proposed Rulemaking 

OHA Office of Hearings and Appeals 

PBP payback period 

PPI producer price indices 

PSI pounds per square inch 

PSC permanent split capacitor 

R&D research and development 

RTTC Refrigeration and Thermal Test Center 

RIA regulatory impact analysis 

SANOPR Supplemental Advanced Notice of Proposed Rulemaking 

SBA U.S. Small Business Administration 

SDHV small duct, high velocity 

SEC U.S. Securities Exchange Commission 

SEER seasonal energy efficiency ratio 

SET saturated evaporator temperature 

SNOPR Supplemental Notice of Proposed Rulemaking 

SPM shaded-pole motors 

SPVU single-package, vertical unit 

SWEF shipment weighted efficiency data 

TSD Technical Support Document 

TSL trial standard level 

TTW through-the-wall 

TXV thermostatic expansion valve 

USC United States Code 

W watt 

WACC weighted-average cost of capital 

AA-ii 

EERE-2008-BT-STD-0006 COMMENT 54
EXECUTIVE SUMMARY 

TABLE OF CONTENTS 

ES.1 OVERVIEW OF PRELIMINARY ANALYSIS ACTIVITIES ......................................... 1 

ES.2 OVERVIEW OF THE PRELIMINARY ANALYSIS AND THE TECHNICAL
 

SUPPORT DOCUMENT ................................................................................................... 3 

ES.3 KEY RESULTS OF THE ANALYSIS .............................................................................. 4 

ES.3.1 Market and Technology Assessment ...................................................................... 4 

ES.3.2 Screening Analysis.................................................................................................. 5 

ES.3.3 Engineering Analysis.............................................................................................. 5 

ES.3.3.1 Product Classes Analyzed................................................................................. 6 

ES.3.3.2 Manufacturing Cost Assessment....................................................................... 6 

ES.3.4 Markups to Determine Product Price...................................................................... 9 

ES.3.5 Energy Use Characterization .................................................................................. 9 

ES.3.5.1 Residential Energy Use..................................................................................... 9 

ES.3.5.2 Commercial Building Energy Use .................................................................. 11 

ES.3.5.3 Regional Analysis ........................................................................................... 11 

ES.3.6 Life-Cycle Cost and Payback Period Analyses .................................................... 15 

ES.3.7 Shipments Analysis............................................................................................... 18 

ES.3.8 National Impact Analysis...................................................................................... 21 

ES.3.8.1 National Energy Savings................................................................................. 22 

ES.3.8.2 Net Present Value ........................................................................................... 23 

ES.3.9 Preliminary Manufacturer Impact Analysis.......................................................... 29 

ES.4 ISSUES ON WHICH DOE SEEKS PUBLIC COMMENT............................................. 29 

ES-i 

EERE-2008-BT-STD-0006 COMMENT 54
 

LIST OF TABLES 

Table ES.1 Manufacturer Production Cost Estimates for Three-Ton Split-System Air
 

Conditioners: Coil-Only Systems ........................................................................... 7
 

Table ES.2 Manufacturer Production Cost Estimates for Three-Ton Split-System Air
 

Table ES.3 Manufacturer Production Cost Estimates for Three-Ton Split-System Heat Pumps
 

Table ES.4 Manufacturer Production Cost Estimates for Three-Ton Single-Package Air 

Table ES.5 Manufacturer Production Cost Estimates for Three-Ton Single-Package Heat
 

Table ES.7 Regions Defined for the Central Air Conditioner and Heat Pump Regional
 

Table ES.8 Split- System Air Conditioners: Average Annual Energy Use by Efficiency
 

Table ES.9 Split-System Air Conditioners: Average Annual Energy Use by Efficiency
 

Table ES.11 Single-Package Air Conditioners: Average Annual Energy Use by Efficiency
 

Table ES.13 LCC and PBP Summary: Highest SEER and HSPF for Which Mean LCC Savings 

Table ES.18 Split-System Air Conditioners: Discounted Cumulative NPV Results (3% 

Table ES.19 Split-System Air Conditioners: Discounted Cumulative NPV Results (7% 

Conditioners: Blower-Coil Systems ....................................................................... 7
 

................................................................................................................................. 8
 

Conditioners............................................................................................................ 8
 

Pumps...................................................................................................................... 8
 

Table ES.6 National Average Markups for Central Air Conditioners and Heat Pumps ........... 9
 

Analysis................................................................................................................. 12
 

Level⎯Coil-Only Systems................................................................................... 13
 

Level—Blower-Coil Systems ............................................................................... 13
 

Table ES.10 Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level .... 14
 

Level ..................................................................................................................... 14
 

Table ES.12 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level 15
 

are Positive, and Corresponding Median PBP in Years ....................................... 17
 

Table ES.14 Split-System Air Conditioners: Cumulative NES Results (quads)....................... 22
 

Table ES.15 Split-System Heat Pumps: Cumulative NES Results (quads) .............................. 23
 

Table ES.16 Single-Package Air Conditioners: Cumulative NES Results (quads)................... 23
 

Table ES.17 Single-Package Heat Pumps: Cumulative NES Results (quads) .......................... 23
 

Discount Rate) ...................................................................................................... 25
 

Discount Rate) ...................................................................................................... 26
 

Table ES.20 Split-System Heat Pumps: Discounted Cumulative NPV Results........................ 27
 

Table ES.21 Single-Package Air Conditioners: Discounted Cumulative NPV Results............ 27
 

Table ES.22 Single-Package Heat Pumps: Discounted Cumulative NPV Results ................... 28
 

ES-ii 

EERE-2008-BT-STD-0006 COMMENT 54
LIST OF FIGURES 

Figure ES.1 Flow Diagram of Analyses for the Residential Central Air Conditioner and Heat 

Pump Rulemaking Process ..................................................................................... 2
 

Figure ES.2 Forecasted Shipments (Base Case) for Split-System Air Conditioners, Coil-Only
 

Figure ES.3 Forecasted Shipments (Base Case) for Split-System Air Conditioners, Blower-

............................................................................................................................... 19
 

Coil........................................................................................................................ 19
 

Figure ES.4 Forecasted Shipments (Base Case) for Split-System Heat Pumps ....................... 20
 

Figure ES.5 Forecasted Shipments (Base Case) for Single-Package Air Conditioners............ 20
 

Figure ES.6 Forecasted Shipments (Base Case) for Single-Package Heat Pumps ................... 21
 

ES-iii 

EERE-2008-BT-STD-0006 COMMENT 54
 

EXECUTIVE SUMMARY 

ES.1 OVERVIEW OF PRELIMINARY ANALYSIS ACTIVITIES
 

The Energy Policy and Conservation Act, as amended (42 U.S.C. 6291 et seq.; EPCA), 

directs the U.S. Department of Energy (DOE) to consider amending the energy conservation 

standards for residential central air conditioners and heat pumps established under EPCA. (42 

U.S.C. 6295(d)(3)(B)) Any amended standard must be designed to “achieve the maximum 

improvement in energy efficiency ... which the Secretary determines is technologically feasible 

and economically justified.” (42 U.S.C. 6295(o)(2)(A)). This executive summary provides an 

overview of DOE’s preliminary analysis in consideration of amended energy conservation 

standards for residential central air conditioners and heat pumps. This summary describes key 

results from DOE’s analyses and delineates issues about which it seeks comment from interested 

parties. These issues will be highlighted in the public meeting presentation on this preliminary 

technical support document (preliminary TSD) and discussed in chapter 2 of the preliminary 

TSD. 

Figure ES.1 presents a summary of the analytical components of the standards-setting 

process and illustrates how key results are generated. The focal point of the figure is the center 

column, labeled “Analyses.” The columns labeled “Key Inputs” and “Key Outputs” show how 

the analyses fit into the process and how they relate to each other. Key inputs are the types of 

data and other information that the analyses require. DOE obtains some key information from 

public databases; it collects other inputs from interested parties or persons having special 

knowledge and expertise. Arrows connecting analyses show the types of information that feed 

from one analysis to another. Key outputs are analytical results that feed directly into the 

standards-setting process. The issues on which DOE seeks comment derive from the preliminary 

analysis. 

ES-1 

EERE-2008-BT-STD-0006 COMMENT 54
Framework Document 

Figure ES.1 Flow Diagram of Analyses for the Residential Central Air Conditioner and 

Heat Pump Rulemaking Process 

Utility Impact

Analysis 

Notice of Proposed Rulemaking (NOPR) 

Final Rule 

Market and Technology 

Assessment 

Screening Analysis 

Engineering Analysis 

Markups for 

Product Price 

Determination Life-Cycle Cost and 

Payback Period

Analyses 

National Impact

Analysis 

Energy Use 

Revise Preliminary 

Analysis 

Life-Cycle Cost 

Sub-group Analysis 

Manufacturer Impact 

Analysis 

Shipments 

Analysis 

Employment Impact

Analysis 

Revise Analyses 

• Product Classes 

• Technology Options 

• Industry Cash Flow 

• Subgroup Cash Flow 

• Direct Employment Impacts 

• Competitive Impacts 

• Cumulative Regulatory Burden 

• Cost-Efficiency Relationship 

• Life-Cycle Costs 

• Payback Periods 

• National Energy Savings 

• Net Present Values 

• National Employment Impacts 

• Revised Results 

• Market Segmentation 

• Non-Regulatory Programs 

• Energy Prices 

• Installation Costs 

• Maintenance & Repair Costs 

• Backcast and Forecast 

• Market Saturation 

• Stakeholder Comments 

• Demographics 

• Emission Rates 

• National Energy Savings 

• Stakeholder Comments 

• Identify Firms/Products 

• Historical Shipments 

• Manufacturer Prices 

• Average Costs 

• Manufacturer Financial Data 

Design Options 

Product Classes 

Retail Prices 

Design Energy 

Preliminary Analysis 

• Efficiency/Performance 

• Manufacturing Cost 

Candidate 

Standard 

Levels 

Environmental 

Assessment 

Regulatory Impact 

Analysis 

Technology Options 

• Emission Estimates 

• Utility Load Factors 

• National Energy Savings 

• Non-Regulatory 

Alternatives 

• Design Options 

• Energy Price Forecasts 

• Site-to-Source Factors 

• Energy-Efficiency Levels 

Direct Employment 

Impacts 

• National Energy Savings 

• National Product Costs 

• National Operating Costs 

• Utility Impacts 

• Life-Cycle Costs 

• Payback Periods 

• Installation 

Costs 

• Maint Costs • Repair Costs 

• UEC 

• Energy 

Prices 

• Annual Energy Use (UEC) 

Preliminary 

Manufacturer Impact 

Analysis 

• Manufacturer Prices 

• Average Costs 

• Conversion Capital Expenditures 

• Direct Employment Impacts 

• National Energy Savings 

• Net Present Values 

• Trial Standard Levels (TSLs) 

TSLs 

• Product Prototypes 

Energy Efficiency 

Levels 

• Department of Justice Review 

ES-2
 

EERE-2008-BT-STD-0006 COMMENT 54
ES.2	 OVERVIEW OF THE PRELIMINARY ANALYSIS AND THE TECHNICAL 

SUPPORT DOCUMENT 

This preliminary TSD details each preliminary analysis, inputs, sources, methodologies, 

and results. Chapter 2 of this preliminary TSD provides an overview of each preliminary 

analysis, the comments received in response to the analytical approaches DOE described in the 

framework document, and DOE’s responses to those comments. 

The following is a brief description of the chapters in the preliminary TSD that address 

the preliminary analyses performed by DOE: 

•	 The market and technology assessment (MTA) characterizes the relevant product markets 

and technology options, including prototype designs (chapter 3). 

•	 The screening analysis reviews each technology option to determine whether it is 

technologically feasible; is practicable to manufacture, install, and service; would 

adversely affect product utility or product availability; or would have adverse impacts on 

health and safety (chapter 4). 

•	 The engineering analysis develops cost-efficiency relationships that show a 

manufacturer’s cost of achieving increased efficiency. DOE uses manufacturer markups 

to convert manufacturer production cost (MPC) to manufacturer selling price (MSP) 

(chapter 5). 

•	 The markups analysis converts the MSPs derived from the engineering analysis to 

consumer product prices (chapter 6). 

•	 The energy use analysis determines the annual energy use in the field of the considered 

products (chapter 7). 

•	 The life-cycle cost (LCC) and payback period (PBP) analyses calculate, at the consumer 

level, the discounted savings in operating costs throughout the estimated average life of 

the covered products, compared to any increase in the product’s installed cost likely to 

result directly from the imposition of a given standard (chapter 8). 

•	 The shipments analysis forecasts product shipments, which then are used to calculate the 

national impacts of standards on energy consumption, the net present value (NPV) of 

consumer costs and savings, and future manufacturer cash flows (chapter 9). 

•	 The national impact analysis (NIA) assesses the cumulative national energy savings 

(NES) from standards and the NPV of consumer costs and savings associated with 

standards at different efficiency levels (chapter 10). 

•	 The preliminary manufacturer impact analysis (MIA) assesses the potential impacts of 

energy conservation standards on manufacturers, such as effects on expenditures for 

ES-3 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

capital conversion, marketing costs, shipments, and research and development costs 

(chapter 12). 

The remaining chapters of the preliminary TSD address the analyses to be performed for 

the NOPR stage: 

•	 The life-cycle cost analysis for subgroups evaluates the effects of energy conservation 

standards on various national subgroups of the population (chapter 11). 

•	 The utility impact analysis examines impacts of energy conservation standards on the 

generation capacity of electric utilities (chapter 13). 

•	 The employment impact analysis examines the effects of energy conservation standards 

on national employment (chapter 14). 

•	 The environmental assessment examines the effects of energy conservation standards on 

various airborne emissions (chapter 15). 

•	 The regulatory impact analysis examines the national impacts of non-regulatory
 

alternatives to mandatory energy conservation standards (chapter 16). 

ES.3 KEY RESULTS OF THE ANALYSIS 

The following sections describe in detail the analyses DOE performed in support of the 

preliminary TSD and present the key results. 

ES.3.1 Market and Technology Assessment 

When initiating an analysis of potential energy efficiency standards for appliances, DOE 

develops information on the present and past industry structure and market characteristics for the 

products concerned. This activity assesses industries and products both quantitatively and 

qualitatively based on publicly available information. 

DOE generally divides covered products into product classes by the type of energy used, 

or by capacity or other performance-related features that affect efficiency. Different energy 

conservation standards may apply to different product classes. (42 U.S.C. 6295(q)) The product 

classes that DOE is considering in this rulemaking are as follows: 

•	 Split-System Air Conditioners 

•	 Split-System Heat Pumps 

•	 Single-Package Air Conditioners 

•	 Single-Package Heat Pumps 

•	 Small-Duct High-Velocity Systems (SDHV) 

•	 Space-Constrained Air Conditioners 

•	 Space-Constrained Heat Pumps 

ES-4 

EERE-2008-BT-STD-0006 COMMENT 54
 

For the residential central air conditioner and heat pump products that are covered by this 

rulemaking, DOE gathered information on (1) manufacturer market share and characteristics, (2) 

existing regulatory and non-regulatory initiatives for improving product efficiency, and (3) 

trends in product characteristics and retail markets. 

DOE reviewed literature and interviewed manufacturers to develop an overall 

understanding of the residential central air conditioner and heat pump products industry in the 

United States. Industry publications, including trade journals, as well as literature from 

manufacturers, government agencies, and trade organizations provided the bulk of the 

information, including (1) manufacturers and their market share, (2) shipments by product type, 

(3) product information, and (4) industry trends. Chapter 3 of the preliminary TSD describes the 

market analysis and resulting information. 

DOE typically uses information about existing and past technology options and prototype 

designs to determine which technologies and combinations of technologies manufacturers use to 

improve energy efficiency. In consultation with interested parties, DOE developed a list of 

technologies to consider, for residential central air conditioner and heat pump products, from 

trade publications, technical papers, and manufacturer literature, and through consultation with 

manufacturers of components and systems. Product literature and direct examination provided 

additional information, because existing products contain many technologies for improving 

product efficiency. Before performing the screening analysis, DOE removed from the list those 

technologies for which the energy consumption could not be adequately measured using the 

relevant DOE test procedure. 

ES.3.2 Screening Analysis 

Next, DOE performed a screening analysis to examine whether the technologies DOE 

identified (1) are technologically feasible; (2) are practicable to manufacture, install, and service; 

(3) have an adverse impact on product utility or availability; and/or (4) have adverse impacts on 

health and safety. DOE conducts this analysis in consultation with interested parties. In the 

subsequent engineering analysis, DOE further examines the technology options that it did not 

remove from consideration pursuant to the screening analysis. 

ES.3.3 Engineering Analysis 

In the engineering analysis (chapter 5), DOE established the relationship between the cost 

of manufacturing residential central air conditioner and heat pumps and their efficiency. This 

relationship served as the basis for calculating costs and benefits of modified product designs for 

consumers, manufacturers, and the nation. Chapter 5 of the preliminary TSD describes the 

product classes that DOE analyzed, the representative baseline units, the efficiency levels DOE 

considered, the methodology that DOE used to develop the manufacturing production cost 

model, and the cost-efficiency results. 

ES-5 

EERE-2008-BT-STD-0006 COMMENT 54
 

ES.3.3.1 Product Classes Analyzed 

The engineering analysis directly analyzed the four primary residential central air 

conditioner and heat pump product classes: (1) split-system air conditioners; (2) split-system heat 

pumps; (3) single-package air conditioners; and (4) single-package heat pumps. These four 

product classes represent most of the total shipments of residential central air conditioners and 

heat pumps. 

For the other three product classes identified in section ES.3.1, DOE found that product 

offerings and available information were limited. Therefore, in chapter 5 of the preliminary TSD, 

DOE describes the technical characteristics and potential areas of energy savings for these 

product classes for the preliminary analysis. DOE intends to fully analyze these product classes 

for the NOPR if it can obtain enough information to quantify potential areas of energy savings. 

DOE requests feedback and data on potential areas of energy savings for space-constrained 

products and SDHV systems. Chapter 5 of the preliminary TSD includes additional details on the 

representative product classes and the cost-efficiency curves developed as part of the engineering 

analysis. 

ES.3.3.2 Manufacturing Cost Assessment 

DOE estimated the manufacturing costs associated with an increase in energy efficiency 

for each of the residential central air conditioner and heat pump product classes analyzed using 

aggregated manufacturer data. The assessment method involved disassembling particular units, 

analyzing the materials in each unit and the manufacturing processes used to produce it, 

analyzing the design approaches manufacturers use, and developing a spreadsheet model to 

evaluate costs. DOE developed a detailed model to estimate the manufacturers product cost 

(MPC) at various efficiency levels. Chapter 5 of the preliminary TSD includes information on 

the inputs DOE used to determine the manufacturing cost, including material, labor, and 

overhead costs. Chapter 5 also includes information on the various components and features 

incorporated into designs for residential central air conditioner and heat pump products. 

DOE’s engineering analysis produced cost-efficiency curves for the four primary 

residential central air conditioner and heat pump product classes. The cost-efficiency curves are 

described by the efficiency levels and the increase in MPC above the baseline for each level. The 

split-system air conditioner and heat pump product classes have two different rating methods for 

determining their seasonal energy efficiency ratio (SEER), depending on whether the fan blower 

is included in the rating. If a system is rated as a “coil-only” system, the SEER is calculated 

using a default fan power. These systems are generally representative of a condensing unit and 

evaporator coil installed with an existing furnace. If a system is rated as a “blower-coil” system, 

the SEER is calculated using a specific fan power. In coil-only systems, only the outdoor 

condensing unit and evaporator coil can be modified to achieve higher system efficiencies; in 

blower-coil systems, which are generally representative of a condensing unit installed with an air 

handler, the outdoor condensing unit, evaporator coil, and fan blower can all be modified to 

achieve higher system efficiencies. 

DOE assumed that coil-only systems and blower-coil systems are both prevalent in the 

split-system air-conditioning market, whereas blower-coil systems are believed to be the 

ES-6 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

overwhelming type of installation in the split-system heat pump market because it is more 

important to match the indoor and outdoor components to obtain proper performance. Therefore, 

DOE characterized the split-system air conditioner product class by developing separate costefficiency curves for coil-only systems and blower-coil systems. DOE characterized the splitsystem heat pump product class using only blower-coil systems. DOE requests comment on the 

market shares of coil-only and blower-coil systems for both split-system air conditioners and 

split-system heat pumps. DOE also requests comment on whether an additional coil-only 

engineering analysis is necessary to characterize split-system heat pumps. Table ES.1 through 

Table ES.5 present the key results of the engineering analysis. 

Table ES.1	 Manufacturer Production Cost Estimates for Three-Ton Split-System Air 

Conditioners: Coil-Only Systems 

Efficiency Level 

SEER 

System Cost 

(without air handler) 

$ 

13.0 580 

13.5 615 

14.0 651 

14.5 692 

15.0 739 

15.5 797 

16.0 871 

16.5* 957 

* Max-tech efficiency level 

Table ES.2	 Manufacturer Production Cost Estimates for Three-Ton Split-System Air 

Conditioners: Blower-Coil Systems 

Efficiency Level SEER 

System Cost 

(with air handler) 

$ 

13.0 715 

13.5 754 

14.0 793 

14.5 834 

15.0 864 

15.5 895 

16.0 927 

17.0 995 

18.0 1,068 

19.0 1,147 

20.0 1,232 

21.0 1,324 

22.0* 1,422 

* Max-tech efficiency level 

ES-7 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table ES.3 Manufacturer Production Cost Estimates for Three-Ton Split-System Heat 

Pumps 

Efficiency Level 

SEER HSPF 

System Cost 

(with air handler) 

$ 

13.0 7.70 861 

13.5 7.85 904 

14.0 8.00 951 

14.5 8.15 986 

15.0 8.30 1,020 

15.5 8.45 1,057 

16.0 8.60 1,105 

17.0 9.10 1,188 

18.0 9.60 1,276 

19.0 10.10 1,372 

19.5* 10.30 1,423 

* Max-tech efficiency level 

Table ES.4	 Manufacturer Production Cost Estimates for Three-Ton Single-Package Air 

Conditioners 

Efficiency Level 

SEER 

System Cost 

$ 

13.0 726 

13.5 792 

14.0 835 

14.5 900 

15.0 952 

15.5 1,018 

16.0 1,097 

16.6* 1,209 

* Max-tech efficiency level 

Table ES.5	 Manufacturer Production Cost Estimates for Three-Ton Single-Package 

Heat Pumps 

Efficiency Level 

SEER HSPF 

System Cost 

$ 

13.0 7.7 899 

13.5 7.9 940 

14.0 8.0 994 

14.5 8.0 1,073 

15.0 8.0 1,142 

15.5 8.5 1,222 

16.0 9.0 1,318 

16.4* 9.0 1,414 

* Max-tech efficiency level 

ES-8 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

ES.3.4 Markups to Determine Product Price 

In the markups analysis (chapter 6), DOE developed appropriate markups in the 

distribution chain to convert the estimates of manufacturer cost derived in the engineering 

analysis to consumer prices. In developing markups, DOE estimated markups taken by 

wholesalers, mechanical contractors, and general contractors, along with sales taxes. DOE 

calculated markups separately for installations in new construction and for replacements. DOE 

also developed separate markups for baseline products (baseline markups) and for the cost 

increase associated with improvements required to produce more efficient products (incremental 

markups). 

Table ES.6 summarizes the markups developed for central air conditioner and heat 

pumps. The markups shown in this table reflect national average values for the given markup. In 

the subsequent LCC analysis, DOE also developed regional markup multipliers to capture 

regional variation in mechanical contractor markups, general contractor markups, and sales tax. 

Table ES.6 National Average Markups for Central Air Conditioners and Heat Pumps 

Baseline Markups Incremental Markups 

Replacement 

Market 

New Construction 

Market 

Replacement 

Market 

New Construction 

Market 

Wholesaler 1.37 1.37 1.11 1.11 

Mechanical 1.38 1.28 1.12 1.04 

General - 1.29 - 1.17 

Sales Tax 1.07 1.07 1.07 1.07 

Overall 2.02 2.42 1.33 1.45 

ES.3.5 Energy Use Characterization 

The energy use characterization provides the basis for developing the energy savings 

from using higher efficiency central air conditioners and heat pumps. The energy savings results 

are incorporated in the LCC and other subsequent analyses. The DOE test procedure provides 

standardized metrics that serve as the basis for comparing the energy consumption of different 

product efficiency levels. It provides a standardized estimate of the seasonal efficiency for each 

air conditioner design. DOE uses the SEER rating to establish an estimate of seasonal cooling 

efficiency for different product designs. For heat pumps, DOE used the national HSPF rating to 

establish an estimate of relative heating efficiency. Since actual usage of central air conditioners 

and heat pumps in the field varies significantly as a function of climate and household use 

preferences, DOE used other data sources to estimate actual baseline energy consumption. 

ES.3.5.1 Residential Energy Use 

Residential households form the largest installed base of central air conditioners and heat 

pumps. For the residential energy use analysis, DOE used the SEER and HSPF estimates from 

the engineering analysis to scale baseline energy consumption estimates to reflect higher SEER 

and HSPF efficiencies. DOE represented the energy consumption of the product at each 

efficiency level using a distribution that accounts for variation in usage and climate conditions 

based on a representative sample of households across the nation. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

The representative sample of households is a subset of the households from the 2005 

Residential Energy Consumption Survey (RECS) produced by the Energy Information 

Administration (EIA), the most recent survey available. RECS is a national sample survey that 

collects statistical information on the consumption of and expenditures for energy in housing 

units along with data on energy-related characteristics of the housing units and occupants. Out of 

a total of 4,382 households surveyed in the 2005 RECS, 1,854 qualified for the central air 

conditioner analysis and 339 qualified for the central heat pump analysis. A small number of 

households reporting use of central air conditioners were not used in the DOE sample for 

specific reasons─ e.g., for reported non-use of the central air-conditioning system or for 

concurrent use of another air-conditioning product type in the same household. 

For each household in the sample, DOE developed a cooling unit energy consumption 

(UEC) as well as a heating UEC for homes served by heat pumps. The UEC was based on the 

reported cooling and heating energy use in RECS for 2005 and is associated with the stock 

products (UECres_stock_non-adj) used in each household. Based on 1987-2007 cooling degree day 

data from the National Oceanographic and Atmospheric Administration National Climatic Data 

Center (NCDC), DOE then normalized this UEC data to long-term average climate conditions 

through the use of a weather adjustment factor developed for each census division and applied to 

all households within the census division. The actual 2005 cooling energy use for each RECS 

household was multiplied by this weather-adjustment factor to generate a weather-normalized 

UECres_stock. For heat pumps, DOE carried out a similar weather normalization using 30-year 

average heating degree day data. 

The weather-adjusted UEC is further adjusted to provide base-case energy consumption 

for 2016 (the start year for LCC analysis) for new central air conditioner and heat pump 

purchasers. The underlying assumption for the energy use characterization is the same that is 

used in the LCC analysis, i.e., that the representative sample of customers will replace or 

purchase new air conditioners in 2016, the year that revised central air-conditioning and heat 

pump standards go into effect. To model a base-case standards scenario for the energy use 

analysis, DOE first used central air conditioner and heat pump vintage data in RECS to establish 

the year that the stock RECS central air conditioner and heat pump unit was installed. It then 

used data on the historical average efficiency for central air conditioners and heat pumps by year 

to estimate the SEER and HSPF for the products in the RECS household. This stock efficiency is 

associated with the UEC values for the individual RECS household observations. Because 

customers are presumed to purchase air conditioners in 2016, DOE used current estimates of the 

efficiency distribution for shipments (by product class) as shipment efficiency weights 

appropriate to new purchases in 2016 in the base case. DOE then selected efficiencies for new 

shipments to each household based on the efficiency distributions. DOE then scaled the weathernormalized UECres_stock cooling and heating electrical energy use by the ratio of selected 

replacement efficiency to RECS stock efficiency established for each household. Because stock 

efficiencies are in general lower than current shipped efficiencies, adjusting the weathernormalized stock energy use by the replacement-to-stock efficiency ratio reduces the estimate for 

household cooling and heating energy consumption to reflect the 2016 base case used for the 

LCC analysis. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

ES.3.5.2 Commercial Building Energy Use 

Central air conditioners and heat pumps are also used in many smaller commercial 

buildings. DOE has estimated the fraction shipped for commercial building applications at 

approximately 7 percent based on industry estimates. For commercial buildings, DOE followed 

the path outlined in the framework document to estimate the energy savings for shipments of 

higher efficiency products. The framework document used the EnergyPlus building energy 

simulation software to simulate the energy consumption of central air conditioners and heat 

pumps used to satisfy the cooling, supply fan—and in the case of central heat pumps, the heating 

energy—required in a small office building. DOE used an existing small office building model 

developed for DOE’s energy benchmarking task for this analysis. DOE simulated the building in 

237 climates corresponding to each of the Typical Meteorological Year (TMY2) weather 

locations within the 50 states. DOE simulated the same building served either by central air 

conditioners or heat pumps and simulated the product for each product type using a 13 SEER, 14 

SEER, 16 SEER, and max tech level for either central air conditioners (SEER 22) (based on 

blower-coil ratings) or central heat pumps (SEER 19.5). Product parameters used in the 

simulation were adjusted to reflect engineering designs corresponding to each efficiency level. 

The simulated building used five individual central air-conditioning and heat pump units. 

DOE extracted the annual energy consumption for cooling and fan energy use and central heat 

pump heating from each unit as well as the product capacity from each unit from each simulation 

run and aggregated these to the whole building level. Using this whole building data, DOE 

normalized the central air conditioner and heat pump energy consumption for each location and 

efficiency level to reflect that of an average 3-ton central air-conditioning or heat pump unit, for 

use in the LCC analysis. To estimate the energy consumption for intermediate efficiency levels 

between those simulated, DOE linearly interpolated the energy use estimates based on the results 

for the four simulated efficiencies. 

DOE used population-based weighting factors developed for each climate to represent the 

relative percentage of customers experiencing each climate in each state, at the national level, 

and in each of three geographic regions being used to assess regional standards (see below). 

These weighting factors, in conjunction with the relative weighting between commercial and 

residential shipments, were used to incorporate the commercial building energy consumption 

into the overall energy consumption for central air conditioners and heat pumps at each 

efficiency level. 

ES.3.5.3 Regional Analysis 

EPCA allows DOE to consider regional standards for central air conditioners and heat 

pumps. DOE defined two separate geographic regions to assess proposed regional standards. One 

is a hot-humid region, consisting of 12 states in the southeastern United States; the second is a 

hot-dry region, consisting of four states in the Southwest. The states comprising the regions are 

listed in Table ES.7. Chapter 7 details the development of these regions. The remainder of the 

United States, to which only the national standard will be applicable, was labeled “Rest of 

Country.” The LCC analysis was conducted both at a national level and at a regional level using 

residential and commercial customer populations defined for each region (based on analysis of 

RECS data for the residential population and the climate weighting factors developed for the 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

commercial analysis). Chapter 7 of the preliminary TSD provides more details on the methods, 

data, and assumptions used for developing the adjusted UECs. 

Table ES.7	 Regions Defined for the Central Air Conditioner and Heat Pump Regional 

Analysis 

Hot-Humid 

(Region 1) 

Hot-Dry 

(Region 2) 

Rest-of-Country 

(Region 0) 

Alabama Arizona Alaska Nebraska 

Arkansas California Colorado New Hampshire 

Florida Nevada Connecticut New Jersey 

Georgia New Mexico Delaware New York 

Hawaii District of Columbia North Dakota 

Louisiana Idaho Ohio 

Mississippi Illinois Oregon 

North Carolina Indiana Pennsylvania 

Oklahoma Iowa Rhode Island 

South Carolina Kansas South Dakota 

Tennessee Kentucky Utah 

Texas Maine Vermont 

Maryland Virginia 

Massachusetts Washington 

Michigan West Virginia 

Minnesota Wisconsin 

Missouri Wyoming 

Montana 

Table ES.8 through Table ES.12 present the average annual energy use for the 

representative product classes at each energy efficiency level DOE considered. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table ES.8 Split- System Air Conditioners: Average Annual Energy Use by Efficiency 

Level⎯Coil-Only Systems 

Efficiency Level 

Annual Energy Consumption 

kilowatt hours per year (kWh/yr) 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF*

 Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,407 0 3,564 0 2,176 0 1,378 0 

Market 

Baseline 

Market 

Baseline N/A 2,291 0 3,393 0 2,071 0 1,310 0 

2 13.5 N/A 2,322 0 3,437 0 2,100 0 1,331 0 

3 14.0 N/A 2,243 0 3,318 0 2,029 0 1,287 0 

4 14.5 N/A 2,168 0 3,205 0 1,960 0 1,244 0 

5 15.0 N/A 2,097 0 3,100 0 1,897 0 1,204 0 

6 15.5 N/A 2,031 0 3,002 0 1,836 0 1,166 0 

7 16.0 N/A 1,968 0 2,909 0 1,780 0 1,130 0 

8 16.5 N/A 1,912 0 2,825 0 1,730 0 1,099 0 

*N/A means not applicable. 

Table ES.9	 Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level—Blower-Coil Systems 

Efficiency Level 

Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,433 0 3,584 0 2,172 0 1,365 0 

Market 

Baseline 

Market 

Baseline N/A 2,315 0 3,410 0 2,067 0 1,302 0 

2 13.5 N/A 2,347 0 3,455 0 2,096 0 1,319 0 

3 14.0 N/A 2,267 0 3,336 0 2,025 0 1,275 0 

4 14.5 N/A 2,190 0 3,223 0 1,957 0 1,233 0 

5 15.0 N/A 2,119 0 3,117 0 1,893 0 1,193 0 

6 15.5 N/A 2,052 0 3,018 0 1,833 0 1,155 0 

7 16.0 N/A 1,988 0 2,925 0 1,777 0 1,120 0 

8 16.5 N/A 1,932 0 2,840 0 1,727 0 1,089 0 

9 17.0 N/A 1,878 0 2,760 0 1,679 0 1,060 0 

10 18.0 N/A 1,780 0 2,613 0 1,592 0 1,007 0 

11 19.0 N/A 1,692 0 2,482 0 1,514 0 960 0 

12 20.0 N/A 1,613 0 2,363 0 1,444 0 917 0 

13 21.0 N/A 1,541 0 2,256 0 1,380 0 878 0 

14 22.0 N/A 1,476 0 2,158 0 1,322 0 842 0 

*N/A means not applicable. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

Table ES.10 Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level 

Efficiency Level 

Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,487 1,749 4,275 1,275 4,203 924 1,978 2,968 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 3,268 1,687 4,006 1,230 3,937 891 1,857 2,862 

2 13.5 7.85 3,363 1,716 4,122 1,251 4,053 906 1,909 2,912 

3 14.0 8.00 3,248 1,685 3,980 1,228 3,913 890 1,846 2,859 

4 14.5 8.15 3,138 1,654 3,845 1,206 3,780 873 1,784 2,808 

5 15.0 8.30 3,035 1,625 3,719 1,184 3,656 858 1,726 2,758 

6 15.5 8.45 2,939 1,597 3,601 1,163 3,539 843 1,671 2,711 

7 16.0 8.60 2,848 1,570 3,490 1,143 3,430 828 1,620 2,665 

8 17.0 9.10 2,688 1,485 3,293 1,081 3,235 783 1,531 2,522 

9 18.0 9.60 2,545 1,409 3,117 1,026 3,062 743 1,452 2,395 

10 19.0 10.10 2,417 1,341 2,959 976 2,907 706 1,381 2,279 

11 19.5 10.30 2,358 1,315 2,886 957 2,835 693 1,348 2,236 

Table ES.11 Single-Package Air Conditioners: Average Annual Energy Use by Efficiency 

Level 

Efficiency Level 

Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF*

 Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,376 0 3,602 0 2,170 0 1,363 0 

Market 

Baseline 

Market 

Baseline N/A 2,348 0 3,559 0 2,144 0 1,348 0 

2 13.5 N/A 2,292 0 3,473 0 2,093 0 1,316 0 

3 14.0 N/A 2,214 0 3,353 0 2,022 0 1,273 0 

4 14.5 N/A 2,139 0 3,239 0 1,954 0 1,230 0 

5 15.0 N/A 2,070 0 3,133 0 1,890 0 1,191 0 

6 15.5 N/A 2,004 0 3,033 0 1,831 0 1,153 0 

7 16.0 N/A 1,942 0 2,940 0 1,774 0 1,118 0 

8 16.6 N/A 1,876 0 2,838 0 1,714 0 1,081 0 

*N/A means not applicable. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

Table ES.12 Single-Package Heat Pumps: Average Annual Energy Use by Efficiency 

Level 

Efficiency Level 

Annual Energy Consumption 

 kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,464 1,720 4,295 1,272 4,211 927 1,964 2,953 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 3,372 1,698 4,179 1,256 4,098 915 1,914 2,916 

2 13.5 7.85 3,341 1,688 4,141 1,248 4,060 910 1,896 2,898 

3 14.0 8.00 3,227 1,657 3,999 1,225 3,920 893 1,833 2,845 

4 14.5 8.00 3,117 1,657 3,863 1,225 3,787 893 1,772 2,845 

5 15.0 8.00 3,015 1,657 3,737 1,225 3,663 893 1,714 2,845 

6 15.5 8.50 2,920 1,561 3,618 1,154 3,546 841 1,660 2,682 

7 16.0 9.00 2,829 1,476 3,506 1,091 3,436 795 1,609 2,538 

8 16.4 9.00 2,763 1,476 3,424 1,091 3,356 795 1,572 2,537 

ES.3.6 Life-Cycle Cost and Payback Period Analyses 

Stipulating new energy conservation standards for products results in changes in 

consumer operating expenses—usually a decrease—and changes in consumer price—usually an 

increase. DOE analyzed the net effect of revised standards on consumers by evaluating the LCCs 

using the cost-efficiency relationships derived in the engineering analysis, as well as the energy 

costs derived from the energy use characterization. Inputs to the LCC calculation included the 

installed cost to the consumer (purchase price plus installation cost), operating costs (energy 

expenses, repair, and maintenance), the lifetime of the appliance, and a discount rate. 

The installed cost of a product typically increases while operating cost typically decreases 

in response to new standards. Therefore, there is a point in time for higher efficiency products 

when the cumulative net operating-cost savings (in dollars) since the time of purchase is equal to 

the increase in the purchase price. The length of time required for products to reach this costequivalence point is known as the payback period (PBP). 

DOE conducted the LCC and PBP analyses using values that reflect energy consumption 

in the field. DOE identified several inputs for estimating the LCC, including retail product 

prices, energy prices, discount rates, and product lifetimes. DOE used EIA’s energy price data to 

determine prices for electricity in 2007, and used projections of these energy prices from the 

April 2009 update to EIA’s Annual Energy Outlook 2009 to estimate future energy prices. DOE 

developed discount rates from estimates of the finance costs for consumers and commercial 

businesses that purchase central air conditioners and heat pumps. 

Because the basis for the lifetime estimates in the literature for air-conditioning products 

is uncertain, DOE used actual data sources to estimate the distribution of central air conditioner 

and heat pump lifetimes in the field. DOE estimated the fraction of appliances of a given age still 

in operation by combining survey results from RECS and the U.S. Census’s American Housing 

Survey with historical appliance shipments. The resulting survival function, which DOE assumed 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

has the form of a cumulative Weibull distribution, provides an average and median appliance 

lifetime. 

There are number of potential complications concerning the configuration of air 

conditioning equipment sold in the future marketplace that affect how efficiency can be 

measured and achieved. For example, efficiency ratings for air conditioning units depend on the 

configuration in which such units are sold. The vast majority of units on the market are 

condensing units and indoor coil combinations designed to be used with furnaces that provide the 

indoor air handling component. For these products, performance ratings can be provided based 

on a coil-only rating, in which case a default supply fan power assumption is used to calculate 

the SEER rating. Higher efficiency, coil-only ratings are achieved through more efficient design 

of the condensing unit and indoor coil. A small fraction of the split-system air conditioner market 

uses dedicated air handlers instead of furnaces. Additional ratings of the same condensing unit 

with specific furnace or air handler blowers can also be provided as blower-coil ratings. Higher 

efficiency blower-coil ratings can also be obtained by improving the indoor blower or furnace. 

Roughly 80 percent of future split-system air conditioner sales are expected to replace 

failing air-conditioning units (most frequently, the outdoor condensing unit, while only about 20 

percent are expected to be installed in new construction). Most of these systems are integrated 

with the air-handling system of a natural-gas fired furnace that provides space heating to the 

building. Since many of these furnaces were installed at the same time as the failing airconditioning unit, some building owners considering air-conditioning replacement will also 

replace the aging furnace at the same time, but others will elect to keep the existing furnace and 

just install a new condensing unit and indoor coil. 

The consumer’s ability to use coil-only systems is also applicable to the new construction 

market. EPCA does not authorize DOE to require a furnace to be purchased in conjunction with 

a new split-system air conditioner. In addition, while the Energy Independence and Security Act 

of 2007 requires DOE to issue furnace fan energy conservation or energy use standards not later 

than December 31, 2013, DOE does not currently regulate furnace fan performance. In practice, 

the furnace could be installed prior to the air conditioner purchase, and a rated efficiency that is 

the result of a particular furnace fan being used (i.e. the blower-coil efficiency) may be difficult 

to achieve in the field. Nevertheless, DOE recognizes that a small number of split-system air 

conditioners are rated using dedicated air handlers only, and a larger fraction are installed in 

conjunction with a new furnace. 

Because of the circumstances described above, DOE has provided an LCC analysis 

assuming both a coil-only scenario, and a blower-coil scenario, using the corresponding coil-only 

and blower-coil engineering curves as appropriate. DOE developed the life-cycle cost for 

consumers purchasing coil-only systems and consumers purchasing blower-coil systems 

assuming that these are independent consumer markets. 

To accurately estimate the share of consumers that would be affected by a standard at a 

particular efficiency level, DOE’s LCC analysis considered the projected distribution of 

efficiencies for products that consumers would purchase under a base case (i.e., absent amended 

energy efficiency standards). DOE refers to this distribution of product efficiencies as a baseES-16 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

case efficiency distribution. Using the projected distribution of base-case product efficiencies for 

each product class, DOE assigned a specific base-case product efficiency to each sample 

household as discussed earlier under energy use characterization. If a household was assigned a 

product efficiency that is greater than or equal to the efficiency of the standard level under 

consideration, the LCC calculation would show that this household is not affected by that 

standard level. 

Table ES.13 summarizes the results for the LCC and PBP analyses, indicating for each 

product class and region the highest SEER and HSPF level where the average LCC savings is 

greater than zero and the median PBP in years corresponding to that level. 

Table ES.13	 LCC and PBP Summary: Highest SEER and HSPF for Which Mean LCC 

Savings are Positive, and Corresponding Median PBP in Years 

Product National Hot-Humid Hot-Dry Rest of Country 

Class SEER/ 

HSPF PBP years 

SEER/ 

HSPF 

PBP 

years 

SEER/ 

HSPF 

PBP 

years 

SEER/ 

HSPF 

PBP 

years 

SplitSystem 

AC Coil 

Only 

13.5/NA 27.8 15.0/NA 17.5 14.5/NA 42.6 13.0/NA NA 

SplitSystem 

AC 

BlowerCoil 

13.5/NA 27.4 19.0/NA 17.9 17.0/NA 30.1 13.0/NA NA 

SplitSystem 

HP 

19.5/10.3 12.0 19.5/10.3 10.0 19.5/10.3 8.8 15.5./8.45** 12.6 

SinglePackage 

AC 

13.0/NA NA 13.0/NA NA 13.0/NA NA 13.0/NA NA 

Single– 

Packag 

e HP 

14.0/8.0 10.5 14.0/8.0 8.2 14.5/8.0 11.4 13.0/7.7 NA 

*NA means not applicable. 

**SEER 15 and 15.5 show very small LCC savings. Savings are negative at SEER13.5-14.5 and at SEER 16.0 and 

above. 

Figures presented in chapter 8 of the preliminary TSD show the range of LCC savings 

and PBPs for all of the efficiency levels DOE considered for each product class. Chapter 8 

provides more details on the methods, data, and assumptions used for the LCC and PBP 

analyses. 

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EERE-2008-BT-STD-0006 COMMENT 54
ES.3.7 Shipments Analysis 

DOE needs shipment forecasts to calculate the national impacts of standards on energy 

use, NPV, and future manufacturer cash flows for each product being considered. DOE’s 

shipments model considered shipments based on sector, market, and region in both residential 

and commercial sectors. DOE analyzed shipments to three markets: new construction, 

replacements, and existing buildings that do not already contain the product (i.e., “new owners”). 

DOE allocated shipments to the three geographic regions described in section ES.3.5.3. Rather 

than simply extrapolating a current shipments trend, the analysis used driver input variables (e.g., 

new construction forecasts and product stock saturations) to forecast sales to each sector, market 

segment, and region. For units shipped to new construction, annual product shipments are equal 

to the number of new building units built times the product purchase rate, which is determined 

by the market share of the product under consideration. To estimate shipments due to 

replacements, the model used sales in previous years and assumptions about the product lifetime, 

which determine how long an appliance is likely to remain in use. Shipments to new owners are 

based on historical rates of adoption. Chapter 9 of the preliminary TSD provides additional detail 

on the shipments analysis. 

Figure ES.2 through Figure ES.6 illustrate the forecasted base-case shipments for all 

product classes included in this rulemaking. Shipments are broken down into each of the three 

regions and designated by market segment (i.e., new construction, replacements, and new 

owners). Shipments to the commercial building sector are estimated to represent only about 7 

percent of all product shipments. For clarity, the figures do not differentiate among units going 

to the residential and commercial sectors. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

0 

1 

2 

3 

4 

5 

6 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure ES.2 Forecasted Shipments (Base Case) for Split-System Air Conditioners, CoilOnly 

0.0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure ES.3	 Forecasted Shipments (Base Case) for Split-System Air Conditioners, 

Blower-Coil 

ES-19 

EERE-2008-BT-STD-0006 COMMENT 54
0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure ES.4 Forecasted Shipments (Base Case) for Split-System Heat Pumps 

0.0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure ES.5 Forecasted Shipments (Base Case) for Single-Package Air Conditioners 

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EERE-2008-BT-STD-0006 COMMENT 54
0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

0.45 

0.50 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure ES.6 Forecasted Shipments (Base Case) for Single-Package Heat Pumps 

ES.3.8 National Impact Analysis 

The NIA estimates four national impacts from possible candidate standard levels for 

residential central air conditioners and heat pumps: (1) national energy savings, (2) monetary 

value of energy savings to consumers of the considered products due to standards, (3) increased 

total installed costs to consumers of the considered products due to standards, and (4) the NPV of 

potential standards (the difference between the energy savings and increased total installed 

costs). DOE prepared an NES spreadsheet model to forecast energy savings and national 

consumer economic costs and savings resulting from new standards. 

A key component of DOE’s estimates of NES and NPV is the trend in energy efficiency 

forecasted for the base case (without new standards) and for each of the standards cases (with 

new standards). To forecast the base-case efficiency distribution for each product class, DOE 

accounted for changes in the market shares of more efficient products based on historical trends. 

For its determination of standards-case efficiency distributions, DOE used a “roll-up + efficiency 

growth” scenario to establish the distribution of efficiencies for the year that revised standards 

are assumed to become effective (i.e., 2016) and subsequent years. DOE assumed that product 

efficiencies in the base case that did not meet the standard level under consideration would “roll 

up” to meet the new standard level in 2016. DOE also assumed that market-pull programs (such 

as ENERGY STAR) would continue to promote efficient appliances after the introduction of 

revised standards in 2016, and that this would lead to increased market shares for products with 

efficiencies above the standard level. DOE assumed the growth in more efficient products for 

ES-21 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

the base case equaled historical rates of efficiency growth. For the standards cases, DOE 

developed growth trends for each standard level that maintained the same per-unit average total 

installed cost difference between the base case and each standards case for the year 2016 over the 

entire forecast period (2016–2046). Chapter 10 of the preliminary TSD provides additional 

detail on the development of the base case and standards case efficiency trends as well as all the 

details regarding the NIA. 

ES.3.8.1 National Energy Savings 

DOE calculated annual NES as the difference between national energy consumption in 

the base case and in each higher efficiency standard case. DOE estimated energy consumption 

and savings based on site energy (electricity directly consumed by the central air 

conditioner/heat pump) and converted the electricity consumption and savings to source energy 

(energy needed to produce the site energy) using factors that account for losses in transmission 

and distribution and in electricity generation. Cumulative energy savings are the sum of the 

annual NES, which DOE determined over specified periods. 

The NES results shown in Table ES.14 through Table ES.17 are cumulative to 2046 and 

are shown as primary energy savings in quads (quadrillion Btus). 

Table ES.14 Split-System Air Conditioners: Cumulative NES Results (quads) 

SEER 

National* Hot-Humid Hot-Dry Rest of Country 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

13.5 0.20 0.18 0.02 0.09 0.08 0.01 0.03 0.03 0.00 0.06 0.05 0.00 

14.0 0.82 0.75 0.07 0.37 0.34 0.03 0.13 0.12 0.01 0.24 0.22 0.02 

14.5 1.46 1.33 0.12 0.65 0.59 0.06 0.24 0.22 0.02 0.43 0.39 0.04 

15.0 2.08 1.90 0.18 0.93 0.85 0.08 0.34 0.31 0.03 0.61 0.56 0.05 

15.5 2.69 2.46 0.23 1.20 1.10 0.10 0.44 0.40 0.04 0.79 0.72 0.07 

16.0 3.23 2.95 0.28 1.44 1.32 0.12 0.52 0.48 0.04 0.95 0.87 0.08 

16.5 3.51 3.18 0.33 1.57 1.43 0.15 0.57 0.52 0.05 1.02 0.93 0.09 

17.0 3.56 0.37 1.59 0.17 0.57 0.06 1.04 0.11 

18.0 3.65 0.47 1.64 0.21 0.59 0.08 1.06 0.13 

19.0 3.75 0.57 1.68 0.25 0.61 0.09 1.09 0.16 

20.0 3.84 0.66 1.72 0.30 0.62 0.11 1.12 0.19 

21.0 3.92 0.74 1.76 0.33 0.63 0.12 1.14 0.21 

22.0 3.96 0.78 1.78 0.35 0.64 0.12 1.15 0.22 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table ES.15 Split-System Heat Pumps: Cumulative NES Results (quads) 

SEER HSPF National* Hot-Humid Hot-Dry Rest of Country 

13.5 7.85 0.11 0.07 0.01 0.03 

14.0 8.00 0.56 0.34 0.07 0.15 

14.5 8.15 1.03 0.63 0.12 0.28 

15.0 8.30 1.53 0.93 0.18 0.42 

15.5 8.45 2.09 1.26 0.24 0.58 

16.0 8.60 2.78 1.66 0.31 0.79 

17.0 9.10 3.93 2.33 0.44 1.15 

18.0 9.60 4.98 2.94 0.55 1.47 

19.0 10.10 5.68 3.36 0.63 1.68 

19.5 10.30 5.78 3.41 0.64 1.71 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

Table ES.16 Single-Package Air Conditioners: Cumulative NES Results (quads) 

SEER National* Hot-Humid Hot-Dry Rest of Country 

13.5 0.08 0.04 0.01 0.02 

14.0 0.15 0.07 0.02 0.04 

14.5 0.24 0.11 0.04 0.07 

15.0 0.30 0.14 0.05 0.09 

15.5 0.36 0.17 0.06 0.11 

16.0 0.41 0.19 0.07 0.12 

16.6 0.43 0.20 0.07 0.13 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

Table ES.17 Single-Package Heat Pumps: Cumulative NES Results (quads) 

SEER HSPF National* Hot-Humid Hot-Dry Rest of Country 

13.5 7.85 0.04 0.02 0.00 0.01 

14.0 8.00 0.10 0.06 0.01 0.03 

14.5 8.00 0.19 0.12 0.02 0.05 

15.0 8.00 0.28 0.17 0.03 0.08 

15.5 8.50 0.36 0.22 0.04 0.11 

16.0 9.00 0.41 0.25 0.05 0.12 

16.4 9.00 0.43 0.26 0.05 0.12 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

ES.3.8.2 Net Present Value 

DOE calculated NPV as the difference between the present value of operating cost 

savings and the present value of increased total installed costs. DOE calculated operating cost 

savings over the life of the products purchased in the forecast period. DOE used discount rates of 

7 percent and 3 percent to discount future costs and savings to the present. The NPV results for 

ES-23 

EERE-2008-BT-STD-0006 COMMENT 54
the representative product classes are shown in Table ES.18 through Table ES.22 as the 

discounted value of the net savings in dollar terms. 

ES-24 

EERE-2008-BT-STD-0006 COMMENT 54
Table ES.18 Split-System Air Conditioners: Discounted Cumulative NPV Results (3% Discount Rate) 

SEER 

National* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) 

Rest of Country 

(bill. 2008$) 

Total** 

CoilOnly Blower Coil Total** Coil- Only Blower Coil Total** Coil- Only Blower Coil Total** Coil- Only Blower Coil 

13.5 -0.76 -0.76 0.00 0.08 0.06 0.02 -0.04 -0.05 0.01 -0.93 -0.88 -0.05 

14.0 -4.14 -4.11 -0.03 0.10 0.00 0.10 -0.37 -0.41 0.03 -4.35 -4.14 -0.21 

14.5 -9.32 -9.25 -0.07 -0.37 -0.53 0.16 -1.07 -1.13 0.06 -8.71 -8.33 -0.38 15.0 -16.86 -16.71 -0.15 -1.48 -1.69 0.22 -2.25 -2.33 0.07 -14.27 -13.70 -0.57 

15.5 -26.88 -26.59 -0.29 -3.28 -3.54 0.26 -3.95 -4.02 0.07 -21.04 -20.25 -0.79 

16.0 -38.02 -37.53 -0.49 -5.54 -5.81 0.27 -5.89 -5.95 0.06 -28.16 -27.13 -1.04 

16.5 -44.43 -43.67 -0.76 -6.89 -7.17 0.27 -7.01 -7.05 0.04 -32.18 -30.86 -1.32 

17.0 -44.77 -1.09 -6.91 

0.25 

-7.05 

0.00 

-32.48 -1.63 

18.0 -45.67 -1.99 -7.01 

0.16 

-7.17 -0.12 -33.23 -2.37 

19.0 -46.89 -3.22 -7.19 -0.03 -7.36 -0.31 -34.14 -3.28 

20.0 -48.41 -4.74 -7.47 -0.30 -7.62 -0.57 -35.19 -4.33 21.0 -50.13 -6.46 -7.81 -0.64 -7.92 -0.87 -36.30 -5.44 22.0 -51.02 -7.35 -8.00 -0.83 -8.08 -1.03 -36.86 -6.00 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NPV for 17 through 22 SEER reflects the Coil-Only economic impacts at 16.5 SEER. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table ES.19 Split-System Air Conditioners: Discounted Cumulative NPV Results (7% Discount Rate) 

SEER 

National* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) 

Rest of Country 

(bill. 2008$) 

Total** 

CoilOnly Blower Coil Total** Coil- Only Blower Coil Total** Coil- Only Blower Coil Total** Coil- Only Blower Coil 

13.5 -0.43 -0.41 -0.02 -0.01 -0.02 0.004 -0.04 -0.04 0.000 -0.42 -0.39 -0.03 

14.0 -2.20 -2.12 -0.08 -0.17 -0.18 0.01 -0.26 -0.26 -0.001 -1.95 -1.84 -0.11 14.5 -4.74 -4.60 -0.14 -0.53 -0.56 0.02 -0.64 -0.64 -0.002 -3.87 -3.67 -0.20 15.0 -8.27 -8.06 -0.21 -1.17 -1.20 0.03 -1.22 -1.21 -0.01 -6.29 -6.00 -0.29 15.5 -13.06 -12.75 -0.31 -2.16 -2.19 0.03 -2.05 -2.04 -0.01 -9.33 -8.95 -0.39 16.0 -18.87 -18.44 -0.43 -3.46 -3.48 0.02 -3.10 -3.07 -0.03 -12.85 -12.35 -0.50 16.5 -22.73 -22.14 -0.59 -4.35 -4.36 0.00 -3.80 -3.75 -0.05 -15.13 -14.50 -0.63 17.0 -22.91 -0.77 -4.38 -0.02 -3.82 -0.07 -15.27 -0.77 18.0 -23.37 -1.24 -4.46 -0.10 -3.89 -0.15 -15.60 -1.11 19.0 -23.98 -1.84 -4.57 -0.22 -4.00 -0.25 -16.01 -1.51 

20.0 -24.71 -2.57 -4.73 -0.37 -4.12 -0.38 -16.47 -1.98 21.0 -25.53 -3.40 -4.91 -0.56 -4.27 -0.52 -16.98 -2.48 22.0 -26.05 -3.91 -5.03 -0.68 -4.37 -0.62 -17.29 -2.79 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. ** Total NPV for 17 through 22 SEER reflects the Coil-Only economic impacts at 16.5 SEER. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table ES.20 Split-System Heat Pumps: Discounted Cumulative NPV Results 

SEER HSPF 

National* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Country (bill. 008$) 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

13.5 7.85 0.34 0.06 0.30 0.08 0.09 0.02 0.01 -0.02 14.0 8.00 1.73 0.32 1.55 0.39 0.44 0.13 0.05 -0.08 14.5 8.15 3.12 0.57 2.82 0.72 0.81 0.23 0.09 -0.16 15.0 8.30 4.31 0.68 4.01 0.97 1.15 0.32 0.06 -0.27 15.5 8.45 5.28 0.61 5.14 1.15 1.47 0.38 -0.05 -0.45 16.0 8.60 6.27 0.44 6.35 1.30 1.81 0.44 -0.19 -0.67 17.0 9.10 7.12 -0.08 7.94 1.41 2.27 0.51 -0.63 -1.08 

18.0 9.60 6.07 -1.35 8.49 1.12 2.46 0.47 -1.64 -1.73 

19.0 10.10 4.17 -2.92 8.21 0.59 2.44 0.37 -2.71 -2.42 

19.5 10.30 3.70 -3.32 8.07 0.43 2.41 0.33 -2.94 -2.59 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

Table ES.21 Single-Package Air Conditioners: Discounted Cumulative NPV Results 

SEER 

National* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Country(bill. 2008$) 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

 Rate 

13.5 -0.62 -0.33 -0.03 -0.04 -0.07 -0.05 -0.54 -0.25 

14.0 -1.26 -0.65 -0.10 -0.09 -0.16 -0.09 -1.05 -0.47 

14.5 -2.32 -1.15 -0.25 -0.19 -0.32 -0.18 -1.82 -0.82 

15.0 -3.31 -1.62 -0.42 -0.28 -0.49 -0.26 -2.49 -1.11 

15.5 -4.53 -2.21 -0.66 -0.41 -0.70 -0.36 -3.27 -1.47 

16.0 -5.67 -2.83 -0.91 -0.56 -0.90 -0.47 -3.97 -1.83 

16.6 -6.37 -3.27 -1.07 -0.66 -1.02 -0.55 -4.39 -2.08 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table ES.22 Single-Package Heat Pumps: Discounted Cumulative NPV Results 

SEER HSPF 

National* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Country (bill. 2008$) 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

3% Disc. 

Rate 

7% Disc. 

Rate 

13.5 7.85 -0.05 -0.05 0.03 -0.006 0.01 0.000 -0.05 -0.03 14.0 8.00 -0.22 -0.18 0.03 -0.04 0.01 -0.006 -0.16 -0.09 

14.5 8.00 -0.58 -0.42 -0.04 -0.12 0.00 -0.02 -0.35 -0.20 

15.0 8.00 -0.94 -0.63 -0.13 -0.20 -0.018 -0.04 -0.51 -0.29 

15.5 8.50 -1.35 -0.87 -0.27 -0.30 -0.05 -0.06 -0.67 -0.37 

16.0 9.00 -1.86 -1.18 -0.47 -0.43 -0.10 -0.09 -0.87 -0.48 

16.4 9.00 -2.16 -1.38 -0.60 -0.52 -0.13 -0.11 -0.99 -0.56 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

ES.3.9 Preliminary Manufacturer Impact Analysis 

The preliminary MIA focused on manufacturers of residential central air conditioners and 

heat pumps. Potential impacts include financial effects, both quantitative and qualitative, that 

might result from new energy conservation standards and consequently lead to changes in 

manufacturing practices for these products. DOE identified potential impacts through interviews 

with manufacturers and other interested parties. Chapter 12 of the preliminary TSD includes 

details on the key issues DOE identified during the preliminary MIA. 

DOE identified eight key issues from energy conservation standards for residential 

central air conditioner and heat pump manufacturers: 

• increased conversion costs, 

• impact on U.S. production and jobs, 

• cumulative regulatory burden, 

• impact on product utility, 

• current economic conditions, 

• product substitution, 

• impacts of regional standards, and 

• technical difficulty of achieving new standards. 

DOE conducted the preliminary MIA by first identifying products, methods, and 

practices used in the residential central air conditioner and heat pump industry. Next, DOE 

examined how energy efficiency improvements affect cost, production, and various other 

manufacturing metrics. Finally, DOE interviewed manufacturers and adjusted the analysis as 

appropriate, based on manufacturers’ feedback. In the interviews, DOE examined any additional 

effects on competition, manufacturing capacity, direct employment, and the cumulative burden 

of other regulations affecting manufacturers, as well as several issues raised by individual 

manufacturers. Chapter 12 of the preliminary TSD provides details on this and other aspects of 

the preliminary MIA. 

ES.4 ISSUES ON WHICH DOE SEEKS PUBLIC COMMENT 

DOE is particularly interested in receiving comments and views of interested parties 

concerning: 

1. Effective Date of Standards 

DOE previously determined that the final rule in this rulemaking must be published by 

June 30, 2011 and tentatively decided that the rule would apply to products manufactured 5 years 

later, in June 2016. Several comments from stakeholders have been received to date expressing 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

concern regarding this compliance date. Specifically, stakeholders are concerned that the 

implementation of the standard during peak season could result in inconsistencies for 

distributors. DOE seeks further comment on compliance during the peak season. (Reference 

Chapter 2 of the preliminary TSD for details.) 

2. Heat Pump Cooling Efficiency Requirements 

Several stakeholders have commented to date that the same standard should apply for 

both central air conditioner and heat pump products. This was the case in previous efficiency 

standards rulemaking, reflecting concerns that different efficiency requirements would cause 

consumers to switch to the product type subject to lower standards. Current analyses are treating 

air conditioners and heat pumps as separate products in order to determine whether separate 

standards may be warranted. DOE seeks comment regarding whether to implement standards 

with equal cooling efficiency requirements for air conditioners and heat pumps. (Reference 

Chapter 2 of the preliminary TSD for details.) 

3. Effects of Expiration of Though-the-Wall (TTW) Product Classes 

Stakeholders previously stated strong beliefs that TTW split air conditioners and heat 

pumps should not be included in the space-constrained product class for new installations. 

According to these manufacturers, inclusion of the products in this class would give TTW 

producers a significant cost advantage due to the lower efficiency that would be required, 

resulting in a market shift for new construction applications. The TTW product class is defined 

to include products manufactured before January 23, 2010. (10 C.F.R. 430.2). As a result, TTW 

units meeting the definition of space-constrained products are now subject to the standard for 

those products, while units meeting the definition of conventional central air conditioners and 

heat pumps are now subject to the standard for those products. DOE seeks comment on possible 

shifts in the market due to the expiration of the TTW product classes. (Reference Chapter 2 of 

the preliminary TSD for details.) 

4. Large-Tonnage Products 

Comments have been received from stakeholders suggesting that 4- and 5-ton units be 

placed in a separate product class. Currently, DOE maintains that the differences between these 

large-tonnage units and 3-ton units are not sufficient to require a separate product class, but 

would consider modifying its analysis in order to incorporate these differences. DOE seeks 

comment regarding methods to account for discrepancies between typical 3-ton units and other 

large-tonnage products. (Reference Chapter 2 of the preliminary TSD for details.) 

5. Replacement Cost of Components of Higher Efficiency Products 

Amended efficiency standards are anticipated to increase the cost of new systems, as 

these units will require larger and/or more sophisticated components to meet the efficiency 

requirements. Several manufacturers have previously commented that the increased cost of 

replacing existing systems with new, higher-SEER units will motivate many users to instead 

repair their current systems. This could include costly repairs that, under current standards, often 

provide cause for end users to perform system replacement. The result would be a change in the 

distribution of product lifetimes as well as the estimated number of compressor replacements. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

DOE requests comment on the impact of increased efficiency standards on end-user decisions of 

whether to repair or replace existing installed units. (Reference Chapter 2 of the preliminary TSD 

for details.) 

6. Impact of Amended Standards on Domestic Manufacturers 

DOE has performed a preliminary manufacturer impact analysis (MIA) in order to 

preliminarily quantify the financial impact of higher conservation standards on domestic 

manufacturers of central air conditioners and heat pumps, as well as the potential impact of these 

standards on manufacturing capacity and employment. The MIA process consists of three 

phases, incorporating quantitative financial analyses as well as input obtained from manufacturer 

interviews. MIA information will be reported as part of the preliminary analysis, and DOE seeks 

comment from involved parties regarding the possible impact of increased efficiency standards 

on domestic manufacturers. (Reference Chapter 2 of the preliminary TSD for details.) 

7. Regional Standards 

DOE has proposed two regions for establishing regional standards. DOE seeks input on 

the definition of the regions proposed and the viability of regional standards, including likely 

financial impacts on product distribution and manufacturing. (Reference Chapter 2 of the 

preliminary TSD for details.) 

8. Hot-Dry SEER Metric 

Based on analysis of climate data, DOE has proposed for consideration a hot-dry SEER 

metric (SEERhd) for the hot-dry region to better characterize the seasonal efficiency of products 

installed in that region, but at this stage has not utilized the metric in the engineering and 

economic analysis. DOE seeks comment on the development of the SEERhd, on the perceived 

value of a SEERhd as defined, and whether this metric should be used in place of SEER in the hot 

dry region. (Reference Chapter 2 of the preliminary TSD for details.) 

9. Split-System Air Conditioner Coil-only and Blower-Coil Markets and Analysis 

DOE has developed the analysis by considering two separate markets for coil-only and 

blower-coil split-system air conditioners. DOE has weighted the relative NPV values for both 

markets together to define the NPV for higher efficiencies for split-system air conditioners. DOE 

believes that higher efficiencies can be obtained with blower-coil systems and higher efficiencies 

appear to be justified when considering that market separately. DOE requests comment on 

whether the differences in costs and other market conditions justify establishing separate product 

classes for coil-only and blower-coil products. (Reference Chapter 5 of the preliminary TSD for 

details.) 

10. Market for Coil-only Heat Pumps 

DOE believes that the majority of split-system heat pumps are sold as a matched set of 

indoor and outdoor units for both the new construction and replacement markets and has not 

provided separate analyses of coil-only and blower-coil heat pumps. DOE recognizes, however, 

that in some instances heat pumps are used in conjunction with gas- or oil-fired furnaces, 

providing a “dual-fuel” heating capability. DOE requests data on the size of this dual-fuel market 

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EERE-2008-BT-STD-0006 COMMENT 54
as well as whether it is strongly regional in nature. DOE also seeks input on the characterization 

of the heat pump replacement market and whether installations of matched sets of indoor and 

outdoor products should be the basis for DOE’s analysis for all heat pumps. DOE seeks input on 

whether it should modify the analysis for split-system heat pumps to define separate coil-only 

and blower-coil markets. DOE also request comment on how it might modify its energy use 

characterization analysis for heat pumps to capture the impact of a home served by two different 

heating fuels, if that is a large market. (Reference Chapter 5 of the preliminary TSD for details.) 

11. Impacts of a Regional Standard on Product Distributors, Dealers, Contractors, and 

Installers. 

 Section 325(o)(6)(D)(i) authorizes the Secretary to establish regional standards only if the 

regional standards will produce significant energy savings in comparison to a single national 

standard and are economically justified. Further, Section 325(o)(6)(D)(ii) of EPCA states that a 

regional standard can only be established if the Secretary considers the impact of additional 

regional standards on consumers, manufacturers, and other market participants, including 

product distributors, dealers, contractors, and installers. DOE received comment on the 

framework document that suggest distributors of central air conditioners and heat pumps to more 

than one region and general contractors could bear disproportionate compliance costs (see 

section 2.10 in chapter 2 of the preliminary TSD). DOE believes that data publicly available 

from EIA and other sources will allow DOE to conduct an LCC analysis and a regional 

“subgroup analysis” to determine the effects on consumers at the regional level. DOE seeks any 

additional information on consumer impacts, and in particular seeks information on the potential 

impacts on distributors, dealers, contractors and installers. DOE specifically seeks quantitative 

and qualitative information concerning market mechanisms and market circumstances that would 

be more likely to generate such impacts. DOE is particularly interested in: (1) how common it is 

for individual distributors and dealers of central air conditioners and heat pumps to distribute 

these products to more than one of the proposed regions; (2) what percent of market sales go 

through multiregional distributors; (3) what effect regional standards would have on the dollar 

value of inventory carried and carrying charges for that inventory; (4) what effect regional 

standards would have on sales and operating costs; and (5) what percent of distributors are small 

businesses. DOE believes that most contractors and installers are likely to do business in only a 

few jurisdictions and are unlikely to bear exceptional costs as a result of the central air 

conditioner and heat pump standards due to operations in more than one region. DOE is 

interested in information (especially quantitative information) that would either support or refute 

this hypothesis. (Reference Chapter 17 of the preliminary TSD for a preliminary assessment of 

the impacts of regional standards on market participants other than manufacturers and 

consumers.) 

12. Enforcement Plan Mechanisms 

If regional standards are adopted for this rulemaking, the Energy Independence and 

Security Act of 2007 (EISA 2007) mandates that an enforcement plan rulemaking be initiated no 

later than 90 days after the issuance of the standard final rule. (42 U.S.C. 6295(o)(6)(G)) DOE 

received comment that it should begin to develop the enforcement plan earlier and believes that 

it is important to do so to understand the impacts of regional standards. DOE requests input on 

the viability of the enforcement mechanisms discussed in section 2.10.3 of chapter 2, as well the 

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EERE-2008-BT-STD-0006 COMMENT 54
 

extent to which these or other proposed mechanisms would result in additional financial burdens 

to consumers, manufacturers, contractors, distributors, dealers, and installers. 

13. Off-Mode Energy Consumption 

EISA 2007 mandates that DOE consider amended test procedures and standards for 

standby-mode and off-mode energy consumption by covered products (such as central air 

conditioners and heat pumps) for any amended standard published after July 1, 2010. (42 U.S.C. 

6295(gg)(3)) DOE’s test procedure already accounts for standby-mode energy consumption in 

the SEER and HSPF metrics for central air conditioners and heat pumps, but does not account 

for off-mode energy consumption. DOE requests comment on the energy consuming components 

during off-mode as well as the potential to reduce the energy consumption of these components. 

DOE also requests comment on the potential impacts of separate standard for off-mode energy 

consumption. (Reference section 2.1.2.8 of chapter 2 for more details.) 

14. Combination Standards Rulemaking for Central Air Conditioners and Heat Pumps, Gas 

Furnaces, and Furnace Fans 

DOE is currently pursuing separate standards rulemakings for three interrelated products: 

(1) central air conditioners and heat pumps; (2) gas furnaces; and (3) furnace fans. DOE is 

required by consent decree to publish a final rule for central air conditioners and heat pumps by 

June 30, 2011. A final rule for gas furnaces published in November 2007 was remanded by the 

Courts to DOE with the requirement that DOE publish a new final rule by May 1, 2011. EISA 

2007 requires that DOE publish a final rule for furnace fans by January 1, 2013. Rather than 

analyze each set of products separately, DOE is contemplating a combined analysis to examine 

the first cost and energy savings impacts of the interaction between the products. If DOE 

conducts such an analysis and the results indicate that a combined approach yields additional 

savings beyond what can be achieved by analyzing each product separately, DOE may decide to 

pursue a combined standards rulemakings that addresses all three sets of products (or two of the 

three, i.e., central air conditioners and heat pumps and furnaces) simultaneously. If such a 

combined rulemaking is pursued, DOE would need to publish a final rule by May 1, 2011; the 

earliest date for which standards for gas furnaces need to be finalized. 

15. Maximum Technologically Feasible Designs 

In assessing the viability of maximum technologically feasible designs, DOE conducts a 

screening analysis to determine their viability based on four criteria: (1) technological feasibility; 

(2) practicability to manufacture, install, and service; (3) impacts on equipment utility or 

equipment availability; and (4) adverse impacts on health or safety. The maximum efficiency 

levels that DOE analyzed for each product class took into account the level’s viability in 

consideration of the four above criteria. However, DOE is aware of two additional designs that it 

may consider in this rulemaking: (1) solar assist technologies and (2) three-stage heat pumps. 

Solar assisted products are currently available in the market. These products utilize solar energy 

to supplement the electrical energy required for the product to operate. Three-stage heat pumps 

are also currently available in the market and operate efficiently at low ambient temperatures 

through the use of additional compressors and components, thereby precluding the need for back 

up electric resistance heat. DOE believes the benefits for this technology result primarily in 

improved heat pump heating, and not cooling, performance. Because both technologies are 

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EERE-2008-BT-STD-0006 COMMENT 54
available on the market, DOE requests comment on how the energy conservation standard 

rulemaking can best address solar assist and three-stage heat pump technologies. DOE also 

requests comment on any other technology that is available on the market and could increase 

maximum technologically feasible efficiency levels. 

16. Consensus Agreement 

On January 26, 2010, the Air-Conditioning, Heating and Refrigeration Institute (AHRI), 

American Council for an Energy Efficient Economy (ACEEE), Alliance to Save Energy (ASE), 

Appliance Standards Awareness Project (ASAP), Natural Resources Defense Council (NRDC), 

and Northeast Energy Efficiency Partnerships (NEEP) submitted a joint comment to DOE 

recommending minimum energy conservation standards for residential central air conditioners, 

heat pumps, and furnaces. This consensus agreement is available on DOE’s website, which can 

be found at: 

http://www1.eere.energy.gov/buildings/appliance_standards/residential/furnaces_boilers.html. 

DOE specifically requests comment on the consensus agreement. In particular, DOE is interested 

in comments relating to the proposed SEER, HSPF, and EER requirements, the proposed 

regional divisions, and the proposed compliance dates for residential central air conditioners and 

heat pumps. 

ES-34 

EERE-2008-BT-STD-0006 COMMENT 54
 

CHAPTER 1. INTRODUCTION 

TABLE OF CONTENTS 

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

1.2	 OVERVIEW OF ENERGY CONSERVATION STANDARDS FOR RESIDENTIAL
 

CENTRAL AIR CONDITIONERS AND HEAT PUMPS ............................................. 1-1
 

1.2.1 Small-Duct, High-Velocity Systems .................................................................... 1-2
 

1.2.2 Space-Constrained Products ................................................................................ 1-5
 

1.2.2.1 Single-Package Vertical Units (SPVUs) .................................................. 1-5
 

1.2.2.2 Through-the-Wall Systems ...................................................................... 1-6
 

1.2.2.3 Single-Package Non-Weatherized Units .................................................. 1-6
 

1.2.3 Ductless Split Systems......................................................................................... 1-7
 

1.3 PROCESS FOR SETTING ENERGY CONSERVATION STANDARDS ................... 1-7
 

1.4 STRUCTURE OF THE DOCUMENT.......................................................................... 1-10
 

LIST OF TABLES 

Table 1.3.1 Central Air Conditioning Analyses Under the Process Rule ................................... 1-2 

EERE-2008-BT-STD-0006 COMMENT 54
 

CHAPTER 1. INTRODUCTION 

1.1 PURPOSE OF THE DOCUMENT 

This preliminary technical support document (preliminary TSD) is a stand-alone report 

that provides the technical analyses and results supporting the information presented in the 

preliminary notice of public meeting (NOPM) and executive summary for residential clothes 

dryers and room air conditioners. This preliminary TSD reports on the preliminary activities and 

analyses conducted in the period preceding the notice of proposed rulemaking (NOPR) of this 

rulemaking. 

1.2	 OVERVIEW OF ENERGY CONSERVATION STANDARDS FOR 

RESIDENTIAL CENTRAL AIR CONDITIONERS AND HEAT PUMPS 

The National Appliance Energy Conservation Act of 1987 (NAECA) established energy 

conservation standards for central air conditioners and heat pumps as well as requirements for 

determining whether these standards should be amended. Specifically, NAECA established 

energy conservation standards for central air conditioners and heat pumps in the form of 

minimum limits on the seasonal energy efficiency ratio (SEER) for air conditioners and for heat 

pumps operating in the cooling mode, and on the heating seasonal performance factor (HSPF) 

for heat pumps operating in the heating mode. NAECA established the following standards for 

central air conditioners and heat pumps: 10.0 SEER/6.8 HSPF for split systems,1

 9.7 SEER/6.6 

HSPF for single-package systems.2

 These standards became effective January 1, 1992 for split 

systems; standards for single-package systems came into effect one year later. See 42 U.S.C. 

6295(d)(1)(A)-(B) and (2)(A)-(B). NAECA also required that DOE conduct two cycles of 

rulemakings to determine if more stringent standards are economically justified and 

technologically feasible. (42 U.S.C. 6295(d)(3)(A)-(B)) 

Pursuant to 42 U.S.C. 6295(d)(3)(A), DOE published a final rule in the Federal Register 

on January 22, 2001 (2001 final rule), amending the energy conservation standards for central air 

conditioners and heat pumps. 66 FR 7170. The amended standards would have increased the 

minimum SEER to 13 and the minimum HSPF to 7.7. Id. This final rule constituted the first 

cycle of revised standards for central air conditioners and heat pumps. 

Shortly after the publication of the 2001 final rule, DOE postponed the effective date of 

the rule to take time to reconsider the amended standards for central air conditioners and heat 

pumps. DOE eventually promulgated a 12 SEER standard in a final rule published May 23, 

1

 “Split systems” consist of outdoor and indoor units which are “split” from each other and connected via refrigerant 

tubing. The outdoor unit resides outdoors and consists of a compressor, heat exchanger coil, fan, and fan motor. 

The indoor unit, consisting of a heat exchanger coil, resides either within a furnace or blower-coil unit, and 

conditioned air is conveyed to the home via ducts

2

 In “single-package systems,” all the components that comprise a split system, including the air circulation 

equipment, are placed in a single cabinet. The single-package system resides outdoors, and conditioned air is 

conveyed to the home via ducts. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

2002 (2002 final rule), 67 FR 36368, but the U.S. Court of Appeals for the Second Circuit ruled 

that DOE had done so improperly. Natural Resources Defense Council v. Abraham, 355 F.3d 

179 (2d Cir. 2004). As a result, DOE published a technical amendment on August 17, 2004, 

which established a 13 SEER standard for all central air conditioners and heat pumps, excluding 

through-the-wall and space-constrained systems. 69 FR 50997. 

EPCA was further amended by the Energy Policy Act of 2005 (EPACT), Pub. L. 109-58. 

In Section 141 of EPACT, Congress directed DOE to submit an initial report regarding a plan for 

expeditiously prescribing new or revised standards. Pursuant to Section 141 of EPACT, DOE 

submitted an implementation report3

 to Congress in January 2006. This report specified a 

schedule for the completion of the second rulemaking cycle of revised standards for central air 

conditioners and heat pumps, requiring DOE to publish a final rule by June 2011, with a 

standards compliance effective date of June 2016. In separate court proceedings (New York v. 

Bodman, No. 05 Civ. 7807 (S.D.N.Y. filed Sept. 7, 2005) and Natural Resources Defense 

Council v. Bodman, No. 05 Civ. 7808 (S.D.N.Y. filed Sept. 7, 2005) the resulting consent decree 

(filed November 6, 2006) adopted the schedule for central air conditioners and heat pumps that 

DOE published in the January 2006 report to Congress (i.e., June 30, 2011). 

More recently, EPCA was amended by the Energy Independence and Security Act of 

2007 (EISA 2007), Pub. L. 110-140. In Section 306 of EISA 2007, Congress directed DOE to 

consider regional standards for central air conditioners and heat pumps (among other products), 

for one or two regions in addition to a base national standard. (42 U.S.C. 6295(o)(6)) EISA 

2007 states that in considering regional standards, DOE may consider regions made up of 

contiguous States only. Further, in Section 310 of EISA 2007, Congress directed DOE to 

consider amended test procedures and standards for standby-mode and off-mode energy 

consumption by covered equipment (such as central air conditioners and heat pumps) for any 

amended standard published after July 1, 2010. (42 U.S.C. 6295(gg)(3)) Because this energy 

conservation standards rulemaking for central air conditioners and heat pumps will be completed 

in 2011, the requirement to incorporate standby-mode and off-mode energy use into the energy 

conservation standards analysis is applicable. 

1.2.1 Small-Duct, High-Velocity Systems 

DOE initially sought to create a separate product class for small-duct, high velocity 

(SDHV) systems. DOE reasoned that SDHV systems have design considerations (confined 

installation spaces, high pressure drops, and blower motor power) that warrant special 

consideration in the analytical and standards-setting process. In the 1999 Supplemental Advance 

Notice of Proposed Rulemaking (SANOPR) (1999 SANOPR; 64 FR 66306 (Nov. 24, 1999)) for 

central air conditioners, DOE proposed the creation of a separate class of “space-constrained” 

products that included SDHV systems and requested feedback from stakeholders on the proposal 

to create a separate product class for SDHV systems. However, DOE received feedback on the 

1999 SANOPR that indicated some SDHV units were capable of reaching 12 SEER, and that 

manufacturers were making investments to produce more efficient SDHV systems. 

3

 Energy Conservation Standards Activities, January 2006. This document can be downloaded from the DOE 

website at: http://www.eere.energy.gov/buildings/appliance_standards/2006_schedule_setting.html. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

For these reasons, in the October 5, 2000, NOPR (2000 NOPR; 65 FR 59590), DOE 

proposed not to create a separate SDHV product class, instead requiring SDHV systems to meet 

the standards for conventional split and single-package systems.4

 However, DOE also proposed 

to allow SDHV systems the option to test as coil-only products. This additional provision in the 

test procedure was estimated to provide an additional 1 to 2.5 SEER points for SDHV systems, 

making it easier for manufacturers to meet the standard. DOE again requested feedback from 

stakeholders on this proposal. 

On January 22, 2001, DOE published the 2001 final rule, establishing a 13 SEER standard 

for conventional split and single-package systems and reiterating that the characteristics of 

available SDHV systems did not warrant the creation of a separate product class. 66 FR at 7197 

DOE explained that revisions to the test procedure would allow testing as coil-only products, and 

stated that SDHV systems were, therefore, subject to the 13 SEER standards being adopted for 

all split-system and single-package air conditioners and heat pumps. 

On July 25, 2001, in response to a petition for reconsideration and as a result of review 

under the President’s Regulatory Review Plan,5

 DOE reopened the standards rulemaking and 

published a Supplemental Notice of Proposed Rulemaking (SNOPR), in which DOE proposed to 

withdraw its January 22, 2001 final rule. 66 FR 38822. As a substitute, DOE proposed 

standards in that SNOPR which would have set a 12 SEER standard for all split-system and 

single-package air conditioners and heat pumps, thereby resulting in a 20 percent increase in the 

minimum energy efficiency levels over prior levels. Again, DOE proposed not to establish a 

separate class for SDHV systems on the grounds that they would be able to meet the 12 SEER 

standard. 

In the subsequent May 23, 2002 final rule, DOE adopted the 12 SEER standard for splitsystem and single-package air conditioners and heat pumps, and responded to additional 

comments from stakeholders on SDHV systems. 67 FR 36368. Further information submitted 

by stakeholders led DOE to conclude that separate standards for SDHV systems were indeed 

warranted, and DOE stated it would perform a separate analysis to determine appropriate 

standard levels. A new product class and definition for SDHV systems were established, and 

standards were set at the 10 SEER NAECA level until a full analysis could be performed. 

Further, DOE stated it would consider stakeholders’ requests that the DOE test procedure be 

amended to allow special testing provisions for SDHV products. At the time of drafting the 

2002 final rule, DOE had begun a separate engineering and life-cycle cost analysis to determine 

appropriate standard levels for SDHV products. 

However, DOE’s efforts to reopen its rulemaking setting energy conservation standard 

levels for central air conditioners and heat pumps were challenged by a number of advocacy 

groups. In its decision in Natural Resources Defense Council, et al. v. Abraham, the Second 

Circuit Court concluded that “the May 23, 2002, final rules promulgated by DOE withdrawing 

the standards it published as a final rule on January 22, 2001, and replacing them with less 

4

 Standards for conventional systems were proposed at 12 SEER for split and single-package air conditioners and 13 

SEER for split-system and single-package heat pumps.

5

 The Regulatory Review Plan, which called for agencies to (among other things) withdraw or postpone the effective 

dates of regulations pending review by the White House, was published in the Federal Register at 66 FR 7702 (Jan. 

24, 2001).
 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

stringent standards, were not a valid exercise of DOE's authority under the EPCA,” in light of the 

“anti-backsliding” provision in 325(o)(1) of EPCA. Section 325(o)(1) of EPCA states that “[t]he 

Secretary may not prescribe any new or amended standard which increases the maximum 

allowable energy use...of a covered product.” 355 F.3d 179, 206 (2d Cir. 2004). Accordingly, 

DOE published a technical amendment on August 17, 2004 (2004 Technical Amendment; 69 FR 

50997). This technical amendment replaced standard levels established by the 2002 final rule 

(12 SEER) with the 13 SEER standards established in the 2001 final rule. 

Because the 2001 final rule did not establish a separate class or separate standards for 

SDHV systems, and because SDHV systems are not considered “space constrained” (see 

discussion in 66 FR at 7197 and 65 FR at 59609-10), they are covered by the 13 SEER/7.7 HSPF 

standard adopted in that rule. The Court’s ruling prohibits DOE from adopting a standard of less 

than 13 SEER for SDHV systems, despite DOE’s more recent conclusion that SDHV systems 

have a maximum technologically feasible efficiency of just over 13 SEER.6 

Further, in the test procedures detailed in the October 11, 2005 final rule, DOE stated that 

test procedure revisions to allow SDHV systems to test as coil-only units would result in 

unrealistic SEER ratings and would discourage manufacturers from making efficiency 

improvements to blower motors. 70 FR at 59124. Therefore, DOE did not amend the test 

procedure to allow testing of SDHV systems as coil-only units, making it more likely that SDHV 

products would be unable to meet even the 12 SEER standard. DOE advised manufacturers of 

SDHV systems of the procedure available under section 504 of the DOE Organization Act (42 

U.S.C. 7194), which allows them to request relief from hardship or inequity caused by a 

regulation issued under EPCA. 

On May 24, 2004, SpacePak and Unico, Inc., filed a joint application with the Office of 

Hearings and Appeals (OHA) for exception from the 13 SEER standard, arguing that they would 

suffer a “serious hardship and unfair distribution of burdens” if forced to comply with the 13 

SEER rule (case nos. TEE-0010 and TEE-0011) The OHA granted the exception to SpacePak 

and Unico, citing technological constraints (compact indoor coils, high static-pressure losses, and 

higher fan motor power) that make it more difficult for SDHV systems to increase energy 

efficiency. Also cited was the serious hardship to SpacePak and Unico that would result should 

exception relief not be granted, possibly resulting in “the loss of all sales within the United 

States.” The OHA further noted that the unavailability of SDHV systems would negatively 

impact domestic consumers, and that granting exception relief would not have a significant 

impact upon competition in the air conditioner industry. On October 14, 2004, the OHA granted 

exception relief to SpacePak and Unico, Inc., authorizing them to manufacture and sell SDHV 

systems that meet an 11 SEER/6.8 HSPF standard. This decision became effective January 23, 

2006, and remains in effect until DOE establishes a different standard for SDHV systems. 

On September 28, 2005, Energy Savings Products, Ltd. (ESP), filed its own application 

for exception relief with the OHA (case no. TEE-0026). ESP asserted that it would suffer a 

6

 In 2002, DOE performed a separate engineering analysis for SDHV systems by evaluating the incremental costs 

and efficiency improvements associated with design changes to blower coil units and pairing of existing SDHV 

blower coil units with higher-efficiency outdoor units. In that analysis, DOE found that the maximum 

technologically feasible (“max-tech”) efficiency of SDHV systems was just over 13 SEER. 

http://eere.energy.gov/buildings/appliance_standards/residential/pdfs/engineering_analysis_112602.pdf 

1-4 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

gross inequity, serious hardship, and an unfair distribution of burdens if forced to comply with 

the 13 SEER standard. On December 20, 2005, the OHA granted the exception relief to ESP, 

citing the same reasons given in the SpacePak/Unico decision and authorizing Energy Savings 

Products to manufacture and sell SDHV systems that meet an 11 SEER/6.8 HSPF standard. This 

decision also became effective January 23, 2006, and remains in effect until DOE establishes a 

different standard for SDHV systems. 

1.2.2 Space-Constrained Products 

In the 1999 SANOPR, DOE first suggested separate product classes as a way to set 

standards for space-constrained niche products. 64 FR at 66310. Originally, these products 

included ductless split systems, SDHV systems, single-package vertical units (SPVU), and 

through-the-wall (TTW) split systems. In the subsequent 2000 NOPR, through-the-wall 

packaged and non-weatherized single-package products were also considered space constrained. 

65 FR at 59597. DOE’s efforts to establish standards for each of these types of products is 

explained below. 

In the 2004 Technical Amendment, DOE established a separate product class for spaceconstrained systems and required them to meet a 12 SEER/7.4 HSPF standard. Product classes 

were also set for split-system and single-package TTWs, with standards at 10.9 SEER/7.1 HSPF 

and 10.6 SEER/7.0 HSPF, respectively. The separate product class for TTW products is set to 

expire January 23, 2010, which will return those products to the space-constrained product class 

and require them to meet the 12 SEER/7.4 HSPF standard. 

Currently, ductless split systems are not considered a space-constrained product and are 

not given special consideration. They are, therefore, required to meet the 13 SEER/7.7 HSPF 

standards for split-system and single-package air conditioners and heat pumps. SDHV systems 

are also not considered space constrained, and are required to meet the 13 SEER/7.7 HSPF 

standards. 

In this rulemaking, DOE is reevaluating whether to give special consideration to these 

space-constrained products. Below, the history of each type of product is reviewed, and DOE’s 

approach for how to handle each type in this rulemaking is presented. 

1.2.2.1 Single-Package Vertical Units (SPVUs) 

In the 2000 NOPR, DOE stated that SPVUs are not covered by standards for residential 

products. 65 FR at 59610. EISA 2007 added definitions7

 and standards8 for SPVUs. While 

7

 Section 314 of EISA 2007 codifies definitions for “single package vertical air conditioner” and “single package 

vertical heat pump.” The term “single package vertical air conditioner” means “air-cooled commercial package air 

conditioning and heating equipment that (A) is factory-assembled as a single package that (i) has major components 

that are arranged vertically; (ii) is an encased combination of cooling and optional heating components; and (iii) is 

intended for exterior mounting on, adjacent interior to, or through an outside wall; (B) is powered by a single- or 3-

phase current; (C) may contain 1 or more separate indoor grilles, outdoor louvers, various ventilation options, indoor 

free air discharges, ductwork, well plenum, or sleeves; and (D) has heating components that may include electrical 

resistance, steam, hot water, or gas, but may not include reverse cycle refrigeration as a heating means.” The term 

“single package vertical heat pump” means “a single package vertical air conditioner that (A) uses reverse cycle 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

EISA 2007 defined SPVUs as commercial equipment, residential single-package TTW products 

are still considered a part this rulemaking. 

1.2.2.2 Through-the-Wall Systems 

In the 2000 NOPR, DOE recognized TTW products as being a niche category of products 

with space constraints, and proposed adopting an 11 SEER standard for them. 65 FR at 59610. 

However, in light of stakeholders’ concerns that TTW products would not be able to meet the 13 

SEER standard, the 2001 Final Rule did not set standards for TTW products, pending completion 

of later rulemaking proceedings. Prior to the subsequent 2001 SNOPR, DOE performed 

engineering and life-cycle cost analyses for TTW products to determine appropriate standard 

levels. Based on those analyses, DOE concluded that 10.9 SEER/7.1 HSPF and 10.6 SEER/7.0 

HSPF were the appropriate standards for split-system and single-package TTW products, 

respectively, and adopted those standards in the 2002 final rule. 67 FR 36368 In the 2004 

Technical Amendment, DOE explained that the standards for TTW products, which fall within 

the definition of “space-constrained product,” would be those set in the 2002 final rule. 

The definition of “through-the-wall air conditioner and heat pump” that DOE adopted in 

10 CFR 430.2 provides that this product class exists only for products manufactured prior to 

January 23, 2010. After that date, the standards for space-constrained products (12 SEER/7.4 

HSPF) will apply to TTW split-system and packaged air conditioners and heat pumps. Because 

this “sunset” provision takes place well before the effective date of this rule (2016), DOE will 

evaluate standards for TTW products based on an assumed baseline of 12 SEER/7.4 HSPF. 

Manufacturers will have six years between the time TTW products must meet the 12 SEER/7.4 

HSPF standard and the time new standards adopted in this rulemaking become effective. 

1.2.2.3 Single-Package Non-Weatherized Units 

In the 2000 NOPR, DOE recognized single-package non-weatherized units as having 

space constraints, but due to the availability of models at the 12 SEER level (the proposed 

standard level for conventional air conditioners in that rulemaking), DOE did not propose a 

separate product class for them. 65 FR at 59610. Additionally, DOE concluded it would be 

difficult to define these products in such a way that would avoid the creation of a loophole 

whereby conventional products could take advantage of lower standards. In the 2001 final rule, 

DOE again made mention of single-package non-weatherized units, but DOE decided to include 

them as a type of space-constrained product. The 2001 final rule established a new product class 

for space-constrained products, but did not set standards in that rule pending completion of later 

rulemaking proceedings. In the subsequent 2001 SNOPR and the 2002 final rule, no specific 

mention was made of single-package non-weatherized units, but DOE still considered them as a 

type of space-constrained product. In the 2002 final rule, DOE concluded that space-constrained 

products (excluding TTW products) would be able to meet the 12 SEER standard for 

conventional products, and did not adopt separate standards for those considered space 

constrained. Ultimately, in the 2004 Technical Amendment, DOE explained that the ruling by 

refrigeration as its primary heat source; and (B) may include secondary supplemental heating by means of electrical 

resistance, steam, hot water, or gas.’’ (42 U.S.C. 6311(22)-(23))
 8

 Section 314 of EISA 2007 set standards at 9.0 EER for single-package vertical air conditioners and 9.0 EER/3.0 

coefficient of performance (COP) for single-package vertical heat pumps.
 

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EERE-2008-BT-STD-0006 COMMENT 54
 

the Second Circuit Court of Appeals in Natural Resources Defense Council v. Abraham did not 

affect the standards established for space-constrained products in the 2002 final rule, since the 

2001 final rule did not establish any standards for space-constrained products. Therefore, the 12 

SEER standard established in the 2002 final rule was adopted for all space-constrained products, 

except those with TTW condensers. 

1.2.3 Ductless Split Systems 

Ductless split systems were included in the revisions to the DOE test procedure in the 

March 14, 1987 final rule. 53 FR 8304. In the 1999 SANOPR, DOE first suggested separate 

product classes as a way to set standards for niche products, including ductless split systems. 64 

FR at 66310. Since consumers may consider the interior units of mini- and multi-splits to be 

more intrusive than ducted systems, manufacturers strive to make them as compact as possible. 

After receiving stakeholder feedback, DOE decided that a separate product class was not 

warranted, and ultimately in the final rule that set the current standards, ductless split systems 

were required to meet the 13 SEER standards developed for regular split-system air conditioners 

and heat pumps. 66 FR at 7197. 

Prior to the latest revision to the test procedure, manufacturers of ductless split systems 

applied for and received waivers from the test procedure because of the differences between 

multi-split systems and traditional split-system air conditioners and heat pumps. In the most 

recent final rule revising the central air conditioner and heat pump test procedure, DOE 

responded to stakeholder comments regarding changes to the test procedure for multi-splits. 72 

FR at 59906, 59908-11 and 59913-14 (Oct. 22, 2007). Stakeholders asserted that multi-split 

systems should be rated using EER if those systems compete primarily with room air 

conditioners and SEER if they compete primarily with ducted residential systems. DOE 

responded in the October 2007 rule that it believes residential-size multi-split systems compete 

primarily with ducted systems, and that consumers will best be served if multi-split systems are 

rated using SEER. This will allow consumers to make direct comparisons of efficiency levels 

when considering system options. 

1.3 PROCESS FOR SETTING ENERGY CONSERVATION STANDARDS 

Under EPCA, when DOE studies new or amended standards, it must consider to the 

greatest extent practicable the following seven factors: 

(1) the economic impact of the standard on the manufacturers and consumers of the 

products subject to the standard; 

(2) the savings in operating costs throughout the estimated average life of the products 

in the type (or class) compared to any increases in the price, initial charges, or 

maintenance expense for the 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; 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

(4) any lessening of the utility or the performance of the products likely to result from 

the imposition of the standard; 

(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. (42 U.S.C. 6295(o)(2)(B)(i)) 

Other statutory requirements are set forth in 42 U.S.C. 6295(o)(1)-(2)(A), (2)(B)(ii)-(iii), 

and (3)-(4). 

DOE considers the participation of interested parties a very important part of the process 

for setting energy conservation standards. Through formal public notifications (i.e., Federal 

Register notices), DOE encourages the participation of all interested parties during the comment 

period in each stage of the rulemaking. Beginning with the framework document and during 

subsequent comment periods, interactions among interested parties provide a balanced 

discussion of the information that is required for the standards rulemaking. 

Before DOE determines whether to adopt a proposed energy conservation standard, it 

must first solicit comments on the proposed standard. (42 U.S.C 6313(a)(6)(B)(i)) Any new or 

amended standard must be designed to achieve significant additional conservation of energy and 

be technologically feasible and economically justified. (42 U.S.C. 6313(a)(6)(A)) To determine 

whether economic justification exists, DOE must review comments on the proposal and 

determine that the benefits of the proposed standard exceed its burdens to the greatest extent 

practicable, weighing the seven factors listed above. (42 U.S.C. 6295(o)(2)(B)(i)) 

After the publication of the framework document, the energy conservation standards 

rulemaking process involves three additional, formal public notices, which DOE publishes in the 

Federal Register. The first of the rulemaking notices is a NOPM, which is designed to publicly 

vet the models and tools used in the preliminary rulemaking and to facilitate public participation 

before the NOPR stage. The second notice is the NOPR, which presents a discussion of 

comments received in response to the NOPM and the preliminary analyses and analytical tools; 

analyses of the impacts of potential amended energy conservation standards on consumers, 

manufacturers, and the Nation; DOE’s weighting of these impacts of amended energy 

conservation standards; and the proposed energy conservation standards for each product. The 

third notice is the final rule, which presents a discussion of the comments received in response to 

the NOPR; the revised analyses; DOE’s weighting of these impacts; the amended energy 

conservation standards DOE is adopting for each product; and the effective dates of the amended 

energy conservation standards. 

In June 2008, DOE published a notice of public meeting and availability of the framework 

document. 73 FR 32243 (June 6, 2008) The framework document, Rulemaking Framework for 

Residential Central Air Conditioners and Heat Pumps, describes the procedural and analytical 

approaches DOE anticipated using to evaluate the establishment of energy conservation 

standards for CAC. This document is available at: 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp_standard 

s.html. 

Subsequently, DOE held a public meeting on June 12, 2008, to discuss procedural and 

analytical approaches to the rulemaking, and to inform and facilitate stakeholders’ involvement 

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

different analyses, such as the engineering analysis and the life-cycle cost (LCC) and payback 

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

the various analyses. See 

 for all the analyses discussed at the public meeting to be undertaken in each of the formal 

public rulemaking documents. 

Table 1.3.1 Analyses During Each Rulemaking Stage 

Preliminary Analyses NOPR Final Rule* 

Market and Technology Assessment Revised Preliminary Analyses Revised NOPR Analyses 

Screening Analysis Life-Cycle Cost Sub-Group 

Analysis 

Engineering Analysis Manufacturer Impact Analysis 

Energy Use Characterization Utility Impact Analysis 

Markups to Determine Equipment Price Employment Impact Analysis 

Life-Cycle Cost and Payback Period 

Analyses 

Environmental Assessment 

Shipments Analysis Regulatory Impact Analysis 

National Impact Analysis 

Preliminary Manufacturer Impact Analysis 

* 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)) 

As part of the information gathering and sharing process, DOE organized and held 

interviews with CAC manufacturers. DOE selected companies that represented production of all 

types of CAC equipment, ranging from small to large manufacturers, and including both AirConditioning, Heating and Refrigeration Institute (AHRI) member companies and non-AHRI 

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 manufacturer impact 

analysis; (3) provide an opportunity, early in the rulemaking process, to express specific 

concerns to DOE; and (4) foster cooperation between the manufacturers and DOE. 

There were six general topics related to the preliminary manufacturer impact analysis 

discussed during each of the interviews: (1) general key issues, (2) CAC shipment projections, 

(3) capital conversion costs, (4) product mix and profitability, (5) market shares and industry 

consolidation, and (6) cumulative regulatory burden. 

DOE incorporated the information gathered at the meetings into its engineering analysis 

(see chapter 5) and the preliminary manufacturer impact analysis (see chapter 12). Following the 

publication of the preliminary analysis and the preliminary analysis public meeting, DOE intends 

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to hold additional meetings with manufacturers as part of the consultative process for the 

manufacturer impact analysis conducted during the NOPR phase of the rulemaking. 

DOE developed spreadsheets for the LCC, PBP, and national impact analyses. DOE 

developed an LCC spreadsheet that calculates the LCC and PBP at various energy efficiency 

levels. DOE also developed a national impact analysis spreadsheet that calculates the national 

energy savings (NES) and national net present values (NPVs) at various energy efficiency levels. 

This spreadsheet includes a model that forecasts the impacts of amended energy conservation 

standards at various levels on product shipments. 

1.4 STRUCTURE OF THE DOCUMENT 

This preliminary TSD outlines the analytical approaches used in this rulemaking. The 

TSD consists of 17 chapters, an environmental assessment, a regulatory impact analysis, and 

appendices. 

Chapter 1 Introduction: provides an overview of the appliance and equipment 

standards program and how it applies to the CAC rulemaking, and outlines 

the structure of the document. 

Chapter 2 Analytical Framework, Comments from Interested Parties, and DOE 

Responses: describes the rulemaking process step by step, summarizes 

comments made from interested parties during the framework document 

comment period, and provides DOE responses to those comments. 

Chapter 3 Market and Technology Assessment: characterizes the CAC equipment 

market and the technologies available for increasing equipment efficiency. 

Chapter 4 Screening Analysis: determines which technology options are viable for 

consideration in the engineering analysis. 

Chapter 5 Engineering Analysis: discusses the methods used for developing the 

relationship between increased manufacturer price and increased 

efficiency. 

Chapter 6 Markups to Determine Product Price: discusses the methods used for 

establishing markups for converting manufacturer prices to customer 

product prices. 

Chapter 7 Energy Use Characterization: discusses the process used for generating 

energy-use estimates of CAC for a variety of product classes, climate 

locations, and standard levels. 

Chapter 8 Life-Cycle Cost and Payback Period Analyses: discusses the economic 

effects of standards on individual customers and users of the products and 

compares the LCC and PBP of products with and without higher 

efficiency standards. 

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Chapter 9 Shipments Analysis: discusses the methods used for forecasting 

shipments with and without higher efficiency standards. 

Chapter 10 National Impact Analysis: discusses the methods used for forecasting 

national energy consumption and national economic impacts based on 

annual product shipments and estimates of future product efficiency 

distributions in the absence and presence of higher efficiency standards. 

Chapter 11 Life-Cycle Cost Sub-Group Analysis: discusses the effects of standards 

on a subgroup of CAC customers and compares the LCC and PBP of 

products with and without higher efficiency standards for these customers. 

Chapter 12 Preliminary Manufacturer Impact Analysis: discusses the effects of 

standards on the finances and profitability of product manufacturers. 

Chapter 13 Utility Impact Analysis: discusses the effects of standards on the installed 

generation capacity of electric utilities. 

Chapter 14 Employment Impact Analysis: discusses the effects of standards on 

National employment. 

Chapter 15 Environmental Assessment: discusses the effects of standards on airborne emissions of electric utilities. 

Chapter 16 Regulatory Impact Analysis: discusses the present regulatory actions as 

well as the impact of non-regulatory alternatives to setting energy 

efficiency standards. 

Chapter 17 Regional Standards Impacts on Market Participants: discusses the effects 

of regional standards on distributors, dealers, contractors, and installers. 

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CHAPTER 2. ANALYTICAL FRAMEWORK, COMMENTS FROM
 

INTERESTED PARTIES, AND DOE RESPONSES 

TABLE OF CONTENTS
 

2.1 INTRODUCTION .............................................................................................................. 1
 

2.1.1 Overview ................................................................................................................. 1
 

2.1.2 Miscellaneous Rulemaking Issues .......................................................................... 3
 

2.2 MARKET AND TECHNOLOGY ASSESSMENT ........................................................... 7
 

2.2.1 Product Classes and Scope of Coverage................................................................. 8
 

2.2.2 Technology Assessment........................................................................................ 10
 

2.3 SCREENING ANALYSIS ............................................................................................... 14
 

2.4 ENGINEERING ANALYSIS........................................................................................... 14
 

2.4.1 Baseline Products .................................................................................................. 16
 

2.4.2 Space-Constrained Products ................................................................................. 17
 

2.5 MARKUPS TO DETERMINE PRODUCT PRICE ......................................................... 17
 

2.5.1 Distribution Channel Structure ............................................................................. 17
 

2.5.2 Data Sources for Distribution Channel Markups .................................................. 19
 

2.5.3 Markups/Price Determination ............................................................................... 20
 

2.6 ENERGY USE CHARACTERIZATION ........................................................................ 20
 

2.6.1 Residential Energy Use analysis........................................................................... 22
 

2.6.2 Impact of Improved Building Codes..................................................................... 23
 

2.6.3 Inclusion of Commercial Energy Use Analysis .................................................... 24
 

2.6.4 Use of Rated Performance versus Degraded Performance ................................... 24
 

2.6.5 Characterization of Energy Using SEER/HSPF ................................................... 25
 

2.6.6 Development of Regions for Regional Standard Analysis ................................... 25
 

2.7 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES ..................................... 29
 

2.7.1 General Approach for Life-Cycle Cost and Payback Period Analyses ................ 30
 

2.7.2 Electricity Prices ................................................................................................... 31
 

2.7.3 Repair Cost............................................................................................................ 34
 

2.7.4 Maintenance Cost.................................................................................................. 35
 

2.7.5 Discount Rate........................................................................................................ 36
 

2.8 NATIONAL IMPACT ANALYSIS................................................................................. 38
 

2.8.1 Shipments Analysis ............................................................................................... 38
 

2.8.2 Efficiency Scenarios and Trends .......................................................................... 41
 

2.8.3 National Energy Savings Analysis........................................................................ 42
 

2.8.4 Net Present Value Analysis .................................................................................. 43
 

2.9 PRELIMINARY MANUFACTURER IMPACT ANALYSIS ........................................ 44
 

2.9.1 Industry Cash-Flow Analysis................................................................................ 45
 

2.9.2 Manufacturer Subgroup Analysis ......................................................................... 45
 

2.9.3 Competitive Impacts Assessment ......................................................................... 46
 

2.9.4 Cumulative Regulatory Burden ............................................................................ 46
 

2.9.5 Preliminary Results for the Manufacturer Impact Analysis ................................. 48
 

2.9.6 Regional Standards Impacts on Manufacturers .................................................... 48
 

2.10 REGIONAL STANDARDS IMPACTS ANALYSIS...................................................... 49
 

2.10.1 Impacts on Manufacturers..................................................................................... 50
 

2.10.2 Impacts on Distributors, Dealers, and Contractors, and Installers........................ 50
 

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2.10.3 Enforcement .......................................................................................................... 51
 

2.11 LIFE-CYCLE COST SUBGROUP ANALYSIS ............................................................. 53
 

2.12 UTILITY IMPACT ANALYSIS...................................................................................... 54
 

2.13 ENVIRONMENTAL ASSESSMENT ............................................................................. 54
 

2.13.1 Carbon Dioxide ..................................................................................................... 54
 

2.13.2 Sulfur Dioxide....................................................................................................... 54
 

2.13.3 Nitrogen Oxides .................................................................................................... 55
 

2.13.4 Mercury ................................................................................................................. 56
 

2.13.5 Particulate Matter.................................................................................................. 56
 

2.13.6 Monetization of Emissions Reduction Benefits .................................................... 56
 

2.14 EMPLOYMENT IMPACT ANALYSIS.......................................................................... 58
 

2.15 REGULATORY IMPACT ANALYSIS .......................................................................... 58
 

LIST OF TABLES 

Table 2.1 Energy Conservation Standards for Space-Constrained Products ............................. 2-17
 

LIST OF FIGURES 

Figure 2.1 Distribution Channels for Central Air Conditioners and Heat Pumps .................... 2-19
 

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CHAPTER 2. ANALYTICAL FRAMEWORK, COMMENTS FROM 

INTERESTED PARTIES, AND DOE RESPONSES 

2.1 INTRODUCTION 

2.1.1 Overview 

Section 6295(o)(2)(A) of the Energy Policy and Conservation Act, as amended, 42 USC 

6291 et. seq., requires that when prescribing new or amended energy conservation standards for 

covered products, the U.S. Department of Energy (DOE) promulgate standards that achieve the 

maximum improvements in energy efficiency that are technologically feasible and economically 

justified. This chapter provides a description of the analytical framework that DOE is using to 

evaluate amended energy conservation standards for residential central air conditioners and heat 

pumps. The chapter sets forth the methodology, analytical tools, and relationships among the 

various analyses that are part of this rulemaking. 

The analyses performed as part of the accompanying notice and reported in this 

preliminary technical support document (preliminary TSD) are as follows: 

•	 A market and technology assessment characterizes the relevant products, their markets 

and technology options for improving their energy efficiency, including prototype 

designs. 

•	 A screening analysis reviews each technology option and determines if it is 

technologically feasible; is practicable to manufacture, install, and service; would 

adversely affect product utility or product availability; or would have adverse impacts on 

health and safety. 

•	 An engineering analysis develops relationships that show the manufacturer’s cost of 

achieving increased efficiency. DOE determines the increased cost to the consumer 

through an analysis of manufacturer markups. The engineering analysis also develops 

manufacturer markups that convert manufacturer production cost (MPC) to manufacturer 

selling price (MSP). 

•	 An energy use analysis determines the annual energy use of the considered products. 

•	 A markup analysis develops the distribution channel markups used to determine final 

customer price starting with MSP. 

•	 The LCC and payback period (PBP) analyses calculate the discounted savings in 

operating costs (less any increase in maintenance and repair costs) at the consumer level 

throughout the life of the covered products compared with any increase in the installed 

cost for the products likely to result directly from imposition of the standard. 

•	 A shipments analysis forecasts product shipments, which then are used to calculate the 

national impacts of standards on energy, net present value (NPV), and future 

manufacturer cash flows. 

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•	 A national impact analysis (NIA) assesses the aggregate impacts at the national level of 

the NPV of total consumer LCC and national energy savings (NES). 

•	 A preliminary manufacturer impact analysis (MIA) assesses the potential impacts of 

energy conservation standards on manufacturers, such as impacts on capital conversion 

expenditures, marketing costs, shipments, and research and development costs. 

In the subsequent notice of proposed rulemaking (NOPR) stage, DOE will revise the 

preliminary analyses just described, to the extent warranted by comments and new information. 

In addition, DOE will perform the following analyses: 

•	 An LCC subgroup analysis will evaluate variations in customer characteristics that might 

cause a standard to affect particular consumer sub-populations (such as low-income 

households) differently than the overall population. 

•	 An MIA will estimate the financial impact of standards on manufacturers and calculate 

impacts on competition, employment, and manufacturing capacity. 

•	 A regional standards impact analysis will examine the impacts of regional standards on 

distributors, dealers, contractors and installers. Analysis of potential impacts of regional 

standards on manufacturers and consumers, as required by EPCA, will be conducted as 

part of the MIA and LCC and PBP analyses, respectively. 

•	 A utility impact analysis will estimate the effects of proposed standards on electric, gas, 

or oil utilities. 

•	 An employment impact analysis will assess the aggregate impacts on national 

employment.
 

•	 An environmental impact analysis will provide estimates of the effects of amended 

energy conservation standards on carbon dioxide (CO2), sulfur dioxide (SO2), nitrogen 

oxides (NOx), and mercury (Hg). 

•	 A regulatory impact analysis (RIA) will evaluate major alternatives to proposed amended 

energy conservation standards, to assess whether such alternatives could achieve 

substantially the same regulatory goal at a lower cost. 

DOE developed this analytical framework in the Rulemaking Framework for Residential 

Central Air Conditioners and Heat Pumps (June 2, 2008). 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 June 6, 2008. 73 FR 32243–45. DOE presented the 

analytical approach to interested parties during a public meeting held on June 12, 2008. The 

framework document is available at 

http://www1.eere.energy.gov/buildings/appliance_standards/residential/pdfs/cac_framework.pdf. 

In response to the publication of the framework document and to the public meeting, 

DOE received numerous comments from interested parties regarding DOE’s analytical approach. 

This chapter summarizes the key comments and describes DOE’s responses. In this chapter, 

DOE also summarizes any significant changes that it has made in the analytical approach 

described in the framework document and that it has incorporated into its preliminary analyses. 

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In the executive summary of the preliminary TSD, DOE identifies a number of issues for which 

DOE seeks public comment. DOE has explained each of those issues in the relevant analysis 

sections below. 

2.1.2 Miscellaneous Rulemaking Issues 

2.1.2.1 Retention of the Advanced Notice of Proposed Rulemaking 

After publication of the framework document, DOE received comments about whether 

the advanced notice of proposed rulemaking (ANOPR) step should be retained in DOE’s 

rulemaking process. In a joint comment submitted by the American Council for an EnergyEfficient Economy (ACEEE), the Appliance Standards Awareness Project (ASAP), the 

California Energy Commission (CEC), the Northwest Power and Conservation Council (NPCC), 

and the Western Cooling Efficiency Center (WCEC) (hereafter “Joint Comment 1”), these 

interested parties cooperatively expressed a desire for DOE to provide all the analyses 

traditionally associated with the ANOPR for review. (Joint Comment 1, No. 25 at p. 9) In 

addition, Heating, Air Conditioning & Refrigeration Distributors International (HARDI) stated 

that the ANOPR process is even more essential for this rulemaking because of the complexity of 

the standard. Specifically, it mentioned DOE’s unprecedented consideration of regionalizing the 

standard and, in its opinion, DOE’s need for a better understanding of the heating, ventilation, 

and air conditioning (HVAC) distribution channel, its cost structure, and its role within the 

industry (HARDI, No. 32 at p. 2). The Southern Company (Southern) also considers the ANOPR 

an essential part of the rulemaking process. (Southern, No. 39 at p. 4) According to Southern, the 

ANOPR allows “consideration and critique of the economic and market assumptions to be used 

in the NOPR without consideration of proposed stringency levels, and allows the NOPR stage of 

the rulemaking to focus on stringency levels without excessive questioning of the analysis 

assumptions.” The National Rural Electric Cooperative Association (NRECA), Trane, Carrier, 

the Air-Conditioning, Heating, and Refrigeration Institute (AHRI), the Air Conditioning 

Contractors of America (ACCA), and the American Supply Association (ASA) also expressed 

support for DOE’s use of the ANOPR for this rulemaking because it provides an increased level 

of transparency to the process and an opportunity for interested parties to provide valuable 

feedback. (NRECA, No. 35 at p. 2; Trane, No. 16 at p. 5; Carrier, No. 18 at p. 4; AHRI, Public 

Meeting Transcript, No. 13 at p. 14; ACCA, Public Meeting Transcript, No. 23 at p. 28; ASA, 

Public Meeting Transcript, No. 13 at p. 32) 

Section 307 of the Energy Independence and Security Act of 2007 (Pub. L. 110–140; 

EISA 2007) amended the Energy Policy and Conservation Act (EPCA) by removing the 

requirement for DOE to publish an ANOPR when amending standards for consumer products. 

DOE agrees, however, that in past rulemakings, ANOPRs have provided a valuable early 

opportunity for DOE to vet its assumptions and analyses and for interested parties to provide 

comments and data. Therefore, DOE developed an alternative to the ANOPR, consisting of a 

preliminary analysis and a notice of TSD availability to the public. These documents include 

summaries of, and DOE responses to, comments received at the framework workshop and during 

the framework comment period. In addition, a public meeting will be held following publication 

of the preliminary analysis materials. Therefore, the preliminary analysis allows for an expedited 

rulemaking process that does not sacrifice transparency or feedback opportunities for interested 

parties. 

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2.1.2.2 Regional Standards 

Section 306(a) of EISA 2007 amended EPCA to authorize DOE to consider regional 

standards for central air conditioners and heat pumps for one or two regions in addition to a base 

national standard. (42 U.S.C. 6295(o)(6)) In the framework document, DOE requested comment 

on the potential impacts that regional standards for residential central air conditioners and heat 

pumps may have on the industry. HARDI commented that it was concerned about how the 

possible adoption of regional standards might affect ENERGY STAR specifications. (HARDI, 

No. 32 at p. 6) HARDI expressed concern that the ENERGY STAR label could be significantly 

degraded by forcing the brand to be regionalized or moving to prohibitively expensive efficiency 

levels in regions with higher minimum standards. 

ENERGY STAR creates an incentive for manufacturers to develop and for consumers to 

purchase higher efficiency products. However, DOE does not have data to determine degradation 

of the ENERGY STAR label through the imposition of regional standards, and welcome 

comments on the issue. 

2.1.2.3 Effective Date of Standards 

This rulemaking implements the EPCA requirement for a second amended energy 

conservation standards rulemaking for central air conditioners and heat pumps. (42 U.S.C. 

6295(d)(3)(B)) In the framework document, DOE explained that pursuant to the consolidated 

consent decree in New York versus Bodman, No. 05 Civ. 7807 (S.D.N.Y. filed September 7, 

2005) and Natural Resources Defense Council versus Bodman, No. 05 Civ. 7808 (S.D.N.Y. filed 

September 7, 2005), DOE must publish a final rule in this rulemaking by June 30, 2011. 

Consistent with the lead time specified in 42 U.S.C. 6295(d)(3)(B) for the second round of 

amended standards for central air conditioners and heat pumps, DOE determined that any such 

standards would apply to products manufactured on or after 5 years after publication of the final 

rule. DOE expects to publish a final rule by June 30, 2011 as required by the consent decree, 

thereby requiring compliance with the standards effective by June 30, 2016. 

At the framework public meeting, DOE received several comments about the June 2016 

effective date. ACCA stated this date will cause inconsistencies for distributors, because they 

will have to switch to more expensive products during peak season. (ACCA, Public Meeting 

Transcript, No. 13 at p. 89) Lennox suggested that the effective date of the standard should be 

January instead of June 2016 to avoid peak season. (Lennox, Public Meeting Transcript, No. 13 

at p. 76) ASAP believes that under 42 U.S.C. 6295(d)(3)(B), DOE is not bound to any particular 

effective date, providing some flexibility to change the date to minimize manufacturing impact. 

(ASAP, Public Meeting Transcript, No. 13 at p. 100) 

DOE previously determined that the final rule in this rulemaking must be published by 

June 30, 2011 and tentatively decided that the rule would apply to products manufactured 5 years 

later, in June 2016. DOE seeks further comment on compliance during the peak season. 

(Reference Chapter 2 of the preliminary TSD for details.) 

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2.1.2.4 Consensus Negotiations 

Efficiency organizations indicated their willingness to participate in developing 

consensus recommendations but requested regular DOE communication with interested parties 

during the preliminary analysis process. They also noted that for consensus negotiations to work, 

DOE should be willing to consider a standard that might include both performance and 

prescriptive elements (such as controls and/or interfaces). (Joint Comment 1, No. 25 at p. 5) For 

residential central air conditioners and heat pumps, DOE lacks the authority to prescribe a 

standard that consists of a “design requirement,” i.e., a prescriptive requirement. (42 U.S.C. 

6291(6)(B), 6292(a)(3)) Further, generally an energy conservation standard must be either a 

performance requirement or a design requirement, but cannot include both elements. (42 U.S.C. 

6291(6)) 

2.1.2.5 Heat Pump Cooling Efficiency Requirements 

NRECA and the Edison Electric Institute (EEI) both stated that final standards for 

cooling efficiency requirements for central air conditioner and heat pump products should be the 

same. (NRECA, No. 35 at p. 1; EEI, No. 20 at p. 3) 

In the previous energy efficiency standards rulemaking for residential central air 

conditioners and heat pumps, DOE prescribed the same cooling-efficiency standard for both 

types of products. This resulted largely from DOE’s concern that higher cooling-efficiency 

ratings for heat pumps might cause consumers to switch to electric resistance furnaces and air 

conditioners, thereby negating the benefits of higher efficiency levels. 66 FR 7169, 7180-81, 

7196 (January 22, 2001)(the 2001 residential central air conditioner and heat pump final rule). In 

this rulemaking, as reflected in this preliminary TSD, DOE is analyzing air-conditioning and 

heat pump products independently of one another to determine if any amended standard levels 

are appropriate. In addition to enabling more precise analysis of each product, these independent 

analyses will facilitate DOE’s determination as to whether to have the same cooling-efficiency 

standards for central air conditioners and heat pumps and will facilitate comments on this issue. 

Based on the analyses it had conducted to date, DOE intends to develop cooling-efficiency 

standards that are the same for both types of products. However, DOE is still considering this 

issue and requests comment on whether to set standards with the same cooling efficiency for air 

conditioners and heat pumps. 

2.1.2.6 Imported Products 

At the framework public meeting, Mitsubishi Electric & Electronics USA, Inc. (MEUS) 

questioned whether the amended energy conservation standard will be applicable to products 

manufactured before but imported after the effective date. (MEUS, Public Meeting Transcript, 

No. 13 at p. 94) 

The amended standards would apply to all such products. If DOE adopts a single set of 

national energy conservation standards for central air conditioners and heat pumps, such 

standards would apply to products “manufactured” on or after a specified date. (42 U.S.C. 

6295(d)(3)(B)) EPCA defines “manufacture" as meaning “to manufacture, produce, assemble or 

import” and "import" as meaning “to import into the customs territory of the United States.” (42 

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EERE-2008-BT-STD-0006 COMMENT 54
U.S.C. 6291(10), (11)) In addition, if DOE adopts any regional standards, the companion base 

national standards would “apply to all products manufactured or imported into the United States 

on and after the effective date for the standard.” (42 U.S.C. 6295(o)(6)(E)(i)(II)) Any regional 

standard for a product would apply “to any such product installed on or after the effective date of 

the standard.” (42 U.S.C. 6295(o)(6)(E)(ii)) Therefore, for either a single set of national energy 

conservation standards or base national standards adopted in conjunction with regional standards, 

products imported into the customs territory of the United States on or after the effective date 

must comply with the standards, regardless of the date of manufacture. Further, because products 

would be installed after the date of manufacture and import, regional standards would be 

applicable to any products manufactured or imported before but installed after the effective date 

of the standards. 

2.1.2.7 Test Procedure Issues 

DOE received multiple comments at the framework public meeting about revisions to the 

residential central air conditioner and heat pump test procedure. DOE addressed these comments 

in a NOPR recently issued to propose revisions to the central air conditioner and heat pump test 

procedure. That rulemaking is being conducted in parallel with this standards rulemaking. The 

comments apply to the following areas: bench testing of third-party coils, defaults for fan power 

in the test procedure, external static pressure in the test, fan time delay relays, incorporation of 

inverter driven compressors, addition of calculation and reporting requirements for sensible heat 

ratio, how to address testing inconsistencies for ductless mini-splits, and incorporation of 

standby-mode and off-mode energy consumption. 

Several of these comments overlap issues surrounding the development of proposed 

standards, including the possible development of different seasonal energy efficiency ratio 

(SEER) metrics that would apply regionally and would better characterize system efficiency and 

performance for the defined regions. Consistent with the requirement in EPCA for DOE to 

express the “efficiency descriptor” for central air conditioners and heat pumps as SEER, DOE is 

considering adoption of revised SEER metrics to reflect regional operating conditions. DOE has 

examined a method of developing a SEER specific to a four-state, hot-dry region. DOE believes 

that the existing SEER ratings sufficiently address performance in hot-humid climates. For the 

preliminary analysis, DOE did not have sufficient information on how product costs and overall 

system performance might change if a SEER hot-dry metric was used. Therefore, DOE used the 

current SEER rating metric for its energy and economic analysis. DOE will examine comments 

on the development of the hot-dry SEER and its utility in standards setting in the NOPR stage of 

the rulemaking. 

2.1.2.8 Standby-Mode and Off-Mode Energy Consumption 

In Section 310 of EISA 2007, Congress directed DOE to amend test procedures for all 

covered products to include standby mode and off mode energy consumption unless current 

procedures already cover such energy consumption or an integrated test procedure is technically 

infeasible, in which case a separate standby mode and off mode test procedure must be 

prescribed, if technically feasible. (42 U.S.C. 6295(gg)(2)) Section 310 also required any final 

rule establishing or revising standards for covered products adopted after July 1, 2010 to 

incorporate standby mode and off mode energy use. (42 U.S.C. 6295(gg)(3)) Because this energy 

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EERE-2008-BT-STD-0006 COMMENT 54
conservation standards rulemaking for central air conditioners and heat pumps is scheduled to be 

completed in 2011, the requirement to incorporate standby-mode and off-mode energy use into 

the energy conservation standards analysis is applicable. 

DOE considers standby-mode for central air conditioners and heat pumps to be in effect 

when the system is on during the cooling and heating seasons, but the compressor is not running. 

In other words, a system is in standby-mode if it is not actively heating or cooling, but the 

compressor is primed to be activated by the thermostat. DOE considers off-mode for central air 

conditioners and heat pumps to be in effect when a system is not set to a heating-mode or 

cooling-mode. For heat pumps, off-mode is generally characterized by the “shoulder seasons” 

(i.e., fall and spring), when consumers are not heating or cooling their homes. For air 

conditioners, off-mode is generally characterized by all non-cooling seasons. DOE determined 

that standby-mode energy consumption is already accounted for in the SEER and heating 

seasonal performance factor (HSPF) metrics for central air conditioners and heat pumps. DOE 

cannot, however, incorporate off-mode energy consumption into the SEER and/or HSPF metrics 

because by definition, these metrics are seasonal efficiency descriptors. If DOE were to integrate 

off-mode energy consumption into the SEER and/or HSPF metrics, these efficiency descriptors 

would expand beyond the cooling and heating seasons, respectively, and would no longer be 

seasonal efficiency descriptors as required by EPCA, but rather annual efficiency descriptors. 

DOE intends to present off-mode energy consumption in terms of kilowatt hours per year as 

additional information for consideration by interested parties and requests comment on this 

approach. 

2.1.2.9 Federal Preemption 

AHRI asserted that a number of local jurisdictions have mandated efficiency standards 

for central air conditioners and heat pumps that are more stringent than the Federal standards, in 

violation of Federal preemption and causing an additional burden on the industry. (AHRI, No. 24 

at p. 12) 

As AHRI appears to be aware, the DOE standards currently applicable to these products, 

codified at 10 CFR 430.32(c), preempt such state and local standards as provided by EPCA in 42 

U.S.C. 6297(c). EPCA allows States to petition DOE for waivers of preemption for specific state 

standards, however, DOE can grant waiver applications if statutory criteria are met. (42 U.S.C. 

6297(d)) 

2.2 MARKET AND TECHNOLOGY ASSESSMENT 

When DOE begins an energy conservation standards rulemaking, it develops information 

that provides an overall picture of the market for the products considered, including the nature of 

the products, market characteristics, and industry structure. This activity consists of both 

quantitative and qualitative efforts based primarily on publicly available information. The market 

assessment examined manufacturers, trade associations, and the quantities and types of products 

sold and offered for sale. 

DOE reviewed relevant literature and interviewed manufacturers to develop an overall 

picture of the residential central air conditioner and heat pump industry in the United States. 

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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 cooling capacity, (3) product information, and (4) industry trends. 

Subsequent sections of this chapter describe the comments DOE received in response to 

its review of the central air conditioner and heat pump market for the framework document. The 

analysis developed as part of the market and technology assessment is described in chapter 3 of 

the preliminary TSD. 

2.2.1 Product Classes and Scope of Coverage 

When evaluating and establishing energy conservation standards, DOE generally divides 

covered products into product classes by the type of energy used, capacity, or other performancerelated features that affect efficiency. Different energy conservation standards may apply to 

different product classes. (42 U.S.C. 6295(q)) 

DOE identified seven product classes for this rulemaking: (1) split-system air 

conditioners, (2) split-system heat pumps, (3) single-package air conditioners, (4) single-package 

heat pumps, (5) small-duct high-velocity (SDHV) systems, (6) space-constrained air 

conditioners, and (7) space-constrained heat pumps. DOE directly analyzed the four primary 

residential central air conditioner and heat pump product classes (the first four classes listed 

above). These four product classes represent most of the total shipments of these products. DOE 

describes the technical aspects and energy savings potential for the three remaining product 

classes in chapter 5 of the preliminary TSD. DOE intends to conduct a full technical analysis for 

these three product classes in the NOPR. 

DOE received input from interested parties on the product definitions and product classes 

that DOE included in the framework document. Specifically, DOE received comments on spaceconstrained products; ductless and variable refrigerant flow (VRF) split systems; SDHVs; and 

large-tonnage products. 

2.2.1.1 Space-Constrained Products 

Carrier expressed opposition to the eventual inclusion of through-the-wall (TTW) split air 

conditioners and heat pumps in the space-constrained product class for all but replacement 

applications. According to Carrier, if DOE allowed these TTW products to be covered under the 

space-constrained definition, they would be installed in new construction applications with the 

potential to capture a significant share of that market segment. Carrier asserted that this market 

share shift could occur because manufacturers of TTWs would have an unfair cost advantage as 

a result of their products being subject to a lower minimum efficiency standard. Carrier 

suggested that DOE exclude TTW products from the space-constrained product class or alter the 

space-constrained definition to ensure that TTW products remain limited to their current 

replacement niche. (Carrier, No. 18 at pp. 4–5) National Refrigeration and Air-Conditioning 

Products (NRACP), a TTW manufacturer, also opposes eliminating the TTW product class. In 

contrast to Carrier, NRACP asserts that the definition of “space-constrained product” is 

ambiguous and could lead to a market shift in the opposite direction. NRACP claims that 

manufacturers of non-TTW products would ask to be considered space-constrained products, 

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allowing their products to compete in the replacement market segment. (NRACP, No. 34 at p. 1) 

Joint Comment 1 supports the phase-out of the TTW product class and subsequent application of 

the more stringent standard for space-constrained products, the class under which TTW products 

will be covered. (Joint Comment 1, No. 25 at p. 9) 

Under DOE’s regulations, the TTW product classes are defined to include only products 

manufactured before January 23, 2010. 10 CFR 430.2 and 430.32(c)(2). On that date, TTWs 

meeting the definition of “space-constrained products” will become subject to the 12 SEER/7.4 

HSPF energy conservation standard that currently applies to “space-constrained products.” Any 

TTWs that do not satisfy DOE’s definition of space-constrained product, but meet the definition 

of conventional central air conditioners and heat pumps will become subject to the 13 SEER/7.7 

HSPF standard that applies to those products. 10 CFR 430.32(c)(2). In addition, while TTW 

products are primarily installed in replacement applications, DOE’s definition for TTW air 

conditioners and heat pumps does not prevent these products from being installed in new 

construction applications. DOE requests comment on whether the expiration of the TTW product 

classes could result in market shifts and the potential magnitude of these shifts. 

2.2.1.2 Ductless and Variable Refrigerant Flow Split Systems 

During the framework public meeting, interested parties discussed the classification of 

ductless split systems. MEUS stated that ductless mini-splits may warrant a separate product 

class because they are intended for different applications than conventional split systems and 

their cooling capacities are about 12,000 British thermal units per hour (Btu/h). A typical central 

air conditioner system capacity is about 30,000 Btu/h. (MEUS, No. 13 at p. 205) MEUS also 

suggested a separate class for VRF air conditioner and heat pump systems. (MEUS, No. 19 at p. 

2) Like MEUS, Trane recommended that mini-splits be included as an additional product class. 

(Trane, No. 16 at p. 7) Carrier does not support special classes for duct-free splits, multi-splits, or 

VRF products, and AHRI commented that no additional separate product classes are necessary 

for these products. (Carrier, No. 18 at p. 4; AHRI, Public Meeting Transcript, No. 24 at pp. 4, 6). 

Further, Lennox recommends that energy requirements for ductless split systems be set in 

conjunction with other central air conditioners and heat pumps because both types of products 

compete for the same sales and installations. (Lennox, No. 22 at p. 3) 

Like AHRI and Carrier, DOE does not believe ductless or VRF split systems warrant a 

separate product class. Although some mini-split and multi-split systems have capacities as low 

as 12,000 Btu/h, others reach capacities as high as 42,000 Btu/h according to the AHRI 

directory. Also, DOE received comments from other manufacturers similar to Lennox’s during 

development of the test procedure, claiming that ductless split systems compete directly with 

conventional split systems, and not with room air conditioners. For these reasons, DOE does not 

intend to create a separate product class for ductless split systems. In addition, DOE believes 

VRF split systems are a variation of multi-split system products and should be subject to the 

same standard. Therefore, DOE does not plan to develop a separate product class for VRF split 

systems. 

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2.2.1.3 Small-Duct, High-Velocity Systems 

Joint Comment 1 expressed support for a separate product class for SDHV systems. 

(Joint Comment 1, No. 25 at p. 9) Unico also favors a separate product class for SDHV with an 

official minimum standard instead of the current exemption provision. (Unico, No. 13 at p. 170) 

AHRI commented that the original DOE-proposed product classes are appropriate, and no 

additional separate product classes are necessary. (AHRI, Public Meeting Transcript, No. 24 at 

pp. 4, 6) Similarly, Trane asserted that SDHV products should be held to the same standards as 

mainstream products. (Trane, No. 16 at p. 14) 

DOE intends to maintain the existing separate product class for SDHV products. The 

indoor coil section of an SDHV system is compactly designed to facilitate retrofit installation in 

tight spaces, resulting in smaller face area and more rows of tubing than conventional systems. 

The compact fan coil design and small ducts contribute to high static-pressure loss that the 

blower must overcome, requiring greater fan power. Greater energy consumption of the blower 

motors and limited space for installing the fan coils make it more difficult for SDHV systems to 

increase energy efficiency. To mitigate the burden on the blowers, designers reduce the required 

air volume by cooling it more than a conventional air conditioner, which offers enhanced 

humidity removal but increases cost. DOE believes these design constraints (confined 

installation spaces, high pressure drops, and blower motor power) warrant special consideration 

in the analytical and standards-setting process. In addition, DOE believes its definition for 

SDHV products, found in 10 CFR 430.2, is sufficient to prevent any separate standards for these 

products from becoming a “loop hole.” For these reasons, DOE is considering maintaining a 

separate product class for SDHV systems. DOE plans to evaluate whether it is necessary to 

amend the existing energy conservation standards for these products. 

2.2.1.4 Large-Tonnage Products 

Trane commented that because of transportation and installation challenges, DOE should 

consider placing 4- and 5-ton units in a separate product class. (Trane, No. 16 at p. 11) AHRI 

also suggested that a product class for large-tonnage units may be useful. (AHRI, Public Meeting 

Transcript, No. 24 at p. 4, 6) 

DOE believes that the differences between typical 3-ton and large-tonnage units are not 

significant enough to warrant a separate product class. However, DOE will consider expanding 

its analysis to account for these differences. For instance, the LCC analysis could be modified to 

account for costs associated with transportation and installation costs of large-tonnage units. 

DOE requests comment on other methodologies and data to account for the differences between 

the typical 3-ton and large-tonnage products. 

2.2.2 Technology Assessment 

As part of the market and technology assessment, DOE developed a list of technologies 

to consider for improving the efficiency of central air conditioners and heat pumps. DOE 

removed from consideration those technology options whose energy consumption could not be 

adequately measured by the existing DOE test procedure. Then DOE removed technologies that 

do not change or affect the energy efficiency metrics of central air conditioners and heat pumps. 

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Chapter 3 of the preliminary TSD includes the detailed list of all technology options DOE 

identified for further consideration in this rulemaking. 

In the framework document, DOE presented a list of energy-saving technologies 

identified as relevant to residential central air conditioners and heat pumps. For this rulemaking, 

DOE is using an efficiency-level approach for the engineering analysis. As explained in section 

2.4, the efficiency-level approach is performed in terms of product efficiency levels rather than 

design options and particular technologies. DOE has received comments on some of these 

technologies, namely higher efficiency expansion valves, micro-channel heat exchangers, liquidto-suction heat exchangers, flat-tube heat exchangers, high-efficiency defrost mechanisms, and 

evaporative pre-cooled AC systems. For more detail regarding the technology assessment for this 

rulemaking, see chapter 3 of the preliminary TSD. 

2.2.2.1 Higher Efficiency Expansion Valves 

Trane stated that in the case of modulated systems (e.g., variable speed), the range of 

refrigerant flow may be broader than a conventional thermostatic expansion valve (TXV) can 

handle. Trane asserted that, in these cases, an electronic expansion valve (EEV) may facilitate 

refrigerant flow control, but by itself offers no efficiency benefit. (Trane, No. 16 at p. 9) AHRI 

also stated that TXVs and EEVs do not offer any particular efficiency benefits. (AHRI, No. 24 at 

p. 5) 

TXVs are commonly used in central air conditioners and heat pumps rated at efficiency 

levels of 13 SEER or above. TXVs allow for some degree of adjustment of refrigerant expansion 

and may be more efficient than the capillary tube device under varying conditions. The 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, an EEV theoretically allows for increases in energy efficiency under varying conditions. 

DOE understands that while the energy savings may be minimal from a TXV or EEV when 

implemented on its own, they are not negligible. In addition, the energy savings from TXVs and 

EEVs become more obvious when they are implemented with more advanced modulating 

systems. 

2.2.2.2 Micro-Channel Heat Exchangers 

Trane commented that micro-channel heat exchangers offer no efficiency benefit. (Trane, 

No. 16 at pp. 9–10) It stated that micro-channel heat exchangers can be used across the 

efficiency and capacity spectrum, and whether they are employed in any particular design is a 

matter of cost and other product constraints. Trane further asserted that micro-channel heat 

exchangers could be used to remove the space constraint of space-constrained products, which 

should then be subject to the same efficiency standards as mainstream products. AHRI also 

stated that micro-channel heat exchangers do not offer any particular efficiency benefits. (AHRI, 

No. 24 at p. 5) 

In its 2004 Emerging Technologies and Practices Report, ACEEE estimated that microchannel heat exchangers are generally 15 percent more efficient than conventional fin and tube 

exchangers.1

 Compared to current fin-tube heat exchangers, the air passing over a micro-channel 

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heat exchanger has a longer dwell time, increasing both the efficiency and rate of heat transfer. 

This increase in effectiveness allows the micro-channel heat exchanger to be smaller yet perform 

the same as a regular heat exchanger. The smaller size of the micro-channel heat exchanger 

reduces the refrigerant pressure drop, improving compressor performance. Likewise, a microchannel heat exchanger may achieve better performance in the same volume as a conventional 

heat exchanger. Micro-channel heat exchangers are an emerging technology in the residential 

central air conditioner and heat pump industry and manufacturers are still facing some challenges 

with implementing this technology. However, DOE believes that micro-channel heat exchangers 

have the potential to contribute to energy savings. 

2.2.2.3 Liquid-to-Suction Heat Exchangers 

Trane stated that there are no benefits of liquid-to-suction heat exchangers (LSHXs) in 

normal-functioning systems employing the refrigerant R-410A. (Trane, No. 16 at p. 10) AHRI 

agreed that LSHXs do not offer any particular efficiency benefits. (AHRI, No. 24 at p. 5) 

LSHXs are indirect liquid-to-vapor heat transfer devices that evaporate any residual 

liquid refrigerant that remain in evaporator discharge lines, thereby minimizing the risk of liquid 

refrigerant entering the compressor suction. Generally, LSHXs are installed in air conditioners 

and heat pumps for proper system operation and to improve system performance. Refrigerant 

type, operating temperature, ambient conditions, and other factors, however, determine how an 

LSHX will affect the SEER as measured by DOE’s test procedure for residential central air 

conditioners and heat pumps. Because DOE has not found any conclusive evidence of the 

benefits of LSHXs using R-410A refrigerant, DOE plans to remove this technology from further 

consideration in this rulemaking. 

2.2.2.4 Flat-Tube Heat Exchangers 

Both Trane and AHRI commented that flat-tube heat exchangers do not offer any 

efficiency benefits or savings. (Trane, No. 16 at p. 10; AHRI, No. 24 at p. 5) A flat-tube heat 

exchanger is similar to a micro-channel heat exchanger in concept, although it implements a 

different fin design. This technology, however, is under development for central air conditioners 

and heat pumps, and any possible benefits of its implementation are unknown. Therefore, DOE 

plans to remove this technology from consideration in this rulemaking. 

2.2.2.5 High-Efficiency Defrost Mechanisms 

The standard method for defrosting the outdoor coil during the heating operation of a heat 

pump is to reverse refrigerant flow refrigerant temporarily. This requires heat from air inside the 

unit to heat the outdoor coil and melt the frost. In the framework document, DOE listed two 

defrost mechanisms as alternatives to reversing the flow of the refrigerant that may reduce 

energy consumption of the system: frostless heat pumps and hot water defrost. Trane and 

NRACP agreed that frostless heat pumps are turned off at low temperatures. As a result, they are 

not operational during certain tests and do not meet the requirements of the DOE test procedure 

for heating performance. (Trane, No. 16 at p. 10; NRACP, No. 34 at p. 3) 

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DOE is not aware of any frostless heat pumps that turn off at low temperatures. A 

frostless heat pump retards frost formation by increasing the temperature of the outdoor coil via 

added heat to the accumulator. This method of slowing frost accumulation is effective only when 

the ambient temperature is above 32 °F. Frost accumulation cannot be prevented when the 

ambient temperature is below 32 °F and the additional heat is no longer added to the 

accumulator. At temperatures below 32 °F, the frostless heat pump will rely on typical defrost 

methods, but it will still be operational.2

 Therefore, DOE believes that a frostless heat pump can 

still be tested using the DOE test procedure for heating performance. Frostless heat pumps are 

still being developed, however, and potential energy-saving benefits are uncertain when tested 

under the DOE test procedure. Therefore, DOE plans to remove this technology from further 

consideration in this rulemaking. 

Trane also stated that hot water defrost raises issues of freezing. It added that if the 

condensing unit coil is connected to a water system, it would presumably permit water heating in 

cooling mode and would not be rated along with the covered products in this rulemaking. (Trane, 

No. 16 at p.10) 

Hot water defrost systems are still being developed for central heat pumps and any 

potential energy saving benefits from this technology are still uncertain. Therefore, DOE plans to 

remove this technology from consideration in this rulemaking. DOE is unaware of any highefficiency defrost mechanisms used in residential central heat pumps other than frostless heat 

pumps and hot water defrost. As a result, DOE plans to remove high-efficiency defrost 

mechanisms from consideration as a design option in this rulemaking. 

2.2.2.6 Evaporative Pre-Cooled Air-Conditioning Systems 

Energy Solutions stated that if this rulemaking will set regional standards, evaporative 

pre-cooled AC systems should be considered in the western United States. (Energy Solutions, 

Public Meeting Transcript, No. 13 at p. 188) 

An evaporative cooler is a device that cools air by passing it over or through an object 

that is cooled by the evaporation of a liquid. This device is particularly effective in hot-dry 

climates. While the potential exists for an evaporative cooler to be used with a conventional 

central air-conditioning system (i.e., evaporative pre-cooled AC system), DOE is unaware of any 

evaporative pre-cooled AC systems offered as a complete package by a residential central airconditioning manufacturer. DOE believes that an evaporative pre-cooled AC system can only be 

achieved through the use of an evaporative cooler as an after-market product. DOE believes that 

evaporative pre-cooled AC systems are outside the scope of this rulemaking, because the 

rulemaking only addresses newly manufactured products and not the use of after-market 

products. DOE lacks the authority to prescribe a standard that consists of a “design requirement,” 

i.e., requiring the use of an after-market product. (42 U.S.C. 6291(6)(B), 6292(a)(3)) Further, 

generally an energy conservation standard must be either a performance requirement or a design 

requirement, but cannot include both elements. (42 U.S.C. 6291(6))Therefore, DOE will not 

consider evaporative pre-cooled AC systems in its analysis. 

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2.3 SCREENING ANALYSIS 

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

2.2.2 to determine which options to consider further 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 

preliminary rulemaking. Chapter 4 of the preliminary 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 central air conditioner and heat pump 

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. 

2.4 ENGINEERING ANALYSIS 

The engineering analysis (chapter 5 of the preliminary TSD) establishes the relationship 

between the manufacturing production cost and the efficiency for each residential central air 

conditioner and heat pump. This relationship serves as the basis for cost-benefit calculations in 

terms of individual consumers, manufacturers, and the nation. Chapter 5 discusses the product 

classes analyzed, representative baseline units, incremental efficiency levels, methodology used 

to develop manufacturing production costs, cost-efficiency curves, impact of efficiency 

improvements on the considered products, and methodology used to extend the analysis to lowshipment-volume product classes. 

In the engineering analysis, DOE evaluates a range of product efficiency levels and 

associated manufacturing costs. The purpose of the analysis is to estimate the incremental 

product MSPs that would result from increasing efficiency levels above the baseline model in 

each product class. The engineering analysis considers technologies not eliminated in the 

screening analysis. The LCC analysis uses the cost-efficiency relationships developed in the 

engineering analysis. 

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 product being analyzed. 

In the framework document, DOE stated its intention to use an efficiency-level approach 

for the engineering analysis. In an efficiency-level approach, analysis is performed in terms of 

product efficiency levels rather than focusing solely on design options. For each product class, 

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the engineering analysis estimates MPCs at each potential efficiency level. Hence, in the 

framework document, DOE requested industry cost-efficiency and shipment data. 

EEI and Joint Comment 1 supported DOE’s use of the efficiency-level approach to 

determine the relationship between MPC and energy efficiency levels. (EEI, No. 20 at p. 5 and 

Joint Comment 1, No. 25 at p. 10) AHRI and ASAP suggested that DOE review the previous 

central air-conditioning and heat pump engineering analysis because prior cost efficiency curves 

were inaccurate. (AHRI, Public Meeting Transcript, No. 13 at p. 196; ASAP, Public Meeting 

Transcript, No. 13 at p. 197) Although AHRI provided industry shipment data, available data 

does not allow DOE to determine the costs to manufacturers of producing central airconditioning and heat pump products at particular efficiency levels. 

For this rulemaking, DOE performed the engineering analysis using an efficiency-level 

approach that incorporated cost-efficiency data that DOE obtained using the reverse-engineering 

methodology. In the rulemaking that resulted in the 2001 residential central air conditioner and 

heat pump final rule, DOE developed its engineering analysis by (1) conducting three teardowns; 

(2) using information obtained from manufacturer interviews; and (3) using manufacturer data 

submissions, AHRI data submissions, and product literature. Because DOE has not received 

cost-efficiency data during the current rulemaking, and because published product literature now 

provides less detail than at the time of the previous rulemaking, DOE has relied primarily on 

system teardowns to develop cost-efficiency relationships for the current rulemaking. As a result, 

DOE has conducted more teardowns for this rulemaking than the previous rulemaking. This 

involved selecting and disassembling several central air conditioners and heat pumps, creating 

bills of materials, and developing a cost model to estimate the MPC of each unit. DOE has also 

shared its draft cost-efficiency data and assumptions with manufacturers in an attempt to 

calibrate its cost-efficiency curves and will continue to do so throughout this rulemaking process. 

Chapter 5 of the preliminary TSD describes the methodology that DOE used to perform the 

efficiency level analysis and derive the cost-efficiency relationship. 

DOE’s engineering analysis produced cost-efficiency curves for the four primary 

residential central air conditioner and heat pump product classes. The cost-efficiency curves are 

described by the efficiency levels and the increase in MPC above the baseline for each level. The 

split-system air conditioner and heat pump product classes have two different rating methods for 

determining SEER, depending on whether the fan blower is included in the rating. If a system is 

rated as a “coil-only” system, the SEER is calculated using a default fan power. These systems 

are generally representative of a condensing unit and evaporator coil installed with an existing 

furnace. If a system is rated as a “blower-coil” system, the SEER is calculated using a specific 

fan power. In blower-coil systems, which are generally representative of a condensing unit 

installed with an air handler or new construction installations, the outdoor condensing unit, 

evaporator coil, and fan blower can all be modified to achieve higher system efficiencies. 

DOE assumed that coil-only systems and blower-coil systems are both prevalent in the 

split-system air-conditioning market, whereas blower-coil systems dominate the vast majority of 

installations in the split-system heat pump market. Therefore, DOE characterized the splitsystem air conditioner product class by developing separate cost-efficiency curves for coil-only 

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systems and blower-coil systems. DOE characterized the split-system heat pump product class 

using only blower-coil systems. DOE requests comment on the market shares of coil-only and 

blower-coil systems for both split-system air conditioners and split-system heat pumps. DOE 

also requests comment on whether an additional coil-only engineering analysis is necessary to 

characterize split-system heat pumps. 

2.4.1 Baseline Products 

The engineering analysis identifies representative baseline products, which are the 

starting point for estimating the cost of improving the energy efficiency of each product class. 

For this rulemaking, DOE selected as baseline products a model or models—currently offered 

for sale—that meet the existing minimum Federal energy efficiency standards. Chapter 5 of the 

preliminary TSD includes details on the baseline products for each product class. 

2.4.1.1 Representative Capacities 

In the framework document, DOE requested comment on typical baseline units for each 

product class. DOE received several comments on the representative capacities for residential 

central air conditioners and heat pumps. Trane and AHRI recommended that, for split-system 

and single-package air conditioners and heat pumps, DOE use nominal 2-, 3-, and 5-ton units as 

representative capacities. (Trane, No. 16 at p. 12; AHRI, No. 24 at p. 6) Carrier agreed that DOE 

should extend its analysis beyond 3-ton units. (Carrier, No. 18 at p. 6) MEUS commented that 

central air conditioner and heat pump systems should be analyzed at 30,000 Btu/h, mini-splits at 

12,000 Btu/h for one-to-one residential systems, and 24,000 Btu/h for multi-splits and small 

commercial systems. (MEUS, No. 19 at p. 3) 

For the preliminary engineering analysis, DOE used 36,000 Btu/h (i.e., 3-ton) 

cooling/heating capacity systems to develop cost-efficiency relationships for the split-system and 

single-package product classes because the most shipments tend to be around this capacity DOE 

acknowledges, however, that residential central air conditioner and heat pump systems tend to 

reach their optimal efficiency around the 3-ton capacity. For the NOPR, DOE is considering 

performing additional engineering analyses on 2- and 5-ton capacity products to account for 

potential capacity-related impacts. Mini-splits and multi-splits fall under the definition of splitsystem air conditioners and heat pumps, so DOE did not consider separate representative 

capacities for those products. 

2.4.1.2 Refrigerant 

DOE also received comments on the assumed refrigerant used in baseline products. Joint 

Comment 1 stated that adequate consideration of the impact of changing to hydrofluorocarbon 

(HFC) refrigerant requires a new approach to the engineering analysis due to the effects on 

product design and efficiency. (Joint Comment 1, No. 25 at p. 11) 

Because hydrochlorofluorocarbon (HCFC) refrigerants were phased out on January 1, 

2010, DOE based its engineering analysis on products that use HFC refrigerants (i.e., R-410A). 

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2.4.2 Space-Constrained Products 

In the framework document, DOE requested comment on the appropriate levels to 

analyze for space-constrained products. DOE also requested comment on appropriate maximum 

technologically feasible efficiency levels for space-constrained products. NRACP commented 

that increasing the SEER for the space-constrained product classes may not be possible. 

(NRACP, No. 34 at pp. 2, 4) NRACP stated that achieving a higher energy conservation standard 

is not possible with components currently available on the market. Therefore, NRACP 

recommended that SEER requirements for space-constrained products remain unchanged. 

Table 2.1 provides current energy conservation standards for space-constrained central 

air conditioners and heat pumps. 

Table 2.1 Energy Conservation Standards for Space-Constrained Products 

Space-Constrained Product Energy Standard 

Air Conditioner 12 SEER 

Heat Pump 12 SEER/7.4 HSPF 

DOE anticipates that, as of January 23, 2010, space-constrained air 

conditioners and heat pumps will include through-the-wall systems. 

DOE did not perform a full engineering analysis for the preliminary analysis for spaceconstrained products due to limited availability of product data. DOE intends to develop an 

engineering analysis for space-constrained products for the NOPR. DOE requests feedback and 

data on space-constrained products to determine potential areas of energy savings. For additional 

information on space-constrained products and DOE’s methodology for developing an 

engineering analysis for these product classes, see chapter 5 of the preliminary TSD. 

2.5 MARKUPS TO DETERMINE PRODUCT PRICE 

DOE used manufacturer-to-consumer markups to convert the MSPs estimated in the 

engineering analysis to customer prices, which then were used in the LCC, PBP, and 

manufacturer impact analyses. DOE calculates markups for baseline products (baseline markups) 

based on the markups at each step in each distribution channels to obtain the consumer purchase 

price for the baseline products sold through each channel. DOE similarly calculates incremental 

markups that relate the change in the manufacturer sales price of higher efficiency models (the 

incremental cost increase) to the change in the contractor sales price. 

To develop markups, DOE must identify how the products are distributed from the 

manufacturer to the customer (the distribution channels). After establishing appropriate 

distribution channels for each product class, DOE used economic data from the U.S. Census 

Bureau, HARDI, ACCA, and other sources to define how prices are marked up as the products 

pass from manufacturers to customers. 

2.5.1 Distribution Channel Structure 

Analysis of distribution markups for central air conditioners and heat pumps focused on 

two distribution channels, with markups calculated at specific points along those paths. The 

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distribution channel differs for new construction or replacement applications (the latter include 

sales to existing buildings that do not already have a residential central air conditioners and heat 

pumps). For new construction applications, the manufacturer typically sells the product to a 

wholesaler-distributor, who sells it to a mechanical contractor, who sells it to a general 

contractor. Each of these latter three entities adds a markup or fee to its purchase price before 

selling the product. DOE understands that virtually all central air conditioners and heat pumps 

installed in new construction follow this distribution channel. For replacement applications, the 

distribution channel is essentially the same, except that there is no general contractor markup. 

In the framework document, DOE proposed the two distribution channels just described, 

as well as a third (manufacturer to large retailer to consumer). While MEUS concurred (MEUS, 

No. 19 at p. 4), DOE received multiple recommendations to combine the three models. HARDI 

suggested one distribution channel with a consistent distribution role. HARDI and CFM 

Distributors, Inc. (CFM) commented that upon understanding the distribution model, DOE 

would need only the distribution channel model to provide more accurate costs. (HARDI, No. 32 

at p. 2; CFM, No. 13 at p. 287) HARDI, CFM, and ACCA all commented that the third channel 

is nonexistent. (HARDI, No. 32 at p. 2; CFM, No. 13 at p. 287; ACCA, No. 23 at p. 5) Other 

manufacturers agreed that a single distribution channel would suffice for the analysis. (Trane, 

No. 16 at p. 18; Carrier, No. 18 at p. 9; Lennox, No. 22 at p. 3; ARI, No. 24 at p. 9) ACEEE 

commented that DOE’s proposal missed two distribution channels: a dealer-direct model 

(merging manufacturing and distribution) and the import model. ACEEE also noted that any 

retail price survey is difficult to use because of the way different contractors price the markup on 

the product versus installation. (ACEEE, No. 13 at p. 293) ACEEE suggested that DOE examine 

manufacturer costs and free on board prices (which are equivalent to DOE’s MSP) in 

conjunction with surveyed retail prices to address regional questions. 

DOE simplified the distribution channels to only two channels, based on industry 

comments. HARDI and the manufacturers’ comments imply that a manufacturer that performs 

its own distribution functions still incurs and charges for those functions. Distribution charges 

would also have to be added in the case of imports. This results in a similar retail price to that in 

a situation of a manufacturer that sells into a separate retail distribution process. There is no need 

to distinguish between these two methods of distribution for calculation of markups. 

While DOE recognizes that the theoretical value in using a valid retail price survey 

directly would avoid the complications associated with calculating individual retail channel 

markups, DOE agrees with ACEEE’s position that a retail price survey is difficult to administer 

and interpret in this market because of the way contractors price their goods and services 

together. Also, current surveyed prices (even if readily available) for high-efficiency products 

today would reflect prices of premium products, not necessarily minimally-compliant products 

under higher standards. 

Based on the comments DOE received in response to the framework document and 

follow-up discussions, DOE determined that distribution channels for new construction units and 

replacement units should be used to develop distribution channel markups. 

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Figure 2.1 shows these two distribution channels. Chapter 6 of the preliminary TSD 

provides further descriptions of these channels and details on the fraction of shipments passing 

through each channel. 

New Construction Units: Manufacturer→Distributor→Mechanical Contractor→General 

Contractor→Customer 

Replacement Units: Manufacturer→Distributor→Mechanical Contractor→Customer 

Figure 2.1 Distribution Channels for Central Air Conditioners and Heat Pumps 

DOE will continue to seek data concerning the prevalence of different distribution 

channels, but two channels appear to satisfy the need for estimating representative percentage 

markups. DOE will index differences in contractor costs and sales tax as two significant 

variations. 

2.5.2	 Data Sources for Distribution Channel Markups 

DOE relied on economic data from the U.S. Census Bureau, HARDI, ACCA, and other 

sources to define how prices are marked up as products pass from manufacturers to consumers. 

DOE based the wholesaler and mechanical contractor markups on company balance-sheet data; 

DOE based the general contractor markups on U.S. Census Bureau data for the commercial and 

institutional building construction industry. HARDI and ACCA are trade associations 

representing wholesalers and mechanical contractors, respectively. DOE obtained the company 

balance sheets from the HARDI 2008 Profit Planning Report and ACCA.3,4 DOE used financial 

data from the 2002 U.S. Census Bureau for developing general contractor markups in the same 

form as the balance sheet data for wholesalers and mechanical contractors.5 These balance sheets 

delineate the components of all costs incurred by firms that supply and install air-conditioning 

products. Wholesalers and mechanical contractors to which these reports refer handle multiple 

commodity lines, including residential central air conditioners and heat pumps as well as warmair furnaces. DOE used three key assumptions to estimate markups with these financial data: 

(1)	 The balance sheets accurately represent the various average costs incurred by 

firms distributing and installing air-conditioning and heating products. 

(2)	 These costs can be divided into two categories: (a) costs that vary in proportion to 

the MSP of the air-conditioning and heating products (variable costs), and (b) 

costs that do not vary with the MSP of air-conditioning or heating products (fixed 

costs). 

(3)	 Wholesaler and contractor prices vary in proportion to the wholesaler and 

contractor costs included in the balance sheets. 

DOE seeks summary data of distribution margins to serve as a baseline for distributor 

markups on HVAC products, or other relevant products, to supplement or replace the published 

data. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

2.5.3 Markups/Price Determination 

DOE received comments on its methods for estimating retail prices for higher efficiency 

central air conditioners and heat pumps. CFM argued that in building a retail price by adding 

distribution channel markups to MSP, DOE must have a full understanding of the market impact 

analysis or DOE will not obtain an accurate idea of the price, and the LCC and PBP analyses will 

be flawed. (CFM, No. 13 at p. 294) CFM also expressed concern about overlooking the cost of 

changes in the standards and product offerings and indicated that the cost of these items would 

have an effect of the overall markup (presumably because of increased inventory carrying cost). 

(CFM, No. 13 at p. 34) It is unclear whether the proposed efficiency standards would materially 

affect inventory turnover rate among elements of the distribution channels or significantly affect 

operation costs, whether the costs could be passed on to customers, and what the resulting 

impacts on markups would be. DOE will search for data to determine such relationships. Unless 

it finds data sources indicating the impact of standards on markups, DOE would not have a basis 

to make an adjustment in the markups during the preliminary analysis. 

HARDI and Trane commented that the cost estimates DOE used in developing the 2001 

residential central air conditioner and heat pump final rule were grossly understated and failed to 

account for the significant costs of getting HVAC products from the point of manufacture to the 

point of proper installation. They stated that a simpler approach would be to use retail prices of 

complete systems at various sizes and SEER levels. (HARDI, No. 32 at p. 3; ARI, No. 24 at p. 5; 

Trane, No. 16 at p. 12) While DOE agrees, in principal, that selecting product prices from a 

database of accurately reported retail prices for complete systems at various efficiency levels 

might be an easier way to get pricing information, DOE knows of no such database and did not 

receive any price data. It is also unclear that such a database would reflect prices that customers 

would pay under different efficiency standard scenarios. Without appropriate retail price data, 

DOE will continue to estimate the retail price using markups in the distribution channel. DOE 

has modified its approach to markups to explicitly include transportation costs, which were 

omitted in 2001 (and which account for effects of product weight on cost). 

HARDI provided two specific comments on the values for markups used in the analysis 

on which DOE based the 2001 residential central air conditioner and heat pump final rule. First, 

HARDI stated that gross margins must be higher on the more efficient systems, not lower as 

previously assumed. (HARDI, No. 32 at p. 3) Second, in assessing current and future product 

prices, HARDI urged DOE to perform a realistic analysis based on recent material price trends. 

(AHRI, No. 24 at p. 4) DOE has included in its estimate of retail price, transportation costs that 

increase with product size, and will increase the price associated with higher efficiency products. 

DOE already captures recent material price increases in the manufacturer costs and will consider 

whether and how best to forecast material prices. 

2.6 ENERGY USE CHARACTERIZATION 

The energy use characterization assesses the energy savings potential from adopting 

higher efficiency standards. The characterization provides the basis for the energy savings values 

DOE uses in the LCC and subsequent analyses. DOE calculated the energy savings for four 

classes of central air conditioner or heat pump products (split-system air conditioners, singlepackage air conditioners, split-system heat pumps, and single-package heat pumps) compared 

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with a base case that included an estimate of the distribution of efficiencies in 2016 by product 

class. DOE considered energy use for both residential and commercial users of these products. 

DOE used data from the 2005 Residential Energy Consumption Survey (RECS) produced 

by the Energy Information Administration (EIA), the most recent survey available, to estimate 

cooling energy use for homes using central air conditioner products, and cooling and heating 

energy use for homes using central heat pump products, with efficiencies representative of those 

in the current stock. DOE used 30 years of state weather data statistics from the National 

Climatic Data Center to weather-normalize the 2005 RECS cooling and heating energy use in 

selected household records to represent long-term average cooling and heating energy. DOE 

assumed that each RECS household had an efficiency equivalent to the average shipped 

efficiency for the vintage central air conditioners or heat pumps identified in RECS, based on 

historical AHRI efficiency data. 

To develop estimates for the DOE base-case energy use for 2016 (the first year for new 

standards), DOE used an estimate of the efficiency distribution in 2016 by product class to select 

for each RECS observation an efficiency level (SEER for air conditioners and HSPF for heat 

pumps) that might be purchased in that year in the absence of new standards. This distribution 

reflects products SEER 13 or higher. DOE then multiplied the weather-normalized cooling 

energy for the RECS household by the ratio of the historical average SEER to the 2016 SEER 

value selected for that record in the base case. Similarly, DOE multiplied the weather-normalized 

heating energy for the RECS household with central heat pumps by the ratio of the vintage-based 

HSPF to the 2016 HSPF value selected for that record in the base case. 

The result of these calculations, carried out over all the selected RECS household records 

and using the RECS sample weights, is an estimated distribution of annual cooling and, for heat 

pumps, heating energy use for residential households. This distribution is provided separately for 

each climate region and represents the DOE 2016 base case. DOE also used the same RECS 

observations and similar ratio techniques to estimate the energy use for each RECS household 

under a higher SEER/HSPF standard, if adopted. DOE uses the difference between the energy 

use for each household in the base case and the standards case to calculate the energy savings for 

that household for each standard level considered. 

DOE also developed estimates of energy use for central air conditioners and heat pumps 

that might be installed in commercial applications. DOE estimated that approximately 7 percent 

of the central air conditioner or heat pump market is actually in commercial buildings. To 

develop the commercial estimates, DOE used the EnergyPlus building energy simulation tool to 

model the energy use of central air conditioners and heat pumps in a single small office building 

served by these products for 238 locations (based on 238 Typical Meteorological Year (TMY2) 

locations). DOE modeled four efficiency levels for central air conditioners and four for heat 

pumps (from 13 SEER to the max-tech level) and extracted the annual cooling, heating, and fan 

energy, as well as the total building cooling capacity, from each simulation at each efficiency 

level. Using the total cooling capacity from each simulation, DOE normalized the simulation 

cooling, heating, and fan energy to that expected for a 3-ton cooling unit. DOE then used 

interpolation to develop annual cooling and, for heat pumps, heating energy by climate at 

intermediate efficiency levels between the baseline level and max-tech level. Annual supply fan 

energy was also calculated and (for the purpose of this analysis) allocated to the cooling or 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

heating energy for the simulation based on relative energy cooling and heating energy use 

respectively. DOE used estimates for the fraction of the U.S. population best represented by each 

TMY2 climate to provide weighting factors for the energy results by climate. As with the 

residential energy use characterization, DOE selected locations at random (based on location 

weighting factors), and a 2016 base-case efficiency level (based on the estimated efficiency 

distribution for shipments) for the corresponding LCC analysis. The result is a distribution of 

commercial energy use within each climate region analyzed in the base case. DOE also used the 

same commercial building simulation data and interpolation techniques described to estimate 

energy use for each commercial observation for scenarios in which DOE mandated a higher 

SEER/HSPF standard level. 

In the corresponding LCC analysis, DOE used the RECS household and commercial 

weights assigned to each TMY2 in conjunction with the 7-percent split between commercial and 

residential customers to select observations in a Monte Carlo analysis to estimate the distribution 

of base-case energy use in each DOE climate region. In addition, DOE developed the energy use 

for each household or commercial observation selected for higher efficiency levels 

corresponding to possible standard levels. The difference in the resulting distribution of energy 

use in the base case—and that in each standards case for each climate region—is the energy 

savings from higher standards. Note that in some cases the selected efficiency for a single 

observation in the base case is higher than the standards case being considered. In those 

instances, no energy savings are calculated for the observation. 

As part of the characterization, DOE made certain implicit assumptions about product 

application, including how the products are operated and under what conditions. Those 

assumptions are documented in chapter 7 of the preliminary TSD, which also provides more 

detail about DOE’s approach. 

During the framework review process, DOE received comments on various segments of 

the proposed analysis. 

2.6.1 Residential Energy Use analysis 

2.6.1.1 Use of RECS Data as Basis of Residential Energy Consumption 

DOE based its estimate of the annual space cooling energy consumption of the stock of 

installed central air conditioners and heat pumps on data from the 2005 RECS. For each 

household with a central air conditioner or heat pump, RECS estimates the product’s annual 

energy consumption from the household’s utility bills. The estimated annual energy consumption 

in RECS corresponds to the unit installed in the household, specifically its capacity and 

efficiency. 

In the framework document, DOE stated that it would use the latest available RECS data 

in the analysis. The latest available RECS data at the time of the public meeting on the 

framework document (June 12, 2008) was from 2001. CFM asserted that using 2001 data in 

2008-2009 is inadequate. (CFM, No. 13 at p. 269) Trane and AHRI also expressed reservations 

about using RECS data. (Trane, No. 16 at p. 16; ARI, No. 24 at p. 7) They contended that the 

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EERE-2008-BT-STD-0006 COMMENT 54
vintage of the baseline stock in 2016 would be different from the vintage of the products of even 

RECS 2005 households and would consequently lead to overestimation of the energy savings. 

DOE uses the latest and most practical available data for its analysis. At the time of the 

public meeting, only the 2001 RECS was available. The 2005 RECS data became available while 

DOE was developing the preliminary analysis, and DOE used this more recent data. In the 

current analysis, DOE uses RECS heating and cooling energy use as a starting point to project 

baseline energy use in 2016 but accounts for the difference between the 10 SEER standard (the 

basis of the product stock in the 2005 RECS) and the 13 SEER standard (the basis of the default 

base-case purchases in 2016). This is done in the LCC baseline by scaling the energy use in the 

2005 RECS by the ratio of (1) the average SEER (or HSPF) of the vintages of the product stock 

in the 2005 RECS, to (2) the SEER (or HSPF) of projected products purchased in 2016 (under 

the current SEER 13 standard). 

2.6.1.2 Use of RECS Data Not in the Public Domain 

Trane asked if DOE has access to RECS, Commercial Building Energy Consumption 

Survey (CBECS), and American housing survey data more detailed than what is publically 

available. (Trane, No. 13 at pp. 270, 284) All of the 2005 RECS data DOE used in its analysis of 

energy use is publicly available. In developing electricity price data for residential central airconditioning and heat pump applications, however, DOE made limited use of non-publically 

available data stemming from the 2001 RECS to allocate annual energy savings across months. 

DOE used this same information in the 2001 residential central air conditioner and heat pump 

rulemaking and believes that it is an important element of the analysis. For the current analysis, 

DOE’s use of this data is based on statistics from the data used in the 2001 rulemaking. DOE 

will make the statistics available for parties interested in assessing this electricity price data. 

2.6.2 Impact of Improved Building Codes 

The impact of improved building codes is a factor that potentially could impact central air 

conditioner and heat pump energy use and product sizing. Trane expressed that one of DOE’s 

national labs, Pacific Northwest National Laboratory (PNNL), is a center of code development 

for residential buildings, and asked if PNNL could come up with reasonable estimates for the 

changes in cooling or heating loads in new construction. (Trane, No. 13 at p. 278) HARDI noted 

that improved building codes lead to smaller sized products and that properly installed and 

appropriately sized products might save more energy that improperly installed and oversized 

high SEER products. (HARDI, No. 32 at p. 5 and No. 13 at p. 279) Southern suggested that 

comparing energy consumption of a well insulated building with an old, inefficient building may 

be instructive. (Southern, No. 13 at p. 279) 

Building codes may affect cooling and heating loads in homes but DOE has not 

incorporated the impact of revised codes into the preliminary analysis due to the difficulty of 

projecting energy use and product sizing under potential new code scenarios. Even as building 

codes have improved design, residential buildings have increased in size, which compensates for 

(and in some cases may overwhelm) any load reductions due to more efficient design. In 

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EERE-2008-BT-STD-0006 COMMENT 54
 

response to HARDI’s comment, DOE agrees that there are likely significant energy savings from 

quality installation and correct sizing; however, these savings would also occur with high SEER 

products. DOE acknowledges that greater care in sizing could, by reducing first costs, serve to 

make high SEER products even more cost effective. 

2.6.3 Inclusion of Commercial Energy Use Analysis 

In the framework document, DOE proposed developing building simulations for a single 

small office prototype building to extract energy savings statistics for higher efficiency central 

air conditioner and heat pump products. In response, Carrier commented that a small office 

building would be the best choice. (Carrier, No. 18 at p. 9) Consequently, DOE opted for using a 

small office prototype for developing commercial energy consumption statistics. Trane asked if 

DOE had access to more detailed data from RECS or CBECS than is available publically. 

(Trane, No. 13 at pp. 270, 284). DOE responded that it does not have ready access to such data 

and has not used any finer resolution data for the energy analysis. 

2.6.3.1	 Fraction of Shipments of Central Air Conditioners and Heat Pumps for 

Commercial Applications 

The preliminary analysis is based on a fixed percentage of product shipments used in 

commercial buildings. Comments from the 2001 residential central air conditioner and heat 

pump rulemaking requested that DOE set this fraction at 10 percent. For this rulemaking, DOE 

requested fresh inputs from interested parties about changes to this fraction based on industry 

statistics. Figures ranged widely, from 3 to 5 percent (Carrier, No. 18 at p. 8), to 7.5 percent 

(AHRI, No. 24 at p. 8; Trane, No. 16 at p. 17), to 10 to 20 percent. (ACCA, No. 23 at p. 4) Other 

responses provided estimates that differed across the product subclasses. Trane indicated that the 

share of shipments to the commercial segment is higher for packaged systems than for split 

systems and could be different for other product subclasses (e.g., package systems with 

gas/electric strip heat not covered in this analysis). (Trane, No. 13 at p. 283) MEUS commented 

that the share of the shipments to the commercial segment could be 25 percent for conventional 

single-package systems, 10 percent for conventional split systems, and 30 to 35 percent for 

ductless split systems. (MEUS, No. 19 at p. 4) 

For the preliminary analysis, DOE set the fraction of central air conditioner and heat 

pump systems (all single phase systems) shipped to commercial buildings at 7 percent. DOE 

based this percentage on industry estimates provided in the framework document as well as 

separate comments made from AHRI to the U.S. Environmental Protection Agency (EPA) 

during the development of revised ENERGY STAR levels for central air conditioners and heat 

pumps.a

 DOE acknowledges variation among the product classes in commercial building 

installations, but has no detailed data on which to base an individual class assessment for such 

installations. DOE requests comments on the fraction of covered products that are shipped to 

commercial buildings. 

2.6.4 Use of Rated Performance versus Degraded Performance 

a

 Stakeholder comments on ENERGY STAR spefications for central air conditioners and heat pumps can be found 

at http://www.energystar.gov/index.cfm?c=archives.ac_ashp_spec. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Degradation of central air conditioner and heat pump performance over their service life 

is a concern. Southern observed that DOE’s analysis assumed no degradation of performance 

during product lifetimes. (Southern, No. 13 at p. 275) AHRI remarked that if DOE considered 

degradation of performance for the higher SEER products, DOE should consider the same for 

base stock. (AHRI, No. 13 at p. 276) In DOE’s analysis, no degradation of performance of the 

central air conditioner systems is assumed either for the base or test case scenarios, thus making 

consistent the differences among the energy consumption estimates. DOE is unaware of any 

statistically significant scientific study on this issue that could be factored into the analysis; 

therefore, DOE used non-degraded efficiencies in its analysis. 

2.6.5 Characterization of Energy Using SEER/HSPF 

Several commenters questioned SEER’s validity and usefulness as the only energy 

efficiency metric. ACEEE stated that the actual energy used at high temperature bin hours is 

higher than the SEER test procedure captures. (ACEEE, No. 13 at p. 272) Joint Comment 1 

stated that as a driver of product development, SEER fails to encourage adequate 

dehumidification under part load conditions (relevant to the southeastern United States) and it 

does not adequately address the need for higher efficiency at higher outdoor temperatures (a 

concern for the southwestern region). (Joint Comment 1, No. 25 at p. 6) Joint Comment 1 

expressed that EER is an essential parameter and should be used in conjunction with the SEER. 

A joint comment from the Northeast Energy Efficiency Partnerships (NEEP), the Connecticut 

Office of Policy and Management, the New Hampshire Office of Energy and Planning, 

Efficiency Maine, and the Department of Energy Resources (hereafter “Joint Comment 4”) and a 

comment from EEI expressed a similar view. (Joint Comment 4, No. 37 at p. 2; EEI, No. 13 at p. 

47) Sempra Energy (Sempra) stated that it supports use of the EER metric for properly 

measuring performance during peak usage. (Sempra, No. 13 at p. 49) 

EPCA’s definition of “efficiency descriptor” at 42 U.S.C. 6291(22) provides that the 

efficiency descriptor for both central air conditioner and heat pump systems is to be expressed in 

terms of SEER. Consequently, DOE’s analysis did not consider the use of EER as an additional 

or alternate descriptor. 

2.6.6 Development of Regions for Regional Standard Analysis 

Section 306 of EISA 2007 amended EPCA to authorize DOE to establish a national base 

level standard and one or two regional standards for central air conditioners and heat pumps, and 

stipulates that the geographical basis for defining the regions must meet certain specific 

conditions. (42 U.S.C. 6295(o)(6)) In the framework document, DOE sought input from 

interested parties on criteria for determining the regions to which the regional standards could 

apply. DOE received multiple comments on this issue. 

Several comments favored setting regional standards. The Pacific Gas and Electric 

Company (PG&E), Southern California Edison (SCE), Sempra Energy Utilities (Southern 

California Gas Company and San Diego Gas and Electric Company) (Sempra), Sacramento 

Municipal Utility District (SMUD), the Nevada Power Company (NPC), and Sierra Pacific 

Power (SPP) submitted a joint comment (hereafter “Joint Comment 2”) concerning the use of 

regional standards. Joint Comment 2 asserted that, because of national climactic variations, 

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EERE-2008-BT-STD-0006 COMMENT 54
regional standards are necessary and would benefit customers, increase grid reliability, and 

reduce environmental impacts with minimal negative effects on manufacturers, distributors, and 

contractors. (Joint Comment 2, No. 30 at p. 2) PG&E and Sempra stated that they support 

regional standards, emphasizing California’s need for a hot-dry climate air conditioner standard 

to meet energy efficiency goals. (PG&E, No. 13 at p. 45; Sempra, No. 13 at p. 49) Ice Energy 

stated that incorporating regional climate factors and time-dependent parameters in the standards 

would encourage deployment of more efficient cooling systems. (Ice Energy, No. 33 at p. 1) 

Southern claimed that if the statutory provisions allowed for a second metric like latent capacity, 

regional standards could address the challenge of adequate dehumidification in hot-humid 

climates. (Southern, No. 13 at p. 43) NRECA and the Florida Solar Energy Center (FSEC) want 

economic analysis for different climate zones using appropriate costs. (NRECA, No. 35 at p. 1; 

FSEC, No. 31 at p. 2) 

Some commenters expressed reservations on the merits of setting regional standards. 

Trane observed that some assertions supporting regional standards are inconsistent with the facts. 

(Trane, No. 13 at p. 62) For example, Trane noted that air conditioners have a remarkable ability 

to adjust automatically and thermodynamically in response to the load, providing higher latent 

capacity with high latent load or no latent capacity when indoor relative humidity is low. CFM 

expressed that regional standards are unrealistic because climate zones are not aligned with state 

borders; a better way to address the issue would be to find what meets the specific needs of the 

hot-dry and hot-humid regions. (CFM, No. 13 at pp. 34, 399) Lennox stated that regional 

standards should be applied to central air conditioners and heat pumps only if DOE is certain that 

the standards will deliver the savings and payback forecast projected in the analysis. (Lennox, 

No. 22 at p. 3) 

ACEEE urged completion of the preliminary economic analysis of regional standards 

before the discussion of enforcement issues. (ACEEE, No. 13 at p. 400) Southern, MEUS, 

ACEEE, and Sempra suggested holding further collaborative meetings to discuss criteria for 

defining the regions. (Southern, No. 13 at p. 391; MEUS, No. 13 at p. 396; ACEEE, No. 13 at p. 

400; Sempra, No. 13 at p. 402) 

DOE considered these comments and will conduct a regional-level detailed economic 

analysis as provided for under EPCA, as amended by EISA 2007. Consequently, DOE studied 

options from the various criteria. Several comments presented alternative criteria for defining 

regions to which different performance standards may apply. Trane suggested that the regions be 

defined according to heating degree days (HDDs) and cooling degree day (CDDs), while AHRI 

stated that the defining criteria should be cooling load hours. (Trane, No. 16 at p. 4 and No. 13 at 

p. 393; AHRI No. 24 at p. 3) Carrier urged DOE to evaluate uniform north/south regions to 

harmonize the heating and cooling standards. (Carrier, No. 18 at p. 2) MEUS suggested using the 

present ASHRAE climate zones but aggregating the eight climate zones into three regions: 1 and 

2; 3 and 4; and 6, 7 and 8. (MEUS, No. 19 at p. 1) CFM commented that while regional 

standards seem positive, climate does not adhere to state lines. (CFM, No. 13 at p. 34) 

NYC and CEC suggested that DOE evaluate regional standards for hot-humid conditions 

in the southeast, hot-dry in the west, and temperate in the north. (NYC, No. 17 at p. 3; CEC, No. 

27 at p. 2) Joint Comment 2 suggested defining three standards: a base national standard, a 

standard for the hot-dry climate, and a standard for the hot-humid climate. (Joint Comment 2, 

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EERE-2008-BT-STD-0006 COMMENT 54
No. 30 at pp. 1, 20) Joint Comment 1 stated that the two regions most appropriate for regional 

standards are the west/southwest (representing a hot-dry climate) and the southeast (representing 

a hot-humid climate). (Joint Comment 1, No. 25 at p. 8) Joint Comment 1 suggested using 

available state-level population-weighted CDD and humidity data as criteria for including states 

in the hot-dry climate region. Joint Comment 1 also suggested an alternative using the latest 

TMY3 data to select contiguous states in which the population-weighted bin-hour distribution is 

systematically hotter and drier than the national average. (Joint Comment 1, No. 25 at pp. 8–9) 

FSEC suggested using the TMY3 dataset and supports a regional standard for the hot-humid 

region. (FSEC, No. 31 at pp. 1–2) Joint Comment 2 suggested developing a hot-dry SEER that 

could be used as a metric for rating the central air conditioner units in this region. (Joint 

Comment 2, No. 30 at pp. 1, 20) 

ACCA said that while EISA 2007 requires that any regional standard be applied to the 

entire state, few states could be associated with a single region based on CDD, cooling load 

hours, or other climate criteria. (ACCA, No. 23 at p. 2) Trane observed that few census divisions 

could be used for defining the boundaries of the regions over the 50 states. (Trane, No. 13 at p. 

350) Trane further contended that while the total cooling capacity of an air conditioner depends 

on the outdoor dry-bulb temperature and the indoor wet-bulb temperature, the latent/sensible 

split depends primarily on the indoor conditions. Since neither the total capacity nor the latent 

split depends on the outdoor relative humidity, it could not be used as a valid parameter to 

distinguish between the hot-dry and hot-humid zones. (Trane, No. 16 at p. 4) 

Joint Comment 1 suggested that DOE compare results of two parallel analyses: one with 

a single national standard and one with up to three regions (hot-dry, hot-humid, and average). 

Joint Comment 1 asserted that although a national increase in the efficiency standard could be 

cost effective, it might not achieve maximum cost-effective energy savings, ensure adequate 

dehumidification or peak load control, or provide manufacturers the best possible routes for 

profitable product differentiation. (Joint Comment 1, No. 25 at p. 3) 

Some comments suggested coordinating the current rulemaking process for central air 

conditioners and heat pumps with other residential products. EEI urged DOE to begin a new 

rulemaking process for the residential central furnaces and boilers to avoid simultaneous 

existence of regional standards for central air conditioners and heat pumps and a single national 

standard for residential heating products. (EEI, No. 20 at p. 2) NRECA advocated quickly 

implementing the central air conditioner and heat pump standards, updating the furnace and 

boiler standards, and ensuring that both have the same effective dates. (NRECA, No. 35 at p. 2) 

AHRI and Trane do not believe that DOE has the authority to establish regional heating 

standards for heat pumps. (AHRI, No. 24 at p. 4; Trane, No. 16 at p. 4) DOE believes that 42 

U.S.C. 6295(o)(6) and other related provisions of EPCA provide authority to set regional 

standards for heat pumps. DOE seeks comment on whether a national standard or regional 

standards would be appropriate for heat pumps. 

Several commenters also expressed a need for harmonization of the central air 

conditioner and heat pump standards with future standards for furnaces and boilers. (Carrier, No. 

18 at p. 2; EEI, No. 20 at p. 2; NRECA, No. 35 at p. 2) DOE examined various alternative 

criteria for establishing regions for analysis. The current calculations for the labeling of central 

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EERE-2008-BT-STD-0006 COMMENT 54
 

air conditioner cooling energy use are based on 1,000 cooling load hours, a representative 

national average condition. Consequently, DOE proposed for the preliminary analysis that states 

with greater than approximately 1,000–1,100 cooling load hours be included in a “hot” region 

(shown in the cooling hour map in the DOE test procedure). 10 CFR part 430, subpart B, 

appendix M. DOE considered where populations are centered in the western states, as well as 

state and regional CDD data. 

As DOE proceeded with the preliminary analysis for regional standards, the furnace and 

boiler final rule from November 2007 (72 FR 65136-65170) was remanded to DOE for 

reconsideration.6 This rule set standards for residential furnaces and boilers. The LCC subgroup 

analysis performed to support the furnace and boiler rule indicated that positive benefits could be 

derived if a higher efficiency condensing gas-fired furnace is used in the northern regions of the 

country. However, before EISA 2007 amended EPCA, DOE could set only a single national 

standard and therefore, the 2007 furnace and boiler rule was based on a single standard. 

However, EISA 2007 authorized DOE to establish one additional regional standard for the gasfired furnaces and consequently DOE was required by the Second Circuit Court to investigate 

regional standards for the furnace and boiler rule. 

DOE believes that a unified regional definition for both central air conditioners/heat 

pumps and furnaces would have several key benefits, although EISA 2007 does not require a 

coordinated approach for defining the regions: 

•	 Because similar manufacturers produce furnaces and central air conditioners/heat pumps 

and the same distribution network is used for both types of products, a unified regional 

definition would be easier for manufacturers and distributors to implement. 

•	 A unified boundary would likely result in only one product type (furnace or central air 

conditioner/heat pump) being subject to a higher efficiency regional standard in any 

given region. Since these appliances are commonly the most expensive appliances 

purchased in a home, the requirement of high-efficiency units for both types of products 

could have a large first-cost impact on consumers. 

•	 Regional standards may shift enforcement from the manufacturer to consumer point-ofsale and to installation. A single unified north-south boundary will simplify enforcement 

for both product types. There will be less possible combinations of furnaces and air 

conditioners, less motivation for non-compliance as the price differential between the 

base-case options on either side of a regional boundary are lower. 

Upon further examination, DOE realized that the hot-humid and hot-dry regions being 

considered in this rulemaking corresponded to states with less than 4,500 HDD65 (heating 

degree days base 65 o F), and that this 4,500 HDD65 boundary is close to the 5,000 HDD65 

boundary already analyzed in the furnace-rule sensitivity study. DOE examined individual states 

with an average HDD65 between 4,500 and 5,000, and tentatively concluded that they would 

benefit more from higher furnace standards than higher air conditioner standards. Consequently, 

DOE is considering a regional boundary that corresponds roughly to 4,500 HDD65 so that states 

with 4,500 or more heating degree days form the northern region, to which the baseline national 

standard developed in this rulemaking would be applicable. The remaining states would form the 

southern region, where two regional central air conditioner standards (eastern hot-humid and the 

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western hot-dry) would be developed. Chapter 7 of this preliminary TSD discusses the 

development of analysis regions. 

2.7 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSES 

The effect of amended standards on individual customers usually includes a reduction in 

operating cost and an increase in purchase cost, which together determine the economic impact 

of standards on individual customers. This chapter describes the following two metrics, which 

DOE used in the analysis to measure this impact: 

•	 LCC is the total customer cost of an appliance or product, generally over the life of the 

appliance or product, including purchase and operating costs. The latter consist of 

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

of purchase and summed over the lifetime of the appliance or product. 

•	 PBP measures the amount of time it takes customers to recover the assumed higher 

purchase price of a more energy-efficient product through reduced operating costs. 

New or amended energy conservation standards typically affect product operating 

expenses and purchase prices. DOE evaluated the net LCC to analyze the net effect of amended 

central air conditioner and heat pump standards on consumers. DOE used the cost-efficiency 

relationship derived from the engineering analysis, along with the energy costs derived from the 

energy use characterization. Inputs to the LCC calculation include the installed consumer cost of 

a product (consumer purchase price plus installation cost), operating expenses (energy, repair, 

and maintenance costs), the lifetime of the unit, and a discount rate. 

Because the installed cost of a product typically increases while operating cost typically 

decreases in response to amended standards, there is a time in the life of products with higherthan-baseline efficiency when the net reduction in operating costs (in dollars) since the time of 

purchase is equal to the increase in the purchase price of the higher efficiency product. The 

length of time required for products to reach this cost-equivalence point is known as the PBP. 

DOE conducted the LCC and PBP analyses using typical values to reflect energy 

consumption in the field. DOE identified several input values for estimating the LCC, including 

retail prices; electricity prices; discount rate; maintenance, repair, and installation costs; and 

product lifetimes. 

DOE developed discount rates from estimates of the interest rate (finance cost) applied to 

residential product purchases. Following accepted principles of financial theory, the finance cost 

of raising funds to purchase such products can be interpreted as either (1) the financial cost of 

any debt incurred to purchase products (interest charges on debt), or (2) the opportunity cost of 

any equity used to purchase products (interest earnings on household or business equity). 

The LCC and PBP model was developed using Microsoft Excel spreadsheets combined 

with Crystal Ball, a commercially available add-in. The LCC and PBP analyses explicitly model 

the uncertainty and variability in the model’s inputs using Monte Carlo simulation and 

probability distributions. 

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The LCC analysis estimated energy use for each central air conditioner or heat pump unit 

as described in chapter 7 of the preliminary TSD. Energy use of central air conditioners and heat 

pumps is sensitive to climate, so it varies by location. An important feature of the LCC and PBP 

analyses is that it has been conducted at both the regional and national levels. Aside from energy 

use, other important factors influencing the analyses include energy prices, installation costs, 

product distribution markups, and sales tax. At the national and regional levels, the LCC 

spreadsheets explicitly model the uncertainty and variability in the model’s inputs using 

probability distributions based on the shipment of products to different regions of the country. 

As mentioned, DOE generated LCC and PBP results as probability distributions using a 

simulation based on Monte Carlo analysis methods in which certain key inputs consist of 

probability distributions rather than single-point values. Therefore, the outcomes can be 

expressed as probability distributions. As a result, the Monte Carlo analysis produces a range of 

LCC and PBP results. A distinct advantage of this type of approach is that DOE can identify the 

percentage of customers achieving LCC savings or attaining certain PBP values, in addition to 

identifying the average LCC savings or average PBP for a particular efficiency level. 

DOE received a number of comments from stakeholders on the LCC and PBP analysis 

methods and proposed sources of data. 

2.7.1 General Approach for Life-Cycle Cost and Payback Period Analyses 

Joint Comment 1 stated that DOE should estimate uncertainty bands in product and 

operating costs (derived from uncertainty in materials costs and in energy costs to consumers) 

and document its methods. DOE should also present methods to examine asymmetries in risks of 

under- versus over-investments in efficiency. (Joint Comment 1, No. 25 at p. 11) Joint Comment 

1 noted that when the LCC analysis gives a rather flat-bottomed curve, DOE must move toward 

maximum feasible efficiency to meet the legal requirements. (Joint Comment 1, No. 25 at p. 11) 

Joint Comment 1 stated that the value of energy during peak load conditions needs to be 

accounted for in the LCC analysis. (Joint Comment 1, No. 25 at pp. 4-5) ACCA asked whether 

the LCC and PBP analyses consider rebates, tax incentives, and other benefits available to the 

consumer to encourage the purchase of more efficient products. (ACCA, No. 13 at p. 277) 

With respect to uncertainty bands, DOE considers costs of materials and services and 

uses a distribution of the costs of such items across the nation. The MSP already accounts for the 

uncertainty of prices of products in the manufacturing process due to uncertainty in materials 

prices. The analysis also considers differences in energy prices across the nation and over time 

(see chapter 7 of the preliminary TSD). DOE’s LCC savings results include the percentages of 

consumers at each efficiency level for whom the LCC savings are positive and negative, and 

those who are not affected (because they already buy products that are more efficient than the 

standard), thus demonstrating the relative risks for consumers from higher efficiency levels (see 

chapter 8 of the preliminary TSD). In addition, the national impact analysis shows the present 

value of net economic savings to the nation at each efficiency level, thus showing the risks to the 

nation of under- and over-investment in efficiency (see chapter 11 of the preliminary TSD). As 

for energy value during the peak load, the LCC analysis uses marginal prices for energy savings 

that account for the prices of residential and commercial energy during the peak periods. With 

respect to meeting legal requirements, DOE considers the LCC at each efficiency level along 

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with the impact on manufacturers (from the manufacturer impact analysis in chapter 12 of the 

preliminary TSD) and the nation (from the national impact analysis in chapter 11 of the 

preliminary TSD), as well as the other factors set forth in 42 U.S.C. 6295(o)(2)(B) to determine 

whether a given standard level achieves the maximum improvement in energy efficiency that is 

both technically feasible and economically justified. 

DOE’s basic analyses calculate the LCC and PBP without rebates, tax incentives, and 

other methods to “buy down” the installed costs of products. The regulatory impact analysis 

calculates the impact of market incentives of rebates and tax incentives (chapter 18 of the 

preliminary TSD). 

2.7.1.1 Uncertainties in Assumptions 

ACEEE noted DOE’s tendency to use the LCC analysis as the driving agent to make its 

determination when there is significant uncertainty in all its assumptions (i.e., from service life to 

the trajectory of electricity prices). (ACEEE, No. 13 at p. 343) 

DOE does estimate LCC at each efficiency level but, as mentioned above, balances LCC 

along with impacts on manufacturers and the nation, as well as the other required factors, when 

determining whether a given standard level achieves the maximum efficiency improvement that 

is technically feasible and economically justified. 

2.7.1.2 Treatment of Non-Compliant Installations in the Analysis 

CFM asked if the LCC model has a degradation factor to account for sub-performing 

noncompliant installations. CFM has had experience with SEER 13 units being installed on 

improperly matched evaporators, especially in multi-family housing units. (CFM, No. 13 at p. 

337) 

The LCC analysis assumes that energy consumption is the amount calculated in the 

energy analysis, which in turn assumes that the products at each efficiency level achieve the 

relative efficiency that corresponds to the increase in SEER or HSPF for that level. DOE 

currently has no data that would show any systematic deviation from this pattern. 

ACCA asked about the availability of the LCC analysis assumptions so that they could be 

reviewed. (ACCA, No. 13 at p. 336) 

All assumptions for the LCC model are discussed in chapter 8 of the preliminary TSD. 

Additional details on retail markup assumptions are discussed in chapter 6, engineering 

assumptions and manufacturer selling price in chapter 5, and energy consumption in chapter 7. 

2.7.2 Electricity Prices 

Electricity price information is required to calculate the dollar benefits to consumers who 

purchase and operate more efficient central air conditioners and heat pumps. The electricity cost 

savings comprise the benefit side of the cost-benefit analysis used to estimate the LCC impacts 

of more efficient central air conditioners and heat pumps. To value the electricity cost savings, 

DOE developed marginal electricity prices. The marginal electricity price for a given consumer 

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is the cost of the next increment of electricity use on their utility bill, and is the correct estimate 

of the value of savings that a consumer would see in the real world. 

DOE developed residential marginal electricity prices from tariffs collected in 2008 from 

a representative sample of electric utilities throughout the United States. DOE collected over 150 

residential tariffs from a sample of about 90 electric utilities. As described earlier, DOE 

developed household samples using central air conditioners and heat pumps from the 2005 

RECS. The location of each household can be identified within broad geographic regions (e.g., 

Census Divisions). As a result, each household is assigned to a utility within a region. In turn, 

DOE developed a weighted-average marginal electricity price for each household from all the 

possible utility tariffs that could be assigned to that household. 

DOE also developed commercial marginal electricity prices from tariffs for those 

commercial building applications that use residential central air conditioners and heat pumps. 

DOE used tariffs collected in 2004. Because central air conditioner and heat pump shipments to 

commercial applications are estimated to be low, DOE did not update its commercial tariff 

collection. Rather, DOE adjusted the prices from the 2004 tariffs with scaling factors based on 

the increase in average electricity prices from 2004 to 2008 based on data from EEI Typical Bills 

reports7

 and a summary report on rate increases published by Regulatory Research Associates.8 

Similar to the residential tariffs, DOE collected over 260 commercial tariffs from a sample of 90 

electric utilities. For the commercial buildings characterized and simulated in the Energy Use 

Characterization analysis, DOE assigned all possible tariffs to each building based on its 

geographic location. As with the residential household sample, DOE developed a weightedaverage marginal electricity price for each commercial building from the utility tariffs that could 

possibly be assigned to that building. 

AHRI and Trane questioned the use of marginal electricity prices given that past 

standards rulemakings found only slight differences between average and marginal electricity 

rates. (AHRI, No. 24 at p. 9; Trane, Public Meeting Transcript, No. 13 at pp. 308–309) Carrier 

and Sempra noted that the projected effective date of the standards is relatively distant (2016), 

which makes it difficult to estimate electricity prices. Carrier also stated that due to the 

uncertainty of electricity pricing in the future, the focus of the analysis should not be on the 

development of electricity prices. (Carrier, Public Meeting Transcript, No. 13 at pp. 314-315; 

Sempra, Public Meeting, No. 13 at pp. 310-311) In contrast, PG&E and EEI believe there are 

likely to be significant differences in average and marginal prices. (PG&E, Public Meeting 

Transcript, No. 13 at p. 309; EEI, Public Meeting Transcript, No. 13 at pp. 311-312) Although 

the marginal electricity prices DOE developed for some prior standards rulemakings 

demonstrated little to no difference between average and marginal prices, there is reason to 

believe that marginal prices differ significantly from average prices for highly seasonal and 

peak-coincident end uses such as air conditioning. For example, in a rulemaking on standards for 

commercial unitary air conditioners (CUAC), the DOE-developed marginal electricity prices 

differed substantially from average prices.9

 Therefore, DOE developed marginal electricity 

prices for this rulemaking to ensure that it accurately calculated the value of electricity savings 

due to more efficient central air conditioners and heat pumps. DOE’s current method of 

determining electricity prices based on tariffs allows the calculation of either average or marginal 

electricity prices with little difference in effort. 

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A joint comment from the National Resources Defense Council (NRDC), the National 

Consumer Law Center, Inc. (NCLC), and Enterprise Community Partners (ECP) stated that DOE 

should develop time-of-use (TOU) rates for the entire country (hereafter “Joint Comment 3”). 

(Joint Comment 3, No. 36 at pp. 2–3) Ice Energy stated that the analysis should account for 

electrical generation costs based on TOU. (Ice Energy, No. 33 at p. 3) As described above, DOE 

collected residential tariffs to characterize marginal electricity prices for central air conditioners 

and heat pumps. These tariffs are based on electricity use charges (in dollars per kilowatt hour 

($/kWh)) that are a function of the overall household electricity use (in kWh). For example, for 

tariffs with increasing block rates, households will be charged a higher price once electricity 

consumption exceeds defined threshold levels. This type of pricing structure does not necessarily 

reflect the cost to a utility of providing electrical service at different times of the day. Many 

utilities offer optional TOU tariffs that generally charge consumers more for electricity during 

peak periods when it presumably costs the utility more to provide electrical service. During offpeak periods, TOU tariffs are also structured to charge consumers less than they would normally 

be charged under a non-TOU tariff. To determine the effect of TOU pricing structures on 

residential consumers, DOE collected TOU tariffs for those utilities in the sample (50 percent) 

that offered optional TOU tariffs to their customers. This represents a larger percentage of 

potential customers because TOU tariffs are typically offered by larger utilities. Coupling hourly 

energy savings derived from typical residential household and central air conditioner/heat pump 

load profiles with TOU tariffs, DOE was able to derive TOU-based marginal electricity prices. 

Appendix 8-D of this preliminary TSD describes this analysis, which compares marginal prices 

developed from TOU tariffs with marginal prices developed from non-TOU tariffs. For 

commercial prices, existing tariff structures already account for the effect that an end use, such 

as central air conditioning, has on marginal electricity prices. Because utilities bill their 

commercial consumers with demand charges (in $/kWh) in addition to energy charges, the 

resulting marginal prices reflect the contribution that air conditioning has on peak demand. 

Joint Comment 3 stated that the electricity prices that DOE uses do not reflect the full 

costs to the utility system of providing electricity to meet air-conditioning demand. (Joint 

Comment 3, No. 36 at pp. 2-3) In the analysis of CUAC efficiency standards, DOE conducted a 

comprehensive analysis of the real marginal cost of serving peak loads, and compared it to the 

marginal price utilities charge their customers through commercial tariffs. While CUAC is a 

different appliance serving a different customer sector, the technical analysis of peak impacts for 

residential and commercial air conditioning is essentially the same. The analysis for CUAC 

accounted for the diversity of CUAC loads and their coincidence with utility system loads. 

Electric utility capacity costs were determined at a regional level (in $/kWh) and applied to the 

CUAC peak load savings to calculate the capacity component of the real marginal cost. The real 

marginal cost calculation included operating, capacity, and other costs incurred to serve 

customers, and so represented the price the utility would have to charge to cover all of its costs at 

the margin. The results of this analysis showed that on a national average basis, the real marginal 

cost and the tariff-based marginal price were nearly equal, with a value of approximately 

10¢/kwh in 2002$. Across the industry, utilities appear to recover through their tariffs the real 

cost of serving peak loads. At the national level, there are no subsidies. Overall, it seems unlikely 

that a peak impact that does not appear significant for commercial air conditioning would be 

significant for residential central air conditioners. In regions where the total electric load peaks in 

summer, commercial air conditioning tends to be more peak-coincident than residential, because 

the overall system peak is driven by the standard 9:00-to-5:00, 5-day work week schedule that 

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most commercial buildings follow. Therefore, DOE believes that the conclusions of the price 

analysis for CUAC also apply to central air conditioners and heat pumps, and that on the average 

current utility tariffs capture the true marginal cost of providing electricity for peak-coincident 

end uses. 

DOE used projections of electricity prices from EIA’s Annual Energy Outlook 2009 

(AEO 2009) to estimate future energy prices.10 Joint Comment 1 recommended that DOE 

perform appropriate sensitivity analyses for broad ranges of energy costs. (Joint Comment 1, No. 

25 at p. 4) DOE conducts sensitivity analyses using alternative AEO forecasts in addition to the 

AEO reference forecast. These alternative forecasts reflect different assumptions about economic 

growth and other factors. In general, the range of AEO forecasts bracket the long-run energy 

price forecasts made by other organizations. Joint Comment 3 stated that DOE should not rely 

solely on the AEO forecasts, but should consider relevant factors that occur after the AEO 

publication date. It also suggested that DOE should examine futures contracts for natural gas and 

adjust its electricity price forecasts accordingly. (Joint Comment 3, No. 36 at pp. 3, 6) The AEO 

forecast of electricity and other energy prices is a widely accepted, thoroughly documented, and 

transparent benchmark analysis. AEO price forecasts are recalibrated each year. DOE has 

consistently relied on AEO price forecasts and has used other forecasts, including the various 

AEO scenarios, to delimit the energy prices used in standards analyses. DOE believes this is the 

best approach for forecasting prices. EEI commented that currently 26 states have renewable 

portfolio standard (RPS) mandates and four have RPS goals, and that DOE should take these into 

account in its analysis. (EEI, Public Meeting Transcript, No. 13 at p. 394) The AEO forecasts 

account for all state RPS mandates and their impact on future electricity prices. 

Earthjustice stated that DOE’s forecast of electricity prices should account for the high 

probability of a nationally applicable mandatory regime to limit CO2 emissions. (Earthjustice, 

No. 29 at pp. 3-4) Until any cap and trade legislation is enacted, analysis of its impacts would be 

speculative. DOE uses the most recent AEO forecasts to estimate future electricity prices. If a 

carbon cap and trade regime is enacted, the AEO is likely to incorporate the projected impacts of 

the regime in its forecast. 

2.7.3 Repair Cost 

2.7.3.1 Replacement Cost of Components of Higher Efficiency Products 

DOE received several general comments on repair costs. ACCA noted that while 

maintenance costs may be only slightly more for higher efficiency products, the cost of repair 

and installation increases are enough to warrant consideration as part of the LCC and PBP 

analyses. (ACCA, No. 23 at p. 5) Unico commented that the product lifetime should include a 

factor for product warranty and coverage. (Unico, No. 13 at p. 342) Unico observed that some 

repairs are so expensive that owners replace the whole unit rather than repair the original and this 

calls into question the assumption of one compressor change-out in a lifetime. Danfoss 

commented that in the replacement industry (two-thirds of the total market), the consumer can 

choose to replace the compressor or put in a new and more efficient unit. Danfoss and Lennox 

both commented that the higher cost of higher SEER products drives homeowners toward repair 

and this trend will continue with lower SEER products. (Danfoss, No. 13 at p. 343; Lennox, No. 

13 at p. 338) 

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DOE plans to scale the cost of repair to the efficiency and cost of the products. DOE 

seeks comment and data on whether increased standard levels will affect the decision to repair 

rather than replace the product enough to significantly affect the distribution of product lifetimes 

and the estimated number of compressor replacements. 

Lennox commented that while the use of micro-channel heat exchangers resulted in 

smaller units with R-22, it is unclear whether this size reduction is possible with R-410A. A leak 

in a micro-channel would likely require replacing the entire coil, leading to higher replacement 

costs. (Lennox, No. 13 at p. 339) 

Trane commented that it will be using electronically commutated motors (ECMs) on 

blowers, fans, and possibly compressors. Trane urged DOE to obtain estimates for replacement 

part costs of induction motors versus ECM motors and for conventional contacts (relays) for an 

electro-mechanical system versus the electronic control board. (Trane, No. 13 at p. 339) Trane 

asserted that an electronic control board cannot be serviced at the same cost as an 

electromechanical system. Trane also commented that if the standard level leads to a requirement 

for multi-speed outdoor units and the variable speed indoor/outdoor motors, this would 

inevitably lead to significantly higher maintenance and repair costs due to the complexity of the 

diagnosis, the prospect of higher failure rates for more complex systems, and higher repair parts 

costs. (Trane, No. 16 at p. 20) 

DOE has modeled the cost of repair proportional to the relative initial cost of the products 

as efficiency increases. Thus, as efficiency levels increase, the cost of repair will also increase, 

consistent with these industry comments. 

DOE plans, at the notice of proposed rulemaking (NOPR) stage, to address the consumer 

repair versus replace decision in the LCC chapter (chapter 8) by conducting sensitivity analyses 

to identify the effects of increased repair costs versus new purchase costs on LCC. However, 

DOE does not plan to carry this sensitivity analysis through to the national impact analysis. DOE 

plans to address the effects of regional standards on low-income consumers within the subgroup 

analysis (chapter 12) by conducting LCC analyses for these subgroups at the regional level, also 

at the NOPR stage of the rulemaking. However, DOE does not plan to carry either of these 

analyses through to the national impact analysis. 

2.7.4 Maintenance Cost 

DOE received multiple comments concerning the effects of the technical complexity of 

higher efficiency products on maintenance costs. HARDI commented that a greater emphasis on 

planned maintenance must be given to higher efficiency products to maintain the installed 

efficiency. (HARDI, No. 32 at p. 4) According to HARDI, the high potential price of the R-410A 

refrigerant would make a noticeable difference in maintenance costs, especially when higher 

efficiencies require larger charge sizes. The cost of the refrigerant could exceed the value of the 

warranty on the product. (HARDI, No. 13 at p. 333) 

Trane commented that if the minimum efficiency level leads to a requirement for multispeed outdoor units and the variable speed indoor/outdoor motors, significantly higher 

maintenance and repair costs would be expected due to the complexity of the diagnosis, the 

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EERE-2008-BT-STD-0006 COMMENT 54
prospect of higher failure rates for more complex systems, and higher repair part costs. (Trane, 

No. 16 at p. 20) 

AHRI and Lennox commented that DOE cannot assume that the maintenance repair and 

installation costs will be negligible for more efficient products. Lennox noted that higher 

efficiency products have much larger coils and clogged coils have a bigger effect (implying 

higher maintenance costs). (AHRI, No. 24 at p. 10; Lennox, No. 13 at pp. 338–339) 

PG&E commented that based on extensive study of its field experience, a higher 

efficiency product maintains its actual field performance better over a range of charge, reducing 

maintenance cost. (PG&E, No. 13 at pp. 334–335) 

ACEEE commented that for those manufacturers not adopting micro-channel heat 

exchangers, it is unclear whether new technologies will lead to higher maintenance costs. The 

new technologies include a great deal of foregone advanced and automated diagnostics. These 

improvements should lead to smarter machinery that will be self-correcting and will notify the 

maintenance technician what to bring and do when conducting maintenance. (ACEEE, No. 13 at 

p. 332) 

DOE acknowledges that although some maintenance costs may not increase in higher 

efficiency products, other components likely would cost more to maintain, such as cleaning of 

larger coils and conducting more complex diagnostics of components such as multi-speed 

compressors and variable-speed motor systems and setting of more complex controls. DOE 

assumed that maintenance cost will increase for higher efficiency products in the analysis and 

will scale maintenance cost to the product selling price, which is a proxy for the complexity of 

the mechanical components, electronics, and size of the coils. 

2.7.5 Discount Rate 

As described below, DOE developed discount rates separately for residential and 

commercial purchasers of central air conditioners and heat pumps. 

2.7.5.1 Residential Rates 

DOE derived discount rates for the LCC analysis from estimates of the cost to finance the 

purchase of the considered products. Following financial theory, the financial cost of raising 

funds to purchase appliances can be interpreted as (1) the financial cost of any debt incurred to 

purchase a product, or (2) the opportunity cost of any equity used to purchase a product. 

Carrier, AHRI, CFM, and Trane stated that DOE should use a discount rate for residential 

consumers equal to the prevailing credit card rate. (Carrier, No. 18 at p. 10; AHRI, No. 24 at p. 

9; CFM, Public Meeting Transcript, No. 13 at p. 328; Trane, Public Meeting Transcript, No. 13 

at p. 329) Carrier and Trane also commented that over 70 percent of unit sales are for 

replacement and that these would not be included in mortgages. (Carrier, No. 18 at p.10; Trane, 

No. 16 at p. 19) Energy Solutions suggested that DOE factor in default rates on credit cards as a 

negative interest rate when determining the rates associated with credit cards. (Energy Solutions, 

Public Meeting Transcript, No. 13 at p. 329) 

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For replacement purchases, households use various methods to finance the purchase of 

major appliances. The frequency with which each financing vehicle is used to purchase an 

appliance is unknown, however. DOE identifies all possible debt or asset classes that might be 

used to purchase the considered appliances or that might be affected indirectly. DOE then 

estimates the average percentage shares of the various types of debt and equity for the average 

U.S. household using data from the Federal Reserve Board’s Survey of Consumer Finances 

(SCF) for a number of years. Using the SCF and other sources, DOE then develops a distribution 

of rates for each type of debt and equity to represent the rates that may apply in the year in which 

amended standards would take effect. For the purchase of products for new homes, which are 

included in the sales price of the home, DOE uses finance costs based on a distribution of 

mortgage rates. Based on data from RECS, DOE determined that new home purchases represent 

approximately 30 percent of residential sales. 

2.7.5.2 Commercial 

DOE developed commercial discount rates based on cost of capital calculated for 

commercial businesses expected to occupy small commercial buildings. For the commercial cost 

of capital data, DOE relied on financial data for industries found in the Damodaran website for 

2009. DOE received a comment on commercial discount rates. 

EEI suggested that DOE use discount rates associated with small businesses most likely 

to use central air conditioners and heat pumps, rather than using discount rates from all types of 

commercial businesses that would use other products. (EEI, No. 20 at p. 7; No. 13 at p. 327) 

For commercial rates, DOE uses discount rates only for businesses that would be 

expected to occupy small commercial buildings. DOE will investigate whether it is possible to 

identify small businesses that would use central air conditioners and heat pumps and whether 

there is likely to be a significant difference in discount rates for such businesses. See chapter 8 in 

the preliminary TSD for further discussion of discount rates. 

2.7.5.3 Product Lifetime 

Product lifetime is the age at which the central air conditioner or heat pump is retired 

from service. In the prior standards rulemaking for these products, DOE conducted a 

comprehensive analysis on product lifetime showing that the average lifetime for central air 

conditioners and heat pumps was 18.4 years. That analysis also demonstrated that compressors 

failed and were replaced on average in year 14 of the system’s life. AHRI and Trane stated that 

the central air conditioner and heat pump lifetimes are 10 and 12 years, respectively. (AHRI, No. 

24 at p. 10; Trane, No. 16 at p. 21) Trane also suggested that DOE use data provided by the 

Census Bureau and/or RECS to deduce central air conditioner and heat pump lifetime. (Trane, 

Public Meeting Transcript, No. 13 at p. 340) ACCA conducted an informal survey of its 

members and determined that central air conditioner and heat pump lifetime is less than 18.4 

years. (ACCA, No. 23 at p. 5) 

DOE based product lifetimes for its prior central air conditioner and heat pump standards 

rulemaking on a consumer survey from the late 1980s commissioned by electric utilities. 

Although the survey was robust and accurate, it may no longer be representative of current 

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product lifetimes. As a result, DOE conducted an analysis of actual product lifetime in the field 

using a combination of shipments data and responses in RECS on the age of household central 

air conditioner and heat pump products. By combining the results of RECS with the known 

history of appliance shipments, DOE estimated the percentage of central air conditioner and heat 

pump products of a given age still in operation. This survival function, which DOE assumed has 

the form of a cumulative Weibull distribution, provides an average and a median appliance 

lifetime. As described in chapter 8, this analysis yielded an estimate of mean life of 19 years for 

central air conditioners and 16.3 years for heat pumps. 

HARDI stated that product lifetimes decrease for higher efficiency products due to their 

complexity. (HARDI, No. 32 at p. 4) Contrary to HARDI, MEUS stated that higher efficiency 

products should have a longer life expectancy. (MEUS, No. 19 at p. 5) DOE’s method of 

developing product lifetimes does not account for the efficiency or complexity of the product. 

DOE is unaware of data that clearly demonstrates that more efficient or sophisticated products 

have longer or shorter liftimes than more conventional products. Without such data, DOE 

assumed that lifetime was not a function of either efficiency or product complexity. 

2.8 NATIONAL IMPACT ANALYSIS 

The NIA assesses the NES and the NPV from a national perspective of total appliance 

consumer costs and savings expected to result from standards at specific efficiency levels. DOE 

determined both the NPV and NES for the performance levels considered for the product classes 

analyzed. To make the analysis more accessible and transparent to all interested parties, DOE 

prepared a Microsoft Excel spreadsheet model to forecast NES and the national consumer 

economic costs and savings resulting from new standards. The spreadsheet model uses typical 

values (as opposed to probability distributions) as inputs. To assess the effect of input 

uncertainty on NES and NPV results, DOE has developed its spreadsheet model to conduct 

sensitivity analyses by running scenarios on specific input variables. 

DOE conducted its NIA to assess impacts for the hot-humid region, the hot-dry region, 

and the remaining parts of the country that are neither hot-humid nor hot-dry (to which the 

national standard would be applicable). Although the sum of the regional impacts does provide 

the impact on the entire Nation, DOE also conducted its NIA for the Nation as a whole without 

consideration of regional implications. This national analysis provided NES and NPV results 

different from those determined by summing the regional impacts. Because inputs to the NIA, 

such as product total installed cost, product annual energy consumption, and product repair and 

maintenance costs, have regional dependencies in addition to being a function of product 

efficiency, the regional level impacts when summed will differ from the impacts that are 

determined at the national level. If DOE proposes regional standards in the NOPR, DOE will 

consider whether to present the national impacts as a sum of the regional results. 

2.8.1 Shipments Analysis 

DOE uses forecasts of product shipments to calculate the national impacts of standards 

on energy use, NPV, and future manufacturer cash flows. DOE developed shipment forecasts 

based on an analysis of key market drivers for each considered product. In DOE’s shipments 

model, shipments of products are driven by new construction, replacement of the existing stock 

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of installed products, and existing households or buildings that do not already own the product 

(referred to hereafter as new owners). DOE accounted for shipments to commercial buildings as 

well as residential households. The industry provided estimates of the percentage of annual 

central air conditioner and heat pump sales shipped to commercial building applications. These 

estimates ranged from 3 to 10 percent. (Trane, No. 16 at p. 17; Carrier, No. 18 at p. 8; MEUS, 

No. 19 at p. 4; AHRI, No. 24 at p. 8) Based on industry input, DOE assumed 7 percent of central 

air conditioner and heat pump shipments were to commercial applications and accounted for this 

in the shipments model. 

The shipments model takes an accounting approach, tracking market shares of each 

product class and the vintage of units in the existing stock. Stock accounting uses product 

shipments as inputs to estimate the age distribution of in-service product stocks for all years. The 

age distribution of in-service product stocks is a key input to NES and NPV calculations because 

operating costs for any year depend on the age distribution of the stock. DOE used historical 

product shipments to assist in calibrating the shipments model. AHRI and other parties provided 

historical product shipments information. (AHRI, Public Meeting Transcript, No. 13 at p. 352) 

AHRI provided historical shipments for each of the four primary product classes—split-system 

air conditioners, single-package air conditioners, split-system heat pumps, and single-package 

heat pumps—but did not disaggregate the shipments data regionally. As a result, DOE relied on 

historical regional product stock saturation data from past RECS surveys as well as past U.S. 

Census Bureau American Housing Surveys (AHS). Put simply, DOE disaggregated AHRI’s 

historical product shipments regionally by calibrating the resulting product stock saturations to 

the values specified by the RECS and AHS data. DOE used this calibration technique for 

residential shipments only. Commercial shipments were allocated regionally based on the 

percentage allocations determined for residential shipments. 

MEUS stated that it would provide historical shipments data for ductless split systems. 

(MEUS, Public Meeting Transcript, No. 13 at p. 34) For SHDV systems, Unico noted that 

SDHV manufacturers sell only the indoor half of the system, and therefore do not know which 

condenser model installation contractors use for outdoor units. As a result, SDHV shipments data 

are not available. As noted in section 2.2.1.2, DOE considers ductless split systems within the 

product class of split systems and does not analyze ductless systems separately. The analyses 

conducted for this preliminary TSD have not addressed the non-primary product classes that 

include space-constrained products and SDHV systems. DOE requests shipment data from 

interested parties for non-primary products (e.g., SDHV systems, space-constrained products, 

ductless split systems), as well as suggestions on how to treat these product classes in the NOPR. 

To estimate the impact that standards have on product shipments, DOE analyzed the 

impact that purchase price, operating costs, and household income have had on historical central 

air conditioner and heat pump shipments. From this analysis, DOE derived a relative price 

elasticity that estimates shipments impacts as a function of the increase in purchase price, 

operating cost savings, and household income. Although the correlation among historical 

shipments and the above three parameters is not strong, there is enough evidence to suggest a 

connection. Of the three parameters, purchase price has the most significant impact on product 

shipments; an increase in product purchase price will lead to a decrease in product shipments. 

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Several interested parties remarked that the increase in purchase price due to higher 

efficiency standards would lead to decreased central air conditioner and heat pump shipments. 

Specifically, EEI and Rheem commented that some consumers may switch from central systems 

to room air conditioners when faced with higher product purchase prices. (EEI, No. 20 at p. 8; 

Rheem, Public Meeting Transcript, No. 13 at p. 376) MEUS stated that central heat pump 

consumers may switch to either electric resistance heating systems or hybrid systems if standards 

significantly increase product purchase price. (MEUS, Public Meeting Transcript, No. 13 at pp. 

358–359) Several parties remarked that consumers may choose to repair their products rather 

than replace it if standards lead to significantly higher product purchase prices. (Danfoss, Public 

Meeting Transcript, No. 13 at pp. 274, 359; Trane, Public Meeting Transcript, No. 13 at p. 360; 

HARDI, Public Meeting Transcript, No. 13 at p. 24; CFM, Public Meeting Transcript, No. 13 at 

p. 35; MEUS, No. 19 at p. 5) DOE acknowledges that a significant increase in central air 

conditioner and heat pump purchase prices could cause some potential new owners to forego or 

delay a central air conditioner or heat pump purchase. As described above, DOE developed a 

relative price elasticity to quantify the potential drop in central air conditioner and heat pump 

sales from an increase in purchase price due to standards. 

DOE considered shipments decreases only in the replacement and new owner markets. 

Because most new construction is now routinely equipped with either a central air conditioner or 

heat pump, DOE assumed that any increase in purchase price caused by standards would not 

affect the decision to install a central air conditioner or heat pump system in new construction. In 

the case of the replacement market, DOE assumed that any drop in shipments would be caused 

by consumers deciding to repair rather than replace their products. DOE estimated that the 

extended repair would last 6 years, after which time the products would be replaced. In the case 

of new owners of central air conditioners, DOE assumed that any consumers forgoing a central 

air conditioner purchase would instead buy a room air conditioner. In the case of new owners of 

central heat pumps, DOE assumed that any consumers forgoing a heat pump purchase would 

instead purchase a combination central air conditioner and electric resistance furnace system. 

ACEEE noted that in 2010, products will need to transition to a new refrigerant—R-410a. 

ACEEE stated that R-410a-based systems require a very different class of refrigerant lubricants. 

Consequently, for split systems, DOE should pay attention to the feasibility of component 

replacements rather than system replacements when consumers are required to move from an R22 system to an R-410A system that uses different lubricants and controls. (ACEEE, Public 

Meeting Transcript, No. 13 at p. 362) As described in section 2.4.1.2. DOE did not account for 

the impact of switching to R-410a in determining manufacturer costs. For modeling the 

replacement of split systems in the shipments analysis, DOE assumed that all consumers would 

replace both the outdoor unit and the indoor coil. Although consumers today may replace only 

the outdoor unit and retain the indoor coil, with the transition to R-410a, DOE assumed all 

consumers would replace both components in order to avoid refrigerant and lubricant 

incompatibility issues. Although not explicitly accounting for the effects of R-410A as described 

above, DOE estimated the impact of higher product prices on a consumer’s decision to repair or 

replace a failed unit. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Chapter 9 of the preliminary TSD provides additional details on the shipments analysis 

and the impact that higher purchase prices, operating costs, and household income due to 

standards have on product shipments. 

2.8.2 Efficiency Scenarios and Trends 

Several of the inputs for determining NES and NPV depend on product efficiency. DOE 

developed efficiency trends for the base case without new standards and the standards case. 

These trends specify the average annual historical and forecasted shipments-weighted product 

efficiencies. 

In the framework document, DOE proposed to use a “roll-up” efficiency scenario in 

developing its forecasts of efficiency trends after standards take effect. Under this scenario, all 

products that perform at levels below a prospective standard are moved, or rolled up, to the 

minimum performance level allowed under the standard. The distribution of products that meet 

the higher efficiency standard levels is unaffected. 

Joint Comment 1 stated that prior rulemakings suggest that the early response to 

standards is a “roll-up” but that eventually, the market begins to shift. Joint Comment 1 

suggested that DOE should attempt to incorporate a blended scenario in the NIA. (Joint 

Comment 1, No. 25 at p. 11) Danfoss also suspected that an initial roll-up and eventual 

efficiency spread are likely. Danfoss stated that the standards that took effect in the early 1990s 

indicate that a roll-up phenomenon occurred immediately, followed a year or two later with the 

sale of products with higher efficiencies. (Danfoss, Public Meeting Transcript, No. 13 at p. 372) 

AHRI stated that over the last 3 years, shipments have included higher product efficiencies. 

AHRI’s expects this trend will continue as energy costs escalate. AHRI suggested forecasting an 

increasing efficiency trend to the effective date of the standard (2016) and using a roll-up 

scenario to estimate the impact from new standards. (AHRI, No. 24 at p. 11) EEI suggests 

reviewing historical efficiency data between 1992 and 2006 to estimate the probable impact from 

new standards. EEI also suggests adding a “time lag” effect once the new standards become 

effective (i.e., accounting for product sales with efficiencies lower than the new standard because 

of manufacturer and distributor inventories). NRDC noted that new legislation and enhanced 

market-pull programs will likely lead to the sale of more efficient products. (NRDC, Public 

Meeting Transcript, No. 13 at p. 375) 

AHRI provided historical shipment-weighted efficiency (SWEF) data for each of the four 

primary product classes between 1992 to 2008, which included new standards for central air 

conditioners and heat pumps in 1992 and 2006. After the 1992 standards took effect, SWEFs 

increased for each product class on average 1 SEER between 1992 and 2005, which is an 

efficiency growth rate of approximately 0.077 SEER per year. After the 2006 standards took 

effect, SWEFs increased in 2007 and 2008, but with limited data, it is difficult to assess the 

growth. After reviewing the historical data from AHRI, DOE believes that new standards will 

cause baseline models to roll up to the standard efficiency level, but that some fraction of 

shipments will remain above the minimum. DOE calculated the SWEF from this resulting 

efficiency distribution. In the years following the standard, DOE estimated that SWEFs for the 

base case will continue to grow at the rate observed between 1992 and 2005 (i.e., 0.077 SEER 

per year) until the max-tech efficiency level is attained, at which point the SWEF was held 

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constant. To develop standards case forecasted SWEFs, DOE developed growth trends for each 

standard level that maintained the same per-unit average total installed cost difference for the 

between the base case and each standards case for the year 2016 over the entire forecast period 

(2016–2046). 

HARDI and Trane commented on the effect that market-pull programs such as ENERGY 

STAR can have on the sale of high-efficiency products. HARDI claimed that higher efficiency 

standards could actually hinder the effectiveness of market-pull programs to improve overall 

building performance. For example, higher product costs due to standards can be an issue in 

qualifying for sustainable building credits and initiatives. (HARDI, No. 32 at p. 8) Trane noted 

that manufacturers run off-season rebate programs to promote the sale of high-efficiency 

products. The method described above for forecasting SWEFs after a standard becomes effective 

assumes the continued existence of market-pull programs to encourage the adoption of more 

efficient products. Because DOE used the same efficiency growth rate as the growth rate 

between 1992 and 2005, the effectiveness of future market-pull programs is implicitly assumed 

to be the same as the effectiveness of programs between 1992 and 2005. Chapter 10 of the 

preliminary TSD details the approach DOE used to forecast product efficiencies. 

2.8.3 National Energy Savings Analysis 

The inputs for determining the national energy savings for each product analyzed are: (1) 

annual energy consumption per unit; (2) shipments; (3) product stock; (4) national energy 

consumption; and (5) site-to-source conversion factors. DOE calculated the national energy 

consumption by multiplying the number of units (stock) of each product (by vintage or age) by 

the unit energy consumption (also by vintage). DOE calculated annual NES based on the 

difference in national energy consumption for the base case (without new efficiency standards) 

and for each higher efficiency standard. DOE estimated energy consumption and savings based 

on site energy and converted the electricity consumption and savings to source energy. 

Cumulative energy savings are the sum of the NES for each year over the timeframe of the 

analysis. 

In the framework document, DOE stated that it would consider a rebound effect in its 

analyses. A rebound effect occurs when the increased energy efficiency and reduced consumer 

costs of higher efficiency products causes the consumer to alter their behavior resulting in an 

increase in energy consumption. Based on limited research, DOE found that the rebound effect 

for residential space-cooling products appears to be highly variable, ranging from 0 to 50 percent 

(i.e., consumers may activate more efficient air-conditioning products 0 to 50 percent more 

frequently than baseline products). AHRI and Trane stated that the rebound effect is not likely to 

be significant for more efficient central air conditioners and heat pumps. (AHRI, No. 24 at p. 8; 

Trane, No. 16 at p. 17) Joint Comment 1 suggested that DOE review the available literature on 

the rebound effect. (Joint Comment 1, No. 25 at p. 11) DOE found no new literature on the 

subject since the publication of the framework document. Because industry experience indicates 

that it is very unlikely that increase product efficiencies will result in a rebound effect, DOE did 

not include this effect in its analysis. 

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AHRI commented that the analysis period for the national energy savings should not 

exceed the period during which the rule is likely to be in effect before being superseded by a 

subsequent rule. The analysis horizon should be on the order of 10 years. (AHRI, No. 24 at p. 8) 

DOE calculates the NPV of new or amended standards to estimate the impacts of 

standards on the nation. In performing the NPV analysis for the first energy conservation 

standards rulemakings, DOE selected a 30-year analysis period beginning on the effective date of 

the standard because it closely matched the lifetime of the longest-lived products considered for 

standards. Matching the lifetime of the longest-lived products allows for a full turnover of the 

stock. For the next few rulemakings on different products, DOE used the same analysis end date 

but the appropriate start-of-standard date that resulted in a shorter analysis period for those 

products. By the 1990s, DOE found that using the same analysis end date would result in 

rulemaking that could not capture the full impact of amended standards. As a result, DOE 

determined it was necessary to change the analysis end date. DOE settled on the 30-year 

analysis, which allows the full-life capture of any product shipped in the first year a standard 

becomes effective. Because products have varying lifetimes, DOE uses a 30-year period to 

maintain a consistent timeframe to compare the energy savings and economic impacts from all 

standards rulemakings. 

DOE believes that using a 30-year analysis period is appropriate. To compare energy 

savings for residential or commercial equipment classes across varying lifetime appliance 

rulemakings, DOE must use the lifetime of the longest-lived product or equipment type because 

the annual energy consequences of improving the longest-lived residential products or 

commercial equipment would remain unknown until all of the market consisted of improved 

units. That scenario would not occur until the last of the pre-standard equipment is retired. Thirty 

years is a practical estimate for that event for short- and long-lived equipment. The NOPR for 

beverage vending machines discusses this point in further detail. 74 FR 26040–41. 

To compare economic costs and savings using discounted present value, it is common in 

economics to use the stream of benefits and costs over the lifetime of the equipment. In DOE 

energy conservation standards rulemakings, the outer limit for economic benefits and costs is 

established in the NPV analysis as the last year of life of the oldest equipment purchased during 

the 30-year period used for energy savings comparisons. 

2.8.4 Net Present Value Analysis 

The inputs for determining NPV are: (1) total annual installed cost; (2) total annual 

savings in operating costs; (3) a discount factor; (4) present value of costs; and (5) present value 

of savings. DOE calculated net savings each year as the difference between the base case and 

each standards case in total savings in operating costs and total increases in installed costs. DOE 

calculated savings over the life of each product, accounting for differences in annual energy 

rates. DOE calculated NPV as the difference between the present value of operating cost savings 

and the present value of total installed costs. DOE used a discount factor based on real discount 

rates of 3 and 7 percent to discount future costs and savings to present values. 

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DOE calculated increases in total installed costs as the difference in total installed cost 

between the base case and standards case (i.e., once the standards take effect). Because the more 

efficient products bought in the standards case usually cost more than products bought in the 

base case, cost increases appear as negative values in the NPV. 

DOE expressed savings in operating costs as decreases associated with the lower energy 

consumption of products bought in the standards case compared to the base efficiency case. 

Total savings in operating costs are the product of savings per unit and the number of units of 

each vintage that survive in a given year. 

The national impacts analysis examines the potential economic impacts of alternative 

standard levels on consumers who purchase the considered products. Joint Comment 3 stated that 

DOE should quantify the effect of the standard on electricity prices and the value of reduced 

electricity bills to all consumers. (Joint Comment 3, No. 36 at p. 5) DOE investigated the 

possibility of estimating the impact of specific standard levels on electricity prices in its 

rulemaking for general service fluorescent lamps and incandescent reflector lamps.11 While 

natural gas markets exhibit a simple chain of agents from producers to consumers, the power 

industry is a complex mix of fuel suppliers, producers, and distributors. Even though the 

distribution of electricity is regulated everywhere, its institutional structure varies. Upstream 

components are more complicated and generation is priced using different methods across the 

country. For these and other reasons, accurate modeling of the response of electricity prices to a 

decrease in residential-sector demand due to standards is problematic. Thus, DOE does not plan 

to estimate the value of potentially reduced electricity costs associated with revised standards for 

all consumers. 

Chapter 10 of the preliminary TSD provides additional details on the national impacts 

analysis. 

2.9 PRELIMINARY MANUFACTURER IMPACT ANALYSIS 

DOE performed a preliminary MIA to estimate the financial impact of higher energy 

conservation standards on residential central air conditioner and heat pump manufacturers, and to 

calculate the impact of such standards on employment and manufacturing capacity. The MIA has 

both quantitative and qualitative aspects. The quantitative part of the MIA relies on the 

government regulatory impact model (GRIM), an industry-cash-flow model customized for these 

three industries. The GRIM inputs are information on the industry cost structure, shipments, and 

revenues. This includes information from many of the analyses described above, such as 

manufacturing costs and prices from the engineering analysis and shipments forecasts. The key 

GRIM output is the industry net present value (INPV). Different sets of assumptions (scenarios) 

will produce different results. The qualitative part of the MIA addresses factors such as product 

characteristics, characteristics of particular firms, and market and product trends, and includes 

assessment of the impacts of standards on manufacturer subgroups. Chapter 12 of the 

preliminary TSD describes the complete preliminary MIA. 

DOE conducts each MIA in three phases and will further tailor the analytical framework 

for each MIA based on comments from interested parties. In Phase I, DOE creates an industry 

profile to characterize the industry and identify important issues that require consideration. In 

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Phase II, DOE prepares an industry cash-flow model and interview questionnaire to guide 

subsequent discussions. In Phase III, DOE interviews manufacturers and assesses the impacts of 

standards quantitatively and qualitatively. DOE assesses industry and subgroup cash flow and 

NPV using the GRIM. DOE then assesses impacts on competition, manufacturing capacity, 

employment, and regulatory burden based on manufacturer interview feedback and discussions. 

Until recently, DOE reported MIA results in its standards rulemakings only during the 

NOPR phase of the rulemaking. However, DOE is now evaluating and reporting preliminary 

MIA information in this preliminary analysis. DOE gathered this information during the 

preliminary manufacturer interviews conducted for the engineering analysis. See chapter 12 of 

the preliminary TSD for a summary of manufacturers’ concerns regarding the impacts of 

amended energy conservation standards for this rulemaking. 

As part of the NOPR, DOE will seek comments from manufacturers about their potential 

loss of market share, changes in the efficiency distribution within each industry, and the total 

reduction in product shipments at each amended energy conservation standard level. DOE will 

then estimate the impacts on the industry quantitatively and qualitatively. DOE seeks further 

comment from interested parties about the impact of amended standards on domestic 

manufacturers. See the issues for which DOE seeks comment in the executive summary. 

The following is an overview of the information DOE will collect and the analysis it will 

conduct during the preliminary MIA (chapter 12 of the preliminary TSD). 

2.9.1 Industry Cash-Flow Analysis 

The industry cash-flow analysis relies primarily on the GRIM. DOE uses the GRIM to 

analyze the financial impacts of more stringent energy conservation standards on the industry 

that produces the products covered by the standard. The GRIM analysis uses many factors to 

determine annual cash flows from a new standard: annual expected revenues; manufacturer 

costs, including cost of goods sold, depreciation, research and development, selling, general, and 

administrative expenses; taxes; and conversion capital expenditures. DOE compares the results 

against base-case projections that involve no new standards. The financial impact of new 

standards is then the difference between the two sets of discounted annual cash flows. Other 

performance metrics such as return on invested capital are available from the GRIM. For more 

information on the industry cash-flow analysis, refer to chapter 12 of the preliminary TSD. 

2.9.2 Manufacturer Subgroup Analysis 

Industry cost estimates are not adequate to assess differential impacts among subgroups 

of manufacturers. For example, small and niche manufacturers, or manufacturers whose cost 

structure differs significantly from the industry average, could be more negatively affected by the 

imposition of standards. Ideally, DOE would consider the impact on every firm individually; 

however, since this usually is not possible, DOE typically uses the results of the industry 

characterization to group manufacturers exhibiting similar characteristics. 

DOE outlined the process it uses to establish manufacturer subgroups in the framework 

document and sought comment from interested parties on any potential subgroups within the 

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EERE-2008-BT-STD-0006 COMMENT 54
 

industry. Joint Comment 1 suggested that DOE should address impacts on other market 

participants (distributors, dealers, etc.) as an extension of DOE’s usual analyses. (Joint Comment 

1, No. 25 at p. 9) HARDI argued that increases in efficiency standards do not guarantee 

significant energy savings and can negatively impact small businesses if all factors and market 

realities are not taken fully into account. (HARDI, No. 32 at pp. 1, 3) AHRI commented that 

DOE should examine the impact of the rule on all manufacturers of different product classes. 

AHRI stated that DOE should also assess the impact on component suppliers, dealers, 

distributors, contractors, and the manufactured housing industry. (AHRI, No. 24 at p. 12) 

DOE has characterized the impacts on the residential central air conditioner and heat 

pump industry. DOE did not identify any manufacturer subgroups within the industry other than 

small manufacturers. DOE will consider the possible effects of amended energy conservation 

standards for residential central air conditioners and heat pumps on small businesses. DOE 

identified a few small businesses within the industry in chapter 3 of the preliminary TSD. During 

the manufacturer interview process conducted as part of the NOPR, DOE will discuss the 

potential subgroups and subgroup members it has identified for the analysis. DOE will encourage 

manufacturers to recommend subgroups or characteristics appropriate for the subgroup analysis. 

DOE will also attempt to contact component suppliers, dealers, distributors, and contractors 

during the manufacturer interview process conducted for the NOPR. For more detail on the 

manufacturer subgroup analysis, see chapter 12 of the preliminary TSD. 

2.9.3 Competitive Impacts Assessment 

DOE must consider whether a new standard is likely to reduce industry competition, and 

the Attorney General must determine the impacts, if any, of reduced competition. DOE will 

make a determined effort to gather and report firm-specific financial information and impacts. 

The competitive impacts assessment will focus on assessing the impacts on smaller 

manufacturers. DOE will base this assessment on manufacturing cost data and information 

collected from interviews with manufacturers. The interviews will focus on gathering 

information to help assess asymmetrical cost increases to some manufacturers, increased 

proportion of fixed costs potentially increasing business risks, and potential barriers to market 

entry (e.g., proprietary technologies). The NOPR will be submitted to the Attorney General for a 

review of the impacts of standards on competition. The Attorney General’s comments on the 

proposed rule will be considered in preparing the final rule. 

2.9.4 Cumulative Regulatory Burden 

DOE recognizes and seeks to mitigate the overlapping effects on manufacturers of new or 

revised DOE standards and other regulatory actions affecting the same products. DOE will 

analyze and consider the impact on manufacturers of multiple, product-specific regulatory 

actions. DOE outlined the cumulative regulatory burden process in the framework document and 

sought comment on any additional regulations facing the residential central air conditioner and 

heat pump industry. 

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EERE-2008-BT-STD-0006 COMMENT 54
2.9.4.1 Refrigerant Phase-Out 

In the framework document, DOE discussed how the EPA HCFC phase-out beginning on 

January 1, 2010 could impact the central air conditioner and heat pump industry. 68 FR 2820. 

Joint Comment 2 stated that the current standard-setting process for residential cooling products 

is complicated by many new factors, including the mandatory shift away from R-22 (HCFC) to 

HFC or other refrigerants in 2010, unprecedented increases in raw material pricing, and sizable 

increases in electricity cost. (Joint Comment 2, No. 30 at p. 3) ACCA stated that the cost of R-22 

has doubled in the last few years as a result of regulatory phase-outs and increased demand. 

(ACCA, No. 23 at p. 3) ACCA suggested that DOE should periodically assess the price of R-22 

throughout the rulemaking to ensure that the engineering analysis is using a proper value. EEI 

stated that manufacturers will have switched over most, if not all, of their products to R-410A by 

2010. Because this rule does not go into effect until 2016, the only impact of the reduced 

availability of R-22 will be on the retrofit market. EEI concluded that the impacts on this rule 

will therefore be minimal. (EEI, No. 20 at p. 6) 

Because production of R-22 central air conditioner and heat pump products will 

discontinue by 2010, any issues regarding the availability of R-22 will be related to the retrofit 

market. The reduced availability of R-22 may result in price increases relative to retrofit 

products. While retrofit products are outside the scope of this rulemaking, any OEMs that also 

deal with retrofit products could face an additional cumulative regulatory burden. DOE will 

consider the potential impact of refrigerant price increases on the retrofit market as part of the 

MIA analysis in the NOPR. 

HARDI commented that the potential for increased refrigerant costs (due to reduced 

availability, shorter lifetimes, and increased charge sizes) poses a significant threat to 

manufacturers. (HARDI, No. 32 at p. 7) HARDI stated that combined with lengthening 

manufacturer warranties on higher efficiency products, the liability may potentially exceed the 

affordability or availability of HFC refrigerants. HARDI also stated that increased speculation 

about the affordability and availability of HFC refrigerants could further hinder already sluggish 

sales of new products. HARDI commented that DOE should consider the refrigerant 

ramifications of residential central air conditioner and heat pump regulations that could increase 

the demand for HFC refrigerants. HARDI stated concerns about R-410A availability in addition 

to slow acceptance of new replacement refrigerants in product manufacturer warranty terms, 

which adds to concerns of long-term refrigerant supplies/options. (HARDI, No. 32 at p. 8) 

Emerson, Trane, and Carrier also expressed concern about the central air conditioner and 

heat pump industry’s transition to R-410A, stating that the supply of the new refrigerant might be 

in question. (Emerson, Public Meeting Transcript, No. 13 at p. 257; Trane, No. 16 at p. 14; and 

Carrier, No. 18 at p. 7) AHRI and Lennox recommended that DOE carefully study the impact of 

climate change legislation on the availability and price of HFC refrigerants, as there is a 

possibility that prices will dramatically increase and that not enough refrigerant will be available 

to meet the new energy conservation standards (AHRI, No. 24 at p. 7; Lennox, Public Meeting 

Transcript, No. 13 at p. 383) HARDI commented that its members have prepared for the 

transition from R-22 to HFC refrigerants such as R-410A. They also said that any regulatory 

efforts to change this to control GHG emissions would adversely impact the industry. (HARDI, 

No. 32 at p. 7) Lennox commented that given the uncertainties around climate change legislation 

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and potential regulation, the industry could be going through another refrigerant change at the 

same time that the new rulemaking becomes effective. (Lennox, Public Meeting Transcript, No. 

13 at p. 363) 

DOE used HFC refrigerant R-410A as the basis for its analysis. While pending climate 

change legislation might result in a phase-out or production caps for HFC refrigerants over the 

course of this rulemaking, any analysis of potential impacts before such legislation is enacted 

would be speculative. During interviews with manufacturers, DOE was unable to obtain any 

data that would quantify HFC refrigerant price increases. DOE requests data or information on 

projected HFC cost increases and the basis for such projections. DOE also seeks comment on the 

extent to which interested parties expect projected HFC costs to increase, the timing of these 

increases, and the certainty of the increases. 

2.9.4.2 Additional Regulations 

In addition to the HCFC refrigerant phase-out, the industry identified other regulations or 

pending regulations that should be considered in the cumulative regulatory burdens analysis. 

MEUS said that DOE should consider ASHRAE standard 90.1-2007 for economizer and 

ventilation air requirements; ASHRAE Draft Standard 189 for advanced energy designs; and 

International Codes Council (ICC) building and energy codes. (ICC 2009 codes) (MEUS, No. 19 

at p. 6) 

DOE identified several regulations relevant to central air conditioners and heat pumps, 

including energy conservation standards and regional standards for other products made by 

central air conditioner and heat pump manufacturers, the EPA phase-out of HCFCs, and building 

codes. DOE will examine the potential impacts of these regulatory burdens in greater detail in 

the MIA conducted for the NOPR. 

2.9.5 Preliminary Results for the Manufacturer Impact Analysis 

As part of the preliminary MIA, DOE discussed potential impacts of amended energy 

conservation standards with manufacturers responsible for a majority of central air conditioner 

and heat pump sales. These discussions occurred during the interviews DOE conducted for the 

engineering analysis. The interviews provided valuable information that DOE used to evaluate 

the impacts of amended energy conservation standards on manufacturers’ cash flows, 

manufacturing capacities, and employment levels. DOE discusses its findings from the 

preliminary MIA interviews in the executive summary and in chapter 12 of the preliminary TSD. 

2.9.6 Regional Standards Impacts on Manufacturers 

For the preliminary analysis, DOE conducted limited interviews with manufacturers 

regarding the potential impacts of regional standards as they relate to residential central air 

conditioners and heat pumps. 

Manufacturers stated that the implementation of regional standards would generally 

complicate their production processes, decrease their economies of scale, and complicate product 

distribution. Any additional testing, certification, rating, or labeling would increase costs, and 

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could have a harmful impact, particularly on small manufacturers. Manufacturers stated that 

margins across the industry have decreased in past years, and that imposing region-specific 

standards would likely further this decline. Manufacturers were also concerned that more 

stringent regional standards may impact consumers’ decisions to repair rather than replace units, 

as well as possible consumer switching to alternative products (i.e., multiple room air 

conditioners). Manufacturers asserted that this would be especially evident in low-income 

regions. Some manufacturers also stated that cost increases resulting from regional standards 

may cause them to stop selling products in certain regions. 

As required by EPCA, DOE plans to evaluate any differential impacts regional standards 

may have on manufacturers. DOE will tailor its MIA interview guides to include questions 

exploring the quantitative and qualitative impacts of regional standards on manufacturers. 

Potential impacts could include additional compliance, inventory, or marketing costs associated 

with the promulgation of regional standards. To the extent appropriate, DOE may evaluate 

subgroups of manufacturers that are differentially impacted by regional standards. One possible 

subgroup, for example, may be manufacturers that own distribution networks. DOE will include 

any differential financial impacts if it determines appropriate in its GRIM analysis. DOE seeks 

further comment regarding the potential impact of regional standards on manufacturers of 

residential central air conditioners and heat pumps. In addition, DOE is seeking market data that 

will assist in the identification and analysis of the impacts of regional standards on 

manufacturers. 

2.10 REGIONAL STANDARDS IMPACTS ANALYSIS 

During the framework public meeting, several interested parties indicated that there could 

be additional impacts on product distributors and contractors if DOE establishes regional 

standards. Several interested parties commented that there would be enforcement issues with 

regional standards. In establishing a framework for regional standards, EISA 2007 appears to 

recognize that DOE has not dealt with these issues previously, as the appliance standards 

programs historically set only national standards, and states that DOE shall consider the impact 

of additional regional standards on consumers, manufacturers, and other market participants, 

including product distributors, dealers, contractors, and installers. 

DOE addresses impacts on consumers in chapter 8 and chapter 11 of the preliminary 

TSD. DOE plans to analyze the impacts of regional standards on consumers within these 

chapters by calculating consumer LCCs and subgroup LCCs on a regional basis. For the NOPR, 

DOE plans to analyze the impacts of regional standards on manufacturers as part of the 

manufacturer impact analysis (chapter 12 of the preliminary TSD), as described in section 2.9.6. 

To address concerns regarding impacts of regional standards on distributors, dealers, contractors 

and installers, DOE intends to develop a new regional standards impacts analysis as a separate 

TSD chapter at the NOPR stage that identifies specific impacts of concern and examines the 

significance and scale of these impacts on the affected parties. If necessary, the analysis will also 

propose how the energy and economic analyses might be adjusted to reflect the impacts. See 

chapter 17 of the preliminary TSD for a preliminary assessment of the impacts of regional 

standards on market participants other than manufacturers and consumers. 

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2.10.1 Impacts on Manufacturers 

DOE will analyze the impacts of regional standards on manufacturers in the MIA. See 

section 2.9.6 for more detail. 

2.10.2 Impacts on Distributors, Dealers, and Contractors, and Installers 

HARDI stated that regional standards will increase non-compliance and would create a 

major competitive disadvantage for contractors that seek to comply. (HARDI, No. 32 at p. 5) 

This situation already exists in California after implementation of Title 24 requirements. Kent & 

O’Connor stated that splitting a metropolitan area with regional standards would have a 

significant competitive impact, particularly if a price difference exists between the higher 

efficiency and the national standard units. (Kent & O’Connor, No. 13 at p. 231) The National 

Association of Home Builders (NAHB) commented that a general contractor usually will not 

have any special HVAC expertise. If regional standards are implemented, a builder is likely to 

use more time and effort double-checking that units are compliant. The extra cost of this effort 

should be included in the payback analysis, the cumulative regulatory burden, the employment 

impact analysis, and the regulatory impact analysis. NAHB also commented that regional 

standards would affect home builders, most of which are small businesses; as such, a regulatory 

flexibility analysis would be necessary. (NAHB, No. 21 at pp. 1, 2). 

For the preliminary analysis, DOE conducted limited interviews with distributors and 

contractors, and sought comment regarding the potential impacts of regional standards as they 

relate to residential central air conditioners and heat pumps. 

Distributors had concerns regarding the implementation of regional standards and the 

potential impact of those standards on their business. Distributors were concerned that possible 

disparities between the regional boundaries for standards and existing distribution boundaries 

may prove problematic. Distributors stated that regional standards may be defined based on 

geographic boundaries composed of state lines, which are usually different than the boundaries 

that affect the composition of markets for central air conditioners and heat pumps. These market 

boundaries are determined by several factors, such as utility service areas, composition of 

existing building types within an area, and the delineation of natural climatic regions. 

Additionally, distributors were concerned about the possible impact of regional standards 

on the efficiency of the distribution chain, and ultimately, their ability to control costs. Similar to 

manufacturers, national and regional distributors stated that they would face decreases in their 

economies of scale, which currently benefit manufacturers of products that can be stocked and 

sold nationwide. Specifically, if certain products could not be sold throughout the entire country, 

then the cost of those products in the regions where they could be sold would be driven up. 

Distributors also stated that climates within a specific geographic region may vary, and certain 

areas within a geographic region may have more limited cooling demand than the surrounding 

areas. As a result, sales in those areas, where high-efficiency cooling equipment would not be as 

well justified, would likely be depressed. Distributors that service areas that lay on borders 

between regions would be particularly affected, as their costs would increase due to the more 

complex and diverse inventories. This would also limit the growth of distributors into 

neighboring areas which fall into a different climate region. DOE seeks further comment 

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regarding the potential impact of regional standards on distributors, dealers, contractors, and 

installers of residential central air conditioners and heat pumps. In addition, DOE is seeking 

market data that will assist in the identification and analysis of the impacts of regional standards 

on distributors, dealers, contractors, and installers. 

DOE plans to address the issues raised in the interviews as well as the comments on 

regional standards. DOE plans to perform a sensitivity analysis of the effects of additional 

inventory costs and carrying charges on firm profitability of typical heating, air-conditioning, 

and refrigeration distributors at the national and regional levels. To conduct this analysis, DOE 

plans to use detailed sample industry data on income statements and balance sheets from 

HARDI’s Profit Reports. Because this source contains data by region and size of firm, DOE 

plans to examine the effects of firm size and region on the profitability calculations. DOE will 

investigate using enterprise sales data from Bureau of the Census County Business Patterns. and 

Bureau of the Census Geographical Area Series for 2002 on border counties for the regions of 

interest to determine the location and net fraction of distributors likeliest to be affected by selling 

in multiple regions. Distribution of air-conditioning wholesalers by size of sales also is available 

in the Bureau of the Census publication Establishment and Firm Size-2002. If similar questions 

concerning elements of the balance sheets and income statements are later raised for contractors 

and installers, similar detailed establishment financial and geographic area data series are also 

available in the 2002 Economic Census for mechanical and general contractors and would allow 

DOE to conduct similar analyses of contractors and installers. 

DOE intends to develop an enforcement plan for regional standards as stated in section 

2.10.3. DOE may also analyze (quantitatively or qualitatively, as data allow) the impacts that 

regional boundaries would have for distributors and dealers. DOE currently does not have data 

available on the potential impact of record-keeping and other administrative compliance costs for 

regional standards on the part of general contractors or other parts of the central air conditioner 

and heat pump distribution channels that would allow DOE to address NAHB’s concern. If such 

data become available, DOE plans to use 2002 Census data identified in this section to analyze 

the effects of such costs on firm profitability in the new chapter on the impacts of the regional 

standards on the distribution channels. 

2.10.3 Enforcement 

As noted above, several comments expressed concerns about enforcement of regional 

standards. HARDI indicated that it has serious concerns that regionalization strategy for central 

air conditioner and heat pump energy conservation standards will be unenforceable. (HARDI, 

No. 32 at p. 5) AHRI also believes that regional standards may be impractical and unenforceable. 

(AHRI, No. 24 at p. 3) ACCA stated their agreement and further commented that regional 

standards will result in confusion to consumers in the marketplace. (ACCA, No. 23 at p. 2) Kent 

& O’Connor stated that when regional boundaries are being drawn, the willingness of a state to 

enforce the standard should be considered. (Kent & O’Connor, No. 13 at p. 240) Trane also 

commented that code officials may be the only entities that could effectively enforce regional 

standards, especially in areas close to regional boundaries. (Trane, No. 16 at p. 5) 

Carrier posed a number of questions for DOE to consider, including: (1) what the 

enforcement mechanism will be; (2) if states will be responsible for enforcing the regional 

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standard; (3) what regulations cover cross state-line transfers of non-compliant products; (4) how 

distributors will supply multiple regions addressed in the enforcement process; and (5) how 

enforcement regulations will address the issue of certain OEM systems that alone cannot meet a 

higher efficiency in one region but may be eligible for sale if an independent manufacturer’s coil 

is used. (Carrier, No. 18 at p. 3) 

ACCA urged DOE not to wait for a regional standards decision before developing an 

enforcement plan, stating that the practicality and feasibility of enforcement should be part of the 

general evaluation of regional standards. (ACCA, No. 23 at p. 2) Lennox agreed that regional 

standards are useless unless the enforcement issues are resolved. (Lennox, No. 13 at p. 395) Joint 

Comment 1 suggested that DOE should consult with industry groups such as HARDI 

(distributors), ACCA, SMACNA, and MCA (contractors) as well as building code officials 

(ICC) and the National Association of State Energy Officials in the development of enforcement 

plans. (Joint Comment 1, No. 25 at p. 9) Carrier suggested that DOE hold sessions with state 

regulators to determine their willingness and ability to enforce regional energy standards. 

(Carrier, No. 18 at p. 4) ACCA encourages DOE to hold another collaborative meeting to discuss 

regional standards enforcement. (ACCA, No. 13 at p. 397) HARDI commented that the U.S. 

Department of Housing and Urban Development was unable to formulate regional criteria due to 

enforcement issues and that enforcement proposals should be made available for public debate. 

(HARDI, No. 13 at p. 398) 

If regional standards are adopted for this rulemaking, EISA 2007 mandates that an 

enforcement plan rulemaking be initiated no later than 90 days after the issuance of the standard 

final rule. 42 U.S.C. 6295(o)(6)(G)(ii)(I). DOE has not yet determined the enforcement 

mechanism for regional standards; however DOE believes that an effective enforcement plan 

will likely be composed of multiple enforcement mechanisms. Among mechanisms DOE is 

considering are: 

1) appropriate modifications to appliance labels to indicate in which regions of the country 

specific equipment is allowed to be installed; 

2)	 requirements that marketing literature for systems clearly indicate in which regions a 

product could be legally installed; 

3)	 encouraging state and local entities to adopt these regional standards in building codes 

and to provide reference to the required minimum efficiencies in required mechanical or 

electrical permits; 

4)	 encouraging states who have regional appliance standards to adopt and codify the 

appropriate regional standards enacted by DOE; 

5)	 clearly indicating in law that installations that don’t meet regional standards could result 

in installers being subject to fines for each occurrence; 

6)	 requirements to certify compliance of installations through warranty registration or other 

registration means; 

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7) an informational program so that consumers are made aware of any regional standards, 

what to look for in purchasing equipment, and what implications there would be for 

improper installation; and 

8)	 competitively-driven enforcement where manufacturers/distributors/contractors report 

other manufacturers/distributors/contractors whose actions result in installations not in 

compliance with Federal standards. 

Certain features of any enforcement plan would be that it not unduly regulate interstate 

commerce or otherwise constrain where a product may be manufactured or through which states 

a product can be transported and that it not place undue financial burden on consumers, 

manufacturers, contractors, distributors, dealers or installers. While DOE believes that much of 

the liability for proper installation will inevitably lie with the installer, it believes that 

manufacturers and distributors can play a role in enforcement through labeling and possibly 

providing data, such as ongoing statistics, regarding non-complying products sold for final 

installation in a given region. 

For the NOPR, as part of its analysis of regional impacts on distributors, dealers, 

contractors, and installers, DOE will analyze California’s Title 24 requirements and other extant 

state-level standards and consider the issues that have developed concerning their enforcement. 

DOE will also seek industry input on the viability of the above enforcement mechanisms, other 

mechanisms DOE should consider, and the extent to which these mechanisms would result in 

additional financial burdens to consumers, manufacturers, contractors, distributors, dealers, and 

installers. DOE will consider and note all comments related to enforcement of regional 

standards submitted before the issuance of an enforcement plan rulemaking. 

2.11 LIFE-CYCLE COST SUBGROUP ANALYSIS 

The LCC subgroup analysis evaluates economic impacts on selected consumers groups 

who might be adversely affected by a change in the national energy conservation standards for 

the considered products. DOE evaluates impacts on particular subgroups of consumers in part by 

analyzing the LCC impacts and PBP for those particular consumers. 

DOE will use the LCC spreadsheet model to evaluate impacts on consumer subgroups. 

DOE can analyze the LCC for any subgroup by applying the LCC spreadsheet model to only that 

subgroup. DOE is particularly sensitive to increases in the consumer price of the considered 

products, wishing to avoid a negative economic impact on any identified consumer subgroup. 

Joint Comment 3 stated that DOE should fully analyze the energy savings potential of 

regional standards. (Joint Comment 3, No. 36 at p. 2) Low-income consumers will be 

disproportionally affected by standard levels unsuited to their region. 

DOE will conduct a regional LCC and PBP analysis that will sample low-income 

households and determine the potential for the proposed standards to disproportionately affect 

them. Low-income households may be disproportionally affected because they may use a 

costlier-than-average mix of debt instruments to pay for first costs. 

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2.12 UTILITY IMPACT ANALYSIS 

The utility impact analysis includes an analysis of the effect of new energy conservation 

standards on the electric and the gas utility industries. For this analysis, DOE adapted National 

Energy Modeling System (NEMS), a large multi-sectoral, partial-equilibrium model of the U.S. 

energy sector that the EIA developed throughout the past decade primarily for preparing EIA’s 

AEO. In previous rulemakings, a variant of NEMS (currently termed NEMS-BT, BT referring to 

DOE’s Building Technologies Program) was developed to address the specific impacts of an 

energy conservation standard. 

Available in the public domain, NEMS produces a widely recognized baseline energy 

forecast for the United States through 2030. The typical NEMS outputs include forecasts of 

electricity sales, prices, and electric generating capacity. DOE conducts the utility impact 

analysis as a scenario that departs from the latest AEO reference case. In other words, the energy 

savings impacts from amended energy conservation standards are modeled using NEMS-BT to 

generate forecasts that deviate from the AEO reference case. 

2.13 ENVIRONMENTAL ASSESSMENT 

The intent of the environmental assessment is to quantify and consider the environmental 

effects of amended energy conservation standards for central air conditioners and heat pumps. 

The primary environmental effects of these standards would be reduced power plant emissions 

resulting from reduced consumption of electricity. DOE will assess these environmental effects 

by using NEMS-BT to provide key inputs to its analysis. The portion of the environmental 

assessment that will be produced by NEMS-BT considers carbon dioxide (CO2), nitrogen oxides 

(NOX), and mercury (Hg). The environmental assessment also considers impacts on SO2 

emissions. After a brief discussion of general methodology, this section will address each of the 

relevant emissions. This section then explains how DOE plans to monetize the benefits 

associated with emissions reductions. 

2.13.1 Carbon Dioxide 

In the absence of any Federal regulation of power plant emissions of CO2, a DOE 

standard is likely to result in reductions of these emissions. The CO2 emission reductions likely 

to result from a standard will be estimated using NEMS-BT and national energy savings 

estimates drawn from the NIA spreadsheet model. The net benefit of the standard is the 

difference between emissions estimated by NEMS-BT at each standard level considered and the 

AEO Reference Case. NEMS-BT tracks CO2 emissions using a detailed module that provides 

results with broad coverage of all sectors and inclusion of interactive effects. 

2.13.2 Sulfur Dioxide 

DOE has preliminarily determined that SO2 emissions from affected Electric Generating 

Units (EGUs) are subject to nationwide and regional emissions cap and trading programs that are 

likely to eliminate the standards’ impact on SO2 emissions. The costs of meeting such emission 

cap requirements are integrated in the electricity prices used in DOE’s analysis of the standards. 

Title IV of the Clean Air Act sets an annual emissions cap on SO2 for all affected EGUs. SO2 

emissions from 28 eastern States and the District of Columbia (DC) are also limited under the 

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Clean Air Interstate Rule (CAIR, published in the Federal Register on May 12, 2005. 70 FR 

25162 (May 12, 2005)), which creates an allowance-based trading program that will gradually 

replace the Title IV program in those States and DC. (The recent legal history surrounding CAIR 

is discussed below.) The attainment of the emissions caps is flexible among EGUs and is 

enforced through the use of emissions allowances and tradable permits. Under existing EPA 

regulations, any excess SO2 emission 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. However, if the standard resulted in a permanent increase 

in the quantity of unused emission allowances, there would be an overall reduction in SO2 

emissions from the standards. While there remains some uncertainty about the ultimate effects of 

efficiency standards on SO2 emissions covered by the existing cap and trade system, the NEMSBT modeling system that DOE plans to use to forecast emissions reductions currently indicates 

that no physical reductions in power sector emissions would occur for SO2. 

Even if there is no significant reduction in the overall emissions of SO2 that results from 

the standard, there may still be some economic benefit from reduced demand for SO2 emission 

allowances that is not fully reflected in the cost savings experienced by individual consumers. 

Electricity savings that decrease the overall demand for SO2 emissions allowances could lower 

allowance prices and thereby result in some economic benefits for all electricity consumers, not 

just those that reduced their electricity use as a result of an efficiency standard. DOE does not 

plan to monetize this particular benefit because the effect on the SO2 allowance price from any 

single energy conservation standard is likely to be small and highly uncertain. 

2.13.3 Nitrogen Oxides 

NEMS-BT also has an algorithm for estimating NOX emissions from power generation. 

The impact of these emissions, however, will be affected by the CAIR, which the Environmental 

Protection Agency (EPA) issued on May 12, 2005. CAIR will permanently cap emissions of 

NOX in 28 eastern states and the District of Columbia. 70 FR 25162 (May 12, 2005). 

Much like SO2 emissions, a cap on NOX emissions means that the amended central air 

conditioner and heat pumps standards may have little or no physical effect on these emissions in 

the 28 eastern States and the DC covered by CAIR. Although CAIR has been remanded to the 

EPA by the DC Circuit, it will remain in effect until it is replaced by a rule consistent with the 

Court’s July 11, 2008, opinion in North Carolina v. EPA. 531 F.3d 896 (DC Cir. 2008); see also 

North Carolina v. EPA, 550 F.3d 1176 (DC Cir. 2008). Because all States covered by CAIR 

opted to reduce NOX emissions through participation in cap-and-trade programs for electric 

generating units, emissions from these sources are capped across the CAIR region. 

Standards may produce an environmental-related economic benefit in the form of lower 

prices for emissions allowance credits. As with SO2 allowance prices, DOE does not plan to 

monetize this particular benefit because the effect on the NOX allowance price from any single 

energy conservation standard is likely small and highly uncertain. 

Accordingly, DOE plans to use NEMS-BT to estimate the emissions reductions from 

possible standards in the 22 States where emissions are not capped. 

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2.13.4 Mercury 

Similar to emissions of SO2 and NOX, future emissions of Hg would have been subject to 

emissions caps. In May 2005, EPA issued the Clean Air Mercury Rule (CAMR). 70 FR 28606 

(May 18, 2005). CAMR would have permanently capped emissions of mercury for new and 

existing coal-fired power plants in all States by 2010. However, on February 8, 2008, the DC 

Circuit issued its decision in New Jersey v. Environmental Protection Agency, in which the DC 

Circuit, among other actions, vacated the CAMR. 517 F.3d 574 (DC Cir. 2008). EPA has 

decided to develop emissions standards for power plants under the Clean Air Act (Section 112), 

consistent with the DC Circuit’s opinion on the CAMR. See 

http://www.epa.gov/air/mercuryrule/pdfs/certpetition_withdrawal.pdf. Pending EPA's 

forthcoming revisions to the rule, DOE is excluding the CAMR from its Environmental 

Analysis. In the absence of CAMR, a DOE standard would likely reduce Hg emissions and DOE 

plans to use NEMS-BT to estimate these emission reductions. 

2.13.5 Particulate Matter 

DOE acknowledges that particulate matter (PM) impacts are of concern due to human 

exposures that can impact health. But impacts of PM emissions reduction are much more 

difficult to estimate than other emissions reductions due to the complex interactions between 

PM, other power plant emissions, meteorology, and atmospheric chemistry that impact human 

exposure to particulates. Human exposure to PM usually occurs at a significant distance from the 

power plants that are emitting particulates and particulate precursors. When power plant 

emissions travel this distance, they undergo highly complex atmospheric chemical reactions. 

Although the EPA does keep inventories of direct PM emissions of power plants, in its source 

attribution reviews, the EPA does not separate direct PM emissions from power plants from the 

sulfate particulates indirectly produced through complex atmospheric chemical reactions. The 

great majority of PM emissions from power plants are of these secondary particles (secondary 

sulfates). Thus, it is not useful to examine how the amended standard impacts direct PM 

emissions independent of indirect PM production and atmospheric dynamics. Therefore, DOE is 

not planning to assess the impact of these standards on particulate emissions. Further, even the 

cumulative impact of PM emissions from power plants and indirect emissions of pollutants from 

other sources is unlikely to be significant. 

2.13.6 Monetization of Emissions Reduction Benefits 

For those emissions for which real national emission reductions are anticipated (CO2, Hg, 

and NOX for 22 states), only ranges of estimated economic values based on environmental 

damage studies of varying quality and applicability are available. Therefore, DOE plans on 

reporting estimates of monetary benefits derived using these values and plans to consider these 

benefits in weighing the costs and benefits of each of the standard levels considered. In 

accordance with U.S. Office of Management and Budget (OMB) guidance, DOE will conduct 

two calculations of the monetary benefits derived using each of the economic values used, one 

using a real discount rate of 3 percent and another using a real discount rate of 7 percent. 

In order to estimate the monetary value of benefits resulting from reduced emissions of 

CO2 emissions, it is DOE’s intent to use in its analysis the most current Social Cost of Carbon 

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(SCC) values developed and/or agreed to by interagency reviews. 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. 

DOE uses the most recent interagency estimates of the potential global benefits resulting 

from reduced CO2 emissions. At the time of this notice, these estimates are $4.7, $21.4, $35.1, 

and $64.9 per metric ton of CO2 (in 2007 dollars). These values are then adjusted to 2009$ using 

the standard GDP deflator value of 2008 and 2009. For emissions (or emission reductions) that 

occur in later years, these 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 will be given to consideration of 

the global benefits of reducing CO2 emissions. 

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 intends to estimate the potential monetary benefit of reduced NOX, and Hg 

emissions resulting from the standard levels it considers. For NOX emissions, available estimates 

suggest a very wide range of monetary values for NOX emissions, ranging from $370 per ton to 

$3,800 per ton of NOX from stationary sources, measured in 2001$ (equivalent to a range of 

$447 to $4,591 per ton in 2009$).). Refer to the OMB, 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,” for additional information. 

For Hg emissions reductions, DOE has previously determined that the impact of mercury 

emissions from power plants on humans is considered highly uncertain. However, DOE 

identified two estimates of the environmental damage of mercury based on two estimates of the 

adverse impact of childhood exposure to methyl mercury on intelligence quotient (IQ) for 

American children, and subsequent loss of lifetime economic productivity resulting from these 

IQ losses. The high-end estimate is based on an estimate of the current aggregate cost of the loss 

of IQ in American children that results from exposure to mercury of U.S. power plant origin 

($1.3 billion per year in year 2000$), which works out to $33.7 million per ton emitted per year 

(in 2009$). Refer to L. Trasande et al., “Applying Cost Analyses to Drive Policy that Protects 

Children,” 1076 Ann. N.Y. Acad. Sci. 911 (2006) for additional information. The low-end 

estimate is $0.66 million per ton emitted (in 2004$) or $0.749 million per ton in 2009$, which 

will be updated to 2009$. DOE derived this estimate from a published evaluation of mercury 

control using different methods and assumptions from the first study but also based on the 

present value of the lifetime earnings of children exposed. See Ted Gayer and Robert Hahn, 

“Designing Environmental Policy: Lessons from the Regulation of Mercury Emissions,” 

Regulatory Analysis 05–01, American Enterprise Institute-Brookings Joint Center for Regulatory 

Studies, Washington, DC (2004). A version of this paper was published in the Journal of 

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Regulatory Economics in 2006. The estimate was derived by back-calculating the annual 

benefits per ton from the net present value of benefits reported in the study. 

For more detail on the environmental assessment, refer to the environmental assessment 

report in the preliminary TSD. 

2.14 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 plants that produce the covered 

products and at the affiliated distribution and service companies. DOE evaluated direct 

employment impacts in the manufacturer impact analysis. Indirect employment impacts may 

result from consumers shifting expenditures between goods (the substitution effect) and from 

changes in income and overall expenditure levels (the income effect). DOE will use PNNL’s 

impact of sector energy technologies (ImSET) model to investigate the combined direct and 

indirect employment impacts. The ImSET model, which was developed for DOE’s Office of 

Planning, Budget, and Analysis, estimates the employment and income effects energy-saving 

technologies produce in buildings, industry, and transportation. Compared with simple economic 

multiplier approaches, ImSET allows for more complete and automated analysis of the economic 

impacts of energy conservation investments. 

2.15 REGULATORY IMPACT ANALYSIS 

In the NOPR, DOE will prepare an RIA pursuant to Executive Order 12866, Regulatory 

Planning and Review, 58 FR 51735, October 4, 1993. The RIA 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 addresses the potential for non-regulatory approaches to 

supplant or augment energy conservation standards in order to improve the energy efficiency or 

reduce the energy consumption of the products covered under this rulemaking. 

DOE recognizes that non-regulatory efforts by manufacturers, utilities, and other 

interested parties can substantially affect energy efficiency or reduce energy consumption. DOE 

will base its assessment on the actual impacts of any such initiatives to date, but also will 

consider information presented by interested parties on the impacts existing initiatives might 

have in the future. 

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11. U.S. Department of Energy–Office of Energy Efficiency and Renewable Energy, Energy 

Conservation Program: Energy Conservation Standards for General Service Fluorescent 

Lamps and Incandescent Reflector Lamps; Proposed Rule. Federal Register 2009 74(69): 

16920–16968. 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 3. MARKET AND TECHNOLOGY ASSESSMENT 

TABLE OF CONTENTS 

3.1 INTRODUCTION ............................................................................................................ 3-1
 

3.1.1 Definitions............................................................................................................. 3-1
 

3.1.2 Product Classes...................................................................................................... 3-2
 

3.1.3 Test Procedures ..................................................................................................... 3-3
 

3.2 MARKET ASSESSMENT ............................................................................................... 3-3
 

3.2.1 Trade Associations ................................................................................................ 3-4
 

3.2.2 Manufacturers and Market Share .......................................................................... 3-5
 

3.2.3 Regulatory Programs............................................................................................. 3-8
 

3.2.4 Non-Regulatory Programs................................................................................... 3-10
 

3.2.5 Industry Cost Structure........................................................................................ 3-15
 

3.2.6 Equipment Lifetime............................................................................................. 3-16
 

3.2.7 Market Performance Data ................................................................................... 3-17
 

3.2.8 Historical Shipments and Efficiencies ................................................................ 3-27
 

3.2.9 Saturations in U.S. Households........................................................................... 3-30
 

3.3 TECHNOLOGY ASSESSMENT................................................................................... 3-31
 

3.3.1 Compressor Improvements.................................................................................. 3-31
 

3.3.2 Fan System Improvements .................................................................................. 3-32
 

3.3.3 Expansion Valve Improvements ......................................................................... 3-33
 

3.3.4 Heat Exchanger Technologies and Improvements.............................................. 3-34
 

3.3.5 Designs Relevant Only to Heat Pumps ............................................................... 3-37
 

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EERE-2008-BT-STD-0006 COMMENT 54
LIST OF TABLES 

Table 3.2.1 AHRI Directory of Certified Product Performance Classifications for Residential 

Central Air Conditioners and Heat Pumps................................................................................... 3-5
 

Table 3.2.2 Manufacturer Brand Names Found in the AHRI’s Directories of Certified Product 

Table 3.2.3 Current Federal Energy Conservation Standards for Residential Central Air 

Table 3.2.4 Canadian Energy Conservation Standards for Residential Central Air Conditioners 

Table 3.2.5 ENERGY STAR Levels for Split System and Single Package Residential Central Air 

Table 3.2.8 Rebate Programs Offered by Local Utilities for Residential Central Air Conditioners
 

Table 3.2.9 Rebate Programs Offered by Local Utilities for Residential Central Air-Cooled Heat 

Table 3.2.10 Air Conditioning and Warm Air Heating Equipment Industry Employment and 

Table 3.2.12 Industry Cost Structure Developed from SEC Data Error! Bookmark not defined.
 

Table 3.2.13 Types of Models Listed in the AHRI Directory of Certified Product Performance....
 

Performance for Residential Central Air Conditioners and Heat Pumps .................................... 3-6
 

Conditioners and Heat Pumps...................................................................................................... 3-9
 

and Heat Pumps ......................................................................................................................... 3-10
 

Conditioners and Heat Pumps.................................................................................................... 3-11
 

Table 3.2.6 CEE Tiers for Residential Central Air Conditioners and Heat Pumps................... 3-12
 

Table 3.2.7 Federal Tax Credits for Residential Central Air Conditioners and Heat Pumps.... 3-12
 

.................................................................................................................................................... 3-13
 

Pumps......................................................................................................................................... 3-14
 

Payroll Data ............................................................................................................................... 3-15
 

Table 3.2.11 Air Conditioning and Warm Air Heating Equipment Industry Cost Data .......... 3-16
 

.................................................................................................................................................... 3-17
 

LIST OF FIGURES 

Figure 3.2.1 2007 Market Shares for Unitary Air Conditioners and Heat Pumps...................... 3-7
 

Figure 3.2.3 SEER Ratings for Single Package Central Air Conditioners in the AHRI Certified 

Figure 3.2.4 SEER Ratings for Single Package Heat Pumps in the AHRI Certified Product 

Figure 3.2.5 SEER Ratings for Split System Central Air Conditioners in the AHRI Certified 

Figure 3.2.6 SEER Ratings for Split System Heat Pumps in the AHRI Directory of Certified 

Figure 3.2.7 SEER Ratings for SDHV Systems in the AHRI Directory of Certified Product 

Figure 3.2.8 HSPF Ratings for Single Package Heat Pumps in AHRI’s Directory of Certified 

Figure 3.2.9 HSPF Ratings for Split System Heat Pumps in AHRI’s Directory of Certified 

Figure 3.2.10 HSPF Ratings for SDHV Heat Pumps in AHRI’s Directory of Certified Product 

Figure 3.2.11 Average SEER Ratings at Each Cooling Capacity for Single Package Air 

Product Performance Directory ................................................................................................. 3-18
 

Performance Directory............................................................................................................... 3-18
 

Product Performance Directory ................................................................................................. 3-19
 

Product Performance.................................................................................................................. 3-19
 

Performance ............................................................................................................................... 3-20
 

Product Performance.................................................................................................................. 3-21
 

Product Performance.................................................................................................................. 3-21
 

Performance ............................................................................................................................... 3-22
 

Conditioners in AHRI’s Directory of Certified Product Performance ...................................... 3-23
 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.12 Average SEER Ratings at Each Cooling Capacity for Split System Air 

Conditioners in AHRI’s Directory of Certified Product Performance ...................................... 3-23
 

Figure 3.2.13 Average SEER Rating at Each Cooling Capacity for Single Package Heat Pumps 

Figure 3.2.14 Average SEER Rating at Each Cooling Capacity for Split System Heat Pumps in 

Figure 3.2.15 Average SEER Rating at Each Cooling Capacity for SDHV Systems in the AHRI
 

Figure 3.2.16 Average HSPF at Each Cooling Capacity for Single Package Heat Pumps in the 

Figure 3.2.17 Average HSPF Rating at Each Cooling Capacity for Split System Heat Pumps in 

Figure 3.2.18 Average HSPF Rating at Each Cooling Capacity for SDHV Heat Pumps in the 

in the AHRI Directory of Certified Product Performance ......................................................... 3-24
 

the AHRI Directory of Certified Product Performance ............................................................. 3-24
 

Directory of Certified Product Performance.............................................................................. 3-25
 

AHRI Directory of Certified Product Performance ................................................................... 3-26
 

the AHRI Directory of Certified Product Performance ............................................................. 3-26
 

AHRI Directory of Certified Product Performance ................................................................... 3-27
 

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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 carried out in support of the ongoing energy conservation standards 

rulemaking for residential central air conditioners and heat pumps. It consists of two sections: the 

market assessment and the technology assessment. 

The goal of the market and technology assessment is to develop a qualitative and 

quantitative characterization of the residential central air conditioner and heat pump industry and 

market structure, based on publicly available information and data and information submitted by 

manufacturers and other stakeholders. Publicly available information includes the equipment 

certification directory from the Air-Conditioning, Heating and Refrigeration Institute (AHRI), as 

well as Current Industry Reports (CIR) and Annual Survey of Manufactures (ASM) from the 

U.S. Census Bureau. Issues addressed include: manufacturer characteristics and market shares; 

existing regulatory and non-regulatory efficiency improvement initiatives; product classes; and 

trends in the equipment markets and characteristics. The technology assessment is a preliminary 

list of technologies that can improve the efficiency of residential central air conditioners and heat 

pumps. These technologies are considered in the screening analysis. 

Residential central air conditioners and heat pumps are products that are used to centrally 

heat and/or cool residential buildings. These products, also called unitary air conditioners and 

heat pumps, are limited to cooling capacities of less than 65,000 Btu/hr (5.4 tons) and do not 

include room air conditionersa

 or packaged terminal air conditioners and heat pumps.b 

3.1.1 Definitions 

The Energy Policy and Conservation Act (EPCA) defines a “central air conditioner” as “a 

product, other than a packaged terminal air conditioner, which is powered by single-phase 

electric current, air cooled, rated below 65,000 Btu per hour, not contained within the same 

cabinet as a furnace, the rated capacity of which is above 225,000 Btu per hour, and is a heat 

pump or a cooling only unit.” (42 U.S.C. 6291(21)(A)-(E)) DOE has incorporated this definition 

into its regulations at 10 CFR 430.2. 

a

 “Room air conditioner” is defined in 10 CFR 430.2 as “a consumer product, other than a ‘packaged terminal air 

conditioner,’ which is powered by a single phase electric current which is an encased assembly designed as a unit 

for mounting in a window or through the wall for the purpose of providing delivery of conditioned air to an enclosed 

space. It includes a prime source of refrigeration and may include a means for ventilating and heating.” For more 

information on room air conditioners, see 

http://www.eere.energy.gov/buildings/appliance_standards/residential/room_ac.html. b

 “Packaged terminal air conditioner” is defined in 10 CFR 430.2 as “a wall sleeve and a separate unencased 

combination of heating and cooling assemblies specified by the builder and intended for mounting through the wall. 

It includes a prime source of refrigeration, separable outdoor louvers, forced ventilation, and heating availability 

energy.” “Packaged terminal heat pump” is defined in 10 CFR 430.2 as “a packaged terminal air conditioner that 

utilizes reverse cycle refrigeration as its prime heat source and should have supplementary heating availability by 

builder’s choice of energy.” For more information on package terminal air conditioners and heat pumps, see 

http://www.eere.energy.gov/buildings/appliance_standards/commercial/packaged_ac_hp.html. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

EPCA defines a “heat pump” as “a product, other than a packaged terminal heat pump, 

which consists of one or more assemblies, powered by single-phase electric current, rated below 

65,000 Btu per hour, utilizing an indoor conditioning coil, compressor, and refrigerant-tooutdoor air heat exchanger to provide air heating, and may also provide air cooling, 

dehumidifying, humidifying circulating, and air cleaning.” (42 U.S.C. 6291(24)(A)-(E)) DOE 

has incorporated this definition into its regulations at 10 CFR 430.2. 

3.1.2 Product Classes 

Residential central air conditioners and heat pumps are divided into nine product classes 

based on physical characteristics of the product that affect performance. Key physical 

characteristics include product type (i.e., air conditioner or heat pump), whether the unit is a 

single package or has individual indoor and outdoor sections, and space constraints that relate to 

product utility. 

3.1.2.1 Existing Product Classes 

The existing Federal energy conservation standards for residential central air conditioners 

and heat pumps went into effect on January 23, 2006. 10 CFR Part 430.32(c)(2) lists the nine 

product classes of residential central air conditioners and heat pumps and their corresponding 

energy conservation standards. The existing product classes are: 

• Split-system air conditioners 

• Split-system heat pumps 

• Single-package air conditioners 

• Single-package heat pumps 

• Through-the-wall air conditioners and heat pumps – split system 

• Through-the-wall air conditioners and heat pumps – single package 

• Small duct, high velocity systems 

• Space-constrained air conditioners 

• Space-constrained heat pumps 

3.1.2.2 Rulemaking Product Classes 

For this residential central air conditioner and heat pump rulemaking, DOE maintained 

the existing product classes. However, two of the existing product classes, through-the-wall air 

conditioners and heat pumps – split system and through-the-wall air conditioners and heat pumps 

– single package, no longer existc

, which is subsequent to the effective date of this rulemaking. 

Therefore, DOE did not consider those two product classes separately (instead DOE considered 

them to be space-constrained products), and examined only seven product classes for this 

residential central air conditioner and heat pump rulemaking. The seven product classes DOE 

examined are: 

c

 As defined in 10 CFR 430.2, the through-the-wall product class applies only to products manufactured prior to 

January 23, 2010. This provision eliminates through-the-wall units as a separate product class after this date. 

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EERE-2008-BT-STD-0006 COMMENT 54
• Split-system air conditioners 

• Split-system heat pumps 

• Single-package air conditioners 

• Single-package heat pumps 

• Small duct, high velocity systems 

• Space-constrained air conditioners 

• Space-constrained heat pumps 

3.1.3 Test Procedures 

The test procedures for central air conditioners and heat pumps are codified in 10 CFR 

430, Subpart B, Appendix M. Most aspects of the existing test procedure for central air 

conditioners and heat pumps date back to its original publication in the Federal Register on 

December 27, 1979. 44 FR 76700. DOE modified the test procedure on March 14, 1988, to cover 

variable-speed central air conditioners and heat pumps, to address testing of split non-ducted 

units, and to change the method used for crediting heat pumps that provide a demand defrost 

capability. 53 FR 8304. 

A further revision of the test procedure for central air conditioners and heat pumps was 

published as a final rule on October 11, 2005 and became effective on April 10, 2006. 70 FR 

59122. Generally, the October 2005 final rule added new sections, revised several sections, and 

re-organized the test procedure in order to eliminate the need for several test procedure waivers 

and to make the test procedure more chronological in its progression. The revisions to the test 

procedure did not alter the minimum energy conservation standards in effect for central air 

conditioners and heat pumps. On July 20, 2006, DOE published a proposed rule to consider 

further changes to the test procedure in response to issues raised by stakeholders prior to the 

publication of the October 11, 2005, final rule. 71 FR 41320. DOE determined that it was 

appropriate to consider additional modifications to the test procedure for the following reasons: 

(1) to implement test procedure revisions that are needed because of new energy conservation 

standards for small-duct, high-velocity (SDHV) systems; (2) to better address test procedure 

waivers for multi-split systems; and (3) to address sampling and rating issues that have been 

raised since new minimum energy conservation standards for these products became effective on 

January 23, 2006. Id. at 41321-22 A final rule adopting additional amendments to the central air 

conditioner and heat pump test procedures related to these issues was published on October 22, 

2007, which became effective on April 21, 2008. 72 FR 59906. Subsequent waivers granted for 

residential modulating multi-split systems terminated on the effective date of the latest test 

procedure final rule. 72 FR at 59906-07. 

3.2 MARKET ASSESSMENT 

The following market assessment identifies manufacturer trade associations, domestic 

and international manufacturers of residential central air conditioners and heat pumps and their 

corresponding market shares, regulatory and non-regulatory programs. The market assessment 

also describes the cost structure for the residential central air conditioner and heat pump industry, 

and summarizes relevant market performance data. 

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EERE-2008-BT-STD-0006 COMMENT 54
3.2.1 Trade Associations 

DOE identified AHRI as the only trade group that supports, or has an interest in, the 

residential central air conditioner and heat pump industry. 

AHRI is a national trade association of manufacturers of residential, commercial, and 

industrial appliances and equipment, components, and related products. AHRI was established in 

January of 2008 when the Air-Conditioning and Refrigeration Institute (ARI) merged with the 

Gas Appliance Manufacturers Association (GAMA). AHRI’s member companies are responsible 

for over 90 percent of the residential and commercial air conditioning and space heating 

equipment sold in North America.1

 AHRI develops and publishes technical standards for 

residential and commercial equipment using rating criteria and procedures for measuring and 

certifying equipment performance. AHRI also participates in developing international standards 

and has established a policy of adopting international standards for use in the United States when 

technologically and economically feasible. 

AHRI administers the ARI Performance Certified programs that test and certify the 

performance of cooling equipment. AHRI maintains the AHRI Directory of Certified Product 

Performance that lists all products that have been certified by the AHRI. AHRI maintains 

certified performance directories for both air conditioners and heat pumps rated below 65,000 

Btu/h. The AHRI directories subdivide these products based upon certain defining 

characteristics, such as single package or split system and coil only or coil and blower 

combinations. Table 3.2.1 shows the AHRI classifications where products are available in the 

AHRI directories of certified products, along with the corresponding DOE product classes for 

this rulemaking. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 3.2.1 AHRI Directory of Certified Product Performance Classifications for 

Residential Central Air Conditioners and Heat Pumps 

DOE Product Class AHRI Classifications* 

Split system air conditioners RCU-A-C 

RCU-A-CB 

RCU-A-CB-O 

RCUY-A-CB 

RCUY-A-CB-O 

RC-A 

Split system heat pumps HRC-A-C 

HRC-A-CB 

HRCU-A-C 

HRCU-A-CB 

HRCU-A-CB-O 

HORC-A-C 

HORCU-A-C 

HORCU-A-CB 

Single package air conditioners SP-A 

SPY-A 

Single package heat pumps HSP-A 

Small duct, high velocity systems SDHV-RCU-A-CB 

SDHV-HRCU-A-CB 

SDHV-HORCU-A-CB 

Space constrained products – air conditioners** TTW-RCU-A-C 

TTW-RCU-A-CB 

Space constrained products – heat pumps** TTW-HRCU-A-C 

TTW-HRCU-A-CB 

*The classifications listed are only those with products available in the AHRI Directories of Certified Product 

Performance for central air conditioners and heat pumps. For more information on AHRI classifications and their 

definitions, visit www.ahridirectory.org/ahriDirectory/pages/fieldHelp.aspx?program=AC&controlID=ariType for 

air conditioners, or www.ahridirectory.org/ahriDirectory/pages/fieldHelp.aspx?program=HP&controlID=ariType for 

heat pumps. 

**The AHRI Directory of Certified Performance did not list any space constrained products as of March 16, 2009. 

However, after January 23, 2010 (which is after the effective date for this rulemaking) the Through-the-wall 

equipment classes will expire, at which time, they will become part of the space constrained product classes. 

3.2.2 Manufacturers and Market Share 

DOE examined AHRI’s Directory of Certified Product Performance for residential 

central air conditioners and heat pumps to identify residential central air conditioner and heat 

pump manufacturers. DOE identified 45 separate companies that manufacture and market air 

conditioner and heat pump systems and coils. The manufacturers found in the AHRI Directories 

of Certified Product Performance for residential central air conditioners and heat pumps are 

listed in Table 3.2.2, along with their parent company in parentheses, if applicable. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 3.2.2 Manufacturer Brand Names Found in the AHRI’s Directories of Certified 

Product Performance for Residential Central Air Conditioners and Heat Pumps2 

Aaon, Inc. Lennox International National Coil Company 

Aire-Flo Friedrich Air Conditioning Co. (US 

Natural Resources, Inc.) 

National Comfort Products 

(National Refrigeration and Air 

Conditioning Products, Inc.) 

Airquest Fujitsu General America, Inc. (Fujitsu 

General Group) 

Nutone 

Airwell-Fedders North America, 

Inc. 

GD Midea Commercial AirConditioning Equipment Co., Ltd. Quietside 

Bard Manufacturing Company Goodman/Amana (Goodman Global, 

Inc.) 

Rheem/Ruud (Paloma Global) 

Beutler Corporation Grandaire Style Crest Products 

Broan Haier America (Haier Group) Summit Manufacturing, Inc. 

Century (Heat Controller) Heat Controller, Inc. Texas Furnace, LLC 

Cold Point Corp. Intertherm Thermo Products, Inc. (Burnham 

Holdings, Inc.) 

Dayton Electric Manufacturing 

Company (WW Grainger, Inc.) 

Kenmore (Sears Holdings Corporation) Trane/American Standard 

(Ingersoll Rand) 

Eair LLC LG Electronics, Inc. Unitary Products Group 

(York/Johnson Controls) 

Ecotemp Mammoth, Inc. (Thomas H. Lee 

Partners, LP) 

United Refrigeration Distributors, 

Inc. 

Enviromaster International (ECR 

International, Inc.) 

McQuay International (Daikin 

Industries, Ltd.) 

V-Aire 

Espitech, LLC Mitsubishi Electric and Electronics 

USA, Inc. 

Whirlpool 

International Comfort Products ­

Carrier/UTC 

Nordyne Xenon 

Figure 3.2.1 displays the 2007 market shares for the residential central air conditioner 

market. The 7 largest residential central air conditioner and heat pump manufacturers controlled 

97 percent of the market. The seven largest manufacturers for the year 2007 are UTC/Carrier, 

Goodman, American Standard (Trane)d

, Lennox, Rheem, York and Nordyne. 

d

 Prior to 2007, Trane was a subsidiary of American Standard Companies. On November 28, 2007 Trane separated 

from the two other branches of American Standard Companies. On June 5, 2008, Ingersoll Rand acquired Trane. For 

more information, visit www.trane.com/Corporate/About/history.asp. 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.1 2007 Market Shares for Unitary Air Conditioners and Heat Pumps3 

3.2.2.1 Small Businesses 

DOE considers the possibility of small businesses being particularly impacted by the 

promulgation of minimum energy conservation standards for residential central air conditioners 

and heat pumps. The Small Business Administration (SBA) defines small business 

manufacturing enterprises for residential central air conditioners and heat pumps as having 750 

employees or fewer.4 SBA lists small business size standards that are matched to industries as 

they are described in the North American Industry Classification System (NAICS). A size 

standard is the largest that a for-profit concern can be and still qualify as a small business for 

Federal Government programs. These size standards are generally the average annual receipts or 

the average employment of a firm. For residential central air conditioners and heat pumps, the 

size standard is matched to NAICS code 333415, Air-Conditioning and Warm Air Heating 

Equipment and Commercial and Industrial Refrigeration Equipment Manufacturing, which has a 

size standard of 750 employees. 

DOE further studied the potential impacts on these small businesses in detail and 

presented the results in manufacturer impact analysis (MIA) (Chapter 12 of this TSD). DOE has 

identified the following as small business residential central air conditioner and heat pump 

manufacturers: 

• Aire-Flo 

• Airquest 

• Bard Manufacturing Company 

• Beutler Corporation 

• Heat Controller 

• Cold Point Corporation 

• Eair, LLC 

• Enviromaster International 

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EERE-2008-BT-STD-0006 COMMENT 54
 

•	 Espitech, LLC 

•	 National Coil Company 

•	 National Comfort Products 

•	 Quietside 

•	 Style Crest Products 

•	 Summit Manufacturing, Inc. 

•	 Texas Furnace, LLC 

3.2.2.2 Mergers and Acquisitions 

A trend in the residential central air conditioning and heat pump industry over the past 

decades has been the consolidation of major manufacturers. In the last ten years or so, the seven 

major manufacturers (i.e., Goodman, Lennox, Carrier, York, Rheem, Nordyne, and Trane) have 

gone through various mergers and acquisitions, and have materialized as differentiated leaders in 

the air conditioning and heat pump manufacturing industry. A brief summary of the recent 

history of each of the seven largest manufacturers is as follows: 

•	 Goodman Global, Inc. was founded and purchased Janitrol in 1982. In 1997, 

Goodman acquired the Amana brand. 

•	 Lennox Industries is a subsidiary of Lennox International, Inc., a holding company 

that was created in 1984. Lennox International acquired Armstrong Air Conditioning 

Inc. in 1988. In 1999, Lennox International completed an Initial Public Offering and 

became a public company. 

•	 Carrier has been a wholly-owned subsidiary of United Technologies Corporation 

since 1979. In 2004, Carrier Corporation acquired Linde Refrigeration. 

•	 York Unitary Products Group and York International are subsidiaries of Johnson 

Controls, Inc. Johnson Controls, Inc. purchased York in 2005. 

•	 Rheem is a privately held firm that was acquired by Paloma Industries of Japan in 

1987. Paloma Industries also acquired Rheem Australia (Solahart) in 2002. 

•	 Nordyne is a subsidiary of the privately held Nortek, Inc. It introduced the Frigidaire, 

Tappan, and Philco brands as potential replacement HVAC brands in 1998. It also 

added the Gibson and Kelvinator brands in 1999. In 2002, the firm added the 

Westinghouse brand as a residential product line. The Mammoth commercial line was 

introduced as a part of Nordyne in 2003. Most recently, Nordyne added the Broan 

brand of products in 2005. 

•	 Trane Inc. was acquired by American Standard Companies in 1984. In 2007 Trane 

separated from American Standard and was subsequently bought by Ingersoll-Rand in 

2008. 

3.2.3 Regulatory Programs 

The following section details current regulatory programs mandating energy conservation 

standards for residential central air conditioners and heat pumps. Section 3.2.3.1 discusses 

current Federal energy conservation standards. Sections 3.2.3.2 and 3.2.3.3 review standards in 

both Canada and Mexico that may impact the companies servicing the North American market. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

3.2.3.1 Current Federal Energy Conservation Standards 

Part A of Title III of EPCA addresses the energy conservation standards for consumer 

products other than automobiles, which include residential central air conditioners and heat 

pumps. (42 U.S.C. 6291-6309) The most recent Federal standards for residential central air 

conditioners and heat pumps went into effect on January 23, 2006 and are codified in? 10 CFR 

Part 430.32. Table 3.2.3 presents the current Federal energy conservation standards for 

residential central air conditioners and heat pumps as presented in part (c)(2) of 10 CFR Part 

430.32. 

Table 3.2.3 Current Federal Energy Conservation Standards for Residential Central Air 

Conditioners and Heat Pumpse 

Product class SEER* HSPF** 

(i) Split system air conditioners 13.0 -

(ii) Split system heat pumps 13.0 7.7 

(iii) Single package air conditioners 13.0 -

(iv) Single package heat pumps 13.0 7.7 

(v)(A) Through-the-wall air conditioners and heat pumps-split 

system*** 

10.9 7.1 

(v)(B) Through-the-wall air conditioners and heat pumps-single 

package*** 

10.6 7.0 

(vi) Small duct, high velocity systems 13.0 7.7 

(vii)(A) Space constrained products-air conditioners 12.0 -

(vii)(B) Space constrained products-heat pumps 12.0 7.4 

*SEER is seasonal energy efficiency ratio. 

**HSPF is heating seasonal performance factor for Region IV. 

***As defined in 10 CFR Part 430.2, this product class applies to products manufactured before January 23, 2010. 

3.2.3.2 Canadian Energy Conservation Standards 

The Natural Resources Canada (NRCan) Office of Energy Efficiency regulation 

mandates minimum energy conservation standards for residential central air conditioners and 

heat pumps. These standards apply to single package and split system air-source air conditioners 

and heat pumps with a cooling capacity less than 65,000 Btu/h. The current standards went into 

effect November 2006, and are shown in Table 3.2.4. 

e Current Federal energy conservation standards for residential central air conditioners taken from 10 CFR 

430.32(c)(2). 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table 3.2.4 Canadian Energy Conservation Standards for Residential Central Air 

Conditioners and Heat Pumps5 

Product Minimum Energy 

Performance Standard 

Air Conditioners – single package & split-system – cooling SEER = 13 

Heat Pumps – single package & split–system – cooling SEER = 13 

Heat Pumps – single package & split system – heating HSPF V* = 6.7 

AC & HP – through–the–wall, cooling – (until January 22, 2010) SEER = 10.9 

AC & HP – through–the–wall, cooling – (after January 23, 2010) SEER = 12 

Heat pumps – through–the–wall – heating – (until January 22, 2010) HSPF V = 6.2 

Heat Pumps – through–the–wall – heating – (after January 23, 2010) HSPF V = 6.4 

AC & HP – space–constrained – cooling SEER = 12 

Heat pumps – space–constrained – heating HSPF V = 6.4 

AC & HP – small duct, high velocity (SDHV) – cooling SEER = 11 

*HSPF V is the Heating Seasonal Performance Factor – Region V. U.S. energy conservation standards specify 

HSPF as HSPF IV (i.e. HSPF – Region IV). HSPF V = HSPF IV/1.15. 

3.2.3.3 Mexican Energy Conservation Standards 

The National Commission for Energy Saving (CONAE)f is the agency responsible for 

developing, updating, and implementing Mexican official standards of energy efficiency. 

CONAE published NOM-011-ENER-2006 (which updated previous standard effective in 2002) 

in June 2007. The standards prescribe minimum efficiencies for central, package, and split 

system central air conditioners with cooling capacities between 30,000 and 65,000 Btu/hg at a 

minimum of 13 SEER.h 

Table 3.2.5 Mexican Energy Conservation Standards for Residential Central Air 

Conditioners6 

Product 

Minimum Energy 

Performance Standard 

Air Conditioners – single package & split-system – cooling SEER = 13 

3.2.4 Non-Regulatory Programs 

DOE identified several non-regulatory programs aimed at improving the energy 

efficiency of residential central air conditioners and heat pumps. DOE reviewed two programs 

based on voluntary efficiency targets for residential central air conditioners and air-source heat 

pumps: the ENERGY STAR program and the Consortium for Energy Efficiency (CEE) 

initiative. In addition, DOE identified rebate programs for residential purchasers of higherefficiency central air conditioners and heat pumps, DOE also identified Federal and State tax 

f

 For more information visit www.conae.gob.mx/wb/CONAE/english/_rid/6600?page=1. g

 Cooling capacity is specified in the standard as 8,800W to 19,050W.
 h

 Mexican efficiency standards for central air conditioners are specified in terms of Relación de eficiencia energética
 

estacional (REEE). NOM-011-ENER-2006 mandates a minimum efficiency of 3.81 REEE, which is equivalent to
 

13 SEER. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

credits for residential consumers of higher-efficiency central air conditioners and heat pumps. 

DOE reviewed Federal procurement specifications for these products as well. 

3.2.4.1 Voluntary Energy Efficiency Targets 

Energy Star 

ENERGY STARi is a voluntary labeling program conducted by the U.S. Environmental 

Protection Agency (EPA) and DOE that identifies and promotes energy-efficient products. To 

qualify, a product must usually exceed federal minimum standards by a specified amount, or if 

no federal standard exists, it must meet minimum efficiency levels set by the program and/or 

exhibit selected energy saving features. ENERGY STAR creates minimum energy efficiency 

specifications for various products, including split system and single package air conditioners 

and heat pumps. ENERGY STAR originally set specifications for central air conditioners and 

heat pumps in 1995, followed by revisions in 2002, 2006, and 2009. The current (2009) 

ENERGY STAR levels are shown in Table 3.2.5. 

Table 3.2.5 ENERGY STAR Levels for Split System and Single Package Residential 

Central Air Conditioners and Heat Pumps 7 

Product Class SEER Rating EER Rating* HSPF Rating 

Split system air conditioners 14.5 12.0 -

Split system heat pumps 14.5 12.0 8.2 

Single package air conditioners 14.0 11.0 -

Single package heat pumps 14.0 11.0 8.0 

*EER is energy efficiency ratio. 

Consortium for Energy Efficiency 

The CEE Residential Central Air Conditioner and Heat Pump Initiative promotes the use 

of high-efficiency residential central air conditioners and heat pumps, along with proper 

installation and sizing of these products. CEE identifies three tiers of efficiency for split system 

central air conditioners, and two tiers of efficiency for split system heat pumps and single 

package central air conditioners and heat pumps. For split system central air conditioners and 

package central air conditioners and heat pumps, the CEE Tier 1 levels are the same as the 

ENERGY STAR levels. The CEE tier requirements are shown in Table 3.2.6. 

i

 For more information, visit www.energystar.gov. 

3-11 

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Table 3.2.6 CEE Tiers for Residential Central Air Conditioners and Heat Pumps8 

Product Class CEE Tier SEER 

Requirement 

EER 

Requirement 

HSPF 

Requirement 

Split System Central Air Conditioners Tier 1 14.5 12.0 -

Tier 2 15.0 12.5 -

Tier 3 16.0 or higher 13.0 or higher -

Single Package Central Air Conditioners Tier 1 14.0 11.0 -

Tier 2 14.0 or higher 12.0 or higher -

Split System Heat Pumps Tier 1 14.5 12.0 8.5 

Tier 2 15.0 or higher 12.5 or higher 8.5 or higher 

Single Package Heat Pumps Tier 1 14.0 11.0 8.0 

Tier 2 14.0 or higher 12.0 or higher 8.0 or higher 

3.2.4.2 Consumer Rebate Programs 

DOE has identified numerous rebate programs that are available to purchasers of new 

residential central air conditioners or heat pumps. These rebates are offered by electric utility 

companies or other agencies to residential consumers who purchase higher-efficiency units. 

Appendix 3-A provides a listing of rebates for residential central air conditioners and heat 

pumps identified by DOE. 

3.2.4.3 Consumer Tax Credits 

Federal Tax Credits 

DOE reviewed the Federal tax credit that provides consumers a credit toward their 

Federal income tax if they purchase qualifying residential central air conditioners or heat pumps. 

These tax credits apply only to products being installed in existing homes; they do not apply to 

central air conditioners and heat pumps for new housing construction. This Federal tax credit is 

30 percent of the installation cost (equipment and labor) to the consumer of the new air 

conditioner or heat pump, with a maximum limit of $1500. To qualify for the Federal tax credit, 

products must meet varying levels of efficiency depending on the product class. Table 3.2.7 

shows the required efficiency level for each product class, along with the amount of the Federal 

tax credit available. 

Table 3.2.7 Federal Tax Credits for Residential Central Air Conditioners and Heat Pumps9 

Product EER 

Requirement 

SEER 

Requirement 

HSPF 

Requirement 

Available Tax Credit 

Central Air Conditioners 

– Split Systems 

≥ 13.0 ≥16.0 N/A 30% of cost, up to $1,500 

Central Air Conditioners 

– Single Package 

≥12.0 ≥ 14.0 N/A 30% of cost, up to $1,500 

Air Source Heat Pumps – 

Split Systems 

≥ 12.5 ≥15.0 ≥ 8.5 30% of cost, up to $1,500 

Air Source Heat Pumps – 

Single Package 

≥ 12.0 ≥14.0 ≥8.0 30% of cost, up to $1,500 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

State Tax Credits 

DOE also identified four states that have tax credits for central air conditioners and heat 

pumps: Montana, Oregon, Indiana, and Kentucky. 

Montana has had an Energy Conservation Tax Credit for residential energy conservation 

measures since 1998.10,11 The tax credit covers a variety of residential energy and water 

efficiency installations, including ENERGY STAR heating/cooling equipment. The amount of 

the credit increased in 2002 from 5 percent of equipment costs (up to $150) to 25 percent (up to 

$500 per taxpayer). The Energy Conservation Tax Credit can be used for equipment installed in 

new construction or remodeling projects, with the tax credit allowed only for the portion of the 

cost and materials above “established standards of construction.” 

Oregon’s Residential Energy Tax Credit (RETC) was created in 1977 to encourage the 

use of renewable resources in households. The Oregon legislature expanded the RETC program 

in 1997 to include residential refrigerators, clothes washers, and dishwashers; participation in the 

program increased significantly after they became eligible. The program subsequently added 

credits for high-efficiency heat pump systems, air conditioners, and water heaters (2001); 

furnaces and boilers, (2002),and other equipment and measures. For HVAC, residential 

appliances, and water heating, the credit is $0.40/kWh saved in the first year, or 25% of net 

purchase price, whichever is less. The credit limit for energy efficient appliances and heating 

and cooling systems is $1,000 per calendar year; excess credit may be carried forward for five 

12,13 years.

To qualify, a central air conditioning or heat pump system must have a performance 

verification test by a tax credit-certified technician. For this verification test there is a separate 

tax credit of 25% of the cost of the test and any needed repairs, up to $250. Purchasers of highefficiency central air conditioners or heat pumps who have premium efficiency ducts qualify for 

an additional $150 tax credit. 

Central air conditioning split-system units must have EER of 13.0 or higher. The tax 

credit for qualifying central air conditioning systems is the amount listed in Table 3.2.8 or 25 

percent of the net purchase price, whichever is less. 

Table 3.2.8 Oregon Tax Credit for Central Air Conditioners 

Tier Minimum Efficiency EER Maximum Tax Credit Amount 

RAC4 13.0 $160 

RAC5 14.0 $225 

RAC6 15.0 $300 

Air-source heat pump split-system equipment must have HSPF of 9.0 or higher and EER 

of 12 or higher. Table 3.2.9 shows the heat pump tax credit levels by system efficiencies. 

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Table 3.2.9 Oregon Tax Credits for Heat Pumps 

HSPF 

EER 

12 12.5 13 

9.0 $300 $320 $340 

9.5 $300 $360 $380 

10.0 $300 $360 $430 

Indiana offers a tax credit beginning in 2009 to individuals and small businesses for the 

costs associated with purchasing ENERGY STAR-qualified central air conditioners,and other 

appliances. The credit may be claimed against the state income tax, insurance premium tax, or 

financial institutions tax. The amount of the tax credit is set at 20% of the expenditures for 

qualified heating and cooling equipment up to $100 per taxable year. The credit is for 

expenditures in 2009 and 2010 and there is no carryover.14,

15 

Kentucky offers a 30% state income tax credit beginning in 2009 for taxpayers who 

install certain energy efficiency measures on their principal residence or residential rental 

property. These energy efficiency measures include “Qualified Energy Property Installation,” 

which includes heat pumps and central air conditioners, among others. Equipment must meet the 

efficiency guidelines specified in the Federal tax credit for residential energy property (see Table 

3.2.7). The total annual tax credit for this equipment may not exceed $250. These credits apply 

to equipment purchased in taxable years 2009-2015 and may be carried forward for one year.16,17 

3.2.4.4 FEMP Procurement Guidelines 

DOE reviewed the Federal Energy Management Program (FEMP) procurement 

guidelines for Federal government equipment purchasing. Federal construction requirements 

include these guidelines for installing or replacing equipment. Table 3.2.10 shows the FEMP 

performance requirements for residential central air conditioners and Table 3.2.11 shows the 

requirements for air source heat pumps.18,

19 

Table 3.2.10 FEMP Performance Requirements for Residential Central Air Conditioners 

System Type SEER EER 

Split 14.5 or greater 12.0 or greater 

Packaged 14.0 or greater 11.0 or greater 

Table 3.2.11 FEMP Performance Requirements for Air Source Heat Pumps 

System Type HSPF EER SEER 

Split 8.0 or greater 11.0 or greater 13.0 or greater 

Single Package 7.6 or greater 10.5 or greater 12.0 or greater 

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EERE-2008-BT-STD-0006 COMMENT 54
   

     

   

3.2.5 Industry Cost Structure 

DOE developed an industry cost structure for residential central air conditioners and heat 

pumps from publicly available information from the Census Bureau’s ASM and the SEC 10-K 

reports filed by publicly owned manufacturers. 

The Census Bureau collects industry-wide employment data based on NAICS codes. As 

stated previously, manufacturers of residential central air conditioners and heat pumps are 

grouped into the Air-Conditioning and Warm Air Heating Equipment and Commercial and 

Industrial Refrigeration Equipment Manufacturing category, which is NAICS code 333415. 

Table 3.2.12 presents the commercial air conditioning and warm air heating equipment 

manufacturing employment levels and earnings from 1997 to 2005 according to the NAICS. 

Table 3.2.12 Air Conditioning and Warm Air Heating Equipment Industry Employment 

and Payroll Data 20,21 

Year Production Workers All Employees

Payroll for All

Employees ($1000)

2006 74,909 98,097 4,019,813

2005 76,011 102,354 3,942,808

2004 73,106 99,035 3,691,029

2003 77,488 104,668 3,776,417

2002 80,417 108,274 3,815,747

2001 88,978 118,876 3,950,483

2000 97,978 127,384 4,267,872

1999 95,904 123,962 4,043,064

1998 91,994 120,011 3,844,667

1997 90,968 119,386 3,678,996

The statistics illustrate a steady decline in both the number of production and nonproduction workers in the industry after the year 2000, with the only exception being in 2005, 

when the number of employees increased. The overall decline in employment may be a result of 

industry consolidation, increased automation in production, or manufacturers moving their 

facilities outside of the United States to reduce labor costs. The increase in employment in 2005 

may have resulted from manufacturers of residential central air conditioners in heat pumps 

augmenting the number of production workers to deal with the increased demand for central air 

conditioners and heat pumps that occurred prior to the most recent Federal standards becoming 

effective in 2006 (as shown by the sharp increase in residential central air conditioner and heat 

pump shipments in 2005). 

Table 3.2.13 presents the costs of materials and industry payroll as a percentage of value 

of shipments from 1997 to 2006. 

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EERE-2008-BT-STD-0006 COMMENT 54
         

       

   

       

       

       

   

       

     

           

   

 

Table 3.2.13 Air Conditioning and Warm Air Heating Equipment Industry Cost Data 10,11 

Year

Cost of Materials as a

percent of value of

shipments (percent)

Cost of Payroll for

production workers as a

percent of value of

shipments (percent)

Cost of Total Payroll

(production + admin.)

as a percent of value of

shipments (percent)

2006 53.2 8.9 13.8

2005 53.8 8.5 13.8

2004 51.1 8.8 14.2

2003 50.6 9.5 15.4

2002 49.4 9.8 15.9

2001 52.6 9.8 15.8

2000 53.0 10.1 16.0

1999 53.4 9.8 15.4

1998 54.9 9.9 15.4

1997 54.2 10.1 16.0

The cost of materials as a percentage of value of shipments has fluctuated slightly over 

the 10-year period. Fluctuations in raw material costs are common from year to year. The cost of 

payroll for production workers as a percentage of value of shipments has followed a declining 

pattern since 1998, with the exception of only the year 2006, during which the cost of payroll 

increased from the previous year. Finally, the cost of total payroll as a percentage of value of 

shipments has generally declined since 2000, illustrating a reduction in industry non-production 

or administrative employees, possibly the product of selling, general, and administrative (SG&A) 

cost-cutting measures. 

A detailed financial analysis of the manufacturers of each of the product types covered by 

this rulemaking is presented in the manufacturer impact analysis (MIA) (Chapter 12 of this 

TSD). This analysis identifies key financial inputs including cost of capital, working capital, 

depreciation, capital expenditures, etc. 

3.2.6 Equipment Lifetime 

The lifetime of residential central air conditioners and heat pumps can vary greatly 

depending on how often the system is used (which is dependent upon the climate of the region 

where the product is installed and the personal preferences of the consumer) and how regularly it 

is maintained and serviced. DOE reviewed available literature to determine the appropriate 

lifetime for residential central air conditioners and air-source heat pumps. Generally, most 

sources estimate the lifetime of residential central air conditioners and heat pumps to be in the 

range of 10 to 20 years. Appliance Magazine publishes an Annual Portrait of the U.S. Appliance 

Industry, in which it estimates low, high, and average lifetimes for a range of home appliances, 

including unitary air conditioners and heat pumps, based on input from appliance experts and 

many additional sources. Appliance Magazine estimates the average lifetime of a residential 

central air conditioner as 11 years and the average lifetime of a residential air-source heat pump 

as 12 years. AHRI estimates the average lifetime of a central air conditioner as 12 to 15 years, 

and the average lifetime of a heat pump as 14 years.22 DOE used national survey data, along with 

manufacturer shipment data, to calculate the distribution of air conditioner and heat pump 

lifetimes. The mean central air conditioner and heat pump lifetimes from the distributions were 

3-16 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

determined to be 19.0 and 16.2 years, respectively. Additional information about equipment 

lifetimes is contained in the Life-Cycle Cost and Payback Period Analysis chapter (Chapter 8) of 

this TSD. 

3.2.7 Market Performance Data 

DOE examined the AHRI Directory of Certified Product Performance for residential 

central air conditioners and heat pumps to determine the characteristics of residential central air 

conditioners and heat pumps currently available on the market. By definition, residential central 

air conditioners and heat pumps are products with a cooling capacity below 65,000 Btu/h and are 

air-cooled, and therefore DOE did not examine any products that did not meet these criteria. In 

addition, DOE excluded from its analysis any products that were manufactured for Canada or 

export only, and any products in the AHRI Directory of Certified Product Performance that were 

not labeled as “active,” meaning that they are currently being manufactured. Table 3.2.14 shows 

the number of the models in the AHRI Directory of Certified Product Performance for each 

equipment class. As the table shows, the large majority of residential central air conditioners and 

heat pumps are split system products, and there are relatively few space constrained (i.e. 

through-the-wall) models. 

Table 3.2.14 Types of Models Listed in the AHRI Directory of Certified Product 

Performance 

Product Class Number of Models Listed in the AHRI 

Directory of Certified Product Performance 

Split system air conditioners 281,184 

Split system heat pumps 153,397 

Single package air conditioners 8,479 

Single package heat pumps 2,876 

Small duct, high velocity system 4,468 

Space constrained – air conditioners 12* 

Space constrained – heat pumps 12* 

*Currently there are no space constrained air conditioners or space constrained heat pumps in the AHRI Directory of 

Certified Performance. However, the AHRI Directory of Certified Performance does list through-the-wall products 

that will be classified as space constrained products prior to the effective date of this rulemaking. 

DOE examined the efficiency of residential central air conditioners and heat pumps 

currently available on the market in AHRI’s Certified Product Performance Directory. DOE 

divided the products into bins based on their efficiency and counted the number of models in 

each efficiency bin. The efficiency ratings were separated into efficiency bins of one SEER each, 

and the SEER ratings are calculated to two decimal points. Figure 3.2.2 through Figure 3.2.6 

show histograms of the efficiency data for split system and single package central air 

conditioners and heat pumps, as well as for SDHV systems. 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.2 SEER Ratings for Single Package Central Air Conditioners in the AHRI 

Certified Product Performance Directory 

Figure 3.2.3 SEER Ratings for Single Package Heat Pumps in the AHRI Certified Product 

Performance Directory 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.4 SEER Ratings for Split System Central Air Conditioners in the AHRI 

Certified Product Performance Directory 

Figure 3.2.5 SEER Ratings for Split System Heat Pumps in the AHRI Directory of 

Certified Product Performance 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 3.2.6 SEER Ratings for SDHV Systems in the AHRI Directory of Certified Product 

Performance 

Figure 3.2.2 through Figure 3.2.6 show that the SEER Ratings for split system and single 

package air conditioners and heat pumps are mostly concentrated in the 13 to 14.99 SEER range, 

although split systems cover a much higher range of efficiencies. The majority of SDHV systems 

are concentrated in the 11 to 12.99 SEER range. The through-the-wall products in the AHRI 

Directory of Certified Product Performance all had a SEER rating of either 10.9 (9 central air 

conditioners and 8 heat pumps were rated 10.9 SEER) or 11.0 (3 central air conditioners and 4 

heat pumps were rated 11.0 SEER). 

DOE also examined the HSPF ratings of the heat pumps in AHRI’s Directory of Certified 

Product Performance. Figure 3.2.7 through Figure 3.2.9 shows the number of single package, 

split system, and SDHV heat pumps models in the directory that fall into the specified HSPF 

bins. 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.7 HSPF Ratings for Single Package Heat Pumps in AHRI’s Directory of 

Certified Product Performance 

Figure 3.2.8 HSPF Ratings for Split System Heat Pumps in AHRI’s Directory of Certified 

Product Performance 

3-21 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.9 HSPF Ratings for SDHV Heat Pumps in AHRI’s Directory of Certified 

Product Performance 

For single package heat pumps, the HSPF ratings are concentrated in the 7.5 to 8.49 

range. Split system heat pumps cover a greater range of HSPF ratings, and are concentrated in 

the 7.5 to 8.99 range. For SDHV heat pumps, a significant number of models fall into the range 

between 6.5 and 8.49. All 12 Through-the-wall heat pump models listed in AHRI’s directory had 

an HSPF rating of 7.1. 

In reviewing the efficiency of residential central air conditioners and heat pumps 

currently available on the market, DOE also examined the relationship between efficiency and 

equipment capacity. Figure 3.2.10 through Figure 3.2.14 show the average SEER ratings at each 

equipment capacity available for single package and split system air conditioners and heat 

pumps, as well as for SDHV systems in AHRI’s Directory of Certified Product Performance. 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.10 Average SEER Ratings at Each Cooling Capacity for Single Package Air 

Conditioners in AHRI’s Directory of Certified Product Performance 

Figure 3.2.11 Average SEER Ratings at Each Cooling Capacity for Split System Air 

Conditioners in AHRI’s Directory of Certified Product Performance 

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EERE-2008-BT-STD-0006 COMMENT 54
 Figure 3.2.12 Average SEER Rating at Each Cooling Capacity for Single Package Heat 

Pumps in the AHRI Directory of Certified Product Performance 

Figure 3.2.13 Average SEER Rating at Each Cooling Capacity for Split System Heat 

Pumps in the AHRI Directory of Certified Product Performance 

3-24 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.14 Average SEER Rating at Each Cooling Capacity for SDHV Systems in the 

AHRI Directory of Certified Product Performance 

The average SEER ratings for single package air conditioners and heat pumps are 

concentrated generally in the 13 to 15 SEER range for the entire range of cooling capacities. 

Split system air conditioners and heat pumps display a greater range of average SEER ratings at 

lower cooling capacities, and then appear to become concentrated between 13 and 15 SEER at 

the higher cooling capacities. Split system air conditioners and heat pumps appear to have “sweet 

spots” near the two and three ton cooling capacities (i.e. 24,000 and 36,000 Btu/h cooling 

capacities) where a greater range of average efficiencies occurs, and where the highest average 

SEER ratings occur. SDHV systems appear to have an average SEER value in the range of 11 to 

13 SEER for the entire range of cooling capacities. 

DOE also examined the average HSPF ratings at each equipment capacity for heat pumps 

listed in AHRI’s Directory of Certified Product Performance. Figure 3.2.15 through Figure 

3.2.17 show the average HSPF at each available capacity rating in AHRI’s directory for single 

package, split system, and SDHV heat pumps. 

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EERE-2008-BT-STD-0006 COMMENT 54
Figure 3.2.15 Average HSPF at Each Cooling Capacity for Single Package Heat Pumps in 

the AHRI Directory of Certified Product Performance 

Figure 3.2.16 Average HSPF Rating at Each Cooling Capacity for Split System Heat 

Pumps in the AHRI Directory of Certified Product Performance 

3-26 

EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 3.2.17 Average HSPF Rating at Each Cooling Capacity for SDHV Heat Pumps in 

the AHRI Directory of Certified Product Performance 

The HSPF ratings for single package heat pumps are consistently between 7.7 and 8.2 

HSPF for the entire range of cooling capacities. Split system heat pumps appear to have a greater 

range of average HSPF ratings at lower cooling capacities, and a smaller range of average HSPF 

ratings at higher cooling capacities. The average HSPF ratings peak near 3 tons (36,000 Btu/h) 

and 5 tons (60,000 Btu/h). The average HSPF ratings of SDHV heat pumps are between 6.8 and 

8 for the entire range of capacities. 

3.2.8 Historical Shipments and Efficiencies 

3.2.8.1 Historical Shipments 

The Air-Conditioning, Heating, and Refrigeration Institute (AHRI) provided historical 

shipments data over the 1990-2007 time-period disaggregated into the four primary product 

classes.23 Historical shipments from 1972-1989 were also provided by AHRI from previous 

data submittals to the Lawrence Berkeley National Laboratory (LBNL).24 The data for 1972­

1989 included some shipments of 3-phase as well as single-phase central air conditioners and 

heat pumps, whereas the data for 1990-2007 included only single-phase central air conditioners. 

DOE disaggregated the shipments for single-phase and 3-phase central air conditioner and heat 

pump equipment in the earlier data and included only single phase units. Table 3.2.14 

summarizes the historical shipments data. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 3.2.15 Central Air Conditioner and Heat Pump Shipments 

Year 

Split CAC 

thousands 

Single Package CAC 

thousands 

Split HP 

thousands 

Single Package HP 

thousands 

1972 1,489 257 28 52 

1973 1,742 318 35 52 

1974 1,503 289 49 48 

1975 888 159 83 45 

1976 1,219 231 177 74 

1977 1,364 218 329 89 

1978 1,546 253 389 97 

1979 1,428 248 376 107 

1980 1,233 134 293 61 

1981 1,293 122 348 66 

1982 1,037 111 267 49 

1983 1,558 192 455 82 

1984 1,857 189 535 98 

1985 1,784 203 619 107 

1986 1,876 203 680 106 

1987 2,204 237 714 103 

1988 2,334 247 649 91 

1989 2,516 267 650 91 

1990 2,241 334 643 104 

1991 2,388 306 615 96 

1992 2,254 330 647 101 

1993 2,474 346 718 107 

1994 3,087 387 825 118 

1995 3,221 384 834 120 

1996 3,635 418 936 139 

1997 3,364 395 917 142 

1998 4,010 406 1,019 148 

1999 4,317 429 1,044 147 

2000 4,280 437 1,073 159 

2001 3,931 361 1,180 165 

2002 4,381 380 1,229 165 

2003 4,281 390 1,350 174 

2004 4,561 414 1,584 190 

2005 5,461 455 1,810 213 

2006 4,038 330 1,807 190 

2007 3,582 338 1,570 199 

Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI) 

3.2.8.2 Historical Efficiencies 

AHRI provided historical shipment-weighted efficiency data (SWEF) data spanning the 

years 1992 to 2008.28 Between 1992, the year in which the first set of standards for central air 

conditioners and heat pumps became effective, and 2006, when an updated set of standards 

became effective, the SWEFs for central air conditioners grew by approximately one SEER 

point. Figure 3.2.18 shows the SWEFs for split system and single package central air 

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EERE-2008-BT-STD-0006 COMMENT 54
 

conditioners. The figure also presents the linear fit to each product class’ SWEF data series. 

The linear fits have high coefficients of determination, i.e., linear fits provide a good estimate of 

the SWEF growth rate. Table 3.2.15 provides a summary of the SWEF growth rates for each 

product class. 

Split A/C 

SEER = 0.0703 * year - 129.65 

R2 = 0.9633 

Package A/C 

SEER = 0.0778 * year - 144.78 

R2 = 0.9455 

10.0 

10.2 

10.4 

10.6 

10.8 

11.0 

11.2 

11.4 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

Year 

Shipment-Weighted SEER 

Split A/C 

Package A/C 

Linear (Split A/C) 

Linear (Package A/C) 

Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI) 

Figure 3.2.18 Central Air Conditioner Historical Shipment-Weighted Efficiencies with 

Linear Fits 

Table 3.2.16 Central Air Conditioner Shipment-Weighted Efficiency Growth Rates 

SWEF Growth Rate 

Product Class SEER increase per year 

Split System Air Conditioners 0.0703 

Single Package Air Conditioners 0.0778 

For heat pumps, between 1992 and 2006, the SEER-based also grew by approximately 

one SEER point. Figure 3.2.19 shows the SEER-based SWEFs for split system and single 

package heat pumps. The figure also presents the linear fit to each product class’ SWEF data 

series. The linear fits have high coefficients of determination, i.e., linear fits provide a good 

estimate of the SWEF growth rate. Table 3.2.16 provides a summary of the SEER-based SWEF 

growth rates for each product class. AHRI did not provide historical SWEF data for heat pump 

HSPFs. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Split HP 

SEER = 0.0739 * year - 136.55 

R2 = 0.9594 

Package HP 

SEER = 0.0736 * year - 136.03 

R2 = 0.8886 

10.2 

10.4 

10.6 

10.8 

11.0 

11.2 

11.4 

11.6 

11.8 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

Year 

Shipment-Weighted SEER 

Split HP 

Package HP 

Linear (Split HP) 

Linear (Package HP) 

Source: Air-Conditioning, Heating, and Refrigeration Institute (AHRI) 

Figure 3.2.19 Heat Pump Historical Shipment-Weighted Efficiencies base on SEER with 

Linear Fits 

Table 3.2.17 Heat Pump Shipment-Weighted Efficiency Growth Rates 

SWEF Growth Rate 

Product Class SEER increase per year 

Split System Heat Pumps 0.0739 

Single Package Heat Pumps 0.0736 

3.2.9 Saturations in U.S. Households 

Saturation refers to the percentage of the housing stock with a given product. The 

American Housing Survey (AHS) provides historical stock saturations for central air 

conditioning and heat pump equipment for every other year between 1991−2007.25 Table 3.2.17 

summarizes the saturations for central air conditioners, heat pump, and both types of equipment. 

Central air conditioerns and heat pump saturation has grown from 38.6 percent to 64.6 percent 

from 1991 to 2007. 

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Table 3.2.18 Central Air Conditioner Heat Pump Historical Housing Stock Saturations 

Year CAC HP Total 

1991 30.8% 7.8% 38.6% 

1993 32.0% 8.5% 40.5% 

1995 33.9% 9.1% 43.0% 

1997 36.3% 12.0% 48.3% 

1999 41.4% 11.4% 52.8% 

2001 45.0% 11.3% 56.3% 

2003 46.5% 11.7% 58.2% 

2005 50.2% 12.7% 62.9% 

2007 51.8% 12.8% 64.6% 

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 central air conditioners and heat 

pumps. The following assessment provides descriptions of technologies and designs that apply to 

subsystems within all product classes of central air conditioners and heat pumps, as well as 

innovations that apply to heat pumps only. 

3.3.1 Compressor Improvements 

Several technologies exist to increase the efficiency of the compressors used in central air 

conditioner and heat pump systems. High efficiency reciprocating and scroll compressors, 

sometimes incorporating variable-speed motors, all have higher efficiencies than the traditional 

reciprocating compressors commonly used in air conditioners. 

Scroll compressors compress gas in a fundamentally different manner from traditional 

compressors—between two spirals, one fixed and one rotating. High efficiency reciprocating 

compressors are as efficient, or more efficient, than scroll compressors. However, these 

compressors are often considered to present some drawbacks exist including noise, cost and 

reliability, compared to scroll compressors. 

Variable-speed compressors are implemented through the use of 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 (but it should be noted that it typically 

increases efficiency over a broad operating range but does not inherently increase maximum 

efficiency at the compressor rating point): 

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. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

3.	 During the off-cycle, the pressure in the system equilibrates. At the intermediate pressure, 

refrigerant vapor will condense in the cold evaporator rather than the condenser. 

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. 

3.3.2 Fan System Improvements 

3.3.2.1 Higher Efficiency Fan Motors 

Fan motors are fractional horsepower in size, are responsible for moving air across the 

indoor and outdoor coils, and typically run at one speed. The manufacturer will match the motor 

size and blade to the coil to meet the expected cooling load under most conditions. Higher 

efficiency 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. 

Nearly all fan motors for standard central air conditioners and heat pumps are of the 

permanent split capacitor (PSC) variety. In PSC motors, the electromagnet consists of windings 

of electrical wire through which current is driven. 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. This makes PSC motors more energy efficient, with motor efficiencies 

ranging from 50 to 70 percent. PSC motors are produced in large quantities and are relatively 

inexpensive. 

Another type of electric motor, the brushless direct current (DC) (i.e., electronicallycommutated motor (ECM), is more energy-efficient than PSC motors of comparable size and 

capacity. Brushless DC motors, which are sold in high volumes, are three-phase electric motors 

with efficiencies ranging from 70 to 80 percent. However, brushless DC motors can weigh twice 

as much as equivalent PSC motors. In addition, brushless DC motors are complex, and can cost 

from two and a half to five times as much as a PSC motor. 

A way to further improve the efficiency of motors used for central air conditioner and 

heat pump applications is to make the critical components of an induction motor's rotor (e.g., 

conductor bars and end rings) out of copper instead of aluminum. Due to difficulties with casting 

copper, making these components out of aluminum is the common current practice. However, 

the greater conductivity of copper results in lower resistance heating losses in the rotor, and thus 

lower losses in the motor when compared to traditional aluminum motor parts. Recently, the 

creation of copper dies made from special alloys has allowed for the advancement of copper 

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EERE-2008-BT-STD-0006 COMMENT 54
casting techniques. Additional improvements in the design and fabrication of copper motors, 

such as optimization of the steel laminations, could further increase the efficiency of copper 

motors over aluminum motors. 

3.3.2.2 Fan Motor Controllers 

Fan motor controllers allow fan motors to run at variable speed to match changing load 

conditions. During periods of frost build-up in heat pumps, fan motor power requirements 

increase; during the post-defrost period, power requirements decrease. Matching the fan speed to 

all conditions ensures more stable discharge air temperatures and improves coil performance. 

Fan motor controllers would also allow both central air conditioners and heat pumps run more 

efficiently at varying ambient humidity and temperature levels. Because of practical limitations 

on efficiency, variable speed systems dominate the market over 14 SEER, and it is unusual to 

find a system over 13 SEER that does not incorporate a variable speed indoor blower. 

3.3.2.3 Higher Efficiency Fan Blades 

High efficiency fan blades move air more efficiently, yielding energy consumption 

savings by reducing the required fan shaft power. The fans typically used in central air 

conditioners and heat pumps have stamped, curved sheet metal blades. The blades are typically 

supplied by a fan blade manufacturer and mounted to the motor by the manufacturer, and may 

not be optimized for the particular central air conditioner or heat pump that they are installed on. 

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 given application. 

3.3.3 Expansion Valve Improvements 

Expansion valves are refrigerant metering devices whose purpose is to 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 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 older, 

less efficient air conditioners and heat pumps. 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 air conditioners and heat pumps 

rated at an efficiency level of 13 SEER or above. 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. 

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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 that allowed by a TXV, an EEV theoretically 

allows for further increases in energy efficiency under varying conditions. 

3.3.4 Heat Exchanger Technologies and Improvements 

3.3.4.1 Baseline Technology 

Most central air conditioners and heat pumps currently on the market utilize traditional 

tube-and-fin heat exchangers for both the evaporator and condenser coils. These coils are 

refrigerant-to-air heat exchangers composed of metals with high thermal conductivity, usually 

aluminum and copper, with the tubes generally being composed of copper and the fins of 

aluminum. 

The evaporator coil is responsible for evaporating and superheating the entering 

refrigerant liquid-vapor mixture while extracting heat from the air in the conditioned 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.” Because a temperature difference is necessary to drive heat from the air into the 

refrigerant, the saturated evaporator temperature must be considerably colder than the 

evaporator’s discharge air temperature. The magnitude of this driving force is directly related to 

the total cooling load and the thermal characteristics of the evaporator. Increasing the area of the 

coil decreases the necessary temperature difference and therefore decreases the required 

saturated evaporator temperature. This results in an increased compressor energy efficiency ratio 

(EER) and lower compressor energy consumption. 

The condenser coil is responsible for condensing and sub-cooling the entering refrigerant 

vapor while rejecting heat from the refrigerant to the ambient air. As with evaporator coils, 

increasing the area of the condenser coil will decrease the necessary change in temperature 

across the coil, resulting in increased compressor efficiency (increased EER). 

The majority of evaporator and condenser coils used in central air conditioners and heat pumps 

currently on the market are of the traditional tube-and-fin heat exchanger design. Many 

manufacturers utilize a similar process in building coils, and this methodology has remained 

fundamentally the same over the long period during which these products have been in use. The 

actual techniques utilized in this process vary by company, and proprietary methods are often 

utilized by specific manufacturers in the production of coils. Manufacturing of coils in-house is a 

process which requires high capital investments in machinery and line setup. As a result, 

manufacturers have been hesitant to move away from the traditional method of coil production, 

as doing so would require large new investments. Instead, companies have historically focused 

on improving the performance of their existing coil designs. 

3.3.4.2 Improvements to Baseline Coils 

Increasing the overall size of the coil in one or more dimensions tends to be the most 

cost-effective way to increase the system efficiency. However, many applications limit the 

amount of coil size increase in order to maintain overall cabinet dimensions. Most approaches to 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

increasing the coil surface area also result in an increase in required fan motor power and an 

increase in refrigerant pressure drop. Enhancements to the refrigerant-side surface area of both 

evaporator and condenser coils typically include rifled or diamond-pattern tubing and increased 

number of tube passes. Enhancements to the air side surface area include increased fin pitch 

(decreased fin spacing), fin patterns (wavy or zig-zag), and increased numbers of tube passes. 

The size constraints facing manufacturers who have already maximized the size of their units 

make it necessary for these companies to consider alternative methods to improving heat 

exchanger performance. 

3.3.4.3 Alternative Coil Technologies 

3.3.4.4.1. 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, thus 

providing 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 gains of liquid suction heat exchangers 

depend on the several factors, including evaporator temperature, type of refrigerant used, and 

system pressures. 

3.3.4.4.2 Microchannel Heat Exchangers 

Several companies produce microchannel heat exchangers, which are mainly used in the 

automobile industry. Unlike a conventional round-tube plate-fin heat exchanger, the 

microchannel has a rectangular cross-section containing several small channels through which 

refrigerant passes. Fins pass between the tubes and are brazed to the tubes, and all components 

are aluminum. The resulting microchannel coil transfers more heat per unit of face area than does 

a round-tube plate-fin coil of comparable capacity. It does so with a lower airside pressure drop, 

yielding reduced fan power consumption. These benefits can improve system EER and SEER 

ratings in residential air conditioners when compared to a condenser coil of the same face area. 

This would allow manufacturers to improve the rated SEER without further increasing the size of 

the units. Because the microchannel fin arrangement prevents natural condensate drainage, their 

use in heat pump and evaporator coil applications is not forthcoming. 

Although the microchannel heat exchanger costs more to produce than a conventional 

round-tube plate-fin coil, this product offers particular opportunities to reduce the size and 

weight of the heat exchanger. Those advantages led to the rapid and almost total transition of the 

automobile air conditioner market to microchannel technology. Microchannel heat exchangers 

also offer significant reductions in refrigerant charge, which suggests that they may reduce the 

rate of compressor failures caused by refrigerant slugging. 

Even after several years of dominance in the automobile market, the microchannel heat 

exchanger has not penetrated the building air conditioning markets where size and weight 

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EERE-2008-BT-STD-0006 COMMENT 54
 

constraints are not as important. The cost advantages of reducing the size and weight of the 

condenser or the capacity of the system have not sufficiently outweighed the added costs and risk 

associated with the microchannel technology for these systems to attain widespread use in 

building applications to date. Additionally, given the fact that most manufacturers produce coils 

in-house, and that setting up a coil production line is an extremely capital-intensive process, 

manufacturers are generally hesitant to make the large investments needed to move away from 

the production of traditional tube-and-fin heat exchangers. Moreover, several limitations and 

uncertainties are particularly hindering the large-scale adoption of microchannel heat 

exchangers. First, microchannel construction makes condensate removal much more challenging 

than traditional tube-and-fin heat exchangers. This poses a serious barrier to the adoption of the 

technology in evaporators and in heat pump condensers. Some manufacturers may decide not to 

adopt the new technology if they cannot offer it in all of their products, including both air 

conditioners and heat pumps. Second, there are concerns whether residential heat exchangers are 

proven to perform well under wide variations in ambient temperatures given that they are 

considerably larger than automobile heat exchangers and are configured differently. Third, 

compressor lubrication is entrained in the refrigerant, and residential microchannel heat 

exchangers must display a proven ability to consistently return lubricant to the compressor to 

avoid costly damage. Fourth, manufacturers are concerned that contractors will not be able to 

repair coil leaks effectively because of the difficulty of successfully brazing aluminum in the 

field. 

3.3.4.4.3 Flat-Tube Heat Exchangers 

Flat-tube, louver-fin heat exchangers offer various advantages over traditional roundtube, plain-fin heat exchangers. The flat-tube design reduces wake region, which decreases heat 

transfer downstream of round tubes. The design improves fin efficiency, and creates a lower 

profile drag as a result of the smaller tube projected area. Serpentine louvered-fin, flat-tube heat 

exchangers have already been utilized in automotive applications because of their ability to 

produce the same amount of heat transfer with much more compact designs than the plain-fin, 

round-tube variety heat exchangers. In laboratory tests, the louver-fin, flat-tube heat exchanger 

was found to produce heat transfer coefficients that were 90% higher than those produced by a 

plain-fin, round-tube heat exchanger. The significant increase in heat transfer coefficient resulted 

in a size reduction factor of two to three for a residential absorption heat pump system. The more 

efficient flat-tube heat exchangers would be able to provide the same amount of heat transfer and 

reduce the amount of airflow needed from the fans, thus reducing the amount of electricity 

consumed by the fan motors and increasing system efficiency. 

Like the microchannel technology, the flat-tube heat exchangers still have not broken 

through into the air conditioner and heat pump market, where the size of the unit is not as much 

of a concern. The extra cost of developing these systems and investing the large amounts of 

capital needed to produce them in-house has not yet been offset by the potential advantages to 

using flat-tube heat exchangers. Also, condensate removal is a concern in louvered-fin, flat-tube 

heat exchangers because of water “bridges” that get into the louver gaps and reduce heat transfer. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

3.3.5 Designs Relevant Only to Heat Pumps 

The following technologies, defrost mechanism and defrost cycle control, are two 

examples of defrost-related improvements applicable to heat pump designs, and it should be 

noted that they are not intended to comprise an exhaustive list of viable technologies. 

3.3.5.1 Defrost Mechanism 

As the outside air passes over the outdoor coil of a heat pump operating in heating mode, 

its heat is absorbed by the refrigerant inside the coil, which lowers the temperature of the 

ambient air. When the temperature of the surrounding air is reduced to less than 32°F, the 

moisture in the air will condense and freeze on the outdoor coil, forming a layer of frost. The 

frost reduces 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. 

The standard method of defrosting the outdoor coil during the heating operation of a heat 

pump is to temporarily reverse the flow of the refrigerant. This will use some of the heat from air 

inside to heat the outdoor coil and melt the frost. At the same time the indoor coil is cooled, and 

it becomes necessary to heat the house using an auxiliary heating system (typically electric 

resistant heaters). 

“Frost-less” heat pump defrost technology slows frost accumulation on the outdoor coil 

while also increasing the heating capacity by adding an accumulator to the heat pump cycle. The 

accumulator traps heat from the condensed liquid from the condenser, and this causes an increase 

the suction pressure of the compressor. This addition of heat to the accumulator increases the 

outdoor coil temperature by several degrees and thus reduces the frost accumulation on the coil. 

Also, much of the heat added to the accumulator is still brought inside by increased heat pump 

supply air temperature since the suction pressure of the compressor was increased. The frostless 

heat pump still may accumulate frost, however, if the heat pump is operated for a long period of 

time at low ambient temperatures, creating the need for a cycle reversal for defrosting. During 

the reverse cycle, the indoor blower is shut off and the refrigerant flows to the accumulator, 

making the accumulator take over the function of the evaporator. This allows for reverse cycle 

defrosting while also preventing cool air from being blown inside, and reduces the need for 

resistance heaters. When the surrounding temperature drops below 32°F, increasing the 

temperature of the outdoor coil a few degrees will not prevent frost accumulation, and heat input 

to the accumulator becomes useless. Therefore, the accumulator should only be used at 

temperatures between 32°F and 41°F, when frost is most likely to collect on the coil and the use 

of the accumulator will be able to reduce the amount of frost. 

Another mechanism for reducing the number and duration of defrost cycles is hot watersource defrosting. In heat pumps equipped with hot water defrost, a specifically designed system 

of valves and conduit allow the heat pump to selectively send the refrigerant to the various heat 

pump components, depending on which heat pump functions are being performed. These heat 

pumps use components and valves arranged in such a way that they are able to cool a space, heat 

a space, heat a liquid without affecting the temperature of the conditioned space, cool a space 

while heating a liquid, and defrost the outdoor coil using only the previously heated water as a 

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EERE-2008-BT-STD-0006 COMMENT 54
heat source. During the defrost mode, hot water that is held in a storage tank is used to defrost 

the outdoor coil, without degrading the overall performance of the heat pump. A refrigerant-towater heat exchanger is used to provide energy to the refrigerant and allow it to melt the frost on 

the outdoor coil. This can be done without any degradation to heat pump performance, and the 

energy taken from the hot water in the system is easily and inexpensively replaced when the heat 

pump switches back into normal heating mode. 

3.3.5.2 Defrost Cycle Control 

During a conventional heat pump defrost cycle some form of supplemental heating is 

needed to compensate for the reversal of the heat pump cycle. Usually electric resistance heaters 

are used to heat air inside the house while the defrost cycle occurs, and this type of heating is 

much less efficient than heating using the heat pump. Since the alternate heat sources are much 

less efficient, the efficiency of a heat pump can be increased by reducing the frequency and 

duration of the defrost cycles. 

Defrost cycle control involves management of the initiation and termination of defrost 

cycles, and thereby the frequency and duration of defrost cycles. In conventional heat pumps 

defrost cycles are typically scheduled, and initiation and termination are timer-controlled. For 

this type of defrost cycle control, cycles are initiated at regular intervals, and terminated after a 

fixed amount of time. Cycle frequency and duration are unrelated to actual frost conditions, and 

are just based on estimations by the manufacturer. Under timer control, the frequency of defrost 

cycles is determined by the amount of time the manufacturer expects it to take for a large frost 

layer to develop in the worst-case scenario, and the cycle duration long enough to ensure 

complete defrost in the worst-case scenario. Timer-based defrost can lead to unnecessarily 

frequent and long defrost cycles. 

Demand-based defrost cycles eliminate unnecessary defrost cycles. Demand-defrost heat 

pumps use sensors to measure outdoor coil and outdoor ambient conditions to determine when to 

initiate and terminate defrost cycles. A microprocessor examines and analyzes the compressor 

run time, ambient air temperature, and outdoor coil temperature, all of which determine the 

environment under which a defrost cycle should occur. The microprocessor is then able to 

determine when the defrost cycle should be initiated and when it should be terminated, reducing 

the overall number and duration of cycles, and improving the efficiency of the heat pump. 

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REFERENCES
 

1	 Air-Conditioning, Heating and Refrigeration Institute. About AHRI. 2009. (Last accessed 

March 24, 2009) < http://ari.org/Content/AboutARI_31.aspx> 

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Product Performance. 2009. (Last accessed March 16, 2009.) < 

<http://www.ahridirectory.org/ahridirectory/pages/home.aspx> 

3	 31st Annual Portrait of the U.S. Appliance Industry: The Share-of-Market Picture for 

2007. Appliance Magazine, Vol.65, No. 9, September 2008. 

4	 U.S. Small Business Administration. Table of Small Business Size Standards matched to 

North American Industry Classification System Codes. August 2008. (Last accessed 

March 24, 2009) 

<http://www.sba.gov/idc/groups/public/documents/sba_homepage/serv_sstd_tablepdf.pdf 

> 

5	 Natural Resources Canada – Office of Energy Efficiency. Single-Phase and Three-Phase 

Split System Central Air Conditioners and Heat Pumps – Energy Efficiency Regulations. 

March 11, 2009. (Last Accessed October 16, 2009) 

<http://oee.nrcan.gc.ca/regulations/product/split-system-ac.cfm?attr=12> 

6	 Secretaría de Energía. NORMA Oficial Mexicana NOM-011-ENER-2006, Eficiencia 

energética en acondicionadores de aire tipo central, paquete o dividido. Límites, métodos 

de prueba y etiquetado. June 22, 2007. (Last Accessed October 16, 2009) 

<http://www.economia.gob.mx/work/normas/noms/2007/011ener2006.pdf> 

7	 ENERGY STAR. Air-Source Heat Pumps and Central Air Conditioners Key Product 

Criteria. (Last Accessed October 16, 2009) 

<http://www.energystar.gov/index.cfm?c=airsrc_heat.pr_crit_as_heat_pumps> 

8	 Consortium for Energy Efficiency. CEE High-Efficiency Specification – Central Air 

Conditioners and Air Source Heat Pumps. (Last Accessed October 16, 2009) 

<http://www.cee1.org/resid/rs-ac/res-ac_specs.pdf> 

9	 ENERGY STAR. Federal Tax Credits for Energy Efficiency – Summary of Tax Credits 

for Homeowners. March 6, 2009. (Last Accessed October 16, 2009) 

<http://www.energystar.gov/index.cfm?c=products.pr_tax_credits> 

10	 Montana Department of Environmental Quality. (Last accessed October 16, 2009.) 

<http://www.deq.state.mt.us/Energy/EEHome/TaxIncentHome.asp> 

11	 Montana Department of Revenue. (Last accessed October 16, 2009). 

<http://mt.gov/REVENUE/energyconservation.asp> 

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12	 Oregon Department of Energy - Conservation Division, Residential Energy Tax Credits. 

(Last accessed October 16, 2009.) 

<http://egov.oregon.gov/ENERGY/CONS/RES/RETC.shtml> 

13	 Oregon Department of Energy - Conservation Division, Residential Energy Tax Credits. 

(Last accessed October 16, 2009.) 

<http://egov.oregon.gov/ENERGY/CONS/RES/tax/HVAC-HP-AC.shtml> 

14	 Indiana Department of Revenue. Information Bulletin #100. December 2007. (Last 

accessed October 16, 2009.) <http://www.in.gov/dor/files/ib100.pdf> 

15	 DSIRE, Database of State Incentives for Renewables and Efficiency. Indiana Incentives 

for Energy Efficiency, Energy Savings Tax Credits (Personal). (Last accessed October 

16, 2009.) 

<http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=IN50F&re=1&ee=> 

16	 Kentucky Dept. of Revenue. 2009 Energy Efficiency Credits. (Last accessed October 16, 

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C6766A3843EE/0/2009EnergyEfficiencyCredits.pdf> 

17	 DSIRE, Database of State Incentives for Renewables and Efficiency. Personal Income 

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<http://www.dsireusa.org/incentives/incentive.cfm?Incentive_Code=KY29F&re=0&ee> 

18	 Federal Energy Management Program. Energy Efficient Products, Energy Efficiency 

Requirements, Residential Equipment, Central Air Conditioners. (Last accessed October 

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19	 Federal Energy Management Program. Energy Efficient Products, Energy Efficiency 

Requirements, Residential Equipment, Air Source Heat Pumps. (Last accessed October 

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<http://www1.eere.energy.gov/femp/procurement/eep_airsource_heatpump.html> 

20	 “Table 2 - Statistics for Industry Groups and Industries: 2006” 2006 Annual Survey of 

Manufacturers (ASM). U.S. Census Bureau, December 2006. 

21	 “Table 2 - Statistics for Industry Groups and Industries: 2005 and Earlier Years.” 2005 

Annual Survey of Manufacturers (ASM). U.S. Census Bureau, November 2006. 

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Systsems, Replacing Your Central Air Conditioner. 2009. (Last accessed March 27, 2009) 

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23	 Air-Conditioning, Heating and Refrigerator Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008. 

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24	 Air-Conditioning, Heating and Refrigerator Institute. Historical shipments data, 1972­

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<http://www.census.gov/hhes/www/housing/ahs/ahs.html> 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 4. SCREENING ANALYSIS 

TABLE OF CONTENTS 

4.1 INTRODUCTION ........................................................................................................... 4-1
 

4.2 SCREENED-OUT TECHNOLOGIES............................................................................ 4-2
 

4.2.1 High-Efficiency Expansion Valves...................................................................... 4-2
 

4.2.2 Condenser Fan Motor Controllers ....................................................................... 4-2
 

4.2.3 Liquid-Suction Heat Exchangers ......................................................................... 4-2
 

4.2.4 Defrost Cycle Controls ........................................................................................ 4-3
 

4.2.5 Defrost Mechanisms ............................................................................................ 4-3
 

4.3 REMAINING TECHNOLOGIES ................................................................................... 4-3
 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

CHAPTER 4. SCREENING ANALYSIS
 

4.1 INTRODUCTION 

This chapter addresses the screening analysis that the U.S. Department of Energy 

(DOE) conducted in support of the ongoing energy conservation standards rulemakings 

for residential central air conditioners and heat pumps. This rulemaking is mandated by 

the National Appliance Energy Conservation Act of 1987 (NAECA), and is effective for 

products manufactured five years after the date of publication of a final rule establishing 

energy conservation standards. 

In the market and technology assessment (chapter 3), DOE presented an initial list 

of technologies that can reduce the energy consumption of central air conditioners and 

heat pumps. The goal of the screening analysis is to screen out technologies that will not 

be considered further in the rulemaking analyses. Some of the technologies considered in 

chapter 3 can reduce annual energy consumption under real-world conditions, but may 

not increase the seasonal energy efficiency ratio (SEER) or heating seasonal performance 

factor (HSPF) as calculated using the DOE test procedure. DOE removed from 

consideration those technologies that do not increase SEER or HSPF. DOE evaluated the 

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) 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)) EPCA also 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, DOE applies the following set of screening criteria to determine 

which design options are unsuitable for further consideration in the rulemaking (Title 10 of 

the Code of Federal Regulations, Part 430, Subpart C, Appendix A at 4(a)(4) and 5(b)): 

Technological feasibility. Technologies incorporated in products or in working 

prototypes will be considered technologically feasible. 

Practicability to manufacture, install, and service. If mass production of a 

technology in products 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. 

Adverse impacts on product utility or product availability. If DOE 

determines that a technology has significant adverse impact on the utility of the product 

to significant subgroups of consumers, or result in the unavailability of any covered 

product type with performance characteristics (including reliability), features, sizes, 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

capacities, and volumes that are substantially the same as products generally available in 

the United States at the time, it will not be considered further. 

Adverse impacts on health or safety. If DOE determines that a technology will 

have significant adverse impacts on health or safety, it will not be considered further. 

In sum, if DOE determines that a particular technology, or combination of 

technologies, fail to meet one or more of the four criteria, it will be screened out. Section 

4.2 below documents the reasons for eliminating any technology. 

4.2 SCREENED-OUT TECHNOLOGIES 

As stated above, technologies that do not increase SEER or HSPF are not 

considered beneficial in the context of this rulemaking. Therefore, DOE removed the 

following technologies from consideration: higher efficiency expansion valves, 

condenser fan motor controllers, liquid-suction heat exchangers (LSHXs), defrost cycle 

controls, and defrost mechanisms. 

4.2.1 High-Efficiency Expansion Valves 

In actual operating conditions, high-efficiency expansion valves such as electronic 

expansion valves (EEVs) can reduce the annual energy consumption of central air 

conditioners and heat pumps by adapting to varying loads and ambient conditions. 

However, because each test within the DOE test procedure is a steady-state test (i.e., tests 

are conducted at a single, specified temperature and relative humidity), there is no 

opportunity for high-efficiency expansion valves to reduce SEER or HSPF. 

Consequently, DOE did not consider high-efficiency expansion valves as a design option 

in the engineering analysis. 

4.2.2 Condenser Fan Motor Controllers 

Under actual operating conditions, condenser fan motor controllers can adapt 

condenser operation to changing ambient temperatures and thereby reduce annual energy 

consumption of central air conditioners and heat pumps. However, because each test 

within the DOE test procedure is a steady-state test (i.e., tests are conducted at a single, 

specified temperature and relative humidity), there is no opportunity to account for the 

effect of a condenser fan motor controller on SEER or HSPF. Consequently, DOE did 

not consider condenser fan motor controllers as a design option in the engineering 

analysis. 

4.2.3 Liquid-Suction Heat Exchangers 

An LSHX is a heat exchanger that serves to cool liquid refrigerant entering the 

expansion valve by utilizing some of the gaseous refrigerant from the evaporator coil. 

The purpose of this is to sub-cool the incoming liquid through superheating of the suction 

vapor. In general, LSHXs are installed in refrigeration systems to ensure proper system 

operation and can potentially improve system performance under actual field operating 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

conditions. However, the performance of an LSHX is dependent upon a number of 

factors, including refrigerant type, operating temperature, and ambient conditions, and 

thus DOE does not have enough information to suggest that an LSHX would consistently 

increase SEER or HSPF as rated using the DOE test procedure. Consequently, DOE did 

not consider LSHXs as a design option in the engineering analysis. 

4.2.4 Defrost Cycle Controls 

A defrost cycle control system is set up to adapt from previous defrost cycles to 

attain improved defrost system operation at various outdoor temperature conditions. This 

technology can save energy annually by using a computer to run the defroster at the 

optimum time and optimum temperature based on the ambient temperature range. 

However, this system adds efficiency because it helps account for outdoor temperature 

variation. The static nature of the DOE test procedure ambient conditions does not allow 

for increases in SEER or HSPF due to implementation of such a system. As a result, DOE 

did not consider defrost cycle controls as a design option in the engineering analysis. 

4.2.5 Defrost Mechanisms 

Several mechanisms exist which may be used to aid in defrosting heat pump heat 

exchanger coils. One of these is the “frost-less” heat pump coil, which adds an 

accumulator to the heat pump cycle, trapping heat from the condenser liquid and using it 

to increase the temperature of the outdoor coil by several degrees. This reduces the 

buildup of frost on the coil, but is only effective within a small range of ambient 

temperatures at and above the freezing point of water. Additionally, such systems 

increase compressor work, and thus do not appear to have any positive benefit on rated 

SEER or HSPF values as measured using the DOE test procedure. 

A second defrost mechanism which currently exists is hot-water defrosting. This 

system uses an additional circuit of valves and tubing which allows for some of the 

refrigerant to be used to heat water, which is then stored and used to defrost the coil by 

being sent through additional tubing around the coil. However, such a system would 

make no impact on the values of SEER or HSPF determined using the DOE test 

procedure. Consequently, DOE did not consider either of these defrost mechanisms as 

design options in the engineering analysis. DOE is not aware of any defrost mechanisms 

other than frost-less heat pumps or hot-water defrost that are currently in use on the 

market or in development that could have a potential benefit to rated SEER or HSPF. 

4.3 REMAINING TECHNOLOGIES 

After eliminating those technologies that do not increase SEER and do not meet 

the four screening criteria described in Section 4.1, DOE is considering the following 

technologies: 

• higher efficiency fan motors 

• higher efficiency fan blades 

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EERE-2008-BT-STD-0006 COMMENT 54
 

• improved evaporator coils 

• improved condenser coils 

• higher efficiency compressors 

• microchannel heat exchangers 

• flat-tube heat exchangers 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 5: ENGINEERING ANALYSIS 

TABLE OF CONTENTS 

5.1 INTRODUCTION ........................................................................................................... 5-1
 

5.2 METHODOLOGY OVERVIEW .................................................................................... 5-1
 

5.3 PRODUCT CLASSES..................................................................................................... 5-2
 

5.4 BASELINE UNITS ......................................................................................................... 5-2
 

5.5 TEARDOWN ANALYSIS.............................................................................................. 5-3
 

5.5.1 Selection of Units................................................................................................. 5-3
 

5.5.2 Generation of Bill of Materials............................................................................ 5-5
 

5.6 COST MODEL ................................................................................................................ 5-6
 

5.6.1 Cost Model Overview.......................................................................................... 5-7
 

5.6.2 Cost Model Assumptions..................................................................................... 5-8
 

5.6.3 Manufacturer Selling Price Estimates................................................................ 5-11
 

5.6.4 Downstream Analyses ....................................................................................... 5-12
 

5.7 NICHE PRODUCTS ..................................................................................................... 5-12
 

5.7.1 Small Duct High Velocity.................................................................................. 5-12
 

5.7.2 Space-Constrained ............................................................................................. 5-15
 

5.7.3 Future Analyses ................................................................................................. 5-17
 

5.8 INDUSTRY COST-EFFICIENCY CURVES............................................................... 5-18
 

5.8.1 Split-System Air Conditioners: Blower-Coil..................................................... 5-18
 

5.8.2 Split-System Air Conditioners: Coil-Only......................................................... 5-22
 

5.8.3 Split-System Heat Pumps .................................................................................. 5-23
 

5.8.4 Single-Package Air Conditioners....................................................................... 5-24
 

5.8.5 Single-Package Heat Pumps .............................................................................. 5-25
 

5.9 MISCELLANEOUS SYSTEM CHARACTERISTICS................................................ 5-25
 

5.9.1 Investigation of the Relationship Between SEER and HSPF ............................ 5-25
 

5.9.2 Calculation of System Weights.......................................................................... 5-30
 

5.10 RESULTS ...................................................................................................................... 5-32
 

5.11 REFERENCES .............................................................................................................. 5-38
 

EERE-2008-BT-STD-0006 COMMENT 54
LIST OF TABLES 

Table 5.6.1: Summary of Raw Material Prices............................................................................ 5-9
 

Table 5.6.2: Purchased Central Air Conditioner and Heat Pump Components........................... 5-9
 

Table 5.6.3: Factory Parameter Assumptions............................................................................ 5-10
 

Table 5.9.1: Comparison of Proposed HSPF Standard Levels with Available Products .......... 5-28
 

Table 5.9.2: Prevalence of HSPF ratings by SEER level for 3-ton Split Heat Pumps with Impacts 

of Suggested HSPF Standards .............................................................................. 5-29
 

Table 5.9.3: Calculated Typical Split-System Air Conditioner Unit Weights .......................... 5-30
 

Table 5.9.4: Calculated Typical Split-System Heat Pump Unit Weights.................................. 5-31
 

Table 5.9.5: Calculated Typical Packaged Air Conditioner Unit Weights................................ 5-31
 

Table 5.9.6: Calculated Typical Packaged Heat Pump Unit Weights ....................................... 5-32
 

Table 5.10.1: Cost-Efficiency Data for Split-System Air Conditioners: Blower-Coil.............. 5-33
 

Table 5.10.2: Cost-Efficiency Data for Split-System Air Conditioners: Coil-Only.................. 5-34
 

Table 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps............................................ 5-35
 

Table 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners................................ 5-36
 

Table 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps ....................................... 5-37
 

LIST OF FIGURES 

Figure 5.2.1: Engineering Analysis Methodology....................................................................... 5-2
 

Figure 5.5.1: Nominal Efficiencies of Selected Split-System Outdoor Units ............................. 5-4
 

Figure 5.5.2: Illustration of System Combinations for Split Systems ......................................... 5-4
 

Figure 5.5.3: Example of BOM Spreadsheet ............................................................................... 5-6
 

Figure 5.6.1: Cost Model Categories ........................................................................................... 5-7
 

Figure 5.6.2: Cost Model Methodology....................................................................................... 5-8
 

Figure 5.6.3: Components of Manufacturer Selling Price ......................................................... 5-11
 

Figure 5.8.1: Illustration of the Absolute Cost versus SEER Relationship ............................... 5-19
 

Figure 5.8.2 Illustration of System Cost Translation Process ................................................ 5-20
 

Figure 5.8.3: Illustration of Cost Trends.................................................................................... 5-21
 

Figure 5.9.1: Relationship Between HSPF and SEER in Available 3-Ton Split-System Heat 

Pumps.................................................................................................................... 5-27
 

Figure 5.10.1: Cost-Efficiency Data for Split-System Air Conditioners: Blower-Coil............. 5-33
 

Figure 5.10.2: Cost-Efficiency Data for Split-System Air Conditioners: Coil-Only ................ 5-34
 

Figure 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps .......................................... 5-35
 

Figure 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners............................... 5-36
 

Figure 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps ...................................... 5-37
 

EERE-2008-BT-STD-0006 COMMENT 54
 

CHAPTER 5. ENGINEERING ANALYSIS 

5.1 INTRODUCTION 

The engineering analysis establishes the relationship between manufacturer selling price 

(MSP) and seasonal energy efficiency ratio (SEER), measured in British thermal units per hour 

per watt (Btu/h/W), for the residential central air conditioners and heat pumps covered in this 

rulemaking. In this analysis, a relationship is also developed for heat pumps between SEER and 

heating seasonal performance factor (HSPF), measured in British thermal units per hour per watt 

(Btu/h/W). The cost-efficiency relationship serves as the basis for subsequent cost/benefit 

calculations for individual customers, manufacturers, and the Nation. In determining this 

relationship, the U.S. Department of Energy (DOE) estimates the increase in the manufacturer 

selling price associated with technological changes that reduce the energy consumption of the 

baseline models. 

The primary inputs to the engineering analysis are data from the market and technology 

assessment (chapter 3 in the TSD), input from manufacturers, baseline specifications and 

production cost estimates developed using a cost model. The primary output of the engineering 

analysis is a set of cost-efficiency curves that represent the average incremental cost of 

increasing efficiency levels above the baseline levels. In the subsequent markups analysis 

(chapter 6 in the TSD), DOE determines customer prices by applying distribution markups, sales 

tax, and contractor markups to the manufacturer sales prices (MSPs) developed in the 

engineering analysis. After applying these markups, the data serve as inputs to the energy use 

characterization (chapter 7 in the TSD) and the life-cycle cost and payback period analyses 

(chapter 8 in the TSD). 

In this chapter, DOE discusses the identification of representative baseline units for each 

class, the methodology used to develop bill of materials and MSPs, the process for constructing 

the cost-efficiency curves, develops an engineering examination of niche product classes, and 

presents cost-efficiency curve outputs. 

5.2 METHODOLOGY OVERVIEW 

This section describes the analytical methodology used in the engineering analysis. In 

this rulemaking, DOE is adopting an efficiency-level approach, which estimates the incremental 

cost of increasing product efficiency. This estimate is based on a reverse engineering analysis 

validated by manufacturer input. First, DOE used information gathered from manufacturers and 

data from the market and technology assessment to identify baseline units and select a set of 

units for teardown analysis. The baseline unit serves as a starting point for the analysis and the 

selected units that span a range of functionality, cooling capacity and efficiency ranges for 

commercially available products. DOE developed a unit cost estimate for the selected products 

by reverse engineering each, developing a bill of materials and inputting the results into a 

manufacturing cost model. To determine the MSP of a machine at each efficiency level, DOE 

added a typical profit to the fully absorbed cost of production. The resulting MSP estimates were 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

used to verify information provided by manufacturers. The results of the engineering analysis are 

a set of cost-efficiency curves, in the form of MSP versus SEER, for each product class. The 

methodology for the engineering analysis is a logical, concise, and reproducible process, as 

illustrated in Figure 5.2.1. 

Identification 

of Baseline 

(5.4) 

Teardown 

Analysis 

(Error! 

Reference 

Cost 

Model 

(5.6) 

CostEfficiency 

Curves 

(5.8) 

Baseline BOM Cost 

Downstream 

Analysis 

(5.6.4) 

MSP 

vs. 

SEER 

Figure 5.2.1: Engineering Analysis Methodology 

5.3 PRODUCT CLASSES 

As discussed in the MTA (chapter 3 of the TSD), DOE identified the following product 

classes for its analysis. 

• Split-system air conditioners 

• Split-system heat pumps 

• Single-package air conditioners 

• Single-package heat pumps 

• Small duct, high velocity systems 

• Space-constrained air conditioners 

• Space-constrained heat pumps 

Conventional products include the first four classes (split-system air conditioners, splitsystem heat pumps, single-package air conditioners, and single-package heat pumps). Niche 

products include the last three classes (small duct, high velocity systems, space-constrained air 

conditioners, and space-constrained heat pumps). The space-constrained product classes are 

assumed to include most through-the-wall air conditioners and heat pumps (both split and single 

package), since through-the-wall products will no longer exist after January 23, 2010a

, which is 

subsequent to the effective date of this rulemaking. Therefore, DOE did not consider those two 

product classes separately. Instead, DOE considered them as space-constrained products. The 

niche product classes are discussed separately and in further detail in section 5.7. 

5.4 BASELINE UNITS 

The identification of baseline units required establishing both a minimum efficiency level 

(minimum SEER rating) and capacity which best represented the span of capacities of 

commercially available products. Currently, the standards for conventional central air 

a

 As defined in 10 CFR 430.2, the through-the-wall product class applies only to products manufactured prior to 

January 23, 2010. This provision eliminates through-the-wall units as a separate product class after this date. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

conditioners and heat pumps (split-system air conditioners, split-system heat pumps, singlepackage air conditioners, and single-package heat pumps) are set at 13 SEER/7.7 HSPF. Thus, 

conventional units that attain only the minimum efficiency rating of 13 SEER/7.7 HSPF will be 

considered baseline units for those product classes. DOE selected a model or models meeting the 

existing minimum Federal energy efficiency standards that are currently offered for sale as 

baseline products. 

Regarding the representative capacity, this rulemaking applies to units with capacities 

below 65,000 Btu/h. For conventional product classes, 36,000 Btu/hour (i.e., 3-tons) was 

selected as the representative capacity for analysis because units at this capacity are ubiquitous 

across manufacturers, have high sales volumes, and span a relatively large range of efficiencies. 

DOE acknowledges, however, that manufacturers tend to optimize residential central air 

conditioner and heat pump systems around the 3-ton capacity. For the NOPR, DOE is 

considering performing additional engineering analyses on 2- and 5-ton capacity products to 

account for potential capacity-related impacts on the cost-efficiency relationship. Baseline units 

serve as a starting point for the engineering analysis and guide the selection process for the 

teardown analysis. 

5.5 TEARDOWN ANALYSIS 

Other than obtaining detailed manufacturing costs directly from a manufacturer, the most 

accurate method for determining the production cost of a product is to disassemble it piece-bypiece, compile a bill of materials (BOM), and estimate the material and labor cost of each 

component. DOE refers to this practice as a physical teardown. A supplementary method, called 

a catalogue teardown, uses published manufacturer product literature and supplementary 

component data to estimate the major physical differences between the catalog teardown unit and 

a similar physical teardown unit. 

Units selected for physical teardowns were dismantled, and each part was characterized 

according to weight, manufacturing processes, dimensions, material, and quantity, in order to 

facilitate the creation of a complete BOM for the product. Bills of materials for catalog 

teardowns are generated by modifying the BOM of a similar unit that has been physically torn 

down to reflect major physical differences. These modifications are based on data taken from 

manufacturer specification sheets and supplementary component data. 

5.5.1 Selection of Units 

The teardown analysis performed for this engineering analysis includes a total of 24 

physical teardowns, including 13 outdoor units (see Figure 5.5.1), 8 indoor units, and 3 

evaporator coils. It also included 7 catalog teardowns for indoor units. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Figure 5.5.1: Nominal Efficiencies of Selected Split-System Outdoor Units 

The collection of products selected for teardown is intended to closely represent the market and 

expose the incremental cost of increasing product efficiency. To accomplish this, DOE selected 

the products for physical teardown and catalog teardown based on the following guidelines: 

1.	 The selected products, taken together, cover the full range of efficiency levels considered 

in the analysis with emphasis placed on efficiencies in the 13-16 SEER range. Figure 

5.5.2 illustrates how indoor and outdoor units from a single manufacturer can be 

combined to provide multiple ratings. 

OUTDOOR UNIT SEER INDOOR UNIT 

OUTDOOR UNIT-A 

OUTDOOR UNIT-B 

OUTDOOR UNIT-C 

INDOOR UNIT-A 

INDOOR UNIT-C 

INDOOR UNIT-B 

13 

14 

16 

18 

20 

Figure 5.5.2: Illustration of System Combinations for Split Systems 

2.	 From most manufacturers, DOE selected at least one low-efficiency product and one 

high-efficiency product, preferably sharing similar characteristics (e.g., same product 

line). 

3.	 The selected products are produced by manufacturers that have relatively large market 

shares in the residential central air conditioning market, and thus are representative of 

typical design approaches. 

4.	 The selected products have minimal product features or options that add cost without 

affecting product efficiency. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

5.	 For split-systems, indoor products were selected based on universality (ability to be 

paired with selected outdoor units) to maximize the number of systems that could be 

modeled. 

5.5.2 Generation of Bill of Materials 

The end result of each teardown was a structured BOM, describing each product 

component and its relationship to the other parts, in the estimated order in which manufacturers 

assembled them. The BOMs describe each fabrication and assembly operation in detail, 

including the type of product needed (e.g., presses, drills) and the process cycle times. The result 

is a thorough and explicit model of the production process. The BOMs incorporate all materials, 

components, and fasteners classified as either raw materials or purchased parts and assemblies. 

The classification into raw materials or purchased parts is based on DOE’s previous industry 

experience, recent information in trade publications, and discussions with high- and low-volume 

original equipment manufacturers (OEMs). DOE also visited several manufacturing plants to 

reinforce its understanding of the industry’s current manufacturing practices. Information was 

gathered to account for product designs specific to central air conditioners and heat pumps and 

ensure that the teardown analysis methodology and pricing were accurate. For purchased parts, 

the purchase price is an estimate based on high-volume price quotations and detailed discussions 

with suppliers. For fabricated parts, the price of intermediate materials (e.g., tube, sheet metal) 

and the cost of transforming them into finished parts is an estimate based on current industry 

pricing. For a continued discussion of the cost details and assumptions, refer to section 5.6.2. 

The BOM for a catalog teardown is identically structured and provides a description in 

equal detail to the BOM of a physical teardown. However, it is generated using a slightly 

different methodology. As stated previously, bills of materials for catalog teardowns are 

generated by modifying the BOM of a similar unit that has been physically torn down. These 

modifications reflect the major physical differences between the units. Specific to this 

engineering analysis, the catalog teardown methodology was employed to generate bills of 

materials for evaporator coils and air handlers. DOE physically tore down 3 evaporator coils and 

8 air handlers. Based on these physical teardowns, DOE executed 4 supplementary evaporator 

coil catalog teardowns and 7 supplementary air handler catalog teardowns. 

Figure 5.5.3 below shows an example of a section of a BOM spreadsheet. Each row of 

the spreadsheet represents a single part of the unit assembly, and includes a description of the 

part, a material type, initial and final dimensions, and weight. These rows also include 

placeholders for the type and number or duration of fabrication processes (stamping, drilling, 

etc.) required to create that part. From this information, a part cost is generated, and the part 

costs are summed across the sheet to create a cost estimate for the entire unit. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 5.5.3: Example of BOM Spreadsheet 

5.6 COST MODEL 

The cost model is a detailed, component-focused, activity-based tool for estimating the 

manufacturing cost of a product. Once teardowns were completed, DOE implemented a 

cost model that could translate the physical information from the BOMs into 

manufacturing costs. The cost model is based on production activities and divides factory 

costs into materials, labor, depreciation, and overhead. DOE defines the cost inputs of these 

broader categories in 

Figure 5.6.1. 

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EERE-2008-BT-STD-0006 COMMENT 54
Major Category Sub-Category Description 

Material Costs 

Direct Raw materials (e.g., coils of sheet metal) and 

purchased parts (e.g., fan motors, compressors) 

Indirect Material used during manufacturing (e.g., welding 

rods, die oil, release media) 

Assembly Part/unit assembly on manufacturing line 

Manufacturing 

Labor 

Fabrication Conversion of raw material into parts ready for 

assembly 

Indirect 

Fraction of overall labor not associated directly with 

product manufacturing (e.g., forklift drivers, quality 

control) 

Supervisory Fraction of indirect labor that 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 

Utilities A fixed fraction of all material costs meant to cover 

electricity and other utility costs 

Other Overhead Maintenance Based on installed equipment and tooling investment 

Property Tax and 

Insurance 

A fixed fraction based on total unit costs 

Figure 5.6.1: Cost Model Categories 

DOE fed the cost data from all the BOMs—whether they were obtained through physical 

teardowns or catalog teardowns—into the cost model. The cost model analysis created cost 

estimates for each of the central air conditioners analyzed in the teardown analysis. The cost 

model uses specific assumptions to provide cost estimates; the following sections describe these 

assumptions. 

5.6.1 Cost Model Overview 

This section provides a general overview of the process by which the cost model converts 

the physical information in each product’s BOM into cost information. After gathering 

component information through physical teardowns and organizing it to form BOMs, the 

resulting data were used as inputs for the cost model spreadsheet. To determine the costs, DOE 

could follow two different paths, depending on whether a subassembly was purchased (outsourced) or produced in-house. For purchased parts, DOE gathered price quotations from major 

suppliers at different production volumes. For parts produced in-house, DOE reconstructed 

manufacturing processes for each part using modeling software based on internal expertise. For 

example, for an access panel, DOE estimated the time required for setup, handling, changeover, 

and punching holes, as well as the number of holes and hits. By repeating this process, DOE was 

able to assign labor time, equipment utilization, and other important factors to each subassembly 

in each of the units considered for this analysis. The last step was the conversion of all this 

information into dollar values. To perform this task, DOE collected information on such factors 

as labor rates, tooling depreciation, and costs of purchased raw materials. DOE assumed values 

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EERE-2008-BT-STD-0006 COMMENT 54
 

for these parameters using internal expertise and confidential information available to its 

contractors. Figure 5.6.2 provides an illustration of the cost model methodology. 

Purchased Parts 

Bill of 

Materials 

Fabrication 

Processes Assembly 

Processes 

Finished 

Materials 

Raw 

Materials 

Figure 5.6.2: Cost Model Methodology 

In sum, DOE assigned costs of labor, materials, and overhead to each part, including coils, 

whether purchased or produced in-house. DOE then aggregated single-part costs into major 

assemblies (e.g., cabinet assembly, condensing unit, evaporator unit, controls, packaging, 

condenser coil assembly, evaporator coil assembly, and compressors) and summarized these 

costs in a spreadsheet. DOE repeated this same process for each unit in the engineering analysis, 

representing a specific efficiency level at the chosen capacity, and mapped the resulting costefficiency points to use as a basis for the cost-efficiency curves. 

5.6.2 Cost Model Assumptions 

Assumptions about manufacturer practices and cost structure play an important role in 

estimating the final cost of the products. DOE used assumptions regarding the manufacturing 

process parameters, e.g., equipment use, labor rates, tooling depreciation, and cost of purchased 

raw materials, to determine the value of each component. It then summed the values of the 

components into assembly costs and, finally, the total product cost. The product cost includes the 

material, labor, depreciation, and overhead costs associated with the manufacturing facility. The 

material costs include both raw materials and purchased part costs. The labor costs include 

fabrication, assembly, and indirect and overhead (burdened) labor rates. The depreciation costs 

include equipment depreciation, tooling depreciation, and building depreciation. The overhead 

costs include indirect process costs, utilities, equipment and building maintenance, and rework. 

The following sections describe the cost model assumptions related to material prices, purchased 

parts and factory parameters. 

5.6.2.1 Material Prices 

DOE determined the cost of raw materials by using prices for copper, steel, and 

aluminum from the American Metals Market.1

 DOE noted that there have been drastic 

fluctuations in metal prices over the last few years. To account for these large fluctuations, DOE 

used prices of metals that reflect a five-year average of the Bureau of Labor Statistics Producer 

Price Indices (PPIs) spanning 2004 to 2009.2

 DOE used the PPIs for steel mill products and 

copper rolling, drawing, and extruding, and adjusted to 2009$ using the gross domestic product 

implicit price deflator.3

 For non-metal materials, such as plastics, DOE uses current PPIs as 

opposed to a five-year average. Table 5.6.1 below lists a selection of the raw material cost values 

used in the cost model. 

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Table 5.6.1: Summary of Raw Material Prices 

Metal Type Five Year Cost Average. 

($/lb 2004-2009) 

Cold Rolled Steel (CRS) $.39 

Aluminized CRS $.55 

Galvanized CRS $.54 

Pre-Painted CRS $.70 

Textured CRS $.61 

Pre-Painted Textured CRS $.86 

Fin Aluminum $1.23 

Cu Tube – Plain for Refrigeration $2.11 

Cu Tube – Rifled for Refrigeration $2.84 

5.6.2.2 Fabricated Parts and Purchased Parts 

DOE characterized parts based on whether manufacturers fabricated them in-house or 

purchased them from outside suppliers. For fabricated parts, DOE estimated the price of 

intermediate materials (e.g. tube, sheet metal) and the cost of forming them into finished parts. 

For purchased parts, DOE estimated the purchase price for OEMs based on discussions with the 

manufacturers. Whenever possible, DOE obtained price quotes directly from suppliers of the 

manufacturers of the units being analyzed. DOE assumed that the components in Table 5.6.2 

below were purchased from outside suppliers. 

Table 5.6.2: Purchased Central Air Conditioner and Heat Pump Components 

Assembly Purchased Sub-Assemblies 

Condensing Unit 

Compressor 

Condenser Fan Blade 

Condenser Fan Motor 

Filter/Dryer 

Hi/Low Pressure Switch 

Accumulator 

Reversing/Shutoff Valve 

Plastic Parts 

Evaporating Unit 

Evaporator Blower 

Evaporator Fan Motor 

TXV/EEV/Orifice 

Plastic Parts 

Controls Control Boards 

Capacitors, transformers, contactors, etc. 

As previously stated, variability in the costs of purchased parts can account for large 

changes in the overall MPC values calculated. Purchased part costs can vary significantly based 

on the quantities desired and the component suppliers chosen. The purchased part prices utilized 

in this study were typical values based on estimated production volume and other factors. In 

actuality, there would be variability in these prices. The role of purchase part prices in the MPC 

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calculation is further magnified because these parts comprise roughly 50-60 percent of these 

systems by cost. Additionally, some parts, such as molded plastic components, may be produced 

in-house by some manufacturers and purchased by others. The choice between these options 

would result in changes to the calculated overall system costs. 

5.6.2.3 Factory Parameters 

Certain factory parameters, such as fabrication rates, labor rates and wages also affect the 

cost of each unit produced. DOE factory parameter assumptions were based on internal 

expertise and manufacturer feedback. Table 5.6.3 below lists the factory parameter assumptions 

used in the cost model. These factory parameters are independent of the efficiency level of the 

unit produced and do not vary between the four major product classes analyzed in the 

engineering analysis. This assumption is consistent with the fact that all major manufacturers 

produce units in all of these product classes, and across a range of efficiency levels. Additionally, 

these assumptions are generalized to represent typical production and are not intended to model a 

specific factory. 

Table 5.6.3: Factory Parameter Assumptions 

Parameter Estimate 

Actual Annual Production Volume (units/year) 1,250,000 

Work Days Per Year (days) 250 

Assembly Shifts Per Day (shifts) 2 

Fabrication Shifts Per Day (shifts) 2.5 

Fabrication Labor Wages ($/hr) 16 

Assembly Labor Wages ($/hr) 16 

Assembly Worker Hours Per Year 3,600 

Fabrication Worker Hours Per Year 4,500 

Length of Shift (hrs) 8 

Units Per Day 6,000 

Average Equipment Installation Cost (% of purchase price) 10% 

Fringe Benefits Ratio 50% 

Indirect to Direct Labor Ratio 33% 

Average Scrap Recovery Value 30% 

Building Cost ($/ft2

) 100 

Worker Downtime 15% 

Building Life (in years) 30 

Burdened Assembly Labor Wage ($/hr) 24 

Burdened Fabrication Labor Wage ($/hr) 24 

Supervisor Span (workers/supervisor) 25 

Supervisor Wage Premium (over fabrication and assembly wage) 30% 

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‐  

   

   

   

   

   

   

   

     

   

   

   

5.6.3 Manufacturer Selling Price Estimates 

The output of the cost model is the manufacturer selling price, or MSP, which includes 

all production and non-production costs, as well as profit. The MSP is related to the MPC 

(manufacturer production cost) by the manufacturer mark-up. The MPC includes all direct costs 

including production-related labor, materials, depreciation and overhead costs (as defined in 

section 5.6). The manufacturer markup is a multiplier that scales MPC to the MSP, and covers 

non-production cost elements, including sales, general and administrative, research and 

development, other corporate expenses and profit. The components of MSP are shown in Figure 

5.6.3. 

Manufacturer

Selling Price

Full Cost of

Product

Manufacturer

Production Cost

Direct

Labor

Direct

Material Overhead

Indirect Labor

Indirect Material

Maintenance

Depreciation

Taxes

Insurance related

to assets

Non Production

Cost

Selling

Market

Research

Advertising

POS Promotion

Salesperson

Comp & Travel

Logistics

(Warehousing,

Delivery, Record‐

Keeping, Order

Processing)

General &

Admin.

Costs of

Service &

Staff Units

General

Corporate

Costs

(Comp, etc)

R & D

Costs associated

with finding new

and improved

products or

processes

Code

Compliance

Modernization

Interest

Cost of

borrowing

funds

Profit

Figure 5.6.3: Components of Manufacturer Selling Price 

The law requires publicly owned companies to disclose financial information on a regular 

basis by filing forms with the U.S. Securities and Exchange Commission (SEC). The SEC form 

10-K, filed by companies annually, provides a comprehensive overview of the company’s 

business and financial conditions. The 10-K report includes the company’s revenues and direct 

and indirect costs. In the preliminary analysis, DOE used 10-Ks from publicly owned residential 

heating product companies to estimate manufacturer markups. The income statement section of 

the 10-K often lists the figures necessary for calculating the manufacturer markup—the net sales, 

costs of sales, and gross profit. After calculating the markup for each manufacturer with 10-K 

data, DOE then calculated a single market-share weighted manufacturer markup to represent the 

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industry. DOE applied a manufacturer markup of 1.32 to the MPC to arrive at a final 

manufacturer selling price. 

5.6.4 Downstream Analyses 

The MSPs derived in the engineering analysis are important inputs to the life-cycle cost 

analysis (LCC) and the manufacturer impact analysis (MIA). In the LCC, the MSPs are 

necessary to calculate the total installed cost of each unit. In the MIA, DOE constructs a number 

of scenarios that analyze how different pricing schemes impact manufacturers financially. In the 

MIA, both MSP and the direct production cost components of MSP are important drivers of 

results. DOE discusses how the engineering analysis is used in the other analyses in chapters 8 

and 12 of the TSD. 

5.7 NICHE PRODUCTS 

For this preliminary analysis, DOE has conducted a basic review of the information 

available regarding products in the niche (small-duct, high-velocity and space-constrained) 

product classes. This consisted of gathering and analyzing publicly available documentation and 

product specification sheets, as well as interviewing some manufacturers directly. At this point, 

however, it should be noted that no formal engineering analysis has been performed, no physical 

or catalogue teardowns have been conducted, and cost-efficiency curves have not yet been 

developed. DOE seeks to perform a full engineering analysis in later stages of the rulemaking, 

including teardowns and cost modeling of units throughout the available efficiency levels, as 

well as modeling of system designs to develop curves depicting theoretical incremental costs of 

efficiency increases. 

5.7.1 Small Duct High Velocity 

Small-duct, high-velocity (SDHV) systems are intended for applications that require 

special design constraints, primarily retrofit applications in older homes and residential buildings 

where the original construction limits the use of conventional ductwork. In these situations, 

SDHV units often serve as the preferred alternative to operating multiple window units or 

installing obtrusive conventional ducting systems. SDHV systems are designed with the intent of 

allowing for simple installation and preserving the appearances of the existing buildings. These 

systems are also utilized in new construction applications, where building designs that would not 

be possible if traditional ductwork, and the required space associated with it, were used. 10 CFR 

430.2 defines “small-duct high-velocity system” as: 

“...a heating and cooling product that contains a blower and indoor coil combination that 

(1) Is designed for, and produces, at least 1.2 inches of external static pressure when 

operated at the certified air volume rate of 220-350 CFM per rated ton of cooling; and (2) 

When applied in the field, uses high velocity room outlets generally greater than 1000 

FPM which have less than 6.0 square inches of free area.” 

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5.7.1.1 Identification of the Baseline 

Currently, the 13 SEER efficiency level mandated by the 2004 technical amendment (69 

FR 50997) to the 2002 final rule applies to all SDHV products. However, all three major 

domestic manufacturers of SDHV units have been granted exceptions to this standard by the 

Office of Hearings and Appeals (OHA), allowing these units to instead adhere to an 11 SEER 

efficiency level. The decisions applying to these manufacturers went into effect on January 23, 

2006 and remain in effect until DOE establishes an independent standard for SDHV systems. 

Therefore, DOE has selected 11 SEER as the current market baseline. Due to the ducting 

constraints mandated by the system size requirements, elevation of system performance to high 

levels is difficult in practice, and manufacturers have stated that they believe the maximum 

technologically feasible efficiency level to be just over 14 SEER. This is in agreement with the 

distribution of efficiency levels of products in the AHRI Certified Directoryb, as roughly 74% of 

the units listed have rated efficiencies between 11 and 12 SEER, while only 5% of units are rated 

at 13 SEER or above. The highest listed efficiency of a matched unit in the AHRI Directory is 

14.5 SEER. 

5.7.1.2 Product Description 

SDHV air conditioners and heat pumps currently sold in the U.S. are similar to traditional 

split-system air conditioners and heat pumps, incorporating an outdoor unit with an indoor 

blower-coil unit. What differentiates SDHV systems from conventional split systems is the use 

of compact ductwork and specialized diffusers designed to accommodate high air velocities, 

combined with a specially designed indoor unit. Since these space constraints only affect the 

indoor portion of the system, the outdoor portion of an SDHV system is a conventional splitsystem model, selected from a manufacturer based on the desired performance specifications of 

the system. The inherent system design constraints prevent SDHV systems from achieving the 

same efficiencies as conventional split-system air conditioners and heat pumps without placing a 

disproportionate burden on consumers and manufacturers. 

Three domestic manufacturers of SDHV systems, SpacePak, Unico, and Energy Saving 

Products, Ltd. (trade name: Hi-Velocity), certify their systems in the AHRI Certified Directory. 

Currently, the AHRI Certified Directory lists 4,469 actively produced mix-match system 

combinations with rated SEER values ranging from 11 SEER to 14.5 SEER. The majority of 

these units are rated between 11 and 12 SEER. The number of distinct SDHV indoor units 

produced by the three manufacturers is quite small compared to the number of choices available 

for the condensing unit, as any conventional condensing unit can be connected to an SDHV 

indoor unit. Additionally, system performance will be constrained by either the condensing unit 

or the blower-coil unit, since the two components are not matched by the manufacturer. Based on 

an examination of the AHRI Certified Directory, for any given SDHV indoor unit, variation of 

the condensing unit can change the system SEER value by up to 3.5 points. 

b

 This refers to the AHRI Certified Directory information as of October 2, 2009, for SDHV air conditioning and heat 

pump units of all residential capacities. 

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SDHV indoor units, along with the return air ducts and supply plenums, are designed to 

fit into confined spaces (e.g., attics, closets, and crawl spaces), within structures that were often 

not originally built with provisions for central air conditioning systems. The design of the SHDV 

unit varies by manufacturer. Spacepak produces packaged blower-coil combination units, while 

Energy Saving Products offers the fan mounted in a housing unit with a space to accommodate 

the evaporator coil, with the coil selectable by the user or installer based on the application. 

Unico produces a modular system, where the blower, evaporator coil, and optional heating coil 

are sold separately and are bolted together by the installer in the desired position, allowing for 

multiple configurations to fit different installation arrangements. 

SDHV ducts possess very small cross-sectional profiles, not more than a few inches in 

diameter. This allows them to be installed in spaces that could not accommodate larger 

conventional ductwork. In other cases, the ductwork is concealed in baseboards or molding, or is 

simply installed visibly along the edge of a wall when no space for concealment exists. In the 

case of new construction, SDHV ducts are often routed between studs in walls and through 

ceilings without requiring the large clearances necessitated by conventional ductwork. These 

systems produce air velocities on the order of four to five times those of conventional systems, 

and as a result, blower motors must be capable of producing high static pressures. However, 

constraints on the maximum velocity of the air through the ductwork and vents exist, imposed by 

the onset of undesirable effects at very high air velocities including noise and drafts within 

rooms. As a result, the maximum volume of air that can be moved per unit time is constrained as 

well. To partially compensate for this limited flow volume, SDHV systems generally operate 

with higher temperature differentials across the evaporator coil in order to achieve the desired 

cooling capacities while moving less air than a conventional split-system air handler. This 

requires that SHDV units utilize evaporator coils with very high efficiencies; however, this 

efficiency gain resulting from the more effective coil is more than offset by the increased power 

consumption of the indoor blower. 

5.7.1.3 Design options 

Based on interviews with SDHV system manufacturers, evaluation of previous analyses, 

and an assessment of SDHV systems currently available, DOE developed a list of design options 

that should be considered in its analysis. This list includes technologies considered to be 

technologically feasible and will serve to establish the maximum technologically feasible (maxtech) design. Due to the aforementioned technological similarities that inherently exist between 

the SDHV and conventional split-system product classes, DOE is currently considering the 

options previously listed for application in split-system air conditioners and heat pumps as 

potential methods for increasing SDHV product efficiency. 

DOE has preliminarily concluded that the ability of manufacturers to implement these 

design options may be limited by the dimensional restrictions imposed upon the systems. 

Namely, the necessity that the indoor unit be compact constrains the maximum possible 

dimensions of the coil. The result is that coil improvements must take the form of improved 

materials and fin designs, or the addition of coil rows to increase effective surface area while 

maintaining the necessary profile. However, increases in coil depth also result in a higher 

pressure drop across the coil, requiring more fan energy to move the air. Manufacturers have 

claimed that they feel additional increases in the size of evaporator coils will not prove to be cost 

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effective. Additionally, the overall rating of an SDHV unit is largely dependent upon the 

condensing unit to which the system is matched. Certain technologies (e.g., high-efficiency fan 

motors and compressors) are required in the condensing unit in order for the whole system to 

achieve the higher efficiency levels. Manufacturers have claimed that a 12 SEER system rating 

generally requires a two-speed compressor on the condensing unit, while a 13 SEER system 

rating can only be attained through the use of a variable-speed compressor. Since the design of 

these condensing units is beyond the control of the SDHV system manufacturer, mandating 

efficiency levels which would require consumers to purchase more costly products from other 

manufacturers could lead to negative consequences for the industry. 

5.7.1.4 Cost of Efficiency Improvements 

Due to constraints on the implementation of the design options available to 

manufacturers, increases in system efficiency would come at a high cost, and improvements 

would meet with diminishing returns beyond a certain point. Increases in coil size would likely 

incur corresponding increases in coil cost, as material costs are the biggest contributor to the 

pricing of coils. Additionally, improved fin designs or other design features would come at a 

high cost as well. Moreover, since overall system performance is highly dependent upon the 

efficiency of the outdoor unit, which is produced by a different manufacturer altogether, costs 

passed on to the consumer in upgrading to a higher-efficiency system would be greater than 

those encountered by the SDHV system manufacturers. 

5.7.2 Space-Constrained 

Certain types of central air conditioners and heat pumps are manufactured for 

applications with space constraints and, therefore, have features that distinguish them 

from the majority of products available. Sometimes these products are not able to meet 

standards designed for conventional split-system air conditioners and heat pumps, or are 

able to, but, in doing so, place a disproportionate burden on manufacturers and 

consumers. This product class covers the products that DOE has determined to fit the 

definition of space constrained. 10 CFR 430.2 defines “space-constrained product” as: 

“...a central air conditioner or heat pump: 

(1) That has rated cooling capacities no greater than 30,000 BTU/hr; 

(2) That has an outdoor or indoor unit having at least two overall exterior dimensions or 

an overall displacement that: 

(i) Is substantially smaller than those of other units that are: 

(A) Currently usually installed in site-built single family homes; and 

(B) Of a similar cooling, and, if a heat pump, heating capacity; and 

(ii) If increased, would certainly result in a considerable increase in the usual cost 

of installation or would certainly result in a significant loss in the utility of the product to 

the consumer; and 

(3) Of a product type that was available for purchase in the United States as of December 

1, 2000.” 

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5.7.2.1 Identification of the Baseline 

In the 1999 SANOPR, DOE first suggested separate product classes as a way to set 

standards for these niche products. 64 FR at 66310. Originally, these products were believed to 

include through-the-wall (TTW) split systems, single-package vertical units (SPVU), ductless 

split systems, and SDHV systems. As of the 2000 NOPR, TTW single-package and nonweatherized single-package systems were also added to this product class. In the 2004 Technical 

Amendment, DOE established a separate product class for space-constrained systems, requiring 

them to meet a 12 SEER standard. TTW systems were made their own product class, and were 

required to meet a 10.9 SEER standard; however, this is set to expire on January 23, 2010. 

Within the scope of this rulemaking, SDHV units have been granted consideration as a separate 

product class, and ductless split systems are being considered as part of the conventional splitsystem air conditioner and heat pump product classes. SPVU’s are considered to be commercial 

equipment, and thus do not fall under the scope of this rulemaking. Additionally, there currently 

appears to be no major manufacturer of domestically-sold single-package non-weatherized units. 

As a result of these changes since the last rulemaking, DOE is currently unaware of any products 

which would fall within the classification of space-constrained products aside from TTW units. 

For this reason, DOE is considering TTW products as the basis for its study of this product class. 

DOE seeks feedback regarding this decision and any other existing products that may be 

considered space-constrained. 

5.7.2.2 Product Description 

There are two main types of TTW products: (1) TTW split systems and (2) TTW singlepackage systems. TTW products were popular in new multi-story residential construction in the 

1960s and 1970s. Major OEMs have since abandoned the replacement market, providing an 

opportunity for lower-volume manufacturers, such as First Company, National Comfort 

Products, and EnviroMaster International .The replacement market is now dominated by these 

lower-volume manufacturers. Most TTW products are in the 1-1/2 to 2-1/2 ton (18,000 Btu/h to 

30,000 Btu/h) capacity range. Residents and building owners are particularly sensitive to any 

increase in price, especially the cost of enlarging the wall opening to accommodate a larger 

product. As a result, new TTW products for retrofit applications must fit within the same wall 

opening as the original units. Since repair is the only other cost-effective alternative to 

replacement, a new standard that increases cabinet size or results in a significant price increase 

could be counter-productive, preventing the turnover of old, inefficient products and instead 

encouraging users to repair those existing units. 

5.7.2.3 Design Options 

DOE uses information about existing and past technology options and prototype designs 

as input in identifying technologies manufacturers could use to meet and/or exceed energy 

conservation standards. In consultation with interested parties, DOE is developing a list of 

technologies that should be considered in the analysis. This list consists of all those technologies 

considered to be technologically feasible and will serve to establish the max-tech design. Due to 

the technological similarities that inherently exist between the space-constrained and 

conventional split-system product classes, DOE is currently considering the options previously 

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EERE-2008-BT-STD-0006 COMMENT 54
listed for application in split-system air conditioners and heat pumps as potential methods for 

increasing space-constrained product efficiency. 

DOE conducted preliminary MIA interviews and various engineering evaluations to 

investigate the technology options available to space-constrained product manufacturers to 

increase the energy efficiency of their units. Based on this investigation, DOE has preliminarily 

concluded that unique factors may prevent TTW products from realizing the full potential of 

many energy saving design options. Typically, increased condenser coil surface area is the most 

cost-effective energy saving measure. However, manufacturers of these products are limited in 

their ability to implement this option by the apparent constraints upon coil size inherently present 

in this product class, and some manufacturers have expressed concern that the available 

condenser coil surface area may have already been maximized in order to reach the 10.9 SEER 

standard. Similarly, manufacturers have claimed that the number of coil rows has also been 

maximized to the point at which the addition of further rows would provide insignificant returns. 

Other coil improvements, such as micro-channel tubing, have not yet proven effective during 

research and development testing. Specifically, manufacturers have been unable to solve 

defrosting issues, calling into question the technological feasibility of this design option. If coil 

improvements are insufficient to increase product efficiency, TTW manufacturers must explore 

more costly design options, such as high-efficiency compressors and fan motors and controls. 

According to certain manufacturers, variable-speed motors are unavailable for the lower 

capacities of TTW split systems, and higher-efficiency compressors are already in products on 

the market, having been implemented to meet the 10.9 SEER standard. As lower-volume 

producers of a niche product, TTW manufacturers may not have the resources or the influence on 

component suppliers to make advancements in motor or compressor technology that could make 

them cost-effective energy saving design options for TTW products. 

5.7.2.4 Cost of Efficiency Improvements 

Based on manufacturer feedback, DOE estimates the MPC of a typical 10.9 SEER splitsystem TTW air conditioner to be between $700 and $800. According to certain TTW 

manufacturers, compliance with the 12 SEER standard for space-constrained products comes 

with an estimated increase in material costs of 15-20%, resulting in cost increases throughout the 

distribution chain. To surpass the 12 SEER standard, TTW manufacturers would have to utilize 

very efficient components purchased from outside suppliers, such as variable-speed fan motors 

and inverter-driven compressors that could greatly increase the MPC. Since the cost of these 

components would be entirely dependent upon the suppliers, TTW manufacturers claim that they 

would be unable to control the costs incurred in procuring these purchased parts, and would be 

forced to pass those costs on to their distributors and, ultimately, consumers. 

5.7.3 Future Analyses 

For this preliminary analysis, DOE did not conduct physical or catalog teardowns on 

these niche products, nor has it developed an engineering model to evaluate the performance of 

the included products. DOE also has not determined what the values of the max-tech SEER 

levels are for these products, due to the scarcity of quantitative data. However, for future stages 

of the rulemaking, DOE has developed a suggested analytical methodology to study these niche 

product classes. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Since SDHV manufacturers only produce the indoor portions of these systems, DOE 

proposes an approach similar to that used with blower-coil split air conditioning systems 

(described in section 5.8.1). As the ratings of specific indoor SDHV systems vary across 

different condensing units, teardowns of a few models from different manufacturers should be 

sufficient to facilitate the development of a cost-efficiency curve across the entire range of 

possible efficiencies, from baseline to max-tech. 

The space-constrained (TTW) air conditioners and heat pumps differ from the SDHV 

systems and other product classes in that all the products currently manufactured are rated at an 

efficiency level of 12 SEER. Therefore a conventional teardown analysis alone will not yield 

sufficient information regarding the cost and effectiveness of incremental efficiency 

improvements. For these products, DOE proposes that information and specifications for 

baseline units be gathered from teardowns of products currently on the market. This baseline 

information will then be used as inputs into models and simulations which will be used to 

explore the possible options that could be used to product incremental increases in efficiency. 

DOE seeks input from interested parties regarding this analytical methodology for the niche 

product classes. 

5.8 INDUSTRY COST-EFFICIENCY CURVES 

5.8.1 Split-System Air Conditioners: Blower-Coil 

In new construction applications, a complete system is always installed. In replacement 

applications for split-system air conditioners, consumers are presented with two options: (1) 

replace a portion of their system, or (2) replace the entire system. For the first option, if a 

consumer has a furnace installed and a portion of the air conditioning system (i.e., condensing 

unit or evaporator coil) fails, the consumer may choose to only replace the air conditioning 

portion of the system. This scenario involves the replacement of a condensing unit and an 

evaporator coil used with the existing fan blower in the furnace. In these applications, 

manufacturers are constrained by the fan blower in the installed furnace, they only have the 

ability to modify the condensing unit or evaporator coil to achieve the desired efficiency. These 

systems are referred to as coil-only systems, and are tested and rated using the combination of a 

specific condensing unit and evaporator coil with default fan specifications identified in the test 

procedure. 

For the second option, if the entire system is replaced, the consumer has the ability to 

select a combination of indoor and outdoor units that can achieve any efficiency within the 

commercially available range of efficiencies for split-system air conditioners. Since the systems 

are sold as specific combinations of indoor and outdoor units, manufacturers have the ability to 

modify all portions of the system (i.e., condensing unit, evaporator coil, and evaporator fan 

blower) to achieve the desired efficiency. These systems are referred to as blower-coil systems 

and are tested and rated using the combination of a specific condensing unit, evaporator coil, and 

evaporator fan blower. Since manufacturers have more options to improve the efficiency of a 

blower-coil system, the cost-efficiency relationship is inherently different than for coil-only 

systems. Both types of systems are prevalent in the marketplace, and DOE characterized split5-18 

EERE-2008-BT-STD-0006 COMMENT 54
 

system air conditioners with a separate cost-efficiency curve for blower-coil and coil-only 

systems. 

DOE first developed an industry cost-efficiency curve for blower-coil, split-system air 

conditioners using the process listed below. These products span the largest efficiency range and 

are the highest-selling product class of all central air conditioners and heat pumps. Creating the 

industry cost-efficiency curve for split-system air conditioners was a four-step process that 

consisted of: (1) plotting the raw data points as absolute system cost versus efficiency, (2) 

translating the absolute system costs by manufacturer to common normalized system costs, (3) 

trending system and subsystem costs, and (4) aggregating the cost data to develop a costefficiency curve representative of the industry. The details of these steps are described in this 

section. 

5.8.1.1 Plotting Absolute System Cost Versus Efficiency 

The cost model analysis developed cost estimates for each of the teardowns, as detailed 

in section 5.6. The output from the model includes all manufacturing costs, which includes 

corporate overhead expenses. DOE developed system costs for blower-coil, split-system air 

conditioners by summing the costs of specific matched pairs of condensing units and air 

handlers. DOE selected matched pairs from manufacturer specification sheets and the AHRI 

database to span the entire efficiency range for split-system products. The combined cost, called 

“absolute system cost” for purposes of this analysis, is the cost to manufacture each system—it is 

not the final cost to the end-user, because it does not include the manufacturing and distribution 

channel markups. 

The absolute system cost from the model is plotted as a function of each product’s 

efficiency—given as SEER. Manufacturers publish SEER values for each of their products, 

according to AHRI specifications. DOE does not present any absolute costs in this document, 

because doing so could expose sensitive financial information about individual manufacturers’ 

products. Figure 5.8.1 illustrates how DOE plotted absolute system cost versus efficiency 

Figure 5.8.1: Illustration of the Absolute Cost versus SEER Relationship 

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5.8.1.2 Translating Absolute System Cost to Normalized System Cost 

For the next step in the process of creating the industry cost-efficiency curves, DOE 

normalized the absolute system costs from each manufacturer. DOE shifted system costs for 

products made by the same manufacturer equally, but shifted system costs for products made by 

different manufacturers independently. 

As illustrated in Figure 5.8.2, the cost translation process shifted the absolute system 

costs of each manufacturer’s products so that the cost of the baseline system (i.e., 13 SEER) is 

consistent across all manufacturers. By ensuring that all manufacturers shared a common 

baseline system cost, DOE was able to compare manufacturers’ data points directly while 

maintaining each manufacturer’s incremental costs as efficiency increases, allowing for a direct 

analysis of the cost of efficiency improvements regardless of baseline costs. To do this, DOE 

first identified the lowest cost 13 SEER system and the manufacturer that produced that system. 

DOE then shifted other manufacturers’ absolute system cost data points down until each 

manufacturer’s lowest-cost 13 SEER system matched the overall lowest-cost 13 SEER system. 

DOE realizes that other methods of normalizing the data are available, such as shifting the cost 

values to center the curves at a market-weighted average rather than the lowest cost, and such 

methods could be considered for use in further analyses. Normalized Cost 

SEER 

Figure 5.8.2 Illustration of System Cost Translation Process 

In analyses downstream of the engineering analysis, DOE accounted for the fact that in 

replacement applications, some consumers will not replace their entire air conditioning system. 

For this scenario, DOE assumed that the consumer will only replace the condensing unit and the 

evaporator coil. For more detail on these replacement scenarios, see chapter 8 of the preliminary 

TSD. In order to model these scenarios, DOE estimated costs for different portions of the central 

air conditioning system. Therefore, DOE simplified the output from the cost model into five 

subsystems for each split-system air conditioner analyzed. The five subsystems were: (1) 

condensing unit, (2) indoor unit casing (sheet metal and insulation), (3) evaporator coil, (4) 

evaporator fan blower, and (5) balance of indoor unit. 

In addition to normalizing system costs, DOE also normalized the subsystem costs that 

were estimated from cost model data. This step was necessary in order to ensure that the sum of 

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EERE-2008-BT-STD-0006 COMMENT 54
 

the subsystem costs equated to the normalized overall system costs developed previously. To do 

this, for each absolute system cost, DOE calculated the percentage that each absolute subsystem 

cost accounted for in the total. DOE then applied these same percentages, specific to each system 

cost, to the normalized system cost to estimate the normalized subsystem costs. As a result, the 

normalized subsystem costs were scaled proportionally to the normalized system costs. 

5.8.1.3 Trending System and Subsystem Costs 

It is rare that a single manufacturer produces a system at every efficiency level 

throughout the entire operating efficiency range of central air conditioners and heat pumps. In 

addition, some manufacturers produce multiple systems in different product lines that achieve 

the same rated efficiency. These variations in product offerings across different manufacturers 

introduce complications to the analysis which must be addressed through trending of the data. 

Trending by manufacturer ensures that there is data at every efficiency level for each 

manufacturer studied, allowing for aggregation across all manufacturers at every data point. If 

the data were not trended, certain efficiency levels would contain more models from some 

manufacturers than others, or perhaps no models at all from some manufacturers. This would 

introduce an undesired weighting effect into the data once the aggregated curves were developed, 

with some manufacturers’ products at certain efficiency levels essentially being represented 

more than others. Therefore, DOE developed trends to estimate each manufacturer’s production 

costs at all efficiency levels. Figure 5.8.3 illustrates the type of trends that DOE developed, first 

showing trend lines produced from normalized data for each manufacturer, then showing an 

overall trend line created using aggregated normalized data. 

Figure 5.8.3: Illustration of Cost Trends 

According to discussions with manufacturers, examination of manufacturer specification 

sheets, and conducting physical teardowns, DOE found that system costs generally increase 

linearly with respect to efficiency from 13-14 SEER. At these lower efficiencies, the most costeffective method for manufacturers to achieve efficiency gains is to increase the surface area of 

the heat exchangers. Without strict constraints on the size of the heat exchangers, the efficiency 

gains resulting from their increased size are relatively proportional to the additional material, and 

thus cost. As air conditioners become more efficient, it becomes increasingly difficult and costly 

to increase efficiency to the next higher level. This is partly because traditional lower-cost design 

changes, such as increasing heat exchanger surface area, may not suffice. This relationship 

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becomes increasingly evident at efficiencies greater than 14 SEER. Therefore, DOE derived the 

system cost-efficiency curve for each manufacturer using a linear line-fit from 13-14 SEER, and 

an exponential curve-fit for efficiencies greater than 14 SEER. 

DOE also developed trends for the five subsystems described above. When examining 

the normalized subsystem costs, DOE found that each manufacturer used different methods to 

increase system efficiency. While each manufacturer’s system costs exhibited a similar trend as 

efficiency increased, the differences in the subsystem trends between different manufacturers 

were masked since all of the subsystem costs summed to the system cost. Therefore, DOE 

analyzed every subsystem from each manufacturer on an individual basis when developing 

trends to estimate subsystem costs for the operating efficiency range of split-system air 

conditioners. 

5.8.1.4 Aggregating System and Subsystem Costs 

To develop the industry cost-efficiency curve for split-system air conditioners, DOE 

aggregated the manufacturer cost-efficiency curves at both the system and subsystem level. 

Since DOE only developed curves for four manufacturers, it adjusted market shares of those four 

manufacturers to represent the entire industry. DOE then used those adjusted market shares to 

weight each manufacturer’s cost-efficiency data. The result was a cost-efficiency curve that 

represented the MPC at each efficiency level for the industry, as well as five subsystem costefficiency curves. 

Since DOE evaluated the subsystems individually for each manufacturer, there were 

small discrepancies between the sum of the aggregated subsystem cost-efficiency curves and the 

aggregated system cost-efficiency curve. Therefore, DOE calibrated the subsystem costs such 

that their sum at each efficiency level was consistent with the system cost at each level. 

5.8.2 Split-System Air Conditioners: Coil-Only 

Since coil-only, split-system air conditioners rely on a default evaporator fan power to 

achieve their SEER rating, DOE’s cost-efficiency curve consisted of only two subsystems, a 

condensing unit and an evaporator coil. Because a coil-only system is constrained by the default 

evaporator fan power in the test procedure, the system faces additional limitations in the 

maximum achievable (i.e., max-tech) SEER level compared to blower-coil systems. Referring to 

the AHRI Certified Directory, DOE determined that the max-tech for coil-only systems was 

roughly 16.5 SEER. Upon review of these systems, DOE found that this max-tech level was 

achieved using a condensing unit similar to a condensing unit used in a 19-20 SEER blower-coil 

system. DOE also found that at lower efficiencies (i.e., 13-14 SEER), the condensing units and 

evaporator coils were very similar to blower-coil systems of the same SEER level. Due to the 

parallels between coil-only and blower-coil systems, DOE used its estimated blower-coil costefficiency curve as the basis for the coil-only cost-efficiency curve. 

As a starting point for the coil-only cost-efficiency curve, DOE eliminated the indoor unit 

casing, evaporator fan blower, and balance of indoor unit subsystems from the blower-coil costefficiency curve. Using manufacturer specification sheets and the AHRI Certified Directory, 

DOE then compared the SEER ratings of the same condensing unit when rated as a blower-coil 

5-22 

EERE-2008-BT-STD-0006 COMMENT 54
 

and a coil-only system. DOE found that through 14 SEER, the condensing units were generally 

consistent between blower-coil and coil-only systems. Above 14 SEER, higher-efficiency 

condensing units were typically required in coil-only systems to achieve the same SEER levels 

as blower-coil systems. 

When assessing the differences between the evaporator coils in coil-only and blower-coil 

systems, DOE found that above the baseline, higher-efficiency evaporator coils were typically 

required for coil-only systems to achieve the same SEER levels as blower-coil systems. As the 

system efficiencies increase, the disparity between the complexity and cost of evaporator coils 

used in blower-coil and coil-only systems also increases. 

5.8.3 Split-System Heat Pumps 

To develop a split-system heat pump cost-efficiency curve, DOE used manufacturer 

specification sheets and limited heat pump teardowns to modify the blower-coil, split-system air 

conditioner cost-efficiency curve. DOE maintained the breakdown of system costs into the five 

subsystems used for blower-coil, split-system air conditioners. DOE first examined manufacturer 

specification sheets to identify any differences in the indoor units used in air conditioners and 

heat pumps. DOE found that the indoor units used in 13 SEER split-system heat pumps are 

generally the same indoor units that are used in 13.5 SEER split-system air conditioners. This 0.5 

SEER offset between the indoor units used with heat pumps and air conditioners existed 

throughout the entire efficiency range. Therefore, DOE shifted all split-system air conditioner 

subsystem costs relating to the indoor unit (i.e., indoor unit casing, evaporator coil, evaporator 

fan blower, and balance of indoor unit)c

 down by 0.5 SEER to modify the cost-efficiency curve 

to be applicable to split-system heat pumps. 

Next, DOE compared the condensing units (i.e., outdoor units) used in split-system air 

conditioners and heat pumps. To do this, DOE compared the estimated system cost (based on 

teardowns) of a 13 SEER heat pump with a 13 SEER air conditioner from the same 

manufacturer. DOE calculated the percentage increase in cost of the system for that 

manufacturer. DOE then applied this percentage increase to the estimated industry cost of a 13 

SEER split-system air conditioner to estimate the industry cost of a 13 SEER split-system heat 

pump. From this, DOE used the estimated industry cost of the indoor unit of a 13 SEER heat 

pump to back out the industry cost of an outdoor unit for a 13 SEER heat pump. DOE then 

calculated the percentage increase in the industry cost of an outdoor unit for a 13 SEER heat 

pump compared to a 13 SEER air conditioner. DOE applied this percentage increase to the 

industry costs of outdoor units for split-system air conditioners to estimate the costs of outdoor 

units for split-system heat pumps throughout the entire efficiency range. 

DOE determined that the max-tech level for split-system heat pumps was 19.5 SEER 

using the AHRI Certified Directory. Since this max-tech level fell between two split-system air 

conditioner SEER levels that were used to estimate the cost of the indoor and outdoor portions of 

c

 For heat pump products (split-system and single-package), DOE refers to the heat exchangers and associated 

system components with respect to their functionality while the system is in cooling mode. For example, in a splitsystem heat pump, the outdoor heat exchanger is referred to as the condenser coil and the indoor heat exchanger is 

referred to as the evaporator coil. 

5-23 

EERE-2008-BT-STD-0006 COMMENT 54
 

the system, DOE interpolated between the two levels. DOE then examined manufacturer 

specification sheets for high-efficiency systems to validate the costs estimated using the blowercoil, split-system air conditioner cost-efficiency curve. DOE did not develop a separate coil-only 

cost-efficiency curve for split-system heat pumps as it did for air conditioners. DOE believes that 

the majority of split-system heat pumps are sold as a matched set of indoor and outdoor units for 

both the new construction and replacement markets. However, DOE recognizes that in some 

instances heat pumps are used in conjunction with gas- or oil-fired furnaces today providing a 

“dual-fuel” heating capability. DOE seeks input on the characterization of the heat pump 

replacement market and whether installations of matched sets of indoor and outdoor products 

should be the basis for DOE’s analysis for all heat pumps. 

5.8.4 Single-Package Air Conditioners 

The basic system components of a single-package air conditioner are very similar to a 

split-system air conditioner. However, the system configurations differ enough that incremental 

costs cannot be estimated based simply on the incremental costs of a split-system air conditioner, 

as was done for split-system heat pumps. Rather, DOE used manufacturer specification sheets 

and information from manufacturer interviews to determine the sizes and complexity of 

components in the baseline system. DOE relied on the cost estimates from split-system air 

conditioners to estimate the costs for various single-package air conditioner components for the 

baseline system. To estimate component costs for single-package air conditioners, DOE 

separated the condensing unit costs for split-system air conditioners into individual component 

costs (i.e., unit casing, condensing coil, condensing fan, compressor, sealed system components, 

and a balance of the condensing unit). DOE then considered the costs of individual components 

at each efficiency level when developing cost estimates for a baseline single-package air 

conditioner. 

To estimate the cost of the baseline casing, DOE used the sum of the indoor unit and 

outdoor unit casings for a 13 SEER split-system air conditioner. DOE found that the baseline 

condensing coils in single-package air conditioners are typically about 10-percent larger than 

those used in 13 SEER split-system air conditioners. Therefore, DOE estimated the baseline cost 

for the condensing coil as 1.1 times the cost of a 13 SEER split-system air conditioner 

condensing coil. DOE also found that variable-speed evaporator fan blowers are typically 

implemented in single-package air conditioners at 13.5 SEER, compared to 14.5 SEER in splitsystem air conditioners. So, DOE estimated that the baseline cost of the evaporator fan blower 

was approximately the same as a 14 SEER split-system air conditioner evaporator fan blower. 

DOE assumed that the baseline costs of the remaining system components were identical to those 

estimated for a 13 SEER blower-coil, split-system air conditioner. 

Once DOE established the component costs for a baseline single-package air conditioner, 

DOE examined the AHRI Certified Database to determine that the max-tech level was 16.6 

SEER. Using information from discussions with manufacturers and product specification sheets, 

DOE estimated the incremental costs of each component from 13-16 SEER in 0.5 SEER 

increments as well as for the 16.6 SEER max-tech level. For simplicity, DOE then grouped the 

component costs into two subsystems: (1) evaporating, and (2) condensing. The evaporating 

subsystem consisted of the evaporator coil and the evaporator fan blower. The condensing 

5-24 

EERE-2008-BT-STD-0006 COMMENT 54
subsystem consisted of all the remaining components in the system. The sum of these two 

subsystems at each efficiency level provides the system MPC for that level. 

5.8.5 Single-Package Heat Pumps 

DOE derived the single-package heat pump cost-efficiency curve using a similar 

methodology as was used to develop the split-system heat pump cost-efficiency curve. However, 

DOE used the single-package air conditioner cost-efficiency curve as the basis rather than the 

split-system air conditioner cost-efficiency curve. DOE retained the two subsystems used for 

single-package air conditioners. To develop the cost-efficiency curve for single-package heat 

pumps, DOE first examined manufacturer specification sheets to identify any differences in the 

evaporator coils and evaporator fan blowers used in air conditioners and heat pumps. DOE found 

that the baseline heat pumps typically used a variable-speed evaporator fan blower. DOE also 

found that the evaporator coils used in 13 SEER heat pumps were about the same size those used 

13.5 SEER air conditioners. This 0.5 SEER offset between the indoor units used with heat pumps 

and air conditioners existed throughout the entire efficiency range. Therefore, DOE shifted the 

evaporating subsystem costs for the single package air conditioners down by 0.5 SEER to 

modify the cost-efficiency curve to be applicable to single-package heat pumps. Next, DOE 

increased the condensing subsystem cost for single-package air conditioners by the same 

percentage used to estimate the cost of the outdoor unit for split-system heat pumps. This was 

done for all efficiencies. 

DOE determined that the max-tech level for split-system heat pumps was 16.4 SEER 

using the AHRI Certified Directory. For the condensing subsystem, this max-tech level fell 

between two single-package air conditioner SEER levels that were used to estimate its cost. So, 

DOE interpolated between the two SEER levels to estimate a corresponding cost for 16.4 SEER. 

For the evaporating subsystem, the air conditioner costs were shifted down by 0.5 SEER, but the 

max-tech level for heat pumps was only 0.2 SEER less than air conditioners. Therefore, DOE 

trended the evaporating subsystem costs using a line of best fit to estimate the subsystem cost at 

16.4 SEER. The sum of these two subsystems at each efficiency level provides the system MPC 

for that level. 

5.9 MISCELLANEOUS SYSTEM CHARACTERISTICS 

5.9.1 Investigation of the Relationship Between SEER and HSPF 

Energy efficiency standards for heat pumps must establish minimum values for HSPF as 

well as SEER. However, this analysis thus far has only been performed in terms of rated SEER 

values, with no trending or aggregation of data with regard to HSPF. In past rulemakings, 

analyses performed in terms of SEER were used as grounds for determination of HSPF 

standards. As part of this analysis, DOE investigated whether the relationship between HSPF and 

SEER is substantial enough to allow a SEER standard to serve as a basis for an HSPF standard as 

well. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

5.9.1.1 Split-System Heat Pumps 

Since SEER and HSPF are calculated values and incorporate factors other than the 

physical properties of the system, no direct relationship between the two would be expected. As 

Figure 5.9.1 illustrates, a survey of available split-system heat pump products, procured from the 

AHRI Certified Directory, supports this hypothesis. Each band in the Figure represents 20 

percent of the products available at the stated SEER level. Although HSPF generally increases 

with SEER, the statistical correlation is rather low (0.626). However, the relationship between 

SEER and HSPF is fairly close over the majority of the SEER values studied, with the middle 60 

percent of the HSPF values falling within a range of +/-0.45 points of the median at SEER values 

of 17 and below. 

To set energy efficiency standards for heat pumps, DOE must determine both an HSPF 

level and a SEER level. This complicates the analysis since each SEER level corresponds to a 

range of varied HSPF ratings. To provide a rationale for selecting SEER-HSPF pairs, DOE 

examined plots based on Figure 5.9.1 that showed the number of models possessing each HSPF 

at each SEER level. Table 5.9.2 lists the results. A proposed minimum HSPF requirement was 

determined based on the distribution of the products currently available throughout the range of 

efficiency levels. Median (50th percentile) HSPFs are generally well above the minimum HSPF 

level proposed, except at the higher SEER levels, where closer to 40 percent of units studied fall 

above these values. This is due to the perceived ability of high-SEER products to attain higher 

HSPF values as well, and follows relationships used in past CAC rulemakings. DOE realizes that 

a number of different methodologies could be utilized in setting the relationship between SEER 

and the required corresponding HSPF. One of these methods could be to construct a line which 

follows the median of the existing data, then offset it so that a chosen percentage of the products 

currently on the market would remain above this line. Such an alternative method could be 

considered in studying the SEER-HSPF relationship during later phases of this rulemaking. 

5-26 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Source: 2008 AHRI Directory of Certified Product Performanced 

Figure 5.9.1: Relationship Between HSPF and SEER in Available 3-Ton Split-System Heat 

Pumps 

After examining the distribution data, DOE plotted the relationship between HSPF and 

SEER for all 3-ton split-system heat pumps currently listed as active in the AHRI Certified 

Directory. At the baseline efficiency of 13 SEER, the difference between the minimum HSPF 

(6.7) and the median (8.0) is 1.3 HSPF. However, the existing standard is 7.7 HSPF, and for this 

reason, DOE chose not to include any units below this level in its analysis. From this base point 

of 7.7 HSPF at 13 SEER, DOE then defined a line that generally followed the median HSPF at 

each SEER level while passing through the 13 SEER, 7.7 HSPF point: 

Equation 5.9.1 

Equation 5.9.2 

The proposed minimum HSPF requirements are derived by inserting the minimum SEER 

requirements into the formula. Even though DOE does not have information on the distribution 

of heat pump sales by HSPF at each SEER level, it is apparent that the market currently favors 

products that exceed the minimum allowable HSPF level. This is due both to the correlation 

between HSPF and SEER and the preference in the market for higher HSPF heat pumps in cooler 

d The AHRI Directory contains some models listed as currently produced which fall below the minimum current 

HSPF value. 

5-27 

EERE-2008-BT-STD-0006 COMMENT 54
 

climates. DOE believes that establishing an HSPF standard well above the current median at a 

given SEER level would impose an undue design constraint on manufacturers, adding to the cost 

and burden of designing, producing, testing, and qualifying the product without resulting in a 

significant increase in the average HSPF of products sold. Table 5.9.1 summarizes the selection 

of HSPF standard levels: 

Table 5.9.1: Comparison of Proposed HSPF Standard Levels with Available Products 

Efficiency/Standard 

Level 

(SEER) 

13 14 15 16 17 18 19 

Recommended 

Minimum 

HSPF 

7.7 8 8.3 8.6 9.1 9.6 10.1 

Median HSPF in 

Available 

Products 

8 8.3 8.6 9 9.2 9.25 9.05 

Offset from Median 

(HSPF) -0.30 -0.30 -0.30 -0.40 -0.10 0.35 1.05 

Fraction of Available 

Products Below 

Recommended HSPF 

Level 

<10% <10% <40% <20% <30% <70% <70% 

Source: 2008 AHRI Directory of Certified Product Performance 

Table 5.9.2 provides a more detailed breakdown of the models available at each 

efficiency level as well as the total number of models at each efficiency level. 

5-28 

EERE-2008-BT-STD-0006 COMMENT 54
Table 5.9.2: Prevalence of HSPF Ratings by SEER Level for 3-Ton Split-System Heat 

Pumps with Impacts of Suggested HSPF Standards 

Decile 

Efficiency Level (SEER) 

13 14 15 16 17 18 19 

Selected HSPF 

7.7 8 8.3 8.6 9.1 9.6 10.1 

0% 6.7 6.7 6.7 6.7 7.1 7.4 8.05 

10% 7.7 8 7.8 8.5 8.5 8.35 8.47 

20% 7.9 8.1 8.1 8.7 9 8.9 8.62 

30% 8 8.2 8.2 8.9 9.1 9 8.73 

40% 8 8.2 8.5 9 9.1 9.25 8.94 

50% 8 8.3 8.6 9 9.2 9.25 9.05 

60% 8.1 8.5 8.6 9.1 9.25 9.5 10.05 

70% 8.2 8.5 8.8 9.1 9.5 9.64 10.25 

80% 8.3 8.6 9 9.2 9.7 10 10.35 

90% 8.5 8.85 9.2 9.5 9.9 10.23 10.43 

100% 9.45 10 10 10.65 10.75 10.6 10.55 

No. 

Models 14939 12211 4892 2024 1517 285 23 

Source: 2008 AHRI Directory of Certified Product Performance 

5.9.1.2 Single-Package Heat Pumps 

The current study of the relation between HSPF and SEER for single-package heat 

pumps, performed as part of this preliminary analysis, is based off of the fit of an equation 

directly to the AHRI Certified Directory data for this product class. However, for use in future 

analyses, DOE also investigated the applicability of the results obtained for split-system heat 

pumps to the single-package heat pump product class. The single-package heat pump product 

class contained a much lower number of product models (623) than the split-system heat pump 

product class, constituting only 0.3 percent of the total heat pump models represented in the 

AHRI Certified Directory. When the products were categorized by SEER rating, it became 

evident that the variation present within the HSPF values at each SEER level was much smaller 

than was the case with split-system heat pumps. Whereas the HSPF values for a given SEER 

could vary by as much as 3.95 HSPF within the split-system products, the largest variation 

observed for the single-package products at a specific SEER was 0.2 HSPF. This suggests that 

there is a strong correlation for these products between SEER and HSPF, and that an HSPF 

standard would likely have a similar effect on all manufacturers. Additionally, when the 

proposed HSPF equation discussed above was compared against the single-package heat pump 

data, a strong agreement was visible. From this it appears that the general, median trend in the 

HSPF/SEER relationship exhibited for split-system products is also followed by single-package 

products. As a result, for the NOPR, DOE proposes that the SEER/HSPF correlation proposed 

for split-system products be extended to apply to single-package heat pumps as well. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

5.9.2 Calculation of System Weights 

Representative system weights for units at all SEER levels were required as an input to 

downstream analyses, including the life-cycle cost calculations and other analyses performed as 

part of this investigation. The basis for this calculation of typical system weight was weight 

information obtained from manufacturer specification sheets. For each of the four conventional 

product classes (split-system air conditioners, split-system heat pumps, single-package air 

conditioners, single-package heat pumps), data were collected across a number of manufacturers 

and across the entirety of the range of applicable rated SEER levels. The breadth of data included 

served to ensure as accurate a view of the market as possible would be obtained. Separate 

calculations were performed for the indoor units and outdoor units for the split-system product 

classes, and for packaged units for the single-package product class. For all of these units, the 

data across the various manufacturers were consistent enough to allow for direct trending of unit 

weight. Therefore, system weights as listed by the manufacturers were plotted against rated 

SEER for all manufacturers and SEER levels, and a best fit curve was fit to the data. From this 

curve fit, typical unit weights were estimated for each applicable SEER level. This trending and 

calculation allowed for a single typical unit weight corresponding to a given SEER value to be 

used for the systems in each product class. Table 5.9.3 through Table 5.9.6 give the calculated 

typical weights by SEER level for each product class examined. 

Table 5.9.3: Calculated Typical Split-System Air Conditioner Unit Weights 

Split AC Typical Weights (lbs) 

SEER Outdoor Unit Weight Indoor Unit Weight 

13 178 110 

13.5 189 114 

14 199 117 

14.5 209 120 

15 220 124 

15.5 230 127 

16 240 130 

16.5 250 132 

17 261 134 

18 282 140 

19 302 144 

20 323 148 

21 344 152 

22 364 156 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 5.9.4: Calculated Typical Split-System Heat Pump Unit Weights 

Split HP Typical Weights (lbs) 

SEER Outdoor Unit Weight Indoor Unit Weight 

13 225 114 

13.5 237 117 

14 248 120 

14.5 258 124 

15 269 127 

15.5 279 130 

16 288 134 

17 307 140 

18 324 144 

19 341 148 

19.5 349 152 

Table 5.9.5: Calculated Typical Packaged Air Conditioner Unit Weights 

SEER 

Packaged AC Typical 

Weights (lbs) 

13 333 

13.5 349 

14 366 

14.5 382 

15 398 

15.5 414 

16 431 

16.6 450 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.9.6: Calculated Typical Packaged Heat Pump Unit Weights 

SEER 

Packaged HP Typical Weights 

(lbs) 

13 379 

13.5 395 

14 411 

14.5 427 

15 443 

15.5 460 

16 476 

16.4 489 

5.10 RESULTS 

The final result of the engineering analysis is a set of cost-efficiency curves. DOE 

developed curves representing the four conventional product classes using the reverseengineering and cost modeling methodology described above. The four cost-efficiency curves 

are shown in Figures 5.10.1 through 5.10.5 below and in tabular form in Tables 5.10.1 through 

5.10.5 in the form of SEER versus MPC. More detailed results, including the design options used 

at each design option level, are provided in appendix B. 

As stated above, DOE used the cost-efficiency curves from the engineering analysis as an 

input to the life-cycle cost (LCC) analysis to determine the price of central air conditioning and 

heat pump units to the customer (see chapter 8 of the TSD). 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.10.1: Cost-Efficiency Data for Split-System Air Conditioners: Blower-Coil 

Efficiency 

Level 

Outdoor 

Unit Indoor Unit System 

SEER 

Condensing 

Unit 

[$] 

Indoor 

Unit 

Casing 

[$] 

Evaporator 

Coil 

[$] 

Evaporator 

Fan Blower 

[$] 

Balance 

of 

Indoor 

Unit 

[$] 

MPC 

[$] 

13 475.32 56.69 104.89 59.27 19.09 715.26 

13.5 495.04 57.72 113.91 64.89 22.37 753.93 

14 514.76 58.75 124.59 71.02 23.47 792.59 

14.5 534.48 59.78 125.16 91.13 23.38 833.92 

15 554.38 60.81 125.86 94.88 27.90 863.84 

15.5 576.72 60.81 128.34 99.55 29.45 894.87 

16 599.95 60.81 130.87 104.44 30.99 927.06 

16.5 624.13 60.81 133.45 109.58 32.50 960.46 

17 649.27 60.81 136.08 114.96 33.99 995.11 

18 702.65 60.81 141.49 126.55 36.87 1,068.36 

19 760.41 60.81 147.11 139.30 39.58 1,147.21 

20 822.92 60.81 152.96 153.34 42.10 1,232.12 

21 890.56 60.81 159.05 168.79 44.35 1,323.56 

22 963.77 60.81 165.37 185.79 46.30 1,422.04 

Figure 5.10.1: Cost-Efficiency Data for Split-System Air Conditioners: Blower-Coil 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.10.2: Cost-Efficiency Data for Split-System Air Conditioners: Coil-Only 

Efficiency 

Level Outdoor Unit Indoor Unit System 

SEER Condensing 

Unit [$] 

Evaporator 

Coil [$] 

MPC 

[$] 

13 475.32 104.89 580.21 

13.5 495.04 119.53 614.57 

14 514.76 136.35 651.11 

14.5 555.55 136.91 692.46 

15 599.95 139.48 739.43 

15.5 649.27 147.83 797.10 

16 712.01 159.16 871.17 

16.5 782.27 174.55 956.82 

0.00 

200.00 

400.00 

600.00 

800.00 

1,000.00 

1,200.00 

1,400.00 

1,600.00 

MPC [$] 

12 13 14 15 16 17 

SEER 

Figure 5.10.2: Cost-Efficiency Data for Split-System Air Conditioners: Coil-Only 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps 

Efficiency 

Level 

Outdoor 

Unit Indoor Unit System 

SEER 

Condensing 

Unit 

[$] 

Indoor 

Unit 

Casing 

[$] 

Evaporator 

Coil 

[$] 

Evaporator 

Fan Blower 

[$] 

Balance 

of 

Indoor 

Unit 

[$] 

MPC 

[$] 

13 601.67 57.72 113.91 64.89 22.37 860.56 

13.5 626.63 58.75 124.59 71.02 23.47 904.47 

14 651.59 59.78 125.16 91.13 23.38 951.04 

14.5 676.55 60.81 125.86 94.88 27.90 986.01 

15 701.75 60.81 128.34 99.55 29.45 1,019.90 

15.5 730.02 60.81 130.87 104.44 30.99 1,057.13 

16 759.43 60.81 136.08 114.96 33.99 1,105.27 

17 821.86 60.81 141.49 126.55 36.87 1,187.57 

18 889.42 60.81 147.11 139.30 39.58 1,276.23 

19 962.54 60.81 152.96 153.34 42.10 1,371.74 

19.5 1,002.10 60.81 156.01 161.06 43.22 1,423.20 

Figure 5.10.3: Cost-Efficiency Data for Split-System Heat Pumps 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners 

Efficiency 

Level Subsystems System 

SEER Condensing 

[$] 

Evaporating 

[$] 

MPC 

[$] 

13 550.42 175.91 726.33 

13.5 575.28 216.29 791.57 

14 608.88 226.52 835.40 

14.5 661.67 238.00 899.67 

15 702.39 249.71 952.10 

15.5 751.43 267.05 1,018.49 

16 811.79 285.46 1,097.25 

16.6 904.63 304.67 1,209.31 

Figure 5.10.4: Cost-Efficiency Data for Single-Package Air Conditioners 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps 

Efficiency 

Level Subsystems System 

SEER Condensing 

[$] 

Evaporating 

[$] 

MPC 

[$] 

13 682.31 216.29 898.60 

13.5 713.79 226.52 940.30 

14 756.32 238.00 994.32 

14.5 823.14 249.71 1,072.85 

15 874.68 267.05 1,141.73 

15.5 936.76 285.46 1,222.21 

16 1,013.16 304.67 1,317.83 

16.4 1,091.51 322.46 1,413.96 

Figure 5.10.5: Cost-Efficiency Data for Single-Package Heat Pumps 

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EERE-2008-BT-STD-0006 COMMENT 54
5.11 REFERENCES 

1

 American Metals Market, http://www.amm.com/. 

2

 U.S. Department of Labor, Bureau of Labor Statistics, Producer Price Indices, 

http://www.bls.gov/ppi/. 

3

 U.S. Department of Commerce, Bureau Economic Analysis, Gross Domestic Product Implicit 

Price Deflator, https://bea.gov/bea/dn/nipaweb/TableView.asp#Mid. 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 6. MARKUPS TO DETERMINE EQUIPMENT PRICE 

TABLE OF CONTENTS
 

6.1	 INTRODUCTION .............................................................................................................. 6-1
 

6.2	 MARKUP CALCULATION PROCEDURE ..................................................................... 6-2
 

6.2.1	 Baseline Markups................................................................................................. 6-3
 

6.2.2	 Incremental Markups ........................................................................................... 6-4
 

6.2.3	 Overall Markups .................................................................................................. 6-4
 

6.3	 ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND CONTRACTOR
 

MARKUPS ......................................................................................................................... 6-5 
 

6.4	 ESTIMATION OF WHOLESALER MARKUPS ............................................................. 6-6
 

6.4.1	 Estimation of Wholesaler Markup Probability Distribution................................ 6-8
 

6.5	 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS.................................. 6-8
 

6.5.1	 Markups for Mechanical Contractors in the Replacement and New 

Construction Markets........................................................................................... 6-9
 

6.5.2	 Estimation of Mechanical Contractor Markup Probability Distribution ........... 6-11
 

6.6	 ESTIMATION OF GENERAL CONTRACTOR MARKUPS........................................ 6-12
 

6.6.1	 Estimation of General Contractor Markup Probability Distribution ................. 6-13
 

6.7	 SALES TAX ..................................................................................................................... 6-14
 

6.8 OVERALL MARKUPS.................................................................................................... 6-15
 

REFERENCES .......................................................................................................................... 6-17
 

LIST OF TABLES 

Table 6.4.1 Wholesaler Expenses and Markups ..................................................................... 6-7
 

Table 6.5.1 Baseline Markup, All Mechanical Contractors.................................................... 6-9
 

Table 6.5.2 Baseline Markups for the Replacement and New Construction Markets, 

All Mechanical Contractors ............................................................................... 6-10
 

Table 6.5.3 Mechanical Contractor Expenses and Baseline Markup, Residential and 

Light Commercial .............................................................................................. 6-10
 

Table 6.5.4 Mechanical Contractor Expenses and Markups Based on Census Bureau 

Data .................................................................................................................... 6-11
 

Table 6.6.1 General Contractor Expenses and Markups....................................................... 6-13
 

Table 6.7.1 State Sales Tax Rates (Percent) ......................................................................... 6-15
 

Table 6.8.1 Average Overall Baseline Markups................................................................... 6-15
 

Table 6.9.2 Average Overall Incremental Markups.............................................................. 6-15
 

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LIST OF FIGURES
 

Figure 6.1.1 Distribution Channels for CAC Equipment......................................................... 6-1 

Figure 6.4.1 Wholesaler Baseline Markup Probability Distribution........................................ 6-8 

Figure 6.4.2 Wholesaler Incremental Markup Probability Distribution .................................. 6-8 

Figure 6.5.1 Residential and Light Commercial Mechanical Contractor Relative 

Markup Probability Distribution........................................................................ 6-12 

Figure 6.6.1 Residential General Contractor Relative Markup Probability Distribution....... 6-14 

Figure 6.6.2 Commercial General Contractor Relative Markup Probability Distribution..... 6-14 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 6. MARKUPS TO DETERMINE EQUIPMENT PRICE 

6.1 INTRODUCTION 

To carry out the life-cycle cost (LCC) calculations described in Chapter 8, the U.S. 

Department of Energy (DOE) needed to determine the cost to the customer of a residential 

central air conditioner or heat pump (CAC) product. This cost was determined for both baseline 

equipment and more-efficient equipment the customer would purchase following the 

promulgation of new energy conservation standards. However, the customer price of baseline or 

higher-efficiency equipment is not known and can be determined based on how the equipment is 

purchased. For the central air conditioner and heat pump rulemaking, direct information on the 

incremental markup on equipment costs for higher efficiency units is not readily available. This 

is partially due to the fact that such units are often included in the construction costs of new 

housing or as a package that includes installation. In addition, because higher efficiency units 

may have different markups than baseline units at minimum efficiency and higher efficiency 

units are not produced at the same volume as baseline units, current incremental equipment costs 

observed in the market may not be representative of the incremental costs under a new standard. 

The manufacturing selling price (MSP) can be determined for both baseline equipment and the 

more-efficient equipment as described in the engineering analysis (Chapter 5). Therefore, by 

applying a multiplier called a “markup” to the MSP, DOE was able to estimate the customer 

price of equipment purchased through various distribution channels. This chapter describes how 

DOE derived such markups. 

The cost to the customer depends on how the customer purchases the equipment. DOE 

identified two distribution channels, as shown in Figure 6.1.1, to describe how the equipment 

passes from the manufacturer to the customer for both new construction and replacement 

markets. In the replacement distribution channel, the manufacturer sells the CAC product to a 

distributor/wholesaler, who in turn sells it to a mechanical contractor, who in turn sells it directly 

to the customer. In new construction distribution channel, the manufacturer sells the equipment 

to a wholesaler, who in turn sells it to a mechanical contractor, who in turn sells it to the 

customer through a general contractor who sells it and its installation to the customer. The 

distribution chain markup consists of a distributor/wholesaler markup applied by distributors and 

wholesalers, a dealer/contractor markup applied by dealers and HVAC contractors and a markup 

for sales tax. For the new housing market, a markup is also applied by housing developers and 

builders. The markups applied in the Pre-NOPR analysis for distributor and dealer markups were 

determined from aggregate average markups for the businesses in the distribution chain. This 

means at each stage of distribution, direct costs of sales, i.e., purchased equipment and materials 

and direct labor costs, were compared with the total volume of business revenues, and the ratio 

of total business revenues to direct costs was used to determine the markup. 

New Units: Manufacturer→Distributor→Mechanical Contractor→General
 

Contractor→Customer 

Replacement Units: Manufacturer→Distributor→Mechanical Contractor→Customer 

Figure 6.1.1 Distribution Channels for CAC Equipment 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

The analysis detailed here for the Pre-NOPR examined the scaling behavior of markups 

for wholesalers and contractors, and determined that markups are neither fixed-dollar, nor 

proportional to all direct costs, but somewhere in-between. Using the available data, we have 

found measurable differences between incremental markups on direct equipment costs and the 

average aggregate markup on direct business costs. Significant differences were found between 

average and incremental markups for heating, ventilation, air-conditioning and refrigeration 

(HVACR) wholesalers/distributors, and for HVAC dealers/contractors. Section 6.3 further 

discusses the differences between average and incremental markups. 

The main reason that the selling price of a product may not be strictly proportional to the 

purchase price of the equipment is that businesses incur a wide variety of costs. Therefore, when 

the purchase price of equipment and materials increases, only a fraction of the business expenses 

increase, while the remainder of the businesses’ expenses stay relatively constant. For example, 

if the unit price of an air conditioner increases by 30%, it is unlikely that the cost of secretarial 

support in an administrative office will increase by 30% also. Certain business expenses are 

relatively uncorrelated with the cost of equipment or cost of goods. 

For each of the steps in the distribution channels presented above, DOE estimated a 

baseline markup and an incremental markup. DOE defined a baseline markup as a multiplier that 

converts the MSP of equipment with baseline efficiency to the customer purchase price for the 

equipment at the same baseline efficiency level. An incremental markup is defined as the 

multiplier to convert the incremental increase in MSP of higher efficiency equipment to the 

customer purchase price for the same equipment. Both baseline and incremental markups are 

only dependent on the particular distribution channel and are independent of the efficiency levels 

of CAC products. 

6.2 MARKUP CALCULATION PROCEDURE 

The following equation describes how DOE determined the equipment price if a 

mechanical contractor sells the equipment to the customer through a general contractor 

distribution chain: 

EQPCUST = MSP x MUWHOLE x MUMECH CONT x MUGEN CONT x (1+ ST) Eq. 6.1 

Where: 

EQPCUST = equipment price to the customer ($), 

MSP= manufacturer selling price ($), 

MUWHOLE = wholesaler markup, 

MUMECH CONT = residential and light commercial mechanical contractor markup, 

MUGEN CONT = general contractor markup, 

ST = sales tax ($). 

The markup multiplier to the equipment price is lessened for shorter distribution chains 

by omitting the applicable markup(s). 

The general contractor markup is only applied to new construction because the general 

contractor not generally involved in the replacement market. The later sections of this chapter 

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describe the determination of the residential and light commercial mechanical contractor 

markups and market type (i.e., new or replacement). For each of the markups presented above, 

DOE further differentiated between a baseline markup and an incremental markup, as described 

below. The overall markup describes the product of all the markups (baseline and incremental) 

plus sales tax within a distribution channel. 

6.2.1 Baseline Markups 

DOE defined baseline markups as cost multipliers that convert the MSP of equipment 

with baseline efficiency to the customer purchase price for the equipment at the same baseline 

efficiency level. 

New equipment is assumed to be sold to a customer by a mechanical contractor through a 

general contractor: 

EQPGEN CONT BASE = MSP BASE x MUWHOLE BASE x MUMECH CONT BASE x MUGEN CONT BASE x 

(1+ST) Eq. 6.2 

Where:
 

EQPGEN CONT BASE = general contractor price of baseline equipment ($), 

MSPBASE = manufacturer selling price of baseline equipment ($),
 

MUWHOLE BASE= wholesaler markup on baseline equipment, 

MUMECH CONT BASE = mechanical contractor markup on baseline equipment, 

MUGEN CONT BASE = general contractor markup on baseline equipment, 

ST= sales tax rate. 

Replacement equipment is assumed to be sold to a customer directly by a mechanical 

contractor: 

EQPMECH CONT BASE = MSP BASE x MUWHOLE BASE x MUMECH CONT BASE x (1+ST) Eq. 6.3 

Where:
 

EQPMECH CONT BASE = mechanical contractor price of baseline equipment ($),
 

MSPBASE = manufacturer selling price of baseline equipment ($),
 

MUWHOLE BASE= incremental wholesaler markup, 

MUMECH CONT BASE = mechanical contractor markup on baseline equipment, 

MUGEN CONT BASE = general contractor markup on baseline equipment,
 

ST = sales tax rate. 

The use of the markups results in the mechanical contractor (EQPMECH CONT BASE), and 

general contractor (EQPGEN CONT BASE) prices of baseline CAC equipment. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

6.2.2 Incremental Markups 

Incremental markups are defined as the cost multipliers to convert the incremental 

increase in MSP of higher efficiency equipment to the customer purchase price for the same 

equipment, as shown in the following equations: 

If sold to a customer by a mechanical contractor through a general contractor: 

EQPGEN CONT INCR = MSP INCR x MUWHOLE INCR x MUMECH CONT INCR x MUGEN CONT INCR x 

(1+ST) Eq. 6.4 

Where: 

EQPGEN CONT INCR = incremental general contractor price ($), 

MSPINCR = manufacturer incremental selling price ($), 

MUWHOLE INCR= incremental wholesaler markup, 

MUMECH CONT INCR = incremental mechanical contractor markup, 

MUGEN CONT INCR = incremental general contractor markup, 

ST= sales tax rate. 

If sold to a customer directly by a mechanical contractor: 

EQPMECH CONT INCR = MSP INCR x MUWHOLE INCR x MUMECH CONT INCR x (1+ST) Eq. 6.5 

Where: 

EQPWHOLE INCR = incremental wholesaler price ($). 

In these equations, MSPINCR refers to a change in the MSP (e.g., brought about by an 

increase in equipment efficiency due to amended energy conservation standards) and MUWHOLE 

INCR, MUMECH CONT INCR, and MUGEN CONT INCR refer to the incremental wholesaler, incremental 

mechanical contractor, and incremental general contractor markups, respectively. The use of the 

incremental markups results in incremental equipment price to the incremental mechanical 

contractor (EQPMECH CONT INCR), and incremental general contractor (EQPGEN CONT INCR) prices 

experienced by the customer. 

6.2.3 Overall Markups 

The overall markup is the product of all the markups, including both overall baseline and 

overall incremental markups, for the different steps within a distribution channel plus sales tax, 

as indicated by the following equations: 

EQPCUST BASE = MSPBASE x (WTMECH CONT BASE x MUWHOLE BASE x MUMECH CONT BASE + WTGEN 

CONT BASE x MUWHOLE BASE x MUMECH CONT BASE x MUGEN CONT BASE) x (1+ST) = MSPBASE x 

MUOVERALL BASE Eq. 6.6 

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EQPCUST INCR = MSPINCR x (WTMECH CONT INCR x MUWHOLE INCR x MUMECH CONT INCR + WTGEN 

CONT INCR x MUWHOLE INCR x MUMECH CONT INCR x MUGEN CONT INCR) x (1+ST) = MSPINCR x 

MUOVERALL INCR	 Eq. 6.7 

EQPCUST = EQPCUST BASE + EQPCUST INCR	 Eq. 6.8 

Where:
 

EQPCUST BASE = baseline customer price ($), 

EQPCUST INCR= incremental customer price ($), 

EQPCUST = total customer price ($),
 

MUOVERALL BASE = overall weighted baseline markup that is the product of all the 

weights and baseline markups for each step of the distribution 

channel, 

MUOVERALL INCR =	 overall weighted incremental markup that is the product of all the 

weights and incremental markups for each step of the distribution 

channel, 

WTMECH CONT BASE = weight (percent) of baseline equipment sales through mechanical 

contractors, 

WTGEN CONT BASE = weight (percent) of baseline equipment sales through general 

contractors, 

WTMECH CONT INCR = weight (percent) of higher efficiency equipment sales through 

mechanical contractors, 

WTGEN CONT INCR = weight (percent) of higher efficiency equipment sales through 

general contractors. 

The use of the overall baseline and overall incremental markups results in the baseline 

customer price (EQPCUST BASE) and the incremental customer price (EQPCUST INCR). For a particular 

higher efficiency level that increases MSP, the total equipment price (EQPCUST ) to the customer 

is the sum of the baseline customer price (EQPCUST BASE) and the incremental customer price 

(EQPCUST INCR). 

6.3	 ASSUMPTIONS USED TO ESTIMATE WHOLESALER AND CONTRACTOR 

MARKUPS 

DOE derived the wholesaler and contractor markups from three key assumptions about 

CAC costs. DOE based the wholesaler and mechanical contractor markups on firm balance-sheet 

data, while it based the general contractor markups on U.S. Census Bureau data for the 

commercial and institutional building construction industry. DOE obtained the firm balance 

sheets from the Heating, Air-conditioning & Refrigeration Distributors International (HARDI) 

2008 Profit Planning Report and from the Air Conditioning Contractors of America (ACCA). 1,2 

HARDI and ACCA are trade associations representing wholesalers and mechanical contractors, 

respectively. DOE used the financial data from the 2002 US Census Bureau for developing 

general contractor markups in the same form as the balance sheet data for wholesalers and 

mechanical contractors.3 These balance sheets break out the components of all costs incurred by 

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EERE-2008-BT-STD-0006 COMMENT 54
 

firms that supply and install air conditioning equipment.a The key assumptions used to estimate 

markups using these financial data are: 

•	 The firm balance sheets accurately represent the various average costs incurred by firms 

distributing and installing commercial air conditioning and heating equipment. 

•	 These costs can be divided into two categories: (1) costs that vary in proportion to the 

MSP of commercial air conditioning and heating equipment (variable costs); and 

(2) costs do not vary with the MSP of commercial air conditioning and heating equipment 

(fixed costs). 

•	 Wholesaler and contractor prices vary in proportion to CAC and HP wholesaler and 

contractor costs included in the balance sheets. 

In support of the first assumption, the balance sheets itemize firm costs into a number of 

expense 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 provide the most accurate available indication of CAC and HP expenses. 

Information obtained from the trade literature and selected heating, ventilating, and air 

conditioning (HVAC) wholesalers, contractors, and consultants support the second assumption. 

This information indicated that wholesaler and contractor markups vary according to the quantity 

of labor and materials used to distribute and install appliances, with markups on labor tending to 

be much higher than markups on materials. The obtained information described markups as 

varying much more in relation to sales volume than in relation to other factors, including 

appliance efficiency. This last finding strongly suggested that labor inputs vary more with sales 

volume than with appliance cost or efficiency. DOE assumed a division of costs between those 

costs that do not scale with the MSP (labor and occupancy expenses), and those costs that do 

(operating expenses and profit). This division of costs led to the estimate of wholesaler and 

contractor markups described below. 

In support of the third assumption, the HVAC wholesaler and contractor industry is 

competitive and customer demand for commercial heating and air conditioning is inelastic, i.e., 

the demand is not expected to decrease significantly with an increase in price of equipment. The 

large number of HVAC firms listed in the 2002 Census indicates the competitive nature of the 

market. For example, there are more than 700 HVAC manufacturers,4

 6,000 wholesalers of heat 

pumps and air-conditioning equipment,5 more than 37,000 general contractors,6 and 87,000 

HVAC contractors7

 listed in the 2002 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 

Wholesalers reported median data in a confidential survey that HARDI conducted of 

member firms.2 In the survey, HARDI itemized revenues and costs into cost categories, 

including direct equipment expenses (cost of goods sold), labor expenses, occupancy expenses, 

a

 Wholesalers and mechanical contractors to which these reports refer handle multiple commodity lines, including 

residential and commercial air-conditioners and warm-air furnaces. 

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other operating expenses, and profit. DOE presents these data in full in appendix C, Detailed 

Data for Equipment Price Markups. Table 6.4.1 summarizes them as cost-per-dollar sales 

revenue in the first data column. 

Table 6.4.1 Wholesaler Expenses and Markups 

Descriptions 

Per Dollar 

Sales Revenue 

$ 

Per Dollar Cost 

of Goods 

$ 

Direct Cost of Equipment Sales: Cost of goods sold 0.730 1.000 

Labor Expenses: Salaries and benefits 0.156 0.214 

Occupancy Expense: Rent, maintenance, and utilities 0.031 0.042 

Other Operating Expenses: Depreciation, advertising, and insurance. 0.052 0.071 

Profit 0.031 0.042 

Baseline Revenue: Baseline revenue earned per dollar cost of goods sold 1.370 

Wholesaler Baseline Markup (MUWHOLE BASE) 1.370 

Incremental Revenue: Increased revenue per dollar increase cost of goods sold 1.114 

Incremental Markup (MUWHOLE INCR) 1.114 

Source: Heating, Air Conditioning & Refrigeration Distributors International. 2008. 2008 Profit Report (2007 Data).2 

In this case, direct equipment expenses (cost of goods sold) represent about $0.73 per 

dollar sales revenue, so for every $1 wholesalers take in as sales revenue, $0.73 is used to pay 

the direct equipment costs. Labor expenses represent $0.16 per dollar sales revenue, occupancy 

expenses represent $0.03, other operating expenses represent $0.05, and profit accounts for $0.03 

per dollar sales revenue. 

DOE converted the expenses per dollar sales into revenue per dollar cost of goods sold, 

by dividing each figure in the first data column by $0.73 (i.e., cost of goods sold per dollar of 

sales revenue). The data in column two 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, $0.214 

to cover labor costs, $0.042 to cover occupancy expenses, $0.071 for other operating expenses, 

and $0.042 in profits. This totals to $1.370 in sales revenue earned for every $1.00 spent on 

equipment costs. Therefore, the wholesaler baseline markup (MUWHOLE BASE) is 1.37 

($1.37 ÷ $1.00). 

DOE also used the data in column two 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 MSP, if all of the other costs scale with the MSP 

(i.e., all costs are variable), the increase in wholesaler price will be $1.370, implying that the 

incremental markup is 1.370, or the same as the baseline markup. At the other extreme, if none 

of the other costs is variable, then a $1.00 increase in the MSP will lead to a $1.00 increase in the 

wholesaler price, for an incremental markup of 1.0. Actually, DOE believes that the labor and 

occupancy costs will be fixed and that the other operating costs and profit will scale with the 

MSP (i.e., be variable). In this case, for a $1.00 increase in the MSP, the wholesaler price will 

increase by $1.114, giving a wholesaler incremental markup (MUWHOLE INCR) of 1.114. 

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EERE-2008-BT-STD-0006 COMMENT 54
6.4.1 Estimation of Wholesaler Markup Probability Distribution 

DOE characterized the markups developed from the above financial data with probability 

distributions from statistics published by the U.S. Census Bureau for wholesalers (see 

appendix C). The analysis provided a standard deviation on the markups of wholesaler firms in 

the U.S. DOE then applied the standard deviation to the single-point baseline and incremental 

markups calculated above to create normal probability distributions for these markups. 

Based on the analysis of U.S. Census data for wholesalers, DOE calculated a relative 

standard deviation as 7.7 percent as a percentage of the baseline markup of 1.362, which resulted 

in a standard deviation of 5.7 percent as described in appendix C. DOE assumed that the 

variation determined for the baseline markup applied to the incremental markup as well. For the 

baseline markup of 1.370, a standard deviation of 7.7 percent translates into an absolute value of 

5.6 percent. For the incremental markup of 1.114, a relative standard deviation of 7.7 percent 

translates into an absolute value of 6.9 percent. 

Figure 6.4.1 and Figure 6.4.2 show the probability distributions that DOE used to 

characterize the wholesaler baseline and incremental markups. 

Figure 6.4.2 Wholesaler Incremental 

Markup Probability Distribution 

Figure 6.4.1 Wholesaler Baseline 

Markup Probability Distribution 

Note that for the incremental markup, the standard deviation of 6.9 percent results in 

markup values that are less than 1.0. Since a markup value of less than 1.0 would not allow the 

wholesaler to recover its costs, DOE truncated all values less than 1.0 from the normal 

distribution as shown in Figure 6.4.2. 

6.5 ESTIMATION OF MECHANICAL CONTRACTOR MARKUPS 

The HVAC contractors, defined here as mechanical contractors, reported median cost 

data in an ACCA financial analysis of the HVAC industry.3

 These data are shown in Table 6.5.1. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 6.5.1 Baseline Markup, All Mechanical Contractors 

Description 

Contractor Expenses or Revenue 

Per Dollar 

Sales Revenue 

$ 

Per Dollar 

Cost of Goods 

$ 

Direct Cost of Equipment Sales: Cost of goods sold 0.73 1.00 

Gross Margin: Labor, occupancy, operating expenses, and profit 0.27 0.37 

Revenue: Baseline revenue earned per dollar cost of goods 1.37 

Baseline Markup (MUMECH CONT BASE) 1.37 

Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry.2 

Data reported in this analysis are not as detailed as that provided by the other sources, 

containing only cost of goods sold and gross margin. Since the gross margin is the sum of labor, 

occupancy expenses, operating expenses, and profit, the gross margin allows for the 

determination of the baseline markup. The first data column in Table 6.5.1 provides the cost of 

goods sold and gross margin as expenses per dollar sales revenue. The only important difference 

is that the direct cost of equipment sales in this table includes installation costs as well as the cost 

of goods sold. As shown in the table, the direct cost of sales represents about $0.73 per dollar 

sales revenue to the contractor and the gross margin is $0.27 per dollar sales revenue. The 

mechanical contractor expenditures per dollar sales revenue in Table 6.5.1 are quite similar to the 

wholesaler expenditures per dollar sales revenue reported in Table 6.4.1. 

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 $0.73. 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, and $0.37 to cover the other costs. This totals $1.37 in sales revenue 

earned for every $1.00 spent on equipment costs, for a baseline markup (MUMECH CONT BASE) of 1.37 

for mechanical contractors, since the contractor earns $1.37 in sales revenue for every $1.00 

spent to purchase the equipment. 

6.5.1	 Markups for Mechanical Contractors in the Replacement and New Construction 

Markets 

The baseline markup derived above for mechanical contractors is the average value for 

all contractors including the replacement and new construction markets. This section describes 

how DOE further derived the baseline and incremental markups for these latter two markets. As 

above, the ACCA financial data provided gross margin data, which allows for the determination 

of only the baseline markup for the two markets, since the gross margin is the sum of all 

contractor labor and operating expenses plus profit. Calculation of the incremental markup uses 

Census Bureau data, because this was not possible with the ACCA data as the variable costs are 

not provided separately. 

Table 6.5.2 summarizes the gross margin and resulting baseline markup data for all 

mechanical contractors that serve the replacement and new construction markets. 

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Table 6.5.2 Baseline Markups for the Replacement and New Construction Markets, All 

Mechanical Contractors 

Description 

Contractor Expenses or Revenue by Market Type 

Replacement New Construction 

Per Dollar 

Sales Revenue 

$ 

Per Dollar 

Cost of Goods 

$ 

Per Dollar 

Sales Revenue 

$ 

Per Dollar 

Cost of Goods 

$ 

Direct Cost of Equipment Sales: Cost 

of goods sold 

0.70 1.00 0.75 1.00 

Gross Margin: Labor, occupancy, 

operating expenses, and profit 

0.30 0.43 0.25 0.33 

Baseline Markup (MUMECH CONT BASE): 

Revenue per dollar cost of goods 

NA 1.43 NA 1.33 

Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry.3 

Using the baseline markup data from Table 6.5.2 and results of a financial analysis3, DOE 

calculated that the baseline markups for the replacement and new markets are 4.4 percent higher 

and 2.9 percent lower, respectively, than that for all mechanical contractors serving all markets. 

DOE then used the ACCA data to calculate the baseline markup of 1.32 for the 

residential and light commercial building construction section as shown in Table 6.5.3. 

Table 6.5.3 Mechanical Contractor Expenses and Baseline Markup, Residential and 

Light Commercial 

Description 

Contractor Expenses or Revenue 

Per Dollar 

Sales Revenue 

$ 

Per Dollar Cost of 

Goods 

$ 

Direct Cost of Equipment Sales: Cost of goods sold 0.76 1.00 

Gross Margin: Labor, occupancy, operating expenses, and profit 0.24 0.32 

Baseline Markup (MUMECH CONT BASE): Revenue per dollar cost of goods 1.32 

Source: Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR Contracting Industry.3 

The markup deviations derived above (i.e., 4.4 percent higher and 2.9 percent of lower 

for the replacement and new construction markets, respectively) were then applied to the 

baseline markup of 1.32 for the residential and light commercial building construction section. 

This resulted in baseline markups of 1.38 and 1.28, respectively, for the replacement and new 

construction markets served by mechanical contractors for the residential and light commercial 

building construction. 

Calculation of the incremental markups for each market type required separation of the 

fixed and variable costs. Since this was not possible using the ACCA data, DOE used more 

detailed 2002 Census Bureau data for all plumbing, heating, and air-conditioning contractors.7 

The Census Bureau data were used to calculate the baseline and incremental markups as shown 

in Table 6.5.4. 

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Table 6.5.4 Mechanical Contractor Expenses and Markups Based on Census Bureau Data 

Description 

Contractor Expenses or Revenue 

Per Dollar 

Sales Revenue 

$ 

Per Dollar 

Cost of Goods 

$ 

Direct Cost of Equipment Sales: Cost of goods sold 0.66 1.00 

Labor Expenses: Salaries (indirect) and benefits 0.17 0.26 

Occupancy Expense: Rent, maintenance, and utilities 0.02 0.03 

Other Operating Expenses: Depreciation, advertising, and insurance. 0.03 0.05 

Net Profit Before Taxes 0.12 0.18 

Baseline Markup (MUMECH BASE): Revenue per dollar cost of goods 1.52 

Incremental Markup (MUMECH INCR): Increased revenue per dollar increase cost of goods sold 1.23 

Source: U.S. Census Bureau. 2002. Plumbing, Heating, and Air-Conditioning Contractors: 2002. Report EC02-231-238220, 

Table 4, Detailed Statistics for Establishments: 2002.7 

Using the data Table 6.5.4, the incremental markup is 19.1 percent lower than the 

baseline markup. DOE assumed that this deviation applies equally to the baseline markups 

calculated for replacement of 1.38 and new construction markets of 1.28. This yields incremental 

markups of 1.12 and 1.04, respectively, for the replacement and new construction markets served 

by mechanical contractors. 

6.5.2 Estimation of Mechanical Contractor Markup Probability Distribution 

DOE characterized the markups developed from the ACCA financial data with 

probability distributions through a statistical analysis of U.S. Census data for plumbing, heating, 

and air-conditioning contractors. The statistical analysis provided a standard deviation on the 

markups of mechanical contractors in the U.S. DOE then applied the standard deviation to the 

single-point baseline and incremental markups calculated above to create normal probability 

distributions for these markups. 

Based on the analysis of U.S. Census data for mechanical contractors, DOE calculated a 

relative standard deviation of 3.7 percent for the baseline markup as described in appendix A. 

DOE assumed that the variation determined for the baseline markup applied to the incremental 

markup as well. For the baseline markup of 1.38 and 1.28 for the replacement and new 

construction markets, respectively, a relative standard deviation of 3.7 percent translates into 

respective absolute values of 0.051 and 0..047. For the incremental markups of 1.12 and 1.04 for 

the replacement and new construction markets, respectively, a standard deviation of 3.7 percent 

translates into respective absolute values of 0.041 and 0.038. 

DOE calculated a relative standard deviation of 3.7 percent for mechanical contractor 

markups but applied the relative markups on a state-by-state basis. Figure 6.5.1 illustrates the 

probability distribution that DOE used to characterize the mechanical contractor baseline and 

incremental markups for the replacement and new markets. The relative values are multiplied 

times the mean markups for all four categories of mechanical contractor markup: both baseline 

and incremental markups for both new construction and replacements. The probability of 

purchasing a CAC or heat pump unit is different in the different U.S. states, and the relative 

markup is different in each state. While the actual probability of a sale in a particular state 

depends on a number of climate, product-specific, regulatory, and population factors, 

Figure 6.5.1 shows what the distribution of relative markups looks like if population were the 

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EERE-2008-BT-STD-0006 COMMENT 54
only determinant. The far right-hand bar shows, for example, that based on population, there is a 

12.1 percent chance that a given CAC sale would be in California (which had an estimated 

12.1 percent of the U.S. population in July, 2008). The relative mechanical contractor markup 

value for California is 1.037, which would be multiplied times the mean markup factor of 1.28 

for a new baseline unit, yielding a mechanical contractor markup of 1.327. If instead the 

incremental markup on a replacement unit were needed, the 1.037 relative markup value would 

be multiplied times the mean incremental markup factor for replacement units of 1.12, yielding a 

mechanical contractor markup value of 1.161. 

Figure 6.5.1 Residential and Light Commercial Mechanical Contractor Relative Markup 

Probability Distribution 

6.6 ESTIMATION OF GENERAL CONTRACTOR MARKUPS 

DOE derived markups for general contractors from U.S. Census Bureau data for the 

commercial and institutional building construction sector.4

 This sector includes establishments 

primarily engaged in construction work, including new construction work, additions, alterations, 

and repairs. The U.S. Census Bureau data for the construction sector include detailed statistics 

for establishments with payrolls, similar to the data reported by ACCA for wholesalers. The 

primary difference is that the U.S. Census Bureau reports itemized revenues and expenses for the 

construction industry as a whole in 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. Similar to the data for wholesalers, 

Table 6.6.1 summarizes the expenses for general contractors as expenses per dollar sales revenue 

in the first data column (appendix A contains the full set of data). 

6-12 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 6.6.1 General Contractor Expenses and Markups 

Description 

Wholesale Firm Expenses or Revenue 

Per Dollar 

Sales Revenue 

$ 

Per Dollar 

Cost of Goods 

$ 

Direct Cost of Equipment Sales: Cost of goods sold 0.78 1.00 

Labor Expenses: Salaries (indirect) and benefits 0.08 0.10 

Occupancy Expense: Rent, maintenance, and utilities 0.02 0.03 

Other Operating Expenses: Depreciation, advertising, and insurance. 0.01 0.01 

Net Profit Before Taxes 0.12 0.15 

Baseline Markup (MUGEN CONT BASE): Revenue per dollar cost of goods 1.29 

Incremental Markup (MUGEN CONT INCR): Increased revenue per dollar increase cost of goods sold 1.17 

Source: U.S. Census Bureau. 2002. Commercial and Institutional Building Construction: 2002. Report EC02-231-236220, Table 

4, Detailed Statistics for Establishments: 2002.7 

For example, the direct cost of sales represents about $0.78 per dollar sales revenue to the 

general contractor. Labor expenses represent $0.08 per dollar sales revenue, occupancy expenses 

represent $0.02 per dollar sales revenue, other operating expenses represent $0.01, and profit 

makes up $0.12 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 $0.78. The data in column two show that, for 

every $1.00 the general contractor spends on equipment costs, the general contractor earns $1.00 

in sales revenue to cover the equipment cost, $0.10 to cover labor costs, $0.03 to cover 

occupancy expenses, $0.01 for other operating expenses, and $0.15 in profits. This totals to 

$1.29 in sales revenue earned for every $1.00 spent on equipment costs. Thus, the general 

contractor baseline markup (MUGEN CONT BASE) is 1.29. 

DOE was also able to use the data in column two in the table above to estimate the 

incremental markups by being able to separate the fixed and variable costs. At one extreme, if all 

of the other costs scale with the equipment price (i.e., all costs are variable), the increase in 

general contractor price will be $1.29, implying that the incremental markup is 1.29, or the same 

as the baseline markup. At the other extreme, if none of the other costs are variable, then a $1.00 

increase in the equipment price will lead to a $1.00 increase in the general contractor price, for 

an incremental markup of 1.0. DOE believed 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 general contractor price will increase by $1.17, 

giving a general contractor incremental markup (MUGEN CONT INCR) of 1.17. 

6.6.1 Estimation of General Contractor Markup Probability Distribution 

DOE characterized the markups developed above with probability distributions derived 

from a statistical analysis of U.S. Census data for general contractors engaged in commercial and 

institutional building construction. The statistical analysis provided a standard deviation on the 

markups of general contractors in the United States. DOE then applied the standard deviation to 

the single-point baseline and incremental markups calculated above to create normal probability 

distributions for these markups. 

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EERE-2008-BT-STD-0006 COMMENT 54
Based on the analysis of U.S. Census data for general contractors, DOE calculated a 

standard deviation of 9.0 percent for the baseline markup as described in appendix A. DOE 

assumed that the variation determined for the baseline markup applied to the incremental markup 

as well. For the baseline markup of 1.29, a standard deviation of 9.0 percent translates to an 

absolute value of 0.116. For the incremental markup of 1.17, a standard deviation of 9.0 percent 

translates to an absolute value of 0.105. 

Figure 6.6.1 and Figure 6.6.2 show the relative probability distributions that DOE used to 

characterize the residential general contractor and commercial general contractor markups. Both 

are for new construction, because general contractors are not part of the distribution channel for 

replacement CACs. The same relative markups apply to both baseline and incremental markups, 

but they are multiplied times different mean values (1.29 for baseline, 1.17 for incremental). The 

state incremental values are applied in the same way as the mechanical contractor values 

discussed in section 6.5.2. 

Figure 6.6.1 Residential General 

Contractor Relative Markup Probability 

Distribution 

Figure 6.6.2 Commercial General 

Contractor Relative Markup Probability 

Distribution 

6.7 SALES TAX 

The sales tax represents State and local sales taxes that are applied to the customer price 

of the packaged terminal equipment. The sales tax is a multiplicative factor that increases the 

customer equipment price. DOE derived sales taxes representative of both State and local sales 

taxes from The Sales Tax Clearinghouse,9

 shown in Table 6.7.1. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

Table 6.7.1 State Sales Tax Rates (Percent) 

State 

Combined 

State and Local 

Tax Rate State 

Combined 

State and 

Local Tax Rate State 

Combined 

State and 

Local Tax Rate 

Alabama 8.15 Kentucky 6 North Dakota 5.75 

Alaska 1.45 Louisiana 8.75 Ohio 6.85 

Arizona 7.15 Maine 5 Oklahoma 8.1 

Arkansas 8.2 Maryland 6 Oregon -­

California 9.0 Massachusetts 5 Pennsylvania 6.25 

Colorado 6.4 Michigan 6 Rhode Island 7 

Connecticut 6 Minnesota 6.85 South Carolina 7.05 

Delaware -­ Mississippi 7 South Dakota 5.5 

Dist. of Columbia 5.75 Missouri 7.10 Tennessee 9.4 

Florida 6.7 Montana -­ Texas 8.05 

Georgia 6.95 Nebraska 6 Utah 6.7 

Hawaii 4.4 Nevada 7.5 Vermont 6.05 

Idaho 6.05 New Hampshire -­ Virginia 5 

Illinois 8.4 New Jersey 6.95 Washington 8.75 

Indiana 7 New Mexico 6.4 West Virginia 6 

Iowa 6.8 New York 8.25 Wisconsin 5.4 

Kansas 6.9 North Carolina 6.8 Wyoming 5.40 

The State level combined tax rates can be applied to the estimated value of State level 

CAC 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 9.4 percent with a population-weighted mean value of 6.99 percent, or approximately 

7.0 percent. DOE applied sales taxes to the customer equipment price irrespective of the 

distribution channel and the market in which the customer is located. 

6.8 OVERALL MARKUPS 

DOE multiplied the wholesaler, mechanical and general contractor, and national account 

markups described above by the sales tax to obtain the overall baseline and incremental markups 

shown in Table 6.8.1 and Table 6.8.2, respectively. 

Table 6.8.1 Average Overall Baseline Markups 

Replacement 

Market 

New Construction 

Market 

Wholesaler 1.370 1.370 

Mechanical Contractor 1.380 1.280 

General Contractor - 1.290 

Sales Tax 1.071 1.071 

Overall 2.025 2.422 

Table 6.8.2 Average Overall Incremental Markups 

Replacement 

Market 

New Construction 

Market 

Wholesaler 1.114 1.114 

Mechanical Contractor 1.120 1.040 

General Contractor - 1.170 

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Sales Tax 1.071 1.071 

Overall 1.336 1.452 

6-16 

EERE-2008-BT-STD-0006 COMMENT 54
REFERENCES 

1. Heating, Air Conditioning & Refrigeration Distributors International. 2008. 2008 Profit 

Report (2007 Data). 

2. Air Conditioning Contractors of America. 2005. Financial Analysis for the HVACR 

Contracting Industry. 

3. U.S. Census Bureau. 2002. Commercial and Institutional Building Construction: 2002. 

Report EC02-231-236220. 

4. U.S. Census Bureau. 2002. Air-Conditioning and Warm Air Heating Equipment and 

Commercial and Industrial Refrigeration Equipment Manufacturing: 2002. 

Report EC02-311-333415. 

5. U.S. Census Bureau. 2005. Product Lines: 2002. Report EC02-42SL-LS. 

6. U.S. Census Bureau. 2002. Commercial and Institutional Building Construction: 2002. 

Report EC02-231-236220. 

7. U.S. Census Bureau. 2002. Plumbing, Heating, and Air-Conditioning Contractors: 2002. 

Report EC02-231-238220. 

8. Pindyck, R. and D. Rubinfeld, Microeconomices, Prentice Hall. 2000. 

9. The Sales Tax Clearinghouse at https://thestc.com/STRates.stm (Accessed on June 4, 2009) 

6-17 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

CHAPTER 7. ENERGY USE CHARACTERIZATION FOR RESIDENTIAL
 

AIR-CONDITIONING AND HEAT PUMP EQUIPMENT
 

TABLE OF CONTENTS
 

7.1 Introduction ...................................................................................................................... 7-1
 

7.1.1 General Approach to the Energy Use Analysis – Residential ............................. 7-1
 

7.1.2 General Approach to the Energy Use Analysis – Commercial............................ 7-3
 

7.1.3 Overview of Energy Use Analysis Inputs............................................................ 7-4
 

7.2 ANALYZED RECS HOUSEHOLDS ................................................................................ 7-4
 

7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL ............... 7-5
 

7.3.1 Methodology for Estimating Stock Annual Space-Cooling Energy Use............. 7-6
 

7.3.2 Stock Annual Space-Cooling Energy Use ........................................................... 7-7
 

7.3.3 Stock Space-Cooling Efficiency (SEER)............................................................. 7-9
 

7.3.4 Estimating Baseline Annual Space-Cooling Energy Use .................................. 7-12
 

7.4	 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP EQUIPMENTRESIDENTIAL................................................................................................................. 7-13
 

7.4.1 Estimating Stock Annual Space-Heating Energy Use ....................................... 7-14
 

7.4.2 Stock Space-Heating Efficiency (HSPF)........................................................... 7-16
 

7.4.3 Estimating Baseline Annual Space-Heating Energy Use .................................. 7-18
 

7.5	 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED 

FOR RECS SAMPLE WEIGHTS.................................................................................... 7-19
 

7.6	 BASELINE COMMERCIAL CAC AND CHP ENERGY USE ...................................... 7-20
 

7.7	 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH ................. 7-21
 

7.7.1 Simulation Tool Description.............................................................................. 7-21
 

7.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters .......... 7-22
 

7.7.3 Small Office Building Characteristics ............................................................... 7-23
 

7.7.4 Building Operating Characteristics.................................................................... 7-24
 

7.7.5 Building Mechanical Systems and Equipment .................................................. 7-27
 

7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION............................................. 7-27
 

7.9	 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS............... 7-29
 

7.10 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING EFFICIENCIES7-29 

7.11 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS ANALYSIS
 

AND CORRESPONDING REGIONAL ENERGY CONSUMPTION BY
 

EFFICIENCY LEVEL ...................................................................................................... 7-32
 

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LIST OF TABLES
 

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine 

Census Divisions and the Four Large States........................................................ 7-7
 

Table 7.3.2. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock) .............................................................................................. 7-8
 

Table 7.3.3. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP-Stock)............................................................................................... 7-8
 

Table 7.3.4. Number of Observations for Each Age Group ...................................................... 7-10
 

Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency............................................. 7-12
 

Table 7.3.6. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (CAC) ....................................................................................... 7-13
 

Table 7.3.7. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at 

Regional Level (CHP)........................................................................................ 7-13
 

Table 7.4.1. 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census 

Divisions and the Four Large States .................................................................. 7-15
 

Table 7.4.2. Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption 

for RECS-Stock CHP at Regional Level ........................................................... 7-15
 

Table 7.4.3. Average Annual Heating Pump HSPF .................................................................. 7-18
 

Table 7.4.4. Baseline (13 SEER) Space-Heating Energy Consumption Statistics at 

Regional Level(CHP)......................................................................................... 7-18
 

Table 7.7.1. CAC and CHP Blower and Characteristics Used in Modeling Commercial 

Cooling and Heating Energy Use ...................................................................... 7-23
 

Table 7.10.1. CAC and CHP Efficiency Distributions Estimated for 2007 .............................. 7-31
 

Table 7.10.2. CAC and CHP Efficiency Distributions Estimated for Market Baseline ............ 7-32
 

Table 7.11.1. Proposed Climate Regions for Regional Standards............................................. 7-33
 

Table 7.11.2. Split-System Air Conditioners: Average Annual Energy Use by Efficiency
 

Level for Coil-Only Systems ............................................................................. 7-34
 

Table 7.11.3. Split-System Air Conditioners: Average Annual Energy Use by Efficiency
 

Level—Blower-Coil Systems ............................................................................ 7-34
 

Table 7.11.4. Split-System Heat Pumps: Average Annual Energy Use by Efficiency
 

Level .................................................................................................................. 7-35
 

Table 7.11.5. Single-Package Air Conditioners: Average Annual Energy Use by
 

Efficiency Level................................................................................................. 7-35
 

Table 7.11.6. Single-Package Heat Pumps: Average Annual Energy Use by Efficiency
 

Level .................................................................................................................. 7-36
 

LIST OF FIGURES 

Figure 7.1.1. Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential CAC and CHPs ................................................................................. 7-2
 

Figure 7.1.2. Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential CHPs ................................................................................................. 7-3
 

Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CHPs in Commercial Use .................................... 7-4
 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Figure 7.3.1. National Distribution of Weather-Adjusted Space-Cooling Energy for 

RECS Observations ............................................................................................. 7-9
 

Figure 7.3.2. National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations ............................................................................................. 7-9
 

Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups ......................... 7-10
 

Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups ......................... 7-11
 

Figure 7.3.5. Distribution of RECS Households with CACs by Vintage.................................. 7-11
 

Figure 7.4.1. National Distribution of Weather-Adjusted Space-Heating Energy for RECS
 

Observations ...................................................................................................... 7-16
 

Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups................................................................................................................ 7-17
 

Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage ........... 7-17
 

Figure 7.5.1. Baseline National Cooling Energy Distribution for CAC – Residential .............. 7-19
 

Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential .............. 7-19
 

Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential ............... 7-20
 

Figure 7.7.1. Small Office Building Design View..................................................................... 7-24
 

Figure 7.7.2. Small Office Building HVAC Zoning.................................................................. 7-24
 

Figure 7.7.3. Small Office Lighting Schedule ........................................................................... 7-25
 

Figure 7.7.4. Small Office Plug Load Schedule ........................................................................ 7-26
 

Figure 7.7.5. Small Office Occupancy Schedule....................................................................... 7-26
 

Figure 7.7.6. Small Office Thermostat Set Point Schedule ....................................................... 7-27
 

Figure 7.8.1. Baseline National Cooling Energy Distribution for CAC-Commercial, 

Weighted ............................................................................................................ 7-28
 

Figure 7.8.2. Baseline National Cooling Energy Distribution for CHP-Commercial, 

Weighted ............................................................................................................ 7-28
 

Figure 7.8.3. Baseline National Heating Energy Distribution for CHP-Commercial, 

Weighted ............................................................................................................ 7-29
 

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7.1 INTRODUCTION 

The energy use analysis provides estimates of the distribution of annual energy 

consumption for central air conditioner (CAC) and central heat pump (CHP) equipment at the 

base case (i.e., with no new standards) and at efficiency standard levels considered in the 

analysis. This information is used in the subsequent life-cycle cost (LCC) and payback period 

(PBP) analyses (chapter 8 of the technical support document [TSD]), which in turn provides the 

raw energy use data for the national impacts analyses (chapter 11 of the TSD). Both energy use 

in the residential sector customers and to the commercial sector customer are considered. In the 

energy use analysis, the United States (U.S.) Department of Energy (DOE) developed energy 

consumption estimates for four equipment classes analyzed in the engineering analysis (chapter 5 

of the TSD). For one equipment class, split-system air conditioners, two installation methods 

were separately considered: coil-only, where the indoor furnace fan is not replaced for higher 

efficiency equipment, and blower-coil, where the indoor blower is replaced, corresponding to the 

similar breakdown of this equipment class in the engineering analysis. 

7.1.1 General Approach to the Energy Use Analysis – Residential 

The general approach adopted in the energy use analysis for CAC equipment used in 

residences was to utilize energy use and household characteristics data from the DOE Energy 

Information Agency (EIA) 2005 Residential Energy Consumption Survey (RECS) to provide 

estimates of cooling and heating energy for the sample households using CAC and CHP 

equipment. This estimate reflects household stock equipment efficiency levels. The energy use 

estimates are then adjusted to reflect long term average weather conditions and then further 

adjusted to reflect equipment energy consumption for the same households assuming that they 

were using new equipment as would be purchased in 2016 under a base case standards scenario. 

A sample population of U.S. homes using CAC and CHP equipment was first identified 

from the RECS households surveyed. This sample provided a dataset of cooling and heating 

energy use for 2005 for households with CACs and CHPs. This data were then adjusted 

(weather-normalized) to reflect corresponding energy-use figures for typical long-term climate 

conditions. Historical efficiency data for shipped CAC and CHP equipment was used in 

conjunction with equipment age information from RECS to estimate the stock equipment 

efficiency for each household record used in the analysis. The annual energy consumption for 

equipment in the 2016 base case (i.e., no new standards) was then calculated for each equipment 

class by multiplying the weather-adjusted cooling or heating energy use for each RECS 

household by the ratio of the efficiency (e.g., SEER) of the stock unit in that household to that of 

an assumed efficiency for that household in the 2016 base case. This 2016 base case provides an 

efficiency level likely to be purchased for each household assuming a new CAC or CHP 

purchase in that year. The 2016 efficiency levels used for each household were selected at 

random from a distribution of shipped efficiencies developed for each product class. This base 

case is also referred to as the market baseline case, since the efficiency distribution is 

representative of the current market for CAC and CHP equipment. 

Once the base case cooling energy use was established for a selected RECS household 

record, the corresponding annual cooling energy consumption for higher efficiencies under new 

standard scenarios was calculated by multiplying the cooling energy consumption for each 

7-1 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

household in the base case by the ratio of the seasonal energy efficiency ratio (SEER) in the base 

case to that of the SEER in the standards case. In the case of heating energy use for heat pumps 

the corresponding household annual heat pump heating energy consumption under new standard 

scenarios was calculated by multiplying the heat pump heating energy consumption for each 

household in the base case by the ratio of the heating seasonal performance factor (HSPF) in the 

base case to the HSPF in the standards case. Figure 7.1.1 and Figure 7.1.2 provide a flow 

diagram on calculation of cooling and heating energy for the residential energy use analysis. 

RECS Baseline SEER Market Baseline
 

Stock Household (SEER 13) SEER Standard Level 

Annual Cooling
 

Estimated SEER 

of Stock 

CAC or CHP 

Distribution SEER
 

Energy (Weather
 

Normalized)
 

RECS
 

Age of Household 

CAC or CHP
 Baseline Market Baseline Standard Level 

Annual Cooling Annual Cooling Annual Cooling 

Energy Use Energy Use Energy Use 

AHRI 

Shipment Average 

SEER 

CAC and CHP 

Figure 7.1.1. Flow Diagram for the Determination of Annual Space-Cooling Energy for 

Residential CAC and CHPs 

7-2 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

RECS 

Stock Household 

Annual Heating 

Energy (Weather 

Normalized) 

RECS 

Age of Household 

CHP 

Baseline SEER 

(HSPF 7.7) 

Baseline 

Annual Heating 

Energy Use 

Market Baseline
 

HSPF Distribution
 

Market Baseline 

Annual Heating 

Energy Use 

Standard Level 

HSPF 

Standard Level 

Annual Heating 

Energy Use 

Estimated 

HSPF of Stock 

CHP 

AHRI 

Shipment Average 

HSPF by Vintage 

CHP 

Figure 7.1.2. Flow Diagram for the Determination of Annual Space-Heating Energy for 

Residential CHPs 

7.1.2 General Approach to the Energy Use Analysis – Commercial 

DOE also developed estimates for the annual energy use for CAC and CHP sold into the 

commercial building market. The commercial market is estimated to use approximately seven 

percent of all CAC and CHP equipment. For the commercial analysis, DOE relied on the use of 

the EnergyPlus building simulation software to estimate the energy consumption of this 

equipment at four specific efficiency levels-from baseline to the max tech level-for 237 climates 

around the United States for a typical commercial application, a small office building. DOE 

extracted equipment sizing, supply fan, condenser and heater energy use from these simulations. 

DOE then used these results to develop estimates of annual energy use for CAC and CHP 

equipment at other efficiency levels defined in the engineering analysis via interpolation between 

the efficiency levels simulated. Figure 7.1.3 provides a flow diagram for the calculation of CAC 

and CHP cooling and heating energy for the commercial energy use analysis. 

7-3 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Figure 7.1.3. Flow Diagram for the Determination of Annual Space-Cooling and SpaceHeating Energy for CAC and CHPs in Commercial Use 

7.1.3 Overview of Energy Use Analysis Inputs 

The following are the principal inputs to the residential energy use analysis: 

• Household cooling and heating energy from 2005 RECS 

• CAC and CHP equipment age information for the RECS households 

• Historical state average monthly cooling and heating degree day data (1978–2007) 

• Historical average cooling and heating efficiency data for CAC and CHP from AHRI 

• Base case efficiency distributions for 2016 developed for this analysis 

• Engineering efficiency levels to be analyzed 

• The following are the principal inputs to the commercial energy use analysis: 

• Engineering efficiency levels to be analyzed 

• Location specific weather file data for use with building simulation tool 

• Population-based weighting factors for each weather file 

7.2 ANALYZED RECS HOUSEHOLDS 

The 2005 RECS includes data for 4,382 housing units, of which 2,317 were reported to 

have “CAC only” cooling systems. These include 416 housing units reporting their CAC unit 

also being cooling-performance heat pumps. The number of households actually included in the 

LCC and PBP analyses were 1,854 for the CAC systems and 339 for heat pumps. Out of the 

1901 (2317-416) households that could have been potentially considered for analysis of CAC 

energy consumption, 47 were not included in the analysis for the following reasons: 

• the CAC system was reported as not being used (40 households), and 

Small Office 

Building Model 

EnergyPlus Simulation Tool 

CAC or CHP 

Characteristics for 

Four Selected 

Efficiency Levels 

TMY Weather 

Data Bldg. Annual 

Cooling, Heating, 

Fan Energy Use 

Zone Peak 

Equipment Sizes 

Annual Cooling, Heating, Fan Energy Use 

for Selected Efficiency Levels 

 (Normalized to 3-Ton unit) 

Market Baseline 

Annual Cooling , 

Heating, and Fan 

Energy Use 

Market Baseline 

SEER /HSPF 

Distribution 

Standard Level 

SEER/HSPF 

Standard Level 

Annual Cooling , 

Heating, and Fan 

Energy Use 

7-4 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

•	 the household reported a “heat pump” being the main heating equipment, contradicting a 

second response that their CAC system is not a heat pump (7 households). 

For the seven households with conflicting responses, it was considered that the response 

regarding the main heating equipment being a heat pump should override the secondary response 

and these records were included in the set for analyzing energy consumption for heat pumps. 

For the heat pumps, out of the 423 (416+7) candidate households, DOE removed 84 for 

the following reasons: 

•	 The system was reportedly not being used (6 households). 

•	 The survey responses reported a non-furnace heating equipment (i.e., heating stove, 

fireplace, built-in wall furnaces etc. being the main heating equipment), thus implying 

that the heating energy use reported for the household should not be primarily attributed 

to the heat pump (17 households). 

•	 Some households indicated a warm air furnace as the main heating equipment and no 

electrical energy use for space heating implying that the heat pump function is not used at 

all or that the RECS may be reporting the “heat pump” energy consumption or presence 

in error (36 households), and 

•	 Some households report a warm air furnace as well as heat pump, but questions on usage 

of any complementary fuel were skipped. This led to an ambiguity about whether the 

heating energy use reported from the conditional demand model was reported as 

representative of a heat pump or an electric furnace. Barring more detail on the analysis 

of these records by EIA, they were removed from consideration in DOE’s analysis (25 

households). 

7.3 BASELINE ANNUAL SPACE-COOLING ENERGY USE – RESIDENTIAL 

In order to estimate the energy savings for higher standards, DOE first established 

estimates of cooling and heating energy consumption for baseline equipment based on energy 

consumption in the current stock and product efficiency assumptions appropriate to the stock 

equipment and the efficiency of baseline products. The energy consumption of CACs and CHPs 

in the equipment stock is related to the capacity and efficiency of these products, the climate, and 

individual household use patterns. The efficiency of the equipment in the building stock also 

varies depending on the vintage. The energy consumption of residential air-conditioners and heat 

pumps in the current stock and estimates of the efficiency in the current stock are used in 

conjunction with the efficiencies of baseline equipment to provide an estimate of energy 

consumption of baseline equipment. The baseline annual space-cooling energy consumption for 

residential air conditioners and cooling-performance heat pumps was estimated for each RECS 

observation using equation 7.3.1. 

SEERres _ stock UEC = UEC ×	 Eq. 7.3.1 res _ base _ c res _ stock _ c SEERbase 

Where: 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

UECres_base_c = the baseline annual unit energy consumption for space-cooling, 

UECres_stock_c = the annual unit energy consumption space-cooling associated with the 

stock equipment, 

SEERbase = the space-cooling efficiency associated with the baseline equipment, 

and 

SEERres_stock_c = the space-cooling efficiency associated with the stock equipment. 

Thus, once the annual space-cooling energy consumption associated with the stock 

equipment, UECres_stock_c, and the space-cooling efficiency, SEERres_stock_c, are determined; the 

baseline annual space-cooling energy consumption is estimated. In the next section, the 

methodology for obtaining UECres_stock_c and SEERres_stock are discussed. 

7.3.1 Methodology for Estimating Stock Annual Space-Cooling Energy Use 

The stock annual space cooling energy consumption was estimated based on data from 

the 2005 RECS. This survey contains data on household characteristics, end use energy 

consumption, general location in the United States (limited to location within census division and 

four large states; New York, Florida, Texas and California), and approximate heating and 

cooling degree days for each sample location for the year of the survey. The latter two statistics 

are purposefully kept general or sufficiently masked by EIA to preclude identification of the 

surveyed residences. 

The household energy consumption for the individual surveyed households in RECS are 

obtained by EIA from the energy suppliers via monthly energy bill records. EIA uses a 

conditional demand analysis (CDA)1 model to further breakdown the household energy use into 

end-use energy consumption estimates (e.g., cooling, heating, lighting, and hot water energy) 

which it reports as annual end-use energy in the survey results. The cooling energy use for the 

selected households with CAC or CHP products represents the cooling energy consumption 

associated with the stock equipment for 2005. Because 2005 may not be representative of typical 

weather for that location, the cooling energy consumption associated with the stock equipment in 

the RECS households are first adjusted (weather normalized) using 30-year-average (1978– 

2007) cooling degree day (CDD) data (base 65 °F) and Eq. 7.3.2: 

CDD30 _ yr _ avg UECres _ stock _ c = UECres _ stock _ c _ non−adj ×

CDD Eq. 7.3.2 

res _ stock _ 2005 

Where: 

UECres_stock_c_non-adj = annual space-cooling energy consumption associated with the 

stock equipment, extracted directly from RECS household data, 

UECres_stock_c = annual space-cooling consumption associated with the stock 

equipment, adjusted by using 30-year average CDD data for the 

RECS location, 

CDDres_stock_2005 = CDD in 2005 for the specific Census Division or state where the 

housing unit is located, and 

CDD30_yr_avg = 30-year average CDD (1978–2007) for the specific Census 

Division or state where the housing unit is located. 

7-6 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

7.3.2 Stock Annual Space-Cooling Energy Use 

DOE first weather-normalized the cooling energy use data for the selected RECS 

households to better reflect long term average weather conditions for each location. DOE 

obtained CDD data for each state on a monthly basis for 1978–2007 from the National Oceanic 

and Atmospheric Administration (NOAA) National Climatic Data Center (NCDC).2 DOE 

aggregated the monthly data for each year to produce annual CDD data for each state. These 

were then further aggregated geographically to the specific census divisions or four large state 

geographic regions used by RECS. These states included in each of these geographic regions are 

shown in Table 7.3.1. 

In estimating annual CDD for each census division, the annual CDD for the states in each 

division are weighted according to the population in the component states for the specific year. 

Population data from 1978 to 2007 were developed based on 1980, 1990, and 2000 U.S. Census 

Bureau data,3 with estimates for other years obtained by linear interpolation or extrapolation as 

necessary. The resulting 30-year average CDD and the 2005 CDD for the regions are shown in 

Table 7.3.1. 

Table 7.3.1. The 30-Year Average CDD (1978–2007) and the 2005 CDD for the Nine Census 

Divisions and the Four Large States 

Division States 30-Year 

Average CDD 

2005 CDD 

1: New England Connecticut, Maine, Massachusetts, New Hampshire, 

Rhode Island, Vermont 

462 579 

2: Middle Atlantic New Jersey, Pennsylvania 737 991 

3: East North Central Indiana, Illinois, Michigan, Ohio, Wisconsin 758 983 

4: West North Central Iowa, Kansas, Minnesota, Missouri, Nebraska, North 

Dakota, South Dakota 

989 1,171 

5: South Atlantic Delaware, District of Columbia, Georgia, Maryland, 

North Carolina, South Carolina, Virginia, West Virginia 

1,382 1,486 

6: East South Central Alabama, Kentucky, Mississippi, Tennessee 1,620 1,747 

7: West South Central Arkansas, Louisiana, Oklahoma 2,215 2,402 

8: Mountain Arizona, Colorado, Idaho, New Mexico, Montana, Utah, 

Nevada, Wyoming 

1,318 1,498 

9: Pacific Alaska, Hawaii, Oregon, Washington 226 226 

Four Large States New York 654 943 

California 949 837 

Texas 2,711 2,908 

Florida 3,505 3,436 

Based on the 2005 RECS annual space-cooling energy consumption data and the CDD 

data, the weather-adjusted annual space-cooling energy consumption for each household was 

obtained by using Eq. 7.3.2. Statistics showing the weather-adjusted annual space-cooling energy 

consumption for the households that have air-conditioners are shown in Table 7.3.2. Statistics 

showing the weather-adjusted annual space-cooling energy consumption for the households that 

have heat pumps are shown in 

7-7 

EERE-2008-BT-STD-0006 COMMENT 54
Table 7.3.3. The frequency distribution of the weather-adjusted annual household energy 

consumption for space-cooling for CAC and CHP for the RECS observations are shown in 

Figure 7.3.1 and Figure 7.3.2. 

Table 7.3.2. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC-Stock) 

Division or State Number of 

Observations 

Min 

kilowatt 

hours per 

year 

(kWh/yr) 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 56 4,186 1,229 

Middle Atlantic 127 289 5,420 1,650 

East North Central 346 130 9,459 1,477 

West North Central 224 207 9,882 2,067 

South Atlantic 233 152 8,628 2,952 

East South Central 173 331 11,573 3,653 

West South Central 79 647 12,359 4,070 

Mountain 130 65 26,078 3,167 

Pacific 23 89 3,610 1,273 

New York 34 333 5,361 1,295 

California 160 36 17,335 1,835 

Texas 181 44 29,326 5,780 

Florida 94 1,508 14,688 6,104 

National 1,854 36 29,326 2,851 

Table 7.3.3. Weather Adjusted Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP-Stock) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 1 432 432 432 

Middle Atlantic 10 214 2,182 1,460 

East North Central 20 455 6,938 2,315 

West North Central 12 234 5,634 2,413 

South Atlantic 108 445 11,059 3,442 

East South Central 54 1,157 11,586 3,968 

West South Central 6 1,246 9,573 4,545 

Mountain 23 3,220 12,893 7,194 

Pacific 13 78 3,221 1,060 

New York 1 761 761 761 

California 11 312 6,449 2,492 

Texas 15 2,166 11,363 6,423 

Florida 65 1,805 17,380 6,738 

National 339 78 17,380 4,264 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

0%

2%

4%

6%

8%

10%

12%

14%

16%

18%

Percentage of Obersavtions 

Weather-Adjusted CAC Cooling Energy from RECS 

(kWh/yr) 

Figure 7.3.1. National Distribution of Weather-Adjusted Space-Cooling Energy for RECS 

Observations 

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Obersavtions 

Weather-Adjusted CHP Cooling Energy from RECS 

(kWh/yr) 

Figure 7.3.2. National Distribution of Weather-Adjusted Space-Cooling Energy for CHPRECS Observations 

7.3.3 Stock Space-Cooling Efficiency (SEER) 

To estimate annual space-cooling energy consumption data at the baseline and higher 

efficiency levels, DOE relies on the cooling and heating energy calculated for the stock 

households and the historic space-cooling efficiency levels of the stock equipment, SEERres_stock. 

The space-cooling efficiency of stock equipment is related to the vintage of the equipment. In the 

2005 RECS database, the age of the equipment is reported in terms of age groups and not the 

specific vintage year. The five age groups are “less than 2 years old,” “2 to 4 years old,” “5 to 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

9 years old,” “10 to 19 years old,” and “20 years or older.” The data also include one additional 

age category: “as old as the home.” In RECS the years of construction of each residence for older 

homes are also reported in age bands though the specific year of construction is indicated for the 

newer homes. DOE assumed that the age of the CAC system, within a given age group in the 

general population would be approximately uniformly distributed throughout the range of the age 

band. For example, for the CAC systems in the “less than 2 years old” age group, it was 

assumed that 50 percent of heat pumps were one year old and the other 50 percent were 2 years 

old. Similar technique was used in ascertaining the probable vintage year of the home and the 

equipment when the equipment was reported to be the age of the home. The resulting age 

distribution of the CACs and CHPs in the RECS households identified for analysis are shown in 

Table 7.3.4 and graphically in Figure 7.3.3 and Figure 7.3.4, respectively. 

Table 7.3.4. Number of Observations for Each Age Group 

Equipment Type Less than 2 

Years Old 

2 to 4 

Years Old 

5 to 9 

Years Old 

10 to 19 

Years Old 

20 Years 

or Older 

Total 

Central Air 243 321 472 502 316 1854 

Conditioners 13.1% 17.3% 25.5% 27.1% 17.0% 100% 

Cooling-Performance 57 61 104 89 28 339 

Heat Pump 16.8% 18.0% 30.7% 26.3% 8.3% 100% 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

Percent Of households 

Less than 2 2 to 4 years 5 to 9 years 10 to 19 20 years or 

years old old old years old older 

Age of CAC Systems 

Figure 7.3.3. The Distribution of CACs in the RECS Sample by Age Groups 

Once the age group in which the household equipment falls into was established, DOE 

estimated the vintage of the equipment for each household in each age group by random 

assignment using the uniform age distribution assumption for each age group and the known 

2005 survey year. For the 20-year and older age group, all equipment were assumed to be 

between 20 and 29 years old with the actual vintage assigned using a uniform distribution. The 

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EERE-2008-BT-STD-0006 COMMENT 54
 

resulting vintage distribution of the residential air conditioners and heat pumps in the overall 

sample is shown in Figure 7.3.5. 

DOE estimated the stock cooling SEER for each household using equipment vintage and 

average shipped efficiency for each vintage year. The latter was developed from AHRI data4 and 

is shown in Table 7.3.5. 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

35.0% 

Less than 

2 years 

old 

2 to 4 

years old 

5 to 9 

years old 

10 to 19 

years old 

20 years 

or older 

Age of Heat Pump Systems 

Percent Of households 

Figure 7.3.4. The Distribution of CHPs in the RECS Sample by Age Groups 

0.0% 

1.0% 

2.0% 

3.0% 

4.0% 

5.0% 

6.0% 

7.0% 

8.0% 

1,9761,9781,9801,9821,9841,9861,9881,9901,9921,9941,9961,9982,0002,0022,004 

Vintage year of CAC Equipm ent 

Percent of Households 

Figure 7.3.5. Distribution of RECS Households with CACs by Vintage 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7.3.5. Average Annual Shipped Space-Cooling Efficiency 

Year Central A/C 

(SEER) 

Heat Pump (SEER) 

1976 7.15 6.87 

1977 7.18 6.89 

1978 7.41 7.24 

1979 7.45 7.34 

1980 7.51 7.51 

1981 7.73 7.70 

1982 8.30 7.79 

1983 8.44 8.23 

1984 8.70 8.45 

1985 8.84 8.56 

1986 8.87 8.70 

1987 8.95 8.93 

1988 9.11 9.13 

1989 9.23 9.26 

1990 9.25 9.41 

1991 9.44 9.73 

1992 10.43 10.56 

1993 10.52 10.82 

1994 10.58 10.89 

1995 10.64 10.93 

1996 10.63 10.95 

1997 10.62 10.93 

1998 10.23 10.52 

1999 10.86 11.24 

2000 10.95 11.23 

2001 11.07 11.31 

2002 11.07 11.32 

2003 11.22 11.48 

2004 11.32 11.58 

2005 11.33 11.69 

7.3.4 Estimating Baseline Annual Space-Cooling Energy Use 

For each class of equipment, the baseline annual space-cooling energy consumption for 

each equipment type (air-conditioner or heat pump) was estimated by using Eq. 7.3.2. The key 

inputs are the weather-adjusted annual space-cooling energy consumption derived from the 2005 

RECS data, the stock space-cooling efficiency estimates for air conditioners and heat pumps 

from Table 7.3.5, and the baseline cooling efficiency, 13 SEER. 

Statistics for the baseline space-cooling energy consumption for RECS households at 

regional and national level are shown in Table 7.3.6 for air conditioners and Table 7.3.7 for heat 

pumps. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 7.3.6. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (CAC) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 45 3,526 987 

Middle Atlantic 127 246 4,550 1,270 

East North Central 346 104 7,967 1,148 

West North Central 224 145 8,324 1,593 

South Atlantic 233 119 7,513 2,314 

East South Central 173 247 10,078 2,864 

West South Central 79 433 10,115 3,082 

Mountain 130 53 21,344 2,536 

Pacific 23 78 3074 1,029 

New York 34 229 3645 1,016 

California 160 24 15,095 1,440 

Texas 181 30 25,536 4,520 

Florida 94 1,234 12,372 4,860 

National 1,854 24 25,536 2,231 

Table 7.3.7. Baseline (13 SEER) Space-Cooling Energy Consumption Statistics at Regional 

Level (CHP) 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 1 249 249 249 

Middle Atlantic 10 118 1,823 1,236 

East North Central 20 323 5,566 1,882 

West North Central 12 190 4,911 1,962 

South Atlantic 108 320 9,417 2,779 

East South Central 54 909 9,465 3,203 

West South Central 6 973 6,797 3,568 

Mountain 23 2,424 8,876 5,616 

Pacific 13 68 2,339 842 

New York 1 663 663 663 

California 11 263 5,492 1,960 

Texas 15 1,473 9,191 5,278 

Florida 65 1,311 13,677 5,339 

National 339 68 13,677 3,412 

7.4	 BASELINE ANNUAL SPACE-HEATING ENERGY USE FOR CHP 

EQUIPMENT- RESIDENTIAL 

The baseline annual space-heating energy consumption for the CHP system is estimated 

following procedures similar to that for estimating the baseline annual space-cooling energy 

consumption. The baseline annual space-heating energy consumption for residential heat pumps 

is estimated by using the following equation: 

HSPFres _ stock UEC = UEC ×	 Eq. 7.4.1 res _ base _ h res _ stock _ h HSPFbase 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

Where, 

UECres_base_h = the baseline annual space-heating energy consumption 

UECres_stock_h = the annual space-heating energy consumption associated with the stock 

heat pump 

HSPFres_stock_h = the space-heating efficiency associated with the stock equipment 

HSPFbase = the space-heating efficiency associated with baseline equipment 

7.4.1 Estimating Stock Annual Space-Heating Energy Use 

The annual space-heating energy consumption for the CHP systems in the stock was 

obtained from the 2005 RECS database for the heat pump sample identified. To account for the 

variation in weather conditions for the year 2005 from statistical normals, the annual spaceheating energy consumption in 2005 was adjusted by using the following equation: 

HDD30 _ yr _ avg UECres _ stock _ h = UECres _ stock _ h _ non−adj ⋅ HDD Eq. 7.4.2 

res _ stock 

Where: 

UECres_stock_h = annual space-heating energy consumption associated with the 

stock equipment after weather-adjustment, 

UECres_stock_h_non-adj = annual space-heating energy consumption, obtained directly from 

RECS database, 

HDD30_yr_avg = 30-year (1978-2007) average heating degree day (HDD, base 65 

°F) for the census division or state where the household is located, 

and 

HDDres-stock = HDD in 2005 (base 65 °F) for the census division or state where 

the household is located. 

State-wise monthly HDD data from 1978 to 2007 were obtained from National Oceanic 

and Atmospheric Administration (NOAA) database center.2 DOE aggregated the monthly data 

for each year to produce annual HDD for each state. The state annual HDD data were used to 

derive annual HDD for the regions identified in RECS (census divisions and separately four 

large states). In estimating divisional annual HDD, the annual HDD values for states within the 

regions were weighted by the state population in that year as described in section 7.3.1. The 30­

year average HDD and the 2005 HDD for the nine census divisions and the four large states are 

shown in Table 7.4.1 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Table 7.4.1. 30-Year Average HDD (1978–2007) and the 2005 HDD for the Nine Census 

Divisions and the Four Large States 

Division or State 30-Year HDD 

Average 

2005 HDD 

New England 6,571 6,453 

Middle Atlantic 5,602 5,612 

East North Central 6,103 6,323 

West North Central 5,989 6,506 

South Atlantic 3,665 3,720 

East South Central 3,309 3,496 

West South Central 2,415 2,723 

Mountain 4,666 5,142 

Pacific 5,133 5,193 

New York 5,912 5,929 

California 2,450 2,488 

Texas 1,686 1,944 

Florida 647 657 

By using equation (7.3.2), the weather-adjusted annual space-heating energy 

consumption was estimated for the equipment in each household. Statistics for the weatheradjusted space-heating energy consumption at both divisional and national level are shown in 

Table 7.4.2. The frequency distribution of the RECS sample households in different heating 

energy consumption bands is shown in Figure 7.4.1. 

Table 7.4.2. Statistics of Annual Weather-Adjusted Space-Heating Energy Consumption 

for RECS-Stock CHP at Regional Level 

Division or State Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Mean 

kWh/yr 

New England 1 2,399 2,399 2,399 

Middle Atlantic 10 581 5,177 2,871 

East North Central 20 1,911 10,037 4,237 

West North Central 12 926 4,778 2,702 

South Atlantic 108 0 6,412 2,692 

East South Central 54 0 5,667 2,468 

West South Central 6 354 4,434 2,386 

Mountain 23 424 1,630 891 

Pacific 13 2,171 5,251 3,621 

New York 1 3,409 3,409 3,409 

California 11 324 3,850 1,391 

Texas 15 998 3,788 1,671 

Florida 65 200 1,470 625 

National 339 0 10,037 2,179 

7-15 

EERE-2008-BT-STD-0006 COMMENT 54
 

0%

5%

10%

15%

20%

25%

Percentage of Obersavtions 

Weather-Adjusted CHP Heating Energy from RECS 

(kWh/yr) 

Figure 7.4.1. National Distribution of Weather-Adjusted Space-Heating Energy for RECS 

Observations 

7.4.2 Stock Space-Heating Efficiency (HSPF) 

The space-heating efficiency of CHP equipment has improved over time in response to 

both technology improvement and minimum efficiency standards. DOE related the space-heating 

efficiency of heat pumps in the stock to the equipment vintage, much as was done for the cooling 

efficiency. In the 2005 RECS database, the age groups of the equipment and not their specific 

vintage is given. The five age groups are “less than 2 years old,” “2 to 4 years old,” “5 to 9 years 

old,” “10 to 19 years old,” and “20 years or older.” The data reported also include one additional 

category: “as old as the home.” The years of construction of the home for older homes are also 

reported in age bands. It was assumed that the age of a heat pump, within a given age group was 

uniformly distributed over the range of the age group. For example, for the heat pumps in the 

“less than 2 years old” age group, it was assumed that 50 percent of heat pumps were one year 

old and the other 50 percent were two years old. Similar technique was used in ascertaining the 

probable vintage year of the home and the equipment when both were reported to have the same 

age. The distribution of households with heating-performance heat pumps by age groups is 

shown in Figure 7.4.2 and the distribution heat pump vintages are shown in Figure 7.4.3. 

AHRI does not publish data on the historical average HSPF for CHP equipment. DOE 

developed historical HSPF estimates from two data sources. For the years from 1973 to 1993, 

DOE used data reported in the Technical Support Document for the 2001 Rulemaking.5

 For the 

period from 1994 to 2005, DOE examined the 1994 ARI directory of Certified Products, and 

developed a regression equation which relates the SEER of residential split system heat pump 

DOE used the 1994 ARI Directory of Certified Equipment Database6

 to generate regressions 

between SEER and HSPF for CHP equipment on the market in 1994. For split systems, DOE 

used a regression based on data for all CHP characterized by the AHRI designations HRCU-ACB and HRCU-A-C. For packaged heat pumps, DOE used a regression for all CHP equipment 

with an HSP-A designation. Only single phase equipment with ratings listed as “Active”, “not 

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EERE-2008-BT-STD-0006 COMMENT 54
 

intended for export only”, were included. This resulted in two regression equations, one for the 

split system heat pump equipment class and one for single package heat pump equipment class. 

The historical average HSPF for each equipment class was calculated using historical annual 

average SEER values by equipment class from AHRI7

 and the appropriate regression equation. 

The annual average HSPF for all CHP equipment was then developed by weighting the annual 

average HSPF values by class using historical shipment data by equipment class. Table 7.4.3 

shows the resulting historical HSPF values by year. 

0.0% 

5.0% 

10.0% 

15.0% 

20.0% 

25.0% 

30.0% 

35.0% 

Less than 

2 years 

old 

2 to 4 

years old 

5 to 9 

years old 

10 to 19 

years old 

20 years 

or older 

Age of Heat Pump Systems 

Percent Of households 

Figure 7.4.2. Distribution of Households with Heating-Performance Heat Pumps by Age 

Groups 

0.0% 

2.0% 

4.0% 

6.0% 

8.0% 

10.0% 

12.0% 

1,976 

1,979 

1,982 

1,985 

1,988 

1,991 

1,994 

1,997 

2,000 

2,003 

Vintage Year of the Heat Pump Systems 

Percent of Households 

Figure 7.4.3. Distribution of RECS Households with Central Heat Pumps by Vintage 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 7.4.3. Average Annual Heating Pump HSPF 

Year Average HSPF Year Average HSPF 

1973 5.66 1990 6.98 

1974 5.66 1991 7.08 

1975 5.66 1992 7.19 

1976 5.66 1993 7.30 

1977 5.74 1994 7.38 

1978 5.83 1995 7.39 

1979 5.91 1996 7.40 

1980 6.00 1997 7.39 

1981 6.09 1998 7.29 

1982 6.18 1999 7.47 

1983 6.28 2000 7.46 

1984 6.37 2001 7.49 

1985 6.47 2002 7.49 

1986 6.56 2003 7.53 

1987 6.66 2004 7.56 

1988 6.81 2005 7.58 

1989 6.87 

7.4.3 Estimating Baseline Annual Space-Heating Energy Use 

For each class of equipment, the baseline annual space-heating energy consumption for 

CHP was estimated by using equation 7.4.2. The key inputs are the weather-adjusted annual 

space-heating energy consumption derived from the 2005 RECS data, the stock space-heating 

efficiency estimates for CHP shown in Table 7.3.5, and the baseline heating efficiency, 

7.7 HSPF. 

Statistics showing the baseline space-heating energy consumption calculated for RECS 

households with CHP equipment at regional and national level are shown in Table 7.4.4. 

Table 7.4.4. Baseline (13 SEER) Space-Heating Energy Consumption Statistics at Regional 

Level(CHP) 

Division Number of 

Observations 

Min 

kWh/yr 

Max 

kWh/yr 

Average 

kWh/yr 

New England 50 1,869 1,869 1,869 

Middle Atlantic 127 443 5,030 2,778 

East North Central 346 1,869 9,855 4,000 

West North Central 224 789 4,585 2,546 

South Atlantic 233 0 6,105 2,554 

East South Central 173 0 5,068 2,323 

West South Central 79 340 3,956 2,240 

Mountain 130 346 1,329 824 

Pacific 23 2,132 4,542 3,407 

New York 34 3,356 3,356 3,356 

California 160 287 3,745 1,305 

Texas 181 982 3,684 1,580 

Florida 94 170 1,351 586 

National 1,854 0 9,855 2,058 

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EERE-2008-BT-STD-0006 COMMENT 54
 

7.5	 BASELINE RESIDENTIAL COOLING AND HEATING RESULTS-ADJUSTED 

FOR RECS SAMPLE WEIGHTS 

Table 7.3.6 , Table 7.3.7, and Table 7.4.4 directly reflect the RECS household sample 

data. These tabulated results do not take into account the sample weights assigned by RECS for 

the different households. Figure 7.5.1, Figure 7.5.2, and Figure 7.5.3 show the distribution of 

calculated baseline cooling and heating energy for CAC and CHP products used in residences 

taking into account the RECS household samples weights. 

0%

5%

10%

15%

20%

25%

Percentage of Households 

Baseline CAC Cooling Energy (kWh/yr) 

Figure 7.5.1. Baseline National Cooling Energy Distribution for CAC – Residential 

0%

2%

4%

6%

8%

10%

12%

14%

Percentage of Households 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.5.2. Baseline National Cooling Energy Distribution for CHP – Residential 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

0%

5%

10%

15%

20%

25%

Percentage of Households 

Baseline CHP Heating Energy (kWh/yr) 

Figure 7.5.3. Baseline National Heating Energy Distribution for CHP – Residential 

7.6 BASELINE COMMERCIAL CAC AND CHP ENERGY USE 

Seven percent of residential-type (i.e., single-phase) CAC and CHP applications are 

assumed to be in commercial buildings. While potentially the variety of buildings to which this 

equipment could be utilized is wide, DOE believes that the vast majority of the shipments are 

utilized in small buildings, primarily small retail and commercial buildings. This is primarily 

because CAC and CHP equipment use single-phase electricity which limits the application to 

smaller buildings. 

Cooling and heating energy use in commercial buildings can be distinctly different from 

residential buildings even for the same equipment. This is predominantly due to commercial 

buildings being operated differently, often having defined operating hours when the equipment is 

used to condition the space, thermostatic setback during other hours, induced ventilation into the 

building structure to meet occupant needs, and typically continuous fan operation during 

occupied hours. Space heat gains in commercial buildings can be significantly different than in 

residential buildings due primarily to high internal thermal loads from lighting and electrical 

equipment during the occupied periods. 

In addition multiple cooling and heating units are commonly used. A similar data source 

to the RECS data discussed earlier is the EIA Commercial Building Energy Consumption Survey 

(CBECS)8

 which provides estimates of end-use energy consumption in commercial buildings. 

Because multiple pieces of cooling and heating equipment are the norm in most commercial 

buildings, and the number of units by equipment type is not captured in the survey, it is not 

possible to readily determine the energy use of individual pieces of CAC and CHP equipment 

using CBECS. In addition, CBECS does not clearly distinguish equipment types by electrical 

phase. Hence, identification of buildings that are predominantly served by CAC and CHP 

equipment is difficult. Given these difficulties, it was determined that CBECS could not be used 

to estimate the cooling and heating energy data for CAC and CHP equipment used in 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

commercial buildings. Instead, DOE relied on a building simulation approach to estimate the 

electrical energy usage of CAC and CHP equipment in commercial buildings. 

7.7 OVERVIEW OF COMMERCIAL ENERGY SIMULATION APPROACH 

In order to develop energy use statistics that reflect the use of CAC and CHP equipment 

in commercial buildings, DOE performed an analysis similar to that described in the Framework 

for Central Air Conditioners.9

 DOE used the EnergyPlus10 whole-building energy simulation 

software to estimate the energy consumption of CAC and CHP used to satisfy the cooling, 

supply fan, and in the case of CHP, the electrical heating energy required in a representative 

small office building. Simulations were carried out for 237 locations around the United States. 

The building model used was an existing single story, 5,500 ft2 office building model developed 

by the DOE for energy benchmarking purposes for this analysis. This benchmark building model 

is one of 16 commercial building benchmark models developed in support of the DOE Net Zero 

Energy Commercial Building Initiative.11,12 

Two variations were considered for the simulations: buildings were either entirely served 

by CAC equipment with gas furnace backup or were entirely served by CHP equipment. The 

simulated building utilized five individual CAC (or CHP units). For each equipment type, DOE 

simulated the equipment at four different efficiency levels starting from the baseline level. For 

CAC, these levels were: 13 SEER, 14 SEER, 16 SEER, and a max tech level of SEER 22 based 

on blower-coil ratings. For CHP these levels were: 13 SEER, 14 SEER, 16 SEER, and a max 

tech level of SEER 19.5 based on blower-coil ratings. Equipment parameters used in the 

simulation were adjusted to reflect engineering designs corresponding to each efficiency level. 

Simulations were carried out using Typical Metrological Weather Files (TMY2) for the 237 U.S. 

locations13. 

DOE extracted the annual energy consumption for cooling and fan energy use and 

heating from each modeled CAC or CHP unit as well as the equipment cooling capacity for each 

unit from each simulation run and aggregated these to the whole building level. Using this whole 

building cooling and heating data as well as the equipment capacities, DOE normalized the CAC 

and CHP energy consumption for each location and efficiency level to that of an average 3-ton 

CAC or CHP unit. These normalized energy use statistics were then used to represent the 

commercial energy use for a 3-ton CAC or CHP product for the LCC analysis. 

To estimate the energy consumption for intermediate efficiency levels between those 

simulated, DOE linearly interpolated the energy use estimates for cooling energy, fan energy and 

heating energy based on the results at the four simulated efficiency levels, the SEER or HSPF 

rating as the independent variable, and using the nearest lower and upper SEER or HSPF levels 

simulated. 

7.7.1 Simulation Tool Description 

DOE chose to use EnergyPlus version 3.0 for the energy analysis. EnergyPlus is the most 

recent of several large scale software programs developed for whole-building energy simulation 

analysis and has been validated by comparing its results with thermal and energy use 

measurements on actual buildings and with other software tools and calculations. EnergyPlus 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

predicts the hourly energy use of a building given hourly weather information and a description 

of the building, the operation of the building, and its heating, ventilation and air-conditioning 

(HVAC) equipment. Energy use statistics for the building can be readily extracted for different 

time steps and at detailed sub-component levels if necessary. EnergyPlus is an integrated 

software tool, where both the building loads and how those loads are served by equipment are 

solved iteratively and has a separate, but robust ground heat transfer model, which is particularly 

useful in the simulation of smaller buildings. DOE is currently using EnergyPlus as the basis for 

most of its building energy simulation research and the tool and its ongoing development are 

actively supported within DOE. 

7.7.2 Efficiency Levels Analyzed and Corresponding Simulation Parameters 

DOE simulated four efficiency levels for CAC equipment and four efficiency levels for 

CHP equipment, corresponding to particular efficiency levels identified in the engineering 

analysis. In order to simulate the equipment within the confines of the simulation software, the 

SEER and HSPF rating from the engineering analysis must be converted to parameters used by 

the simulation software. These parameters are the cooling COP, and for CHP the heating COP, 

of the condensing unit at rated conditions, and the fan power. The CAC and CHP condensing 

unit parameters are in turn calculated from 95 °F EER (EER) and 47 °F COP (COP47 °F) ratings 

for the equipment and the fan power at rated conditions. DOE first estimated these from the 

SEER and HSPF rating. 

The EER rating reflects the cooling performance for CAC equipment at a single-point 

rating condition defined by 95 °F outdoor temperature, 80 °F entering air dry bulb temperature 

and a 67 °F entering air wet bulb temperature. The COP47 °F rating reflects the heating 

performance of the heat pump at a single point rating condition defined by 47 °F outdoor 

temperature, 70 °F entering air dry bulb temperature and a maximum 60 °F entering air wet bulb 

temperature. The EER and COP47 °F ratings for equipment at different SEER levels were 

estimated using best fit curves for residential air conditioning equipment and heat pump 

equipment established by Wassmer and Brandemuehl.14 These curve fits are expressed in 

equation 7.7.1 and 7.7.2. 

EER = −0.0182 × SEER2 +1.1088× SEER Eq. 7.7.1 

COP47 F = −0.0255× HSPF 2 + 0.6239 × HSPF Eq. 7.7.2 

For 13 SEER equipment, the fan power at rating conditions was established assuming a 

blower motor efficiency of 0.65, a fan efficiency of 0.58, and a constant total static pressure of 

1.105 in H2O for the furnace/air handler. The same characteristics for fan power were also 

assumed to apply to the heat pumps at rating condition. The blower motor efficiency was 

assumed to be 0.65 for the 13 and 14 SEER ratings, consistent with that of a permanent split 

capacitor (PSC) blower motor. The blower motor efficiency was assumed to be 0.80 for the 

16 SEER and higher SEER ratings consistent with that of an electronically commutated motor 

(ECM) blower motor in this size range. A transition to ECM blower motors between the 14 and 

16 SEER ratings reflects the use of that technology in the CAC/CHP market from the 

engineering analysis where ECM motors appear to be commonplace at 16 SEER, but not 

common at 14 SEER. These assumptions result in a blower power under rating conditions of 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

138 W/ton for 13 and 14 SEER equipment, and a lower fan power of 112 W/ton for higher SEER 

equipment at rated conditions. For comparison, using the test procedure default 365 W/1,000 

CFM default for a coil-only rating would provide the same power levels assumed for 13 and 

14 SEER equipment at an airflow rate of 377 CFM/ton. 

The cooling and heating condensing unit COP values that are entered in the EnergyPlus 

software reflect the EER and COP47 °F ratings but are adjusted for the impact of the blower 

power. The blower power is directly incorporated into the total system power for these ratings, 

but because of the effect of fan heat, the incorporating the blower reduces the cooling output and 

raises the heating output. Equations 7.73 and 7.74 provide cooling and heating COP ratings for 

the condensing unit alone after adjusting for the fan power and fan heat. 

(EER / 3.413 + R) COPCUCool ,95°F = Eq. 7.7.3 1− R 

⎛COP 47°F − R ⎞ COPCUHeat,47°F = ⎜ ⎟ Eq. 7.7.4 ⎝ 1− R ⎠

Where: 

R = ratio of supply fan power to total equipment power at the AHRI rating 

condition, 

COPCUCool,95 °F = condensing unit cooling COP, and 

COPCUHeat,47 °F = condensing unit heating COP. 

Table 7.7.1 shows the resulting equipment performance statistics for the commercial 

building models. 

Table 7.7.1. CAC and CHP Blower and Characteristics Used in Modeling Commercial 

Cooling and Heating Energy Use 

Equipment 

Class 

SEER HSPF EER 47 °F 

COP 

Blower 

Motor 

Energy 

Efficiency 

Blower 

Power 

(w/ton)* 

Fan Power to 

Total Power 

(Rated 

Conditions) 

Cool 

COP95°F 

(Condensin 

g Unit Only) 

Heating 

COP47°F 

(Condensing 

Unit Only) 

CAC 13 NA 11.339 NA 0.65 138 0.13 3.966 NA 

14 NA 11.956 NA 0.65 138 0.135 4.208 NA 

16 NA 13.802 NA 0.80 112 0.123 4.511 NA 

22 NA 15.585 NA 0.80 112 0.14 5.471 NA 

CHP 13 7.7 11.339 3.292 0.65 138 0.13 3.966 3.626 

14 8 11.956 3.359 0.65 138 0.135 4.208 3.703 

16 8.6 13.802 3.480 0.80 112 0.123 4.511 3.842 

22 10.3 15.585 3.721 0.80 112 0.14 5.471 4.118 

* Calculated for rating conditions. 

7.7.3 Small Office Building Characteristics 

The small office building prototype model is a theoretical building modeled with 

characteristics typical of buildings of this size and use. The building is a 5,500 ft2

 single-story 

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EERE-2008-BT-STD-0006 COMMENT 54
building. The building is rectangular shaped, 52 ft by 105 ft with an aspect ratio of 1.5. The 

building has a window-area-fraction of 21 percent with a 10 ft floor-to-ceiling height. The small 

office building is assumed to have slab-on-grade construction for the floor and an attic. A picture 

of the building structure is shown in Figure 7.7.1. The building is divided into five HVAC zones, 

four perimeter zones and a core zone as illustrated in Figure 7.7.2, with a single CAC or CHP 

unit assumed for each HVAC zone. The perimeter zone depth in the center of each zone is 16 ft. 

Figure 7.7.1. Small Office Building Design View 

Figure 7.7.2. Small Office Building HVAC Zoning 

The building model presumes wood frame construction and punch-out type windows. 

Where applicable the building components for this model were assumed to “just meet” the 

minimum prescriptive requirements of the ASHRAE 90.1-2004 standard. Components not 

regulated by Standard 90.1 are assumed to be designed as is considered standard practice for a 

small office building. Standard practice is determined from various sources including a review of 

the Commercial Buildings Energy Consumption Survey (CBECS 2003) and the input of various 

design and construction industry professionals including members of the ASHRAE 90.1 

Standing Standard Project Committee. The following sections provide a review of the baseline 

building and how the baseline building is simulated in EnergyPlus, including characteristics of 

the building envelope, building internal loads (people, lighting, miscellaneous equipment, and 

infiltration), HVAC equipment, and service water heating. 

7.7.4 Building Operating Characteristics 

The building is assumed to follow typical small office occupancy patterns with peak 

occupancy occurring from 8 AM to 5 PM weekdays with limited occupancy beginning at 6 AM 

and extending until midnight for janitorial functions. The building is assumed to be unoccupied 

Saturday, Sunday and holidays. Schedules for lighting and miscellaneous equipment were 

matched to occupancy schedules with lower usage during unoccupied times. HVAC system 

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EERE-2008-BT-STD-0006 COMMENT 54
 

schedules were matched to the occupancy schedules, and allow for earlier startup times to bring 

the space to the desired temperature at the beginning of normal occupancy. Figure 7.7.3, Figure 

7.7.4, Figure 7.7.5, and Figure 7.7.5 show the EnergyPlus schedules for lighting, plug loads, 

occupancy, and thermostat set point. Detailed schedules are shown in appendix 7-A for these as 

well as for HVAC fans, infiltration, and service hot water. These schedules represent multipliers 

to defined daily “peak” conditions. In the case of ventilation, it is assumed that ventilation occurs 

whenever the fan system is operational. In the case of infiltration, a maximum infiltration rate for 

each hour is calculated hourly using wind speed and multiplied by the value shown in the hourly 

infiltration schedule. That value is 1.0 for hours when the ventilation is off and the building is 

assumed to be unpressurized. The schedule multiplier is assumed to be 0.25 during hours when 

the fan system is on and the building is pressurized. 

The HVAC systems are scheduled to be on from 6 a.m. to 7 p.m. weekdays 

(13 hours/day) and our schedule off weekends and holidays. Building thermostats are set to 

70 °F degree heating, 75 °F degree cooling during the occupied period. Thermostats are setback 

to 60 °F heating, 85 °F cooling during the unoccupied period. Between 6 a.m and 7 a.m weekday 

mornings the thermostats are set to 65 °F and 80 °F cooling heating set points to provide a onehour thermostat ramp between the setback and occupied set points to prevent equipment sizing 

and temperature balance problems. 

For the occupancy, lighting, plug use, ventilation, the schedules shown in Appendix 7-B 

are multipliers to defined peak densities. Lighting density was defined using the ASHRAE 90.1­

2004 maximum LPD requirement of 1.0 w/ft2

. Plug load density (e.g., computers and other 

miscellaneous loads) was 0.63 w/ft2

. Occupancy peak density was defined as 31 persons for the 

building (5.6 persons per thousand square foot). Ventilation was based on ASHRAE Standard 

62-1999 and set to 0.1 cfm/ft2 (cubic feet per minute per square ft) of floor area for each 

conditioned zone. The peak infiltration for the building was based on hourly wind speed as 

discussed previously and averages to 0.2016 cfm/ft2

 of total exterior conditioned zone wall area 

at a wind velocity of 10 miles per hour. 

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Percent of Peak Power Density

Weekday

Sat/Sun/Hol

Figure 7.7.3. Small Office Lighting Schedule 

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Figure 7.7.4. Small Office Plug Load Schedule 

Figure 7.7.5. Small Office Occupancy Schedule 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

0

10

20

30

40

50

60

70

80

90

100

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24

Thermostat Setpoint(°F)

Heat‐Weekday

Heat‐Sat/Sun/Hol

Cool‐Weekday

Cool‐Sat/Sun/Hol

Figure 7.7.6. Small Office Thermostat Set Point Schedule 

7.7.5 Building Mechanical Systems and Equipment 

As discussed, the building used either five CAC units or five CHP units, one for each 

conditioned zone depending on which equipment class was analyzed. Equipment performance 

characteristics were developed using performance curves based on existing equipment. 

Performance curves and model inputs are documented in appendix 7-A. 

Blower energy for the building model used the characteristics for blower motor and fan 

power efficiency discussed in section 7.7.2. However, the total fan static pressure was 1.45 in 

H20 based on the assumption used in the benchmark prototype, compared to 1.105 in H20 total 

static pressure used to characterize the equipment performance at rating conditions. 

Cooling equipment was sized based on ASHRAE 2.5 percent cooling design day sizing 

for all climates. A sizing run is done prior to the hourly simulations in EnergyPlus and is used to 

size all HVAC equipment. The design-day sizes are then used in the annual simulation runs. For 

the heat pumps, equipment sizing is based on cooling design-day and electric resistance heat is 

used to make up any remaining heating load. 

7.8 BASELINE COMMERCIAL ENERGY DISTRIBUTION 

To be of use in the CAC analysis, the baseline commercial CAC and CHP use developed 

for the 237 TMY locations must have relative weighting factors associated with each TMY 

location much as the residential analysis uses the representative RECS weights. DOE used 

population-based weighting factors developed for each TMY climate based on data from the 

2000 U.S. Census data to represent the importance of each climate in each state. The 

development and documentation of these weighting factors is found in Appendix 7-B. Because 

certain TMY locations represent climates that cover more than one state (e.g., for instance where 

the TMY location is on the border between two states), DOE originally developed weighting 

factors for a total of 543 TMY-State combinations. These weighting factors were then used in the 

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EERE-2008-BT-STD-0006 COMMENT 54
subsequent LCC analysis in addressing CAC and CHP energy use in commercial buildings. 

Seventeen Alaskan locations, which make up approximately 0.2 percent of the national weight, 

were however removed from the energy analysis due to issues with electrical price data. Figure 

7.8.1, Figure 7.8.2, and Figure 7.8.3 shows a distribution of commercial CAC cooling and CHP 

cooling and heating energy use in the nation which accounts for the relative weights attached to 

each of the remaining 526 TMY-State combinations. 

0%

10%

20%

30%

40%

50%

60%

70%

Percentage of Simulated 

Commercial Small Offices 

Baseline CAC Cooling Energy (kWh/yr) 

Figure 7.8.1. Baseline National Cooling Energy Distribution for CAC-Commercial, 

Weighted 

0%

10%

20%

30%

40%

50%

60%

70%

Percentage of Simulated 

Commercial Small Offices 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.8.2. Baseline National Cooling Energy Distribution for CHP-Commercial, 

Weighted 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

0%

10%

20%

30%

40%

50%

60%

Percentage of Simulated 

Commercial Small Offices 

Baseline CHP Cooling Energy (kWh/yr) 

Figure 7.8.3. Baseline National Heating Energy Distribution for CHP-Commercial, 

Weighted 

7.9	 COMMERCIAL ENERGY FOR INTERMEDIATE EFFICIENCY LEVELS 

Calculation of commercial annual cooling, and fan energy for intermediate efficiency 

levels not simulated was by linear interpolation between SEER levels simulated. Calculation of 

commercial heating energy use for heat pumps for intermediate levels not simulation was by 

interpolation between HSPF levels simulated. 

7.10	 MARKET BASELINE SPACE-COOLING AND SPACE-HEATING 

EFFICIENCIES 

The analysis results presented in this chapter up to this point presents the development of 

the baseline space-cooling and space-heating energy use for CAC and CHP equipment. Baseline 

in this discussion refers to the energy consumption if all equipment was brought to the current 

standard levels of SEER 13 and HSPF 7.7 for packaged and split system CAC and CHP product 

classes. Not all equipment is sold at the baseline efficiency levels. Much equipment exceeds the 

baseline level in the current market and is expected to continue to do so in the absence of new 

standards. In order to account for this within the LCC analysis discussed in the next chapter, 

DOE defined a base case efficiency distribution for 2016, also referred to as the market baseline. 

The market baseline efficiency distribution was defined to represent the range of efficiencies 

likely sold into the market in 2016 in the absence of new standards. The market baseline energy 

consumption is calculated as the energy estimated to be consumed by each individual entity (as 

characterized by RECS household observation or commercial building TMY-State combination) 

DOE estimated this energy use in the same manner as was used in estimating the baseline 

energy consumption. For RECS household records, DOE first randomly selected a 2016 

efficiency level from the market baseline distribution and then equations 7.3.1 and 7.4.1 were 

utilized to calculate the cooling and heating consumption for the RECS observations in the 2016 

base case, by replacing the baseline efficiency (cooling or heating) with the selected efficiency 

for each observation in the base case. For commercial TMY-State observations, DOE first 

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EERE-2008-BT-STD-0006 COMMENT 54
 

randomly selected a 2016 efficiency level from the market baseline distributions and calculated 

the correspond cooling fan, and heating energy use for that observation in 2016 by linear 

interpolation between the efficiency levels simulated in the commercial energy analysis. 

DOE did not have access to sales data describing the actual distribution of efficiencies in 

current sales, nor was such information provided by industry for this rulemaking. As a 

consequence, DOE developed estimates of the distribution of SEER levels for four classes of 

product: split system CAC, single package CAC, split system CHP, and single package CHP. 

The development of these distributions was based on the following key data inputs: 

From AHRI data, the average SEER of equipment sold in each product class in 2006 as 

well as the relative shipments by product class for the market as a whole. 

An industry trade press article which indicated approximate sales segmentation by SEER 

for the CAC/CHP industry in 2007.15 

AHRI Directory of Certified Product Performance16 which allowed review of specific 

efficiencies sold into the market for each product class. 

According to the trade press article, the distribution in 2007 had approximately 9 percent 

of sales at 14 SEER, 3 percent of sales at 15 SEER, 2 percent at 16 SEER, and 2 percent for 

17 SEER. The remainder of the product sales was assumed to fall below 14 SEER. 

According to AHRI data7, product sales in 2007 were as follows: 63.0 percent split CAC, 

5.9 percent single-package CAC, 27.6 percent split CHP, and 3.5 percent single-package CHP. 

Product sales in 2008 through September were as follows: 63.0 percent split CAC, 4.8 percent 

single-package CAC, 28.8 percent split CHP, and 3.4 percent single-package CHP. 

AHRI reported average shipped SEER by product class for 2007: split CAC, 13.72; 

single-package CAC, 12.83; split CHP 13.86, single-package CHP 13.16. DOE did not know if 

the average 12.83 for single-package CAC represented continued sales of pre-SEER 13 

equipment or if it included through the wall or other classes with lower efficiency. As this data 

were provided by AHRI for this rulemaking, it was assumed to be representative of single phase 

equipment only. AHRI reported average shipped SEER for 2008 as: split CAC, 13.77; singlepackage CAC, 13.17; split CHP 13.97, single-package CHP 13.39. 

DOE first created 16 SEER bins corresponding roughly to the SEER efficiency levels 

developed in the engineering analysis with those engineering levels serving as a representative 

efficiency for each bin. These bins are shown in Table 7.10.1. Then through an iterative process 

which took into account available efficiency levels in each product class, DOE developed an 

efficiency distribution for each product class which was consistent with the above data sources in 

that it provided average efficiency by split CAC, split CHP, and single-package CHP product 

class as reported by AHRI in 2007 as well as provided an overall distribution by SEER that 

corresponded with the industry trade press article cited above. Bins that included 14 and 15 

SEER were assumed to be uniformly distributed efficiencies above and below the characteristic 

efficiency in the bin. It was obviously not possible to develop a shipment-weighted efficiency 

below 13 SEER as was seen for single package CAC using this distribution. Instead DOE chose 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

to match the 2008 shipment weighted average value for this product class. The estimated 

distribution for all classes for 2007 is shown in Table 7.10.1. 

Table 7.10.1. CAC and CHP Efficiency Distributions Estimated for 2007 

SEER Bins SEER Distribution by Equipment Class Industry- Wide 

SEER 

Distribution 

(Four Classes) 

% 

Bottom of Bin Top of Bin Characteristic 

Efficiency in Bin Split 

CAC 

Single 

Package 

CAC 

% 

Split 

CHP% 

Single 

Package 

CHP 

% 

13 13.25 13 25.00 76.20 15.00 76.20 27.07 

13.25 13.75 13.5 56.00 18.80 57.00 18.80 52.77 

13.75 14.25 14 6.00 2.00 8.00 2.00 6.18 

14.25 14.75 14.5 2.50 2.00 7.50 2.00 3.83 

14.75 15.25 15 3.00 1.00 5.00 1.00 3.36 

15.25 15.75 15.5 2.00 0.00 2.00 0.00 1.81 

15.75 16.5 16 3.10 0.00 2.00 0.00 2.50 

16.5 17.5 17 1.00 0.00 1.50 0.00 1.04 

17.5 18.5 18 0.60 0.00 1.50 0.00 0.79 

18.5 19.5 19 0.30 0.00 0.50 0.00 0.33 

19.5 20.5 20 0.20 0.13 

20.5 21.5 21 0.20 0.13 

21.5 22.5 22 0.10 0.06 

22.5 23.5 23 

23.5 24.5 24 

24.5 25.5 25 

Wt. Average SEER 13.71 13.16 13.85 13.16 13.70 

13.66 13.78 

DOE was not able to develop a distribution using the same methodology for the 2008 

data that would be consistent with the industry trade press article overall distribution. DOE made 

slight changes to the relative shipment weights by efficiency bin from 2007 distribution, in order 

to match the higher average SEERs in 2008 while maintaining the general flavor of the 

distribution by product class. This overall 2008 distribution is shown in Table 7.10.2. DOE 

assumed that this distribution was representative of the market baseline distribution in 2016 and 

used it as such for the energy and subsequent LCC analysis. 

DOE did not have similar data on space heating efficiencies for CHP equipment. For 

analysis of the market baseline HSPF efficiencies, DOE used the HSPF values that corresponded 

to each CHP SEER level as identified in the engineering analysis. Because these engineering 

levels represented typical market averages based on the AHRI data, they were deemed sufficient 

for characterizing average market HSPF by SEER level and corresponding average CHP heating 

energy use in the market baseline. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

Table 7.10.2. CAC and CHP Efficiency Distributions Estimated for Market Baseline 

SEER Bins SEER Distribution by Equipment Class IndustryWide SEER 

Distribution 

(Four Classes) 

% 

Bottom of 

Bin 

SEER 

Top of Bin 

SEER 

Characteristic 

Efficiency in Bin 

SEER 

Split 

CAC 

% * 

SinglePackage 

CAC 

% 

Split 

CHP 

% 

SinglePackage 

CHP 

% 

13 13.25 13 24.00 75.00 13.00 50.00 24.18 

13.25 13.75 13.5 55.00 20.00 52.00 32.00 51.66 

13.75 14.25 14 4.00 2.00 10.00 11.00 5.87 

14.25 14.75 14.5 5.25 2.00 9.00 5.00 6.17 

14.75 15.25 15 3.25 1.00 5.50 2.00 3.75 

15.25 15.75 15.5 2.00 0.00 3.50 0.00 2.27 

15.75 16.5 16 3.50 0.00 3.00 0.00 3.07 

16.5 17.5 17 1.50 0.00 2.00 0.00 1.52 

17.5 18.5 18 0.70 0.00 1.50 0.00 0.87 

18.5 19.5 19 0.30 0.00 0.50 0.00 0.33 

19.5 20.5 20 0.20 0.13 

20.5 21.5 21 0.20 0.13 

21.5 22.5 22 0.10 0.06 

22.5 23.5 23 

23.5 24.5 24 

24.5 25.5 25 

Wt. Average SEER 13.77 13.17 13.97 13.39 13.78 

13.72 13.91 *

 A separate, coil-only split air conditioner distribution was created by truncating the split AC distribution shown at 

SEER bin 8 (16.5-17.5 bin) since the max tech level for this type of equipment was 16.5. The distribution was then 

normalized back to 100%. This distribution is shown in chapter 8, Life Cycle Cost and Payback Period Analysis. 

7.11	 ESTABLISHMENT OF GEOGRAPHIC REGIONS FOR STANDARDS 

ANALYSIS AND CORRESPONDING REGIONAL ENERGY CONSUMPTION 

BY EFFICIENCY LEVEL 

Under EPCA, regional efficiency standards for CAC may be defined for up to two 

regions consisting of contiguous groups of states. These regional standards are in addition to a 

base national standard efficiency that represents the minimum efficiency that a manufacturer 

could produce or that could be imported into the United States. In order to consider establishing 

regional standards, DOE needed to identify regions for which such standards might be 

applicable. For cooling equipment performance, the most important regional variations in 

climate are the annual number of operating hours, and the coincident relative humidity during 

those hours. For the CAC standard analysis, DOE is considering establishing two regions, hothumid and hot-dry, for the establishment of regional standards in addition to a national standard. 

In addition, DOE considered using two variants of the SEER rating to establish performance 

standards: the current SEER definition and a modified definition termed “SEER hot-dry” 

(SEERHD). The SEERHD would be calculated using revised temperature bin data and design 

sizing data as established for the defined hot-dry region. 

A national standard and a standard for the proposed hot-humid region may be established 

using SEER, although potentially at different SEER efficiencies based on the cooling load and 

other information characteristic to the nation and to the hot-humid region respectively. The 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

SEERHD rating would be developed to be more appropriate for hot and dry climates in certain 

western States where the average outdoor air temperature during cooling may be considerably 

higher than that seen in the remainder of the United States. Whether these regional standards are 

appropriate will be determined by the LCC and other analyses. For the purpose of DOE’s 

preliminary analysis, DOE established the two regions allowed under EPCA as shown in Table 

7.11.1. Region 1 refers to the hot-humid region. Region 2 refers to the hot-dry region. For the 

purpose of characterizing the geographic remainder of the nation, DOE uses a Region 0 

nomenclature. DOE notes that while analysis can be performed for Region 0, DOE does not have 

authority to set a regional standard for this geographic area. Rather, this area would be covered 

under the national standard. 

Table 7.11.1. Proposed Climate Regions for Regional Standards 

Hot-Humid 

(Region 1) 

Hot-Dry 

(Region 2) 

Rest-of-Country 

(Region 0) 

Alabama Arizona Alaska Nebraska 

Arkansas California Colorado New Hampshire 

Florida Nevada Connecticut New Jersey 

Georgia New Mexico Delaware New York 

Hawaii District of Columbia North Dakota 

Louisiana Idaho Ohio 

Mississippi Illinois Oregon 

North Carolina Indiana Pennsylvania 

Oklahoma Iowa Rhode Island 

South Carolina Kansas South Dakota 

Tennessee Kentucky Utah 

Texas Maine Vermont 

Maryland Virginia 

Massachusetts Washington 

Michigan West Virginia 

Minnesota Wisconsin 

Missouri Wyoming 

Montana 

For the purposes of the preliminary analysis for the CAC rulemaking, DOE did not 

develop energy consumption characteristics in conformance with the SEERHD rating as this 

rating was not used in the engineering analysis and no mapping between SEER and SEERHD had 

been developed. However, DOE did develop the energy and subsequent LCC analysis at both the 

national level and individually for the regions defined in Table 7.11.1. A complete discussion on 

the development of both the standard regions and the SEERHD parameter are discussed in 

Appendix 7-C. 

For each equipment class, DOE developed energy use statistics for the market baseline 

and for higher efficiency levels by using a Monte Carlo random selection process to select 

10,000 observations in each region and 10,000 for the nation as a whole. Ninety three percent of 

those observations were residential and 7 percent were commercial instances of the use of CAC 

(or CHP) equipment. Details for the selection process are found in chapter 8, LCC. However 

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Table 7.11.6 show the resultant baseline, market baseline, and higher efficiency annual energy 

statistics developed for each region for each equipment class analyzed. 

Table 7.11.2. Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level for Coil-Only Systems 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,407 0 3,564 0 2,176 0 1,378 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,291 0 3,393 0 2,071 0 1,310 0 

2 13.5 N/A 2,322 0 3,437 0 2,100 0 1,331 0 

3 14.0 N/A 2,243 0 3,318 0 2,029 0 1,287 0 

4 14.5 N/A 2,168 0 3,205 0 1,960 0 1,244 0 

5 15.0 N/A 2,097 0 3,100 0 1,897 0 1,204 0 

6 15.5 N/A 2,031 0 3,002 0 1,836 0 1,166 0 

7 16.0 N/A 1,968 0 2,909 0 1,780 0 1,130 0 

8 16.5 N/A 1,912 0 2,825 0 1,730 0 1,099 0 

* N/A means not applicable. 

Table 7.11.3. Split-System Air Conditioners: Average Annual Energy Use by Efficiency 

Level—Blower-Coil Systems 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,433 0 3,584 0 2,172 0 1,365 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,315 0 3,410 0 2,067 0 1,302 0 

2 13.5 N/A 2,347 0 3,455 0 2,096 0 1,319 0 

3 14.0 N/A 2,267 0 3,336 0 2,025 0 1,275 0 

4 14.5 N/A 2,190 0 3,223 0 1,957 0 1,233 0 

5 15.0 N/A 2,119 0 3,117 0 1,893 0 1,193 0 

6 15.5 N/A 2,052 0 3,018 0 1,833 0 1,155 0 

7 16.0 N/A 1,988 0 2,925 0 1,777 0 1,120 0 

8 16.5 N/A 1,932 0 2,840 0 1,727 0 1,089 0 

9 17.0 N/A 1,878 0 2,760 0 1,679 0 1,060 0 

10 18.0 N/A 1,780 0 2,613 0 1,592 0 1,007 0 

11 19.0 N/A 1,692 0 2,482 0 1,514 0 960 0 

12 20.0 N/A 1,613 0 2,363 0 1,444 0 917 0 

13 21.0 N/A 1,541 0 2,256 0 1,380 0 878 0 

14 22.0 N/A 1,476 0 2,158 0 1,322 0 842 0 

* N/A means not applicable. 

7-34 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 7.11.4. Split-System Heat Pumps: Average Annual Energy Use by Efficiency Level 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,487 1,749 4,275 1,275 4,203 924 1,978 2,968 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 

3,268 1,687 4,006 1,230 3,937 891 1,857 2,862 

2 13.5 7.85 3,363 1,716 4,122 1,251 4,053 906 1,909 2,912 

3 14.0 8.00 3,248 1,685 3,980 1,228 3,913 890 1,846 2,859 

4 14.5 8.15 3,138 1,654 3,845 1,206 3,780 873 1,784 2,808 

5 15.0 8.30 3,035 1,625 3,719 1,184 3,656 858 1,726 2,758 

6 15.5 8.45 2,939 1,597 3,601 1,163 3,539 843 1,671 2,711 

7 16.0 8.60 2,848 1,570 3,490 1,143 3,430 828 1,620 2,665 

8 17.0 9.10 2,688 1,485 3,293 1,081 3,235 783 1,531 2,522 

9 18.0 9.60 2,545 1,409 3,117 1,026 3,062 743 1,452 2,395 

10 19.0 10.10 2,417 1,341 2,959 976 2,907 706 1,381 2,279 

11 19.5 10.30 2358 1315 2886 957 2835 693 1,348 2,236 

Table 7.11.5. Single-Package Air Conditioners: Average Annual Energy Use by Efficiency 

Level 

Efficiency Level Annual Energy Consumption 

kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF* Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 N/A 2,376 0 3,602 0 2,170 0 1,363 0 

Market 

Baseline 

Market 

Baseline 

N/A 2,348 0 3,559 0 2,144 0 1,348 0 

2 13.5 N/A 2,292 0 3,473 0 2,093 0 1,316 0 

3 14.0 N/A 2,214 0 3,353 0 2,022 0 1,273 0 

4 14.5 N/A 2,139 0 3,239 0 1,954 0 1,230 0 

5 15.0 N/A 2,070 0 3,133 0 1,890 0 1,191 0 

6 15.5 N/A 2,004 0 3,033 0 1,831 0 1,153 0 

7 16.0 N/A 1,942 0 2,940 0 1,774 0 1,118 0 

8 16.6 N/A 1,876 0 2,838 0 1,714 0 1,081 0 

* N/A means not applicable. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

Table 7.11.6. Single-Package Heat Pumps: Average Annual Energy Use by Efficiency Level 

Efficiency Level Annual Energy Consumption

 kWh/yr 

National Hot-Humid Hot-Dry Rest of Country 

# SEER HSPF Cooling Heating Cooling Heating Cooling Heating Cooling Heating 

1 13.0 7.70 3,464 1,720 4,295 1,272 4,211 927 1,964 2,953 

Market 

Baseline 

Market 

Baseline 

Market 

Baseline 

3,372 1,698 4,179 1,256 4,098 915 1,914 2,916 

2 13.5 7.85 3,341 1,688 4,141 1,248 4,060 910 1,896 2,898 

3 14.0 8.00 3,227 1,657 3,999 1,225 3,920 893 1,833 2,845 

4 14.5 8.00 3,117 1,657 3,863 1,225 3,787 893 1,772 2,845 

5 15.0 8.00 3,015 1,657 3,737 1,225 3,663 893 1,714 2,845 

6 15.5 8.50 2,920 1,561 3,618 1,154 3,546 841 1,660 2,682 

7 16.0 9.00 2,829 1,476 3,506 1,091 3,436 795 1,609 2,538 

8 16.4 9.00 2,763 1,476 3,424 1,091 3,356 795 1,572 2,537 

7-36 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

REFERENCES
 

1. Residential Energy Consumption Survey: Quality Profile, DOE Publication No. DOE/EIA0555(96)/1 

2. NOAA, 2009. NNDC Climate Data Online. 

<www7.ncdc.noaa.gov/CDO/CDODivisionalSelect.jsp> (Assessed February, 2009) 

3. Missouri Census Data Center. U.S. Census Data Archive for 1980, 1990, 2000 U.S. Census 

Data http://mcdc2.missouri.edu/applications/uexplore.shtml#top and (Accessed February 

2009) 

4. AHRI 2008, Air Conditioning and Refrigeration Institute Statistical Profile, 2008. 

Efficiency data averaged by shipment weights across air conditioner, and for heat pump 

product classes. 

5. DOE, 2001. Central Air Conditioner Rulemaking SNOPR Technical Support Document, 

Chapter 5. Life Cycle Cost and Payback Analysis. 

<http://www1.eere.energy.gov/buildings/appliance_standards/residential/ac_central_1000_ 

r.html> (Accessed April, 2009) 

6. ARI, 2004. Directory of Certified Unitary Equipment Standards 210/240 270. ARI 2003 

V. 2.0. Arlington, Va. 

7. AHRI, 2008. Shipment Data and Efficiency data by CAC and CHP equipment class 

supplied to DOE for the current CAC rulemaking 

8. EIA 2003. Commercial Building Energy Consumption Survey (CBECS). U.S. Department 

of Energy Energy Information Administration. 

<http://www.eia.doe.gov/emeu/cbecs/cbecs2003> (Accessed May, 2009). 

9. DOE, 2008. Rulemaking Framework for Residential Central Air Conditioners and Heat 

Pumps. Accessed at 

http://www1.eere.energy.gov/buildings/appliance_standards/residential/pdfs/cac_framewor 

k.pdf 

10. DOE, 2008. EnergyPlus Energy Simulation Software V3.0. U.S. Department of Energy. 

Washington, D.C. Available at < http://apps1.eere.energy.gov/buildings/energyplus> 

11. DOE, 2008. DOE to Pursue Zero-Net Energy Commercial Buildings, Available at 

http://www1.eere.energy.gov/buildings/commercial_initiative/about.html 

12. DOE, 2009. Commercial Building Benchmark Models. 

http://www1.eere.energy.gov/buildings/commercial_initiative/benchmark_models.html 

13. NREL, 1995. Typical Meteorological Years Derived from the 1961-1990 National Solar 

Radiation Database. National Renewable Energy Laboratory. Golden, CO. 

7-37 

EERE-2008-BT-STD-0006 COMMENT 54
 

14. Wassmer M and MJ Brandemuehl. 2006. Effect of Data Availability on Modeling of 

Residential Air Conditioners and Heat Pumps for Energy Calculations. ASHRAE 

Transactions 111(1), pp. 214-225. 

15. ACH&R News, 2007. “Higher SEERs Got Popular”, December 2007. Accessed March 

2009 at http://www.achrnews.com/Articles/Web_Exclusive/BNP_GUID_9-5­

2006_A_10000000000000222513 

16. AHRI, 2009. Directory of Certified Product Performance. Available at 

<http://www.ahridirectory.org/ahridirectory/pages/home.aspx>. Accessed March, 2009. 

7-38 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

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 Analyses ............... 8-1 

8.1.2 Overview of Life-Cycle Cost and Payback Period Analyses Inputs ................... 8-2 

8.1.3 Analysis Use of Residential Energy Consumption Survey (RECS) in LCC and 

PBP ...................................................................................................................... 8-6 

8.1.4 Commercial Building Analysis............................................................................ 8-7 

8.2 LIFE-CYCLE COST ANALYSIS INPUTS ....................................................................... 8-9 

8.2.1 Definition ............................................................................................................. 8-9 

8.2.2 Total Installed Cost Inputs ................................................................................. 8-10 

8.2.3 Operating Cost Inputs ........................................................................................ 8-25 

8.3 PAYBACK PERIOD INPUTS ......................................................................................... 8-54 

8.3.1 Definition ........................................................................................................... 8-54 

8.3.2 Inputs.................................................................................................................. 8-54 

8.4 SEER AND HSPF RESULTS .......................................................................................... 8-55 

8.4.1 Split-system Air Conditioners............................................................................ 8-56 

8.4.2 Split-System Heat Pumps .................................................................................. 8-68 

8.4.3 Single Package Air Conditioners ....................................................................... 8-74 

8.4.4 Single Package Heat Pumps............................................................................... 8-80 

8.5 OFF-MODE AND STANDBY POWER CONSUMPTION............................................ 8-86 

REFERENCES .......................................................................................................................... 8-88 

LIST OF TABLES 

Table 8.1.1 Summary of Inputs and Key Assumptions used in the LCC and PBP 

Analyses............................................................................................................... 8-4 

Table 8.2.1 Representative CAC Products Evaluated for the Life-Cycle Cost and 

Payback Analyses .............................................................................................. 8-11 

Table 8.2.2 Baseline Manufacturer Selling Prices per Unit.................................................. 8-11 

Table 8.2.3 SEER Standard-Compliant Manufacturer Selling Prices per Unit .................... 8-12 

Table 8.2.4 Shipping Weights of SEER Standard-compliant Products ................................ 8-13 

Table 8.2.5 MSP Including Transportation of SEER Standard-compliant Products ............ 8-14 

Table 8.2.6 Overall National Average Baseline Markup Factors by Product Type ............. 8-15 

Table 8.2.7 Overall National Incremental Markup Factors by Product Type....................... 8-15 

Table 8.2.8 Installation Costs for Baseline CAC Products (SEER 13)................................. 8-16 

Table 8.2.9 Installation Cost Indices (National Average Value = 100.0)............................. 8-17 

Table 8.2.10 Costs and Markups for Determination of Weighted-Average Total 

Installed Costs for a New 3-Ton Split-system AC Coil-Only Unit 

(Efficiency Level 5: SEER 15............................................................................ 8-17 

Table 8.2.11 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system AC (Coilonly), at Average Prices*................................................................................... 8-19 

8-i 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 8.2.12 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system AC (BlowerCoil), at Average Prices* ................................................................................... 8-20 

Table 8.2.13 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system HP, at 

Average Prices* ................................................................................................. 8-22 

Table 8.2.14 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Single Package AC, at 

Average Prices* ................................................................................................. 8-23 

Table 8.2.15 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Single Package HP, at 

Average Prices * ................................................................................................ 8-24 

Table 8.2.16 Regional Averages of the Annual Average Prices and January and July
 

Marginal Prices .................................................................................................. 8-28 

Table 8.2.17 Effective Marginal Price by Region for the Commercial Building Sample 

(¢/kWh). ............................................................................................................. 8-29 

Table 8.2.18 Central Air Conditioner and Heat Pump Basic Average Repair Costs by
 

Efficiency Level................................................................................................. 8-33 

Table 8.2.19 Central Air Conditioner and Heat Pump Average Repair Costs by
 

Efficiency Level and Region ............................................................................. 8-33 

Table 8.2.20 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs 

by Efficiency Level............................................................................................ 8-36 

Table 8.2.21 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs 

by Efficiency Level............................................................................................ 8-37 

Table 8.2.22 Central Air Conditioners: Comparison of RECS and AHS with Modeled 

Stock .................................................................................................................. 8-42 

Table 8.2.23 Heat Pumps: Comparison of RECS and AHS Stock to Stock Calculated 

from a Weibull Survival Function ..................................................................... 8-45 

Table 8.2.24 Types of Household Debt and Equity by Percentage Shares............................. 8-48 

Table 8.2.25 Average Nominal Interest Rates for Household Debt ....................................... 8-48 

Table 8.2.26 Average Real Effective Interest Rates for Household Debt .............................. 8-49 

Table 8.2.27 Average Nominal and Real Interest Rates for Household Equity ..................... 8-49 

Table 8.2.28 Average Interest on Household Debt and Equity .............................................. 8-50 

Table 8.2.29 Data Used to Calculate Real Effective Mortgage Rates .................................... 8-51 

Table 8.2.30 2008 Market Distribution of Efficiency Levels by Product Class ..................... 8-53 

Table 8.4.1 Mean Market Baseline Installed Costs, Total Annual Energy
 

Consumption, and Percentage Change for Split-System Air Conditioners 

(Coil-Only) by Region by Efficiency Level (SEER Value) .............................. 8-56 

Table 8.4.2 Mean Market Baseline Installed Costs, Total Annual Energy
 

Consumption, and Percentage Change for Split-System Air Conditioners 

(Blower-Coil) by Region by Efficiency Level (SEER Value)........................... 8-56 

Table 8.4.3 Mean LCC Savings for Split-System Air Conditioners (Coil-only) by
 

Region by Efficiency Level (SEER Value) ....................................................... 8-58 

Table 8.4.4 Mean LCC Savings for Split-System Air Conditioners (Blower-Coil) by
 

Region by Efficiency Level (SEER Value) ....................................................... 8-59 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.4.5 Mean Payback Period for Split-System Air Conditioners (Coil-Only) by 

Region ................................................................................................................ 8-61 

Table 8.4.6 Mean Payback Period for Split-system Air Conditioners (Blower-Coil) by
 

Region ................................................................................................................ 8-61 

Table 8.4.7 Mean Rebuttable Payback Period for Split-System Air Conditioners (CoilOnly) by Region................................................................................................. 8-62 

Table 8.4.8 Mean Rebuttable Payback Period for Split-system Air Conditioners 

(Blower-Coil) by Region ................................................................................... 8-62 

Table 8.4.9 National LCC and PBP Results for Split-System Air Conditioners (CoilOnly) by Efficiency Level (SEER Value): Nation ............................................ 8-64 

Table 8.4.10 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by
 

Efficiency Level (SEER Value): Nation............................................................ 8-64 

Table 8.4.11 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by
 

Efficiency Level (SEER Value): Hot-Humid Region ........................................ 8-65 

Table 8.4.12 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by
 

Efficiency Level (SEER Value): Hot-Humid Region ........................................ 8-65 

Table 8.4.13 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by
 

Efficiency Level (SEER Value): Hot-Dry Region............................................. 8-66 

Table 8.4.14 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by
 

Efficiency Level (SEER Value): Hot-Dry Region............................................. 8-66 

Table 8.4.15 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by
 

Efficiency Level (SEER Value): Rest of Country ............................................. 8-67 

Table 8.4.16 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by
 

Efficiency Level (SEER Value): Rest of Country ............................................. 8-67 

Table 8.4.17 Mean Market Baseline Installed Costs, Total Annual Energy
 

Consumption, and Percentage Change for Split-System Heat Pumps by 

Region by Efficiency Level (SEER Value) ....................................................... 8-68 

Table 8.4.18 Mean LCC Savings for Split-System Heat Pumps by Region by Efficiency
 

Level (SEER Value and HSPF Value)............................................................... 8-69 

Table 8.4.19 Mean Payback Period for Split-System Heat Pumps by Region (Years) .......... 8-71 

Table 8.4.20 Mean Rebuttable Payback Period for Split-System Heat Pumps by Region 

(Years)................................................................................................................ 8-71 

Table 8.4.21 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Nation........................................................................................ 8-72 

Table 8.4.22 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Hot-Humid Region ................................................................... 8-73 

Table 8.4.23 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Hot-Dry Region ........................................................................ 8-73 

Table 8.4.24 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Rest of Country......................................................................... 8-74 

Table 8.4.25 Mean Market Baseline Installed Costs, Total Annual Energy
 

Consumption, and Percentage Change for Single Package Air 

Conditioners by Region by Efficiency Level (SEER Value)............................. 8-75 

Table 8.4.26 Mean LCC Savings for Single Package Air Conditioners by Region by
 

Efficiency Level (SEER Value)......................................................................... 8-76 

Table 8.4.27 Mean Payback Period for Single Package Air Conditioners by Region............ 8-77 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.4.28 Mean Rebuttable Payback Period for Single Package Air Conditioners by 

Region ................................................................................................................ 8-78 

Table 8.4.29 LCC and PBP Results for Single Package Air Conditioners by Efficiency
 

Level (SEER Value): Nation ............................................................................. 8-79 

Table 8.4.30 LCC and PBP Results for Single Package Air Conditioners by Efficiency
 

Level (SEER Value): Hot-Humid Region ......................................................... 8-79 

Table 8.4.31 LCC and PBP Results for Single Package Air Conditioners by Efficiency
 

Level (SEER Value): Hot-Dry Region .............................................................. 8-79 

Table 8.4.32 LCC and PBP Results for Single Package Air Conditioners by Efficiency
 

Level (SEER Value): Rest of Country............................................................... 8-80 

Table 8.4.33 Mean Market Baseline Installed Costs, Total Annual Energy
 

Consumption, and Percentage Change for Single Package Heat Pumps by 

Region by Efficiency Level (SEER Value) ....................................................... 8-81 

Table 8.4.34 Mean LCC Savings for Single Package Heat Pumps by Region by
 

Efficiency Level (SEER Value)......................................................................... 8-82 

Table 8.4.35 Mean Payback Period for Single Package Heat Pumps by Region (Years) ...... 8-84 

Table 8.4.36 Mean Rebuttable Payback Period for Single Package Heat Pumps by
 

Region (Years)................................................................................................... 8-84 

Table 8.4.37 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Nation........................................................................................ 8-85 

Table 8.4.38 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Hot-Humid Region ................................................................... 8-85 

Table 8.4.39 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Hot-Dry Region ........................................................................ 8-86 

Table 8.4.40 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Rest of Country......................................................................... 8-86 

Table 8.5.1 Details of Regional LCC and Payback Period for Off-Mode Power 

Consumption Measure: Crank Case Heaters (National Only)........................... 8-87 

8-iv 

EERE-2008-BT-STD-0006 COMMENT 54
LIST OF FIGURES
 

Figure 8.1.1 Flow Diagram of Inputs for the Determination of LCC and PBP ....................... 8-4 

Figure 8.2.1 Electricity Price Trends for Residential Rates to 2047 ...................................... 8-31 

Figure 8.2.2 Electricity Price Trends for Commercial Rates to 2047 .................................... 8-31 

Figure 8.2.3 Comparison of DOE Modeled Air Conditioner Age Distribution with 

RECS Reported Stock........................................................................................ 8-43 

Figure 8.2.4 Comparison of DOE Modeled Total Air Conditioner Stock with Adjusted 

AHS Stock ......................................................................................................... 8-43 

Figure 8.2.5 Central AC Survival Function, Characterized by Weibull Parameters α = 

20.29, β = 1.89, and θ = 1.0. .............................................................................. 8-44 

Figure 8.2.6 Comparison of DOE Modeled Total Heat Pump Stock with Adjusted AHS 

Stock .................................................................................................................. 8-46 

Figure 8.2.7 Heat Pump Survival Function, Characterized by Weibull Parameters α = 

17.04, β = 1.64, and θ = 1.0. .............................................................................. 8-46 

Figure 8.4.1 Market Baseline Distributions of LCC for Split-System Air Conditioners 

(Coil-Only) by Region ....................................................................................... 8-57 

Figure 8.4.2 Market Baseline Distributions of LCC for Split-System Air Conditioners 

(Blower-Coil) by Region ................................................................................... 8-58 

Figure 8.4.3 Plots of the Distributions of LCC Savings for Split-System Air 

Conditioners (Coil-Only) by Region ................................................................. 8-60 

Figure 8.4.4 Plots of the Distributions of LCC Savings for Split-system Air 

Conditioners (Blower-Coil) by Region.............................................................. 8-60 

Figure 8.4.5 Plots of the Distributions of PBP for Split-system Air Conditioners (CoilOnly) by Region................................................................................................. 8-63 

Figure 8.4.6 Plots of the Distributions of PBP for Split-system Air Conditioners 

(Blower-Coil) by Region ................................................................................... 8-63 

Figure 8.4.7 Market Baseline Distributions of LCC for Split-System Heat Pumps by
 

Region ................................................................................................................ 8-69 

Figure 8.4.8 Plots of the Distributions of LCC Savings for Split-system Heat Pumps by
 

Region ................................................................................................................ 8-70 

Figure 8.4.9 Plots of the Distributions of PBP for Split-System Heat Pumps by Region...... 8-72 

Figure 8.4.10 Market Baseline Distributions of LCC for Single Package Air 

Conditioners by Region ..................................................................................... 8-76 

Figure 8.4.11 Plots of the Distributions of LCC Savings for Single Package Air 

Conditioners by Region ..................................................................................... 8-77 

Figure 8.4.12 Plots of the Distributions of PBP for Single Package Air Conditioners by
 

Region ................................................................................................................ 8-78 

Figure 8.4.13 Market Baseline Distributions of LCC for Single Package Heat Pumps by
 

Region ................................................................................................................ 8-82 

Figure 8.4.14 Plots of the Distributions of LCC Savings for Single Package Heat Pumps 

by Region........................................................................................................... 8-83 

Figure 8.4.15 Plots of the Distributions of PBP for Single Package Heat Pumps by
 

Region ................................................................................................................ 8-84 

8-v 

EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 8. LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS 

8.1 INTRODUCTION 

The effect of amended standards on individual customers usually includes a reduction in 

operating cost and an increase in purchase cost. This chapter describes two metrics used in the 

analysis to determine the economic impact of standards on individual commercial customers: 

•	 Life-cycle cost (LCC) is the total customer cost over the life of an appliance or product, 

including purchase costs and operating costs (which in turn include maintenance, repair, 

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

summed over the lifetime of the appliance or product. 

•	 Payback period (PBP) measures the amount of time it takes customers to recover the 

assumed higher purchase price of more energy-efficient product through reduced 

operating costs. 

DOE conducted the LCC and PBP analysis using a spreadsheet model developed in 

Microsoft Excel. When combined with Crystal Ball (a commercially available software 

program), the LCC and PBP model generates a Monte Carlo simulation to perform the analysis 

by incorporating uncertainty and variability considerations in certain of the key parameters as 

discussed below. 

Inputs to the LCC and PBP analyses of central air conditioning (CAC) and central heat 

pump (CHP) products are discussed in sections 8.2 and 8.3 respectively. Results for each metric 

are presented in section 8.4. Key variables and calculations are presented for each metric. The 

calculations discussed here were performed with a series of Microsoft Excel spreadsheets which 

are accessible over the Internet 

(http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp.html). 

Details of, and instructions for, using the spreadsheets are discussed in appendix A. A 

more complete set of results of the analyses are presented in appendix F. 

8.1.1 General Approach for Life-Cycle Cost and Payback Period Analyses 

In recognition that each building where air conditioners or heat pumps are used is unique, 

variability and uncertainty is analyzed by performing the LCC and PBP calculations detailed 

here for a representative sample of individual households and commercial buildings. The 

analysis takes into account product use in commercial buildings based on the assumption that 

seven percent of product applications are in commercial buildings. The results are expressed as 

the number of buildings experiencing economic impacts of different magnitudes. The LCC and 

PBP model was developed using Microsoft Excel spreadsheets combined with Crystal Ball (a 

commercially available add-in). The LCC and PBP analyses explicitly model both the 

uncertainty and the variability in the model’s inputs using Monte Carlo simulation and 

probability distributions. 

The LCC analysis used the estimated energy use for each CAC unit as described in the 

energy use characterization analysis in Chapter 7 of the TSD. Energy use of CACs is sensitive to 

climate, so it varies by location within the United States. An important feature of the LCC and 

8-1 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

PBP analysis is that it has been conducted at both the regional and national level. Aside from 

energy use, other important factors influencing the LCC and PBP analyses include energy prices, 

installation costs, product distribution markups, and sales tax. At both the National and the 

regional level, the LCC spreadsheets explicitly modeled both the uncertainty and the variability 

in the model’s inputs, using probability distributions based on the shipment of CAC product to 

different regions of the country. 

As mentioned above, DOE generated LCC and PBP results as probability distributions 

using a simulation based on Monte Carlo analysis methods, in which certain key inputs to the 

analysis consist of probability distributions rather than single-point values. Therefore, the 

outcomes of the Monte Carlo analysis can also be expressed as probability distributions. As a 

result, the Monte Carlo analysis produces a range of LCC and PBP results. A distinct advantage 

of this type of approach is that DOE can identify the percentage of customers achieving LCC 

savings or attaining certain PBP values due to an increased efficiency level, in addition to the 

average LCC savings or average PBP for that efficiency level. 

The LCC and PBP results are displayed as distributions of impacts compared to a market 

baseline. As described in Chapter 7, the market baseline efficiency level is for 2016 is defined as 

a mix of CAC efficiency levels reflecting the current distribution of efficiency levels purchased 

by product class. Results are presented at the end of this chapter. A variety of graphic displays 

can be created to illustrate the implications of the analysis. Examples of graphic displays are 

(1) a cumulative probability distribution showing the percentage of CAC product in U.S. 

residential and commercial buildings that would experience a net LCC savings, and (2) a 

cumulative frequency chart depicting variation in PBP for each CAC efficiency level considered. 

All analyses were performed under the assumption that the current R-22 refrigerant 

would have been displaced by an alternative refrigerant in 2010 due to provisions in the Clean 

Air Act. The analysis methodology and results presented in this chapter assume that all CAC 

and CHP products manufactured after 2010 will use R-410A. 

8.1.2 Overview of Life-Cycle Cost and Payback Period Analyses Inputs 

The LCC is the total customer cost over the life of the product, including purchase price 

(including retail markups, sales taxes, and installation costs), and operating cost (including repair 

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

purchase and summed over the lifetime of the product. The PBP is the increase in purchase cost 

of higher efficiency product divided by the change in annual operating cost (as a result of lower 

energy consumption) of the product. It represents the number of years that it will take the 

customer to recover the increased purchase cost through decreased operating costs. In the 

calculation of PBP, future costs are not discounted. 

Inputs to the LCC and PBP analyses are categorized as follows: (1) inputs for 

establishing the purchase cost, otherwise known as the total installed cost, and (2) inputs for 

calculating the operating cost (i.e., energy, maintenance, and repair costs). 

The primary inputs for establishing the total installed cost are: 

8-2 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

•	 Baseline manufacturer selling price: The baseline manufacturer selling price (MSP) is 

the price charged by the manufacturer to either a wholesaler or customer for product 

meeting existing minimum efficiency (or baseline) standards. The manufacturer selling 

price includes a markup that converts the cost of production (i.e., the manufacturer cost) 

to a manufacturer selling price. 

•	 Standard-level manufacturer selling price increase: The standard-level MSP is the 

incremental change in MSP associated with producing product at each of the higher 

standard levels. 

•	 Markups and sales tax: Markups and sales tax are the wholesaler and contractor margins 

and state and local retail sales taxes associated with converting the MSP to a customer 

price. The markups and sales tax are described in detail in Chapter 6, Markups for 

Product Price Determination. 

•	 Installation cost: Installation cost is the cost to the customer of installing the product. 

The installation cost represents all costs required to install the CAC product but does not 

include the marked-up customer product price. The installation cost includes labor, 

overhead, and any miscellaneous materials and parts. Thus, the total installed cost equals 

the customer product price plus the installation price. 

The primary inputs for calculating the operating cost are: 

•	 Product energy consumption: The product energy consumption is the site energy use 

associated with the use of the CAC units to provide space-conditioning to the building. 

Chapter 7, Building Energy Use Characterization, provides complete details on CAC 

energy use simulations and their results. 

•	 Energy Prices: Electricity prices used in the analysis are the price per kilowatt-hour in 

cents or dollars ($/kWh) paid by each customer for electricity. Electricity prices are 

determined using marginal residential and commercial prices calculated from electrical 

tariff information on individual service areas, as determined from utility data on 90 

utilities, in 2008 dollars1

. 

•	 Electricity, natural gas, and fuel oil price trends: The EIA’s April 2009 update to the 

Annual Energy Outlook 2009 (AEO 2009) is used to forecast electricity prices into the 

future2

. 

•	 For the results presented in this chapter, DOE used the April 2009 update to the AEO 

2009 reference case to forecast future electricity prices. 

•	 Maintenance costs: The labor and material costs associated with maintaining the 

operation of the product (e.g., cleaning heat exchanger coils and drain pans, changing air 

filters, etc.). 

•	 Repair costs: The labor and material costs associated with repairing or replacing 

components that have failed. 

•	 Lifetime: The age at which the CAC product is retired from service. 

•	 Discount rate: The rate at which future costs are discounted to establish their present 

value. Figure 8.1.1 graphically depicts the relationships between the installed cost and 

operating cost inputs for the calculation of the LCC and PBP. 

8-3 

EERE-2008-BT-STD-0006 COMMENT 54
Manufacturer Sales 

Price Standard i 1...n

Manufacturer Sales 

Price Standard i= 1...n

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

Wholesaler/ 

Distributor Markup

Electricity Prices

Equipment Prices

Sales Tax

Manufacturer Selling 

Price (Base)

Installation Costs

Manufacturer Selling 

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

Manufacturer Sales 

Price Standard i 1...n

Manufacturer Sales 

Price Standard i= 1...n

Installation Costs Installation Costs

Repair Costs Repair Costs Lifetimes Lifetimes

Annual Maintenance

Electricity 

Consumption onsumption

Manufacturer Base 

Price

anufacturer Base 

ice

 

Annual Maintenance

 

 

 

=

 –

=

 -

= 

Electricity 

C 

Total Installed Cost 

(Std i –Base) 

M 

Pr 

Contractor Markups 

Wholesaler/ 

Distributor Markup 

Electricity Prices 

Equipment Prices 

Sales Tax 

Manufacturer Selling 

Price (Base) 

Installation Costs 

Manufacturer Selling 

Price Standard i= 1...n 

Electricity 

Consumption Annual Energy Costs 

Repair Costs 

Annual Operating 

Cost (Std i - Base) 

Payback 

Period 

Discount Rate 

Lifetimes 

Lifetime 

Operating 

Cost (Std 

i – Base) 

Lifecycle 

Cost 

Annual Maintenance 

Costs 

Figure 8.1.1 Flow Diagram of Inputs for the Determination of LCC and PBP 

Table 8.1.1 provides descriptions for the various inputs to the calculation of the LCC and 

PBP. As noted earlier, most of the inputs are characterized by probability distributions that 

capture variability in the input variables. 

Table 8.1.1 Summary of Inputs and Key Assumptions used in the LCC and PBP 

Analyses 

Inputs Description 

Affecting Installed Costs 

Product Price 

Derived by multiplying MSP for 3-ton capacity units (from the engineering 

analysis) by wholesaler markups and contractor markups plus sales tax (from 

markups analysis). Used the probability distribution for the different 

markups to describe their variability. 

Installation Cost 

Includes installation labor derived from RS Means CostWorks 2009 and RS 

Means Residential Cost Data 2009. Overhead and materials costs and 

profits are assumed to be included in the contractor’s markup. Thus, the 

total installed cost equals the consumer product price (manufacturer 

cost multiplied by the various markups plus sales tax) plus the 

installation cost. 

Transportation Cost 

Shipping cost of units based on weight of the unit, average shipment distance 

of 1100 miles, and an average cost of $0.20 per pound based on that distance 

and a range of rates from the FreightCenter.com website. 

Affecting Operating Costs 

Annual Energy Use 

For central air conditioners, the annual energy consumption is the 

annual site energy use associated with providing space-cooling. For 

heat pumps, the annual energy consumption is the annual site energy 

8-4 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

use associated with providing both space-cooling and space-heating. 

For households, the annual energy consumption is based on data from 

the EIA 2005 Residential Energy Consumption Survey (RECS). For 

those households surveyed in RECS with either a central air 

conditioner or heat pump, the estimated annual energy consumption 

corresponds to the household’s air conditioner or heat pump, 

specifically its capacity and efficiency. For products used in 

commercial buildings, the annual energy consumption is determined 

through computer simulations of a representative small commercial 

building based DOE commercial small-office benchmark building 

developed for use as a baseline benchmark for DOE’s Net Zero 

Commercial Building Initiative3 . 

Energy Efficiency 

The seasonal energy efficiency ratio (SEER) is the efficiency 

descriptor for central air conditioners. For heat pumps, the cooling 

efficiency is represented with the SEER while the heating efficiency is 

represented with the heating seasonal performance factor (HSPF). 

Central air conditioner and heat pump efficiencies in existing 

households are primarily based on data from the 2005 RECS. For 

product used in commercial buildings, all buildings were assumed to 

have product efficiencies equal to existing minimum efficiency 

standards (SEER 13). To estimate the annual energy consumption 

associated with a particular standard-level, the ratio of the building’s 

stock efficiency to the standard-level efficiency is multiplied by the 

building’s annual energy consumption. 

Table 8.1.1 (contd) 

Inputs Description 

Energy Prices 

For residential customers, calculated for RECS 2005 households from 

marginal and average electricity price in each utility service area in each 

region, as determined from utility tariff data for 2008, escalated by the 

AEO2009 forecasts to estimate the future electricity prices. For commercial 

customers, the analysis used commercial marginal and average electricity 

price in each utility service area in each region, as determined for 2004, 

escalated to 2008 prices using data from Edison Electric Institute and 

Regulatory Research Associates. 

Maintenance Cost 

The cost associated with maintaining the operation of the product 

(e.g., cleaning heat exchanger coils, checking refrigerant charge 

levels). Costs were chosen from an array of services from a variety of 

published sources. Annual maintenance cost increased as a function of 

MSP. 

Repair Cost 

Estimated the annualized repair cost for baseline efficiency CAC product, 

based on costs of major repair (compressor replacement), from a variety of 

published sources. It is assumed that repair costs would vary in direct 

proportion with the MSP at higher efficiency levels because it generally 

costs more to replace components that are more efficient. 

Affecting Present Value of Annual Operating Cost Savings 

Product Lifetime Used the probability distribution of lifetimes, with mean lifetime for each of 

four product classes assumed to be 19 years for air conditioning units and 

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EERE-2008-BT-STD-0006 COMMENT 54
16.3 years for heat pumps based on literature reviews and consultation with 

industry experts. 

Discount Rate 

Mean real discount rates ranging from 0 percent to 10.7 percent for various 

classes of residential customers based on Federal Reserve Board’s Survey 

of Consumer Finances. Commercial sector customers are expected to have 

a mean real discount rate of 7.4 percent based on a sample of 1750 

companies on the Damodaran Online website. Probability distributions are 

assumed for the discount rates of both groups of customers. 

Date Standards Become 

Effective June 30, 2016 (five years after the publication of the final rule) 

Analyzed Efficiency Levels 

Analyzed Efficiency 

Levels 

Baseline efficiency levels will follow the estimated market distribution of 

efficiency levels in 2016 based on a minimum SEER of 13 for new units and 

from seven to fifteen higher efficiency levels available in four principal 

product classes. 

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	 Analysis Use of Residential Energy Consumption Survey (RECS) in LCC and 

PBP 

The LCC and PBP calculations detailed here are for a representative sample of individual 

households and commercial buildings. Ninety-three percent of product applications are assumed 

to be in residential buildings (households)4

. 

For products used in households, the 2005 Residential Energy Consumption Survey 

(RECS)1 serves as the basis for determining the representative sample. The 2005 RECS is based 

on a sample of 4382 households which were surveyed for information on their housing units, 

energy consumption and expenditures, stock of energy-consuming appliances, and energyrelated behavior. Information was also collected on certain demographic and economic 

characteristics of household members. 

The information collected represents all households nationwide – approximately 111 

million. RECS is conducted every three years with data collected directly from energy end users. 

The 2005 RECS is the twelfth survey of residential housing units conducted by the U.S 

Department of Energy’s (DOE) Energy Information Administration (EIA). Previous RECS were 

conducted annually from 1978 to 1982 and triennially since 1984. The RECS consists of three 

parts: 

•	 Personal interviews with households for information about energy used, how it is used, 

energy-using appliances, structural features, energy efficiency measures, and 

demographic characteristics of the household. 

•	 Telephone interviews with rental agents for households that have any of their energy use 

included in their rent. This information augments information collected from those 

households that may not be knowledgeable about the fuels used for space heating or 

water heating. 

8-6 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

•	 Mail questionnaires sent to energy suppliers (after obtaining permission from households) 

to collect the actual billing data on energy consumption and expenditures. 

Of the 4,382 households surveyed in the 2005 RECS, 1,854 households representing 

25.1% of the housing population have a central air conditioner while 339 households 

representing 7.7% of housing population have an electric heat pumpa. Using the households in 

RECS that utilize a central air conditioner or heat pump, LCC and PBP analyses are performed 

on a household-by-household basis to determine whether an increase in the minimum efficiency 

standard is economically justified. Each RECS household is identified to be within one of the 

three geographic regions discussed previously in chapter 7 and has a associated household 

weight representing the number of similar households in the nation.. 

Of the inputs necessary for the LCC and PBP analysis, there are four inputs (as depicted 

in Figure 8.1.1) which are based on data from the 2005 RECS; 1) space-conditioning annual 

energy consumption (RECS-based), 2) product efficiency, 3) average electricity price, and 

4) marginal electricity price. All four of these inputs are used in determining the operating cost. 

With the exception of the product efficiency, each household in RECS with a central air 

conditioner or heat pump has a unique value for the space-conditioning annual energy 

consumption, the average electricity price, and the marginal electricity price. In other words, the 

annual energy consumption, average electricity price, and marginal electricity price associated 

with a particular RECS household are not uncertain and are, therefore, not expressed with 

probability distributions. Although the above three input variables are not uncertain, they are 

extremely variable. Due to the large number of households considered in the LCC and PBP 

analysis (over 1850 for central air conditioners and over 300 for heat pumps), the range of annual 

energy use, average electricity price, and marginal electricity price is quite large (the actual 

ranges are presented and discussed later in this chapter). Thus, although the above three input 

variables are not uncertain for any particular household, their variability across all households 

contributes significantly to the range of LCCs and PBPs calculated for any particular standard 

level. 

8.1.4 Commercial Building Analysis 

Seven percent of residential-type (i.e., single-phase) central air conditioner and heat 

pump applications are assumed to be in commercial buildings. A small commercial office 

building was simulated at 237 different locations around the country corresponding to the 

Typical Meteorological Year-2 weather stations)5

 was used to represent commercial applications 

for CAC and CHP units. The results from these simulations were used for the LCC and PBP 

analysis of commercial buildings, allowing for a building-by-building approach to be utilized for 

determining whether an increase in the standard is economically justified (e.g., similar to the 

approach described above for households from the 2005 RECS). DOE used population 

weighting factors to represent the importance of each climate in each state, and in each of the 

a

 The number of households actually used in the central air conditioner and heat pump LCC and PBP analyses were 

1,854 and 339, respectively. A small number of central air-conditioned households were dropped from the analysis 

for one or more of the following reasons: 1) the central air conditioner was not used, 2) a room air conditioner was 

present and used, or 3) marginal energy prices could not be determined for the household. With regard to households 

with heat pumps, they were dropped from the analysis for one or more of the following reasons: 1) the heat pump 

was not used or 2) marginal energy prices could not be determined for the household. 

8-7 

EERE-2008-BT-STD-0006 COMMENT 54
three regions. These weighting factors, in conjunction with the relative weighting between 

commercial and residential shipments were used to incorporate the commercial building energy 

consumption into the overall energy consumption for CAC and CHP equipment at each 

efficiency level. Seventeen locations in Alaska, representing less than 0.2 percent of the national 

population, were eventually removed from the LCC analysis due to lack of data for electrical 

pricing and uncertainty about commercial use in these climates. 

As with the analysis of residential buildings, four inputs are necessary (as depicted in 

Figure 8.1.1) from the commercial building analysis in order to perform the LCC and PBP 

calculations: 1) space-conditioning annual energy consumption, 2) product efficiency, 3) average 

electricity price, and 4) marginal electricity price. The space-conditioning energy consumption 

associated with the commercial building in each of the full set of 237 locations simulated were 

determined through computer modeling performed at Pacific Northwest National Laboratory 

(PNNL) using the Energy Plus simulation tool. The procedure for calculating space-conditioning 

energy consumption relied on the determination of hourly operating loads for each of the 237 

buildings. 

DOE performed an analysis in which DOE used the Energy Plus building energy 

simulation software to simulate the energy consumption of CAC and CHP used to satisfy the 

cooling, supply fan, and in the case of CHP, the electrical heating energy required in a small 

office building. DOE used an existing small office building model developed for DOE’s energy 

benchmarking task for this analysis. The determination of space cooling and space-heating loads 

assumed that a single type of product, in our case residential-type space-conditioning product, 

was used to condition the building. DOE simulated the same building as served either by CAC or 

CHP equipment and for each equipment type, simulated the equipment using four different 

efficiency levels. These levels were a 13 SEER, 14 SEER, 16 SEER, and a max tech level for 

either CAC (SEER 22, based on blower-coil ratings, or SEER 16.5, based on coil-only ratings) 

or CHP (SEER 19.5). Equipment parameters used in the simulation were adjusted to reflect 

engineering designs corresponding to each efficiency level. The simulated building utilized five 

individual CAC or CHP units. DOE extracted the annual energy consumption for cooling and 

fan energy use and CHP heating from each unit as well as the equipment capacity from each unit 

from each simulation run and aggregated these to the whole building level. Using this whole 

building data, DOE normalized the CAC and CHP energy consumption for each location and 

efficiency level to reflect that of an average 3-ton CAC or CHP unit for use in the LCC analysis. 

To estimate the energy consumption for intermediate efficiency levels between those simulated, 

DOE linearly interpolated the energy use estimates based on the results for the four simulated 

efficiencies. A complete description of the commercial energy use calculations is found in 

Chapter 7. 

The baseline commercial CAC and CHP use developed for the 237 TMY locations were 

associated with relative weighting factors for each TMY location much as the residential analysis 

uses the representative RECS weights. DOE used population-based weighting factors developed 

for each TMY climate based on data from the USGS to represent the importance of each TMY2 

climate in each state. The development and documentation of these weighting factors is 

discussed in chapter 7. Because certain TMY locations represent climates that cover more than 

one state DOE originally developed weighting factors for a total of 543 TMY-State 

combinations. Removal of the seventeen Alaskan locations discussed previously resulted in 526 

8-8 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

TMY-State combinations, with associated population weights, which then formed the basis of 

the commercial energy use sample. 

The average and marginal electricity prices were developed through a procedure of 

matching building hourly loads for each of the 526 represented buildings to actual modeled 

commercial tariffs (including any time-of-use rates) and then calculating customer bills. The 

methodology for matching commercial building peak demands to modeled tariffs is explained in 

appendix 8-B. Energy bills are calculated for a market baseline case and standards cases. 

Average electricity prices are determined by taking the bill for the market baseline case and 

dividing it by the amount of energy consumed. Marginal electricity prices are determined by 

taking the bill difference between the market baseline and standard cases (in dollars) and 

dividing it by the usage difference (in kWh) to give a “marginal” rate of $/kWh for that 

increment. 

Since several tariffs were applied to each building, both the average and marginal rates 

calculated from each tariff were weighted by the number of customers covered by the tariff to 

come up with a weighted-average marginal and average rate for each building in each region. 

The above procedure was used to develop space-cooling and space-heating average and marginal 

rates. Since detailed building loads and demands were not available for space-heating, average 

rather than marginal electricity prices were used to determine the energy costs associated with 

the operation of heat pumps during the space-heating season. 

As with the residential buildings from the RECS sample, the annual energy consumption, 

average electricity price, and marginal electricity price associated with each of the 526 

commercial buildings observations are not uncertain and are, therefore, not expressed with 

probability distributions. Although the above three input variables are not uncertain, they are 

variable. Due to the number of buildings considered in the LCC and PBP analysis, the range of 

annual energy use, average electricity price, and marginal electricity price is large (the actual 

ranges are presented and discussed later in this chapter). Thus, although the above three input 

variables are not uncertain for any particular building, their variability across all buildings 

contributes significantly to the range of LCCs and PBPs calculated for any particular standardlevel. 

8.2 LIFE-CYCLE COST ANALYSIS INPUTS 

8.2.1 Definition 

Life-cycle cost is the total customer cost over the life of a piece of product, including 

purchase cost and operating costs (which are comprised of energy costs, maintenance costs, and 

repair costs). Future operating costs are discounted to the time of purchase and summed over the 

lifetime of the product. Life-cycle cost is defined by the following equation: 

N 

LCC = IC +∑OCt /(1+ r)

t Eq. 8.2.1 t =1 

Where: 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 LCC = life-cycle cost ($),

 IC = total installed cost ($), 

∑ = sum over the lifetime, from year 1 to year N, 

where N = lifetime of product (years),

 OC = operating cost ($),

 r = discount rate, and

 t = year for which operating cost is being determined. 

Although DOE gathered most of its data for the LCC analysis in 2009, DOE expresses all 

the costs in 2008$. By convention, DOE reports its costs in the years’ dollars preceding the year 

of the analysis. Total installed cost, operating cost, lifetime, and discount rate are discussed in 

the following sections. In the LCC analysis, the year of product purchase is assumed to be 2016, 

the effective date of the amended energy conservation standards for CACs. 

8.2.2 Total Installed Cost Inputs 

The total installed cost to the customer is defined by the following equation: 

IC = EQP + INST Eq. 8.2.2 

Where:

 EQP = product price ($) (i.e., customer price for the product only),

 INST = installation cost or the customer price to install product ($) (i.e., the cost for 

labor and materials). 

The product price is based on the distribution channel through which the customer 

purchases the product. As discussed in Chapter 6, Markups for Product Price Determination, 

DOE defined one major distribution channel for new units to describe how the product passes 

from the manufacturer to the customer: the manufacturer sells the product to a 

wholesaler/distributor, who sells to a mechanical contractor hired by a general contractor. The 

general contractor purchases and installs the product on behalf of the customer and adds its 

markup to the mechanical contractor’s price. Replacement products follow the same distribution 

channel, except that there is no general contractor. Instead, the mechanical contractor takes on 

the general contractor’s function. 

The remainder of this section provides information about the variables DOE used to 

calculate the total installed cost for CAC products. Inputs to determine total installed cost are 

shown below: 

• Baseline manufacturer selling prices ($) (section 8.2.2.1) 

• Standard-level manufacturer selling price increases ($) (section 8.2.2.2) 

• Transportation costs ($) (section 8.2.2.3) 

• Overall markups (section 8.2.2.4) 

• Installation costs ($) (section 8.2.2.5) 

• Weighted-average total installed costs ($) (section Error! Reference source not found.) 

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EERE-2008-BT-STD-0006 COMMENT 54
 

8.2.2.1 Baseline Manufacturer Selling Price 

The baseline MSP is the price charged by manufacturers to either a wholesaler or very 

large customer for product meeting existing minimum efficiency (or baseline) standards. The 

MSP includes a markup that converts the cost to manufacture (i.e., the manufacturing cost) to a 

MSP. DOE developed the baseline MSP through an efficiency level analysis supplemented by 

certain design-option considerations. Refer to Chapter 5, Engineering Analysis, for details. 

DOE developed MSP for product classes identified in market and technology assessment 

analysis, Chapter 3 of the TSD. The LCC and PBP were calculated based on the same set of 

representative products as given in Table 8.2.1. 

Table 8.2.1 Representative CAC Products Evaluated for the Life-Cycle Cost and 

Payback Analyses 

Product Class 

Representative 

Products Description 

SS-AC (Coil- Only) SS-AC-3T (Coil- Only) Split-system air conditioners, inside evaporator coil-only (no 

blower unit purchased) 

SS-AC (Blower-Coil) SS-AC-3T (Blower-Coil) Split-system air conditioners, including blower unit 

(evaporator coil and air handler purchased) 

SS-HP SS-HP-3T Split-system heat pumps 

SP-AC SP-AC-3T Single-package air conditioners 

SP-HP SP-HP-3T Single-package heat pumps 

SDHV SDHV-3T Small-duct high-velocity (SDHV) systems 

SC-AC SC-AC-3T Space-constrained products – air conditioners 

SC-HP SC-HP-3T Space-constrained products – heat pumps 

DOE determined the market baseline with a minimum requirement of 13 SEER6 as the 

baseline efficiency levels for CACs. The minimum efficiency levels specified are detailed in 

Chapter 5, Engineering Analysis. In the case of split-system air conditioners, DOE analyzed 

options with and without a complete air handler unit, since it is not clear whether a furnace or 

other fan unit would be purchased at the same time as the inside evaporator coil and outside 

condensing unit. DOE developed the MSP for the baseline efficiency product as a part of the 

engineering analysis (see Chapter 5 of the TSD), which are shown in Table 8.2.2. 

Table 8.2.2 Baseline Manufacturer Selling Prices per Unit 

Representative Product 

SEER 

(Baseline 

Efficiency) 

Baseline 

Manufacturer Selling 

Price* 2008$ 

SS-AC-3T (Coil-Only) 13.0 885 

SS-AC-3T ( Blower-Coil) 13.0 1,063 

SS-HP-3T 13.0 1,255 

SP-AC-3T 13.0 959 

SP-HP-3T 13.0 1,186 

SDHV-3T 13.0 1,191 

SC-AC-3T 13.0 1,196 

SC-HP-3T 13.0 1,201 

* Baseline MSP is based upon the CAC products using R-410A refrigerant. 

8-11 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Since air conditioners and heat pumps are commonly sold in situations where heating 

and cooling equipment are being considered together, there is some uncertainty determination of 

what assumption should be made concerning any cost and efficiency benefit for a fuel-fired 

(gas-, oil-, or LPG-fired) furnace. To account for this, the manufacturer selling price for splitsystem air conditioner is handled two ways. 1) In coil-only purchases, the air conditioning unit is 

installed in a situation where a medium-efficiency furnace fan is available to circulate air. This 

accounts for replacement scenarios in which a furnace fan is already available as well as new 

systems where the furnace is purchased separately. 2) In blower-coil purchases, it is assumed 

that there either is no furnace or that its air-handling capacity is not adequate for the air 

conditioning unit. In this case, the cost includes an air handler with a blower and evaporative 

coil. Systems using a blower coil can use improvements on the indoor air-handler to achieve 

higher SEER ratings. Systems rated as “coil-only” systems must use improvements on the 

indoor coil or outdoor condensing unit to achieve higher SEER rating. For simplicity, splitsystem heat pumps were assumed to always be sold with an air handler, due to the need to 

closely match condensing, evaporative, and air handling capabilities to gain efficiency in a heat 

pump system. Single package heat pumps and single package air conditioners sold as complete 

packages, including condensing unit, evaporator unit, and blower. 

8.2.2.2 Standard-Compliant Manufacturer Selling Price Increases 

The standard-compliant MSP increase is the change in MSP associated with producing 

product at higher efficiency levels. DOE developed MSP increases associated with increases in 

product efficiency levels through a combination of efficiency level and design-option analyses in 

the engineering analysis (see Chapter 5 of the TSD). MSP increases as a function of product 

efficiency were developed for each of the representative product categories in the engineering 

analysis as well. Table 8.2.3 summarizes the estimated MSP for CAC and CHP efficiency levels 

considered in the LCC and PBP analyses. 

Table 8.2.3 SEER Standard-Compliant Manufacturer Selling Prices per Unit 

Efficiency 

Level 

MSP for Representative Standard-Compliant Products 

2008$ 

Splitsystem 

AC (CoilOnly) 

Splitsystem 

AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP 

Level 2 930 1,114 1,313 1,045 1,241 

Level 3 979 1,165 1,375 1,103 1,312 

Level 4 1,033 1,220 1,421 1,188 1,416. 

Level 5 1,095 1,259 1,465 1,257 1,507 

Level 6 1,171 1,300 1,515 1,344 1,613 

Level 7 1,269 1,343 1,578 1,448 1,740 

Level 8 1,382 1,387 1,687 1,596. 1,866 

Level 9 NA 1,433 1,804 NA NA 

Level 10 NA 1,529 1,930 NA NA 

Level 11 NA 1,634 1,998 NA NA 

Level 12 NA 1,746 NA NA NA 

Level 13 NA 1,866 NA NA NA 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

Level 14 NA 1,996 NA NA NA 

8.2.2.3 Transportation Cost 

The MSP cost of CAC and CHP products derived above is considered to be a price that 

includes freight on board charges at the manufacturer’s shipping dock. The additional cost of 

transporting a CAC or CHP unit to the local distribution point depends mainly on its weight. 

The estimated shipping weight of these units is shown in Table 8.2.4. 

Table 8.2.4 Shipping Weights of SEER Standard-compliant Products 

Efficiency 

Level 

Shipping Weight for Representative Standard-Compliant 

Products Lbs 

Splitsystem AC 

(CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem HP 

Single 

Package 

AC 

Single 

Package 

HP 

Level 1 206 288 339 333 379 

Level 2 218 303 354 349 395 

Level 3 228 316 368 366 411 

Level 4 250 329 382 382 427 

Level 5 271 344 396 398 443 

Level 6 293 357 409 414 460 

Level 7 318 370 422 431 476 

Level 8 344 382 447 450 489 

Level 9 NA 395 468 NA NA 

Level 10 NA 422 489 NA NA 

Level 11 NA 446 501 NA NA 

Level 12 NA 471 NA NA NA 

Level 13 NA 496 NA NA NA 

Level 14 NA 520 NA NA NA 

Table 8.2.5 shows the estimated overall MSPs, including transportation. DOE visited a 

freight transportation website (FreightCenter.com7

) and obtained quotes for a number of 

shipment options. FreightCenter.com quotes were obtained for palletized full truckloads 

assumed to be 26,880 and 15,000 pounds with varying configurations for a shipment from Fort 

Smith, AR to Richmond, VA (1,117 miles), which was assumed to be a typical shipment 

distance. Prices ranged for $0.064 per pound to $0.56 per pound for that route, depending on 

services offered. Excluding high-priced services, DOE determined that a value of $0.20 per 

pound adequately represented the middle of the range of shipping costs. The value of $0.20 per 

pound was used for all transportation cost calculations. 

8-13 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Table 8.2.5 MSP Including Transportation of SEER Standard-compliant Products 

Efficiency 

Level 

MSP Including Transportation for Representative Standard-Compliant 

Products 

2008$ 

Split-system 

AC (CoilOnly) 

Split-system 

AC 

(BlowerCoil) 

Split-system 

HP 

Single 

Package AC 

Single 

Package HP 

Level 1 926 1,121 1,323 1,025 1,262 

Level 2 974 1,175 1,384 1,115 1,320 

Level 3 1,024 1,229 1,448 1,176 1,395 

Level 4 1,083 1,286 1,497 1,264 1,502 

Level 5 1,149 1,328 1,545 1,336 1,596 

Level 6 1,230 1,372 1,596 1,427 1,705 

Level 7 1,333 1,417 1,663 1,534 1,835 

Level 8 1,451 1,463 1,776 1,686 1,964 

Level 9 NA 1,512 1,898 NA NA 

Level 10 NA 1,614 2,028 NA NA 

Level 11 NA 1,723 2,098 NA NA 

Level 12 NA 1,840 NA NA NA 

Level 13 NA 1,965 NA NA NA 

Level 14 NA 2,100 NA NA NA 

8.2.2.4 Overall Markup 

For a given distribution channel, the overall markup is the value determined by 

multiplying all the associated markups and the applicable sales tax together to arrive at a single 

overall distribution chain markup value. The overall markup is multiplied times the baseline or 

standard-compliant manufacturing selling price (including transportation) to arrive at the price 

paid by the customer. Because there are baseline and incremental markups associated with the 

wholesaler and mechanical contractor, the overall markup is also divided into a baseline markup 

(i.e., a markup used to convert the baseline manufacturer price into a customer price) and an 

incremental markup (i.e., a markup used to convert a standard-compliant MSP increase due to an 

efficiency increase into an incremental customer price). Markups can differ depending whether 

the product is being purchased for a new construction installation or is being purchased to 

replace an existing product replacement. DOE developed the overall baseline markups and 

incremental markups for both the new construction and replacement applications as a part of the 

markups analysis (chapter 6 of the TSD). 

Based on the percentages of the market attributed to each distribution channel in 

chapter 6, Table 8.2.6 and Table 8.2.7 display the weighted-average overall markups and their 

associated components for the baseline and incremental markups, respectively. The differences 

between national average incremental markups for standard size and non-standard size units are 

small enough that the last columns in Table 8.2.7 are identical. DOE used the appropriate 

baseline markup times the baseline and incremental MSP (including transportation) to obtain 

estimates of the retail price of the CAC and CHP equipment. The calculations are demonstrated 

in section Error! Reference source not found.. 

8-14 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 8.2.6 Overall National Average Baseline Markup Factors by Product Type 

Factor 

New 

Construction 

Application 

Replacement 

Application 

Wholesale Markup 1.370 1.370 

Mechanical Contractor 

Markup 1.280 1.380 

General Contractor 

Markup 1.290 NA* 

Sales Tax 1.071 1.071 

Total Markup 2.422 2.025 

* General contractors do not appear in the replacements 

distribution channel 

Table 8.2.7 Overall National Incremental Markup Factors by Product Type 

Factor 

New 

Construction 

Application 

Replacement 

Application 

Wholesale Markup 1.114 1.114 

Mechanical Contractor 

Markup 1.040 1.120 

General Contractor 

Markup 1.170 NA* 

Sales Tax 1.071 1.071 

Total Markup 1.452 1.336 

* General contractors do not appear in the replacements 

distribution channel 

8.2.2.5 Installation Cost 

The installation cost is the price to the customer of labor and materials (other than the 

actual product) needed to install the CAC product. DOE derived installation cost for CAC 

product from data in the RS Means Residential Cost Data 20098 and RS Means CostWorks 

2009.9 

RS Means Residential Cost Data provides estimates on the person-hours required to 

install CAC and CHP products, labor rates, and costs associated with the type of crew required to 

install the products. Generally speaking, installation involves movement into the building, 

installation or setting of product (including sleeve), connecting to power supply, 

filling/flushing/cleaning/touchup, startup and running adjustments, training the owner’s 

representative, and warranty and call-back service. DOE calculated the installation cost by 

building up the labor costs for installing the components of the system types discussed in the 

Engineering Analysis, chapter 5, since materials costs, overheads, and profits were assumed to 

be captured in the contractor markups. Labor rates vary significantly from region to region of 

the country and the RS Means data provide the necessary information to capture this regional 

variability. RS Means CostWorks provides cost indices that reflect the labor rates for 295 cities 

in the United States. Cities in all 50 States and the District of Columbia are identified in the RS 

Means data and most states are represented by more than one city. DOE used the city indices to 

develop population weighted averages for each state and the District of Columbia. DOE 

8-15 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

incorporated the state indices into the analysis to capture place-to-place variation in installation 

cost. 

Table 8.2.8 summarizes the nationally representative installation costs based on personhours and labor rates associated with the installation of CAC and CHP products as presented in 

RS Means. DOE assumed that these installation costs remain fixed regardless of efficiency level 

(a “flat” installation cost scenario). DOE’s LCC spreadsheet initially allowed for an alternative 

scenario - that the installation cost increases with higher efficiency levels - and this alternative 

was implemented in the LCC spreadsheet by providing for an installation price that varies in 

proportion to increased manufacturer cost above the baseline efficiency level. However, DOE 

discussed installation costs with a small sample of installers and did not find a basis for 

installation costs increasing with efficiency. DOE therefore assumed that installation costs 

varied by region but not by efficiency level. 

Table 8.2.8 Installation Costs for Baseline CAC Products (SEER 13) 

MSP for Representative Standard-Compliant Products 

2008$ 

Split-system AC 

(Coil- Only) 

Split-system AC 

(Blower-Coil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP 

508 648 561 528 403 

Table 8.2.9 summarizes the cost indices for installations in each of the 50 states, plus the 

District of Columbia, used to vary the nationally representative installation costs in Table 8.2.8. 

To arrive at an average index for each state, DOE weighted the city indices in each state 

by their population within each state. Because city-level population estimates were not available 

for 2008, DOE used estimated city population weights for the year 2007 from the U.S. Census 

Bureau10 to calculate a weighted-average index for each state from the RS Means CostWorks 

data. Weighted averages and estimates at the regional and national level were computed using 

2008 state population weights from the U.S. Census Bureau11. 

8.2.2.6 Weighted-Average Total Installed Cost 

As presented in Eq.8.2, the total installed cost is the sum of the product price and the 

installation cost. DOE derived the customer product price for any given efficiency level by 

taking the product of the baseline MSP and the baseline markup index (including the sales tax) 

and adding to it the product of the incremental MSP and the incremental markup index 

(including the sales tax). MSPs, markups, and the sales tax all can take on a variety of values, 

depending on location, so the resulting total installed cost for a particular efficiency level will not 

be a single-point value, but rather a distribution of values. 

The baseline MSP and the standard-compliant MSP increases are the starting points for 

determining the total installed cost (values are taken directly from Table 8.2.5). DOE used the 

baseline and incremental markups and installation costs to convert the MSPs into total installed 

costs. Both the percentage retail markups and the percentage installation cost may change with 

the efficiency level. As an example, the weighted average costs for a 3-ton Split-System AC 

product category are presented for the baseline level. Table 8.2.10 summarizes the weighted8-16 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

average costs and markups necessary for determining the weighted-average baseline and 

standard-compliant total installed costs for a new Split-System AC Coil-Only unit. 

Table 8.2.9 Installation Cost Indices (National Average Value = 100.0) 

State Index State Index State Index 

Alabama 61.8 Kentucky 85.8 North Dakota 62.9 

Alaska 112.3 Louisiana 63.1 Ohio 101.2 

Arizona 79.6 Maine 74.2 Oklahoma 61.5 

Arkansas 60.9 Maryland 96.5 Oregon 111.7 

California 133.0 Massachusetts 128.3 Pennsylvania 126.4 

Colorado 86.9 Michigan 110.1 Rhode Island 116.9 

Connecticut 124.8 Minnesota 122.3 South Carolina 44.5 

Delaware 122.6 Mississippi 66.5 South Dakota 51.2 

Dist. Of Columbia 102.3 Missouri 105.2 Tennessee 71.4 

Florida 67.1 Montana 78.8 Texas 64.7 

Georgia 75.2 Nebraska 87.3 Utah 75.8 

Hawaii 117.1 Nevada 112.1 Vermont 70.8 

Idaho 75.4 New Hampshire 93.0 Virginia 76.3 

Illinois 141.3 New Jersey 132.1 Washington 108.6 

Indiana 90.2 New Mexico 78.8 West Virginia 93.6 

Iowa 79.8 New York 170.7 Wisconsin 102.8 

Kansas 71.4 North Carolina 44.6 Wyoming 65.3 

 Table 8.2.10 Costs and Markups for Determination of Weighted-Average Total Installed 

Costs for a New 3-Ton Split-system AC Coil-Only Unit (Efficiency Level 5: SEER 15 

Variable 

SEER Weighted Average Value 

National 

Average 

HotHumid Hot-Dry Rest of 

Country 

Baseline Manufacturer 

Selling Price, Including 

Transportation (SEER 13) 

$926.15 $926.15 $926.15 $926.15 

Standard-compliant 

Manufacturer selling price 

Increase (Efficiency Level 

5—SEER 15) 

$223.28 $223.28 $223.28 $223.28 

Average Overall Baseline 

Markup (Regional) 

2.423 2.435 2.858 2.444 

Average Overall 

Incremental Markup 

(Regional) 

1.452 1.459 1.712 1.464 

Installation Cost $508 $508 $508 $508 

Installation Cost Factor – 

Regional 

1.000 0.641 1.223 1.145 

To illustrate the derivation of the weighted-average total installed cost shown in 

Table 8.2.10, DOE presents the calculations for the baseline efficiency (Eq. 8.2.3) and a higher 

efficiency SS-AC-3T unit at SEER 15 (Level 5) (Eq. 8.2.4). For baseline products, the 

calculation of the Hot-Humid regional average total installed cost is as follows: 

ICBASE SS-AC-3T = EQPBASE-SS-AC-3T +INSTBASE-SS-AC-3T x INSTNDEX Eq. 8.2.3 

= MSPBASE- SS-AC-3T X MU BASE- SS-AC-3T + INST BASE- SS-AC-3T x INSTNDEX 

= $926.15 x 2.435 + $508 x 0.641 

8-17 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

= $2,255.18 + $325.62
 

= $2580.80. 

Where: 

IC = total installed cost ($), 

EQP = product price ($), 

MSP = manufacturer selling price ($), 

MU = overall baseline markup, 

INST = installation cost or the customer price to install product ($), 

INSTINDEX = location dependent installation cost index, approximately 1.0 at a 

national average. 

In this specific example, MSP is the national average baseline MSP for the Split-System 

Coil-Only CAC product class and MU is the overall baseline markup factor. The calculation of 

the higher efficiency (efficiency level 5-SEER 15) total installed cost includes the use of a MSP 

adder. In addition, DOE derived an incremental markup. 

Based on incremental product price changes, the derivation of the efficiency level 5 total 

installed cost is based on determining the change in product price over the baseline product price. 

The manufacturer price increment for higher efficiency product is multiplied by the incremental 

markup. 

DOE calculated the efficiency level 5 total installed cost (IC SS-AC-3T Level 5) as follows: 

ICSS-AC-3T Level5 = (EQP BASE-SS-AC-3T + ∆EQP SS-AC-3T Level 5) 

+ INST SS-AC-3T Level 5 x INSTINDEX Eq. 8.2.4 

= (MSP BASE-SS-AC-3T X MU BASE-SS-AC-3T ) +( ∆MSP SS-AC-3T Level 5
 

X MU SS-AC-3T Level 5) + INST SS-AC-3T Level 5 x ISTINDEX 

= $926.15 x 2.435 + $223.28 x 1.459 + $508 x 0.641 

= $2906.57 

Where: 

∆EQP = increase in product price ($),
 

∆MFG = increase in manufacturer price ($), 

MU = markup factor (base or incremental, as shown in Table 8.2.6 and 

Table 8.2.7, respectively) 

Table 8.2.11 presents the average product price, installation costs, and total installed costs 

for the representative product Split-system AC (Coil-only) at the baseline level and each 

efficiency level examined. Table 8.2.12 through Table 8.2.15 present these data for the other 

product classes. 

8-18 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.2.11 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system AC (Coil-only), at Average 

Prices* 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

National Average 

Level 1 926 2,244 508 2,752 

Level 2 974 2,316 508 2,824 

Level 3 1,024 2,391 508 2,899 

Level 4 1,083 2,479 508 2,987 

Level 5 1,149 2,578 508 3,086 

Level 6 1,230 2,699 508 3,207 

Level 7 1,333 2,853 508 3,361 

Level 8 1,451 3,030 508 3,538 

Hot-Humid Region 

Level 1 926 2,255 325 2,581 

Level 2 974 2,325 325 2,651 

Level 3 1,024 2,399 325 2,724 

Level 4 1,083 2,485 325 2,810 

Level 5 1,149 2,581 325 2,907 

Level 6 1,230 2,699 325 3,024 

Level 7 1,333 2,848 325 3,174 

Level 8 1,451 3,021 325 3,347 

Hot-Dry Region 

Level 1 926 2,647 621 3,268 

Level 2 974 2,728 621 3,350 

Level 3 1,024 2,815 621 3,436 

Level 4 1,083 2,915 621 3,537 

Level 5 1,149 3,029 621 3,650 

Level 6 1,230 3,167 621 3,788 

Level 7 1,333 3,343 621 3,964 

Level 8 1,451 3,545 621 4,166 

Rest of Country 

Level 1 926 2,263 582 2,845 

Level 2 974 2,334 582 2,916 

Level 3 1,024 2,409 582 2,991 

Level 4 1,083 2,497 582 3,078 

Level 5 1,149 2,595 582 3,177 

Level 6 1,230 2,715 582 3,296 

Level 7 1,333 2,867 582 3,449 

Level 8 1,451 3,043 582 3,625 

* Details may not add to total due to rounding. 

8-19 

EERE-2008-BT-STD-0006 COMMENT 54
Table 8.2.12 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system AC (Blower-Coil), at Average 

Prices* 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

National Average 

Level 1 1,121 2,954 1,102 4,056 

Level 2 1,175 3,028 1,102 4,130 

Level 3 1,229 3,102 1,102 4,204 

Level 4 1,286 3,181 1,102 4,283 

Level 5 1,328 3,239 1,102 4,341 

Level 6 1,372 3,299 1,102 4,401 

Level 7 1,417 3,362 1,102 4,464 

Level 8 1,463 3,426 1,102 4,528 

Level 9 1,512 3,492 1,102 4,594 

Level 10 1,614 3,633 1,102 4,735 

Level 11 1,723 3,783 1,102 4,885 

Level 12 1,840 3,944 1,102 5,046 

Level 13 1,965 4,117 1,102 5,219 

Level 14 2,100 4,303 1,102 5,405 

Hot-Humid Region 

Level 1 1,121 2,968 706 3,675 

Level 2 1,175 3,041 706 3,747 

Level 3 1,229 3,113 706 3,819 

Level 4 1,286 3,190 706 3,896 

Level 5 1,328 3,247 706 3,953 

Level 6 1,372 3,305 706 4,011 

Level 7 1,417 3,366 706 4,072 

Level 8 1,463 3,428 706 4,134 

Level 9 1,512 3,493 706 4,199 

Level 10 1,614 3,630 706 4,336 

Level 11 1,723 3,777 706 4,483 

Level 12 1,840 3,934 706 4,640 

Level 13 1,965 4,103 706 4,809 

Level 14 2,100 4,284 706 4,990 

8-20 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.2.12 (contd) 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

Hot-Dry Region 

Level 1 1,121 3,483 1,348 4,831 

Level 2 1,175 3,568 1,348 4,916 

Level 3 1,229 3,653 1,348 5,001 

Level 4 1,286 3,743 1,348 5,091 

Level 5 1,328 3,810 1,348 5,158 

Level 6 1,372 3,879 1,348 5,227 

Level 7 1,417 3,950 1,348 5,298 

Level 8 1,463 4,023 1,348 5,371 

Level 9 1,512 4,099 1,348 5,447 

Level 10 1,614 4,260 1,348 5,608 

Level 11 1,723 4,432 1,348 5,780 

Level 12 1,840 4,616 1,348 5,964 

Level 13 1,965 4,814 1,348 6,162 

Level 14 2,100 5,027 1,348 6,375 

Rest of Country 

Level 1 1,121 2,979 1,262 4,241 

Level 2 1,175 3,052 1,262 4,314 

Level 3 1,229 3,126 1,262 4,388 

Level 4 1,286 3,204 1,262 4,466 

Level 5 1,328 3,262 1,262 4,524 

Level 6 1,372 3,322 1,262 4,584 

Level 7 1,417 3,384 1,262 4,646 

Level 8 1,463 3,447 1,262 4,709 

Level 9 1,512 3,513 1,262 4,775 

Level 10 1,614 3,653 1,262 4,915 

Level 11 1,723 3,802 1,262 5,064 

Level 12 1,840 3,962 1,262 5,224 

Level 13 1,965 4,134 1,262 5,396 

Level 14 2,100 4,319 1,262 5,581 

* Details may not add to total due to rounding. 

8-21 

EERE-2008-BT-STD-0006 COMMENT 54
Table 8.2.13 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Split-system HP, at Average Prices*
 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

National Average 

Level 1 1,323 2,679 561 3,240 

Level 2 1,384 2,763 561 3,324 

Level 3 1,448 2,852 561 3,412 

Level 4 1,497 2,919 561 3,480 

Level 5 1,545 2,985 561 3,545 

Level 6 1,596 3,056 561 3,616 

Level 7 1,663 3,147 561 3,708 

Level 8 1,776 3,304 561 3,864 

Level 9 1,898 3,471 561 4,031 

Level 10 2,028 3,650 561 4,210 

Level 11 2,098 3,747 561 4,307 

Hot-Humid Region 

Level 1 1,323 2,692 359 3,052 

Level 2 1,384 2,774 359 3,133 

Level 3 1,448 2,861 359 3,220 

Level 4 1,497 2,926 359 3,286 

Level 5 1,545 2,990 359 3,349 

Level 6 1,596 3,060 359 3,419 

Level 7 1,663 3,149 359 3,508 

Level 8 1,776 3,301 359 3,660 

Level 9 1,898 3,464 359 3,823 

Level 10 2,028 3,639 359 3,998 

Level 11 2,098 3,733 359 4,093 

Hot-Dry Region 

Level 1 1,323 3,159 686 3,845 

Level 2 1,384 3,255 686 3,941 

Level 3 1,448 3,357 686 4,042 

Level 4 1,497 3,434 686 4,120 

Level 5 1,545 3,509 686 4,194 

Level 6 1,596 3,590 686 4,276 

Level 7 1,663 3,695 686 4,380 

Level 8 1,776 3,874 686 4,559 

Level 9 1,898 4,065 686 4,751 

Level 10 2,028 4,270 686 4,956 

Level 11 2,098 4,381 686 5,067 

8-22 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.2.13 (contd) 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

Rest of Country 

Level 1 1,323 2,702 642 3,343 

Level 2 1,384 2,785 642 3,427 

Level 3 1,448 2,873 642 3,515 

Level 4 1,497 2,940 642 3,582 

Level 5 1,545 3,005 642 3,647 

Level 6 1,596 3,076 642 3,718 

Level 7 1,663 3,167 642 3,808 

Level 8 1,776 3,322 642 3,964 

Level 9 1,898 3,488 642 4,130 

Level 10 2,028 3,666 642 4,308 

Level 11 2,098 3,762 642 4,404 

* Details may not add to total due to rounding. 

Table 8.2.14 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Single Package AC, at Average Prices* 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

National Average 

Level 1 1,025 2,077 528 2,604 

Level 2 1,115 2,200 528 2,664 

Level 3 1,176 2,284 528 2,727 

Level 4 1,264 2,405 528 2,811 

Level 5 1,336 2,505 528 2,933 

Level 6 1,427 2,630 528 3,033 

Level 7 1,534 2,778 528 3,158 

Level 8 1,686 2,987 528 3,305 

Hot-Humid Region 

Level 1 1,025 2,087 338 2,425 

Level 2 1,115 2,207 338 2,545 

Level 3 1,176 2,289 338 2,627 

Level 4 1,264 2,407 338 2,745 

Level 5 1,336 2,505 338 2,843 

Level 6 1,427 2,627 338 2,965 

Level 7 1,534 2,771 338 3,109 

Level 8 1,686 2,975 338 3,313 

8-23 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 8.2.14 (contd) 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

Hot-Dry Region 

Level 1 1,025 2,449 645 3,094 

Level 2 1,115 2,590 645 3,235 

Level 3 1,176 2,686 645 3,331 

Level 4 1,264 2,825 645 3,470 

Level 5 1,336 2,939 645 3,584 

Level 6 1,427 3,082 645 3,728 

Level 7 1,534 3,251 645 3,896 

Level 8 1,686 3,490 645 4,136 

Rest of Country 

Level 1 1,025 2,094 604 2,698 

Level 2 1,115 2,133 604 2,820 

Level 3 1,176 2,216 604 2,904 

Level 4 1,264 2,300 604 3,025 

Level 5 1,336 2,421 604 3,124 

Level 6 1,427 2,520 604 3,248 

Level 7 1,534 2,644 604 3,395 

Level 8 1,686 2,791 604 3,602 

* Details may not add to total due to rounding. 

Table 8.2.15 Manufacturer Selling Price (Including Transportation), Product Price, 

Installation Cost, and Total Installed Costs for Single Package HP, at Average Prices * 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

National Average 

Level 1 1,262 2,556 403 2,958 

Level 2 1,320 2,636 403 3,038 

Level 3 1,395 2,739 403 3,141 

Level 4 1,502 2,886 403 3,288 

Level 5 1,596 3,016 403 3,418 

Level 6 1,705 3,166 403 3,569 

Level 7 1,835 3,345 403 3,747 

Level 8 1,964 3,523 403 3,925 

Hot-Humid Region 

Level 1 1,262 2,568 258 2,826 

Level 2 1,320 2,647 258 2,904 

Level 3 1,395 2,747 258 3,005 

Level 4 1,502 2,890 258 3,148 

8-24 

EERE-2008-BT-STD-0006 COMMENT 54
 

Efficiency Level 

Manufacturer 

Selling 

Price 2008$ 

Product 

Price (Including 

Markups) 2008$ 

Installation 

Cost 2008$ 

Total Installed 

Cost 2008$ 

Level 5 1,596 3,017 258 3,275 

Level 6 1,705 3,164 258 3,422 

Level 7 1,835 3,338 258 3,595 

Level 8 1,964 3,511 258 3,769 

Hot-Dry Region 

Level 1 1,262 3,014 492 3,506 

Level 2 1,320 3,106 492 3,598 

Level 3 1,395 3,223 492 3,715 

Level 4 1,502 3,392 492 3,884 

Level 5 1,596 3,540 492 4,032 

Level 6 1,705 3,712 492 4,205 

Level 7 1,835 3,916 492 4,409 

Level 8 1,964 4,120 492 4,613 

Rest of Country 

Level 1 1,262 2,577 461 3,038 

Level 2 1,320 2,657 461 3,118 

Level 3 1,395 2,759 461 3,220 

Level 4 1,502 2,905 461 3,366 

Level 5 1,596 3,034 461 3,495 

Level 6 1,705 3,184 461 3,645 

Level 7 1,835 3,361 461 3,822 

Level 8 1,964 3,538 461 3,999 

* Details may not add to total due to rounding. 

8.2.3 Operating Cost Inputs 

The operating cost is determined for households using data from the 2005 Residential 

Energy Consumption Survey (RECS) and industry sources on repair cost and maintenance cost. 

The operating cost for commercial buildings is based on computer modeling of a representative 

commercial building in 237 climates. For the LCC analysis of central air conditioners (either 

split or package systems), the LCC of an increased efficiency level is calculated for those 

residential and commercial buildings that are determined to have a central air conditioner. For 

heat pumps (either split or package systems), the LCC of an increased efficiency level is 

calculated for those buildings that are determined to have a central heat pump. The LCC analysis 

results in a distribution of LCC savings (i.e., the LCC difference between the baseline product 

and product with a higher efficiency level) for 10,000 individual observations at each higher 

efficiency level nationally, and in each region. The analysis computes the mean LCC difference 

at each efficiency level in each region, as well as the percentage of buildings analyzed that have 

positive LCC savings associated with the more-efficient product. 

8-25 

EERE-2008-BT-STD-0006 COMMENT 54
DOE defined the operating cost by the following equation: 

OC = EC+ RC+ MC Eq. 8.2.5 

Where: 

OC = operating cost ($), 

EC = energy cost associated with operating the product ($), 

RC = repair cost associated with component failure ($), 

MC = annual maintenance cost for maintaining product operation ($). 

The remainder of this section provides information about the variables that DOE used to 

calculate the operating cost for CAC and CHP products. Product lifetime, discount rate, and 

effective date of the amended energy conservation standard are required for determining the 

operating cost and for establishing the operating cost present value. The annual energy costs of 

the product are computed from energy consumption per unit for the baseline efficiency and 

standard-compliant cases (efficiency level 1, 2, etc.), combined with the electricity prices. 

Chapter 7, Building Energy Use Characterization Analysis, provides complete details on the 

CAC product energy consumption results for three regions and the nation as a whole. The key 

inputs for the determination of operating costs are shown below: 

• Baseline and standard-compliant annual energy consumption (kWh) (Chapter 7) 

• Electricity price (cents/kWh) (section 8.2.3.1) 

• Electricity price trend (section 8.2.3.2) 

• Repair cost ($) (section 8.2.3.3 ) 

• Maintenance cost ($) (section 8.2.3.4) 

• Equipment lifetime (years) (section 8.2.3.5) 

• Discount rate (percentage) (section8.2.3.6) 

• Effective date of amended energy conservation standard (section 8.2.3.7) 

8.2.3.1 Electricity Price Analysis 

Electricity price information is required to calculate the dollar benefits to consumers who 

purchase and operate a more efficient appliance. The electricity cost savings comprise the benefit 

side of the cost-benefit analysis used to define the life-cycle cost impacts of a proposed standard. 

In previous rulemakings, DOE has used estimates of marginal electricity prices to calculate these 

cost savings. The marginal price for a given consumer is the cost of the next increment of 

electricity use on the consumer’s utility bill, and is the correct estimate of the value of savings 

that a consumer would see in the real world. In some cases, it may be sufficient to use estimates 

of average electricity prices, which are less accurate but simpler to calculate. However, if there is 

reason to believe that marginal prices differ significantly from average prices, the approximation 

is not justified. For a peak-coincident end use such as air-conditioning, there is a general 

expectation that the actual cost of operating the appliance is higher than the average price of 

electricity. These increased costs are often reflected in utility tariff structures, through block 

8-26 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

rates, different types of demand charges, or mandatory time-of-use rates. Accurate estimation of 

marginal prices requires taking rate structures into account explicitly. 

In general, several methods and data sources can be used to calculate electricity prices. 

After reviewing the strengths and weaknesses of different approaches and the available data, the 

Department chose to base the analysis on the utility tariffs comprising the TAP (Tariff Analysis 

Project) database.12 The TAP database and calculation tools were first developed at LBNL for 

use in the Commercial Unitary Air Conditioning (CUAC) rulemaking.13 This approach provides 

an up-to-date and geographically diverse data set that can accurately capture real prices. Other 

data sources have various weaknesses that could lead to significant errors in the estimated 

electricity cost savings, and do not provide sufficient information to allow DOE to respond 

adequately to stakeholder comments. A more detailed discussion of electricity price data and 

calculation methods is presented in appendix 8-B, along with a description of the tariff-based 

approach, the data used, and validation tests. Detailed documentation is also available in 

published reports.10, 11, 14Residential electricity cost savings are calculated based on the default 

tariffs collected in the TAP database. Currently, for all utilities the default tariff is not time-ofuse. A large number of utilities offer optional time-of-use (TOU) tariffs, but there are currently 

very few customers enrolled in these optional rate plans. appendix 8-C provides a quantitative 

comparison of prices for consumers on TOU vs. default tariffs for utilities that offer both 

For the analysis conducted for CAC and HP, electricity prices are required for both 

residential and commercial consumers. The LCC is based on a consumer sample derived from 

RECS and EIA’s Commercial Building Energy Consumption Survey (CBECS),15 and both an 

average annual price and a seasonal marginal price are required for each household or building in 

the sample. Following the methodology in the LCC, the consumer sample is also segregated 

according to product type (i.e., CAC or HP). The basic methodology is to estimate the 

customer’s monthly electricity use, and use the tariff data to calculate the corresponding 

electricity bill. Empirical marginal prices (EMPs) are calculated by taking the difference between 

the bill for the baseline electricity use and the bill for a candidate standard level, and dividing by 

the change in energy use. This approach requires estimation of monthly consumer electricity use 

for the baseline and the energy savings associated with each candidate standard level. As both 

the rate structures and the required energy data differ significantly for residential vs. commercial 

consumers, the details of the approach for these two sectors are discussed separately. 

Calculation of Residential Prices 

The calculation methodology provides, for each household in the building sample, an 

average annual price and a monthly marginal price. To compute these prices, the monthly 

baseline energy consumption must first be estimated. This is done using the monthly billing data 

from the RECS 2001 dataset because the detailed monthly billing data from the RECS 2005 was 

considered to be proprietary and could not be used; details of the calculation are presented in 

appendix 8-C. Given the monthly energy use, twelve monthly bills per household are calculated 

using the tariffs. To increase the effective size of the sample, within a region each household is 

paired with each utility in its region. DOE refers to the pairing of a household with a utility as an 

account. The utilities are weighted by the fraction of customers they serve within a region.11, 12 

Taking the weighted sum over accounts provides a single set of prices for each household. 

8-27 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

The annual average baseline price is calculated as a simple average over the twelve 

monthly baseline bills. To calculate monthly marginal prices for each account, the monthly 

energy use is decremented by seven percent and the bill recalculated. The marginal price in each 

month is defined as the bill savings divided by the energy savings under this test. This will be the 

valid price under all candidate standard levels. Monthly variability in the marginal price is due 

primarily to seasonal rates, as season definitions vary by utility. Within the LCC, the annual cost 

savings are equal to the monthly marginal price times the monthly energy savings, summed 

across months. A description of how the monthly energy savings are estimated for each CSL is 

given in appendix 8-C. 

To provide an indication of the prices that result from this analysis, Table 8.2.16 shows 

the annual average price and marginal prices for January and July. The table presents regional 

averages calculated for the hot-humid, hot-dry and rest-of-country regions defined for this 

rulemaking. The table also shows the total RECS weight associated with the household sample 

for each product type. Note that these regional averages are for information only; the LCC uses 

household-level prices. 

Table 8.2.16 Regional Averages of the Annual Average Prices and January and July 

Marginal Prices 

Product and Region RECS Nweight 

Residential Electricity Prices cents/kWh 

Annual 

Average Price 

January 

Marginal Price 

July 

Marginal Price 

Central Air 

Hot-Humid 

Hot-Dry

Rest of Country 

Nation 

19,045,578 

 6,164,451 

25,769,446 

50,979,476 

10.04 

16.11 

10.73 

11.12 

8.86 

19.79 

9.11 

10.30 

9.75 

19.97 

10.57 

11.40 

Heat Pump 

Hot-Humid 

Hot-Dry

Rest of Country 

Nation 

5,545,454 

 837,752 

3,608,821 

9,992,026 

10.01 

14.35 

9.68 

10.26 

9.50 

16.22 

8.52 

9.71 

10.20 

15.80 

9.93 

10.57 

Calculation of Commercial Prices 

Electricity tariffs for commercial consumers can be very complex, incorporating block 

rates, seasonal rates, demand charges, time-of-use rates, etc. To calculate commercial electricity 

bills requires both the monthly consumption and demand; for utilities with mandatory time-ofuse (TOU) tariffs, consumption and demand data are required for each TOU period. For the CAC 

and HP analysis, this data is provided from building simulations. The simulation approach is 

described in more detail in Chapter 7. Briefly, in this approach a representative set of small 

commercial building is simulated at several SEER levels across the full set of weather locations 

defined in the TMY2 data set.b The simulation output for SEER 13 is taken as the baseline. As 

b

 TMY means typical meteorological year; version 3 of this dataset is the most recent. 

8-28 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

with the residential data, a set of accounts are created by pairing each building in the simulation 

set with each utility in its region. For the commercial analysis the regions are defined as census 

divisions. Once a building is assigned to a utility, the tariff is assigned automatically based on the 

annual peak demand and/or energy consumption and the tariff rules. For each account and each 

SEER level, monthly energy and demand values, by TOU period if necessary, are determined 

from the hourly simulation output. With this data, monthly bills can be calculated using the 

tariffs. 

Given the monthly bills, the bill savings in dollars for each account at each SEER level 

are determined relative to the baseline bill. The EMP can be calculated by taking the ratio of the 

bill savings to the energy savings. Note that, as far as the analysis is concerned, the EMP is a 

derived quantity that is used for information purposes only— the LCC uses the total annual bill 

savings for each customer directly. 

The commercial tariff data were last updated in 2004. To convert to 2008 dollars, two 

datasets were used: The report Average Regulated Retail Price of Electricity for the years 2004 

through 2007,16 and the EEI Typical Bill reports for 2007 to 2008.17 Based on these data, a 

weighted-average price escalation factor for each region was calculated using consumer counts 

as the weights. The consumer counts come from the most recent EIA Form 861 data, which is for 

2006.18 EIA data from 2003 through 2006 were used to determine how much the rate of price 

escalation differs on average between the publicly vs. privately owned utility companies. 

To give an indication of the prices obtained with this methodology, Table 8.2.17 shows 

the regional average values of the empirical marginal price at the SEER levels simulated. These 

regional averages were calculated based on population-weighting of the building simulation 

sample. The table also shows the scaling factors used to convert from 2004 to 2008 nominal 

dollars. Note that the EMP varies by SEER level, and this variation may be non-monotonic. This 

behavior results from the complex block structures for both demand and energy charges that 

exist in commercial tariffs.12 

Table 8.2.17 Effective Marginal Price by Region for the Commercial Building Sample 

(¢/kWh). 

Census 

Division 

Marginal Prices cents/kWh 

Scaling 

Factor* 

Central Air Conditioners 

SEER 14 SEER 16 SEER 19 SEER 14 

Heat Pumps 

SEER 16 SEER 19 

1 

2 

3 

4 

5 

6 

7 

8 

9 

32.7 22.1 25.3 

25.0 17.4 19.6 

22.2 14.3 16.6 

7.4 6.6 6.9 

14.6 12.3 13.1 

10.7 9.5 10.0 

17.5 14.8 16.0 

10.9 9.8 10.1 

12.7 12.2 12.5 

28.5 

22.6 

19.0 

8.0 

14.6 

10.3 

16.3 

13.2 

13.6 

19.5 

15.4 

12.2 

6.5 

11.7 

9.1 

13.5 

9.8 

11.6 

21.9 

17.4 

14.1 

6.9 

12.6 

9.4 

14.5 

10.6 

11.8 

1.44 

1.15 

1.25 

1.07 

1.36 

1.28 

1.34 

1.18 

1.09 

* The scaling factors used to convert from 2004 to 2008 dollars . 

8-29 

EERE-2008-BT-STD-0006 COMMENT 54
 

8.2.3.2 Electricity Price Trend 

The electricity price trend provides the relative change in electricity prices for future 

years out to the year 2047. 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 applies a projected trend in national average electricity prices to each customer’s 

energy prices. Of the following four scenarios, the LCC analysis uses the April 2009 update to 

the AEO 2009 reference price scenario: 

1. Constant energy prices at 2008 values (Constant index at 2008 = 1.0) 

2. AEO 2009, High Growth (“High Growth” in Figure 8.2.1). 

3. AEO 2009, Reference Case (“Reference” in Figure 8.2.1) 

4. AEO 2009, Low Growth (“Low Growth” in Figure 8.2.1) 

Figure 8.2.1 shows the trends for the three AEO 2009 residential price projections where 

prices are assumed to change. DOE extrapolated the values in later years (i.e., after 2030) from 

their relative sources because AEO 2009 does not forecast beyond 2030. To arrive at values for 

these later years, DOE used the price trend from 2020 to 2030 of the forecast to establish prices 

in the years 2030 to 2047. This method of extrapolation is in line with methods currently used 

by the EIA to forecast fuel prices for the Federal Energy Management Program. 

The default electricity price trend scenario used in the LCC analysis is the trend from the 

April 2009 update to the AEO 2009 Reference Case, which is the middle line in Figure 8.2.1 

Spreadsheets used in calculating the LCC have the capability to analyze the other electricity 

price trend scenarios, namely, the AEO 2009 High Growth and the AEO 2009 Low Growth price 

trends and constant energy prices. A similar set of trend scenarios for the commercial sector is 

shown in Figure 8.2.2. 

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EERE-2008-BT-STD-0006 COMMENT 54
2007 

2009 

2011 

2013 

2015 

2017 

2019 

2021 

2023 

2025 

2027 

2029 

2031 

2033 

2035 

2037 

2039 

2041 

2043 

2045 

2047 

2007 

2009 

2011 

2013 

2015 

2017 

2019 

2021 

2023 

2025 

2027 

2029 

2031 

2033 

2035 

2037 

2039 

2041 

2043 

2045 

2047 

Residential Prices 

0.80 

0.85 

0.90 

0.95 

1.00 

1.05 

1.10 

1.15 

1.20 

1.25 

1.30 

Index 2008=1.00

Low Grow t h 

R e f e renc e 

H i gh G r o w t h 

Years 

Figure 8.2.1 Electricity Price Trends for Residential Rates to 2047 

Commercial Prices 

0.80 

0.85 

0.90 

0.95 

1.00 

1.05 

1.10 

1.15 

1.20 

1.25 

Index 2008=1.00

Low Grow t h 

R e f e renc e 

H i gh G r o w t h 

Years 

Figure 8.2.2 Electricity Price Trends for Commercial Rates to 2047 

8-31 

EERE-2008-BT-STD-0006 COMMENT 54
 

8.2.3.3 Repair Cost 

The repair cost is the cost to the consumer for replacing or repairing components in the 

BVM equipment that have failed. The assumed annualized repair cost for baseline efficiency 

central air-conditioning and heat pump equipment (i.e., the cost the consumer pays annually for 

repairing the equipment) and equipment with efficiencies of 13 SEER and greater are based on 

the following expression: 

EQPSTD RCSTD = RCBase • • (mr ) • (str ) Eq. 8.2.6 

EQPBASE 

Where: 

RCSTD = repair cost at a standard efficiency level (e.g., level 2, 3, etc.) 

RCBASE = repair cost at the base efficiency level (level 1) 

EQP STD = equipment price (consumer price for only the equipment) at a standard 

level, 

EQP BASE = equipment price (consumer price for only the equipment) at the base 

efficiency level, 

mr = mechanical contractor markup index in region r 

str = state and local tax rate index (factor relative to national average) 

Data on average repair costs are scarce in published sources. However, based on 

information in a few consumer advice websites and discussions with service representatives, it 

appears that the range of values for parts and labor for major repairs such as replacing a 

compressor is between $700 and $150019. Furthermore, it appears that compressor replacements 

are rarely needed before about the eighth year and are often covered by warranty, if needed. In 

addition, if the equipment is older than 15 years, it is usually economically rational to replace the 

entire system rather than to incur the cost of a major repair for the limited average equipment life 

remaining. Because this is a range rather than a specific value associated with a particular 

technology, DOE applied the range to all classes and assumed that the range included average 

national values for wholesale markups, mechanical contractor markups, and sales taxes. 

Through 14 SEER, system technology generally does not incorporate sophisticated 

electronic components, which are believed to incur higher repair costs. Increases in SEER are 

generally achieved through more efficient single-speed compressors or more efficient and/or 

larger heat exchanger coils. Systems with efficiencies beyond 14 SEER start to incorporate twospeed and variable-speed fans, as well as larger coils and more complex electronics, all of which 

are expected to be more susceptible to failure and cost more to repair. 

Table 8.2.18 shows the basic average repair costs by standard level for split-system and 

single package central air conditioners and heat pumps. Since equipment prices are a function of 

variables that are represented by distributions rather than single point values (e.g., manufacturer, 

distributor, dealer, and builder markups, installation costs, and sales tax), repair costs are actually 

represented by a distribution of values rather than just the average values shown in Table 8.2.18. 

8-32 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Table 8.2.18 Central Air Conditioner and Heat Pump Basic Average Repair Costs by 

Efficiency Level 

Efficiency 

Level 

Repair Costs for Representative Standard-Compliant Products 

2008$ 

Splitsystem AC 

(CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package HP 

Level 1 63.48 63.48 63.48 63.48 63.48 

Level 2 65.44 65.50 65.41 67.13 65.42 

Level 3 67.51 67.50 67.45 69.63 67.89 

Level 4 69.93 69.64 69.00 73.23 71.44 

Level 5 72.65 71.23 70.50 76.19 74.56 

Level 6 75.96 72.86 72.14 79.90 78.20 

Level 7 80.18 74.54 74.24 84.28 82.50 

Level 8 85.03 76.28 77.84 90.48 86.79 

Level 9 NA 78.08 81.68 NA NA 

Level 10 NA 81.90 85.80 NA NA 

Level 11 NA 85.97 88.03 NA NA 

Level 12 NA 90.34 NA NA NA 

Level 13 NA 95.04 NA NA NA 

Level 14 NA 100.08 NA NA NA 

Because labor rates and sales taxes vary across the country and repair costs also vary for 

any given efficiency level for each product type, Table 8.2.19 shows the average repair costs by 

region of the country and product type for the largest product classes. 

Table 8.2.19 Central Air Conditioner and Heat Pump Average Repair Costs by Efficiency 

Level and Region 

Efficiency 

Level 

Average Repair Costs for Representative StandardCompliant Products 

2008$ 

Splitsystem 

AC (CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP

 National Average 

Level 1 69 68 68 69 71 

Level 2 71 70 70 73 73 

Level 3 73 72 72 75 76 

Level 4 76 75 74 79 80 

Level 5 79 76 76 82 84 

Level 6 82 78 77 86 88 

Level 7 87 80 80 91 92 

Level 8 92 82 83 98 97 

Level 9 NA 84 87 NA NA 

Level 10 NA 88 92 NA NA 

Level 11 NA 92 94 NA NA 

Level 12 NA 97 NA NA NA 

Level 13 NA 102 NA NA NA 

Level 14 NA 107 NA NA NA 

8-33 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8.2.19 (contd) 

Efficiency 

Level 

Average Repair Costs for Representative StandardCompliant Products 

2008$ 

Splitsystem 

AC (CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP

 Hot-Humid Region 

Level 1 68 68 68 68 71 

Level 2 70 70 70 72 73 

Level 3 72 72 72 74 76 

Level 4 75 74 74 78 80 

Level 5 78 76 75 81 83 

Level 6 81 78 77 85 87 

Level 7 86 80 79 90 92 

Level 8 91 82 83 97 97 

Level 9 NA 83 87 NA NA 

Level 10 NA 88 92 NA NA 

Level 11 NA 92 94 NA NA 

Level 12 NA 97 NA NA NA 

Level 13 NA 102 NA NA NA 

Level 14 NA 107 NA NA NA

 Hot-Dry Region 

Level 1 71 71 71 71 74 

Level 2 73 73 73 75 77 

Level 3 76 76 75 78 79 

Level 4 78 78 77 82 84 

Level 5 81 80 79 85 87 

Level 6 85 82 81 89 91 

Level 7 90 83 83 94 96 

Level 8 95 85 87 101 102 

Level 9 NA 87 91 NA NA 

Level 10 NA 92 96 NA NA 

Level 11 NA 96 98 NA NA 

Level 12 NA 101 NA NA NA 

Level 13 NA 106 NA NA NA 

Level 14 NA 112 NA NA NA

 Rest of Country 

Level 1 69 69 69 69 72 

Level 2 71 71 71 73 74 

Level 3 73 73 73 75 77 

Level 4 76 75 75 79 81 

Level 5 79 77 76 82 84 

Level 6 82 79 78 86 88 

Level 7 87 81 80 91 93 

Level 8 92 82 84 98 98 

Level 9 NA 84 88 NA NA 

Level 10 NA 89 93 NA NA 

Level 11 NA 93 95 NA NA 

Level 12 NA 98 NA NA NA 

Level 13 NA 103 NA NA NA 

Level 14 NA 108 NA NA NA 

8-34 

EERE-2008-BT-STD-0006 COMMENT 54
 

8.2.3.4 Maintenance Cost 

The maintenance cost is the routine annual cost to the consumer of maintaining 

equipment operation. The maintenance cost excludes the cost associated with the replacement or 

repair of components that have failed (discussed in section 8.2.3.3). It is the cost associated with 

general maintenance (e.g., checking and maintaining refrigerant charge levels, cleaning heat 

exchanger coils). 

Virtually no published data are available on annual maintenance cost per unit. DOE 

estimated the annualized maintenance costs for CAC products based on fragmentary data 

available on the internet. The cost of the basic preventative maintenance for an individual CAC 

unit his specified as range of values from $20 per year (2008$) for minimal maintenance 

(homeowner replaces the unit’s air filter two times per year) to an advertised full maintenance 

service at $120 (2008$) per year.20 The full maintenance service involved the following 

activities: 

For the Indoor Component: 

• Inspect refrigerant lines for signs of leakage 

• Check and maintain standard air filters 

• Check operating temperatures 

• Check blower/air handler operation and lubricate as necessary 

• Check blower belt and tension 

• Check condensate drain and maintain as necessary 

• Check operational controls and thermostat 

For the Outdoor Component: 

• Inspect refrigerant lines for signs of leakage 

• Inspect and clean condenser coil as necessary 

• Check condenser fan operation and lubricate as necessary 

• Check operation and condition of the compressor contactor 

• Check system voltage 

• Check operating temperatures 

Data were not available to indicate how maintenance costs vary with equipment 

efficiency, but stakeholder comments on the Framework Document indicated that they likely 

increase as equipment efficiency increases. DOE decided to use preventative maintenance costs 

that increase as equipment efficiency increases. The costs were also expected to vary regionally 

with labor costs. Installation costs vary in the same geographic pattern, so average national costs 

were multiplied times the installation cost index. 

EQP M STD = M Base • STD • (icr ) Eq. 8.2.7 

EQPBASE 

8-35 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 Where:
 

MSTD = repair cost at a standard efficiency level (e.g., level 2, 3, etc.)
 

MBASE = repair cost at the base efficiency level (level 1)
 

EQP STD = equipment price (consumer price for only the equipment) at a standard 

level, 

EQP BASE = equipment price (consumer price for only the equipment) at the base 

efficiency level, 

icr = installation cost index in region r (factor relative to national average). 

Table 8.2.20 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs 

by Efficiency Level 

Efficiency 

Level 

Maintenance Cost for Representative Standard-Compliant 

Products 2008$ 

SplitSystem AC 

(CoilOnly) 

SplitSystem AC 

(BlowerCoil) 

SplitSystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP 

Level 1 70.00 70.00 70.00 70.00 70.00 

Level 2 72.16 72.22 72.13 74.03 72.13 

Level 3 74.44 74.43 74.37 76.78 74.86 

Level 4 77.11 76.79 76.09 80.75 78.77 

Level 5 80.11 78.54 77.74 84.01 82.22 

Level 6 83.76 80.34 79.55 88.10 86.23 

Level 7 88.41 82.20 81.86 92.93 90.97 

Level 8 93.76 84.11 85.83 99.77 95.71 

Level 9 NA 86.10 90.06 NA NA 

Level 10 NA 90.31 94.61 NA NA 

Level 11 NA 94.80 97.07 NA NA 

Level 12 NA 99.62 NA NA NA 

Level 13 NA 104.80 NA NA NA 

Level 14 NA 110.36 NA NA NA 

Level 15 NA NA NA NA NA 

Level 16 NA NA NA NA NA 

Because labor rates and sales taxes vary across the country and maintenance costs also 

vary for any given efficiency level for each product type, Table 8.2.21 shows the average repair 

costs by region of the country and product type for the largest product classes. 

8-36 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 8.2.21 Central Air Conditioner and Heat Pump Basic Average Maintenance Costs 

by Efficiency Level 

Efficiency 

Level 

Average Maintenance Costs for Representative StandardCompliant Products 2008$ 

Splitsystem 

AC (CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP 

National Average 

Level 1 75 75 75 75 75 

Level 2 77 77 77 79 77 

Level 3 80 80 80 82 80 

Level 4 83 82 82 86 84 

Level 5 86 84 83 90 88 

Level 6 90 86 85 94 92 

Level 7 95 88 88 100 97 

Level 8 100 90 92 107 103 

Level 9 NA 92 96 NA NA 

Level 10 NA 97 101 NA NA 

Level 11 NA 102 104 NA NA 

Level 12 NA 107 NA NA NA 

Level 13 NA 112 NA NA NA 

Level 14 NA 118 NA NA NA

 Hot-Humid Region 

Level 1 48 48 48 48 48 

Level 2 50 50 50 51 50 

Level 3 51 51 51 53 52 

Level 4 53 53 52 56 54 

Level 5 55 54 54 58 57 

Level 6 58 55 55 61 59 

Level 7 61 57 56 64 63 

Level 8 65 58 59 69 66 

Level 9 NA 59 62 NA NA 

Level 10 NA 62 65 NA NA 

Level 11 NA 65 67 NA NA 

Level 12 NA 69 NA NA NA 

Level 13 NA 72 NA NA NA 

Level 14 NA 76 NA NA NA 

 Hot-Dry Region 

Level 1 93 93 93 93 93 

Level 2 96 96 96 98 96 

Level 3 99 99 99 102 99 

Level 4 102 102 101 107 105 

Level 5 106 104 103 112 109 

Level 6 111 107 106 117 115 

Level 7 117 109 109 123 121 

Level 8 125 112 114 133 127 

Level 9 NA 114 120 NA NA 

Level 10 NA 120 126 NA NA 

Level 11 NA 126 129 NA NA 

Level 12 NA 132 NA NA NA 

Level 13 NA 139 NA NA NA 

Level 14 NA 147 NA NA NA 

8-37 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

Table 8.2.21 (contd) 

Efficiency 

Level 

Average Maintenance Costs for Representative StandardCompliant Products 2008$ 

Splitsystem 

AC (CoilOnly) 

Splitsystem AC 

(BlowerCoil) 

Splitsystem 

HP 

Single 

Package 

AC 

Single 

Package 

HP

 Rest of Country 

Level 1 85 85 85 85 85 

Level 2 88 88 88 90 88 

Level 3 91 91 91 94 91 

Level 4 94 94 93 98 96 

Level 5 98 96 95 102 100 

Level 6 102 98 97 107 105 

Level 7 108 100 100 113 111 

Level 8 114 103 105 122 117 

Level 9 NA 105 110 NA NA 

Level 10 NA 110 115 NA NA 

Level 11 NA 116 118 NA NA 

Level 12 NA 121 NA NA NA 

Level 13 NA 128 NA NA NA 

Level 14 NA 135 NA NA NA 

8.2.3.5 Lifetime 

DOE defined lifetime as the age when a CAC unit is retired from service. DOE used 

national survey data, along with manufacturer shipment data, to calculate the distribution of air 

conditioner and heat pump lifetimes. This analysis concluded that the mean lifetime for central 

air conditioners is 19.01 years and the mean lifetime for heat pumps is 16.24 years. 

EIA’s RECS 21 surveys occupied primary housing units and notes the presence of a range 

of appliances, and places the age of each appliance into several-year bins. The U.S. Census’s 

American Housing Survey (AHS)22 surveys all housing, including vacant and second homes, and 

allowed DOE to adjust the RECS data to reflect some appliance use outside of primary 

residences. AHS also has a larger sample size, with correspondingly smaller sampling error. By 

combining these survey results with the known history of appliance shipments (collected from 

manufacturer trade associations) DOE estimated the fraction of appliances of a given age still in 

operation. This survival function, which DOE assumed has the form of a cumulative Weibull 

distribution, provides an estimate of the average and median appliance lifetime. 

The Weibull distribution is a probability distribution function commonly used to measure 

failure rates.23 Its form is similar to an exponential distribution, which would model a fixed 

failure rate, except that it allows for a failure rate which changes over time in a particular 

fashion. The cumulative distribution takes the form: 

8-38 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

β ⎛ x−θ ⎞ −⎜ ⎟ P(x) = e ⎝ α ⎠ for x > θ and P(x) = 1 for x ≤ θ, Eq. 8.2.8

 Where: 

P(x) = probability that the appliance is still in use at age x, 

x = appliance age, 

α = the scale parameter, which is the decay length in an exponential distribution, 

β = the shape parameter, which determines the way in which the failure rate changes 

in time, and 

θ = the delay parameter, which allows for a delay before any failures occur. 

When β = 1, the failure rate is constant over time, and this distribution takes the form of a 

cumulative exponential distribution. For the case of appliances, β is commonly greater than 1, 

which results from a rising failure rate as the appliance ages. A plot of a Weibull distribution 

(DOE’s calculated air conditioner survival function) with α = 20.29, β = 1.89, and θ = 1.0 is 

shown Figure 8.2.5. 

The RECS survey is DOE’s primary resource for air conditioner and heat pump ages. For 

several appliances, including air conditioners, the survey asks respondents to place the 

appliance’s age into one of these bins: 

• Less than 2 years, 

• 2 to 4 years, 

• 5 to 9 years, 

• 10 to19 years, and 

• Over 20 years. 

The RECS survey has been conducted every three or four years for the last several 

decades. For this analysis, DOE used the surveys conducted in 1990, 1993, 1997, 2001, and 

2005. The AHS Survey is conducted every other year, and DOE used the surveys conducted 

from 1991 to 2007. DOE used the AHS count of housing units with air conditioners to scale the 

RECS data to better match the total installed stock. DOE used the surveys’ household-level 

micro-data to count households with shared or multiple air conditioners or heat pumps. 

Households which did not know the age of their appliance were allocated among the remaining 

age bins according to the distribution of respondents who did report their appliance age. 

DOE used RECS appliance age data, AHS total installed stock data, and the history of 

appliance shipments to generate an estimate of the survival function. For example, DOE summed 

the total shipments from 5 to 9 years prior to the RECS survey, and compared this number with 

the number of units of those ages still in use, to calculate one approximation of the surviving 

appliance fraction within that age bin. The AHS total stock acts as an “all ages” bin. By 

combining the age bins from five RECS surveys and 9 AHS surveys with shipments data, DOE 

had enough data to build a fit to a Weibull distribution and find the parameters (α, β, θ) that best 

approximate the surviving units, using a least-squares method. Because the first two (youngest) 

RECS bin data tend to have a large scatter relative to the shipments in those years, DOE 

combined the RECS and shipments data in the first two bins. Generally, appliances do not tend 

8-39 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

to fail in large numbers during this period, so combining bins does not appreciably lower the 

accuracy of the shape of the distribution. DOE weighted each bin’s contribution to the sum of 

squares by the inverse of the variance in the survey results, which controls for the changes in 

sample size between RECS bins, between RECS and AHS, and within each survey over time.24 

RECS and AHS have complicated error models; DOE used only the error due to finite sample 

size to determine the variance used to weight each data point’s contribution. The error due to 

sampling is less than one percent for AHS survey data, and typically about five percent for 

RECS age bins. The equation for the sum of squares DOE minimized is therefore 

2 2

(RECS − Surv ) (AHS j − Surv j ) ∑ i i + ∑	 Eq. 8.2.9 

i σ2 σ2
 

i ,RECS j j, AHS
 

Where: 

i = the identifier for a bin from a single RECS, 

j = the identifier for a single AHS survey 

RECSi = the number of appliances reported by RECS in bin i, 

AHSj = the number of appliances reported by AHS in survey year j, 

Survi = the number of surviving appliances in bin i predicted by the Weibull 

distribution applied to the number of appliances shipped 

(a function of α, β, and θ), and 

σi,RECS = the standard error (square root of the variance) of the RECS data point for 

bin i. 

σj,AHS = the standard error (square root of the variance) of the AHS data point for 

year j. 

DOE adjusted the RECS and AHS survey data in several ways to place it on an even 

footing with the historical shipment data. In particular, DOE adjusted for the fact that the RECS 

survey is scaled to July of its reference year and the AHS survey is conducted in the middle 

portion of the year, while shipment data is provided for each calendar year. Adjustments 

included: 

•	 DOE modeled the additional retirement of older appliances and their replacement by new 

ones which took place in the latter half of the survey year (after a given respondent had 

been surveyed), using the survival function. This had the effect of moving households 

from the older RECS age bins to the youngest age bin. 

•	 For appliances installed directly in new construction, such as central air conditioners, 

DOE added units to the youngest RECS age bin and to the AHS total stock to represent 

half of the new construction for the final year of the survey known to have installed the 

appliance type in question, using data from the U.S. Census. 

•	 DOE assumed that 93 percent of appliances were installed in residences, and 7 percent in 

commercial or other applications not counted by AHS or RECS. 

•	 Households that shared an air conditioner were counted as owning half of one air 

conditioner, and households who reported owning more than one air conditioner were 

counted as owning two. (For AHS surveys before 1997, the number of air conditioners 

8-40 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

was not reported; DOE assumed a linear increase with time in the fraction of homes with 

2 air-conditioning units.) 

Assumptions 

DOE’s lifetime-calculation technique depends on several assumptions: 

•	 Appliance lifetime can be modeled by a survival function. In particular, a Weibull 

distribution is an appropriate survival function.
 

•	 The appliance survival function does not change over time. 

•	 The survival function is independent of other household factors (such as household size, 

region, etc.) as well as product class (within air conditioners or heat pumps). 

•	 The age bin for the appliance as reported by the RECS respondent is correct. 

•	 The historical shipment data is correct. 

•	 The Weibull delay parameter, θ, is limited to between 1 and 5 years. 

Three of these assumptions are of particular importance. The first is the assumption that a 

Weibull distribution is the correct distribution to use for appliance retirement rates. This 

distribution is the standard distribution for use in lifetime analysis, but it is not guaranteed to 

reflect actual consumer behavior. The second assumption is that consumer behavior and 

mechanical appliance lifetime have not changed over time. This assumption required DOE to 

treat all data from different RECS surveys on an equal footing. Using only recent surveys (to 

potentially better reflect recent consumer behavior and appliance lifetime) would result in 

attempted least-squares fits using a small number of data points, leading to large statistical 

uncertainty. 

DOE limited the delay parameter to between one and five years to reflect the range of 

common appliance warranties. A delay of less than one would imply that some appliances fail or 

are replaced within their initial year of use, when they are commonly covered by parts and labor 

warranties. A delay of greater than five implies that no appliances are replaced for some length 

of time after the end of the longest standard warranty. Fits with θ > 5 also commonly show 

nonsensical behavior with sharp changes in consumer behavior or appliance survival 

immediately following the “delay” period. 

Central Air Conditioners 

Table 8.2.22 shows the RECS and AHS data for air conditioners and the corresponding 

total shipments and best-fit Weibull calculation of stock by age bin. Figure 8.2.3 plots the data 

from the RECS portion of the third and fourth columns of Table 8.2.22 against each other to 

show the quality of the fit. Figure 8.2.4 plots the AHS survey total stock against the Weibullbased calculated stock. DOE allowed the delay parameter, θ, to vary only between one and five 

years, which corresponds to common warranty periods (see discussion below); for air 

conditioners and heat pumps the best fit within this range is 1 year. This Weibull distribution is 

characterized by the parameters α = 20.29, β = 1.89, and θ = 1.0, and shown in Figure 8.2.5. This 

distribution has a mean air conditioner lifetime of 19.01 years and a median lifetime of 

17.70 years. 

8-41 

EERE-2008-BT-STD-0006 COMMENT 54
Table 8.2.22 Central Air Conditioners: Comparison of RECS and AHS with Modeled Stock 

Age bin 

RECS 2005 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

23,384,298 

20,606,096 

26,252,849 

29,643,170 

21,121,201 

15,568,739 

15,840,393 

6,611,168 

23,202,596 

18,628,161 

16,908,120 

5,434,630 

Age bin 

RECS 2001 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

20,833,446 

15,707,082 

20,982,218 

23,056,758 

16,179,828 

14,511,234 

14,367,204 

5,583,734 

20,669,235 

14,252,361 

13,670,285 

4,771,136 

Age bin 

RECS 1997 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

16,822,938 

12,555,897 

16,825,109 

17,112,973 

12,213,941 

12,441,915 

10,799,049 

4,046,096 

16,697,701 

11,311,053 

10,843,901 

4,137,030 

Age bin 

RECS 1993 

Shipments RECS Stock Modeled stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

12,781,848 

10,579,559 

14,275,598 

11,535,301 

11,450,065 

9,198,439 

9,410,523 

3,727,973 

12,671,267 

9,572,156 

8,960,434 

3,257,844 

Age bin 

RECS 1990 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

11,836,478 

7,930,531 

15,067,767 

6,644,873 

10,544,271 

7,343,580 

10,136,090 

3,025,410 

11,745,800 

7,200,298 

9,435,899 

1,897,721 

Survey year 

AMERICAN HOUSING SURVEY 

Adjusted AHS Stock Modeled Stock 

2007

2005

2003

2001

1999

1997

1995

1993

1991

 66,850,067 

 63,023,984 

 56,640,747 

 54,080,318 

 48,189,582 

 41,173,857 

 38,446,053 

 35,072,816 

 32,893,755 

67,116,846 

64,173,507 

58,293,705 

53,363,017 

48,428,026 

42,989,684 

38,517,301 

31,793,586 

31,733,007 

8-42 

EERE-2008-BT-STD-0006 COMMENT 54
 

Calculated number of households with AC by bin

25000000 

20000000 

15000000 

10000000 

5000000 

0 

Age bins 

ideal 

0 5000000 10000000 15000000 20000000 25000000 

RECS reported number of households with AC by bin 

Figure 8.2.3 Comparison of DOE Modeled Air Conditioner Age Distribution with RECS 

Reported Stock 

70,000,000 

60,000,000 

AHS surveys 

ideal 

Calculated CAC Stock 50,000,000 

40,000,000 

30,000,000 

20,000,000 

20,000,000 30,000,000 40,000,000 50,000,000 60,000,000 70,000,000 

Adjusted American Housing Survey CAC Stock 

Figure 8.2.4 Comparison of DOE Modeled Total Air Conditioner Stock with Adjusted 

AHS Stock 

8-43 

EERE-2008-BT-STD-0006 COMMENT 54
17.70 

19.01 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

Fraction surviving 

Survival function 

Median lifetime 

Mean lifetime 

0 10 20 30 40 50 

Age (years) 

Figure 8.2.5 Central AC Survival Function, Characterized by Weibull Parameters α = 

20.29, β = 1.89, and θ = 1.0. 

Heat Pumps 

DOE undertook a very similar calculation for heat pumps as it did for central air 

conditioners. The only difference between the heat pump and central air conditioner analyses 

was in the number of AHS survey years included. DOE found that when the heat pump stock 

analysis was done with AHS-reported stock from all nine AHS surveys between 1991 and 2007 

with manufacturer-reported shipments history, an assumed unchanging heat pump lifetime, and 

an assumed 95 percent to five percent residential/commercial market split, the results were 

inconsistent. In the interest of timeliness and consistency, DOE chose to use only the most recent 

four surveys (2001, 2003, 2005, and 2007). Using only the most recent four AHS surveys, DOE 

was able to develop a consistent survival function. Figure 8.2.6 shows the AHS survey results 

plotted against the modeled stock, and shows the contrast between earlier and more recent data. 

The best-fit Weibull parameters for heat pump lifetime are α = 17.04, β = 1.64, and 

θ = 1.0. The resulting calculated mean heat pump lifetime is 16.24 years; the median lifetime is 

14.63 years. Table 8.2.23 lists the (adjusted) heat pumps reported in each of the RECS age bins 

and AHS survey year along with the modeled stock based on the best fit Weibull survival 

function and the manufacturer-provided shipments history. Figure 8.2.7 shows the survival 

function used in the life-cycle cost and national impact analyses. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 8.2.23 Heat Pumps: Comparison of RECS and AHS Stock to Stock Calculated from 

a Weibull Survival Function 

Age Bin 

RECS 2005 

Shipments RECS Dtock Modeled Dtock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

7,656,050 

5,437,867 

7,609,488 

5,421,606 

5,903,720 

4,186,956 

4,167,868 

1,172,137 

7,531,948 

4,545,002 

3,947,892 

947,223 

Age Bin 

RECS 2001 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

5,693,105 

4,318,866 

6,413,059 

3,320,977 

4,564,988 

3,641,519 

3,191,956 

1,273,838 

5,593,500 

3,626,504 

3,383,920 

622,144 

Age Bin 

RECS 1997 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

4,615,287 

3,500,621 

5,271,716 

1,671,785 

4,550,375 

3,871,200 

3,828,288 

575,473 

4,536,486 

2,914,225 

2,852,397 

319,727 

Age Bin 

RECS 1993 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

3,582,387 

3,514,244 

3,308,542 

822,935 

3,847,273 

3,043,034 

2,425,988 

523,705 

3,515,747 

2,938,354 

1,803,756 

139,039 

Age Bin 

RECS 1990 

Shipments RECS Stock Modeled Stock 

0 to 4 yrs. 

5 to 9 yrs. 

10 to 19 yrs. 

20 or more yrs. 

3,637,163 

2,494,052 

2,327,546 

600,009 

2,929,208 

3,030,644 

1,846,344 

168,614 

3,565,942 

2,112,769 

1,356,527 

111,330 

Survey year 

AMERICAN HOUSING SURVEY 

Adjusted AHS Stock Modeled Stock 

2007

2005

2003

2001

1999

1997

1995

1993

1991

 16,718,490 

 16,130,513 

 14,318,151 

 13,653,239 

 13,331,680 

 13,658,054 

 11,460,574 

 10,412,946 

 9,349,377 

18,037,674 

16,123,461 

14,017,726 

12,564,764 

11,290,213 

10,091,692 

8,980,076 

7,977,051 

7,165,773 

8-45 

EERE-2008-BT-STD-0006 COMMENT 54
Modeled stock of heat pumps

20,000,000 

15,000,000 

10,000,000 

5,000,000 

0 

Recent AHS surveys 

Older AHS surveys 

ideal 

0 5,000,000 10,000,000 15,000,000 20,000,000 

AHS reported stock of heat pumps 

Figure 8.2.6 Comparison of DOE Modeled Total Heat Pump Stock with Adjusted AHS 

Stock 

14.63 

16.24 

0.0 

0.2 

0.4 

0.6 

0.8 

1.0 

1.2 

Fraction surviving 

Survival function 

Median lifetime 

Mean lifetime 

0 5 10 15 20 25 30 35 40 45 50 

Age (years) 

Figure 8.2.7 Heat Pump Survival Function, Characterized by Weibull Parameters α = 

17.04, β = 1.64, and θ = 1.0. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

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 LCC analysis by estimating the cost of 

capital for individuals and companies that purchase CAC products. 

In the case of individual households, the financing of purchasing products installed in 

new homes is different than the financing of appliances bought directly by consumers (i.e., as a 

replacement for a failed unit or as a new purchase for an existing household that does not already 

own the appliance). Thus, DOE used different discount rates for these residential purchases. 

Residential Discount Rates for Products Purchased in Existing Households 

Households use various methods to finance the purchase of major appliances. In 

principle, one could estimate the interest rates on the actual financing vehicles used to purchase 

appliances. However, the frequency with which each financing vehicle is used to purchase an 

appliance is unknown. 

DOE’s approach involved identifying all possible debt or asset classes that might be used 

to purchase the considered appliances, including household assets that might be affected 

indirectly.c

 DOE excluded debt from primary mortgages and the equity of assets considered 

non-liquid (such as retirement accounts), because those financing methods are unlikely to be 

used by households in existing housing to purchase appliances. DOE estimated the average 

percentage shares of the various types of debt and equity in the average U.S. household using 

data from the Federal Reserve Board’s Survey of Consumer Finances (SCF) for 1989, 1992, 

1995, 1998, 2001, 2004, and 2007.25 Table 8.2.24 shows the average percentages of each 

considered type of debt or equity. DOE derived the mean percentages of each source of financing 

for the seven years surveyed. 

An indirect effect would arise if a household sold assets in order to pay off a loan or credit card debt that might 

have been used to finance the appliance purchase. 

8-47 

c 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 8.2.24 Types of Household Debt and Equity by Percentage Shares 

Debt or Equity 

Distribution % 

1989 1992 1995 1998 2001 2004 2007 Mean 

Home equity loan 4.3 4.5 2.7 2.8 2.8 4.4 4.6 3.7 

Credit card 1.6 2.1 2.6 2.2 1.7 2.0 2.4 2.1 

Other installment loan 2.8 1.7 1.4 1.7 1.1 1.3 1.1 1.6 

Other residential loan 4.4 6.9 5.2 4.3 3.1 5.8 7.1 5.3 

Other line of credit 1.1 0.6 0.4 0.2 0.3 0.5 0.3 0.5 

Checking account 5.8 4.7 4.9 3.9 3.6 4.2 3.4 4.4 

Savings or money market account 19.2 18.8 14.0 12.8 14.2 15.1 13.0 15.3 

Certificate of deposit 14.5 11.7 9.4 7.0 5.4 5.9 6.5 8.6 

Savings bond 2.2 1.7 2.2 1.1 1.2 0.9 0.7 1.4 

Bonds 13.8 12.3 10.5 7.0 7.9 8.4 6.7 9.5 

Stocks 22.4 24.0 25.9 36.9 37.5 28.0 28.6 29.0 

Mutual funds 8.0 11.1 20.9 20.1 21.3 23.4 25.5 18.6 

Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 

2007. 

DOE also estimated interest or return rates associated with each type of equity and debt. 

The source for interest rates for loans, credit cards, and lines of credit was the Federal Reserve 

Board’s SCF for 1989, 1992, 1995, 1998, 2001, 2004, and 2007. Table 8.2.25 shows the average 

nominal rates in each year and the inflation factors used to calculate real rates. DOE calculated 

effective interest rates for home equity loans in a similar manner as for mortgage rates, because 

interest on both such loans is tax deductible. Table 8.2.26 shows the average effective real rates 

in each year and the mean rate across years. Because the interest rates for each type of household 

debt reflect economic conditions throughout numerous years, they are expected to be 

representative of rates that may be in effect in 2016. 

Table 8.2.25 Average Nominal Interest Rates for Household Debt 

Debt 

Average Nominal Interest Rate % 

1989 1992 1995 1998 2001 2004 2007 Mean 

Home equity loan 11.5 9.6 9.6 9.8 8.7 5.7 6.3 7.9 

Credit card* - - 14.2 14.5 14.2 11.7 7.9 9.0 

Other installment loan 9.0 7.8 9.3 7.8 8.7 7.4 12.6 13.4 

Other residential loan 8.8 7.6 7.7 7.7 7.5 6.0 10.4 8.6 

Other line of credit 14.8 12.7 12.4 11.9 14.7 8.8 6.3 7.4 

Inflation rate 4.82 3.01 2.83 1.56 2.85 2.66 2.85 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, and 

2007. 

* No data on interest rates available for credit cards in 1989 or 1992. 

8-48 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table 8.2.26 Average Real Effective Interest Rates for Household Debt 

Debt 

Average Real Effective Interest Rate % 

1989 1992 1995 1998 2001 2004 2007 Mean 

Home equity loan 3.8 4.3 4.4 5.8 3.8 1.9 2.1 3.0 

Credit card* - - 11.0 12.7 11.1 9.1 3.3 3.9 

Other installment loan 4.9 5.8 7.0 6.6 6.1 5.4 9.7 10.7 

Other residential loan 4.0 4.7 4.8 6.0 4.6 3.3 5.8 6.0 

Other line of credit 9.6 9.4 9.3 10.2 7.3 6.0 3.4 4.4 

Sources: Federal Reserve Board. Survey of Consumer Finances (SCF) for 1989, 1992, 1995, 1998, 2001, 2004, 

and 2007. 

* No data on interest rates available for credit cards in 1989 or 1992. 

No similar rate data are available from the SCF for classes of assets, so the Department 

derived that information from national historical data. The interest rates associated with 

certificates of deposit,26 savings bonds,27 and bonds (AAA corporate bonds)28 were collected 

from Federal Reserve Board time-series data for 1977–2008. DOE assumed rates on checking 

accounts to be zero. Rates on savings and money market accounts came from Cost of Savings 

Index data covering 1984–2008. 29 The rates for stocks are the annual returns on the Standard and 

Poor’s 500 for 1977–2008. 30 Rates for mutual funds are a weighted average of the stock rates 

(two-thirds weight) and the bond rates (one-third weight) in each year for 1977–2008. DOE 

adjusted the nominal rates to real rates using the annual inflation rate for each year. Average 

nominal and real interest rates for the classes of household assets are listed in Table 8.2.27. 

Because the interest and return rates for each type of asset reflect economic conditions 

throughout numerous years, they are expected to be representative of rates that may be in effect 

in 2016. 

Table 8.2.27 Average Nominal and Real Interest Rates for Household Equity 

Type of Equity 

Average Nominal 

Rate % 

Average Real 

Rate % 

Checking account - 0.0 

Savings and money market accounts 5.4 2.2 

Certificate of deposit 6.6 2.3 

Savings bond 7.7 3.3 

Bonds 8.5 4.1 

Stocks 11.6 7.1 

Mutual funds 10.3 5.8 

Table 8.2.28 summarizes the mean real effective rates of each type of equity or debt. 

DOE determined the average percentage of each type of debt and asset using SCF data for 1989, 

1992, 1995, 1998, 2001, 2004, and 2007. Each year of SCF data provides the percents of debts 

and assets for U.S. households. DOE averaged those percentages for the seven years of survey 

data to arrive at the percentages shown in Table 8.2.28. The average rate across all types of 

household debt and equity, weighted by the percentages of each type, is 4.8 percent. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 8.2.28 Average Interest on Household Debt and Equity 

Type of Debt or Equity 

Average Percentage of 

Household Debt plus Equity* Mean Effective Real Rate %** 

Home equity loan 3.7 3.9 

Credit card 2.1 10.7 

Other installment loan 1.6 6.0 

Other residential loan 5.3 4.4 

Other line of credit 0.5 8.8 

Checking account 4.4 0.0 

Savings and money market account 15.3 2.2 

Certificate of deposit 8.6 2.3 

Savings bond 1.4 3.3 

Bonds 9.5 4.1 

Stocks 29.0 7.1 

Mutual funds 18.6 5.8 

Total/weighted-average discount rate 100.0 4.8 

* Not including primary mortgage or retirement accounts.
 

** Adjusted for inflation and, for home equity loans, tax deduction of interest.
 

DOE developed a normal probability distribution of interest rates for each asset type by 

using the mean value and standard deviation from the distribution. To account for variation 

among households, DOE sampled a rate for each household from the distributions for the 

appropriate asset class. Appendix 8-E presents the probability distributions for each class that 

DOE used in the LCC and PBP analyses. 

Residential Discount Rates for Products Installed in New Housing 

Appliances installed in new homes (“new-housing appliances”) are purchased as part of 

the home, which is almost always financed with a mortgage loan. DOE estimated discount rates 

for new-housing appliances using the effective real (after-inflation) mortgage rate for 

homebuyers. This rate corresponds to the interest rate after deduction of mortgage interest for 

income tax purposes and after adjusting for inflation (using the Fisher formula).d

 For example, a 

six-percent nominal mortgage rate has an effective nominal rate of 4.5 percent for a household at 

the 25-percent marginal tax rate. When adjusted for inflation of two percent, the effective real 

rate becomes 2.45 percent. 

The data source DOE used for mortgage interest rates is the SCF in 1989, 1992, 1995, 

1998, 2001, 2004, and 2007. Using the appropriate SCF data for each year, DOE adjusted the 

mortgage interest rate for each relevant household in the SCF for mortgage tax deduction and 

inflation (see Table 8.2.29). In cases where the effective interest rate is equal to or below the 

inflation rate (resulting in a negative real interest rate), DOE set the real effective interest rate to 

zero. 

d

 Fisher formula is given by: Real Interest Rate = [(1 + Nominal Interest Rate) / (1 + Inflation Rate)] – 1. 

8-50 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

The average nominal mortgage rate carried by homeowners in these six years was 

7.9 percent. Since the mortgage rates carried by households in these years were established over 

a range of time, DOE believes they are representative of rates that may apply when amended 

standards take effect. After adjusting for inflation and interest tax deduction, effective real 

interest rates on mortgages across the six surveys averaged 3.0 percent. 

Table 8.2.29 Data Used to Calculate Real Effective Mortgage Rates 

Year 

Mortgage Interest Rates in Selected Years % 

Average Nominal 

Interest Rate Inflation Rate58 

Marginal Tax Rate 

Applicable to Mortgage 

Interest59 

Average Real 

Effective Interest Rate 

1989 9.7 4.82 24.3 2.4 

1992 9.1 3.01 23.4 3.8 

1995 8.2 2.83 24.1 3.3 

1998 7.9 1.56 23.9 4.4 

2001 7.6 2.85 22.9 2.9 

2004 6.2 2.66 20.6 2.2 

2007 6.3 2.85 21.6 2.1 

Average 7.9 3.0 

To account for variation among households, DOE sampled a rate for each household in 

the RECS samples from a distribution of mortgage rates. DOE developed the distribution based 

on the SCF data. Appendix 8-E presents the probability distribution that DOE used in the LCC 

and PBP analyses. 

Commercial Discount Rate 

The commercial discount rate for central air conditioners is estimated using cost of 

capital data for firms that might occupy or rent out office space in small office buildings. DOE 

estimated the cost of equity using the capital asset pricing model (CAPM). The CAPM assumes 

that the cost of equity (ke) for a particular company is proportional to the 

systematic risk faced by that company, where high risk is associated with a high cost of equity 

and low risk is associated with a low cost of equity. The systematic risk facing a firm is 

determined by several variables: the risk coefficient of the firm (β), the expected return on risk 

free assets (Rf), and the equity risk premium (ERP). The risk coefficient of the firm indicates the 

risk associated with that firm relative to the price variability in the stock market. The expected 

return on risk-free assets is defined by the yield on long-term government bonds. The ERP 

represents the difference between the expected stock market return and the risk-free rate. 

Described below, we estimate the cost of equity for each sector with the CAPM model as 

follows: 

ke = Rf + (β • ERP) Eq. 8.2.10 

Where: 

ke = the cost of equity, 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Rf = the expected return of the risk-free asset (long term treasury bonds), 

β = the beta of the sector, and ERP is the expected equity risk premium. 

From data available on β for individual U.S. commercial companies, estimated market 

ERP from Damodaran Online31 and long term treasury bond rates for Rf from the Economic 

Report of the President32, we calculate the cost of equity ke for each firm. 

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. 

k = R + R , d f a 

Where: 

kd = the cost of debt financing for each firm, 

Rf = the expected return on risk-free assets, and 

Ra = is 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 weighted average cost 

of capital worksheets for 2001-2008. 

Finally, as inflation has already been accounted for in both the cost of debt and the cost of 

equity, the real weighted average cost of capital WACCr (real discount rate) is calculated as 

follows: 

 WACCr =ke• we+ kd• wd Eq. 8.2.11 

Where: 

ke = the cost of equity, 

we = the percent of equity financing, 

kd = the cost of debt, and 

wd = the percent of debt financing. 

The discount rate is estimated for each firm for 2009. The two sources of cost of capital 

data that are used in our calculations are individual company data from Damodaran Online’s 

Data Page. DOE used Damodaran Online data from the SIC categories with Standard Industrial 

Classification (SIC) 6000-9975, with the exception of Hotels and Gaming (SIC code 7000). 

Broadly speaking, this includes all of the commercial subsectors that could occupy small offices 

that might use a residential-sized central air conditioner. The sample includes 1750 companies 

with usable data. It includes both large and small companies, since it is not clear that small 

offices would be occupied or owned by an entity that was also a small business. The weighted 

average cost of capital for this sample of U.S. companies was 7.56 percent. Nominal rates for 

individual firms varied from 2.58 percent to 14.10 percent, which were fitted to a normal 

distribution truncated at 0 to prevent negative rates. The standard deviation of the statistical 

8-52 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

sample was 1.54 percent. Adjusted for the long-term expected inflation rate of 1.8 percent rate 

from the January, 2009 Economic Report of the President, the discount rate was 5.66 percent, 

which is used as the average real discount rate for central air conditioners purchased for small 

offices. 

8.2.3.7 Effective Date of Standard 

The effective date is the future date when a new standard becomes operative. Pursuant to 

42 U.S.C. 6295(m), the effective date of any new energy efficiency standard for CAC equipment 

will be 5 years after the final rule is published. DOE calculated the LCC for all customers as if 

they each would purchase a new air conditioner or heat pump in the year the standard takes 

effect. Consistent with its published regulatory agenda, DOE assumed that the final rule would 

be issued in 2011 and that, therefore, the new standards would take effect in 2016 and used these 

dates in the NOPR analyses. It based the cost of the equipment on this year; however, all dollar 

values are expressed in 2008$. Annual energy prices are included for the life of the central air 

conditioner or heat pump. 

8.2.3.8 Base Case Distribution of Efficiency Levels 

The market mix of efficiency levels in 2008 is shown in Table 8.2.30 for the four largest 

product classes, the development of which is discussed in chapter 7. This same distribution is 

assumed to prevail in 2016 in the absence of an energy conservation standard above 13 SEER. 

The three smaller product classes (Confined Space A/C, Confined Space heat Pump, and SmallDiameter High Velocity A/C units) currently have not been analyzed. 

Table 8.2.30 2008 Market Distribution of Efficiency Levels by Product Class 

Bin 

Bottom 

of Bin 

Top of 

Bin 

Assumed 

Average 

SEER in Bin 

Split-System AC % SplitSystem HP 

% 

Single 

Package AC 

% 

Single 

Package 

HP % 

CoilOnly BlowerCoil 

1 13 13.25 13.0 24.37% 24.00 50.00 75.00 50.00 

2 13.25 13.75 13.5 55.84% 55.00 32.00 20.00 32.00 

3 13.75 14.25 14.0 4.06% 4.00 11.00 2.00 11.00 

4 14.25 14.75 14.5 5.33% 5.25 5.00 2.00 5.00 

5 14.75 15.25 15.0 3.30% 3.25 2.00 1.00 2.00 

6 15.25 15.75 15.5 2.03% 2.00 NA NA NA 

7 15.75 16.5 16.0 3.55% 3.50 NA NA NA 

8 16.5 17.5 17.0* 1.52% 1.50 NA NA NA 

9 17.5 18.5 18.0 NA 0.70 NA NA NA 

10 18.5 19.5 19.0 NA 0.30 NA NA NA 

11 19.5 20.5 20.0 NA 0.20 NA NA NA 

12 20.5 21.5 21.0 NA 0.20 NA NA NA 

13 21.5 22.5 22.0 NA 0.10 NA NA NA 

14 22.5 23.5 23.0 NA NA NA NA NA 

15 23.5 24.5 24.0 NA NA NA NA NA 

16 24.5 25.5 25.0 NA NA NA NA NA 

* The selected corresponding efficiency level for this bin is 16.5 for coil-only split system air conditioners 

8-53 

EERE-2008-BT-STD-0006 COMMENT 54
 

8.3 PAYBACK PERIOD INPUTS
 

8.3.1 Definition 

The payback period is the amount of time it takes the customer to recover the assumed 

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 (i.e., from a less efficient 

design to a more efficient design) 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 0 percent. 

The equation for PBP is: 

PBP =∆IC/∆OC Eq. 8.3.1 

Where: 

PBC = payback period in years, 

∆ IC = difference in the total installed cost between the more efficient standard level 

equipment (efficiency levels 2,3, etc.) and the baseline efficiency equipment, 

and 

∆OC = difference in first year annual operating costs. 

Payback periods are expressed in years. Payback periods greater than the life of the 

equipment mean that the increased total installed cost of the more efficient equipment is not 

recovered fast enough in reduced operating costs. 

DOE also calculates a rebuttable payback period, which is the time it takes the consumer 

to recover the assumed higher purchase cost of more energy-efficient equipment as a result of 

lower energy costs. Numerically, the rebuttable PBP is the ratio of the increase in purchase cost 

(i.e., from a less efficient design to a more efficient design) to the decrease in annual energy 

expenditures; that is, the difference in first year annual energy cost. The calculation excludes 

repair costs and maintenance costs. This type of calculation also is a “simple” payback period. 

8.3.2 Inputs 

The data inputs to PBP are the total installed cost of the equipment to the customer for 

each efficiency level and the annual (first year) operating costs for each efficiency level. 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 (or in the case of rebuttable PBP, only the annual energy cost). The PBP uses the same 

inputs as the LCC analysis described in section 8.2, except that electricity price trends and 

discount rates are not required. Since the PBP is a “simple” (undiscounted) payback, the required 

electricity cost is only for the year in which a new efficient standard is to take effect—in this 

case, the year 2016. The electricity price used in the PBP calculation was the price projected for 

2016, expressed in 2008$. Discount rates are not used in the PBP calculation. 

8-54 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

8.4 SEER AND HSPF RESULTS
 

This section presents the LCC and PBP results for residential CACs and CHPs that are 

used in residential and commercial (small office) applications. As discussed in Section 8.1.1, 

DOE’s approach for conducting the LCC and PBP analysis relied on developing samples of 

households that use each of the products. DOE also characterized the uncertainty of many of the 

inputs to the analysis with probability distributions. DOE used a Monte Carlo simulation 

technique to perform the LCC and PBP calculations on the households in the sample. For each 

set of sample households using the equipment in each product class, DOE calculated the average 

LCC and LCC savings and the median and average PBP for each of the efficiency levels. These 

efficiency levels are also referred to as candidate standard levels (CSLs). 

DOE calculated LCC savings and PBPs relative to the market baseline equipment that it 

assigned to the households and commercial consumers. DOE assigned market baseline 

equipment that is more efficient than some of the CSLs. For that reason, the average LCC 

impacts are not equal to the difference between the LCC of a specific CSL and the LCC of the 

market baseline equipment. 

LCC and PBP calculations were performed 10,000 times on the sample of households 

established for each residential product. Each LCC and PBP calculation was performed on a 

single household that was selected from the sample of the residential observations or 

alternatively, from one of the commercial buildings commercial building using the CAC or CHP 

equipment. The first sampling conducted was based on the probability of whether the given 

observation was a residential or a commercial application. The probability of a residential 

observation was 93 percent, while that of a commercial observation was 7 percent. If the 

observation was residential, then the selection of a household was based on its weight (i.e., how 

representative a particular household is of other households in the distribution-either regionally 

or nationally) in the Energy Information Administration’s 2005 Residential Energy Consumption 

Survey Public Use Sample, as described in TSD chapter 7. Each LCC and PBP calculation also 

sampled from the probability distributions that DOE developed to characterize many of the 

inputs to the analysis. For the commercial applications, DOE sampled from commercial small 

office building simulations using weights representative of 526 combinations of TMY weather 

file and State. . The weights assigned were population weights assigned to each combination as 

described in chapter 7. The LCC and PBP calculations were performed 10,000 times by sampling 

observations from the total of the Residiential and Commercial samples (reflecting the relative 

residential and commercial sales weights) and using the probability distributions that DOE 

developed to characterize many of the inputs. 

Based on the Monte Carlo simulations that DOE performed, for each standard-level, 

DOE calculated the share of households and commercial consumers receiving a net LCC benefit, 

with a net LCC cost, and with no impact. DOE considered a household or commercial user to 

receive no impact at a given if DOE assigned it base case equipment that is the same as or has 

higher efficiency than the CSL. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

8.4.1 Split-system Air Conditioners 

This section presents summary LCC results for the efficiency improvement levels 

specified in the engineering analysis (Chapter 5) and also presented in Section 8.2.2.2, StandardLevel Manufacturer Price Increases. The results presented here are based on annual operating 

costs calculated from residential and commercial electricity tariffs, repair costs, and maintenance 

costs developed for each individual observation. Section 8.2 presents the electricity price inputs 

as well as all other LCC inputs. 

To provide perspective on the LCC and PBP results, Table 8.4.1 and Table 8.4.4 present 

the average values for market baseline installed cost of split-system air conditioners for coil-only 

and blower-coil options, their average energy consumption at market baseline and the percentage 

changes in these values at the efficiency improvement levels. 

Table 8.4.1 Mean Market Baseline Installed Costs, Total Annual Energy Consumption, 

and Percentage Change for Split-System Air Conditioners (Coil-Only) by Region by 

Efficiency Level (SEER Value) 

Efficiency 

Level 

(SEER) 

Nation Hot-Humid Hot-Dry Rest of Country 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Market 

Baseline 2,647 2,291 2,400 3,393 3,056 2,071 2,626 1,310 

Percentage Change from Market Baseline 

13.5 (1.8) 1.4 (1.9) 1.3 (1.8) 1.4 (1.8) 1.6 

14 0.9 (2.1) 0.9 (2.2) 0.9 (2.0) 0.9 (1.7) 

14.5 4.1 (5.4) 4.3 (5.5) 4.0 (5.3) 4.0 (5.0) 

15 7.7 (8.5) 8.1 (8.6) 7.4 (8.4) 7.5 (8.1) 

15.5 12.0 (11.4) 12.6 (11.5) 11.7 (11.3) 11.7 (11.0) 

16 17.6 (14.1) 18.5 (14.3) 17.0 (14.1) 17.1 (13.7) 

16.5 24.0 (16.6) 25.2 (16.8) 23.3 (16.5) 23.3 (16.1) 

*Values in parentheses denote negative values. 

Table 8.4.2 Mean Market Baseline Installed Costs, Total Annual Energy Consumption, 

and Percentage Change for Split-System Air Conditioners (Blower-Coil) by Region by 

Efficiency Level (SEER Value) 

Efficiency 

Level 

(SEER) 

Nation Hot-Humid Hot-Dry Rest of Country 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Market 

Baseline 4,128 2,315 3,671 3,410 4,782 2,067 4,125 1,302 

Percentage Change from Market Baseline 

13.5 (0.9) 1.4 (0.9) 1.3 (0.8) 1.4 (0.8) 1.3 

14 1.0 (2.1) 1.1 (2.2) 1.0 (2.0) 1.0 (2.0) 

14.5 3.0 (5.4) 3.2 (5.5) 2.9 (5.3) 2.9 (5.3) 

15 4.5 (8.5) 4.8 (8.6) 4.3 (8.4) 4.3 (8.4) 

15.5 6.0 (11.4) 6.4 (11.5) 5.8 (11.3) 5.8 (11.3) 

16 7.5 (14.1) 8.1 (14.2) 7.3 (14.1) 7.3 (14.0) 

16.5 9.2 (16.6) 9.8 (16.7) 8.8 (16.5) 8.8 (16.3) 

17 10.8 (18.9) 11.6 (19.1) 10.5 (18.8) 10.5 (18.5) 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

18 14.4 (23.1) 15.4 (23.4) 13.9 (23.0) 13.9 (22.6) 

19 18.2 (26.9) 19.5 (27.2) 17.5 (26.7) 17.5 (26.3) 

20 22.2 (30.3) 23.8 (30.7) 21.5 (30.2) 21.5 (29.6) 

21 26.6 (33.4) 28.5 (33.8) 25.7 (33.2) 25.7 (32.6) 

22 31.3 (36.3) 33.5 (36.7) 30.2 (36.1) 30.2 (35.3) 

*Values in parentheses denote negative values. 

As stated earlier, DOE used the Monte Carlo method of analysis relying on Crystal Ball 

(i.e., random sampling from distributions) to conduct the LCC analysis. The results presented 

here are based on 10,000 samples per Monte Carlo run. DOE’s first step in developing LCC 

results was to establish the market baseline LCC for each of the product classes. The market 

baseline efficiency level for the preliminary analysis is the market-weighted efficiency level in 

each region. These distributions are shown in Figure 8.4.1 for coil-only split-system AC units 

and in Figure 8.4.2 for blower-coil AC units. 

National Standard Hot-Humid 

Hot-Dry Rest of Country 

Figure 8.4.1 Market Baseline Distributions of LCC for Split-System Air Conditioners 

(Coil-Only) by Region 

8-57 

EERE-2008-BT-STD-0006 COMMENT 54
Nation Hot-Humid 

Hot-Dry Rest of Country 

Figure 8.4.2 Market Baseline Distributions of LCC for Split-System Air Conditioners 

(Blower-Coil) by Region 

8.4.1.1 Mean LCC Savings for Split-system Air Conditioners by Region 

Because the values of most inputs are uncertain in this analysis, DOE represents them as 

a distribution of values rather than a single point-value. Thus, DOE also represents the LCC 

results as a distribution of values. Before proceeding with the presentation of the distribution of 

LCC results, DOE presents average values for LCC savings to show how these savings vary with 

efficiency for each of the split-system CAC product classes and by region. Table 8.4.3 presents 

results for coil-only improvements. LCC savings are positive at the national level standards up to 

SEER 13.5, and in the Hot-Humid and Hot-Dry regions up to SEER 15 and SEER 14.5, 

respectively. No SEER level beyond SEER 13 produces LCC savings for a coil-only standard in 

the rest of the country. Table 8.4.4 shows that LCC savings are positive at national level blowercoil standards up to SEER 13.5, but in the Hot-Humid and Hot-Dry regions savings are positive 

up to SEER 19 and SEER 18, respectively. No SEER level beyond SEER 13 produces LCC 

savings for a blower-coil standard in the rest of the country. 

Table 8.4.3 Mean LCC Savings for Split-System Air Conditioners (Coil-only) by Region 

by Efficiency Level (SEER Value) 

Efficiency LCC by Region 2008$ 

Level SEER Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 4 11 8 (15) 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

3 14 (1) 36 20 (75) 

4 14.5 (29) 39 4 (157) 

5 15 (83) 19 (40) (265) 

6 15.5 (180) (39) (134) (414) 

7 16 (341) (154) (300) (624) 

8 16.5 (565) (324) (537) (902) 

*Values in parentheses denote negative savings. 

Table 8.4.4 Mean LCC Savings for Split-System Air Conditioners (Blower-Coil) by 

Region by Efficiency Level (SEER Value) 

Efficiency 

Level SEER 

LCC by Region 2008$ 

Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 2 11 7 (16) 

3 14 0 38 24 (73) 

4 14.5 (15) 53 27 (140) 

5 15 (5) 90 56 (183) 

6 15.5 (5) 118 74 (234) 

7 16 (14) 137 81 (291) 

8 16.5 (36) 142 73 (361) 

9 17 (68) 137 54 (437) 

10 18 (159) 100 (19) (611) 

11 19 (285) 28 (133) (810) 

12 20 (443) (77) (287) (1,036) 

13 21 (634) (214) (480) (1,288) 

14 22 (859) (384) (713) (1,568) 

*Values in parentheses denote negative savings. 

It is worth reiterating that the results shown in Table 8.4.3 and Table 8.4.4 are mean 

values and do not show the distributions of savings. Thus, although observations can be made as 

to how the various inputs impact life-cycle cost and, in turn, how the resulting life-cycle costs 

change with efficiency, conclusions should only be drawn from the distribution of life-cycle cost 

results that are presented in Figure 8.4.3 and Figure 8.4.4. Section 8.4.1.3 provides information 

on the percentages of consumers in each region at each efficiency level that would experience 

LCC savings benefits, LCC cost increases, and no impact from the standard. 

8-59 

EERE-2008-BT-STD-0006 COMMENT 54
-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life-cycle Cost Savings($) 

2 3 

Mean 

4 5 

Median 

6 7 8 -1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life-cycle Cost Savings($) 

Mean Median 

` 

Efficiency Level National 2 3 4 5 

Efficiency Level 

6 7 8 

Hot-Humid 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life-cycle Cost Savings($) 

Mean Median 

` 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life-cycle Cost Savings($) 

Mean Median 

2 3 

Efficiency Level 

4 5 6 7 

Hot-Dry 

8 2 3 

Efficiency Level 

4 5 6 

Rest-of-Country 

7 8 

Figure 8.4.3 Plots of the Distributions of LCC Savings for Split-System Air Conditioners 

(Coil-Only) by Region 

-2500 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life‐cycle Cost Savings($)

2 3 4 5 

Mean 

6 7 8 9 

Efficiency Level

Median 

`

10 11 12 13 14 

National

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life‐cycle Cost Savings($)

2 3 4 5 

Mean 

6 7 8 9 

Efficiency Level

Median 

`

10 11 12 13 14 

Hot‐Humid

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life‐cycle Cost Savings($)

Mean Median 

`

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

Life‐cycle Cost Savings($)

Mean Median 

2 3 4 5 6 

Efficiency Level

7 8 9 10 11 12 13 

Hot‐Dry

14 2 3 4 5 6 

Efficiency Level

7 8 9 10 11 12 

Rest-of-Country 

13 14 

Figure 8.4.4 Plots of the Distributions of LCC Savings for Split-system Air Conditioners 

(Blower-Coil) by Region 

8-60 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

8.4.1.2 Mean PBP Results for Split-system Air Conditioners by Region 

This section presents PBP results for the efficiency improvement levels specified in the 

engineering analysis (Chapter 5) and also presented in section 8.2.2.2, Standard-Level 

Manufacturer Price Increases. The results presented here are based on annual operating costs 

calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP 

inputs. 

Similar to LCC, the analysis provides an estimate of the simple payback period at 

different ranges of energy prices, sales taxes, and installation costs that prevail across the country 

for each efficiency level and each building (building) type. Table 8.4.5 and Table 8.4.6 show the 

effect on payback period as the level of efficiency changes from the market baseline for CAC 

products in residential and commercial buildings for each region’s energy prices, sales taxes, and 

installation costs. 

Similar to the LCC differences, DOE estimated PBP results as a distribution of values. 

The means of these distributions are shown in Table 8.4.5 and Table 8.4.6 and the distributions 

of values for PBP are shown in Figure 8.4.5 and Figure 8.4.6. Mean rebuttable PBP for each 

region and efficiency level is shown in Table 8.4.7 and Table 8.4.8. In addition, DOE provides 

data on the median PBP for each efficiency level in each region in section 8.4.1.3. 

Table 8.4.5 Mean Payback Period for Split-System Air Conditioners (Coil-Only) by 

Region 

Efficiency 

Level SEER 

Payback Period by Region years 

Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 48.6 27.3 47.6 75.9 

3 14 53.5 30.2 50.1 80.8 

4 14.5 57.0 33.8 53.5 84.1 

5 15 61.0 38.2 57.2 87.3 

6 15.5 66.0 44.0 61.8 90.8 

7 16 71.6 51.6 67.2 94.1 

8 16.5 76.8 59.7 72.0 96.5 

Table 8.4.6 Mean Payback Period for Split-system Air Conditioners (Blower-Coil) by 

Region 

Efficiency 

Level SEER 

Payback Period by Region years 

Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 48.8 26.3 46.6 75.3 

3 14 50.8 27.9 48.0 77.8 

4 14.5 52.1 29.0 49.0 79.2 

5 15 49.4 26.7 46.3 76.5 

6 15.5 49.0 26.3 45.6 76.1 

7 16 49.4 26.8 45.8 76.6 

8 16.5 51.5 28.6 48.0 78.4 

9 17 53.3 30.2 49.7 80.2 

10 18 56.9 33.7 53.0 83.5 

11 19 60.2 37.3 55.9 86.5 

12 20 63.3 41.0 58.6 89.0 

13 21 66.3 44.7 61.3 91.2 

14 22 69.1 48.4 63.9 93.1 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 8.4.7 Mean Rebuttable Payback Period for Split-System Air Conditioners (CoilOnly) by Region 

Efficiency 

Level SEER 

Payback Period by Region 

years 

Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 14.3 8.9 14.5 23.4 

3 14 16.5 9.8 15.9 25.6 

4 14.5 18.1 10.8 17.3 27.5 

5 15 19.9 11.9 19.1 30.2 

6 15.5 22.4 13.5 21.4 33.6 

7 16 25.7 15.7 24.4 38.0 

8 16.5 29.5 18.4 28.0 43.1 

Table 8.4.8 Mean Rebuttable Payback Period for Split-system Air Conditioners (BlowerCoil) by Region 

Efficiency 

Level SEER 

Payback Period by Region 

years 

Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 16.3 10.0 16.2 26.7 

3 14 17.6 10.3 16.9 27.6 

4 14.5 18.3 10.8 17.5 28.4 

5 15 17.3 10.3 16.6 27.1 

6 15.5 17.3 10.2 16.5 26.9 

7 16 17.6 10.4 16.8 27.4 

8 16.5 18.3 10.8 17.5 28.4 

9 17 18.9 11.2 18.1 29.3 

10 18 20.5 12.2 19.6 31.4 

11 19 22.1 13.2 21.2 33.7 

12 20 23.7 14.3 22.8 36.0 

13 21 25.4 15.5 24.5 38.5 

14 22 27.2 16.7 26.2 41.0 

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EERE-2008-BT-STD-0006 COMMENT 54
40 

60 

80 

40 

60 

80 

120 120 

100 100 

80 

Mean Median National

2 3 4 5 6 7 8 

Efficiency Level Mean Median Hot‐Humid

2 3 4 5 6 7 8 

Efficiency Level

Payback Period (years) Payback Period (years)Payback Period (years) Payback Period (years)

60 

40 

20 20 

0 0 

120 120 

100 100 

Mean Median Hot‐Dry

2 3 4 5 6 7 8 

Efficiency Level Mean Median 

`

Rest‐of‐Country

2 3 4 5 6 7 8 

Efficiency Level

80 

60 

40 

20 20 

0 0 

Figure 8.4.5 Plots of the Distributions of PBP for Split-system Air Conditioners (CoilOnly) by Region 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 12 13 14 

Efficiency Level

Payback Period (years)

Mean Median National

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 12 13 14 

Efficiency Level

Payback Period (years)

Mean Median Hot‐Humid

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 12 13 14 

Efficiency Level

Payback Period (years)

Mean Median Hot‐Dry

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 12 13 14 

Efficiency Level

Payback Period (years)

Mean Median 

`

Rest‐of‐Country

Figure 8.4.6 Plots of the Distributions of PBP for Split-system Air Conditioners (BlowerCoil) by Region 

8-63 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

8.4.1.3 Detailed Regional Results for Split-system Air Conditioners 

This section provides data on the detailed results for split-system CAC life-cycle cost, the 

components of life-cycle cost, life-cycle cost savings, and payback period. Table 8.4.9 through 

Table 8.4.16 present these details separately for coil-only CAC units and blower-coil CAC units, 

and for each region by efficiency level 

Nation 

Table 8.4.9 National LCC and PBP Results for Split-System Air Conditioners (CoilOnly) by Efficiency Level (SEER Value): Nation 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,647 418 7,915 - - - - - -

13.5 2,598 418 7,875 4 16 76 8 27.8 48.6 

14 2,670 414 7,881 (1) 56 20 24 41.9 53.5 

14.5 2,755 410 7,916 (29) 62 16 22 59.4 57.0 

15 2,850 408 7,977 (83) 69 10 20 100.0 61.0 

15.5 2,965 408 8,084 (180) 75 7 17 100.0 66.0 

16 3,112 411 8,255 (341) 81 5 14 100.0 71.6 

16.5 3,282 416 8,478 (565) 87 2 11 100.0 76.8 

*Values in parentheses denote negative values. 

Table 8.4.10 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by 

Efficiency Level (SEER Value): Nation 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 4,128 418 9,382 - - - - - -

13.5 4,092 420 9,366 2 16 76 8 27.4 48.8 

14 4,169 415 9,370 0 55 21 24 33.3 50.8 

14.5 4,251 410 9,389 (15) 60 17 23 36.2 52.1 

15 4,312 405 9,378 (5) 62 12 26 29.9 49.4 

15.5 4,374 400 9,378 (5) 64 9 28 29.0 49.0 

16 4,439 396 9,388 (14) 66 7 28 29.6 49.4 

16.5 4,506 393 9,411 (36) 70 3 27 34.8 51.5 

17 4,575 390 9,444 (68) 71 3 26 39.9 53.3 

18 4,721 387 9,537 (159) 74 1 24 56.4 56.9 

19 4,878 385 9,664 (285) 77 1 22 84.1 60.2 

20 5,045 385 9,823 (443) 80 1 19 100.0 63.3 

21 5,226 387 10,015 (634) 83 0 17 100.0 66.3 

22 5,419 390 10,239 (859) 84 0 15 100.0 69.1 

*Values in parentheses denote negative values. 

8-64 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hot-Humid Region 

Table 8.4.11 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by 

Efficiency Level (SEER Value): Hot-Humid Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,400 456 8,157 ­ - - - - -

13.5 2,354 458 8,139 11 12 76 12 9.9 27.3 

14 2,423 450 8,107 36 41 20 39 11.6 30.2 

14.5 2,503 444 8,103 39 49 16 36 14.3 33.8 

15 2,594 439 8,126 19 57 10 33 17.5 38.2 

15.5 2,704 436 8,189 (39) 64 7 29 23.1 44.0 

16 2,845 435 8,313 (154) 72 5 23 34.5 51.6 

16.5 3,006 437 8,484 (324) 80 2 18 63.5 59.7 

*Values in parentheses denote negative values. 

Table 8.4.12 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by 

Efficiency Level (SEER Value): Hot-Humid Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,671 457 9,428 - - - - - -

13.5 3,637 459 9,428 11 12 76 12 11.7 26.3 

14 3,710 451 9,395 38 41 21 38 12.8 27.9 

14.5 3,789 444 9,377 53 46 17 37 11.7 29.0 

15 3,847 437 9,336 90 46 12 42 11.5 26.7 

15.5 3,906 430 9,306 118 48 9 44 11.7 26.3 

16 3,968 424 9,287 137 49 7 44 12.6 26.8 

16.5 4,031 419 9,281 142 53 3 44 13.5 28.6 

17 4,098 414 9,286 137 55 3 42 15.5 30.2 

18 4,237 407 9,324 100 60 1 38 17.9 33.7 

19 4,386 401 9,396 28 65 1 35 20.9 37.3 

20 4,546 397 9,501 (77) 69 1 31 24.7 41.0 

21 4,718 395 9,639 (214) 72 0 27 29.7 44.7 

22 4,902 395 9,809 (384) 76 0 24 11.7 48.4 

*Values in parentheses denote negative values. 

8-65 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hot-Dry Region 

Table 8.4.13 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by 

Efficiency Level (SEER Value): Hot-Dry Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,056 490 9,205 ­ - - - - -

13.5 3,001 491 9,167 8 15 76 9 22.3 47.6 

14 3,082 484 9,153 20 52 20 28 28.4 50.1 

14.5 3,177 479 9,172 4 58 16 27 42.6 53.5 

15 3,283 475 9,224 (40) 64 10 25 64.3 57.2 

15.5 3,412 473 9,327 (134) 71 7 22 100.0 61.8 

16 3,577 475 9,504 (300) 77 5 18 100.0 67.2 

16.5 3,767 479 9,741 (537) 84 2 15 100.0 72.0 

*Values in parentheses denote negative values. 

Table 8.4.14 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by 

Efficiency Level (SEER Value): Hot-Dry Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 4,782 491 10,967 - - - - - -

13.5 4,742 494 10,964 7 15 76 9 21.5 46.6 

14 4,828 486 10,943 24 51 21 28 24.3 48.0 

14.5 4,920 479 10,941 27 55 17 28 28.2 49.0 

15 4,988 471 10,907 56 57 12 31 24.2 46.3 

15.5 5,058 465 10,887 74 59 9 33 23.3 45.6 

16 5,130 459 10,879 81 61 7 33 23.8 45.8 

16.5 5,205 454 10,887 73 64 3 33 26.9 48.0 

17 5,283 450 10,908 54 66 3 31 30.1 49.7 

18 5,446 443 10,982 (19) 69 1 29 38.6 53.0 

19 5,621 439 11,096 (133) 72 1 27 51.9 55.9 

20 5,809 438 11,251 (287) 75 1 25 76.4 58.6 

21 6,010 438 11,445 (480) 77 0 23 100.0 61.3 

22 6,227 440 11,678 (713) 80 0 20 100.0 63.9 

*Values in parentheses denote negative values. 

8-66 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Rest of Country 

Table 8.4.15 LCC and PBP Results for Split-System Air Conditioners (Coil-Only) by 

Efficiency Level (SEER Value): Rest of Country 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,626 295 6,287 ­ - - - - -

13.5 2,579 294 6,230 (15) 22 76 2 100.0 75.9 

14 2,649 295 6,304 (75) 75 20 5 100.0 80.8 

14.5 2,730 297 6,403 (157) 80 16 4 100.0 84.1 

15 2,822 299 6,524 (265) 87 10 3 100.0 87.3 

15.5 2,933 304 6,687 (414) 91 7 2 100.0 90.8 

16 3,075 311 6,912 (624) 94 5 1 100.0 94.1 

16.5 3,239 320 7,184 (902) 98 2 1 100.0 96.5 

*Values in parentheses denote negative values. 

Table 8.4.16 LCC and PBP Results for Split-System Air Conditioners (Blower-Coil) by 

Efficiency Level (SEER Value): Rest of Country 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 4,125 293 7,625 - - - - - -

13.5 4,090 292 7,731 (16) 22 76 2 100.0 75.3 

14 4,164 292 7,813 (73) 73 21 6 100.0 77.8 

14.5 4,244 293 7,892 (140) 78 17 5 100.0 79.2 

15 4,302 292 7,939 (183) 81 12 7 100.0 76.5 

15.5 4,362 292 7,990 (234) 84 9 7 100.0 76.1 

16 4,425 293 8,048 (291) 86 7 7 100.0 76.6 

16.5 4,489 293 8,120 (361) 90 3 7 100.0 78.4 

17 4,556 295 8,197 (437) 91 3 6 100.0 80.2 

18 4,697 298 8,373 (611) 94 1 4 100.0 83.5 

19 4,848 303 8,572 (810) 96 1 3 100.0 86.5 

20 5,010 308 8,799 (1,036) 97 1 3 100.0 89.0 

21 5,183 315 9,053 (1,288) 98 0 2 100.0 91.2 

22 5,370 323 9,333 (1,568) 98 0 1 100.0 93.1 

*Values in parentheses denote negative values. 

8-67 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

8.4.2 Split-System Heat Pumps 

This section presents LCC results for the efficiency improvement levels specified in the 

engineering analysis for split-system CHPs (Chapter 5) and also presented in Section 8.2.2.2, 

Standard-Level Manufacturer Price Increases. The results presented here are based on annual 

operating costs calculated from residential and commercial electricity tariffs, repair costs, and 

maintenance costs developed for each individual observation. Section 8.2 presents the electricity 

price inputs as well as all other LCC inputs. 

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., 

random sampling from distributions) was used to conduct the LCC analysis. The following 

results presented here are based on 10,000 samples per Monte Carlo run. DOE’s first step in 

developing LCC results was to establish the market baseline LCC for each of the product classes. 

The market baseline efficiency level for the preliminary analysis is the market-weighted 

efficiency level in each region. Figure 8.4.7 shows the market baseline distribution of life-cycle 

costs for split-system heat pumps for each region. 

To provide perspective on the LCC and PBP results, Table 8.4.17 presents the average 

values for market baseline installed cost of split-system heat pumps, their average energy 

consumption at market baseline and the percentage changes in these values at the efficiency 

improvement levels. 

Table 8.4.17 Mean Market Baseline Installed Costs, Total Annual Energy Consumption, 

and Percentage Change for Split-System Heat Pumps by Region by Efficiency Level (SEER 

Value) 

Efficiency 

Level 

(SEER) 

Nation Hot-Humid Hot-Dry Rest of Country 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Market 

Baseline 3,682 4,954 3,387 5,236 4,239 4,828 3,634 4,719 

Percentage Change from Market Baseline 

13.5 (2.0) 2.5 (2.1) 2.6 (2.0) 2.7 (2.0) 2.2 

14 0.5 (0.4) 0.5 (0.5) 0.5 (0.5) 0.5 (0.3) 

14.5 2.4 (3.3) 2.5 (3.5) 2.3 (3.6) 2.4 (2.7) 

15 4.3 (5.9) 4.4 (6.3) 4.2 (6.5) 4.2 (5.0) 

15.5 6.3 (8.5) 6.6 (9.0) 6.1 (9.2) 6.2 (7.1) 

16 8.9 (10.8) 9.3 (11.5) 8.7 (11.8) 8.7 (9.2) 

17 13.4 (15.8) 13.9 (16.5) 13.0 (16.8) 13.1 (14.1) 

18 18.2 (20.2) 18.8 (20.9) 17.7 (21.2) 17.8 (18.5) 

19 23.3 (24.2) 24.2 (24.9) 22.6 (25.2) 22.8 (22.4) 

19.5 26.1 (25.9) 27.0 (26.6) 25.3 (26.9) 25.5 (24.0) 

*Values in parentheses denote negative values. 

8-68 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Nation Hot-Humid 

Hot-Dry Rest of Country 

Figure 8.4.7 Market Baseline Distributions of LCC for Split-System Heat Pumps by 

Region 

8.4.2.1 Mean LCC Savings for Split-System Heat Pumps by Region 

Because the values of most inputs are uncertain in this analysis, DOE represents them as 

a distribution of values rather than a single point-value. Thus, DOE also represents the LCC 

results as a distribution of values. In Table 8.4.18 DOE presents average values for LCC savings 

to show how these savings vary with efficiency for the split-system CHP product classes and by 

region. In contrast to the situation with split-system CAC units, LCC savings for split-system 

CHPs are positive at the national level standards and in both hot regions up to the max tech level 

(SEER 19.5). Although SEER 14.5 appears to have positive LCC savings, this is probably a 

statistical anomaly. It is unlikely that any standard level above SEER13 produces LCC savings 

in the colder part of the country. 

Table 8.4.18 Mean LCC Savings for Split-System Heat Pumps by Region by Efficiency 

Level (SEER Value and HSPF Value) 

Efficiency 

Level SEER HSPF 

LCC Savings by Region 2008$ 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 8 11 17 0 

3 14 8 40 51 81 (10) 

4 14.5 8.15 95 113 174 (1) 

5 15 8.3 150 176 269 8 

8-69 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

6 15.5 8.45 194 228 350 3 

7 16 8.6 200 245 388 (36) 

8 17 9.1 262 312 509 (44) 

9 18 9.6 275 333 570 (94) 

10 19 10.1 241 311 574 (185) 

11 19.5 10.3 196 276 544 (259) 

*Values in parentheses denote negative values. 

It is worth reiterating that the results shown in Table 8.4.18 are mean values and do not 

show the distributions of savings. Thus, although observations can be made as to how the various 

inputs impact life-cycle cost and, in turn, how the resulting life-cycle costs change with 

efficiency, conclusions should only be drawn from the distribution of life-cycle cost results that 

are presented in Figure 8.4.8. Section 8.4.2.3 provides information on the percentages of 

consumers in each region at each efficiency level that would experience LCC savings benefits, 

LCC cost increases, and no impact from the standard. 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Humid 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

National 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Dry 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

Rest-of-Country 

Figure 8.4.8 Plots of the Distributions of LCC Savings for Split-system Heat Pumps by 

Region 

8.4.2.2 Mean PBP Results for Split-System Heat Pumps by Region 

This section presents PBP results for the efficiency improvement levels specified in the 

engineering analysis (Chapter 5) and also presented in section 8.2.2.2, Standard-Level 

Manufacturer Price Increases. The results presented here are based on annual operating costs 

calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP 

inputs. 

Similar to LCC, the analysis provides an estimate of the simple payback period at 

different ranges of energy prices, sales taxes, and installation costs that prevail across the country 

8-70 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

for each efficiency level and each building (building) type. Table 8.4.19 shows the effect on 

payback period as the level of efficiency changes from the market baseline for split-system CHP 

products in residential and commercial buildings for each region’s energy prices, sales taxes, and 

installation costs. 

Similar to the LCC differences, DOE depicted PBP results as a distribution of values. 

The means of these distributions are shown in Table 8.4.19 and the distributions of values for 

PBP are shown in Figure 8.4.9. Mean rebuttable PBP for each region and efficiency level is 

shown in Table 8.4.20. In addition, DOE provides data on the median PBP for each efficiency 

level in each region in section 8.4.2.3. 

Table 8.4.19 Mean Payback Period for Split-System Heat Pumps by Region (Years) 

Efficiency 

Level SEER HSPF 

Payback Period by Region years 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 22.1 16.1 16.7 28.7 

3 14 8 24.2 17.8 18.2 34.5 

4 14.5 8.15 20.1 13.5 15.8 29.1 

5 15 8.3 18.4 11.8 14.0 27.1 

6 15.5 8.45 18.6 11.9 13.8 27.8 

7 16 8.6 21.1 13.8 15.4 31.7 

8 17 9.1 22.0 15.5 17.4 30.9 

9 18 9.6 23.8 17.6 18.9 32.5 

10 19 10.1 26.0 19.8 20.6 35.1 

11 19.5 10.3 27.5 21.2 21.7 37.2 

*Values in parentheses denote negative values. 

Table 8.4.20 Mean Rebuttable Payback Period for Split-System Heat Pumps by Region 

(Years) 

Efficiency 

Level SEER HSPF 

Payback Period by Region years 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 9.5 7.7 8.3 11.3 

3 14 8 10.2 8.5 9.0 12.6 

4 14.5 8.15 7.9 6.8 6.6 10.2 

5 15 8.3 7.5 6.4 6.2 9.6 

6 15.5 8.45 7.6 6.5 6.2 9.8 

7 16 8.6 8.3 7.2 6.8 10.7 

8 17 9.1 8.6 7.6 7.3 10.6 

9 18 9.6 9.2 8.2 7.9 11.1 

10 19 10.1 9.9 8.8 8.6 11.9 

11 19.5 10.3 10.4 9.3 9.1 12.4 

*Values in parentheses denote negative values. 

8-71 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Payback Period (years) 

Mean Median National 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Payback Period (years) 

Mean Median Hot-Humid 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Payback Period (years) 

Mean Median Hot-Dry 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 9 10 11 

Efficiency Level 

Payback Period (years) 

Mean Median 

` 

Rest-of-Country 

Figure 8.4.9 Plots of the Distributions of PBP for Split-System Heat Pumps by Region 

8.4.2.3 Detailed Regional Results for Split-System Heat Pumps 

This section provides data on the detailed results for split-system CHP life-cycle cost, the 

components of life-cycle cost, life-cycle cost savings, and payback period. These details are 

shown separately by region and efficiency level. Table 8.4.21 through Table 8.4.24 present these 

details for each region by efficiency level. 

Nation 

Table 8.4.21 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Nation 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,682 705 11,550 - - - - - -

13.5 3,607 716 11,601 8 6 87 7 8.0 22.1 

14 3,700 703 11,551 40 32 35 33 9.0 24.2 

14.5 3,771 690 11,477 95 33 25 42 7.8 20.1 

15 3,840 679 11,409 150 36 16 48 7.6 18.4 

15.5 3,915 668 11,361 194 39 11 50 7.9 18.6 

16 4,011 659 11,354 200 46 7 47 9.1 21.1 

17 4,176 639 11,289 262 48 4 48 9.3 22.0 

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18 4,352 623 11,275 275 52 2 46 10.1 23.8 

19 4,540 610 11,309 241 56 1 43 11.2 26.0 

19.5 4,642 605 11,354 196 59 0 41 12.0 27.5 

*Values in parentheses denote negative values. 

Hot-Humid Region 

Table 8.4.22 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Hot-Humid Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,387 647 10,636 - - - - - -

13.5 3,316 658 10,688 11 5 87 8 6.4 16.1 

14 3,404 645 10,627 51 27 35 38 7.4 17.8 

14.5 3,472 632 10,544 113 28 25 47 6.5 13.5 

15 3,538 620 10,469 176 30 16 54 6.3 11.8 

15.5 3,609 609 10,413 228 33 11 57 6.6 11.9 

16 3,701 599 10,394 245 39 7 54 7.5 13.8 

17 3,858 580 10,325 312 42 4 54 7.8 15.5 

18 4,026 563 10,303 333 46 2 52 8.5 17.6 

19 4,206 550 10,325 311 51 1 49 9.4 19.8 

19.5 4,303 545 10,360 276 54 0 46 10.0 21.2 

*Values in parentheses denote negative values. 

Hot-Dry Region 

Table 8.4.23 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Hot-Dry Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 4,239 842 13,642 - - - - - -

13.5 4,155 857 13,733 17 4 87 9 5.2 16.7 

14 4,259 839 13,632 81 23 35 42 6.2 18.2 

14.5 4,339 822 13,507 174 24 25 51 5.5 15.8 

15 4,416 805 13,393 269 26 16 58 5.4 14.0 

15.5 4,500 790 13,303 350 29 11 61 5.6 13.8 

16 4,607 777 13,261 388 34 7 59 6.4 15.4 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

17 4,791 750 13,135 509 37 4 59 6.7 17.4 

18 4,988 727 13,071 570 42 2 56 7.4 18.9 

19 5,199 709 13,067 574 46 1 53 8.3 20.6 

19.5 5,313 702 13,097 544 49 0 51 8.8 21.7 

*Values in parentheses denote negative values. 

Rest of Country 

Table 8.4.24 LCC and PBP Results for Split-System Heat Pumps by Efficiency Level 

(SEER Value): Rest of Country 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,634 618 10,520 - - - - - -

13.5 3,561 624 10,514 0 8 87 5 12.0 28.7 

14 3,651 618 10,530 (10) 44 35 21 15.2 34.5 

14.5 3,719 611 10,517 (1) 46 25 29 12.7 29.1 

15 3,786 604 10,507 8 50 16 34 12.0 27.1 

15.5 3,858 599 10,512 3 55 11 34 12.6 27.8 

16 3,951 594 10,554 (36) 63 7 30 15.0 31.7 

17 4,110 582 10,562 (44) 63 4 33 13.9 30.9 

18 4,279 572 10,613 (94) 66 2 32 14.7 32.5 

19 4,461 564 10,704 (185) 71 1 29 16.3 35.1 

19.5 4,560 562 10,778 (259) 74 0 26 17.8 37.2 

*Values in parentheses denote negative values. 

8.4.3 Single Package Air Conditioners 

This section presents LCC results for the efficiency improvement levels specified in the 

engineering analysis for single package CACs (Chapter 5) and also presented in Section 8.2.2.2, 

Standard-Level Manufacturer Price Increases. The results presented here are based on annual 

operating costs calculated from residential and commercial electricity tariffs, repair costs, and 

maintenance costs developed for each individual observation. Section 8.2 presents the electricity 

price inputs as well as all other LCC inputs. 

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., 

random sampling from distributions) was used to conduct the LCC analysis. The following 

results presented here are based on 10,000 samples per Monte Carlo run. DOE’s first step in 

developing LCC results was to establish the market baseline LCC for each of the product classes. 

The market baseline efficiency level for the preliminary analysis is the market-weighted 

efficiency level. Figure 8.4.10 shows the market baseline distribution of LCC for single package 

CAC products in each region. 

8-74 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

To provide perspective on the LCC and PBP results, Table 8.4.25 presents the average 

values for market baseline installed cost of single package air conditioners, their average energy 

consumption at market baseline and the percentage changes in these values at the efficiency 

improvement levels. 

Table 8.4.25 Mean Market Baseline Installed Costs, Total Annual Energy Consumption, 

and Percentage Change for Single Package Air Conditioners by Region by Efficiency Level 

(SEER Value) 

Efficiency 

Level 

(SEER) 

Nation Hot-Humid Hot-Dry Rest of Country 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Market 

Baseline 2,807 2,348 2,550 3,559 3,241 2,144 2,784 1,348 

Percentage Change from Market Baseline 

13.5 3.1 (2.4) 3.3 (2.4) 3.0 (2.4) 3.0 (2.3) 

14 6.2 (5.7) 6.5 (5.8) 6.0 (5.7) 6.0 (5.5) 

14.5 10.7 (8.9) 11.3 (9.0) 10.4 (8.9) 10.4 (8.7) 

15 14.4 (11.9) 15.1 (12.0) 14.0 (11.8) 14.0 (11.7) 

15.5 19.1 (14.7) 20.0 (14.8) 18.5 (14.6) 18.5 (14.4) 

16 24.5 (17.3) 25.8 (17.4) 23.8 (17.3) 23.9 (17.1) 

16.6 32.3 (20.1) 33.9 (20.3) 31.3 (20.0) 31.4 (19.8) 

*Values in parentheses denote negative values. 

Nation Hot-Humid 

Hot-Dry Rest of Country 

8-75 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Figure 8.4.10 Market Baseline Distributions of LCC for Single Package Air Conditioners 

by Region 

8.4.3.1 Mean LCC Savings for Single Package Air Conditioners by Region 

Because the values of most inputs are uncertain in this analysis, DOE represents them as 

a distribution of values rather than a single point-value. Thus, DOE also represents the LCC 

results as a distribution of values. In Table 8.4.26 DOE presents average values for LCC savings 

to show how these savings vary with efficiency for each of the single package CAC product 

classes and by region. The LCC savings for single package CACs are negative at the national 

level in all regions for a standard at any level beyond SEER 13. 

Table 8.4.26 Mean LCC Savings for Single Package Air Conditioners by Region by 

Efficiency Level (SEER Value) 

Efficiency 

Level SEER 

LCC Savings by Region 2008$ 

Nation Hot-Humid Hot-Dry Rest of country 

2 13.5 (68) (29) (57) (123) 

3 14 (95) (17) (64) (214) 

4 14.5 (195) (71) (155) (375) 

5 15 (266) (101) (212) (504) 

6 15.5 (391) (180) (332) (683) 

7 16 (564) (303) (507) (907) 

8 16.6 (842) (517) (799) (1,243) 

*Values in parentheses denote negative values. 

The results shown in Table 8.4.26 are mean values and do not show the distributions of 

savings. Thus, although observations can be made as to how the various inputs impact life-cycle 

cost and, in turn, how the resulting life-cycle costs change with efficiency, conclusions should 

only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.11. 

Section 8.4.3.3 provides information on the percentages of consumers in each region at each 

efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact 

from the standard. 

8-76 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Humid 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

National 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Dry 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

Rest-of-Country 

Figure 8.4.11 Plots of the Distributions of LCC Savings for Single Package Air 

Conditioners by Region 

8.4.3.2 Mean PBP Results for Single Package Air Conditioners by Region 

This section presents PBP results for the efficiency improvement levels specified in the 

engineering analysis (Chapter 5) and also presented in section 8.2.2.2, Standard-Level 

Manufacturer Price Increases. The results presented here are based on annual operating costs 

calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP 

inputs. 

Similar to LCC, the analysis provides an estimate of the simple payback period at 

different ranges of energy prices, sales taxes, and installation costs that prevail across the country 

for each efficiency level and each building (building) type. Table 8.4.27 shows the effect on 

payback period as the level of efficiency changes from the market baseline for CAC products in 

residential and commercial buildings for each region’s energy prices, sales taxes, and installation 

costs. 

Similar to the LCC differences, DOE estimated PBP results as a distribution of values. 

The means of these distributions are shown in Table 8.4.27 and the distributions of values for 

PBP are shown in Figure 8.4.12. Mean rebuttable PBP is shown in Table 8.4.28. In addition, 

DOE provides data on the median PBP for each efficiency level in each region in section 8.4.3.3. 

Table 8.4.27 Mean Payback Period for Single Package Air Conditioners by Region 

Efficiency Payback Period by Region years 

Level SEER Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 70.6 49.2 65.0 93.7 

3 14 64.3 41.7 59.0 89.6 

8-77 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

40 

60 

80 

4 14.5 68.6 46.6 63.1 92.6 

5 15 68.9 46.8 63.4 92.7 

6 15.5 71.5 50.1 65.9 94.0 

7 16 74.6 54.6 68.8 95.5 

8 16.6 78.6 61.1 72.6 97.2 

Table 8.4.28 Mean Rebuttable Payback Period for Single Package Air Conditioners by 

Region 

Efficiency Payback Period by Region years 

Level SEER Nation Hot-Humid Hot-Dry Rest of Country 

2 13.5 26.6 16.2 24.9 39.4 

3 14 23.0 13.7 21.4 34.4 

4 14.5 25.1 15.1 23.3 37.3 

5 15 25.2 15.2 23.3 37.4 

6 15.5 26.7 16.2 24.7 39.5 

7 16 28.7 17.6 26.4 42.2 

8 16.6 31.8 19.9 29.2 46.4 

120 120 

100 100 

Payback Period (years) 

Mean Median National 

2 3 4 5 6 7 8 

Efficiency Level 

Payback Period (years) 

Mean Median Hot-Humid 

2 3 4 5 6 7 8 

Efficiency Level 

80 

60 

40 

20 20 

0 0 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 

Efficiency Level 

Payback Period (years) 

Mean Median Hot-Dry 

0 

20 

40 

60 

80 

100 

120 

2 3 4 5 6 7 8 

Efficiency Level 

Payback Period (years) 

Mean Median 

` 

Rest-of-Country 

Figure 8.4.12 Plots of the Distributions of PBP for Single Package Air Conditioners by 

Region 

8.4.3.3 Detailed Regional Results for Single Package Air Conditioners 

This section provides data on the detailed results for single package CAC life-cycle cost, 

the components of life-cycle cost, life-cycle cost savings, and payback period. through Table 

8.4.32 present these details separately for single package CAC units for each region by efficiency 

level. 

8-78 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

Nation 

Table 8.4.29 LCC and PBP Results for Single Package Air Conditioners by Efficiency 

Level (SEER Value): Nation 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,807 419 8,087 - - - - - -

13.5 2,894 418 8,148 (68) 64 25 11 100.0 70.6 

14 2,982 414 8,178 (95) 77 5 18 100.0 64.3 

14.5 3,108 412 8,281 (195) 82 3 15 100.0 68.6 

15 3,212 410 8,353 (266) 83 1 16 100.0 68.9 

15.5 3,342 411 8,478 (391) 86 0 14 100.0 71.5 

16 3,496 413 8,651 (564) 88 0 12 100.0 74.6 

16.6 3,714 418 8,929 (842) 91 0 9 100.0 78.6 

*Values in parentheses denote negative values. 

Hot-Humid Region 

Table 8.4.30 LCC and PBP Results for Single Package Air Conditioners by Efficiency 

Level (SEER Value): Hot-Humid Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,550 468 8,440 - - - - - -

13.5 2,633 464 8,468 (29) 56 25 19 30.0 49.2 

14 2,717 457 8,455 (17) 63 5 32 20.4 41.7 

14.5 2,837 452 8,511 (71) 71 3 26 26.5 46.6 

15 2,936 447 8,540 (101) 72 1 27 27.1 46.8 

15.5 3,061 444 8,620 (180) 76 0 24 32.6 50.1 

16 3,207 443 8,743 (303) 80 0 20 42.2 54.6 

16.6 3,415 444 8,957 (517) 85 0 15 69.5 61.1 

*Values in parentheses denote negative values. 

Hot-Dry Region 

Table 8.4.31 LCC and PBP Results for Single Package Air Conditioners by Efficiency 

Level (SEER Value): Hot-Dry Region 

Efficiency 

Level Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

8-79 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,241 497 9,507 - - - - - -

13.5 3,339 494 9,562 (57) 60 25 15 100.0 65.0 

14 3,437 488 9,568 (64) 71 5 24 85.9 59.0 

14.5 3,578 485 9,661 (155) 76 3 21 100.0 63.1 

15 3,694 481 9,719 (212) 78 1 21 100.0 63.4 

15.5 3,840 479 9,839 (332) 81 0 19 100.0 65.9 

16 4,012 480 10,014 (507) 84 0 16 100.0 68.8 

16.6 4,256 485 10,305 (799) 87 0 13 100.0 72.6 

*Values in parentheses denote negative values. 

Rest of Country 

Table 8.4.32 LCC and PBP Results for Single Package Air Conditioners by Efficiency 

Level (SEER Value): Rest of Country 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 2,784 294 6,424 - - - - - -

13.5 2,868 296 6,535 (123) 74 25 1 100.0 93.7 

14 2,952 298 6,631 (214) 93 5 2 100.0 89.6 

14.5 3,074 302 6,798 (375) 95 3 2 100.0 92.6 

15 3,174 304 6,927 (504) 97 1 2 100.0 92.7 

15.5 3,300 309 7,107 (683) 99 0 1 100.0 94.0 

16 3,448 316 7,331 (907) 99 0 1 100.0 95.5 

16.6 3,658 326 7,667 (1,243) 99 0 1 100.0 97.2 

*Values in parentheses denote negative values. 

8.4.4 Single Package Heat Pumps 

This section presents LCC results for the efficiency improvement levels specified in the 

engineering analysis for single package CHPs (Chapter 5) and also presented in Section 8.2.2.2, 

Standard-Level Manufacturer Price Increases. The results presented here are based on annual 

operating costs calculated from residential and commercial electricity tariffs, repair costs, and 

maintenance costs developed for each individual observation. Section 8.2 presents the electricity 

price inputs as well as all other LCC inputs. 

As stated earlier, the Monte Carlo method of analysis relying on Crystal Ball (i.e., 

random sampling from distributions) was used to conduct the LCC analysis. The following 

results presented here are based on 10,000 samples per Monte Carlo run. DOE’s first step in 

8-80 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

developing LCC results was to establish the market baseline LCC for each of the product classes. 

The market baseline efficiency level for the preliminary analysis is the market-weighted 

efficiency level in each region. Figure 8.4.13 shows the market baseline distribution of life-cycle 

costs for single package heat pumps for each region. 

To provide perspective on the LCC and PBP results, Table 8.4.33 presents the average 

values for market baseline installed cost of single-package heat pumps, their average energy 

consumption at market baseline and the percentage changes in these values at the efficiency 

improvement levels. 

Table 8.4.33 Mean Market Baseline Installed Costs, Total Annual Energy Consumption, 

and Percentage Change for Single Package Heat Pumps by Region by Efficiency Level 

(SEER Value) 

Efficiency 

Level 

(SEER) 

Nation Hot-Humid Hot-Dry Rest of Country 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Installed 

Cost 

2008$ 

Total 

Energy 

kWh 

Market 

Baseline 3,293 5,070 3,064 5,436 3,785 5,013 3,237 4,830 

Percentage Change from Market Baseline 

13.5 0.3 (0.8) 0.3 (0.8) 0.3 (0.9) 0.3 (0.7) 

14 3.6 (3.7) 3.7 (3.9) 3.5 (4.0) 3.5 (3.1) 

14.5 8.3 (5.8) 8.5 (6.4) 8.0 (6.6) 8.1 (4.4) 

15 12.4 (7.8) 12.7 (8.7) 12.1 (9.1) 12.2 (5.6) 

15.5 17.2 (11.6) 17.6 (12.2) 16.8 (12.5) 16.9 (10.1) 

16 22.9 (15.1) 23.5 (15.4) 22.3 (15.6) 22.5 (14.1) 

16.4 28.6 (16.4) 29.3 (16.9) 27.8 (17.2) 28.1 (14.9) 

*Values in parentheses denote negative values. 

8-81 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

Nation Hot-Humid 

Hot-Dry Rest of Country 

Figure 8.4.13 Market Baseline Distributions of LCC for Single Package Heat Pumps by 

Region 

8.4.4.1 Mean LCC Savings for Single Package Heat Pumps by Region 

Because the values of most inputs are uncertain in this analysis, DOE represents them as 

a distribution of values rather than a single point-value. Thus, DOE also represents the LCC 

results as a distribution of values. In Table 8.4.34 DOE presents average values for LCC savings 

to show how these savings vary with efficiency for the single package CHP product classes and 

by region. 

Table 8.4.34 Mean LCC Savings for Single Package Heat Pumps by Region by Efficiency 

Level (SEER Value) 

Efficiency 

Level SEER HSPF 

LCC Savings by Region 2008$ 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 27 34 54 (3) 

3 14 8 31 54 96 (44) 

4 14.5 8 (65) (10) 30 (199) 

5 15 8 (146) (62) (21) (340) 

6 15.5 8.5 (169) (88) (21) (379) 

7 16 9 (253) (168) (91) (480) 

8 16.4 9 (455) (336) (291) (720) 

*Values in parentheses denote negative values. 

8-82 

EERE-2008-BT-STD-0006 COMMENT 54
The results shown in Table 8.4.34 are mean values and do not show the distributions of 

savings. Thus, although observations can be made as to how the various inputs impact life-cycle 

cost and, in turn, how the resulting life-cycle costs change with efficiency, conclusions should 

only be drawn from the distribution of life-cycle cost results that are presented in Figure 8.4.14. 

Section 8.4.4.3 provides information on the percentages of consumers in each region at each 

efficiency level that would experience LCC savings benefits, LCC cost increases, and no impact 

from the standard. 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Humid 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

National 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

` 

Hot-Dry 

-2000 

-1500 

-1000 

-500 

0 

500 

1000 

1500 

2000 

2 3 4 5 6 7 8 

Efficiency Level 

Life-cycle Cost Savings($) 

Mean Median 

Rest-of-Country 

Figure 8.4.14 Plots of the Distributions of LCC Savings for Single Package Heat Pumps by 

Region 

8.4.4.2 Mean PBP Results for Single Package Heat Pumps by Region 

This section presents PBP results for the efficiency improvement levels specified in the 

engineering analysis (Chapter 5) and also presented in section 8.2.2.2, Standard-Level 

Manufacturer Price Increases. The results presented here are based on annual operating costs 

calculated from residential and commercial electricity tariffs. Section 8.3 describes the PBP 

inputs. 

Similar to LCC, the analysis provides an estimate of the simple payback period at 

different ranges of energy prices, sales taxes, and installation costs that prevail across the country 

for each efficiency level and each building (building) type. Table 8.4.35 shows the effect on 

payback period as the level of efficiency changes from the market baseline for single package 

CHP products in residential and commercial buildings for each region’s energy prices, sales 

taxes, and installation costs. 

Similar to the LCC differences, DOE depicted PBP results as a distribution of values. 

The means of these distributions are shown in Table 8.4.35 and the distributions of values for 

8-83 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

40 

60 

80 

PBP are shown in Figure 8.4.15. Mean rebuttable PBP for each region and efficiency level is 

shown in Table 8.4.36. In addition, DOE provides data on the median PBP for each efficiency 

level in each region in section 8.4.4.3. 

Table 8.4.35 Mean Payback Period for Single Package Heat Pumps by Region (Years) 

Efficiency 

Level SEER HSPF 

Payback Period by Region years 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 21.5 15.5 16.3 30.0 

3 14 8 27.6 19.9 19.8 39.0 

4 14.5 8 42.2 30.3 27.9 64.1 

5 15 8 46.5 33.3 30.2 72.3 

6 15.5 8.5 39.8 30.5 29.2 56.1 

7 16 9 39.8 32.0 31.0 53.0 

8 16.4 9 47.0 38.0 36.0 63.6 

Table 8.4.36 Mean Rebuttable Payback Period for Single Package Heat Pumps by Region 

(Years) 

Efficiency 

Level SEER HSPF 

Payback Period by Region years 

Nation 

HotHumid Hot-Dry Rest of 

Country 

2 13.5 7.85 8.8 7.3 7.8 11.1 

3 14 8 11.1 9.0 9.7 13.6 

4 14.5 8 15.0 11.4 11.4 21.1 

5 15 8 16.4 12.2 12.1 24.0 

6 15.5 8.5 13.1 11.3 10.8 16.6 

7 16 9 13.0 11.7 11.1 15.7 

8 16.4 9 15.2 13.4 12.8 18.7 

120 120 

100 100 

2 3 4 5 6 7 8 

Efficiency Level 

2 3 4 5 6 7 8 

Efficiency Level 

Payback Period (years) Payback Period (years) Payback Period (years) Payback Period (years) 

80 

60 

40 

20 20 

0 0 

Mean Median National Mean Median Hot-Humid 

120 120 

100 100 

2 3 4 5 6 7 8 

Efficiency Level 

` 

2 3 4 5 6 7 8 

Efficiency Level 

80 

60 

40 

20 20 

0 0 

Mean Median Hot-Dry Mean Median Rest-of-Country 

Figure 8.4.15 Plots of the Distributions of PBP for Single Package Heat Pumps by Region 

8-84 

40 

60 

80 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

8.4.4.3 Detailed Regional Results for Single Package Heat Pumps 

This section provides data on the detailed results for single package CHP life-cycle cost, 

the components of life-cycle cost, life-cycle cost savings, and payback period. These details are 

shown separately by region and efficiency level. Table 8.4.37 through Table 8.4.40 present these 

details for each region by efficiency level. 

Nation 

Table 8.4.37 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Nation 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,293 715 10,440 - - - - - -

13.5 3,303 711 10,408 27 22 50 28 7.5 21.5 

14 3,411 700 10,401 31 45 18 37 10.5 27.6 

14.5 3,566 695 10,503 (65) 67 7 26 20.2 42.2 

15 3,702 690 10,586 (146) 74 2 24 24.9 46.5 

15.5 3,861 677 10,609 (169) 74 0 26 19.9 39.8 

16 4,048 667 10,693 (253) 76 0 24 20.5 39.8 

16.4 4,236 669 10,895 (455) 82 0 18 28.1 47.0 

*Values in parentheses denote negative values. 

Hot-Humid Region 

Table 8.4.38 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Hot-Humid Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,064 666 9,746 - - - - - -

13.5 3,073 662 9,710 34 18 50 32 6.1 15.5 

14 3,176 650 9,687 54 38 18 44 8.2 19.9 

14.5 3,324 642 9,756 (10) 60 7 33 13.4 30.3 

15 3,454 635 9,809 (62) 67 2 31 15.6 33.3 

15.5 3,605 623 9,835 (88) 68 0 32 14.3 30.5 

16 3,784 614 9,914 (168) 71 0 29 15.4 32.0 

16.4 3,963 613 10,083 (336) 78 0 22 19.4 38.0 

*Values in parentheses denote negative values. 

8-85 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Hot-Dry Region 

Table 8.4.39 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Hot-Dry Region 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

2008$ 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,785 865 12,451 - - - - - -

13.5 3,796 859 12,400 54 15 50 35 5.2 16.3 

14 3,917 842 12,349 96 33 18 49 7.1 19.8 

14.5 4,090 832 12,419 30 55 7 38 11.4 27.9 

15 4,242 823 12,471 (21) 62 2 36 13.0 30.2 

15.5 4,420 806 12,472 (21) 64 0 36 12.6 29.2 

16 4,630 793 12,542 (91) 67 0 33 13.8 31.0 

16.4 4,840 792 12,741 (291) 75 0 25 17.3 36.0 

*Values in parentheses denote negative values. 

Rest of Country 

Table 8.4.40 LCC and PBP Results for Single Package Heat Pumps by Efficiency Level 

(SEER Value): Rest of Country 

Efficiency 

Level 

Life-Cycle Cost Life-Cycle Cost Savings 

Payback Period 

years 

Average 

Installed 

Cost 2008$ 

Average 

Operating 

Cost 2008$ 

Average 

LCC 

2008$ 

Average 

Savings 

Percent of Households with 

Median Average 

Net 

Cost 

No 

Impact 

Net 

Benefit 

Market 

Baseline 3,237 626 9,504 - - - - - -

13.5 3,246 624 9,484 (3) 31 50 19 12.2 30.0 

14 3,350 619 9,533 (44) 62 18 20 18.5 39.0 

14.5 3,499 621 9,700 (199) 86 7 7 87.1 64.1 

15 3,631 622 9,844 (340) 94 2 4 100.0 72.3 

15.5 3,784 612 9,883 (379) 91 0 9 43.8 56.1 

16 3,965 604 9,984 (480) 90 0 10 36.4 53.0 

16.4 4,146 611 10,224 (720) 95 0 5 70.0 63.6 

*Values in parentheses denote negative values. 

8.5 OFF-MODE AND STANDBY POWER CONSUMPTION 

Residential air conditioners and heat pumps use a small amount of electricity during their 

“off mode” (neither cooling nor heating), especially during periods of mild weather in the spring 

and fall seasons. The principal sources of this off-mode power consumption are crank case 

heaters in the outside unit (approximately 60 watts) and transformers in the inside unit. For this 

8-86 

EERE-2008-BT-STD-0006 COMMENT 54
 

analysis, DOE separately calculated the impact on LCC of thermostatic controls on crank case 

heaters and replacement of transformers with converter units. This analysis was conducted only 

at the national level. The impacts are shown in Table 8.5.1. For the analysis in Table 8.5.1, the 

baseline unit was assumed to have no temperature control, so that the crank case heater is “on” 

whenever the CAC is in the off mode. The other four levels are as follows: 

Level 1 – Temperature controls so that the CCH is only activated below 65°F. 

Level 2 – Temperature controls so that the CCH cycles to hold the compressor at a 

specific temperature. 

Level 3 – Modulating CCH to hold the compressor at a specific temperature. 

Level 4 – Compressor redesign to go to a modulating compressor, which could 

potentially eliminate the need for a CCH. The cost is an estimate for the difference in cost 

between a single-speed compressor and a variable-speed compressor. 

Estimated installed cost is shown in the first column of Table 8.5.1. The installed cost is 

assumed equal the manufacturer’s sales price, plus average national retail markup. There is 

assumed to be no cost for installing the temperature control equipment. There are LCC savings 

through Level 3, for which the payback period is 3.5 years. The LCC savings turn negative at 

Level 4, and the payback period exceeds the average life of the equipment. 

Table 8.5.1 Details of Regional LCC and Payback Period for Off-Mode Power 

Consumption Measure: Crank Case Heaters (National Only) 

Efficiency 

Level 

Life-Cycle Cost 2008$ Savings 

Average 

Installed 

Cost 

Average 

Operating 

Cost 

Average 

LCC 

Average 

LCC 

Savings 

2008$ 

Payback 

Period 

years 

Baseline 8 13 118 - NA 

1 10 6 62 56 0.3 

2 11 4 51 68 0.4 

3 38 4 73 45 3.5 

4 292 0 292 (173) 22.5 

8-87 

EERE-2008-BT-STD-0006 COMMENT 54
REFERENCES
 

1. DOE developed residential marginal electricity prices from tariffs collected in 2008 from a 

representative sample of electric utilities throughout the United States. DOE collected over 

150 residential tariffs from a sample of about 90 electric utilities. DOE also developed 

commercial marginal electricity prices from tariffs for those commercial building 

applications that use residential CAC and CHP equipment. DOE used 260 commercial tariffs 

collected in 2004 and adjusted the values to a 2008 basis using data in Edison Electric 

Institute, EEI Typical Bills and Average Rates Report 

http://www.eei.org/products_and_services/descriptions_and_access/typ_bills_report.htm and 

in Regulatory Research Associates, Inc., Average Regulated Retail Price of Electricity, 2007 

& Comparative Historical Data, 2008. Jersey City, NJ. 

2. EIA (Energy Information Administration). 2009. Updated Annual Energy Outlook 2009 

Reference Case Service Report, April 2009. EIA, Washington, D.C., DOE/EIA-0383 

(2009). 

3 . DOE, 2008. DOE to Pursue Zero-Net Energy Commercial Buildings, Available at 

http://www1.eere.energy.gov/buildings/commercial_initiative/about.html 

4. Letter to Mrs. Rachel Schmeltz, Energy Star Program Manager, Environmental Protection 

Agency from Karim Amrane, Vice President, Regulatory & Research, Air-Conditioning, 

Heating, and Refrigeration Institute (AHRI), “EPA Proposed Draft Energy Star 

Specification for Light Commercial HVAC Equipment,” Jan. 30, 2009. 

5. NREL, 1995. Typical Meteorological Years Derived from the 1961-1990 National Solar 

Radiation Database. National Renewable Energy Laboratory. Golden, CO. 

6. American Society of Heating, Refrigerating and Air-Conditioning Engineers, Inc. 

(ASHRAE). 1999. ASHRAE/IES Standard 90.1-1999, “Energy Efficient Design of New 

Buildings Except Low-Rise Residential Buildings.” Atlanta, Georgia. 

7. FreightCenter.com quotes vary continuously. Quotes cited were obtained at 

http://www.freightcenter.com/QuickQuote.aspx on July 10, 2009. 

8. R.S. Means Company, Inc. 2009. RS Means Residential Cost Data. 28th Annual Edition. 

R.S. Means Company, Inc. Kingston , MA., 725 pp. 

9. R.S. Means Company, Inc. 2009. RS Means CostWorks 2009. 

http://www.meanscostworks.com. Accessed March 19, 2009. 

10. U.S. Bureau of the Census. American Factfinder. 2007 Population Estimates, Detailed 

Tables. 

http://factfinder.census.gov/servlet/DTGeoSearchByListServlet?ds_name=PEP_2007_EST 

&_lang=en&_ts=257948836197. (Accessed April 15, 2009.) 

8-88 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

11. U.S. Bureau of the Census. American Factfinder. 2008 Population Estimates, Detailed 

Tables. 

http://factfinder.census.gov/servlet/DTGeoSearchByListServlet?ds_name=PEP_2008_EST 

&_lang=en&_ts=257949675405. (Accessed April 15, 2009.) 

12. Coughlin, Katie, Richard White, Chris Bolduc, Diane Fisher and Greg Rosenquist. The 

Tariff Analysis Project: A database and analysis platform for electricity tariffs. 2006. 

Lawrence Berkeley National Laboratory: Berkeley, CA. Report No. LBNL-55680. For 

data updates see the website <tariffs.lbl.gov>. 

13. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy. 

Technical Support Document: Energy Efficiency Program for Commercial and Industrial 

Equipment: Commercial Unitary Air Conditioners and Heat Pumps. July, 2004. 

Washington, D.C. Chapter 8. 

<http://www1.eere.energy.gov/buildings/appliance_standards/commercial/pdfs/cuac_tsd_c 

hp_8.pdf> 

14. Coughlin, K., C. Bolduc, R. Van Buskirk, G. Rosenquist and J. E. McMahon. Tariff-based 

Analysis of Commercial Building Electricity Prices. 2008. Lawrence Berkeley National 

Laboratory: Berkeley, CA. Report No. LBNL-55551. 

15. U.S. Department of Energy, Energy Information Administration (EIA). 2003 Commercial 

Building Energy Consumption Survey, Consumption and Expenditures (CBECS), Public 

Use Data, 2003. Micro-data files on EIA website: 

ftp://ftp.eia.doe.gov/emeu/cbecs/microdata.html 

16. Regulatory Research Associates. Average Regulated Retail Price of Electricity, 2007 & 

Comparative Historical Data. 2008. Jersey City NJ. 

17. Edison Electric Institute, EEI Typical Bills and Average Rates Report (Winter 2007, 

Summer 2007, Winter 2008 and Summer 2008). Washington, DC. 

18. U. S. Department of Energy – Energy Information Administration. Form EIA-861 Annual 

Electric Power Industry Database. 

<http://www.eia.doe.gov/cneaf/electricity/page/eia861.html> 

19. The sites visited included: Ask Me Help Desk (http://www.askmehelpdesk.com/heatingair-conditioning/labor-cost-replace-air-compressor-228111.html), Yahoo! Answers 

(http://answers.yahoo.com/question/index?qid=20080809203714AAhtqbk), All Experts 

(http://en.allexperts.com/q/Heating-Air-Conditioning-696/AC-Compressor-ReplacementCosts.htm), Home Inspector Locator 

(http://www.homeinspectorlocator.com/resources/Costtorepair.htm). (All were accessed on 

April 15, 2009) Also visited were the Harkness Repair and Maintenance Cost Guide for 

Western Pennsylvania http://cost-guide.com/costlst1.html Ingram’s Water and Air 

Equipment Labor Warranties page http://ingramswaterandair.com/-i-14.html, and Accutex 

8-89 

EERE-2008-BT-STD-0006 COMMENT 54
Home Inspection Service Inc. page on Buying and Air Conditioner 

http://www.accutekhomeinspection.com/library/cooling.html. 

20. Direct Energy, 

http://www.directenergy.com/EN/Ontario/RES/Pages/HC/CoolingRepairAndService.aspx 

(Accessed April 15, 2009). 

21. U.S. Department of Energy–Energy Information Administration. Residential Energy 

Consumption Survey, Public Use Data Files.. U.S. Department of Energy: Washington, 

D.C. <www.eia.doe.gov/emeu/recs/recspubuse05/pubuse05.html> 

22. U.S. Census Bureau, Housing and Household Economic Statistics Division. American 

Housing Survey. Washington, DC. 

<http://www.census.gov/hhes/www/housing/ahs/ahs.html> 

23. For reference on the Weibull distribution, see Section 1.3.6.6.8 and 8.4.1.3 of the 

NIST/SEMATECH e-Handbook of Statistical Methods, 

http://www.itl.nist.gov/div898/handbook/. 

24. See sections 4.1.4.3, 4.4.3.2, and 4.4.5.2 of NIST/SEMATECH e-Handbook of Statistical 

Methods, http://www.itl.nist.gov/div898/handbook/. 

25. The Federal Reserve Board. Survey of Consumer Finances. 1989, 1992, 1995, 1998, 2001, 

and 2004. <www.federalreserve.gov/pubs/oss/oss2/scfindex.html> 

26. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, 

Historical Data, Instrument: CDs (secondary market), Maturity: 6-month, Frequency: 

Annual, Description: Average rate on 6-month negotiable certificates of deposit (secondary 

market), quoted on an investment basis. 2009. Washington, D.C. 

<www.federalreserve.gov/releases/H15/data.htm> 

27. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, 

Historical Data, Instrument: State and local bonds, Maturity: 20-year, Frequency: 

Monthly, Description: Bond buyer go 20-bond municipal bond index. 2009. Washington, 

D.C. <www.federalreserve.gov/releases/H15/data.htm> 

28. The Federal Reserve Board. Federal Reserve Statistical Release, Selected Interest Rates, 

Historical Data, Instrument: Corporate bonds/Moody’s Seasoned AAA, Frequency: 

Annual, Description: Moody’s yield on seasoned corporate bonds—all industries, AAA. 

2009. Washington, D.C. <www.federalreserve.gov/releases/H15/data.htm> 

29. Mortgage-X, Mortgage Information Service. Cost of Savings Index (COSI), Index History. 

2009. <http://mortgage-x.com/general/indexes/default.asp> (Last accessed, February 25, 

2009.) 

30. Damodaran Online. The Data Page: Historical Returns on Stocks, Bonds, and Bills— 

United States. 2009. <http://pages.stern.nyu.edu/~adamodar/> 

8-90 

EERE-2008-BT-STD-0006 COMMENT 54
 

31. Damodaran Online. 

http://pages.stern.nyu.edu/~adamodar/New_Home_Page/datafile/wacc.htm (Accessed June 

4, 2009). 

32. Economic Report of the President, January 2009. http://www.gpoaccess.gov/eop/ 

(Accessed June 4, 2009). 

8-91 

EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 9. SHIPMENTS ANALYSIS 

TABLE OF CONTENTS 

9.1 INTRODUCTION ........................................................................................................... 9-1 

9.1.1 Definition of Market Segments for the Shipments Analysis ........................................... 9-1 

9.1.2 Fundamental Model Equations ........................................................................................ 9-3 

9.2 DATA INPUTS AND SUPPORTING CALCULATIONS ............................................ 9-5 

9.2.1 Historical Shipments and the Calculation of Replacement Shipments ............................ 9-5 

9.2.1.1 Historical Shipments ...................................................................................... 9-5 

9.2.1.2 Calculation of Replacement Shipments......................................................... 9-7 

9.2.2 Shipments to New Construction ...................................................................................... 9-7 

9.2.3 Model Calibration and New Owners ............................................................................. 9-10 

9.3 DECISION MODEL FOR NEW OWNERS AND REPLACEMENTS ....................... 9-11 

9.3.1 Purchase Price Elasticity................................................................................................ 9-11 

9.3.2 Impact from Increase in Relative Price.......................................................................... 9-13 

9.3.2.1 New Owner Shipment Impacts and Equipment Switching.......................... 9-14 

9.3.2.2 Replacement Shipment Impacts ................................................................... 9-15 

9.4 REGIONAL SHIPMENTS MODEL............................................................................. 9-15 

9.4.1 Allocation of Historical Shipments to Regions ............................................................. 9-16 

9.4.2 Regional New Construction and New Construction Saturations ................................... 9-19 

9.4.2.1 Regional New Construction ......................................................................... 9-19 

9.4.2.2 Regional New Construction Saturations ...................................................... 9-20 

9.5 RESULTS ...................................................................................................................... 9-22 

9.5.1 Split CAC....................................................................................................................... 9-22 

9.5.2 Single Package CAC ...................................................................................................... 9-30 

9.5.3 Split HP.......................................................................................................................... 9-32 

9.5.4 Single Package HP......................................................................................................... 9-35 

LIST OF TABLES 

Table 9.1.1 CAC and HP Product Classes.............................................................................. 9-2 

Table 9.1.2 Stock Categories, Input Data, Decisions, and Resulting Actions used in the 

Shipments Model ................................................................................................. 9-3 

Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments*......................... 9-6 

Table 9.2.2 Historical New Owner Market Shares of CAC and HP Equipment .................. 9-11 

Table 9.3.1 Change in Relative Price Elasticity following a Purchase Price Change .......... 9-13 

Table 9.4.1 CAC Residential Regional Stock Saturations .................................................... 9-16 

Table 9.4.2 HP Residential Regional Stock Saturations ....................................................... 9-17 

Table 9.4.3 CAC Shipment Regional Allocation Factors..................................................... 9-17 

Table 9.4.4 HP Shipment Regional Allocation Factors........................................................ 9-17 

9-i 

EERE-2008-BT-STD-0006 COMMENT 54
Table 9.4.5 Population Projected for 2020 for Areas defined by the Overlap of Census 

Divisions with Climate Regions ........................................................................ 9-19 

Table 9.5.1 Split CAC: Base Case and Standards Case Cumulative Shipments from 

2016-2046 (millions) ......................................................................................... 9-29 

Table 9.5.2 Single Package CAC: Base Case and Standards Case Cumulative 

Shipments from 2016-2046 (millions)............................................................... 9-32 

Table 9.5.3 Split HP: Base Case and Standards Case Cumulative Shipments from 

2016-2046 (millions) ......................................................................................... 9-34 

Table 9.5.4 Single Package HP: Base Case and Standards Case Cumulative 

Shipments from 2016-2046 (millions)............................................................... 9-36 

LIST OF FIGURES 

Figure 9.2.1 CAC and HP Saturations in Residential New Construction ................................ 9-8 

Figure 9.2.2 CAC and HP Saturation in Commercial New Construction ................................ 9-9 

Figure 9.4.1 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: 

American Housing Survey (AHS) vs. Shipments Model (Calculated).............. 9-18 

Figure 9.4.2 CAC National and Regional Saturations in Residential New Construction ...... 9-20 

Figure 9.4.3 HP National and Regional Saturations in Residential New Construction ......... 9-21 

Figure 9.4.4 CAC and HP National and Regional Saturations in Commercial New 

Construction....................................................................................................... 9-22 

Figure 9.5.1 Forecasted Shipments (Base Case) for Split-System CACs, Coil-Only............ 9-23 

Figure 9.5.2 Forecasted Shipments (Base Case) for Split-System CACs, Blower Coil ........ 9-23 

Figure 9.5.3 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) Replacement 

Shipments Forecasts........................................................................................... 9-25 

Figure 9.5.4 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) New Owner
 

Shipments Forecasts........................................................................................... 9-26 

Figure 9.5.5 Split Coil-Only CAC: Base Case New Construction Shipments Forecasts....... 9-27 

Figure 9.5.6 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) Total Shipments 

Forecasts ............................................................................................................ 9-28 

Figure 9.5.7 Forecasted Shipments (Base Case) for Single Package CACs .......................... 9-30 

Figure 9.5.8 Single Package CAC: Base Case and CSL 7 (16.6 SEER) Total Shipments 

Forecasts ............................................................................................................ 9-31 

Figure 9.5.9 Forecasted Shipments (Base Case) for Split System HPs ................................. 9-32 

Figure 9.5.10 Split HP: Base Case and CSL 10 (19.5 SEER / 10.3 HSPF) Total 

Shipments Forecasts........................................................................................... 9-33 

Figure 9.5.11 Forecasted Shipments (Base Case) for Single Package HPs ............................. 9-35 

Figure 9.5.12 Single Package HP: Base Case and CSL 7 (16.4 SEER / 9.0 HSPF Total 

Shipments Forecasts........................................................................................... 9-36 

9-ii 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

CHAPTER 9. SHIPMENTS ANALYSIS 

9.1 INTRODUCTION
 

Estimates of future product shipments are a necessary input to calculations of the national 

energy savings (NES) and net present value (NPV), as well as to the manufacturer impact 

analysis (MIA). This chapter describes the data and methods the U.S. Department of Energy 

(DOE) used to forecast annual product shipments, and presents results for each of the central air 

conditioner (CAC) and heat pump (HP) product classes being considered in this analysis. The 

shipments model divides the population of appliance users into specific market segments and 

estimates the shipment of new equipment to each of these segments under each candidate 

standard level (CSL). The model starts from a historical base year and calculates, for each year 

of the analysis period, both shipments and retirements by market segment. This approach 

produces an estimate of the total equipment stock, broken down by age or vintage, in each year 

of the analysis period. The equipment stock distribution is calculated for the base case and for 

each CSL as well as for each product class. The stock distribution is used in the national impact 

analysis (NIA) to estimate the total dollar and energy costs and benefits associated with each 

CSL. 

The shipments model was developed as a Microsoft Excel spreadsheet that is accessible 

on DOE’s Appliance and Commercial Equipment Standards website 

(http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp.html). 

Appendix 10-A discusses how to access and utilize the shipments model spreadsheet, which is 

integrated into the spreadsheet for the NIA. The rest of this chapter explains how the shipments 

model is constructed and provides some summary output. The rest of section 9.1 describes the 

methodological approach. The analysis incorporates a large number of components or market 

segments, describing different product classes, market sectors and geographic regions; for 

simplicity, the methodology is explained for a single product class for residential consumers for 

the country as a whole. Section 9.2 defines the input data, pre-processing and calibration steps 

that are used in the model. Section 9.3 defines the decision models used to differentiate between 

the base case and the CSLs. Section 9.4 presents the modifications to the input data that were 

used to develop shipments models specific to the three regions (hot-humid, hot-dry and rest-ofcountry) used in the analysis. Section 9.5 presents summary output from the shipments model, 

including the shipments forecast for the base cases and different energy conservation standardlevel scenarios. The methodology used to develop price elasticities is described in Appendix 9-

A. 

9.1.1 Definition of Market Segments for the Shipments Analysis 

The shipments model disaggregates the total stock according to the following 

characteristics: 

9-1 

EERE-2008-BT-STD-0006 COMMENT 54
 

1.	 Product class: there are four product classes as summarized in Table 9.1.1. DOE further 

disaggregated the split system CAC product class into two unit types: coil-only and 

blower coil units. Although not considered as separate product classes, DOE structured 

the shipments model to analyze both split CAC coil-only and split CAC blower coil 

systems separately. 

2.	 Market sector: residential and commercial building sectors; approximately 93 percent of 

shipments are to the residential sector with the balance going to the commercial sector.1 

This ratio is held constant over the analysis period. 

3.	 Repair status: this is defined as default (i.e., normal repairs and maintenance as accounted 

for in the lifetime of the equipment) or extended repair (ER). The shipments model 

allows for the price increase associated with a CSL to influence the consumer decision to 

repair, rather than replace, broken equipment. The extended repair stock category 

represents equipment that has been repaired after failure. This component of the stock is 

accounted for separately because it is further assumed that equipment that has undergone 

one extended repair will last another six years and then be replaced. This category is 

referred to as extended repair because it models major equipment failures; minor repairs 

are accounted for in the annual maintenance costs and determination of equipment 

lifetimes. 

Table 9.1.1 CAC and HP Product Classes 

Product Type Product Class Unit Type 

Coil-Only 

Central Air Conditioner (CAC) Split System Blower Coil 

Single Package NA 

Heat Pump (HP) Split System NA 

Single Package NA 

Each market sector (i.e., residential and commercial) is further disaggregated into three 

product placement channels (hereafter referred to as “channels”) as follows: 

1.	 New construction: a certain fraction of new buildings are assumed to acquire CAC and 

HP equipment in the year of construction. This fraction is defined as the new construction 

saturation, which varies by year, by region, and by product type. 

2.	 Existing owners: these are defined as existing buildings with CAC and HP equipment 

installed. This category receives new shipments when existing equipment is replaced. 

3.	 New owners: these are defined as existing buildings that acquire CAC and HP equipment 

for the first time during the analysis period. The fraction of new owners is estimated from 

trends in overall market saturation. As described later in this chapter, the new owner 

channel is necessary for calibrating the shipments model to historical shipments. 

9-2 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

These three channels are treated differently in the way that the consumer decision is 

modeled. For new construction the placement of equipment is automatic, in line with observed 

trends in the data. For new owners, the consumer decision to purchase CAC and HP equipment is 

affected by the change in purchase price and operating costs; for this category, the number of 

new purchases will generally decrease for the higher CSLs. In those cases where new owners of 

CAC and HP equipment have been modeled to forego a new purchase, DOE assumed that 

potential new owners would purchase alternative space-conditioning systems; room air 

conditioners in the case of CAC consumers and combination warm-air electric resistance 

furnaces and CACs in the case of HP consumers. For existing owners, the repair versus replace 

decision is also affected by the change in ownership cost associated with higher efficiency. In 

those cases where existing owners have been modeled as being affected by higher ownership 

costs, DOE assumed they would perform an extended repair which prolongs the life of the 

equipment by six years, after which the equipment would be replaced. The three channels and 

related decisions modeled in the spreadsheet are summarized in Table 9.1.2. 

Table 9.1.2	 Stock Categories, Input Data, Decisions, and Resulting Actions used in the 

Shipments Model 

Category Input data Decision Action 

Equipment Stock = 

+ new construction nc_starts (year) buy => add to equip_stock, age=0 nc_saturation(year) 

- demolitions housing demolitions(year) remove => subtract from equip_stock Equip_stock(age, year) 

+ existing owners 

Equip_stock(age, year) does not break => stays in equip_stock; increment age 

survival_function(age) breaks: replace => add to equip_stock, age=0 

Repair_probability(year) breaks: repair => convert to ER_equip_stock, a2=0 

Extended Repair ER_equip_stock(year,a2) a2 < 6 years => stays in ER_equip_stock; increment a2 

a2=6 years, replace => add to equip_stock, age=0 

New owners 

(no CAC or HP) 

housing_stock(year) buy => add to equip_stock, age=0 Equip_stock(age, year) 

max_saturation(year) do not buy => stays in no cooling stock purchase_probability(year) 

9.1.2 Fundamental Model Equations 

The fundamental dependent variable in the shipments model is the equipment stock 

which is represented as a function of analysis year (indexed by j), and equipment vintage or age 

(the equipment age is noted as a, and is equal to the analysis year minus the vintage). The stock 

function is adjusted in each year of the analysis period by new shipments coming in and broken 

or demolished equipment being taken out. 

For existing stock: 

9-3 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Stock (j,a) = Stock (j − 1,a − 1)− Rem (j,a) p p p

and for new units: 

Stockp (j,a = 1) = Shipp (j − 1).

Where: 

Stockp (j, a) = number of units of product class p and age a in analysis year j, 

Remp (j, a) = number of units of product class p and age a removed in analysis year j, 

and 

Shipp(j) = number of units of product class p shipped in year j. 

Shipments are directed to one of the three channels: 

Ship (j) = Rpl (j)+ NC (j)+ NO (j) p p p p

Where: 

Rplp(j) = number of units of product p replaced in year j; it depends on removals, 

NCp(j) = number of units installed in new construction of product p in year j, and 

NOp(j) = number of units shipped to “new owners” of product p in year j. 

Removals due to equipment breakage contains two terms. In the first, a survival function 

fp(a) is used to represent the probability that a unit of age a will survive in a given year; 

equivalently the probability that this unit will fail is 1- fp(a). The second term is the extended 

repair stock that has been in use for six years following the repair date. Total removals in the 

base case are then: 

Rem (j,a) = [1 − f (a)]× Stock (j,a)+ ER _Stock (j,a2 = 6) p p p p

Where: 

a2 = number of years since the equipment was repaired, and 

ER_Stockp(j, a2) = number of extended-repair units of product p replaced in year j. 

The new construction and new owner markets depend on changes to the building stock, which is 

included as a component of the shipments model. This is discussed in the next section. 

9-4 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

9.2 DATA INPUTS AND SUPPORTING CALCULATIONS
 

Data inputs and supporting calculations that are necessary for the shipments model are 

explained in detail in the following sections. 

9.2.1 Historical Shipments and the Calculation of Replacement Shipments 

9.2.1.1 Historical Shipments 

DOE used historical shipments data (i.e., domestic shipments and imports) to populate its 

shipments model for CAC and HP equipment. As part of its data submittal to the DOE standards 

rulemaking, the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) provided 

historical shipments data over the 1990-2007 time-period disaggregated into the four primary 

product classes.2 Historical shipments from 1972-1989 were also provided by AHRI from 

previous data submittals to the Lawrence Berkeley National Laboratory (LBNL).3

 The data for 

1972-1989 included some shipments of 3-phase as well as single-phase CAC and HP, whereas 

the data for 1990-2007 included only single-phase CAC. DOE disaggregated the shipments for 

single-phase and 3-phase CAC and HP equipment in the earlier data and included only single 

phase units in the analysis. 

DOE further broke down split system CAC historical shipments into coil-only and blower 

coil unit shipments. Because DOE believes that a majority of split CAC shipments are coil-only 

units, it estimated that coil-only units account for 90 percent of annual split system shipments. 

As discussed earlier in section 9.1.1, DOE divided all historical shipments for all product 

classes into two market segments, i.e., the residential and commercial building sectors. DOE 

allocated 93 percent of historical shipments to the residential building sector and the remaining 

seven percent to the commercial building sector. 

Table 9.2.1 summarizes the historical shipments data. DOE developed a total stock 

estimate for each product class and market segment by integrating historical shipments. Over 

time, units are retired and removed from the stock based on a survival function as discussed in 

section 9.1.1, triggering the purchase of a new unit. Because of the relationship between 

retirements and total stock, there is a strong correlation between past and future shipments, 

independent of conservation standards. 

9-5 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 9.2.1 Central Air Conditioner and Heat Pump Historical Shipments* 

Year 

Split CAC** 

thousands

Single Package CAC 

 thousands 

Split HP 

thousands 

Single Package HP 

thousands 

1972 1,489 257 28 52 

1973 1,742 318 35 52 

1974 1,503 289 49 48 

1975 888 159 83 45 

1976 1,219 231 177 74 

1977 1,364 218 329 89 

1978 1,546 253 389 97 

1979 1,428 248 376 107 

1980 1,233 134 293 61 

1981 1,293 122 348 66 

1982 1,037 111 267 49 

1983 1,558 192 455 82 

1984 1,857 189 535 98 

1985 1,784 203 619 107 

1986 1,876 203 680 106 

1987 2,204 237 714 103 

1988 2,334 247 649 91 

1989 2,516 267 650 91 

1990 2,241 334 643 104 

1991 2,388 306 615 96 

1992 2,254 330 647 101 

1993 2,474 346 718 107 

1994 3,087 387 825 118 

1995 3,221 384 834 120 

1996 3,635 418 936 139 

1997 3,364 395 917 142 

1998 4,010 406 1,019 148 

1999 4,317 429 1,044 147 

2000 4,280 437 1,073 159 

2001 3,931 361 1,180 165 

2002 4,381 380 1,229 165 

2003 4,281 390 1,350 174 

2004 4,561 414 1,584 190 

2005 5,461 455 1,810 213 

2006 4,038 330 1,807 190 

2007 3,582 338 1,570 199 

Source: AHRI 

* For each product class, 93 percent of annual shipments are allocated to the residential building sector and the 

remaining seven percent are allocated to the commercial building sector. 

**Annual split CAC shipments are disaggregated into coil-only and blower coil unit shipments. Coil-only unit 

shipments estimated to comprise 90 percent of annual split CAC shipments. 

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9.2.1.2 Calculation of Replacement Shipments 

When an equipment unit is broken, it is removed from the stock. The following 

retirement function rp(a) is used to represent the probability that a unit will be broken at age a. 

Re mp (j) = ∑ ra (a)× Stockp (j,a) a

Retirement functions and product lifetimes are discussed in more detail in Chapter 8. The 

average lifetimes are 18.3 years for split and single package CAC equipment and 15.5 years for 

split and single package heat pumps. 

In each year, equipment are removed with demolished buildings. As represented by the 

following expression, the shipments model assumes that the saturation of the equipment in the 

demolished buildings is the same of that of the overall population. 

D( )j = H _ Stock(j −1)+ H _ Starts(j)− H _ Stock(j)

Dem( j) = D( j)× sat( p, j −1)

Where: 

H_Stock (j) = number of housing units in analysis year j, 

H_Starts(j) = number of new housing units in year j, 

D(j) = number of demolished buildings, and 

Dem (j) = number of equipment units demolished in analysis year j. 

sat(p,j) = saturation of equipment of product class p for all buildings in year j 

The shipments model assumes that units that are going away with demolished buildings, 

Dem(j), are included in the mix of broken units Remp (j). Since the demolished units do not need 

to be replaced, they are deducted from Remp(j) when calculating the required replacements, as 

represented by the following expression. 

Rpl p (j) = Re mp (j)− Dem(j)

9.2.2 Shipments to New Construction 

DOE multiplied new construction market saturations by forecasts of new construction to 

estimate CAC and HP shipments to the new construction channel. On a product class basis, the 

determination of shipments to new construction is represented by the following expression. 

NC p (j) = NC _ Starts(j)× NC _ Sat p (j)

Where: 

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EERE-2008-BT-STD-0006 COMMENT 54
NC_Starts (j) = number of new construction starts in year j, and 

NC_Sat(j) = new construction saturation for product class p and year j. 

For the residential market segment, DOE developed new construction market saturations 

from Characteristics of New Housing data from the U.S. Census Bureau.4

 CAC and HP 

historical and projected saturations are depicted in Figure 9.2.1. DOE used historical new 

construction saturations for all CAC and HP equipment to project saturations into the future. As 

evidenced in Figure 9.2.1., DOE used a logistic fit to the historical data to estimate future 

saturations. DOE used product class market shares based on historical shipments (as shown in 

Table 9.2.1) to calculate specific market saturations fore each CAC and HP product class. 

Saturation = 0.10Ln(Year-1977) + 0.52 

R2 = 0.94 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

0 10 20 30 40 50 60 70 

Year - 1977 

Residential New Consturciton Saturaitons

CAC + HP 

HP 

CAC 

Figure 9.2.1 CAC and HP Saturations in Residential New Construction 

DOE determined new construction starts to the residential market segment, otherwise 

referred to as housing starts, by using recorded data through 2007 and projections from the DOEEnergy Information Administration (EIA)’s Annual Energy Outlook 2009 (AEO2009) for the 

period 2008–2030.5

 New housing includes newly constructed single- and multi-family units, 

termed “new housing completions,” and mobile home placements. AEO2009 provides three sets 

of economic growth scenarios: a Reference case, a High Economic Growth case, and a Low 

Economic Growth case. The original AEO2009 analysis published by the EIA in March 2009 

was modified in April 2009 to incorporate the effects of the American Recovery and 

Reinvestment Act.1

 DOE used the high and low growth scenarios from the March 2009 release 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

of the AEO20096

, and the Reference case from the modified April release. For 2031−2046, DOE 

froze completions at the 2030 level for all three economic scenarios. 

For the commercial market segment, DOE developed new construction market 

saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS).7 

Past CBECS surveys for the years 1992, 1995, 1999, and 2003 provided the saturation of 

residential-type central air conditioners in all new commercial buildings by Census Division. To 

determine nationally representative saturation values, DOE calculated a weighted-average 

saturation based on historical construction commercial starts by Census Division (in millions of 

square feet) from AEO2009. DOE considered residential-type central air conditioners to 

comprise all split system and single package CAC and HP equipment. DOE used product class 

market shares based on historical shipments to calculate specific market saturations for each 

CAC and HP product class. Figure 9.2.2 depicts the new construction saturations for the 

commercial market segment. Actual data from CBECS are shown as “black diamonds” in 

Figure 9.2.2. Saturations prior to 1992 were fixed by DOE to the 1992 value. DOE used linear 

interpolation to develop the saturations for non-CBECS years between 1992 and 2003. DOE 

averaged the saturations for the four CBECS years to forecast saturation values after the year 

2003. 

0% 

1% 

2% 

3% 

4% 

5% 

6% 

1990 1995 2000 2005 2010 2015 2020 2025 2030 

Year 

Saturation (percent sq.ft. cooled

by CAC and HP) 

Sources: DOE-EIA, CBECS; AEO2009

Figure 9.2.2 CAC and HP Saturation in Commercial New Construction 

As with the residential market segment, DOE determined new construction starts to the 

commercial building market segment by using recorded data through 2007 and projections from 

EIA’s AEO2009 for the period 2008–2030. For 2031−2046, DOE froze completions at the 2030 

9-9 

EERE-2008-BT-STD-0006 COMMENT 54
 

level for all three economic scenarios. DOE used the same data sources that were used for the 

residential market to estimate new construction starts for a Reference case, a High Economic 

Growth case, and a Low Economic Growth case. 

9.2.3 Model Calibration and New Owners 

The shipments model begins with an estimate of the building stock and equipment stock 

in the base year, and steps forward adding shipments each year and removing retirements. In 

principle, only building and market saturation data are needed to allow the shipments model to 

estimate shipments to new construction and replacements. The third product channel, new 

owners, is more difficult to describe based on existing data. However, the historical shipments 

data (as described above in section 9.2.1.1) can be used to calibrate the shipments model and 

improve the representation of the new owner market. 

To calibrate estimated shipments with the historical data, as represented by the following 

expression, DOE treated the new owner market NOp(j) as a residual after shipments for new 

construction and replacements were subtracted from total shipments. 

NOp (j) = Ship p (j) − Rpl p (j) − NC p (j)

The three terms on the left are known quantities (calculation of Rplp(j) and NCp(j) are described 

above). 

The results of the historical calibration are shown in Table 9.2.2. The values are 

historical market shares of total CAC and HP equipment in the new owner channel. The 

residential market share is the total CAC and HP shipments to the new owner housing market 

divided by the number of households without either CACs or HPs. The commercial market 

share is the number of total CAC and HP shipments to the new owner commercial building 

market divided by the commercial building stock not conditioned by CAC and HP equipment. 

DOE determined the commercial building stock not conditioned by CAC and HP equipment by 

dividing the total stock in square feet by 500 square feet (i.e., the amount of square feet 

conditioned by one piece of CAC and HP equipment). DOE used product class market shares 

based on historical shipments (as shown in Table 9.2.1) to calculate specific new owner market 

saturations fore each CAC and HP product class. 

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Table 9.2.2 Historical New Owner Market Shares of CAC and HP Equipment 

Year Residential Commercial 

1990 2.05% 0.10% 

1991 1.78% 0.09% 

1992 1.35% 0.08% 

1993 1.59% 0.07% 

1994 2.25% 0.07% 

1995 2.43% 0.06% 

1996 3.22% 0.11% 

1997 2.53% 0.10% 

1998 3.34% 0.15% 

1999 3.82% 0.19% 

2000 4.04% 0.16% 

2001 3.31% 0.12% 

2002 4.10% 0.12% 

2003 3.93% 0.09% 

2004 4.81% 0.14% 

2005 7.75% 0.15% 

2006 3.51% 0.07% 

2007 1.94% 0.02% 

To forecast future shipments to the new owner market, DOE calculated the average 

market share over the 1990 to 2007 time-period for the residential and commercial markets, 

3.21% and 0.10%, respectively, and held the market share fixed from 2008-2046. 

9.3 DECISION MODEL FOR NEW OWNERS AND REPLACEMENTS 

In the shipments model, two sets of consumer purchase decisions are modeled. These 

decisions are influenced by the purchase price and operating cost of equipment, and therefore 

will be different in the base case vs. different CSLs. These decisions are modeled by estimating 

the purchase price elasticity for cooling equipment. The purchase price elasticity is defined as the 

change in the percentage of consumers acquiring CAC and HP equipment divided by a change in 

the relative price (defined below) for that equipment. This elasticity and information obtained 

from the life-cycle cost (LCC) and payback period (PBP) analysis on the change in purchase 

price and operating costs under different CSLs are used in the shipments model to estimate the 

resulting change in equipment shipped. 

9.3.1 Purchase Price Elasticity 

DOE conducted a literature review and an analysis of appliance price and efficiency data 

to estimate the combined effects on product shipments from increases in product purchase price, 

decreases in product operating costs, and changes to household income. Appendix 9-A provides 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

a detailed explanation of the methodology DOE used to quantify the impacts from these 

variables. 

Existing studies of appliance markets suggest that the demand for appliances is priceinelastic. Other information in the literature suggests that appliances are a normal good, so that 

rising incomes increase the demand for appliances, and that consumers use relatively high 

implicit discount ratesa

 when comparing appliance prices and appliance operating costs. 

DOE used the available data for the period 1980-2002 on large appliance purchases to 

evaluate broad market trends and conduct simple regression analyses. These data indicate that 

there has been a rise in appliance shipments and a decline in appliance purchase price and 

operating costs over the time period. Household income has also risen during this time. Because 

purchase decisions are sensitive to income, and also to potential savings in the operating cost of 

the appliance, DOE combined the available economic information into one variable, termed the 

relative price. This variable was used in a regression analysis to parameterize historical market 

trends. The relative price is defined with the following expression: 

TP PP + PVOC RP = = Income Income

Where: 

RP = relative price, 

TP = total price, 

Income = household income, 

PP = appliance purchase price, and 

PVOC = present value of operating cost, based on an implicit discount rate of 37 

percent. 

DOE’s regression analysis of the relevant data suggests that the relative price elasticity of 

demand is approximately -0.34; this implies that a relative price increase of 10 percent results in 

a 3 to 4 percent decrease in shipments. Note that the relative price elasticity incorporates the 

impacts from purchase price, operating cost, and household income, so the impact from any 

single effect can be mitigated by changes from the other two effects. The relative price elasticity 

of -0.34 is consistent with estimates in the literature, but is based on a small data set. More 

importantly, the measure is based on an assumption that economic variables, including purchase 

price, operating costs, and household income, explain most of the trend in appliances per 

household in the United States since 1980. Changes in appliance quality and consumer 

preferences may have occurred during this period, but DOE did not account for them in this 

analysis. Despite these uncertainties, DOE believes that its estimate of the relative price elasticity 

a

 A high implicit discount rate with regard to operating costs means that consumers do not put much economic value 

on the operating cost savings realized from more-efficient appliances. In other words, consumers are much more 

concerned with higher purchase prices. 

9-12 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

of demand provides a reasonable assessment of the impact that purchase price, operating cost, 

and household income have on product shipments. 

The forecasts of shipments and national impacts due to standards are for a 30-year time 

period, and it is possible that over this time period the numerical value of the relative price 

elasticity could change; in particular, it can be affected by a new standard that changes consumer 

expectations about equipment performance. DOE considered the relative price elasticity 

provided by the preceding analysis to be a short-run value. No data exists to allow the 

determination of long run price elasticities for appliances, so DOE relied on a study pertaining to 

automobiles.8

 This study shows that the automobile price elasticity of demand changes in the 

years following a purchase price change, becoming smaller (more inelastic) until it reaches a 

terminal value around the tenth year after the price change. Table 9.3.1 shows the relative change 

in the price elasticity of demand for automobiles over time. DOE developed a time series of 

relative price elasticities for CAC and CAC-HP based on the relative change in the automobile 

price elasticity of demand. For years not shown in Table 9.3.1, DOE performed a linear 

interpolation to obtain the relative price elasticity. 

Table 9.3.1 Change in Relative Price Elasticity following a Purchase Price Change 

Years Following Price Change 

1 2 3 5 10 20 

Relative Change in 

Elasticity to 1st year 

1.00 0.78 0.63 0.46 0.35 0.33 

Relative Price Elasticity -0.34 -0.26 -0.21 -0.16 -0.12 -0.11 

9.3.2 Impact from Increase in Relative Price 

Using the relative price elasticity, DOE was able to estimate the impact of the increase in 

relative price from a particular CSL. The impact, as shown in the equation below, is expressed as 

a percentage drop in market share for each year, dMSp

j , which is applied in the new owner 

market channel as well as the decision for replacement versus extended repair. As noted in 

section 9.1.1, for the new construction market channel, the placement of equipment is automatic, 

in line with observed trends in the data. In other words, DOE assumed that the new construction 

market channel was unaffected by changes in either the total installed cost or operating costs of 

the equipment as well as changes in household income. 

p

⎡ ⎛

⎜ RP _ std p (j) ⎞

⎟

⎤

dMSj = ⎢1 − ⎜ ⎟

⎥ × eRP ( )j

⎢ RP _base p ( )j ⎥ ⎣ ⎝ ⎠⎦

Where: 

dMSp

j = percentage market share drop for class p, year j, 

RP_stdp(j)= relative price in the standards case for product class p, year j, 

RPp(j)= relative price in the base case for product class p, year j, and 

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eRP(j) = relative price elasticity in year j. 

9.3.2.1 New Owner Shipment Impacts and Equipment Switching 

DOE estimated standards case shipments to the new owner product channel by 

incorporating the impact of the relative price into the standards case shipments forecast. The 

relative price and the relative price elasticity are both a function of time. 

NO _ std (j) = NO (j)× (1 − dMS p

) p p j

Where: 

NO_stdp(j)= shipments to new owners in the standards case for product class p, year j, 

and 

NOp(j)= shipments to new owners in the base case for product class p, year j. 

The new owner market is equal to the total building stock minus the building stock with 

equipment; if each building is assumed to have just one CAC or HP unit then the number of 

building units with CAC and HP equipment is equal to the CAC and HP equipment stock. 

DOE assumed that the new owners impacted by the relative price increase and do not 

purchase the equipment would switch to purchase an alternative type of space-conditioning 

equipment. The number of new owners impacted and switching to an alternative equipment type 

is represented by the following expression. 

p NO _ swp (j) = NOp (j)× dMSj

Where: 

NO_swp(j)= new owners for product class p switching to buy other products, year j. 

For new owner purchases of split system and single package CACs, DOE assumed that 

consumers affected by a relative price increase would switch equipment and purchase a room air 

conditioner rather than a CAC. Because room air conditioners have lower cooling capacities and 

lower overall annual energy consumption than CACs, DOE did not explicitly account for the 

increased sales of room air conditioners in its analysis. Doing so would have credited a standard 

with energy savings from displaced CAC shipments. To avoid including savings from displaced 

shipments to new owners, DOE used the shipments projection estimates for the standards cases 

to calculate the annual energy consumption in the base case. 

For new owner purchases of split system and single package HPs, DOE assumed that 

consumers affected by a relative price increase would switch equipment and purchase a 

combination electric resistance furnace and CAC rather than a HP. In its analysis of HP 

shipments in the NIA (discussed in chapter 10), DOE tracked purchases of electric furnaces and 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

CACs due to decreases in shipments of HPs in order to quantify the energy, operating cost, and 

total installed cost impacts for consumers who were estimated to forgo a purchase of a new HP. 

Because DOE explicitly accounted for the energy consumption, operating cost, and total installed 

cost of the displaced shipments of HPs, it maintained use of the base case shipments to determine 

the annual energy consumption in the base case. 

9.3.2.2 Replacement Shipment Impacts 

For replacement purchases of split system and single package CACs and HPs, DOE 

assumed consumers affected by an increase in total installed cost would repair their equipment 

rather than replace it, extending the life of the product by six years. When the extended repaired 

units fail after six more years, they will be replaced with new ones. 

The model calculates for each year after the standard, the relative percentage market 

drop, dMSp

j, due to the equipment price increase as described in 9.3.1.1. The extended repair is 

only applicable to broken equipment that are purchased before 2016. For broken equipment that 

are purchased after 2016, extended repair will not be considered since there will be no longer a 

price impact from standards between new units and the broken units. 

The number of broken units that will be further repaired instead of being replaced is 

calculated as follows: 

p XRi = ∑Re m( j,a)× dMSi for ( j − a )< 2016 a 

Rpl( )j = ∑Re m( j,a ) − XRi + XR j −6 − Dem( j) a 

Where: 

dMSp

j = percentage market share drop for class p, year j, 

a = age of an equipment 

j = year, 

Rem(j,a) = retiring units in year j of age a, 

XRj = extended repair units, year j, 

Rpl(j) = replacement units in year j, 

Dem (j) = number of units gone with demolished buildings in analysis year j. 

9.4 REGIONAL SHIPMENTS MODEL 

As described in Chapter 6, Energy Use Determination, some of the CSLs involve the 

division of the U.S. into three climate regions: hot-humid, hot-dry, and rest-of-country. For the 

shipments model, DOE constructed two variants of the national analysis. In the first, the nation 

as a whole is treated as a single region. In the second, the U.S. is disaggregated into the three 

climate regions, a separate shipments model is run for each region, and the results are summed to 

9-15 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

provide national-level output under a regional standard scenario. In the regional standards case, 

the mechanics of the shipments model are identical to the one-region case already described. The 

only changes needed to analyze a specific region are definitions of the various data inputs for the 

region in question. This section describes how these data inputs were disaggregated. 

Not every data input can be or needs to be defined at a regional level. DOE assumed the 

product lifetimes, purchase prices, and relative price elasticities did not vary by region. Product 

operating costs do vary by region and this information is available from the LCC and PBP 

analysis (see Chapter 8). For the shipments model, historical shipments, housing starts and 

housing stock, commercial buildings starts and stock (in square feet), and market saturations for 

new construction must be developed for each region. The following sections describe the 

development of regional historical shipments, housing and commercial building starts and stock, 

and market saturations. 

9.4.1 Allocation of Historical Shipments to Regions 

DOE developed regional allocation factors to divide historical shipments into each of the 

three climatic regions. The regional allocation factors were determined by trial and error by 

calibrating to historical residential stock saturations in the American Housing Survey (AHS).9 

Tables 9.4.1 and 9.4.2 provide the historical regional and national stock saturations for CAC and 

HP equipment for every other year between 1991−2007 as specified in the AHS. The stock 

saturations are specific to each region or the nation, i.e., the individual regional stock saturations 

do not add up to the national stock saturation. 

Table 9.4.1 CAC Residential Regional Stock Saturations 

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S. 

1991 32.5% 48.6% 23.8% 30.8% 

1993 33.5% 50.0% 25.0% 32.0% 

1995 36.6% 50.7% 27.3% 33.9% 

1997 42.4% 47.3% 29.2% 36.3% 

1999 48.0% 54.0% 33.3% 41.4% 

2001 51.5% 58.1% 36.6% 45.0% 

2003 53.8% 58.1% 38.5% 46.5% 

2005 55.9% 61.5% 43.0% 50.2% 

2007 63.5% 62.8% 42.8% 51.8% 

Source: AHS 

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Table 9.4.2 HP Residential Regional Stock Saturations 

Year Hot-Dry Hot-Humid Rest of U.S. Entire U.S. 

1991 6.3% 18.1% 3.7% 7.8% 

1993 7.5% 19.7% 3.9% 8.5% 

1995 7.1% 21.6% 4.1% 9.1% 

1997 9.9% 28.0% 4.4% 12.0% 

1999 8.3% 26.8% 4.2% 11.4% 

2001 8.0% 26.2% 4.4% 11.3% 

2003 7.8% 27.4% 4.4% 11.7% 

2005 8.8% 29.0% 5.4% 12.7% 

2007 8.1% 28.8% 5.3% 12.8% 

Source: AHS 

Tables 9.4.3 and 9.4.4 provide the shipment allocation factors for CAC and HP, 

respectively. For each of the years presented in the tables below, DOE used the allocation 

factors to assign the fraction of shipments for each region until the market saturations calculated 

by the shipments model were nearly equal to the regional stock saturations reported by AHS. 

Table 9.4.3 CAC Shipment Regional Allocation Factors 

Year Hot-Dry Hot-Humid Rest U.S. 

1983 15.0% 50.0% 35.0% 

1987 15.0% 45.0% 40.0% 

1990 17.0% 38.0% 45.0% 

1993 17.0% 35.0% 48.0% 

1997 17.0% 30.0% 53.0% 

2001 17.0% 30.0% 53.0% 

2003 17.0% 30.0% 53.0% 

2005 17.0% 32.0% 51.0% 

2007 17.0% 32.0% 51.0% 

Table 9.4.4 HP Shipment Regional Allocation Factors 

Year Hot-Dry Hot-Humid Rest U.S. 

1983 14.0% 75.0% 11.0% 

1987 14.0% 72.0% 14.0% 

1990 14.0% 70.0% 16.0% 

1993 12.0% 70.0% 18.0% 

1997 9.0% 70.0% 21.0% 

2001 9.0% 60.0% 31.0% 

2003 9.0% 50.0% 41.0% 

2005 9.0% 50.0% 41.0% 

2007 9.0% 50.0% 41.0% 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 9.4.1 provides the resulting comparison between the CAC and HP stock 

saturations by region and the entire U.S. from the AHS and those calculated from the shipments 

model. As shown in the figure below, the calculated values are relatively close to the values 

from the AHS. After establishing the appropriate CAC and HP shipment allocation factors, DOE 

used product class market shares based on historical shipments (as shown in Table 9.2.1) to 

calculate specific allocations factors for each CAC and HP product class. 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

CAC & HP Saturation Hot-Dry CAC & HP Saturation Hot-Humid 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 

Saturation 

CAC calculated HP calculated 

CAC AHS HP AHS 

CAC & HP Saturation Entire U.S. 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 

Saturation 

CAC calculated HP calculated 

CAC AHS HP AHS 

CAC calculated 

CAC AHS 

HP calculated 

HP AHS 

Saturation 

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 

CAC & HP Saturation Rest of U.S. 

100% 

90% 

80% 

70% 

60% 

50% 

40% 

30% 

20% 

10% 

0% 

1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 

CAC calculated HP calculated 

CAC AHS HP AHS 

Saturation 

Figure 9.4.1	 Residential CAC and HP Stock Saturations by Region and the Entire U.S.: 

American Housing Survey (AHS) vs. Shipments Model (Calculated) 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

It is worth noting that, once historical shipments are allocated to each of the three 

climatic regions, DOE calculated replacement shipments for each region based on when the 

equipment is forecasted to break. Refer back to section 9.2.1.2 for a description of the method 

for determining replacement shipments. 

9.4.2 Regional New Construction and New Construction Saturations 

9.4.2.1 Regional New Construction 

AEO2009 provides housing forecasts by Census Division. These were converted to the 

three climate regions by using population data to allocate the housing stock. Each state can be 

allocated to both a Census Division and a climate region; hence, a set of overlap regions can 

defined at the state level. For example, Florida is in the hot-humid climate region and the South 

Atlantic census division; therefore, the intersection of hot-humid with South Atlantic contains 

the state of Florida. (The list of states included in each climate region is defined in Chapter 7, 

section 7.11). The U.S. Census provides historical population, and population projections, by 

state at five-year intervals for the years 2005-2030.10 These data were used to define annual 

populations for each of the intersection regions over the same period. First, the Census data were 

interpolated onto one-year intervals by assuming a constant rate of growth within the given fiveyear period. Next, the one-year data were aggregated to provide regional populations. Projections 

out to 2046 were constructed by assuming that the rate of growth in each region would remain 

constant for the years after 2030. The constant in each region was defined as the average of the 

U.S. Census growth rates for 2025 and 2030. Sample output from this calculation is represented 

in Table 9.4.5, which shows the population in each area defined by the overlap of a climate 

region with a census division. For example, both the hot-dry and the rest-of-country regions 

overlap with the Mountain and Pacific census divisions, while the West North Central census 

division is entirely in the hot-humid region. 

Table 9.4.5	 Population Projected for 2020 for Areas defined by the Overlap of Census 

Divisions with Climate Regions 

Region 

Census Division Hot-Dry Hot-Humid Rest-of-Country Total 

Northeast - - 15,309,528 15,309,528 

Mid-Atlantic - - 41,825,909 41,825,909 

East North Central - - 48,208,733 48,208,733 

West North Central - - 21,246,442 21,246,442 

South Atlantic - 49,782,144 18,659,882 68,442,026 

East South Central - 14,554,397 4,424,431 18,978,828 

West South Central - 40,149,965 - 40,149,965 

Mountain 13,993,072 - 11,563,977 25,557,049 

Pacific 42,206,743 - 13,879,323 56,086,066 

Total by Region 56,199,815 104,486,506 175,118,225 335,804,546 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Using these numbers for each census division, the fraction of its population that belongs 

to a given climate region can be determined. This is used to allocate housing stock to climate 

regions. 

In a similar manner, the year-on-year change in population for each Census Division can 

be disaggregated onto the climate regions that overlap that Census Division. The disaggregation 

of population growth is used to allocate housing starts to climate regions. 

The same coefficients are used to allocate commercial building floor space and 

commercial building starts to the three climate regions. 

9.4.2.2 Regional New Construction Saturations 

DOE developed residential regional new construction saturations from Characteristics of 

New Housing data from the U.S. Census Bureau.3

 The data breaks down CAC and HP 

saturations for single-family and multi-family households into the four Census Regions (i.e., 

northeast, midwest, south, and west). DOE used population allocation factors (as discussed 

previously) to properly allocate saturations into the three climate regions (i.e., hot-humid, hotdry, and rest-of-country). Figures 9.4.2 and 9.4.2 depict the national and regional saturations for 

CACs and HPs, respectively. The regional saturations depicted in the figures below were 

determined using the entire U.S. housing stock. In other words, the regional saturations when 

summed equal the national saturation. 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 

Year 

CAC Residential New Construction Saturations

Entire U.S. 

Rest of Country 

Hot-Humid 

Hot-Dry 

Figure 9.4.2 CAC National and Regional Saturations in Residential New Construction 

9-20 

EERE-2008-BT-STD-0006 COMMENT 54
 

0% 

10% 

20% 

30% 

40% 

50% 

60% 

70% 

80% 

90% 

100% 

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050 

Year 

HP Residential New Construction Saturations 

Entire U.S. 

Rest of Country 

Hot-Humid 

Hot-Dry 

Figure 9.4.3 HP National and Regional Saturations in Residential New Construction 

For the commercial market segment, DOE developed new construction market 

saturations from data in EIA’s Commercial Building Energy Consumption Survey (CBECS).6 

As noted above in section 9.2.2, DOE developed new construction saturations through the use of 

past CBECS surveys and commercial starts from AEO2009. The assembled data breaks down 

CAC and HP saturations into nine Census Divisions. DOE used population allocation factors (as 

discussed previously) to properly allocate saturations into the three climate regions (i.e., hothumid, hot-dry, and rest-of-country). Figures 9.4.4 depicts the national and regional saturations 

for CAC and HP equipment. The regional saturations depicted in the Figure 9.4.4 below were 

determined using the entire commercial building stock. In other words, the regional saturations 

when summed equal the national saturation. 

9-21 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

0% 

1% 

2% 

3% 

4% 

5% 

6% 

1985 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 

Year 

CAC and HP Commercial New Construction Saturations

Entire U.S. 

Hot-Humid 

Rest of Country 

Hot-Dry 

Figure 9.4.4	 CAC and HP National and Regional Saturations in Commercial New 

Construction 

9.5 RESULTS 

This section presents the shipments forecasts for the base case and for various candidate 

standard levels (CSL) that DOE considered for each of the four CAC and HP product classes. 

9.5.1 Split CAC 

As noted in section 9.2.1.1, split CAC shipments are divided into coil-only and blower 

coil units. Figures 9.5.1 and 9.5.2 show the base case shipments forecasts for split system CAC 

coil-only and blower coil units, respectively. Shipments are broken down into each of the three 

regions and designated by market segment (i.e., new construction, replacements, and new 

owners). Shipments to the commercial building sector are estimated to represent only about 

seven percent of all product shipments. Therefore, the figures do not differentiate among units 

going to the residential and commercial sectors. 

9-22 

EERE-2008-BT-STD-0006 COMMENT 54
0 

1 

2 

3 

4 

5 

6 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure 9.5.1 Forecasted Shipments (Base Case) for Split-System CACs, Coil-Only 

0.0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure 9.5.2 Forecasted Shipments (Base Case) for Split-System CACs, Blower Coil 

9-23 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

To demonstrate the impact of higher efficiency standards on base case shipments, the 

following figures focus on coil-only units, as they represent approximately 90 percent of total 

split CAC shipments. Figures 9.5.3 through 9.5.6 show the split CAC coil-only shipments 

forecasts for the base case and the standards case corresponding to the highest efficiency CSL 

(i.e., CSL 13 – 22 SEER) for the replacement, new owner, and new construction market 

channels, respectively. In each figure, shipments are disaggregated by climate region (HH = hothumid; HD = hot-dry; ROC = rest-of-country). The solid blue line represents the entire U.S. 

shipments forecast (i.e., the sum of the three climate regions).b 

In Figure 9.5.3, representing replacement shipments, a drop in shipments occurs in the 

year that standards are effective (i.e., 2016) due to the consumers affected by a relative price 

increase (i.e., the change in total installed cost and operating costs relative to household income 

caused by the CSL). As discussed in section 9.3.2.2, affected consumers repair their equipment 

rather than replace it, extending the life of the product by six years. When the extended repaired 

units fail after six more years, they are replaced with new ones. The replacement of extended 

repairs are shown in Figure 9.5.1 as additional shipments over the base case, i.e., six years after 

the effective date of the standard to account for CAC purchases delayed by extended repairs. For 

example, note the increase in shipments in the year 2022 over the base case which is six years 

after the effective date of the standard. Because the relative price elasticity decreases over time 

(as summarized in Table 9.3.1), decreases and increases in shipments due to extended repairs are 

not significant after the year 2022. 

b

 Because DOE determined shipments for the entire U.S. independently from the shipments that were determined for 

each climate region, the regional shipments do not add up precisely to the national value. Because inputs to the 

NIA, such as product total installed cost, product annual energy consumption, and product repair and maintenance 

costs, have regional dependencies in addition to being a function of product efficiency, the regional level impacts 

when summed will differ from the impacts that are determined at the national level. For split CACs, the sum of the 

regional shipments for any year over the forecast period was less than 0.4 percent of the shipments determined for 

the nation as a whole. For the three other primary product classes, the percentage differences between the sum of 

the regional shipments and the shipments determined for the nation as a whole were the following: 0.4 percent for 

single package CAC, 1.3 percent for split HP, and 1.3 percent for single package HP. 

9-24 

EERE-2008-BT-STD-0006 COMMENT 54
0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

3.00 

3.50 

4.00 

4.50 

5.00 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL13) 

HD (CSL13) 

ROC (CSL13) 

U.S. 

Figure 9.5.3 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) 

Replacement Shipments Forecasts 

9-25 

EERE-2008-BT-STD-0006 COMMENT 54
 InFigure 9.5.4, representing new owner shipments, a drop in shipments occurs in the 

year that standards are effective (i.e., 2016) due to the change in total installed cost and operating 

costs caused by the CSL. As discussed in section 9.3.2.1, consumers affected by a relative price 

increase switch equipment and purchase a room air conditioner rather than a CAC. As shown in 

Figure 9.5.1, the drop in shipments to this market channel is slight. 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL13) 

HD (CSL13) 

ROC (CSL13) 

U.S. 

Figure 9.5.4 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) 

New Owner Shipments Forecasts 

9-26 

EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 9.5.5 shows the shipment forecasts for the base case. As noted previously in 

section 9.1.1, the standards case shipments are identical to the base case as shipments to new 

constructions are assumed to be unaffected by increase in the relative price. 

0.00 

0.20 

0.40 

0.60 

0.80 

1.00 

1.20 

1.40 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

U.S. 

Figure 9.5.5 Split Coil-Only CAC: Base Case New Construction 

Shipments Forecasts 

9-27 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 9.5.6 provides the total base case and CSL shipments, which are a combination of 

the shipments depicted from the previous three figures. Most of the decrease in shipments is due 

to extended repairs. 

0.00 

1.00 

2.00 

3.00 

4.00 

5.00 

6.00 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL13) 

HD (CSL13) 

ROC (CSL13) 

U.S. (CSL13) 

U.S. 

Figure 9.5.6	 Split Coil-Only CAC: Base Case and CSL 13 (22 SEER) 

Total Shipments Forecasts 

Table 9.5.1 summarizes the cumulative shipments over the 30 year period starting from 

the assumed effective date of the standard (i.e., 2016) for the base case and each of the thirteen 

CSLs that DOE considered for split CACs. Cumulative shipments are shown for coil-only units, 

blower coil units, and total CAC shipments. Shipments are also disaggregated by region and 

sector. Also of note, the efficiency levels for CSLs 8 through 13 for coil-only units are 

equivalent to CSL 7 (16.5 SEER). 

9-28 

EERE-2008-BT-STD-0006 COMMENT 54
Table 9.5.1 Split CAC: Base Case and Standards Case Cumulative Shipments from 2016-2046 (millions) 

Base Case CSL 1 (13.5 SEER) CSL 2 (14 SEER) CSL 3 (14.5 SEER) CSL 4 (15 SEER) CSL 5 (1

Region Sector Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Bl

C

HotDry Res 25.31 2.81 28.12 25.30 2.81 28.12 25.30 2.81 28.11 25.28 2.81 28.10 25.27 2.81 28.08 25.25 2

Com 2.68 0.30 2.98 2.68 0.30 2.98 2.68 0.30 2.98 2.67 0.30 2.97 2.67 0.30 2.97 2.67 0

HotHumid Res 41.72 4.65 46.37 41.71 4.65 46.37 41.70 4.65 46.35 41.69 4.65 46.34 41.67 4.65 46.32 41.64 4

Com 4.58 0.51 5.09 4.58 0.51 5.09 4.57 0.51 5.09 4.57 0.51 5.08 4.56 0.51 5.08 4.56 0

Rest of U.S. 

Res 71.91 7.99 79.90 71.90 7.99 79.89 71.85 7.99 79.84 71.79 7.99 79.78 71.72 7.98 79.70 71.63 7

Com 7.33 0.81 8.15 7.33 0.81 8.15 7.33 0.81 8.14 7.32 0.81 8.13 7.31 0.81 8.13 7.30 0

Entire U.S. 

Res 139.71 15.52 155.24 139.70 15.52 155.22 139.63 15.52 155.15 139.55 15.52 155.07 139.45 15.51 154.96 139.32 1

Com 14.32 1.59 15.91 14.31 1.59 15.91 14.30 1.59 15.89 14.29 1.59 15.88 14.27 1.59 15.86 14.25 1

CSL 7 (16.5 SEER) CSL 8 (17 SEER)* CSL 9 (18 SEER)* CSL 10 (19 SEER)* CSL 11 (20 SEER)* CSL 12 (

Region Sector Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Blower Coil Total Coil- Only Bl

C

HotDry Res 25.21 2.81 28.02 25.21 2.81 28.02 25.21 2.81 28.02 25.21 2.81 28.02 25.21 2.80 28.02 25.21 2

Com 2.66 0.30 2.95 2.66 0.30 2.95 2.66 0.30 2.95 2.66 0.30 2.95 2.66 0.30 2.95 2.66 0

HotHumid Res 41.59 4.65 46.24 41.59 4.65 46.24 41.59 4.65 46.23 41.59 4.64 46.23 41.59 4.64 46.23 41.59 4

Com 4.54 0.51 5.05 4.54 0.51 5.05 4.54 0.51 5.05 4.54 0.51 5.05 4.54 0.51 5.05 4.54 0

Rest of U.S. 

Res 71.45 7.98 79.42 71.45 7.97 79.42 71.45 7.96 79.41 71.45 7.96 79.40 71.45 7.95 79.39 71.45 7

Com 7.28 0.81 8.10 7.28 0.81 8.10 7.28 0.81 8.09 7.28 0.81 8.09 7.28 0.81 8.09 7.28 0

Entire U.S. 

Res 139.06 15.50 154.56 139.06 15.50 154.55 139.06 15.49 154.54 139.06 15.48 154.53 139.06 15.46 154.52 139.06 1

Com 14.21 1.59 15.80 14.21 1.59 15.80 14.21 1.58 15.79 14.21 1.58 15.79 14.21 1.58 15.79 14.21 1

* CSL 7 is the maximum efficiency level for Blower Coil units. CSLs 8 -13 for Blower Coil units is equivalent to CSL 7. 

9-29 

EERE-2008-BT-STD-0006 COMMENT 54
9.5.2 Single Package CAC 

Figure 9.5.7 shows the base case shipments forecasts for single package CACs. 

Shipments are broken down into each of the three regions and designated by market segment 

(i.e., new construction, replacements, and new owners). Shipments to the commercial building 

sector are estimated to represent only about seven percent of all product shipments. Therefore, 

the figures do not differentiate among units going to the residential and commercial sectors. 

0.0 

0.1 

0.2 

0.3 

0.4 

0.5 

0.6 

0.7 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure 9.5.7 Forecasted Shipments (Base Case) for Single Package CACs 

9-30 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 9.5.8 shows total single package CAC shipments forecasts for the base case and 

the standards case corresponding to the highest efficiency CSL (i.e., CSL 7 – 16.4 SEER). 

Because the impact of standards on single package CAC shipments is similar to that exhibited 

for split CAC, figures disaggregating total shipments into the replacement, new owner, and new 

construction market channels are not provided. In the figure below, shipments are disaggregated 

by climate region (HH = hot-humid; HD = hot-dry; ROC = rest-of-country). The solid blue line 

represents the entire U.S. shipments forecast (i.e., the sum of the three climate regions). 

0.00 

0.10 

0.20 

0.30 

0.40 

0.50 

0.60 

0.70 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL7) 

HD (CSL7) 

ROC (CSL7) 

U.S. (CSL7) 

U.S. 

Figure 9.5.8	 Single Package CAC: Base Case and CSL 7 (16.6 SEER) Total 

Shipments Forecasts 

Table 9.5.2 summarizes the cumulative shipments over the 30 year period starting from 

the assumed effective date of the standard (i.e., 2016) for the base case and each of the seven 

CSLs that DOE considered for single package CACs. Shipments are disaggregated by region 

and sector. 

9-31 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

Table 9.5.2 Single Package CAC: Base Case and Standards Case Cumulative Shipments 

from 2016-2046 (millions) 

Region Sector Base 

Case 

CSL 1 

(13.5 SEER) 

CSL 2 

(14 SEER) 

CSL 3 

(14.5 SEER) 

CSL 4 

(15 SEER) 

CSL 5 

(15.5 SEER) 

CSL 6 

(16 SEER) 

CSL 7 

(16.6 SEER) 

Hot-Dry 

Res 2.77 2.77 2.76 2.76 2.76 2.76 2.76 2.75 

Com 0.29 0.29 0.29 0.29 0.29 0.29 0.29 0.28 

Hot-Humid 

Res 4.67 4.66 4.66 4.66 4.66 4.65 4.65 4.65 

Com 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 

Rest of U.S. 

Res 7.85 7.84 7.83 7.82 7.81 7.80 7.79 7.78 

Com 0.79 0.79 0.79 0.79 0.78 0.78 0.78 0.78 

Entire U.S. 

Res 15.35 15.34 15.33 15.31 15.30 15.29 15.27 15.26 

Com 1.55 1.54 1.54 1.54 1.54 1.54 1.53 1.53 

9.5.3 Split HP 

Figure 9.5.9 shows the base case shipments forecasts for split system HPs. Shipments are 

broken down into each of the three regions and designated by market segment (i.e., new 

construction, replacements, and new owners). Shipments to the commercial building sector are 

estimated to represent only about seven percent of all product shipments. Therefore, the figures 

do not differentiate among units going to the residential and commercial sectors. 

0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure 9.5.9 Forecasted Shipments (Base Case) for Split System HPs 

9-32 

EERE-2008-BT-STD-0006 COMMENT 54
 

Figure 9.5.10 shows total split HP shipments forecasts for the base case and the standards 

case corresponding to the highest efficiency CSL (i.e., CSL 10 – 19.5 SEER / 10.3 HSPF). 

Because the impact of standards on split HP shipments is similar to that exhibited for split CAC, 

figures disaggregating total shipments into the replacement, new owner, and new construction 

market channels are not provided. In the figure below, shipments are disaggregated by climate 

region (HH = hot-humid; HD = hot-dry; ROC = rest-of-country). The solid blue line represents 

the entire U.S. shipments forecast (i.e., the sum of the three climate regions). 

0.00 

0.50 

1.00 

1.50 

2.00 

2.50 

3.00 

3.50 

4.00 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL10) 

HD (CSL10) 

ROC (CSL10) 

U.S. (CSL10) 

U.S. 

Figure 9.5.10 Split HP: Base Case and CSL 10 (19.5 SEER / 10.3 HSPF) Total 

Shipments Forecasts 

Table 9.5.3 summarizes the cumulative shipments over the 30 year period starting from 

the assumed effective date of the standard (i.e., 2016) for the base case and each of the ten CSLs 

that DOE considered for split HPs. Shipments are disaggregated by region and sector. 

9-33 

EERE-2008-BT-STD-0006 COMMENT 54
Table 9.5.3 Split HP: Base Case and Standards Case Cumulative Shipments from 2016-2046 (millions) 

Region Sector Base Case 

CSL 1 

(13.5 SEER 

7.85 HSPF) 

CSL 2 

(14 SEER 

8.0 HSPF) 

CSL 3 

(14.5 SEER 

8.15 HSPF) 

CSL 4 

(15 SEER 

8.3 HSPF) 

CSL 5 

(15.5 SEER 

8.45 HSPF) 

CSL 6 

(16 SEER 

8.6 HSPF) 

CSL 7 

(17 SEER 

9.1 HSPF) 

CSL 1 

(18 SEER 

9.6 HSPF

Hot-Dry 

Res 8.43 8.43 8.43 8.43 8.43 8.43 8.43 8.43 8.42 

Com 1.16 1.16 1.16 1.16 1.16 1.16 1.15 1.15 1.15 

Hot-Humid 

Res 42.40 42.40 42.40 42.40 42.39 42.39 42.38 42.38 42.37 

Com 3.97 3.97 3.97 3.97 3.97 3.97 3.97 3.97 3.96 

Rest of U.S. 

Res 25.26 25.26 25.25 25.25 25.24 25.23 25.21 25.21 25.18 

Com 3.03 3.03 3.03 3.03 3.02 3.02 3.02 3.02 3.01 

Entire U.S. 

Res 77.12 77.12 77.11 77.10 77.08 77.06 77.04 77.04 77.00 

Com 8.20 8.20 8.19 8.19 8.19 8.18 8.17 8.17 8.16 

9-34 

EERE-2008-BT-STD-0006 COMMENT 54
9.5.4 Single Package HP 

Figure 9.5.11 shows the base case shipments forecasts for single package HPs. 

Shipments are broken down into each of the three regions and designated by market segment 

(i.e., new construction, replacements, and new owners). Shipments to the commercial building 

sector are estimated to represent only about seven percent of all product shipments. Therefore, 

the figures do not differentiate among units going to the residential and commercial sectors. 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

0.45 

0.50 

1990 

1994 

1998 

2002 

2006 

2010 

2014 

2018 

2022 

2026 

2030 

2034 

2038 

2042 

2046 

Year 

Shipments (million) 

Hot-Dry: New Construction Hot-Dry: New Ow ner Hot-Dry: Replace 

Hot-Humid: New Construction Hot-Humid: New Ow ner Hot-Humid: Replace 

Rest of Country: New Construction Rest of Country: New Ow ner Rest of Country: Replace 

Rest-of-Country 

Hot-Humid 

Hot-Dry 

Figure 9.5.11 Forecasted Shipments (Base Case) for Single Package HPs 

Figure 9.5.12 shows total single package HP shipments forecasts for the base case and the 

standards case corresponding to the highest efficiency CSL (i.e., CSL 7 – 16.4 SEER / 9.0 

HSPF). Because the impact of standards on single package HP shipments is similar to that 

exhibited for split CAC, figures disaggregating total shipments into the replacement, new owner, 

and new construction market channels are not provided. In the figure below, shipments are 

disaggregated by climate region (HH = hot-humid; HD = hot-dry; ROC = rest-of-country). The 

solid blue line represents the entire U.S. shipments forecast (i.e., the sum of the three climate 

regions). 

9-35 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

0.45 

0.50 

2000 2004 2008 2012 2016 2020 2024 2028 2032 2036 2040 2044 

millions 

HH 

HD 

ROC 

HH (CSL7) 

HD (CSL7) 

ROC (CSL7) 

U.S. (CSL7) 

U.S. 

Figure 9.5.12 Single Package HP: Base Case and CSL 7 (16.4 SEER / 9.0 HSPF 

Total Shipments Forecasts 

Table 9.5.4 summarizes the cumulative shipments over the 30 year period starting from 

the assumed effective date of the standard (i.e., 2016) for the base case and each of the ten CSLs 

that DOE considered for single package HPs. Shipments are disaggregated by region and sector. 

Table 9.5.4	 Single Package HP: Base Case and Standards Case Cumulative Shipments 

from 2016-2046 (millions) 

Region Sector Base 

Case 

CSL 1 

(13.5 SEER 

7.85 HSPF) 

CSL 2 

(14 SEER 

8.0 HSPF) 

CSL 3 

(14.5 SEER 

8.0 HSPF) 

CSL 4 

(15 SEER 

8.0 HSPF) 

CSL 5 

(15.5 SEER 

8.5 HSPF) 

CSL 6 

(16 SEER 

9.0 HSPF) 

CSL 7 

(16.4 SEER 

9.0 HSPF) 

Hot-Dry 

Res 1.10 1.10 1.10 1.10 1.10 1.10 1.09 1.09 

Com 0.15 0.15 0.15 0.15 0.15 0.15 0.15 0.15 

Hot-Humid 

Res 5.55 5.55 5.55 5.54 5.54 5.54 5.54 5.54 

Com 0.52 0.52 0.51 0.51 0.51 0.51 0.51 0.51 

Rest of U.S. 

Res 3.22 3.22 3.21 3.21 3.21 3.20 3.20 3.20 

Com 0.38 0.38 0.38 0.38 0.38 0.38 0.38 0.38 

Entire U.S. 

Res 10.00 10.00 9.99 9.99 9.98 9.97 9.97 9.96 

Com 1.05 1.05 1.05 1.05 1.05 1.05 1.05 1.04 

9-36 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

REFERENCES
 

1	 Letter to Mrs. Rachel Schmeltz, Energy Star Program Manager, Environmental Protection 

Agency from Karim Amrane, Vice President, Regulatory & Research, Air-Conditioning, 

Heating, and Refrigeration Institute (AHRI), “EPA Proposed Draft Energy Star Specification 

for Light Commercial HVAC Equipment,” Jan. 30, 2009. 

2	 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008. 

3	 Air-Conditioning, Heating and Refrigeration Institute. Historical shipments data, 1972-1989 

– provided to Lawrence Berkeley National Laboratory. 

4	 U.S. Census Bureau. Characteristics of New Housing, History Tables, 2008. Washington, 

DC. < http://www.census.gov/const/C25Ann/c25ann2008.pdf> 

5	 U.S. Department of Energy-Energy Information Administration. An Updated Annual Energy 

Outlook 2009 Reference Case Reflecting Provisions of the American Recovery and 

Reinvestment Act and Recent Changes in the Economic Outlook, April, 2009. Washington, 

DC. SR/OIAF/2009-03. 

<http://www.eia.doe.gov/oiaf/servicerpt/stimulus/pdf/sroiaf(2009)03.pdf> 

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

2009 with Projections to 2030. March 2009. U.S. DOE–EIA: Washington, D.C. DOE/EIA0383(2009). <http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2009).pdf> 

7	 U.S. Department of Energy–Energy Information Administration. Commercial Building 

Energy Consumption Survey. Washington, D.C. Surveys for 1992, 1995, 1999 and 2003. 

<http://www.eia.doe.gov/emeu/cbecs/> 

8	 S. Hymans. Consumer Durable Spending: Explanation and Prediction, Brookings Papers on 

Economic Activity, 1971. Vol. 1971, No. 1, pp. 234-239. 

9	 U.S. Census Bureau, Housing and Household Economic Statistics Division. American 

Housing Survey. Washington, DC. 

<http://www.census.gov/hhes/www/housing/ahs/ahs.html> 

10	 U.S. Census Bureau, National Population Projections Released 2008. 

http://www.census.gov/population/www/projections/summarytables.html 

9-37 

EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 10. NATIONAL AND REGIONAL IMPACT ANALYSES 

TABLE OF CONTENTS 

10.1 INTRODUCTION ......................................................................................................... 10-1 

10.1.1 Approach............................................................................................................ 10-1 

10.1.2 Factors Relevant to the Analysis........................................................................ 10-2 

10.2 BASE AND STANDARDS CASE EFFICIENCY DISTRIBUTIONS AND
 

FORECASTED EFFICIENCY TRENDS ..................................................................... 10-3 

10.2.1 Central Air Conditioners.................................................................................... 10-4 

10.2.1.1 Base and Standards Case Efficiencies ............................................. 10-4 

10.2.1.2 Forecasted Efficiency Trends .......................................................... 10-6 

10.2.1.3 Forecasted Efficiency Distributions............................................... 10-10 

10.2.2 Heat Pumps ...................................................................................................... 10-13 

10.2.2.1 Base and Standards Case Efficiencies ........................................... 10-13 

10.2.2.2 Forecasted Efficiency Trends ........................................................ 10-16 

10.2.2.3 Forecasted Efficiency Distributions............................................... 10-21 

10.3 CALCULATING NATIONAL AND REGIONAL ENERGY SAVINGS................. 10-23 

10.3.1 Definition ......................................................................................................... 10-24 

10.3.2 Inputs to Calculation........................................................................................ 10-25 

10.3.2.1 Annual Energy Consumption per Unit .......................................... 10-25 

10.3.2.2 Shipments including Equipment Switching................................... 10-37 

10.3.2.3 Equipment Stock ............................................................................ 10-41 

10.3.2.4 Annual Energy Consumption ......................................................... 10-41 

10.3.2.5 Site-to-Source Energy Conversion Factors.................................... 10-41 

10.4 CALCULATING NATIONAL AND REGIONAL NET PRESENT VALUE ........... 10-42 

10.4.1 Definition ......................................................................................................... 10-42 

10.4.2 Inputs to Calculation........................................................................................ 10-44 

10.4.2.1 Total Installed Cost per Unit .......................................................... 10-44 

10.4.2.2 Annual Operating Cost per Unit .................................................... 10-54 

10.4.2.3 Shipments including Equipment Switching................................... 10-62 

10.4.2.4 Equipment Stock ............................................................................ 10-64 

10.4.2.5 Increases in Total Annual Installed Cost ....................................... 10-64 

10.4.2.6 Savings in Total Annual Operating Cost ....................................... 10-65 

10.4.2.7 Discount Factors ............................................................................ 10-65 

10.4.2.8 Present Value of Increased Installed Cost ..................................... 10-65 

10.4.2.9 Present Value of Savings ............................................................... 10-66 

10.5 RESULTS OF CALCULATIONS .............................................................................. 10-66 

10.5.1 Summary of Inputs ........................................................................................... 10-66 

10.5.2 National and Regional Energy Savings ........................................................... 10-67 

10.5.2.1 Central Air Conditioners................................................................ 10-67 

10.5.2.2 Heat Pumps .................................................................................... 10-72 

10.5.3 Calculating Annual Cost and Savings.............................................................. 10-74 

10.5.4 Net Present Values........................................................................................... 10-75 

10-i 

EERE-2008-BT-STD-0006 COMMENT 54
10.5.4.1 Central Air Conditioners................................................................ 10-76 

10.5.4.2 Heat Pumps .................................................................................... 10-85 

LIST OF TABLES 

Table 10.2.1 Split System CAC, Coil Only Units: SEER Distributions for the Base and 

Standards Cases in 2016 .................................................................................... 10-5 

Table 10.2.2 Split System CAC, Blower Coil Units: SEER Distributions for the Base
 

and Standards Cases in 2016.............................................................................. 10-5 

Table 10.2.3 Single Package Central Air Conditioners: SEER Distributions for the Base
 

and Standards Cases in 2016.............................................................................. 10-6 

Table 10.2.4 CAC SWEF Growth Rates................................................................................. 10-7 

Table 10.2.5 Split System CAC, Coil-Only Units: Base Case Efficiency Distributions 

and SWEFs....................................................................................................... 10-11 

Table 10.2.6 Split System CAC, Blower Coil Units: Base Case Efficiency Distributions 

and SWEFs....................................................................................................... 10-12 

Table 10.2.7 Single Package CAC: Base Case Efficiency Distributions and SWEFs.......... 10-13 

Table 10.2.8 Split System HP: Efficiency Distributions for the Base and Standards 

Cases in 2016 ................................................................................................... 10-16 

Table 10.2.9 Single Package HP: Efficiency Distributions for the Base and Standards 

Cases in 2016 ................................................................................................... 10-16 

Table 10.2.10 Heat Pump SWEF Growth Rates ..................................................................... 10-17 

Table 10.2.11 Split System HPs: SEER-based Base Case Efficiency Distributions and 

SWEFs ............................................................................................................. 10-22 

Table 10.2.12 Single Package HPs: SEER-based Base Case Efficiency Distributions and 

SWEFs ............................................................................................................. 10-23 

Table 10.3.1 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for Base and 

Standards Cases in 2016 .................................................................................. 10-26 

Table 10.3.2 Split System CAC, Coil-Only Units, Replacement and New Owner 

Markets: Shipment-Weighted Average per-Unit Annual Energy 

Consumption for Base and Standards Cases in 2016....................................... 10-27 

Table 10.3.3 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Annual Energy 

Consumption for Base and Standards Cases in 2016....................................... 10-28 

Table 10.3.4 Split System Central Air Conditioners, Blower Coil Units: Replacement 

and New Owner Markets, Shipment-Weighted Average per-Unit Annual 

Energy Consumption for Base and Standards Cases in 2016 .......................... 10-29 

Table 10.3.5 Single Package Central Air Conditioners: Shipment-Weighted Average 

per-Unit Annual Energy Consumption for Base and Standards Cases in 

2016.................................................................................................................. 10-30 

Table 10.3.6 Split System Heat Pump: Shipment-Weighted Average per-Unit Annual 

Energy Consumption for Base and Standards Cases in 2016 .......................... 10-32 

10-ii 

EERE-2008-BT-STD-0006 COMMENT 54
Table 10.3.7	 Single Package Heat Pump: Shipment-Weighted Average per-Unit Annual
 

Energy Consumption for Base and Standards Cases in 2016 .......................... 10-35 

Table 10.3.8	 Equipment Switching for New Owner Purchasers of Split System Heat 

Pumps: Shipment-Weighted Average per-Unit Annual Energy
 

Consumption of Alternative Combination Coil-Only Split System Central 

Air Conditioner and Electric Furnace System for Base and Standards 

Cases in 2016 ................................................................................................... 10-39 

Table 10.3.9	 Equipment Switching for New Owner Purchasers of Single Package Heat 

Pumps: Shipment-Weighted Average per-Unit Annual Energy
 

Consumption of Alternative Combination Single Package Central Air 

Conditioner and Electric Furnace System for Base and Standards Cases in 

2016.................................................................................................................. 10-40 

Table 10.3.10 Site-to-Source Conversion Factors .................................................................. 10-42 

Table 10.4.1	 Split System Central Air Conditioners, Coil-Only Units, New 

Construction: Shipment-Weighted Average per-Unit Total Installed Cost 

for Base and Standards Cases in 2016 ............................................................. 10-45 

Table 10.4.2	 Split System Central Air Conditioners, Coil-Only Units, Replacement and 

New Owner Markets: Shipment-Weighted Average per-Unit Total 

Installed Cost for Base and Standards Cases in 2016 ...................................... 10-46 

Table 10.4.3	 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Total Installed Cost 

for Base and Standards Cases in 2016 ............................................................. 10-47 

Table 10.4.4	 Split System Central Air Conditioners, Blower Coil Units, Replacement 

and New Owner Markets: Shipment-Weighted Average per-Unit Total 

Installed Cost for Base and Standards Cases in 2016 ...................................... 10-47 

Table 10.4.5	 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Total Installed Cost for Base and Standards 

Cases in 2016 ................................................................................................... 10-49 

Table 10.4.6	 Single Package Central Air Conditioners, Replacement and New Owner 

Markets: Shipment-Weighted Average per-Unit Total Installed Cost for
 

Base and Standards Cases in 2016 ................................................................... 10-49 

Table 10.4.7	 Split System Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Total Installed Costs for Base and Standards Cases in 

2016.................................................................................................................. 10-51 

Table 10.4.8	 Split System Heat Pumps, Replacement and New Owner Markets: 

Shipment-Weighted Average per-Unit Total Installed Costs for Base and 

Standards Cases in 2016 .................................................................................. 10-51 

Table 10.4.9	 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Total Installed Costs for Base and Standards Cases in 

2016.................................................................................................................. 10-53 

Table 10.4.10 Single Package Heat Pumps, Replacement and New Owner Markets: 

Shipment-Weighted Average per-Unit Total Installed Costs for Base and 

Standards Cases in 2016 .................................................................................. 10-53 

10-iii 

EERE-2008-BT-STD-0006 COMMENT 54
Table 10.4.11 Split System Central Air Conditioners, Coil-Only Units: ShipmentWeighted Average per-Unit Repair and Maintenance Cost for Base and 

Standards Cases in 2016 .................................................................................. 10-56 

Table 10.4.12 Split System Central Air Conditioners, Blower Coil Units: ShipmentWeighted Average per-Unit Repair and Maintenance Cost for Base and 

Standards Cases in 2016 .................................................................................. 10-57 

Table 10.4.13 Single Package Central Air Conditioners: Shipment-Weighted Average 

per-Unit Repair and Maintenance Cost for Base and Standards Cases in 

2016.................................................................................................................. 10-59 

Table 10.4.14 Split System Heat Pumps: Shipment-Weighted Average per-Unit Repair 

and Maintenance Costs for Base and Standards Cases in 2016 ....................... 10-60 

Table 10.4.15 Single Package Heat Pumps: Shipment-Weighted Average per-Unit 

Repair and Maintenance Costs for Base and Standards Cases in 2016 ........... 10-62 

Table 10.4.16 Equipment Switching for New Owner Purchasers of Split System Heat 

Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of 

Alternative Combination Coil-Only Split System Central Air Conditioner 

and Electric Furnace System for Base and Standards Cases in 2016 .............. 10-63 

Table 10.4.17 Equipment Switching for New Owner Purchasers Single Package Heat 

Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of 

Alternative Combination Single Package Central Air Conditioner and 

Electric Furnace System for Base and Standards Cases in 2016 ..................... 10-64 

Table 10.5.1 Inputs to Calculations ...................................................................................... 10-67 

Table 10.5.2 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Residential Sector (quads) .............. 10-68 

Table 10.5.3 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Commercial Sector (quads)............. 10-69 

Table 10.5.4 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Residential and Commercial 

Sectors (quads)................................................................................................. 10-69 

Table 10.5.5 Single Package Central Air Conditioners: Cumulative National and 

Regional Energy Savings from 2016-2046 (quads)......................................... 10-71 

Table 10.5.6 Split System Heat Pumps: Cumulative National and Regional Energy
 

Savings from 2016-2046 (quads)..................................................................... 10-72 

Table 10.5.7 Single Package Heat Pumps: Cumulative National and Regional Energy
 

Savings from 2016-2046 (quads)..................................................................... 10-74 

Table 10.5.8 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Residential Sector (3% 

Discount Rate) ................................................................................................. 10-77 

Table 10.5.9 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Commercial Sector 

(3% Discount Rate).......................................................................................... 10-77 

Table 10.5.10 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Residential and 

Commercial Sectors (3% Discount Rate) ........................................................ 10-78 

10-iv 

EERE-2008-BT-STD-0006 COMMENT 54
Table 10.5.11 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Residential Sector (7% 

Discount Rate) ................................................................................................. 10-80 

Table 10.5.12 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Commercial Sector 

(7% Discount Rate).......................................................................................... 10-80 

Table 10.5.13 Split System Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 for the Residential and 

Commercial Sectors (7% Discount Rate) ........................................................ 10-81 

Table 10.5.14 Single Package Central Air Conditioners: Discounted Cumulative 

National and Regional NPV Results from 2016-2046 (3% Discount Rate).... 10-83 

Table 10.5.15 Single Package Central Air Conditioners: Discounted Cumulative 

National and Regional NPV Results from 2016-2046 (7% Discount Rate).... 10-84 

Table 10.5.16 Split System Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (3% Discount Rate)......................................... 10-85 

Table 10.5.17 Split System Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (7% Discount Rate)......................................... 10-87 

Table 10.5.18 Single Package Heat Pumps: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 (3% Discount Rate) ......................... 10-88 

Table 10.5.19 Single Package Heat Pumps: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 (7% Discount Rate) ......................... 10-89 

LIST OF FIGURES 

Figure 10.2.1 CAC Historical SWEFs with Linear Fits........................................................... 10-7 

Figure 10.2.2 Split System CAC, Coil Only Units: SEER-based Historical SWEFs and 

Forecasted Efficiency Trends for the Base Case and Standards Cases ............. 10-8 

Figure 10.2.3 Split System CAC, Blower Coil Units: SEER-based Historical SWEFs and 

Forecasted Efficiency Trends for Base Case and Standards Cases ................... 10-9 

Figure 10.2.4 Single Package CAC: SEER-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases ......................................... 10-9 

Figure 10.2.5 Split System HP: HSPF and SEER relationship .............................................. 10-14 

Figure 10.2.6 Single Package HP: HSPF and SEER relationship.......................................... 10-15 

Figure 10.2.7 Heat Pump Historical SWEFs based on SEER with Linear Fits ..................... 10-17 

Figure 10.2.8 Split System HP: SEER-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases ....................................... 10-19 

Figure 10.2.9 Split System HP: HSPF-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases ....................................... 10-19 

Figure 10.2.10 Single Package HP: SEER-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases ....................................... 10-20 

Figure 10.2.11 Single Package HP: HSPF-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases ....................................... 10-21 

10-v 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 10.3.1 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period ............. 10-27 

Figure 10.3.2 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Annual Energy 

Consumption for the Base Case and Three Standards Cases over the 2016­

2046 Forecast Period........................................................................................ 10-29 

Figure 10.3.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period ............. 10-31 

Figure 10.3.4 Split System Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Cooling Energy Consumption for the Base Case 

and Three Standards Cases over the 2016-2046 Forecast Period .................... 10-33 

Figure 10.3.5 Split System Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Heating Energy Consumption for the Base Case 

and Three Standards Cases over the 2016-2046 Forecast Period .................... 10-34 

Figure 10.3.6 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Cooling Energy Consumption for the Base Case 

and Two Standards Cases over the 2016-2046 Forecast Period...................... 10-36 

Figure 10.3.7 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Heating Energy Consumption for the Base Case 

and Two Standards Cases over the 2016-2046 Forecast Period...................... 10-37 

Figure 10.4.1 Split System Central Air Conditioners, Coil-Only Units, New 

Construction: Shipment-Weighted Average Total Installed Cost for the 

Base Case and Two Standards Cases over the 2016-2046 Forecast Period .... 10-46 

Figure 10.4.2 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average Total Installed Cost for the 

Base Case and Three Standards Cases over the 2016-2046 Forecast Period .. 10-48 

Figure 10.4.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Total Installed Cost for the Base Case and Two 

Standards Cases over the 2016-2046 Forecast Period ..................................... 10-50 

Figure 10.4.4 Split System Heat Pumps, New Construction: Shipment-Weighted 

Average Total Installed Cost for the Base Case and Three Standards Cases 

over the 2016-2046 Forecast Period ................................................................ 10-52 

Figure 10.4.5 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average Total Installed Cost for the Base Case and Two Standards Cases 

over the 2016-2046 Forecast Period ................................................................ 10-54 

Figure 10.4.6 Split System Central Air Conditioners, Coil-Only Units, New 

Construction: Shipment-Weighted Average Annual Repair and 

Maintenance Costs for the Base Case and Two Standards Cases over the 

2016-2046 Forecast Period .............................................................................. 10-56 

Figure 10.4.7 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average Annual Repair and 

Maintenance Costs for the Base Case and Three Standards Cases over the 

2016-2046 Forecast Period .............................................................................. 10-58 

10-vi 

EERE-2008-BT-STD-0006 COMMENT 54
Figure 10.4.8 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Annual Repair and Maintenance Costs for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period ............. 10-59 

Figure 10.4.9 Split System Heat Pumps, New Construction: Shipment-Weighted 

Average Annual Repair and Maintenance Costs for the Base Case and 

Three Standards Cases over the 2016-2046 Forecast Period ........................... 10-61 

Figure 10.4.10 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average Annual Repair and Maintenance Costs for the Base Case and 

Two Standards Cases over the 2016-2046 Forecast Period ............................. 10-62 

Figure 10.5.1 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 (quads) ........................................................ 10-70 

Figure 10.5.2 Single Package Central Air Conditioners: Cumulative National and 

Regional Energy Savings from 2016-2046 (quads)......................................... 10-71 

Figure 10.5.3 Split System Heat Pumps: Cumulative National and Regional Energy
 

Savings from 2016-2046 (quads)..................................................................... 10-73 

Figure 10.5.4 Single Package Heat Pumps: Cumulative National and Regional Energy
 

Savings from 2016-2046 (quads)..................................................................... 10-74 

Figure 10.5.5 Non-Discounted Annual Increases in Installed Cost and Savings in 

Operating Cost for Split System Coil-Only Central Air Conditioners, 

Candidate Standard Level 2 ............................................................................. 10-75 

Figure 10.5.6 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (3% discount rate)........................................................ 10-79 

Figure 10.5.7 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (7% discount rate)........................................................ 10-82 

Figure 10.5.8 Single Package Central Air Conditioners: Cumulative National and 

Regional NPV from 2016-2046 (3% discount rate) ........................................ 10-83 

Figure 10.5.9 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (7% discount rate)........................................................ 10-84 

Figure 10.5.10 Split System Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (3% discount rate).......................................................................... 10-86 

Figure 10.5.11 Split System Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (7% discount rate).......................................................................... 10-87 

Figure 10.5.12 Single Package Heat Pumps: Cumulative National and Regional NPV 

from 2016-2046 (3% discount rate)................................................................. 10-89 

Figure 10.5.13 Single Package Heat Pumps: Cumulative National and Regional NPV 

from 2016-2046 (7% discount rate)................................................................. 10-90 

10-vii 

EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 10. NATIONAL AND REGIONAL IMPACT ANALYSES 

10.1 INTRODUCTION
 

This chapter describes the method that the U.S. Department of Energy (DOE) developed 

to estimate the energy savings, and net present value of those energy savings, that consumers 

would receive from potential new energy efficiency standards for residential and commercial 

consumers of central air conditioners (CAC) and heat pumps (HP). Chapter 5 describes the 

efficiency levels, otherwise known as candidate standard levels (CSLs), for the products 

represented by central air conditioners and heat pumps. This chapter examines the national 

energy savings (NES) attributable to each CSL, along with the energy savings specific to three 

regions based on climate: a hot-humid climate (the Southeast), a hot-dry climate (the Southwest), 

and the rest of the Nation. The results presented here for the nation as a whole and for each of the 

three regions include: (1) potential energy consumption and savings; (2) the monetary value of 

energy savings attributable to each CSL; (3) increased total installed costs (purchase price plus 

installation costs) attributable to each CSL; and (4) the net present value (NPV) of energy 

savings (the difference between the value of energy savings and increased total installed costs in 

2008$). 

DOE determined both the energy savings and NPV for each CSL considered for the 

product comprising central air conditioners and heat pumps. The calculations were performed 

using a Microsoft Excel spreadsheet model, which is accessible on the Internet 

(http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp.html). 

The spreadsheet model, termed the National Impact Analysis (NIA) model, calculates energy 

savings and NPV for the nation and for each of the three regions (hot-humid, hot-dry, and rest of 

the Nation). Details regarding and instructions for using the NIA model are provided in appendix 

10-A. 

10.1.1 Approach 

The critical factors that govern energy consumption by CAC and HPs are: (1) the 

quantities shipped; (2) financial considerations such as consumer response to changes in total 

installed cost, operating expenses, and household income; and (3) voluntary programs that 

promote higher-efficiency products. Chapter 9 describes in detail the shipments model that DOE 

used to forecast future purchases of central air conditioners and heat pumps. Chapter 9 includes 

detailed descriptions of consumers’ sensitivities to total installed cost, operating expense, and 

income (otherwise known as elasticities), and how DOE captured those elasticities within the 

NIA model. 

Voluntary programs increase the market share of energy efficient equipment. Between 

1992 (the effective date of the first federal energy efficiency standards for central air 

conditioners and heat pumps) and 2005, the shipment-weighted efficiency of central air 

conditioners and heat pumps has grown by approximately one SEER point. Presumably, the 

10-1 

EERE-2008-BT-STD-0006 COMMENT 54
 

efficiency increase over this time period has been due at least in part to voluntary programs. 

Consequently, DOE assumed that market-based initiatives would continue to have the same 

effect on the efficiency of product shipments as it has in the past. Details on how this effect was 

captured in the analysis are detailed below in section 10.2. 

10.1.2 Factors Relevant to the Analysis 

The product and product classes being considered for new standards are described in 

detail in chapter 3. Below is a brief description of the product, product classes, and other factors 

that were considered in evaluating the effects of potential new energy standards. 

•	 Product being considered: 

o	 central air conditioners (CACs) and heat pumps (HPs) 

•	 Product classes within this product:a 

o	 split system air conditioners, 

o	 single package air conditioners, 

o	 split system heat pumps, and 

o	 single package heat pumps, 

•	 Markets: 

o	 Central air conditioners: 93 percent used in residential settings; 7 percent used in 

commercial settings. 

 Split systems comprise 90.4 percent of both the residential and 

commercial markets. 

 Single package systems represent 9.6 percent of both the residential and 

commercial markets. 

o	 Heat pumps: 93 percent used in residential settings; 7 percent used in commercial 

settings. 

 Split systems comprise 87.7 percent of both the residential and 

commercial markets. 

 Single package systems represent 12.3 percent of both the residential and 

commercial markets. 

•	 Channels (i.e., product placement): 

o	 Central air conditioners are purchased for: 

 new construction, 

 replacements, and 

 existing households and commercial building owners that do not already 

own the product (hereafter referred to as “new owners”). 

o	 Heat pumps are purchased for: 

 new construction, 

 replacements, and 

a

 There are three other product classes including small duct high velocity (SDHV) systems, space-constrained air 

conditioners, and space-constrained heat pumps which are not being analyzed for this preliminary TSD due to lack 

of available data and limited product offerings. 

10-2 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 new owners. 

• Effects of increased purchase price, operating cost savings, and household income: 

o Central air conditioners: Evaluated for replacement and new owner purchases. 

 For replacement purchases, effected consumers repair their product rather 

than replace it, extending the life of the product by six years. 

 For new owner purchases, effected consumers purchase a room air 

conditioner rather than a central air conditioner. 

o	 Heat pump: Evaluated for replacement and new owner purchases. 

 For replacement purchases, effected consumers repair their product rather 

than replace it, extending the life of the product by six years. 

 For new owner purchases, effected consumers purchase a combination 

electric resistance furnace and central air conditioner rather than a heat 

pump. 

•	 Regional standards considered:b 

o	 hot-humid region (consisting of states in the Southeastern U.S. including 

Alabama, Arkansas, Florida, Georgia, Louisiana, Mississippi, North Carolina, 

Oklahoma, South Carolina, Tennessee, and Texas; Hawaii is also included); 

o	 hot-dry region (consisting of states in the Southwest including Arizona, Nevada, 

and New Mexico; California is also included); 

o	 the rest of the Nation; that is, the remaining 33 states including Alaska. 

•	 Standard Levels: 

o	 seven levels for split system air conditioners, coil-only units and 13 levels for split 

system air conditioners, blower coil units, 

o	 seven levels for single package air conditioners, 

o	 ten levels for split system heat pumps, and 

o	 seven levels for single package heat pumps. 

10.2	 BASE AND STANDARDS CASE EFFICIENCY DISTRIBUTIONS AND 

FORECASTED EFFICIENCY TRENDS 

A key component of DOE’s estimates of national and regional energy savings and net 

present value (NPV) is the energy efficiency forecasted over time for the base case (without new 

standards) and for each of the standards cases (with potential new standards). The forecasted 

efficiencies represent the annual shipment-weighted energy efficiency (SWEF) of the product 

classes under consideration from the assumed effective date of a new standard to 30 years after 

that date. Key inputs to the calculation of both national and regional energy savings and NPV 

depend on estimated energy efficiencies. Per-unit annual energy consumption, for example, is a 

direct function of product efficiency and dictates energy savings. Chapter 6, Energy Use 

Determination, describes how per-unit energy consumption changes as a function of efficiency 

for each product class. With regard to the NPV, two inputs, the per-unit total installed cost and 

the per-unit annual operating cost, depend on efficiency. The per-unit total installed cost is a 

b

 Regional standards are being considered in addition to standards for the Nation as a whole. 

10-3 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

direct function of efficiency because more efficient products are assumed to be more expensive 

than their less efficient counterparts. Because per-unit annual operating cost is a direct function 

of per-unit annual energy consumption, it too is dependent on product efficiency. Section 8.2.2 

of chapter 8, Life-Cycle Cost (LCC) and Payback Period (PBP) Analysis, describes how per-unit 

total installed cost changes as a function of efficiency for each product class. The above and all 

other inputs to the calculation of energy savings and NPV are discussed in sections 10.3.2 and 

10.4.2. The two sections below (sections 10.2.1 and 10.2.2) describe how DOE developed base 

and standards case efficiency distributions and forecasted efficiency trends. 

As noted in section 10.1.2, DOE constructed and conducted its NIA to analyze standards 

for the Nation as a whole and three specific regions (hot-humid, hot-dry, and rest-of-country). 

Ideally, the base case and standards case efficiency distributions and forecasted efficiency trends 

would be characterized as a function of region. Unfortunately, DOE only received data at the 

national level. As a result, DOE assumed that the distributions and trends developed for the 

entire Nation are also representative for the three regions (i.e., efficiency distributions and trends 

do not vary by region). 

10.2.1 Central Air Conditioners 

10.2.1.1 Base and Standards Case Efficiencies 

For both CAC product classes—split systems and single package systems—DOE 

developed product efficiencies in the base case by assigning equipment to specific efficiency 

levels for the year 2016. In other words, DOE determined the distribution of product efficiencies 

currently in the marketplace to develop a SEER-based SWEF for the year 2016. DOE derived its 

base case efficiency distributions for split system and single package CACs on SWEF data 

provided by AHRI in combination with the range of product offerings in AHRI’s listing of 

certified unitary air-conditioner equipment. For more details on the derivation of the split system 

and single package base case efficiencies, refer to section 8.2.3.8 of chapter 8, LCC and PBP 

Analysis. 

For its determination of standards-case efficiencies, DOE assumed a “roll-up” scenario to 

establish the SWEF for the year that standards are assumed to become effective (i.e., 2016). 

DOE assumed that product efficiencies in the base case that did not meet the standard under 

consideration would “roll up” to meet the new standard level. Also, DOE assumed that all 

product efficiencies in the base case that were above the standard under consideration would not 

be affected. 

Tables 10.2.1 and 10.2.2 present the SEER-based efficiency distributions and resulting 

SWEF for the base case and standards cases for split system coil-only and blower coil CACs, 

respectively, in the year 2016 (the assumed effective date of new standards). Table 10.2.3 

presents the SEER-based efficiency distributions and resulting SWEF for the base case and 

standards cases for single package CACs in the year 2016. Each table clearly shows how each 

standards case, under a “roll-up” scenario, affects the efficiency distribution. 

10-4 

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Table 10.2.1 Split System CAC, Coil Only Units: SEER Distributions for the Base and 

Standards Cases in 2016 

CSL SEER 

Market Share 

Base Case 

Standards Case 

1 2 3 4 5 6 7 

Baseline 13.0 24.6% - - - - - - -

1 13.5 56.4% 81.0% - - - - - -

2 14.0 4.1% 4.1% 85.1% - - - - -

3 14.5 5.4% 5.4% 5.4% 90.5% - - - -

4 15.0 3.3% 3.3% 3.3% 3.3% 93.8% - - -

5 15.5 2.1% 2.1% 2.1% 2.1% 2.1% 95.9% - -

6 16.0 3.6% 3.6% 3.6% 3.6% 3.6% 3.6% 99.5% -

7 16.5 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 100% 

SWEF 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50 

Table 10.2.2 Split System CAC, Blower Coil Units: SEER Distributions for the Base and 

Standards Cases in 2016 

CSL SEER 

Market Share 

Base 

Case 

Standards Case 

1 2 3 4 5 6 7 8 9 10 11 12 13 

Baseline 13.0 18.5% - - - - - - - - - - - - -

1 13.5 42.3% 60.8% - - - - - - - - - - - -

2 14.0 3.1% 3.1% 63.8% - - - - - - - - - - -

3 14.5 4.0% 4.0% 4.0% 67.9% - - - - - - - - - -

4 15.0 2.5% 2.5% 2.5% 2.5% 70.4% - - - - - - - - -

5 15.5 1.5% 1.5% 1.5% 1.5% 1.5% 71.9% - - - - - - - -

6 16.0 2.7% 2.7% 2.7% 2.7% 2.7% 2.7% 74.6% - - - - - - -

7 16.5 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 0.4% 75.0% - - - - - -

8 17.0 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 10.0% 85.0% - - - - -

9 18.0 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 7.0% 92.0% - - - -

10 19.0 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 95.0% - - -

11 20.0 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 97.0% - -

12 21.0 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 99.0% -

13 22.0 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 1.0% 100% 

SWEF 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

10-5 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

Table 10.2.3 Single Package Central Air Conditioners: SEER Distributions for the Base 

and Standards Cases in 2016 

CSL SEER 

Market Share 

Base Case 

Standards Case 

1 2 3 4 5 6 7 

Baseline 13.0 75% - - - - - - -

1 13.5 20% 95% - - - - - -

2 14.0 2% 2% 97% - - - - -

3 14.5 2% 2% 2% 99% - - - -

4 15.0 1% 1% 1% 1% 100% - - -

5 15.5 0% 0% 0% 0% 0% 100% - -

6 16.0 0% 0% 0% 0% 0% 0% 100% -

7 16.6 0% 0% 0% 0% 0% 0% 0% 100% 

SWEF 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60 

10.2.1.2 Forecasted Efficiency Trends 

Historical Efficiency Trends 

Using the SWEF for the year 2016 as a starting point, DOE developed base-case 

forecasted efficiency trends based on assumptions regarding future efficiency growth. To 

estimate SWEFs over the 30 year forecast spanning 2016–2046, DOE reviewed historical SWEF 

data provided by the Air-Conditioning, Heating, and Refrigeration Institute (AHRI) spanning the 

years 1992 to 2008.1

 Between 1992, the year in which the first set of standards for CAC and 

HPs became effective, and 2006, when an updated set of standards became effective, the SWEFs 

for CACs grew by approximately one SEER point. Figure 10.2.1 shows the SWEFs for split 

system and single package CACs. The figure also presents the linear fit to each product class’ 

SWEF data series. The linear fits have high coefficients of determination, i.e., linear fits provide 

a good estimate of the SWEF growth rate. Table 10.2.1 provides a summary of the SWEF 

growth rates for each product class. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Split A/C 

SEER = 0.0703 * year - 129.65 

R2 = 0.9633 

Package A/C 

SEER = 0.0778 * year - 144.78 

R2 = 0.9455 

10.0 

10.2 

10.4 

10.6 

10.8 

11.0 

11.2 

11.4 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

Year 

Shipment-Weighted SEER 

Split A/C 

Package A/C 

Linear (Split A/C) 

Linear (Package A/C) 

Figure 10.2.1 CAC Historical SWEFs with Linear Fits 

Table 10.2.4 CAC SWEF Growth Rates

 SWEF Growth Rate 

Product Class SEER increase per year 

Split System Air Conditioners 0.0703 

Single Package Air Conditioners 0.0778 

Base Case Efficiency Trends 

Because various market-pull programs such as Energy Star and utility rebate programs 

were in existence from 1992 to 2005, the SWEF growth rate evident in the historical data was 

likely due in part to these market-pull programs. As a result, DOE applied the SWEF growth 

rates in Table 10.2.4 to the base case SWEFs in 2016 to forecast annual SWEFs for the CAC 

product classes from 2016 to 2046. Application of the SWEF growth rates in this manner 

assumes that future market-pull programs will be as effective at increasing product efficiency as 

past programs. 

Standards Case Efficiency Trends 

To develop standards case forecasted SWEFs, DOE developed growth trends for each 

candidate standard level that maintained the same per-unit average total installed cost difference 

for the year 2016 between the base case and each standards case over the entire forecast period 

(2016–2046). DOE’s approach for developing standards case SWEFs in this manner assumes 

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EERE-2008-BT-STD-0006 COMMENT 54
that the rate of adoption of more efficient products under the standards case can occur only at a 

rate which ensures that the average total installed cost difference between the standards case and 

base case over the entire forecast period is held constant. Because the total installed cost versus 

efficiency relationship for each product class demonstrates an increasing cost rate for more 

efficient products, the SWEF growth rate for each standards case is lower than the SWEF growth 

rate for the base case. 

Depicting Base Case and Standards Case Efficiency Trends 

Figures 10.2.2 and 10.2.3 show the SEER-based base case historical SWEFs, the base 

case forecasted efficiency trend, and each standards case forecasted efficiency trend for split 

system coil-only and blower coil CACs, respectively. Figure 10.2.4 shows the SEER-based 

SWEFs for single package CACs. Looking at each figure closely, it can be seen that the 

standards case SWEF growth rates are slightly lower than the SWEF growth rate for the base 

case. Note that for some standards cases, the efficiency trend does not increase past the Max 

Tech level. The Max Tech levels for split system coil-only and blower coil units are 16.5 SEER 

and 22 SEER, respectively. The Max Tech level for single package units is 16.6 SEER. 

10 

11 

12 

13 

14 

15 

16 

17 

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

SWEF (SEER) 

Base Case 

CSL 1: 13.5 SEER 

CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 16.5 SEER 

Figure 10.2.2 Split System CAC, Coil Only Units: SEER-based Historical SWEFs and 

Forecasted Efficiency Trends for the Base Case and Standards Cases 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

SWEF (SEER) 

22 

21 

20 

19 

18 

17 

16 

15 

14 

13 

12 

11 

10 

1990 

Base Case 

CSL 1: 13.5 SEER 

CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 16.5 SEER 

CSL 8: 17 SEER 

CSL 9: 18 SEER 

CSl 10: 19 SEER 

CSL 11: 20 SEER 

CSL 12: 21 SEER 

CSL 13: 22 SEER 

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

Figure 10.2.3	 Split System CAC, Blower Coil Units: SEER-based Historical SWEFs 

and Forecasted Efficiency Trends for Base Case and Standards Cases 

17 

Base Case 

CSL 1: 13.5 SEER 16
 CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

15 CSL 4: 15 SEER 

SWEF (SEER) 13 

14 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 16.6 SEER 

12 

11 

10 

1990 1995 2000 2005 2010 2015 2020 

Year 

2025 2030 2035 2040 2045 

Figure 10.2.4 Single Package CAC: SEER-based Historical SWEFs and Forecasted
 

Efficiency Trends for the Base and Standards Cases 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

10.2.1.3 Forecasted Efficiency Distributions 

Once DOE developed base case and standards case efficiency trends, it derived a 

distribution of product efficiencies from the forecasted SWEFs for each year of the analysis 

period (2016–2046) by developing appropriate market shares for the various standard levels. 

As specified in Tables 10.2.1, 10.2.2, and 10.2.3, DOE developed the product efficiency 

distributions for the year the standard is assumed to become effective (2016) using a “roll-up” 

scenario. For subsequent years (2017–2046), DOE assigned the market shares to the standard 

levels so that the resulting calculated SWEF remained equal to the forecasted SWEF. This 

assignment was conducted by pulling market shares from lower efficiency levels to higher 

efficiency levels until the calculated SWEF equaled the forecasted value. 

Tables 10.2.4 and 10.2.5 provide examples of forecasted efficiency distributions—the 

specific cases of the forecasted efficiency distributions for the base case (without standards) for 

split system coil-only and blower coil central air conditioners, respectively. As an example for 

single package central air conditioners, Table 10.2.6 provides the forecasted efficiency 

distributions for the base case. The tables also provide the resulting SWEF for each year during 

the forecast period. The NIA spreadsheet (detailed in Appendix 10-A) provides the forecasted 

efficiency distributions for all the standards cases for both split system and single package 

CACs. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 10.2.5 Split System CAC, Coil-Only Units: Base Case Efficiency Distributions and 

SWEFs 

Year 

Market Shares by SEER Level 

13 13.5 14 14.5 15 15.5 16 16.5 SWEF

2016 24.6% 56.4% 4.1% 5.4% 3.3% 2.1% 3.6% 0.5% 13.65 

2017 10.6% 70.5% 4.1% 5.4% 3.3% 2.1% 3.6% 0.5% 13.72 

2018 0.0% 77.5% 7.6% 5.4% 3.3% 2.1% 3.6% 0.5% 13.79 

2019 0.0% 63.5% 21.7% 5.4% 3.3% 2.1% 3.6% 0.5% 13.86 

2020 0.0% 49.4% 35.7% 5.4% 3.3% 2.1% 3.6% 0.5% 13.93 

2021 0.0% 35.3% 49.8% 5.4% 3.3% 2.1% 3.6% 0.5% 14.00 

2022 0.0% 21.3% 63.9% 5.4% 3.3% 2.1% 3.6% 0.5% 14.07 

2023 0.0% 7.2% 77.9% 5.4% 3.3% 2.1% 3.6% 0.5% 14.14 

2024 0.0% 0.0% 78.3% 12.3% 3.3% 2.1% 3.6% 0.5% 14.21 

2025 0.0% 0.0% 64.2% 26.3% 3.3% 2.1% 3.6% 0.5% 14.28 

2026 0.0% 0.0% 50.1% 40.4% 3.3% 2.1% 3.6% 0.5% 14.35 

2027 0.0% 0.0% 36.1% 54.4% 3.3% 2.1% 3.6% 0.5% 14.42 

2028 0.0% 0.0% 22.0% 68.5% 3.3% 2.1% 3.6% 0.5% 14.49 

2029 0.0% 0.0% 7.9% 82.6% 3.3% 2.1% 3.6% 0.5% 14.56 

2030 0.0% 0.0% 0.0% 84.4% 9.5% 2.1% 3.6% 0.5% 14.63 

2031 0.0% 0.0% 0.0% 70.3% 23.5% 2.1% 3.6% 0.5% 14.70 

2032 0.0% 0.0% 0.0% 56.3% 37.6% 2.1% 3.6% 0.5% 14.77 

2033 0.0% 0.0% 0.0% 42.2% 51.6% 2.1% 3.6% 0.5% 14.84 

2034 0.0% 0.0% 0.0% 28.1% 65.7% 2.1% 3.6% 0.5% 14.91 

2035 0.0% 0.0% 0.0% 14.1% 79.8% 2.1% 3.6% 0.5% 14.98 

2036 0.0% 0.0% 0.0% 0.0% 93.8% 2.1% 3.6% 0.5% 15.05 

2037 0.0% 0.0% 0.0% 0.0% 79.8% 16.1% 3.6% 0.5% 15.12 

2038 0.0% 0.0% 0.0% 0.0% 65.7% 30.2% 3.6% 0.5% 15.19 

2039 0.0% 0.0% 0.0% 0.0% 51.7% 44.2% 3.6% 0.5% 15.26 

2040 0.0% 0.0% 0.0% 0.0% 37.6% 58.3% 3.6% 0.5% 15.34 

2041 0.0% 0.0% 0.0% 0.0% 23.5% 72.4% 3.6% 0.5% 15.41 

2042 0.0% 0.0% 0.0% 0.0% 9.5% 86.4% 3.6% 0.5% 15.48 

2043 0.0% 0.0% 0.0% 0.0% 0.0% 91.3% 8.2% 0.5% 15.55 

2044 0.0% 0.0% 0.0% 0.0% 0.0% 77.2% 22.2% 0.5% 15.62 

2045 0.0% 0.0% 0.0% 0.0% 0.0% 63.2% 36.3% 0.5% 15.69 

2046 0.0% 0.0% 0.0% 0.0% 0.0% 49.1% 50.4% 0.5% 15.76 

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Table 10.2.6 Split System CAC, Blower Coil Units: Base Case Efficiency Distributions and 

SWEFs 

Year 

Market Shares by SEER Level 

13 13.5 14 14.5 15 15.5 16 16.5 17 18 19 20 21 22 SWEF

2016 18.5% 42.3% 3.1% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.81 

2017 4.4% 56.4% 3.1% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.88 

2018 0.0% 51.1% 12.7% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 14.95 

2019 0.0% 37.0% 26.8% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.02 

2020 0.0% 23.0% 40.9% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.09 

2021 0.0% 8.9% 54.9% 4.0% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.16 

2022 0.0% 0.0% 58.7% 9.2% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.23 

2023 0.0% 0.0% 44.6% 23.3% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.30 

2024 0.0% 0.0% 30.6% 37.3% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.37 

2025 0.0% 0.0% 16.5% 51.4% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.44 

2026 0.0% 0.0% 2.4% 65.4% 2.5% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.51 

2027 0.0% 0.0% 0.0% 56.3% 14.1% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.58 

2028 0.0% 0.0% 0.0% 42.2% 28.2% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.65 

2029 0.0% 0.0% 0.0% 28.1% 42.2% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.72 

2030 0.0% 0.0% 0.0% 14.1% 56.3% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.79 

2031 0.0% 0.0% 0.0% 0.0% 70.4% 1.5% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.86 

2032 0.0% 0.0% 0.0% 0.0% 56.3% 15.6% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 15.93 

2033 0.0% 0.0% 0.0% 0.0% 42.3% 29.7% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.00 

2034 0.0% 0.0% 0.0% 0.0% 28.2% 43.7% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.07 

2035 0.0% 0.0% 0.0% 0.0% 14.1% 57.8% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.14 

2036 0.0% 0.0% 0.0% 0.0% 0.1% 71.8% 2.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.21 

2037 0.0% 0.0% 0.0% 0.0% 0.0% 57.9% 16.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.28 

2038 0.0% 0.0% 0.0% 0.0% 0.0% 43.9% 30.7% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.35 

2039 0.0% 0.0% 0.0% 0.0% 0.0% 29.8% 44.8% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.42 

2040 0.0% 0.0% 0.0% 0.0% 0.0% 15.7% 58.9% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.49 

2041 0.0% 0.0% 0.0% 0.0% 0.0% 1.7% 72.9% 0.4% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.56 

2042 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 62.2% 12.8% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.63 

2043 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 48.2% 26.8% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.70 

2044 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 34.1% 40.9% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.77 

2045 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 20.0% 55.0% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.84 

2046 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 6.0% 69.0% 10.0% 7.0% 3.0% 2.0% 2.0% 1.0% 16.92 

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Table 10.2.7 Single Package CAC: Base Case Efficiency Distributions and SWEFs 

Year 

Market Share by SEER Level 

13 13.5 14 14.5 15 15.5 16 16.6 SWEF

2016 75.0% 20.0% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.17 

2017 59.4% 35.6% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.25 

2018 43.9% 51.1% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.33 

2019 28.3% 66.7% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.40 

2020 12.8% 82.2% 2.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.48 

2021 0.0% 92.2% 4.8% 2.0% 1.0% 0.0% 0.0% 0.0% 13.56 

2022 0.0% 76.6% 20.4% 2.0% 1.0% 0.0% 0.0% 0.0% 13.64 

2023 0.0% 61.1% 35.9% 2.0% 1.0% 0.0% 0.0% 0.0% 13.71 

2024 0.0% 45.5% 51.5% 2.0% 1.0% 0.0% 0.0% 0.0% 13.79 

2025 0.0% 30.0% 67.0% 2.0% 1.0% 0.0% 0.0% 0.0% 13.87 

2026 0.0% 14.4% 82.6% 2.0% 1.0% 0.0% 0.0% 0.0% 13.95 

2027 0.0% 0.0% 95.8% 3.2% 1.0% 0.0% 0.0% 0.0% 14.03 

2028 0.0% 0.0% 80.3% 18.7% 1.0% 0.0% 0.0% 0.0% 14.10 

2029 0.0% 0.0% 64.7% 34.3% 1.0% 0.0% 0.0% 0.0% 14.18 

2030 0.0% 0.0% 49.2% 49.8% 1.0% 0.0% 0.0% 0.0% 14.26 

2031 0.0% 0.0% 33.6% 65.4% 1.0% 0.0% 0.0% 0.0% 14.34 

2032 0.0% 0.0% 18.0% 81.0% 1.0% 0.0% 0.0% 0.0% 14.41 

2033 0.0% 0.0% 2.5% 96.5% 1.0% 0.0% 0.0% 0.0% 14.49 

2034 0.0% 0.0% 0.0% 85.9% 14.1% 0.0% 0.0% 0.0% 14.57 

2035 0.0% 0.0% 0.0% 70.4% 29.6% 0.0% 0.0% 0.0% 14.65 

2036 0.0% 0.0% 0.0% 54.8% 45.2% 0.0% 0.0% 0.0% 14.73 

2037 0.0% 0.0% 0.0% 39.3% 60.7% 0.0% 0.0% 0.0% 14.80 

2038 0.0% 0.0% 0.0% 23.7% 76.3% 0.0% 0.0% 0.0% 14.88 

2039 0.0% 0.0% 0.0% 8.1% 91.9% 0.0% 0.0% 0.0% 14.96 

2040 0.0% 0.0% 0.0% 0.0% 92.6% 7.4% 0.0% 0.0% 15.04 

2041 0.0% 0.0% 0.0% 0.0% 77.0% 23.0% 0.0% 0.0% 15.11 

2042 0.0% 0.0% 0.0% 0.0% 61.5% 38.5% 0.0% 0.0% 15.19 

2043 0.0% 0.0% 0.0% 0.0% 45.9% 54.1% 0.0% 0.0% 15.27 

2044 0.0% 0.0% 0.0% 0.0% 30.3% 69.7% 0.0% 0.0% 15.35 

2045 0.0% 0.0% 0.0% 0.0% 14.8% 85.2% 0.0% 0.0% 15.43 

2046 0.0% 0.0% 0.0% 0.0% 0.0% 99.2% 0.8% 0.0% 15.50 

10.2.2 Heat Pumps 

10.2.2.1 Base and Standards Case Efficiencies 

For both HP product classes—split systems and single package systems—DOE 

developed product efficiencies in the base case by assigning equipment to specific efficiency 

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EERE-2008-BT-STD-0006 COMMENT 54
 

levels for the year 2016. In other words, DOE determined the distribution of product efficiencies 

currently in the marketplace to develop a SEER-based SWEF for the year 2016. DOE derived its 

base-case efficiency distributions for split system and single package HPs on SWEF data 

provided by AHRI in combination with the range of product offerings in AHRI’s listing of 

certified unitary HP equipment. For more details on the derivation of the split system and single 

package base case efficiencies, refer to section 8.2.3.8 of chapter 8, LCC and PBP Analysis. 

AHRI’s SWEF data for HPs was based solely on SEER—not HSPF. To determine 

HSPF-based SWEFs for the base case, DOE used the SEER and HSPF pairings presented in 

section 5.9.1 of chapter 5, Engineering Analysis, to define the relationship between SEER and 

HSPF for both split system and single package HPs. The SEER and HSPF pairings for split 

system HPs are graphically presented in Figure 10.2.5. As is evident from this figure, the 

relationship can be represented accurately with a second-order polynomial expression. 

10.5 

10.0 

9.5 

9.0 

8.5 

8.0 

7.5 

12 13 14 15 16 17 18 19 20 

SEER 

Figure 10.2.5 Split System HP: HSPF and SEER relationship 

The SEER and HSPF pairings for single package HPs are graphically presented in Figure 10.2.6. 

For single package units, the HSPF is dependent on the following ranges of SEER: 

SEER < 14, HSPF = 0.30 * SEER + 3.80; 

14 ≤ SEER < 15, HSPF = 8.0; 

10-14 

HSPF 

HSPF = 0.025 * SEER2 - 0.408 * SEER + 8.789 

EERE-2008-BT-STD-0006 COMMENT 54
15 ≤ SEER < 16, HSPF = 1.0 * SEER + 7.00; and 

SEER ≥ 16, HSPF = 9.00. 

HSPF 

9.5 

9.0 

8.5 

HSPF = 0.30 * SEER + 3.80 

SEER < 14 

HSPF = 8.00 

14 < SEER < 15 

HSPF = 1.00 * SEER - 7.00 

15 < SEER < 16 

HSPF = 9.00 

SEER > 16 

8.0 

7.5 

12 16 17 

Figure 10.2.6 Single Package HP: HSPF and SEER relationship 

For its determination of standards-case efficiencies, DOE assumed a “roll-up” scenario to 

establish both a SEER-based and HSPF-based SWEF for the year that standards are assumed to 

become effective (i.e., 2016). Using the same method as was developed for CACs, DOE 

assumed that product efficiencies in the base case that did not meet the standard under 

consideration would “roll up” to meet the new standard level. Also, DOE assumed that all 

product efficiencies in the base case that were above the standard under consideration would not 

be affected. 

Tables 10.2.8 and 10.2.9 present the efficiency distributions and resulting SEER-based 

and HSPF-based SWEFs for the base case and standards cases for split system and single 

package HPs, respectively. Each table clearly shows how each standards case, under a “roll-up” 

scenario, affects the efficiency distribution. 

13 14 15 

SEER 

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Table 10.2.8 Split System HP: Efficiency Distributions for the Base and Standards Cases 

in 2016 

CSL SEER HSPF 

Market Share 

Base 

Case 

Standards Case 

1 2 3 4 5 6 7 8 9 10 

Baseline 13.0 7.7 13% - - - - - - - - - -

1 13.5 7.9 52% 65% - - - - - - - - -

2 14.0 8.0 10% 10% 75% - - - - - - - -

3 14.5 8.2 9.0% 9.0% 9.0% 84% - - - - - - -

4 15.0 8.3 5.5% 5.5% 5.5% 5.5% 89.5% - - - - - -

5 15.5 8.5 3.5% 3.5% 3.5% 3.5% 3.5% 93% - - - - -

6 16.0 8.6 3.0% 3.0% 3.0% 3.0% 3.0% 3.0% 96% - - - -

7 17.0 9.1 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 2.0% 98% - - -

8 18.0 9.6 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 1.5% 99.5% - -

9 19.0 10.1 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 0.5% 100% -

10 19.5 10.3 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 100% 

SWEF (SEER) 13.97 14.03 14.36 14.73 15.15 15.60 16.07 17.03 18.01 19.00 19.50 

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8.49 8.63 9.11 9.60 10.10 10.30 

Table 10.2.9 Single Package HP: Efficiency Distributions for the Base and Standards 

Cases in 2016 

CSL SEER HSPF 

Market Share 

Base Case 

Standards Case 

1 2 3 4 5 6 7 

Baseline 13.0 7.7 50% - - - - - - -

1 13.5 7.9 32% 82% - - - - - -

2 14.0 8.0 11% 11% 93% - - - - -

3 14.5 8.0 5% 5% 5% 98% - - - -

4 15.0 8.0 2% 2% 2% 2% 100% - - -

5 15.5 8.5 0% 0% 0% 0% 0% 100% - -

6 16.0 9.0 0% 0% 0% 0% 0% 0% 100% -

7 16.4 9.0 0% 0% 0% 0% 0% 0% 0% 100% 

SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40 

SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00 

10.2.2.2 Forecasted Efficiency Trends 

Historical Efficiency Trends 

Using the SWEF for the year 2016 as a starting point, DOE developed a SEER-based 

base case forecasted efficiency trend based on assumptions regarding future efficiency growth. 

To estimate SEER-based SWEFs over the 30 year forecast spanning 2016–2046 (2016 being the 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

assumed effective date of a new standard), DOE reviewed historical SWEF data provided by the 

Air-Conditioning, Heating, and Refrigeration Institute (AHRI) spanning the years 1992 to 2008.1 

Between 1992, the year in which the first set of standards for CAC and HPs became effective, 

and 2006, when an updated set of standards became effective, the SEER-based SWEFs for HPs 

grew by approximately one SEER point. Figure 10.2.7 shows the SEER-based SWEFs for split 

system and single package HPs. The figure also presents the linear fit to each product class’ 

SWEF data series. The linear fits have high coefficients of determination, i.e., linear fits provide 

a good estimate of the SWEF growth rate. Table 10.2.10 provides a summary of the SEERbased SWEF growth rates for each product class. 

Split HP 

SEER = 0.0739 * year - 136.55 

R2 = 0.9594 

Package HP 

SEER = 0.0736 * year - 136.03 

R2 = 0.8886 

10.2 

10.4 

10.6 

10.8 

11.0 

11.2 

11.4 

11.6 

11.8 

1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 

Year 

Shipment-Weighted SEER 

Split HP 

Package HP 

Linear (Split HP) 

Linear (Package HP) 

Figure 10.2.7 Heat Pump Historical SWEFs based on SEER with Linear Fits 

Table 10.2.10 Heat Pump SWEF Growth Rates 

 SWEF Growth Rate 

Product Class SEER increase per year 

Split System Heat Pumps 0.0739 

Single Package Heat Pumps 0.0736 

Base Case Efficiency Trends 

Because various market-pull programs such as Energy Star and utility rebate programs 

were in existence from 1992 to 2005, the SEER-based SWEF growth rate evident in the 

historical data was likely due in part to these market-pull programs. As a result, DOE applied 

the SEER-based SWEF growth rates in Table 10.2.6 to the SWEFs in 2016 to forecast annual 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

SEER-based SWEFs for the HP product classes from 2016 to 2046. Application of the SWEF 

growth rates in this manner assumes that future market-pull programs will be as effective at 

increasing product efficiency as past programs. 

Standards Case Efficiency Trends 

To develop standards case forecasted SEER-based SWEFs, DOE developed growth 

trends for each candidate standard level that maintained the same per-unit average total installed 

cost difference for the year 2016 between the base case and each standards case over the entire 

forecast period (2016–2046). DOE’s approach for developing standards case SWEFs assumes 

that the rate of adoption of more efficient products under the standards case can occur only at a 

rate which ensures that the average total installed cost difference between the standards case and 

base case over the entire forecast period is held constant. Because the total installed cost versus 

efficiency relationship for each product class demonstrates an increasing cost rate for more 

efficient products, the SEER-based SWEF growth rate for each standards case is lower than the 

SEER-based SWEF growth rate for the base case. 

Depicting Base Case and Standards Case Efficiency Trends 

Figures 10.2.8 and 10.2.9 show the base case historical SWEFs, the base case forecasted 

efficiency trend, and each standards case forecasted efficiency trend for split system HP SEER 

and HSPF, respectively. The HSPF-based SWEFs were derived from the SEER-based SWEFs 

using the SEER and HSPF relationship for split systems presented in section 10.2.2.1. Looking 

at Figure 10.2.8 closely, it can be seen that the standards case SEER-based SWEF growth rates 

are slightly lower than the SWEF growth rate for the base case. Note that for some standards 

cases, the efficiency trend does not increase past the Max Tech level. The Max Tech level for 

split systems is 19.5 SEER and 10.3 HSPF. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

SWEF (SEER) 

20 

19 

18 

17 

16 

15 

14 

13 

12 

11 

10 

1990 

Base Case 

CSL 1: 13.5 SEER 

CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 17 SEER 

CSL 8: 18 SEER 

CSl 9: 19 SEER 

CSL 10: 19.5 SEER 

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

Figure 10.2.8	 Split System HP: SEER-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases 

10.5
 

Base Case
 

CSL 1: 13.5 SEER 10.0
 

CSL 2: 14 SEER
 

CSL 3: 14.5 SEER 9.5 

SWEF (HSPF) 

9.0 

8.5 

8.0 

7.5 

7.0 

1990 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 17 SEER 

CSL 8: 18 SEER 

CSl 9: 19 SEER 

CSL 10: 19.5 SEER 

1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

Figure 10.2.9	 Split System HP: HSPF-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Figures 10.2.10 and 10.2.11 show the base case historical SWEFs, the base case 

forecasted efficiency trend, and each standards case forecasted efficiency trend for single 

package HP SEER and HSPF, respectively. The HSPF-based SWEFs were derived from the 

SEER-based SWEFs using the SEER and HSPF relationship for single package units presented 

in section 10.2.2.1. Looking at Figure 10.2.10 closely, it can be seen that the standards case 

SEER-based SWEF growth rates are slightly lower than the SWEF growth rate for the base case. 

Note that for some standards cases, the efficiency trend does not increase past the Max Tech 

level. The Max Tech level for single package units is 16.4 SEER and 0.9 HSPF. 

10 

11 

12 

13 

14 

15 

16 

17 

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

SWEF (SEER) 

Base Case 

CSL 1: 13.5 SEER 

CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 16.4 SEER 

Figure 10.2.10 Single Package HP: SEER-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases 

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6.5 

7.0 

7.5 

8.0 

8.5 

9.0 

1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 

Year 

SWEF (HSPF) 

Base Case 

CSL 1: 13.5 SEER 

CSL 2: 14 SEER 

CSL 3: 14.5 SEER 

CSL 4: 15 SEER 

CSL 5: 15.5 SEER 

CSL 6: 16 SEER 

CSL 7: 16.4 SEER 

Figure 10.2.11 Single Package HP: HSPF-based Historical SWEFs and Forecasted 

Efficiency Trends for the Base and Standards Cases 

10.2.2.3 Forecasted Efficiency Distributions 

Once DOE developed base case and standards case efficiency trends, it derived a 

distribution of product efficiencies from the forecasted SWEFs for each year of the analysis 

period (2016–2046) by developing appropriate market shares for the various standard levels. 

As specified in Tables 10.2.8 and 10.2.9, DOE developed the product efficiency 

distributions for the year the standard is assumed to become effective (2016) using a “roll-up” 

scenario. For subsequent years (2017–2046), DOE assigned the market shares to the standard 

levels so that the resulting calculated SWEF remained equal to the forecasted SWEF. This 

assignment was conducted by pulling market shares from lower efficiency levels to higher 

efficiency levels until the calculated SWEF equaled the forecasted value. 

Tables 10.2.11 and 10.2.12 provide examples of forecasted efficiency distributions—the 

specific cases of the forecasted SEER-based efficiency distributions for the base case (without 

standards) for split system and single package HPs, respectively. The tables also provide the 

resulting SEER-based SWEF for each year during the forecast period. The NIA spreadsheet 

(detailed in Appendix 10-A) provides the forecasted efficiency distributions for all the standards 

cases for both split system and single package HPs. 

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Table 10.2.11 Split System HPs: SEER-based Base Case Efficiency Distributions and 

SWEFs 

Year 

Market Shares by SEER Level 

13 13.5 14 14.5 15 15.5 16 17 18 19 19.5 SWEF

2016 13.0% 52.0% 10.0% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 13.97 

2017 0.0% 63.2% 11.8% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.04 

2018 0.0% 48.4% 26.6% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.12 

2019 0.0% 33.7% 41.3% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.19 

2020 0.0% 18.9% 56.1% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.26 

2021 0.0% 4.1% 70.9% 9.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.34 

2022 0.0% 0.0% 64.3% 19.7% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.41 

2023 0.0% 0.0% 49.5% 34.5% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.48 

2024 0.0% 0.0% 34.7% 49.3% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.56 

2025 0.0% 0.0% 20.0% 64.0% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.63 

2026 0.0% 0.0% 5.2% 78.8% 5.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.71 

2027 0.0% 0.0% 0.0% 74.4% 15.1% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.78 

2028 0.0% 0.0% 0.0% 59.6% 29.9% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.85 

2029 0.0% 0.0% 0.0% 44.8% 44.7% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 14.93 

2030 0.0% 0.0% 0.0% 30.0% 59.5% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.00 

2031 0.0% 0.0% 0.0% 15.3% 74.2% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.08 

2032 0.0% 0.0% 0.0% 0.5% 89.0% 3.5% 3.0% 2.0% 1.5% 0.5% 0.0% 15.15 

2033 0.0% 0.0% 0.0% 0.0% 75.2% 17.8% 3.0% 2.0% 1.5% 0.5% 0.0% 15.22 

2034 0.0% 0.0% 0.0% 0.0% 60.4% 32.6% 3.0% 2.0% 1.5% 0.5% 0.0% 15.30 

2035 0.0% 0.0% 0.0% 0.0% 45.6% 47.4% 3.0% 2.0% 1.5% 0.5% 0.0% 15.37 

2036 0.0% 0.0% 0.0% 0.0% 30.9% 62.1% 3.0% 2.0% 1.5% 0.5% 0.0% 15.45 

2037 0.0% 0.0% 0.0% 0.0% 16.1% 76.9% 3.0% 2.0% 1.5% 0.5% 0.0% 15.52 

2038 0.0% 0.0% 0.0% 0.0% 1.3% 91.7% 3.0% 2.0% 1.5% 0.5% 0.0% 15.59 

2039 0.0% 0.0% 0.0% 0.0% 0.0% 79.5% 16.5% 2.0% 1.5% 0.5% 0.0% 15.67 

2040 0.0% 0.0% 0.0% 0.0% 0.0% 64.7% 31.3% 2.0% 1.5% 0.5% 0.0% 15.74 

2041 0.0% 0.0% 0.0% 0.0% 0.0% 49.9% 46.1% 2.0% 1.5% 0.5% 0.0% 15.82 

2042 0.0% 0.0% 0.0% 0.0% 0.0% 35.2% 60.8% 2.0% 1.5% 0.5% 0.0% 15.89 

2043 0.0% 0.0% 0.0% 0.0% 0.0% 20.4% 75.6% 2.0% 1.5% 0.5% 0.0% 15.96 

2044 0.0% 0.0% 0.0% 0.0% 0.0% 5.6% 90.4% 2.0% 1.5% 0.5% 0.0% 16.04 

2045 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 91.4% 6.6% 1.5% 0.5% 0.0% 16.11 

2046 0.0% 0.0% 0.0% 0.0% 0.0% 0.0% 84.0% 14.0% 1.5% 0.5% 0.0% 16.18 

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Table 10.2.12 Single Package HPs: SEER-based Base Case Efficiency Distributions and 

SWEFs 

Year 

Market Share by SEER Level 

13 13.5 14 14.5 15 15.5 16 16.4 SWEF

2016 50.0% 32.0% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.39 

2017 35.3% 46.7% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.46 

2018 20.6% 61.4% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.53 

2019 5.9% 76.1% 11.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.61 

2020 0.0% 73.2% 19.8% 5.0% 2.0% 0.0% 0.0% 0.0% 13.68 

2021 0.0% 58.4% 34.6% 5.0% 2.0% 0.0% 0.0% 0.0% 13.75 

2022 0.0% 43.7% 49.3% 5.0% 2.0% 0.0% 0.0% 0.0% 13.83 

2023 0.0% 29.0% 64.0% 5.0% 2.0% 0.0% 0.0% 0.0% 13.90 

2024 0.0% 14.3% 78.7% 5.0% 2.0% 0.0% 0.0% 0.0% 13.97 

2025 0.0% 0.0% 92.6% 5.4% 2.0% 0.0% 0.0% 0.0% 14.05 

2026 0.0% 0.0% 77.9% 20.1% 2.0% 0.0% 0.0% 0.0% 14.12 

2027 0.0% 0.0% 63.2% 34.8% 2.0% 0.0% 0.0% 0.0% 14.19 

2028 0.0% 0.0% 48.5% 49.5% 2.0% 0.0% 0.0% 0.0% 14.27 

2029 0.0% 0.0% 33.7% 64.3% 2.0% 0.0% 0.0% 0.0% 14.34 

2030 0.0% 0.0% 19.0% 79.0% 2.0% 0.0% 0.0% 0.0% 14.41 

2031 0.0% 0.0% 4.3% 93.7% 2.0% 0.0% 0.0% 0.0% 14.49 

2032 0.0% 0.0% 0.0% 87.6% 12.4% 0.0% 0.0% 0.0% 14.56 

2033 0.0% 0.0% 0.0% 72.9% 27.1% 0.0% 0.0% 0.0% 14.64 

2034 0.0% 0.0% 0.0% 58.2% 41.8% 0.0% 0.0% 0.0% 14.71 

2035 0.0% 0.0% 0.0% 43.5% 56.5% 0.0% 0.0% 0.0% 14.78 

2036 0.0% 0.0% 0.0% 28.8% 71.2% 0.0% 0.0% 0.0% 14.86 

2037 0.0% 0.0% 0.0% 14.1% 85.9% 0.0% 0.0% 0.0% 14.93 

2038 0.0% 0.0% 0.0% 0.0% 99.3% 0.7% 0.0% 0.0% 15.00 

2039 0.0% 0.0% 0.0% 0.0% 84.6% 15.4% 0.0% 0.0% 15.08 

2040 0.0% 0.0% 0.0% 0.0% 69.9% 30.1% 0.0% 0.0% 15.15 

2041 0.0% 0.0% 0.0% 0.0% 55.2% 44.8% 0.0% 0.0% 15.22 

2042 0.0% 0.0% 0.0% 0.0% 40.5% 59.5% 0.0% 0.0% 15.30 

2043 0.0% 0.0% 0.0% 0.0% 25.8% 74.2% 0.0% 0.0% 15.37 

2044 0.0% 0.0% 0.0% 0.0% 11.1% 88.9% 0.0% 0.0% 15.44 

2045 0.0% 0.0% 0.0% 0.0% 0.0% 96.4% 3.6% 0.0% 15.52 

2046 0.0% 0.0% 0.0% 0.0% 0.0% 81.7% 18.3% 0.0% 15.59 

10.3 CALCULATING NATIONAL AND REGIONAL ENERGY SAVINGS 

This section describes DOE’s calculation of national energy savings (NES) and regional 

energy savings (RES) for central air conditioners and heat pumps under various CSLs or 

standards cases. Similar methods are used to calculate energy savings for the Nation and for each 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

of the three climate regions that are evaluated separately (hot-humid, hot-dry, and rest of the 

Nation). 

10.3.1 Definition 

As the following equation illustrates, DOE calculates annual NES and RES as the 

difference between two projections: a base case (without new standards) and a standards case 

(with new standards). Positive values of NES or RES indicate energy savings (i.e., annual energy 

consumption (AEC) in the standards case is less than AEC in the base case). The calculation of 

annual nation energy savings (NESy) and annual regional energy savings (RESy) are represented 

by the following expressions. 

_ NES y = AECnatl −base AECnatl −std 

_ REGy = AECreg −base AECreg −std 

Cumulative energy savings are the sum over the forecast period, which extends from a standard’s 

assumed effective date (2016), to 30 years after the effective date (2046), of the annual NES and 

annual RES for each region. This calculation is represented by the following equations for : 

NES cum = ∑ NES y 

REScum = ∑RESy 

 DOE calculated AEC by multiplying the number or stock of a given product (by vintage) 

by its unit energy consumption (also by vintage). The calculation of the national and each 

regional AEC is represented by the following equation: 

AEC = ∑STOCKV ×UECV 

DOE defined the variables in the above expressions as follows: 

AEC = annual energy consumption each year for the Nation or region in quadrillion 

British thermal units (Btus)—or quads—summed over vintages of the product 

stock, STOCKV; 

NESy = national annual energy savings (quads); 

RESy = regional annual energy savings (quads); 

NEScum = national cumulative energy savings (quads); 

REScum = regional cumulative energy savings (quads); 

STOCKV = stock of product (millions of units) of vintage V that survive in the year for which 

DOE calculated annual energy consumption (vintages range from approximately 

10-24 

EERE-2008-BT-STD-0006 COMMENT 54
two to approximately 50 years, depending on the retirement function of the 

product); 

UECV = annual energy consumption per product in kilowatt-hours (kWh); electricity 

consumption is converted from site energy to source energy (quads) by applying a 

time-dependent conversion factor; 

natl = designates the quantity corresponds to the Nation; 

reg = designates the quantity corresponds to a region; 

base = designates the quantity corresponds to the base case; 

std = designates the quantity corresponds to the standards case; 

y = year in the forecast (2016–2046); and 

cum = cumulative over the forecast period (2016–2046); and 

V = year in which the product was purchased as a new unit. 

The stock of equipment depends on annual shipments and the lifetime of the given 

product. As described in chapter 9, DOE projected shipments for the base case and standards 

cases. 

10.3.2 Inputs to Calculation 

The inputs for calculating national and regional energy savings are: 

• Average annual energy consumption per unit (UEC), 

• shipments, 

• equipment stock (STOCKV), 

• annual energy consumption for the Nation or a give region (AEC), and 

• site-to-source conversion factor (src_conv). 

10.3.2.1 Annual Energy Consumption per Unit 

For each product class, DOE presented the per-unit annual energy consumption as a 

function of product efficiency in chapter 6, Energy Use Determination. Because the per-unit 

annual energy consumption is directly dependent on efficiency, DOE used the shipmentsweighted energy efficiency (SWEF) of the base and standards cases presented in section 10.2, 

along with the annual energy use data presented in chapters 6 and 8, to estimate the shipmentweighted average annual per-unit energy consumption (UEC) under the base and standards 

cases. The following sections describe DOE’s calculation of the shipment-weighted average 

annual UEC for both product classes of CAC and HPs. 

Split System CACs 

DOE based its calculation of the annual UEC of split system CACs on data presented in 

chapter 6. Based on the relationship between CAC efficiency (SEER) and annual UEC, Table 

10.3.1 presents the base case and standards case shipment-weighted annual UECs in the year 

2016 (the assumed effective date of new standards) for new construction coil-only installations 

for the Nation and the three specific regions (hot-humid, hot-dry, and rest-of-country). Table 

10-25 

EERE-2008-BT-STD-0006 COMMENT 54
10.3.2 presents the same UEC data but for coil-only units installed as either replacements or for 

new owners. In both tables, UECs are presented for both residential and commercial 

installations. In each table, the SWEF corresponding to the shipment-weighted annual UEC is 

also provided. 

To illustrate how shipment-weighted annual UECs change over the forecast period, 

Figure 10.3.1 demonstrates how the UECs for new construction coil-only installations for the 

base case and two standards cases (CSL 2 and CSL 7) change over time. Because SWEFs in the 

base case and each standards case were forecasted to increase over the forecast period, the 

corresponding UEC decreases over time. As noted earlier in section 10.2.1.2, DOE’s approach 

for forecasting standards case SWEFs assumes that the rate of adoption of more efficient 

products under the standards case can occur only at a rate which ensures that the shipmentweighted average total installed cost difference between the standards case and base case over 

the entire forecast period be held constant. Because the total installed cost versus efficiency 

relationship for split system coil-only CACs demonstrates an increasing cost rate for more 

efficient products, the SWEF growth rate for each standards case is lower than the SWEF growth 

rate for the base case. This is evident in Figure 10.3.1 as the gap in the shipment-weighted UECs 

between CSL 2 and the base case decreases over time. This is not evident in CSL 7, the Max 

Tech standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted 

UEC have achieved their maximum and minimum values, respectively, in the first year that the 

standard is assumed to become effective (2016). 

Table 10.3.1 Split System CAC, Coil-Only Units, New Construction: Shipment-Weighted 

Average per-Unit Annual Energy Consumption for Base and Standards 

Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50 

Annual 

Energy Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 2351 2328 2260 2193 2126 2061 2000 1939 

Hot-Humid 3458 3425 3324 3226 3128 3033 2942 2853 

Hot-Dry 1998 1979 1921 1864 1807 1752 1700 1648 

Rest-of-Country 1252 1240 1203 1167 1132 1098 1065 1032 

Comm. 

Nation 2338 2331 2307 2260 2210 2157 2104 2091 

Hot-Humid 2637 2627 2596 2545 2490 2432 2374 2357 

Hot-Dry 2403 2395 2370 2321 2269 2215 2160 2147 

Rest-of-Country 2053 2048 2032 1989 1943 1896 1848 1840 

10-26 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 10.3.2	 Split System CAC, Coil-Only Units, Replacement and New Owner Markets: 

Shipment-Weighted Average per-Unit Annual Energy Consumption for Base 

and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50 

Annual 

Energy Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 2287 2265 2199 2133 2069 2006 1945 1887 

Hot-Humid 3472 3439 3338 3239 3140 3045 2953 2864 

Hot-Dry 2076 2056 1996 1936 1878 1821 1766 1713 

Rest-of-Country 1268 1256 1219 1182 1146 1112 1078 1046 

Comm. 

Nation 2345 2338 2314 2267 2216 2164 2110 2098 

Hot-Humid 2607 2598 2567 2516 2461 2405 2347 2331 

Hot-Dry 2375 2368 2344 2295 2244 2191 2136 2123 

Rest-of-Country 2050 2045 2029 1986 1941 1894 1846 1837 

1800 

1850 

1900 

1950 

2000 

2050 

2100 

2150 

2200 

2250 

2300 

2350 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Cooling Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.5 SER) 

Figure 10.3.1	 Split System CAC, Coil-Only Units, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period 

10-27 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 10.3.3 presents the base case and standards case shipment-weighted annual UECs 

in the year 2016 (the assumed effective date of new standards) for new construction blower coil 

installations for the Nation and the three specific regions (hot-humid, hot-dry, and rest-ofcountry). Table 10.3.4 presents the same UEC data but for blower coil units installed as either 

replacements or for new owners. In both tables, UECs are presented for both residential and 

commercial installations. In each table, the SWEF corresponding to the shipment-weighted 

annual UEC is also provided. 

To illustrate how shipment-weighted annual UECs change over the forecast period, 

Figure 10.3.2 demonstrates how the UECs for new construction blower coil installations for the 

base case and three standards cases (CSL 2, CSL 9, and CSL 13) change over time. For the same 

reasons given above for coil-only units, the gap in the shipment-weighted UECs between the 

CSLs and the base case decrease over time. This is not evident in CSL 13, the Max Tech 

standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted UEC 

have achieved their maximum and minimum values, respectively, in the first year that the 

standard is assumed to become effective (2016). 

Table 10.3.3 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Annual Energy 

Consumption for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 11 12 13 

SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

Annual 

Energy Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 2229 2212 2160 2109 2059 2010 1963 1917 1874 1784 1697 1616 1541 1471 

Hot-Humid 3310 3285 3207 3132 3057 2984 2914 2846 2782 2649 2519 2399 2288 2185 

Hot-Dry 1906 1891 1847 1803 1760 1718 1678 1639 1602 1525 1451 1382 1318 1258 

Rest-of-Cntry 1150 1142 1115 1088 1062 1037 1013 989 967 921 876 834 795 759 

Comm. 

Nation 2287 2282 2264 2228 2190 2150 2110 2100 2091 2069 2045 2020 1995 1970 

Hot-Humid 2532 2525 2502 2464 2423 2380 2336 2324 2312 2284 2253 2222 2190 2157 

Hot-Dry 2306 2300 2282 2245 2207 2167 2126 2116 2106 2084 2059 2034 2008 1982 

Rest-of-Cntry 1987 1984 1971 1940 1906 1870 1834 1828 1821 1806 1790 1774 1757 1740 

10-28 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 10.3.4	 Split System Central Air Conditioners, Blower Coil Units: Replacement and 

New Owner Markets, Shipment-Weighted Average per-Unit Annual Energy 

Consumption for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 11 12 13 

SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

Annual 

Energy Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 2167 2150 2100 2050 2001 1954 1908 1863 1821 1734 1649 1571 1498 1431 

Hot-Humid 3257 3232 3156 3082 3008 2937 2868 2801 2738 2606 2479 2361 2252 2150 

Hot-Dry 1933 1918 1873 1829 1785 1742 1702 1662 1624 1546 1471 1401 1336 1276 

Rest-of-Cntry 1180 1171 1143 1116 1090 1064 1039 1015 992 944 898 855 816 779 

Comm. 

Nation 2274 2269 2251 2215 2177 2138 2098 2088 2079 2057 2033 2009 1984 1959 

Hot-Humid 2546 2539 2516 2477 2436 2393 2349 2337 2325 2296 2265 2234 2201 2168 

Hot-Dry 2311 2305 2287 2250 2212 2172 2131 2121 2111 2088 2064 2038 2012 1986 

Rest-of-Cntry 1989 1985 1973 1941 1907 1872 1836 1829 1823 1808 1792 1775 1758 1741 

1300 

1400 

1500 

1600 

1700 

1800 

1900 

2000 

2100 

2200 

2300 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Cooling Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 9 (18 SEER) 

CSL 13 (22 SEER) 

Figure 10.3.2	 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Annual Energy 

Consumption for the Base Case and Three Standards Cases over the 2016-

2046 Forecast Period 

10-29 

EERE-2008-BT-STD-0006 COMMENT 54
Central Air Conditioners—Single Package System 

DOE based its calculation of the annual UEC of single package CACs on data presented 

in chapter 6. Based on the relationship between CAC efficiency (SEER) and annual UEC, Table 

10.3.5 presents the base case and standards case shipment-weighted annual UECs in the year 

2016 (the assumed effective date of new standards). Unlike split systems, the UECs for single 

package systems do not vary based on the installation (i.e., new construction, replacement, or 

new owner). In the table below, UECs are presented for both residential and commercial 

installations. Also, the SWEF corresponding to the shipment-weighted annual UEC is also 

provided. 

To illustrate how shipment-weighted annual UECs change over the forecast period, 

Figure 10.3.3 demonstrates how the UECs for the base case and two standards cases (CSL 2 and 

CSL 7) change over time. For the same reasons given above for coil-only and blower coil split 

system central air conditioners, the gap in the shipment-weighted UECs between the CSL 2 and 

the base case decrease over time. This is not evident in CSL 7, the Max Tech standards case, as 

the shipment-weighted SWEF and the corresponding shipment-weighted UEC have achieved 

their maximum and minimum values, respectively, in the first year that the standard is assumed 

to become effective (2016). 

Table 10.3.5	 Single Package Central Air Conditioners: Shipment-Weighted Average perUnit Annual Energy Consumption for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60 

Annual 

Energy 

Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 2346 2280 2202 2129 2058 1992 1930 1860 

Hot-Humid 3627 3525 3405 3291 3182 3080 2983 2876 

Hot-Dry 2123 2063 1993 1926 1863 1803 1746 1683 

Rest-of-Country 1292 1256 1213 1173 1134 1097 1063 1025 

Comm. 

Nation 2376 2354 2327 2273 2218 2162 2106 2091 

Hot-Humid 2662 2634 2598 2540 2480 2419 2359 2339 

Hot-Dry 2422 2399 2370 2315 2259 2202 2145 2129 

Rest-of-Country 2071 2057 2038 1989 1940 1890 1840 1830 

10-30 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

1800 

1900 

2000 

2100 

2200 

2300 

2400 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Cooling Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.6 SER) 

Figure 10.3.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Annual Energy Consumption for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period 

Heat Pumps—Split System 

DOE based its calculation of the annual UEC of split system HPs on data presented in 

chapter 6. Based on the relationship between HP efficiency and annual UEC, Table 10.3.6 

presents the base case and standards case shipment-weighted annual space-cooling and spaceheating UECs in the year 2016 (the assumed effective date of new standards). The UECs for 

split system heat pumps do not vary based on the installation (i.e., new construction, 

replacement, or new owner). In the table below, UECs are presented for both residential and 

commercial installations. Also, the SEER-based and HSPF-based SWEFs corresponding to the 

shipment-weighted annual space-cooling and space-heating UECs, respectively, are also 

provided. 

To illustrate how shipment-weighted annual UECs change over the forecast period, 

Figures 10.3.4 and 10.3.5 demonstrate how the space-cooling and space-heating UECs, 

respectively, for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change 

over time. For the same reasons given above for split system and single package central air 

conditioners, the gap in the shipment-weighted UECs between the CSLs and the base case 

decrease over time. This is not evident in CSL 10, the Max Tech standards case, as the 

10-31 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

shipment-weighted SWEFs and the corresponding shipment-weighted UECs have achieved their 

maximum and minimum values, respectively, in the first year that the standard is assumed to 

become effective (2016). 

Table 10.3.6	 Split System Heat Pump: Shipment-Weighted Average per-Unit Annual 

Energy Consumption for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15.59 16.06 17.03 18.02 19.01 19.50 

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8.49 8.63 9.11 9.60 10.10 10.30 

Cooling 

Annual 

Energy 

Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 3337 3320 3240 3154 3065 2975 2888 2725 2576 2441 2379 

Hot-Humid 4109 4087 3989 3884 3773 3664 3556 3355 3172 3006 2929 

Hot-Dry 4054 4033 3936 3832 3724 3615 3509 3310 3130 2966 2890 

Rest-of-Country 1840 1831 1787 1740 1690 1641 1593 1503 1421 1346 1312 

Comm. 

Nation 2366 2364 2354 2315 2271 2224 2175 2149 2123 2096 2082 

Hot-Humid 2643 2640 2627 2585 2538 2488 2436 2402 2368 2333 2316 

Hot-Dry 2398 2396 2386 2346 2301 2253 2204 2177 2149 2121 2107 

Rest-of-Country 2070 2069 2062 2026 1986 1943 1898 1881 1863 1844 1835 

Heating 

Annual 

Energy 

Use 

(kWh/yr) 

Resid. 

Nation 1779 1775 1753 1728 1702 1674 1647 1560 1480 1407 1380 

Hot-Humid 1306 1303 1287 1269 1249 1229 1209 1145 1087 1033 1013 

Hot-Dry 949 946 935 922 907 893 878 832 789 750 736 

Rest-of-Country 2998 2991 2953 2912 2867 2822 2776 2629 2494 2371 2325 

Comm. 

Nation 463 463 462 463 464 465 466 464 462 459 458 

Hot-Humid 215 215 215 215 215 215 216 215 213 212 212 

Hot-Dry 121 121 121 121 121 121 121 121 121 120 120 

Rest-of-Country 1065 1064 1062 1064 1066 1068 1070 1066 1061 1056 1053 

10-32 

EERE-2008-BT-STD-0006 COMMENT 54
2300 

2500 

2700 

2900 

3100 

3300 

3500 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Cooling Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (17 SEER) 

CSL 10 (19.5 SEER) 

Figure 10.3.4	 Split System Heat Pumps, New Construction: Shipment-Weighted Average 

per-Unit Annual Cooling Energy Consumption for the Base Case and 

Three Standards Cases over the 2016-2046 Forecast Period 

10-33 

EERE-2008-BT-STD-0006 COMMENT 54
1300 

1350 

1400 

1450 

1500 

1550 

1600 

1650 

1700 

1750 

1800 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Heating Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (17 SEER) 

CSL 10 (19.5 SEER) 

Figure 10.3.5	 Split System Heat Pumps, New Construction: Shipment-Weighted Average 

per-Unit Annual Heating Energy Consumption for the Base Case and 

Three Standards Cases over the 2016-2046 Forecast Period 

Heat Pumps—Single Package System 

DOE based its calculation of the annual UEC of split system heat pumps (HPs) on data 

presented in chapter 6. Based on the relationship between HP efficiency and annual UEC, Table 

10.3.7 presents the base case and standards case shipment-weighted annual space-cooling and 

space-heating UECs in the year 2016 (the assumed effective date of new standards). The UECs 

for split system heat pumps do not vary based on the installation (i.e., new construction, 

replacement, or new owner). In the table below, UECs are presented for both residential and 

commercial installations. Also, the SEER-based and HSPF-based SWEFs corresponding to the 

shipment-weighted annual space-cooling and space-heating UECs, respectively, are also 

provided. 

To illustrate how shipment-weighted annual UECs change over the forecast period, 

Figures 10.3.6 and 10.3.7 demonstrate how the space-cooling and space-heating UECs, 

respectively, for the base case and two standards cases (CSL 2 and CSL 7) change over time. 

For the same reasons given above for split system heat pumps, the gap in the shipment-weighted 

UECs between the CSL 2 and the base case decrease over time. This is not evident in CSL 7, the 

Max Tech standards case, as the shipment-weighted SWEFs and the corresponding shipment10-34 

EERE-2008-BT-STD-0006 COMMENT 54
weighted UECs have achieved their maximum and minimum values, respectively, in the first 

year that the standard is assumed to become effective (2016). 

Table 10.3.7	 Single Package Heat Pump: Shipment-Weighted Average per-Unit Annual 

Energy Consumption for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40 

SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00 

Cooling 

Annual 

Energy 

Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 3446 3380 3280 3175 3071 2972 2879 2809 

Hot-Humid 4294 4212 4087 3956 3826 3703 3587 3500 

Hot-Dry 4223 4143 4020 3891 3764 3642 3529 3443 

Rest-of-Country 1899 1863 1808 1750 1692 1638 1587 1548 

Comm. 

Nation 2392 2384 2372 2323 2272 2219 2167 2157 

Hot-Humid 2666 2656 2640 2588 2533 2478 2422 2408 

Hot-Dry 2429 2421 2408 2358 2306 2253 2200 2188 

Rest-of-Country 2102 2097 2088 2044 1997 1949 1900 1893 

Heating 

Annual 

Energy 

Use 

(kWh/yr) 

Resid. 

Nation 1790 1773 1745 1745 1745 1643 1551 1551 

Hot-Humid 1334 1321 1301 1301 1301 1224 1156 1156 

Hot-Dry 975 965 950 950 950 894 845 845 

Rest-of-Country 3056 3027 2980 2980 2980 2805 2649 2649 

Comm. 

Nation 477 476 475 476 477 478 479 478 

Hot-Humid 221 221 220 220 221 221 221 221 

Hot-Dry 125 125 124 125 125 125 125 125 

Rest-of-Country 1054 1052 1050 1052 1054 1057 1059 1057 

10-35 

EERE-2008-BT-STD-0006 COMMENT 54
2800 

2900 

3000 

3100 

3200 

3300 

3400 

3500 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Cooling Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.4 SER) 

Figure 10.3.6	 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Cooling Energy Consumption for the Base Case 

and Two Standards Cases over the 2016-2046 Forecast Period 

10-36 

EERE-2008-BT-STD-0006 COMMENT 54
1500 

1550 

1600 

1650 

1700 

1750 

1800 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Heating Energy Use (kWh/yr) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.4 SER) 

Figure 10.3.7 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Annual Heating Energy Consumption for the Base Case 

and Two Standards Cases over the 2016-2046 Forecast Period 

10.3.2.2 Shipments including Equipment Switching 

DOE forecasted shipments for the base case and all standards cases for the Nation as a 

whole and for the three climate regions that were evaluated separately (the hot-humid region, 

hot-dry, and rest of the Nation). An extensive description of the methodology for conducting 

and generating the shipments forecasts for all four of the product classes is presented in Chapter 

9, Shipments Analysis. 

In projecting standards case shipments, DOE analyzed the combined effects of increased 

total installed costs (purchase price plus installation costs), operating cost savings, and household 

income on consumer replacement and new owner purchase decisions. DOE determined that 

increased total installed cost is the most significant effect and impacts consumer replacement and 

new owner purchase decisions. As described in section 9.3 of chapter 9, DOE treated the impact 

of total installed cost increases on standards case shipments differently for the new construction, 

replacement, and new owner markets. 

For new construction purchases of split system and single package CACs and HPs, DOE 

assumed consumers were unaffected by an increase in total installed cost. In other words, DOE 

10-37 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

assumed new construction shipments under any standards case equaled new construction 

shipments under the base case. 

For replacement purchases of split system and single package CACs and HPs, DOE 

assumed consumers affected by an increase in total installed cost would repair their equipment 

rather than replace it, extending the life of the product by six years. 

For new owner purchases of split system and single package CACs, DOE assumed 

consumers affected by an increase in total installed cost would switch equipment and purchase a 

room air conditioner rather than a CAC. Because room air conditioners have lower cooling 

capacities and lower overall annual energy consumption than CACs, DOE did not explicitly 

account for the increased sales of room air conditioners in its analysis. Doing so would have 

credited a standard with energy savings from displaced CAC shipments. To avoid including 

savings from displaced shipments to new owners, DOE used the shipments projection estimates 

for the standards cases to calculate the annual energy consumption in the base case. 

For new owner purchases of split system and single package HPs, DOE assumed that 

consumers affected by an increase in total installed cost would switch equipment and purchase a 

combination electric resistance furnace and CAC rather than a HP. In its analysis of HP 

shipments in the NIA, DOE tracked purchases of electric furnaces and CACs due to decreases in 

shipments of HPs in order to quantify the energy impacts for consumers who were estimated to 

forgo purchasing a new HP. Because DOE explicitly accounted for the energy consumption of 

the displaced shipments of HPs, it maintained use of the base case shipments to determine the 

annual energy consumption in the base case. 

For the analysis of new owner purchases of split system HPs, DOE assumed that those 

consumers switching equipment would purchase a combination coil-only split system CAC and 

electric resistance furnace. For a given split system HP standard level, DOE assumed that the 

efficiency of the alternative split system CAC would be equal to the SEER of the foregone HP. 

As a result, DOE assumed the space-cooling UEC of the alternative split system CAC was no 

different than the space-cooling UEC of the forgone split system HP. The exception pertains to 

HP standard levels of 17 SEER and greater. The alternative coil-only split system CAC has a 

maximum efficiency of 16.5 SEER while the split system HP has a higher maximum efficiency 

level of 19.5 SEER. Therefore, for split system HP standard levels of 17 SEER and higher, the 

efficiency of the alternative coil-only split system CAC was held at 16.5 SEER. 

Correspondingly, at these maximum efficiency levels, the space-cooling UEC of the alternative 

split system CAC was greater than the UEC of the forgone split system HP which it was 

replacing. On the space-heating side, DOE assumed the UEC of the replacement electric 

resistance furnace had a coefficient of performance (COP) of 1.0 (equivalent to a 3.41 HSPF). 

Therefore, the electric furnace space-heating UEC was assumed to equal the space-heating UEC 

of the forgone HP at the base case level multiplied by the ratio of the HP efficiency at the base 

case level and the electric furnace efficiency. Table 10.3.8 presents the space-cooling and spaceheating UECs of the alternative coil-only split system CAC and electric furnace combination in 

the year 2016. UECs are provided for each of the candidate standard levels considered for split 

system HPs. As with the space-cooling UECs for heat pumps, the space-cooling UECs of the 

10-38 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

alternative split system CACs also decrease over the forecast period of 2016─2046 because of 

the adoption of more efficient equipment over time (refer to Figure 10.3.4 for split system HPs). 

Because electric resistance furnaces only have a single efficiency (COP = 1.0), the space-heating 

UECs of electric furnaces remain constant over the forecast period. 

Table 10.3.8	 Equipment Switching for New Owner Purchasers of Split System Heat 

Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption 

of Alternative Combination Coil-Only Split System Central Air Conditioner 

and Electric Furnace System for Base and Standards Cases in 2016 

Base 

Case 

Split Heat Pump Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

Cooling 

Annual 

Energy 

Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 3407 3374 3275 3178 3081 2988 2898 2728 2728 2728 2728 

Hot-Humid 4195 4155 4033 3913 3794 3679 3568 3359 3359 3359 3359 

Hot-Dry 4140 4100 3979 3861 3744 3630 3521 3315 3315 3315 3315 

Rest-of-Country 1879 1861 1806 1753 1699 1648 1598 1505 1505 1505 1505 

Comm. 

Nation 2385 2381 2368 2324 2276 2227 2177 2150 2150 2150 2150 

Hot-Humid 2664 2659 2642 2595 2544 2492 2438 2403 2403 2403 2403 

Hot-Dry 2417 2413 2400 2355 2306 2256 2205 2177 2177 2177 2177 

Rest-of-Country 2086 2083 2075 2034 1990 1945 1899 1881 1881 1881 1881 

Heating 

Annual 

Energy 

Use 

(kWh/yr) 

Resid. 

Nation 4173 4173 4171 4169 4168 4168 4167 4166 4166 4166 4166 

Hot-Humid 3063 3063 3062 3061 3060 3060 3059 3058 3058 3058 3058 

Hot-Dry 2225 2225 2224 2224 2223 2223 2222 2222 2222 2222 2222 

Rest-of-Country 7032 7032 7029 7026 7025 7023 7022 7021 7020 7020 7020 

Comm. 

Nation 1086 1089 1100 1117 1137 1157 1178 1238 1299 1360 1384 

Hot-Humid 505 506 511 519 527 536 546 573 601 629 639 

Hot-Dry 283 284 287 292 297 302 307 323 339 355 362 

Rest-of-Country 2496 2502 2528 2568 2612 2659 2708 2846 2985 3125 3179 

For the analysis of new owner purchases of single package HPs, DOE assumed that those 

consumers switching equipment would purchase a combination single package CAC and electric 

furnace. For a given single package HP standard level, DOE assumed that the efficiency of the 

alternative single package CAC would be equal to the SEER of the foregone HP. As a result, the 

space-cooling UEC of the alternative single package CAC was assumed to be no different than 

the space-cooling UEC of the forgone single package HP. The one exception pertains to the 

maximum efficiency HP standard level of 16.4 SEER. The alternative single package CAC has a 

maximum efficiency of 16.6 SEER. Therefore, for the single package HP standard levels of 16.4 

SEER, the efficiency of the alternative single package CAC was set at 16.6 SEER. 

Correspondingly, at the maximum efficiency level, the space-cooling UEC of the alternative 

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EERE-2008-BT-STD-0006 COMMENT 54
 

single package CAC was slightly less than the UEC of the forgone single package HP which it 

was replacing. On the space-heating side, DOE assumed the UEC of the replacement electric 

furnace had a coefficient of performance (COP) of 1.0 (equivalent to a 3.41 HSPF). Therefore, 

the electric furnace space-heating UEC was assumed to equal the space-heating UEC of the 

forgone HP at the base case level multiplied by the ratio of the HP efficiency at the base case 

level and the electric furnace efficiency. Table 10.3.9 presents the space-cooling and spaceheating UECs of the alternative single package CAC and electric furnace combination. UECs 

are provided for each of the candidate standard levels considered for single package HPs. As 

with the space-cooling UECs for heat pumps, the space-cooling UECs of the alternative single 

package CACs will also decrease over the forecast period of 2016─2046 because of the adoption 

of more efficient equipment over time (refer to Figure 10.3.6 for single package HPs). Because 

electric resistance furnaces only have a single efficiency (COP = 1.0), the space-heating UECs of 

electric furnaces remain constant over the forecast period. 

Table 10.3.9 Equipment Switching for New Owner Purchasers of Single Package Heat 

Pumps: Shipment-Weighted Average per-Unit Annual Energy Consumption 

of Alternative Combination Single Package Central Air Conditioner and 

Electric Furnace System for Base and Standards Cases in 2016 

Base 

Case 

Single Package Candidate Standard Level 

1 2 3 4 5 6 7 

Cooling 

Annual 

Energy 

Use 

(kWh/yr) 

Sector Region 

Resid. 

Nation 3500 3402 3286 3176 3071 2972 2879 2809 

Hot-Humid 4361 4239 4094 3957 3826 3703 3587 3500 

Hot-Dry 4290 4169 4027 3892 3764 3642 3529 3443 

Rest-of-Country 1929 1875 1811 1750 1692 1638 1587 1548 

Comm. 

Nation 2400 2389 2374 2323 2272 2219 2167 2157 

Hot-Humid 2676 2662 2643 2589 2533 2478 2422 2408 

Hot-Dry 2438 2426 2410 2359 2306 2253 2200 2188 

Rest-of-Country 2109 2101 2091 2044 1997 1949 1900 1893 

Heating 

Annual 

Energy 

Use 

(kWh/yr) 

Resid. 

Nation 4071 4092 4092 4092 4092 4092 4092 4092 

Hot-Humid 3054 3050 3050 3050 3050 3050 3050 3050 

Hot-Dry 2238 2228 2228 2228 2228 2228 2228 2228 

Rest-of-Country 6970 6988 6987 6987 6987 6987 6987 6987 

Comm. 

Nation 1089 1100 1115 1117 1119 1192 1264 1262 

Hot-Humid 505 510 516 517 518 551 584 583 

Hot-Dry 285 288 292 292 293 312 331 330 

Rest-of-Country 2406 2429 2462 2467 2472 2633 2794 2788 

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10.3.2.3 Equipment Stock 

The stock of equipment in any given year depends on annual shipments and the lifetime 

of a given product class. The NIA model keeps track of the number of units shipped each year. 

The lifetime of a unit (18.3 years for CACs and 15.5 years for heat pumps) determines how 

many units shipped in previous years survive in the given year. DOE assumes that products have 

an increasing probability of retiring as they age. The probability of survival as a function of years 

since purchase is termed the survival function. Refer to chapter 8, section 8.2.3.5 for further 

details on the survival functions that DOE used in its analysis. 

10.3.2.4 Annual Energy Consumption 

For each product class, DOE calculated national annual energy consumption (AEC) and 

AECs for each of the three climate regions being evaluated separately (the hot-humid, hot-dry, 

and rest of the Nation). Annual energy consumption is the product of the AEC per unit [also 

termed the unit energy consumption (UEC)] and the number of units of each vintage. This 

method accounts for differences in UEC from year to year. The equation for determining annual 

energy consumption, presented in section 10.3.1, is repeated here. 

AEC = ∑STOCKV ×UECV 

10.3.2.5 Site-to-Source Energy Conversion Factors 

In determining annual energy consumption for the Nation and for each of the three 

regions being evaluated separately, DOE initially calculated the annual energy consumption at 

the site (i.e., the energy in kWh consumed at the household or establishment). It then derived 

primary (source) energy from site energy consumption by applying a conversion factor to 

account for losses associated with the generation, transmission, and distribution of electricity. 

The site-to-source conversion factor is a multiplicative factor used for converting site energy 

consumption into primary or source energy consumption, expressed in quads. DOE used annual 

site-to-source conversion factors based on the version of the National Energy Modeling System 

(NEMS) that corresponds to Energy Information Administration (EIA’s) Annual Energy Outlook 

2009 (AEO 2009).2

 The factors used are marginal values, which represent the response of the 

electrical system to an incremental decrease in consumption. The conversion factors change over 

time, in response to projected changes in generation sources (the types of power plants projected 

to provide electricity to the country). DOE assumed that conversion factors remain constant at 

2030 values throughout the rest of forecast period. Table 10.3.10 shows the site-to-source 

conversion factors from 2005 to the end of the forecast period (2046). 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table 10.3.10 Site-to-Source Conversion Factors 

Year 

Electricity 

Btu/kWh Year 

Electricity 

Btu/kWh 

2005 11,500 2011 9,737 

2006 11,500 2012 9,649 

2007 11,200 2013 9,649 

2008 10,000 2014 8,649 

2009 9,737 2015 7,324 

2010 9,737 2016-2070 7,024 

10.4 CALCULATING NATIONAL AND REGIONAL NET PRESENT VALUE 

This section describes DOE’s calculation of the national and regional net present value 

(NPV) of costs and savings for the four product classes of central air conditioners and heat 

pumps under various candidate standards levels. Calculations were performed for the national 

NPV and NPVs for each of the three climate regions that are evaluated separately (hot-humid, 

hot-dry, and the rest of the Nation). 

10.4.1 Definition 

The NPV is the value in the present of a time-series of costs and savings. The NPV for 

the Nation as a whole and the three regions evaluated separately is described by the equation: 

_ NPV = PVS PVC 

Where: 

PVS = present value of savings in operating cost (including costs for energy, repair, and 

maintenance); and 

PVC = present value of increase in total installed cost (including costs for equipment and 

installation). 

DOE determined the PVS and PVC according to the following expressions. 

PVS = ∑OCSy × DFy 

PVC = ∑TICy × DFy 

DOE calculated the total annual savings in operating cost for the Nation as a whole and 

the three regions evaluated separately by multiplying the number or stock of a given product (by 

vintage) by its per-unit operating cost savings (also by vintage). DOE calculated the total annual 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

increase in installed cost for the Nation as a whole and the three regions by multiplying the 

number or stock of a given product (by vintage) by its per-unit total installed cost increase (also 

by vintage). Total annual savings in operating cost and increases in installed cost are calculated 

using the following equations. 

OCS y = ∑STOCKV ×UOCSV 

TIC y = ∑STOCKV ×UTICV 

DOE defined the variables in the above expressions as follows. 

OCS = total annual savings in operating cost each year summed over vintages of the 

product stock, STOCKV; 

TIC = total annual increase in installed cost each year summed over vintages of the 

product stock, STOCKV; 

DF = discount factor in each year; 

STOCKV = stock of product (millions of units) of vintage V that survive in the year for which 

DOE calculated annual energy consumption (vintages range from approximately 

two to approximately 50 years, depending on the retirement function of the 

product); 

UOCSV = annual per-unit savings in operating cost; 

UTICV = annual total per-unit increase in installed cost; 

V = year in which the product was purchased as a new unit; and 

y = year in the forecast (2016–2046). 

DOE determined the PVC for each year from the effective date of the standard until 2046. 

DOE determined the PVS for each year from the effective date of the standard until the year 

when units purchased in 2046 retire. DOE calculated costs and savings as the difference between 

a standards case and case without new standards (base case). 

DOE calculated a discount factor from the discount rate (7.0%) and the number of years 

between the “present” (2009, the year to which the sum is being discounted) and the year in 

which the costs and savings occur. The NPV is the sum over time of the discounted net savings. 

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10.4.2 Inputs to Calculation 

Listed below are the inputs to DOE’s calculation of the NPV of costs and savings for the 

Nation as a whole and the three areas evaluated separately. 

• Total installed cost per unit, 

• annual per-unit savings in operation cost, 

• shipments, 

• equipment stock (STOCKV), 

• total annual increases in installed cost (TIC), 

• total annual operating cost (OCS), 

• discount factor (DF), 

• present value of costs (PVC), and 

• present value of savings (PVS). 

The total annual increase in installed cost is equal to the annual change in the total perunit installed cost (difference between base case and standards case) multiplied by the shipments 

forecasted for each candidate standards level. As with calculating energy savings, DOE did not 

use base-case shipments to calculate total annual installed costs for all of the product classes. 

DOE assumed that consumers who forgo the purchase of a central air conditioner because of 

standards instead would purchase a room air conditioner, which will cost far less to purchase and 

operate. DOE used the projected shipments and stock for each candidate standard level to 

calculate costs. In the case of heat pumps, DOE assumed that any decrease in shipments caused 

by standards would result in the purchase of an electric furnace plus CAC. Thus the analysis 

tracked sales of electric furnaces and CACs that result from decreases in sales of heat pumps. 

The annual operating cost includes energy, repair, and maintenance costs. The total 

annual savings in operating cost are equal to the change in the annual operating costs (difference 

between base case and standards case) per unit multiplied by the shipments forecasted for each 

candidate standards level. As with calculating total annual installed costs, DOE did not 

necessarily use base-case shipments to calculate savings in operating cost. 

10.4.2.1 Total Installed Cost per Unit 

DOE described the total per-unit installed cost for each product class as a function of 

product efficiency in section 8.2.2 of Chapter 8, Life-Cycle Cost and Payback Period Analysis. 

Because the total per-unit annual installed cost depends directly on efficiency, DOE used the 

shipments-weight efficiencies (SWEFs) for the base and standards cases presented in section 

10.2, combined with the total installed cost presented in chapter 8, to estimate the shipmentsweighted total per-unit average annual installed cost under the base and standards cases. The 

following sections describe the shipments-weighted total per-unit average annual installed cost 

for all four product classes of central air conditioners and heat pumps. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

Central Air Conditioners—Split System 

DOE based its total per-unit installed cost for split system CACs on data presented in 

sections 8.2.2 of chapter 8. The total installed cost includes both the purchase price and 

installation cost. DOE based average equipment prices on average manufacturer costs multiplied 

by average overall markup values. Based on the relationship between CAC efficiency (SEER) 

and total installed cost presented in chapter 8, Tables 10.4.1 and 10.4.2 present the total per-unit 

installed cost for split system coil-only CACs based on the shipments-weighted energy factors 

(SWEFs) that correspond to the base case and each candidate standard level. Table 10.4.1 

presents the base case and standards case shipment-weighted total per-unit installed costs in the 

year 2016 (the assumed effective date of new standards) for new construction coil-only 

installations for the Nation and the three specific regions (hot-humid, hot-dry, and rest-ofcountry). Table 10.4.2 presents the same total per-unit installed cost data but for coil-only units 

installed as either replacements or for new owners. In both tables, per-unit total installed costs 

are the same for both residential and commercial installations. In each table, the SWEF 

corresponding to the shipment-weighted annual per-unit total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.1 demonstrates how the total installed costs for new construction 

coil-only installations for the base case and two standards cases (CSL 2 and CSL 7) change over 

time. Because SWEFs in the base case and each standards case were forecasted by DOE to 

increase over the forecast period, the corresponding total installed cost increases over time. As 

noted in earlier in section 10.2.1.2, DOE’s approach for forecasting standards case SWEFs 

assumes that the rate of adoption of more efficient products under the standards case can occur 

only at a rate which ensures that the shipment-weighted average total installed cost difference 

between the standards case and base case over the entire forecast period is held constant. This is 

evident in Figure 10.4.1 as the gap in the shipment-weighted total installed cost between CSL 2 

and the base case remains constant over time. This is not evident in CSL 7, the Max Tech 

standards case, as the shipment-weighted SWEF and the corresponding shipment-weighted total 

installed cost have achieved their maximum values in the first year that the standard is assumed 

to become effective (2016). 

Table 10.4.1 Split System Central Air Conditioners, Coil-Only Units, New Construction: 

Shipment-Weighted Average per-Unit Total Installed Cost for Base and 

Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Total 

Installed 

Cost 

 Region 

Nation $2,943 $2,961 $3,024 $3,101 $3,192 $3,308 $3,459 $3,639 

Hot-Humid $2,685 $2,702 $2,761 $2,835 $2,922 $3,032 $3,176 $3,348 

Hot-Dry $3,395 $3,415 $3,485 $3,571 $3,674 $3,803 $3,972 $4,173 

Rest-of-Country $2,905 $2,922 $2,982 $3,056 $3,145 $3,256 $3,402 $3,576 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table 10.4.2	 Split System Central Air Conditioners, Coil-Only Units, Replacement and 

New Owner Markets: Shipment-Weighted Average per-Unit Total Installed 

Cost for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Total 

Installed 

Cost 

 Region 

Nation $2,718 $2,813 $2,895 $3,015 $3,116 $3,244 $3,395 $3,609 

Hot-Humid $2,464 $2,554 $2,631 $2,746 $2,843 $2,965 $3,109 $3,313 

Hot-Dry $3,138 $3,244 $3,335 $3,470 $3,583 $3,726 $3,895 $4,134 

Rest-of-Country $2,699 $2,790 $2,869 $2,985 $3,082 $3,206 $3,352 $3,558 

$2,900 

$3,000 

$3,100 

$3,200 

$3,300 

$3,400 

$3,500 

$3,600 

$3,700 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Total Installed Cost ($/unit) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.5 SER) 

Figure 10.4.1	 Split System Central Air Conditioners, Coil-Only Units, New Construction: 

Shipment-Weighted Average Total Installed Cost for the Base Case and 

Two Standards Cases over the 2016-2046 Forecast Period 

Table 10.4.3 presents the base case and standards case shipment-weighted per-unit total 

installed costs in the year 2016 (the assumed effective date of new standards) for new 

construction blower coil installations for the Nation and the three specific regions (hot-humid, 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

hot-dry, and rest-of-country). Table 10.4.4 presents the same per-unit total installed cost data but 

for blower coil units installed as either replacements or for new owners. In both tables, per-unit 

total installed costs are the same for both residential and commercial installations. In each table, 

the SWEF corresponding to the shipment-weighted per-unit total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.2 demonstrates how the total installed costs for new construction 

blower coil installations for the base case and three standards cases (CSL 2, CSL 9, and CSL 13) 

change over time. For the same reasons given above for coil-only units, the gap in the shipmentweighted per-unit total installed costs between the CSLs and the base case are maintained over 

time. This is not evident in CSL 13, the Max Tech standards case, as the shipment-weighted 

SWEF and the corresponding shipment-weighted per-unit total installed cost have achieved their 

maximum values in the first year that the standard is assumed to become effective (2016). 

Table 10.4.3	 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average per-Unit Total Installed Cost for 

Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 11 12 13 

SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

Total 

Installed 

Cost 

Region 

Nation $3,738 $3,753 $3,803 $3,859 $3,903 $3,950 $4,000 $4,053 $4,108 $4,241 $4,395 $4,565 $4,752 $4,956 

Hot-Humid $3,413 $3,427 $3,475 $3,528 $3,570 $3,615 $3,663 $3,713 $3,766 $3,892 $4,039 $4,201 $4,379 $4,574 

Hot-Dry $4,315 $4,332 $4,388 $4,451 $4,500 $4,553 $4,609 $4,668 $4,730 $4,879 $5,051 $5,241 $5,450 $5,679 

Rest-of-Country $3,695 $3,709 $3,758 $3,811 $3,854 $3,899 $3,947 $3,998 $4,052 $4,179 $4,327 $4,491 $4,671 $4,868 

Table 10.4.4	 Split System Central Air Conditioners, Blower Coil Units, Replacement and 

New Owner Markets: Shipment-Weighted Average per-Unit Total Installed 

Cost for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 11 12 13 

SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

Total 

Installed 

Cost 

Region 

Nation $4,422 $4,436 $4,482 $4,533 $4,574 $4,617 $4,663 $4,711 $4,763 $4,885 $5,026 $5,182 $5,354 $5,542 

Hot-Humid $3,921 $3,935 $3,979 $4,028 $4,066 $4,107 $4,151 $4,198 $4,246 $4,363 $4,497 $4,647 $4,810 $4,990 

Hot-Dry $5,119 $5,135 $5,186 $5,244 $5,289 $5,338 $5,389 $5,443 $5,500 $5,637 $5,795 $5,970 $6,162 $6,373 

Rest-of-Country $4,423 $4,436 $4,480 $4,530 $4,569 $4,611 $4,655 $4,702 $4,751 $4,869 $5,005 $5,157 $5,322 $5,504 

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EERE-2008-BT-STD-0006 COMMENT 54
$3,700 

$3,800 

$3,900 

$4,000 

$4,100 

$4,200 

$4,300 

$4,400 

$4,500 

$4,600 

$4,700 

$4,800 

$4,900 

$5,000 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Total Installed Cost ($/unit) 

Base Case 

CSL 2 (14 SEER) 

CSL 9 (18 SEER) 

CSL 13 (22 SEER) 

Figure 10.4.2 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average Total Installed Cost for the 

Base Case and Three Standards Cases over the 2016-2046 Forecast Period 

Central Air Conditioners—Single Package 

DOE based its total per-unit installed cost for single package central air conditioners 

(CACs) on data presented in sections 8.2.2 of chapter 8. The total installed cost includes both the 

purchase price and installation cost. DOE based average equipment prices on average 

manufacturer costs multiplied by average overall markup values. Using the relationship between 

CAC efficiency (SEER) and total installed cost presented in chapter 8, Table 10.4.5 presents the 

base case and standards case shipment-weighted total per-unit installed costs in the year 2016 

(the assumed effective date of new standards) for new construction installations for the Nation 

and the three specific regions (hot-humid, hot-dry, and rest-of-country). Table 10.4.6 presents 

the same total per-unit installed cost data but for units installed as either replacements or for new 

owners. In both tables, per-unit total installed costs are the same for both residential and 

commercial installations. In each table, the SWEF corresponding to the shipment-weighted 

annual per-unit total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.3 demonstrates how the total installed costs for new construction 

installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

the same reasons given above for split system CACs, the gap in the shipment-weighted per-unit 

total installed costs between CSL 2 and the base case are maintained over time. This is not 

evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the 

corresponding shipment-weighted per-unit total installed cost have achieved their maximum 

values in the first year that the standard is assumed to become effective (2016). 

Table 10.4.5	 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average per-Unit Total Installed Cost for Base and Standards 

Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Total 

Installed 

Cost 

 Region 

Nation $3,141 $3,244 $3,333 $3,463 $3,573 $3,712 $3,877 $4,109 

Hot-Humid $2,877 $2,975 $3,059 $3,184 $3,289 $3,421 $3,578 $3,799 

Hot-Dry $3,629 $3,744 $3,843 $3,989 $4,112 $4,268 $4,452 $4,712 

Rest-of-Country $3,103 $3,201 $3,287 $3,413 $3,519 $3,653 $3,811 $4,035 

Table 10.4.6	 Single Package Central Air Conditioners, Replacement and New Owner 

Markets: Shipment-Weighted Average per-Unit Total Installed Cost for Base 

and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Total 

Installed 

Cost 

 Region 

Nation $2,718 $2,813 $2,895 $3,015 $3,116 $3,244 $3,395 $3,609 

Hot-Humid $2,464 $2,554 $2,631 $2,746 $2,843 $2,965 $3,109 $3,313 

Hot-Dry $3,138 $3,244 $3,335 $3,470 $3,583 $3,726 $3,895 $4,134 

Rest-of-Country $2,699 $2,790 $2,869 $2,985 $3,082 $3,206 $3,352 $3,558 

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EERE-2008-BT-STD-0006 COMMENT 54
3100 

3200 

3300 

3400 

3500 

3600 

3700 

3800 

3900 

4000 

4100 

4200 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Total Installed Cost ($/unit) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.6 SER) 

Figure 10.4.3 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Total Installed Cost for the Base Case and Two 

Standards Cases over the 2016-2046 Forecast Period 

Heat Pumps—Split System 

DOE based its total per-unit installed cost for split system heat pumps (HPs) on data 

presented in sections 8.2.2 of chapter 8. The total installed cost includes both the purchase price 

and installation cost. DOE based average equipment prices on average manufacturer costs 

multiplied by average overall markup values. Using the relationship between HP efficiency 

(SEER/HSPF) and total installed cost presented in chapter 8, Table 10.4.7 presents the base case 

and standards case shipment-weighted total per-unit installed costs in the year 2016 (the assumed 

effective date of new standards) for new construction installations for the Nation and the three 

specific regions (hot-humid, hot-dry, and rest-of-country). Table 10.4.8 presents the same total 

per-unit installed cost data but for units installed as either replacements or for new owners. In 

both tables, per-unit total installed costs are the same for both residential and commercial 

installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit 

total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.4 demonstrates how the total installed costs for new construction 

installations for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

over time. For the same reasons given above for split system CACs, the gap in the shipmentweighted per-unit total installed costs between the CSLs and the base case are maintained over 

time. This is not evident in CSL 10, the Max Tech standards case, as the shipment-weighted 

SWEF and the corresponding shipment-weighted per-unit total installed cost have achieved their 

maximum values in the first year that the standard is assumed to become effective (2016). 

Table 10.4.7	 Split System Heat Pumps, New Construction: Shipment-Weighted Average 

per-Unit Total Installed Costs for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15.59 16.06 17.03 18.02 19.01 20.00 

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8.49 8.63 9.11 9.60 10.10 10.30 

Total 

Installed 

Cost 

Region 

Nation $4,051 $4,063 $4,127 $4,184 $4,245 $4,316 $4,410 $4,577 $4,759 $4,957 $5,065 

Hot-Humid $3,746 $3,758 $3,819 $3,873 $3,931 $3,998 $4,088 $4,247 $4,421 $4,610 $4,713 

Hot-Dry $4,657 $4,671 $4,742 $4,806 $4,874 $4,953 $5,059 $5,245 $5,449 $5,670 $5,791 

Rest-of-Country $3,986 $3,998 $4,059 $4,114 $4,172 $4,241 $4,332 $4,492 $4,668 $4,859 $4,963 

Table 10.4.8	 Split System Heat Pumps, Replacement and New Owner Markets: ShipmentWeighted Average per-Unit Total Installed Costs for Base and Standards 

Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15.59 16.06 17.03 18.02 19.01 20.00 

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8.49 8.63 9.11 9.60 10.10 10.30 

Total 

Installed 

Cost 

Region 

Nation $3,492 $3,503 $3,562 $3,614 $3,670 $3,735 $3,822 $3,976 $4,143 $4,326 $4,425 

Hot-Humid $3,203 $3,213 $3,270 $3,319 $3,372 $3,435 $3,517 $3,664 $3,824 $3,997 $4,092 

Hot-Dry $4,024 $4,036 $4,102 $4,160 $4,223 $4,296 $4,393 $4,565 $4,752 $4,957 $5,067 

Rest-of-Country $3,452 $3,463 $3,520 $3,570 $3,624 $3,687 $3,771 $3,919 $4,080 $4,256 $4,352 

10-51 

EERE-2008-BT-STD-0006 COMMENT 54
4000 

4100 

4200 

4300 

4400 

4500 

4600 

4700 

4800 

4900 

5000 

5100 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Total Installed Cost ($/unit) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (17 SEER) 

CSL 10 (19.5 SEER) 

Figure 10.4.4 Split System Heat Pumps, New Construction: Shipment-Weighted Average 

Total Installed Cost for the Base Case and Three Standards Cases over the 

2016-2046 Forecast Period 

Heat Pumps—Single Package 

DOE based its total per-unit installed cost for single package heat pumps (HPs) on data 

presented in sections 8.2.2 of chapter 8. The total installed cost includes both the purchase price 

and installation cost. DOE based average equipment prices on average manufacturer costs 

multiplied by average overall markup values. Using the relationship between HP efficiency 

(SEER/HSPF) and total installed cost presented in chapter 8, Table 10.4.9 presents the base case 

and standards case shipment-weighted total per-unit installed costs in the year 2016 (the assumed 

effective date of new standards) for new construction installations for the Nation and the three 

specific regions (hot-humid, hot-dry, and rest-of-country). Table 10.4.10 presents the same total 

per-unit installed cost data but for units installed as either replacements or for new owners. In 

both tables, per-unit total installed costs are the same for both residential and commercial 

installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit 

total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.5 demonstrates how the total installed costs for new construction 

installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

the same reasons given above for split system CACs, the gap in the shipment-weighted per-unit 

total installed costs between CSL 2 and the base case are maintained over time. This is not 

evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and the 

corresponding shipment-weighted per-unit total installed cost have achieved their maximum 

values in the first year that the standard is assumed to become effective (2016). 

Table 10.4.9	 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average per-Unit Total Installed Costs for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40 

SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00 

Total 

Installed 

Cost 

Region 

Nation $3,646 $3,691 $3,784 $3,936 $4,078 $4,245 $4,444 $4,642 

Hot-Humid $3,408 $3,450 $3,539 $3,684 $3,819 $3,979 $4,168 $4,357 

Hot-Dry $4,185 $4,235 $4,339 $4,510 $4,668 $4,855 $5,076 $5,298 

Rest-of-Country $3,575 $3,618 $3,708 $3,855 $3,991 $4,152 $4,343 $4,534 

Table 10.4.10 Single Package Heat Pumps, Replacement and New Owner Markets: 

Shipment-Weighted Average per-Unit Total Installed Costs for Base and 

Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40 

SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00 

Total 

Installed 

Cost 

Region 

Nation $3,120 $3,161 $3,247 $3,387 $3,517 $3,671 $3,853 $4,036 

Hot-Humid $2,895 $2,935 $3,017 $3,150 $3,274 $3,421 $3,595 $3,769 

Hot-Dry $3,589 $3,635 $3,731 $3,888 $4,033 $4,206 $4,410 $4,614 

Rest-of-Country $3,071 $3,110 $3,193 $3,328 $3,454 $3,602 $3,778 $3,954 

10-53 

EERE-2008-BT-STD-0006 COMMENT 54
 

3600 

3700 

3800 

3900 

4000 

4100 

4200 

4300 

4400 

4500 

4600 

4700 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Total Installed Cost ($/unit) 

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.4 SER) 

Figure 10.4.5 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average Total Installed Cost for the Base Case and Two Standards Cases 

over the 2016-2046 Forecast Period 

10.4.2.2 Annual Operating Cost per Unit 

The per-unit annual operating cost includes costs for energy, repair, and maintenance. 

DOE calculated the annual savings in cost per unit for the nation as a whole and for the three 

regions that were evaluated separately. 

Annual Energy Costs 

DOE determined the per-unit annual savings in energy costs by multiplying the per-unit 

annual savings in energy consumption developed for each product class by the appropriate 

energy price. 

For both classes of both CACs and HPs, estimates of the per-unit annual energy 

consumption for the base case and each standards case were presented in section 10.3.2.1. As 

described previously, DOE forecasted the per-unit annual energy consumption for the base case 

and each standards case for all product classes by applying a growth trend in efficiency. 

10-54 

EERE-2008-BT-STD-0006 COMMENT 54
 

Energy prices are described in section 8.2.3.1 of chapter 8. DOE forecasted energy prices 

based on EIA’s AEO2009. Trends in energy prices are described in section 8.2.3.2 of chapter 8. 

Annual Repair and Maintenance Costs 

DOE described the total per-unit repair and maintenance costs for each product class as a 

function of product efficiency in sections 8.2.3.3 and 8.2.3.4 of Chapter 8, Life-Cycle Cost and 

Payback Period Analysis. Because the per-unit repair and maintenance costs depend directly on 

efficiency, DOE used the shipments-weight efficiencies (SWEFs) for the base and standards 

cases presented in section 10.2, combined with the repair and maintenance costs presented in 

chapter 8, to estimate the shipments-weighted per-unit average repair and maintenance costs 

under the base and standards cases. 

Based on the relationship between CAC efficiency (SEER) and repair and maintenance 

costs presented in chapter 8, Table 10.4.11 presents the base case and standards case shipmentweighted per-unit repair and maintenance costs for coil-only installations in the year 2016 (the 

assumed effective date of new standards) for the Nation and the three specific regions (hothumid, hot-dry, and rest-of-country). The per-unit repair and maintenance costs are the same for 

both residential and commercial installations as well as new construction and replacement/new 

owner installations. In each table, the SWEF corresponding to the shipment-weighted annual 

per-unit total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit repair and maintenance costs change 

over the forecast period, Figure 10.4.6 demonstrates how the costs for coil-only installations for 

the base case and two standards cases (CSL 2 and CSL 7) change over time. Because SWEFs in 

the base case and each standards case were forecasted by DOE to increase over the forecast 

period, the corresponding repair and maintenance costs increase over time. As noted in earlier in 

section 10.2.1.2, DOE’s approach for forecasting standards case SWEFs assumes that the rate of 

adoption of more efficient products under the standards case can occur only at a rate which 

ensures that the shipment-weighted average total installed cost difference between the standards 

case and base case over the entire forecast period is held constant. Because the change in repair 

and maintenance costs (as a function of efficiency) mirrors the change in total installed costs, the 

repair and maintenance cost difference between the standards case and base case over the entire 

forecast period also remains constant. This is evident in Figure 10.4.6 as the gap in the shipmentweighted repair and maintenance costs between CSL 2 and the base case remains constant over 

time. This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted 

SWEF and the corresponding shipment-weighted repair and maintenance costs have achieved 

their maximum values in the first year that the standard is assumed to become effective (2016). 

10-55 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

Table 10.4.11 Split System Central Air Conditioners, Coil-Only Units: Shipment-Weighted 

Average per-Unit Repair and Maintenance Cost for Base and Standards 

Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.65 13.77 14.18 14.60 15.05 15.52 16.00 16.50

Repair 

and 

Maint. 

Cost 

 Region 

Nation $152 $153 $157 $162 $168 $176 $186 $198 

Hot-Humid $122 $123 $127 $131 $136 $142 $150 $160 

Hot-Dry $173 $174 $179 $185 $192 $200 $212 $225 

Rest-of-Country $159 $160 $165 $170 $176 $184 $195 $207 

$150 

$155 

$160 

$165 

$170 

$175 

$180 

$185 

$190 

$195 

$200 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Repair and Maintenance Costs ($/unit)

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.5 SER) 

Figure 10.4.6	 Split System Central Air Conditioners, Coil-Only Units, New Construction: 

Shipment-Weighted Average Annual Repair and Maintenance Costs for 

the Base Case and Two Standards Cases over the 2016-2046 Forecast 

Period 

Table 10.4.12 presents the base case and standards case shipment-weighted per-unit 

repair and maintenance costs for split system CAC blower coil installations in the year 2016 (the 

assumed effective date of new standards) for the Nation and the three specific regions (hothumid, hot-dry, and rest-of-country). The per-unit repair and maintenance costs are the same for 

10-56 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

both residential and commercial installations as well as new construction and replacement/new 

owner installations. In each table, the SWEF corresponding to the shipment-weighted annual 

per-unit total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.7 demonstrates how the repair and maintenance costs for blower coil 

installations for the base case and three standards cases (CSL 2, CSL 9, and CSL 13) change 

over time. For the same reasons given above for coil-only units, the gap in the shipmentweighted per-unit repair and maintenance costs between the CSLs and the base case are 

maintained over time. This is not evident in CSL 13, the Max Tech standards case, as the 

shipment-weighted SWEF and the corresponding shipment-weighted per-unit repair and 

maintenance costs have achieved their maximum values in the first year that the standard is 

assumed to become effective (2016). 

Table 10.4.12 Split System Central Air Conditioners, Blower Coil Units: ShipmentWeighted Average per-Unit Repair and Maintenance Cost for Base and 

Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 11 12 13 

SWEF (SEER) 14.81 14.90 15.20 15.52 15.86 16.21 16.57 16.95 17.32 18.17 19.09 20.04 21.01 22.00 

Repair 

and 

Maint. 

Cost 

Region 

Nation $160 $161 $164 $167 $169 $172 $175 $177 $180 $188 $196 $205 $216 $227 

Hot-Humid $129 $130 $132 $134 $136 $138 $141 $143 $145 $151 $158 $166 $174 $183 

Hot-Dry $182 $183 $186 $190 $192 $195 $198 $202 $205 $213 $223 $233 $245 $258 

Rest-of-Country $168 $169 $172 $175 $177 $180 $183 $186 $189 $197 $205 $215 $226 $237 

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EERE-2008-BT-STD-0006 COMMENT 54
$160 

$170 

$180 

$190 

$200 

$210 

$220 

$230 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Repair and Maintenance Costs ($/unit)

Base Case 

CSL 2 (14 SEER) 

CSL 9 (18 SEER) 

CSL 13 (22 SEER) 

Figure 10.4.7 Split System Central Air Conditioners, Blower Coil Units, New 

Construction: Shipment-Weighted Average Annual Repair and 

Maintenance Costs for the Base Case and Three Standards Cases over the 

2016-2046 Forecast Period 

Table 10.4.13 presents the base case and standards case shipment-weighted per-unit 

repair and maintenance costs for single package CAC installations in the year 2016 (the assumed 

effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both 

residential and commercial installations as well as new construction and replacement/new owner 

installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit 

total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.8 demonstrates how the repair and maintenance costs for blower coil 

installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. For 

the same reasons given above for split system CACs, the gap in the shipment-weighted per-unit 

repair and maintenance costs between the CSLs and the base case are maintained over time. 

This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and 

the corresponding shipment-weighted per-unit repair and maintenance costs have achieved their 

maximum values in the first year that the standard is assumed to become effective (2016). 

10-58 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 10.4.13 Single Package Central Air Conditioners: Shipment-Weighted Average perUnit Repair and Maintenance Cost for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.17 13.55 14.02 14.51 15.00 15.50 16.00 16.60

Repair 

and 

Maint. 

Cost 

 Region 

Nation $147 $154 $159 $167 $173 $182 $191 $205 

Hot-Humid $119 $124 $128 $134 $140 $146 $154 $165 

Hot-Dry $168 $175 $181 $190 $197 $206 $218 $233 

Rest-of-Country $154 $161 $166 $175 $181 $190 $200 $215 

140 

150 

160 

170 

180 

190 

200 

210 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Repair and Maintenance Costs ($/unit)

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.6 SER) 

Figure 10.4.8	 Single Package Central Air Conditioners, New Construction: ShipmentWeighted Average Annual Repair and Maintenance Costs for the Base 

Case and Two Standards Cases over the 2016-2046 Forecast Period 

Table 10.4.14 presents the base case and standards case shipment-weighted per-unit 

repair and maintenance costs for split system HP installations in the year 2016 (the assumed 

effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both 

residential and commercial installations as well as new construction and replacement/new owner 

10-59 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit 

total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.9 demonstrates how the repair and maintenance costs for blower coil 

installations for the base case and three standards cases (CSL 2, CSL 7, and CSL 10) change 

over time. For the same reasons given above for split system CACs, the gap in the shipmentweighted per-unit repair and maintenance costs between the CSLs and the base case are 

maintained over time. This is not evident in CSL 10, the Max Tech standards case, as the 

shipment-weighted SWEF and the corresponding shipment-weighted per-unit repair and 

maintenance costs have achieved their maximum values in the first year that the standard is 

assumed to become effective (2016). 

Table 10.4.14 Split System Heat Pumps: Shipment-Weighted Average per-Unit Repair and 

Maintenance Costs for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

SWEF (SEER) 13.77 13.89 14.28 14.70 15.14 15.59 16.06 17.03 18.02 19.01 20.00 

SWEF (HSPF) 8.00 8.02 8.12 8.23 8.36 8.49 8.63 9.11 9.60 10.10 10.30 

Repair 

and 

Maint. 

Cost 

Region 

Nation $153 $153 $156 $159 $162 $165 $169 $177 $185 $194 $199 

Hot-Humid $123 $124 $126 $128 $130 $133 $136 $142 $149 $157 $160 

Hot-Dry $174 $174 $178 $181 $184 $187 $192 $201 $210 $221 $226 

Rest-of-Country $160 $161 $164 $166 $169 $173 $177 $185 $194 $203 $209 

10-60 

EERE-2008-BT-STD-0006 COMMENT 54
 

150 

155 

160 

165 

170 

175 

180 

185 

190 

195 

200 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average

Annual Repair and Maintenance Costs ($/unit)

Base Case 

CSL 2 (14 SEER) 

CSL 7 (17 SEER) 

CSL 10 (19.5 SEER) 

Figure 10.4.9 Split System Heat Pumps, New Construction: Shipment-Weighted Average 

Annual Repair and Maintenance Costs for the Base Case and Three 

Standards Cases over the 2016-2046 Forecast Period 

Table 10.4.15 presents the base case and standards case shipment-weighted per-unit 

repair and maintenance costs for single package HP installations in the year 2016 (the assumed 

effective date of new standards) for the Nation and the three specific regions (hot-humid, hotdry, and rest-of-country). The per-unit repair and maintenance costs are the same for both 

residential and commercial installations as well as new construction and replacement/new owner 

installations. In each table, the SWEF corresponding to the shipment-weighted annual per-unit 

total installed cost is also provided. 

To illustrate how shipment-weighted annual per-unit total installed costs change over the 

forecast period, Figure 10.4.10 demonstrates how the repair and maintenance costs for blower 

coil installations for the base case and two standards cases (CSL 2 and CSL 7) change over time. 

For the same reasons given above for split system CACs, the gap in the shipment-weighted perunit repair and maintenance costs between the CSLs and the base case are maintained over time. 

This is not evident in CSL 7, the Max Tech standards case, as the shipment-weighted SWEF and 

the corresponding shipment-weighted per-unit repair and maintenance costs have achieved their 

maximum values in the first year that the standard is assumed to become effective (2016). 

10-61 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 10.4.15 Single Package Heat Pumps: Shipment-Weighted Average per-Unit Repair 

and Maintenance Costs for Base and Standards Cases in 2016 

Base 

Case 

Candidate Standard Level 

1 2 3 4 5 6 7 

SWEF (SEER) 13.39 13.64 14.05 14.51 15.00 15.50 16.00 16.40 

SWEF (HSPF) 7.80 7.88 8.00 8.00 8.00 8.50 9.00 9.00 

Repair 

and 

Maint. 

Cost 

Region 

Nation $151 $153 $158 $165 $172 $181 $190 $200 

Hot-Humid $122 $124 $128 $134 $139 $146 $154 $162 

Hot-Dry $172 $174 $179 $188 $196 $205 $216 $227 

Rest-of-Country $158 $161 $165 $173 $180 $189 $199 $209 

150 

155 

160 

165 

170 

175 

180 

185 

190 

195 

200 

2015 2020 2025 2030 2035 2040 2045 

Year 

Shipment-Weighted Average 

Annual Repair and Maintenance Costs ($/unit)

Base Case 

CSL 2 (14 SEER) 

CSL 7 (16.4 SER) 

Figure 10.4.10 Single Package Heat Pumps, New Construction: Shipment-Weighted 

Average Annual Repair and Maintenance Costs for the Base Case and Two 

Standards Cases over the 2016-2046 Forecast Period 

10.4.2.3 Shipments including Equipment Switching 

DOE forecasted shipments for the base case and all standards cases for the Nation as a 

10-62 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

whole and for the three climate regions that were evaluated separately (the hot-humid region, 

hot-dry, and rest of the Nation). An extensive description of the methodology for conducting 

and generating the shipments forecasts for all four of the product class is presented in Chapter 9, 

Shipments Analysis. 

In projecting standards case shipments, DOE analyzed the combined effects of increased 

total installed costs (purchase price plus installation costs), operating cost savings, and household 

income on consumer replacement and new owner purchase decisions. DOE determined that 

increased total installed cost is the most significant effect and impacts consumer replacement and 

new owner purchase decisions. As described in section 9.4 of chapter 9, DOE treated the impact 

of total installed cost increases on standards case shipments differently for the new construction, 

replacement, and new owner markets. 

As described earlier in section 10.3.2.2, for new construction purchases of split system 

and single package CACs and HPs, DOE assumed consumers were unaffected by an increase in 

total installed cost. In other words, DOE assumed new construction shipments under any 

standards case equaled new construction shipments under the base case. For replacement 

purchases of split system and single package CACs and HPs, DOE assumed consumers affected 

by an increase in total installed cost would repair their equipment rather than replace it, 

extending the life of the product by six years. For new owner purchases of split system and 

single package CACs, DOE assumed consumers affected by an increase in total installed cost 

would switch equipment and purchase a room air conditioner rather than a CAC. For new owner 

purchases of split system and single package HPs, DOE assumed that consumers affected by an 

increase in total installed cost would switch equipment and purchase a combination electric 

resistance furnace and CAC rather than a HP. 

Table 10.4.16 presents the per-unit total installed costs of the alternative coil-only split 

system CAC and electric furnace combination to replace split system HPs. Per-unit costs are the 

same for residential and commercial installations. 

Table 10.4.16 Equipment Switching for New Owner Purchasers of Split System Heat 

Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of 

Alternative Combination Coil-Only Split System Central Air Conditioner 

and Electric Furnace System for Base and Standards Cases in 2016 

Region 

Base 

Case 

Split Heat Pump Candidate Standard Level 

1 2 3 4 5 6 7 8 9 10 

Nation $3,188 $3,205 $3,262 $3,333 $3,417 $3,524 $3,663 $3,828 $3,828 $3,828 $3,828 

Hot-Humid $2,946 $2,961 $3,016 $3,084 $3,164 $3,265 $3,398 $3,556 $3,556 $3,556 $3,556 

Hot-Dry $3,583 $3,602 $3,666 $3,745 $3,839 $3,958 $4,114 $4,299 $4,299 $4,299 $4,299 

Rest-of-Country $3,173 $3,189 $3,244 $3,313 $3,394 $3,497 $3,630 $3,790 $3,790 $3,790 $3,790 

10-63 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 10.4.17 presents the per-unit total installed costs of the alternative single package 

CAC and electric furnace combination to replace single package HPs. Per-unit costs are the 

same for residential and commercial installations. 

Table 10.4.17 Equipment Switching for New Owner Purchasers Single Package Heat 

Pumps: Shipment-Weighted Average per-Unit Total Installed Costs of 

Alternative Combination Single Package Central Air Conditioner and 

Electric Furnace System for Base and Standards Cases in 2016 

Region 

Base 

Case 

Single Package Candidate Standard Level 

1 2 3 4 5 6 7 

Nation $3,359 $3,454 $3,535 $3,656 $3,757 $3,885 $4,036 $4,249 

Hot-Humid $3,104 $3,194 $3,272 $3,387 $3,483 $3,605 $3,749 $3,953 

Hot-Dry $3,779 $3,885 $3,976 $4,111 $4,224 $4,367 $4,536 $4,775 

Rest-of-Country $3,340 $3,431 $3,510 $3,626 $3,723 $3,847 $3,992 $4,199 

10.4.2.4 Equipment Stock 

The stock of equipment in any given year depends on annual shipments and the lifetime 

of a given product class. The NIA model keeps track of the number of units shipped each year. 

The lifetime of a unit determines how many units shipped in previous years survive in the given 

year. DOE assumes that products have an increasing probability of retiring as they age. The 

probability of survival as a function of years since purchase is termed the survival function. 

Refer to the specific section for each product class in Chapter 9, Shipments Analysis, for further 

details on the survival functions that DOE used in its analysis. 

10.4.2.5 Increases in Total Annual Installed Cost 

The increase in total annual installed cost for a product under any given standards case is 

the product of the increase in total installed cost per unit attributable to the standard and the 

number of units of each vintage. This method accounts for differences in total installed cost from 

year to year. The equation for determining the total annual installed cost increase for a given 

candidate standards level, presented in section 10.4.1 is repeated here. 

TIC = ∑STOCKV ×UTICV 

As noted earlier, when considering heat pumps DOE accounted for the total installed cost 

for those consumers who decided to switch from a heat pump to an electric furnace plus CAC 

because standards increased the cost of new units. Therefore, the total annual increase in 

installed cost accounts for the total installed cost of CACs purchased in lieu of new heat pumps. 

10-64 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

10.4.2.6 Savings in Total Annual Operating Cost 

The savings in total annual operating cost for any given candidate standards level is the 

product of the annual per-unit savings in operating cost attributable to the standard and the 

number of units of each vintage. This method accounts for the year-to-year differences in annual 

operating cost savings. The equation for determining the total annual savings in operating cost 

for a given candidate standards level, which was presented in section 10.4.1, is repeated here. 

OCS = ∑STOCKV ×UOCSV 

As noted earlier, when considering heat pumps DOE accounted for the energy use of 

those consumers who decided to switch from a heat pump to an electric furnace and CAC in 

response to standards. Therefore, the total annual savings in operating cost accounts for the 

energy costs of the CACs purchased in lieu of heat pumps. 

10.4.2.7 Discount Factors 

DOE multiplied monetary values in future years by a discount factor to determine the 

present value. The discount factor (DF) is described by the equation: 

1

DF = _ ( y yp ) (1+ r ) 

Where:
 

r = discount rate, 

y = year of the monetary value, and 

yP = year in which the present value is being determined. 

Although DOE used consumer discount rates to determine the life-cycle cost of 

refrigeration products (chapter 8), it used national discount rates to calculate national NPV. DOE 

estimated NPV using both a 3-percent and a 7-percent real discount rate, in accordance with the 

Office of Management and Budget’s guidance to Federal agencies on the development of 

regulatory analysis, particularly section E therein: Identifying and Measuring Benefits and 

Costs.

3

 DOE defined the present year as 2009. 

10.4.2.8 Present Value of Increased Installed Cost 

The present value of increased installed cost is the difference between installation cost in 

each standards case and the base case discounted to the present and summed throughout the 

period over which DOE is considering the installation of units (from the effective date of 

standards, 2016, to 2046). 

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EERE-2008-BT-STD-0006 COMMENT 54
 

The increase in total installed cost refers to both the purchase price and installation cost 

associated with the more expensive units purchased in the standards case compared to the base 

case. DOE calculated annual increases in installed cost as the difference in total installed cost for 

new equipment purchased each year, multiplied by the shipments in the standards case. 

10.4.2.9 Present Value of Savings 

The present value of annual savings in operating cost is the difference between the base 

case and each standards case discounted to the present and summed throughout the period from 

the effective date, 2016, to the time when the last unit installed in 2046 is retired from service. 

Savings represent decreases in operating cost (including electricity, repair, and 

maintenance) associated with the more energy efficient equipment purchased in each standards 

case compared to the base case. Total annual savings in operating cost are the savings per unit 

multiplied by the number of units of each vintage that survive in a particular year. For units 

purchased in 2046, energy consumption continues until the unit is retired from service. 

10.5 RESULTS OF CALCULATIONS 

The National Impacts Analysis (NIA) model estimates the national energy savings 

(NES), the regional energy savings (RES), and the net present value (NPV) attributable to each 

candidate standards level. DOE generated the NES, RES, and NPV results using a Microsoft 

Excel spreadsheet, which is accessible on the Internet at: 

(http://www1.eere.energy.gov/buildings/appliance_standards/residential/central_ac_hp.html). 

Details and instructions for using the spreadsheet are provided in appendix 10-A. 

10.5.1 Summary of Inputs 

Table 10.5.1 summarizes the inputs to the NIA model. The inputs were discussed in 

sections 10.3.2 (inputs for NES and RES) and 10.4.2 (inputs for the national and regional NPV). 

A brief description of the data source or each input also is provided in Table 10.5.1. 

10-66 

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Table 10.5.1 Inputs to Calculations 

Input Data Description 

Shipments Annual shipments from shipments model (chapter 9). 

Effective date of standard 2016. 

Forecasted efficiencies for base 

case 

SWEF* determined in the year 2016 for each product class. Growth trend 

applied to SWEF throughout forecast period, 2016–2046 (section 10.2). 

Efficiencies for standards case Growth trends applied to determine SWEF for each standards case and each 

product class for 2016–2046 (section 10.2). 

Annual energy consumption per 

unit 

Annual weighted-average values are a function of SWEF (section 10.3.2.1). 

Total installed cost per unit Annual weighted-average values are a function of SWEF (section 10.4.2.1). 

Energy cost per unit Annual weighted-average values are a function of annual energy consumption 

per unit and energy prices. (See section 8.2.3.1 of chapter 8 for energy prices.) 

Repair and maintenance costs 

per unit 

Annual weighted-average values are a function of SWEF (section 10.4.2.3). 

Increase in energy prices EIA AEO 2009 forecasts (to 2030) and extrapolation to 2046. (See section 

8.2.3.2 of chapter 8.) 

Energy site-to-source conversion Conversion factor, which changes yearly, is generated by DOE/EIA’s NEMS† 

program as a time-series factor that includes electric generation, transmission, 

and distribution losses. 

Discount rate Seven percent real. 

Present year Future expenses are discounted to 2009. 

* SWEF = shipments-weighted energy factor (efficiency).

† NEMS = National Energy Modeling System. Chapter 13 , Utility Impact Analysis, and the Environmental 

Assessment Report [Give reference]provide more detail on NEMS. 

10.5.2 National and Regional Energy Savings 

The following sections provide the national energy savings (NES) and regional energy 

savings (RES) that DOE calculated for each of the candidate standard levels (CSLs) analyzed for 

all four product classes of central air conditioners and heat pumps. Results, which are cumulative 

to 2046, are shown as primary energy savings. DOE based the inputs to the NIA model on 

weighted-average values, producing results that are discrete point values, rather than a 

distribution of values such as is generated by the life-cycle cost and payback period analyses. 

10.5.2.1 Central Air Conditioners 

This section provides NES and RES results for the efficiency levels considered for the 

two product classes of central air conditioners (split system and single package). 

Central Air Conditioners—Split System 

Tables 10.5.2 through 10.5.4 show the energy savings for the CSLs analyzed for split 

system CACs for the Nation as a whole and for each of the three climate regions evaluated 

separately (the hot-humid, hot-dry, and rest of the Nation). Table 10.5.2 shows the results for the 

residential sector only, Table 10.5.3 shows the results for the commercial sector only, and Table 

10.5.4 shows the results for both sectors. Each table shows the breakdown of energy savings for 

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coil-only units and blower coil units. Figure 10.5.1 depicts the total national and regional energy 

savings for each CSL. 

Table 10.5.2	 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Residential Sector (quads) 

CSL SEER 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 0.19 0.17 0.02 0.08 0.08 0.01 0.03 0.03 0.00 0.05 0.05 0.00 

2 14.0 0.77 0.71 0.07 0.35 0.32 0.03 0.12 0.11 0.01 0.22 0.20 0.02 

3 14.5 1.36 1.24 0.12 0.62 0.56 0.05 0.22 0.20 0.02 0.38 0.35 0.03 

4 15.0 1.94 1.77 0.17 0.88 0.80 0.08 0.31 0.28 0.03 0.55 0.50 0.05 

5 15.5 2.51 2.29 0.22 1.14 1.04 0.10 0.40 0.37 0.03 0.71 0.65 0.06 

6 16.0 3.03 2.77 0.26 1.37 1.26 0.12 0.49 0.44 0.04 0.86 0.78 0.07 

7 16.5 3.30 2.99 0.31 1.50 1.36 0.14 0.53 0.48 0.05 0.93 0.85 0.09 

8 17.0 3.35 0.36 1.52 0.16 0.54 0.06 0.94 0.10 

9 18.0 3.45 0.45 1.56 0.20 0.55 0.07 0.97 0.13 

10 19.0 3.54 0.55 1.60 0.25 0.57 0.09 1.00 0.15 

11 20.0 3.63 0.63 1.64 0.29 0.58 0.10 1.02 0.18 

12 21.0 3.70 0.71 1.68 0.32 0.59 0.11 1.04 0.20 

13 22.0 3.74 0.75 1.70 0.34 0.60 0.12 1.05 0.21 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

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Table 10.5.3 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Commercial Sector (quads) 

CSL SEER 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 0.01 0.01 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

2 14.0 0.05 0.05 0.00 0.02 0.02 0.00 0.01 0.01 0.00 0.02 0.02 0.00 

3 14.5 0.09 0.09 0.01 0.03 0.03 0.00 0.02 0.02 0.00 0.04 0.04 0.00 

4 15.0 0.14 0.13 0.01 0.05 0.04 0.00 0.03 0.02 0.00 0.06 0.06 0.00 

5 15.5 0.18 0.16 0.01 0.06 0.06 0.00 0.03 0.03 0.00 0.08 0.07 0.01 

6 16.0 0.20 0.18 0.01 0.07 0.06 0.01 0.04 0.03 0.00 0.09 0.08 0.01 

7 16.5 0.20 0.19 0.02 0.07 0.07 0.01 0.04 0.04 0.00 0.09 0.08 0.01 

8 17.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01 

9 18.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01 

10 19.0 0.21 0.02 0.07 0.01 0.04 0.00 0.09 0.01 

11 20.0 0.21 0.02 0.08 0.01 0.04 0.00 0.09 0.01 

12 21.0 0.22 0.03 0.08 0.01 0.04 0.01 0.10 0.01 

13 22.0 0.22 0.03 0.08 0.01 0.04 0.01 0.10 0.01 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

Table 10.5.4	 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 for the Residential and Commercial Sectors 

(quads) 

CSL SEER 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 0.20 0.18 0.02 0.09 0.08 0.01 0.03 0.03 0.00 0.06 0.05 0.00 

2 14.0 0.82 0.75 0.07 0.37 0.34 0.03 0.13 0.12 0.01 0.24 0.22 0.02 

3 14.5 1.46 1.33 0.12 0.65 0.59 0.06 0.24 0.22 0.02 0.43 0.39 0.04 

4 15.0 2.08 1.90 0.18 0.93 0.85 0.08 0.34 0.31 0.03 0.61 0.56 0.05 

5 15.5 2.69 2.46 0.23 1.20 1.10 0.10 0.44 0.40 0.04 0.79 0.72 0.07 

6 16.0 3.23 2.95 0.28 1.44 1.32 0.12 0.52 0.48 0.04 0.95 0.87 0.08 

7 16.5 3.51 3.18 0.33 1.57 1.43 0.15 0.57 0.52 0.05 1.02 0.93 0.09 

8 17.0 3.56 0.37 1.59 0.17 0.57 0.06 1.04 0.11 

9 18.0 3.65 0.47 1.64 0.21 0.59 0.08 1.06 0.13 

10 19.0 3.75 0.57 1.68 0.25 0.61 0.09 1.09 0.16 

11 20.0 3.84 0.66 1.72 0.30 0.62 0.11 1.12 0.19 

12 21.0 3.92 0.74 1.76 0.33 0.63 0.12 1.14 0.21 

13 22.0 3.96 0.78 1.78 0.35 0.64 0.12 1.15 0.22 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

** Total NES for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

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0.0 

0.5 

1.0 

1.5 

2.0 

2.5 

3.0 

3.5 

4.0 

1 2 3 4 5 6 7 8 9 10 11 12 13 

Candidate Standard Level 

National or Regional Energy Savings (quads) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.1	 Split System Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 (quads) 

Central Air Conditioners—Single Package 

Table 10.5.5 shows the energy savings for the CSLs analyzed for single package CACs 

for the Nation as a whole and for each of the three climate regions that were evaluated separately 

(the hot-humid, hot-dry, and rest of the Nation). Total energy savings in Table 10.5.5 are also 

broken down by sector (i.e., residential and commercial). Figure 10.5.2 depicts the total national 

and regional energy savings for each CSL. 

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Table 10.5.5 Single Package Central Air Conditioners: Cumulative National and Regional 

Energy Savings from 2016-2046 (quads) 

CSL SEER 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 0.08 0.08 0.00 0.04 0.04 0.00 0.01 0.01 0.00 0.02 0.02 0.00 

2 14.0 0.15 0.14 0.01 0.07 0.07 0.00 0.02 0.02 0.00 0.04 0.04 0.00 

3 14.5 0.24 0.22 0.02 0.11 0.11 0.01 0.04 0.04 0.00 0.07 0.06 0.01 

4 15.0 0.30 0.28 0.02 0.14 0.13 0.01 0.05 0.05 0.00 0.09 0.08 0.01 

5 15.5 0.36 0.34 0.02 0.17 0.16 0.01 0.06 0.05 0.00 0.11 0.10 0.01 

6 16.0 0.41 0.39 0.02 0.19 0.18 0.01 0.07 0.06 0.00 0.12 0.11 0.01 

7 16.6 0.43 0.41 0.03 0.20 0.19 0.01 0.07 0.07 0.00 0.13 0.12 0.01 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

0.45 

1 2 3 4 5 6 7 

Candidate Standard Level 

National or Regional Energy Savings (quads) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.2 Single Package Central Air Conditioners: Cumulative National and 

Regional Energy Savings from 2016-2046 (quads) 

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10.5.2.2 Heat Pumps 

This section provides NES and RES results for the efficiency levels considered for the 

two product classes of heat pumps (split system and single package). 

Heat Pumps—Split System 

Table 10.5.6 shows the energy savings for the CSLs analyzed for split system HPs for the 

Nation as a whole and for each of the three climate regions that were evaluated separately (the 

hot-humid, hot-dry, and rest of the Nation). Total energy savings in Table 10.5.6 are also broken 

down by sector (i.e., residential and commercial). Figure 10.5.3 depicts the total national and 

regional energy savings for each CSL. 

Table 10.5.6	 Split System Heat Pumps: Cumulative National and Regional Energy 

Savings from 2016-2046 (quads) 

CSL SEER HSPF 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 0.11 0.10 0.00 0.07 0.06 0.00 0.01 0.01 0.00 0.03 0.03 0.00 

2 14.0 8.00 0.56 0.54 0.02 0.34 0.33 0.01 0.07 0.06 0.00 0.15 0.14 0.01 

3 14.5 8.15 1.03 1.00 0.03 0.63 0.61 0.02 0.12 0.11 0.00 0.28 0.27 0.01 

4 15.0 8.30 1.53 1.48 0.05 0.93 0.90 0.03 0.18 0.17 0.01 0.42 0.40 0.02 

5 15.5 8.45 2.09 2.03 0.06 1.26 1.23 0.03 0.24 0.23 0.01 0.58 0.56 0.02 

6 16.0 8.60 2.78 2.71 0.07 1.66 1.62 0.04 0.31 0.30 0.01 0.79 0.77 0.02 

7 17.0 9.10 3.93 3.84 0.09 2.94 2.28 0.05 0.44 0.42 0.01 1.15 1.12 0.03 

8 18.0 9.60 4.98 4.88 0.10 3.36 2.88 0.06 0.55 0.54 0.01 1.47 1.44 0.03 

9 19.0 10.10 5.68 5.57 0.11 3.41 3.29 0.06 0.63 0.61 0.02 1.68 1.65 0.03 

10 19.5 10.30 5.78 5.67 0.11 2.94 3.35 0.06 0.64 0.62 0.02 1.71 1.68 0.03 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

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0.0 

1.0 

2.0 

3.0 

4.0 

5.0 

6.0 

1 2 3 4 5 6 7 8 9 10 

Candidate Standard Level 

National or Regional Energy Savings (quads) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.3	 Split System Heat Pumps: Cumulative National and Regional Energy 

Savings from 2016-2046 (quads) 

Heat Pumps—Single Package 

Table 10.5.7 shows the energy savings for the CSLs analyzed for single package HPs for 

the Nation as a whole and for each of the three climate regions that were evaluated separately 

(the hot-humid, hot-dry, and rest of the Nation). Total energy savings in Table 10.5.7 are also 

broken down by sector (i.e., residential and commercial). Figure 10.5.4 depicts the total national 

and regional energy savings for each CSL. 

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Table 10.5.7 Single Package Heat Pumps: Cumulative National and Regional Energy 

Savings from 2016-2046 (quads) 

CSL SEER HSPF 

Nation* Hot-Humid Hot-Dry Rest of Country 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 0.04 0.04 0.00 0.02 0.02 0.00 0.00 0.00 0.00 0.01 0.01 0.00 

2 14.0 8.00 0.10 0.10 0.00 0.06 0.06 0.00 0.01 0.01 0.00 0.03 0.02 0.00 

3 14.5 8.00 0.19 0.19 0.01 0.12 0.12 0.00 0.02 0.02 0.00 0.05 0.05 0.00 

4 15.0 8.00 0.28 0.27 0.01 0.17 0.17 0.00 0.03 0.03 0.00 0.08 0.08 0.00 

5 15.5 8.50 0.36 0.35 0.01 0.22 0.21 0.01 0.04 0.04 0.00 0.11 0.11 0.00 

6 16.0 9.00 0.41 0.40 0.01 0.25 0.24 0.01 0.05 0.04 0.00 0.12 0.12 0.00 

7 16.4 9.00 0.43 0.41 0.01 0.26 0.25 0.01 0.05 0.05 0.00 0.12 0.12 0.00 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NES. 

0.00 

0.05 

0.10 

0.15 

0.20 

0.25 

0.30 

0.35 

0.40 

0.45 

1 2 3 4 5 6 7 

Candidate Standard Level 

National or Regional Energy Savings (quads) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.4	 Single Package Heat Pumps: Cumulative National and Regional Energy 

Savings from 2016-2046 (quads) 

10.5.3 Calculating Annual Cost and Savings 

To illustrate the basic inputs to the calculations of net present value (NPV) of costs and 

savings attributable to proposed standards for central air conditioners and heat pumps, Figure 

10.5.5 shows the non-discounted annual increases in installed cost and annual savings in 

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EERE-2008-BT-STD-0006 COMMENT 54
operating cost at the national level for CSL 2 for split system coil-only CACs. The figure also 

shows net savings, which is the difference between the savings and costs for each year. The 

annual total installed cost is the increase in the total installed cost for products purchased each 

year for 2016–2046. The annual savings in operating cost applies to products that are operating 

in each year. The NPV is the difference between the cumulative annual discounted savings and 

the cumulative annual discounted cost. DOE could create figures like the one below for every 

standards case for all four product classes of CACs and heat pumps. 

-0.4 

-0.3 

-0.2 

-0.1 

0.0 

0.1 

0.2 

2016 2020 2024 2028 2032 2036 2040 2044 2048 2052 2056 2060 2064 2068 2072 2076 2080 

Year 

Billion of 2008 Dollars 

Total Installed Cost Increase 

Operating Cost Savings 

Net Savings 

Figure 10.5.5 Non-Discounted Annual Increases in Installed Cost and Savings in 

Operating Cost for Split System Coil-Only Central Air Conditioners, 

Candidate Standard Level 2 

10.5.4 Net Present Values 

The following sections provide results of calculating the net present value (NPV) for each 

candidate standard level considered for the four product classes of central air conditioners and 

heat pumps (split systems and packaged systems). Results were calculated for the nation as a 

whole and for each of the three climate regions that were evaluated separately (the hot-humid, 

hot-dry, and rest of the Nation). Results, which are cumulative, are shown as the discounted 

dollar value of the savings. DOE based the inputs to the NIA model on weighted-average values, 

yielding results that are discrete point values, rather than a distribution of values such as 

produced by the life-cycle cost and payback period analyses. 

The present value of increased total installed cost is the total annual increase (the 

difference between the standards case and base case) discounted to the present and summed 

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EERE-2008-BT-STD-0006 COMMENT 54
 

throughout the period for which DOE evaluates the effect of standards (from the effective date of 

standards, 2016, to 2046). 

Savings derive from decreases in operating costs related to the energy consumption 

associated with the higher energy efficiency of equipment purchased in the standards case 

compared to the base case. Total savings in operating costs are the savings per unit multiplied by 

the number of units of each vintage (i.e., the year of manufacture) that survive in a particular 

year. Equipment consumes energy and must be maintained throughout its lifetime. For units 

purchased through 2046, the operating cost includes energy consumed until the last unit is retired 

from service. 

10.5.4.1 Central Air Conditioners 

The following sections provide the results of calculating net present value (NPV) based 

on a discount rate of seven percent for the candidate standard levels DOE analyzed for the two 

product classes of central air conditioners, split system and single package. Results are 

cumulative to 2046. 

Central Air Conditioners—Split System 

Tables 10.5.8 through 10.5.10 show the NPVs at a three percent real discount rate for the 

CSLs analyzed for split system CACs for the Nation as a whole and for each of the three climate 

regions evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Table 10.5.8 shows 

the results for the residential sector only, Table 10.5.9shows the results for the commercial sector 

only, and Table 10.5.10 shows the results for both sectors. Each table shows the breakdown of 

the NPV for coil-only units and blower coil units. Figure 10.5.6 depicts the total national and 

regional NPVs for each CSL. 

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Table 10.5.8	 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Residential Sector (3% 

Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.65 -0.65 0.00 0.10 0.08 0.02 -0.01 -0.02 0.01 -0.86 -0.81 -0.05 

2 14.0 -3.65 -3.63 -0.01 0.19 0.09 0.10 -0.23 -0.27 0.04 -4.07 -3.87 -0.20 

3 14.5 -8.33 -8.29 -0.04 -0.18 -0.34 0.16 -0.79 -0.86 0.07 -8.16 -7.80 -0.36 

4 15.0 -15.13 -15.04 -0.09 -1.11 -1.33 0.22 -1.79 -1.88 0.09 -13.32 -12.78 -0.54 

5 15.5 -24.15 -23.95 -0.20 -2.67 -2.94 0.27 -3.24 -3.35 0.10 -19.55 -18.82 -0.74 

6 16.0 -34.13 -33.78 -0.35 -4.61 -4.91 0.30 -4.94 -5.04 0.10 -26.06 -25.10 -0.96 

7 16.5 -39.83 -39.27 -0.57 -5.78 -6.09 0.31 -5.91 -6.00 0.09 -29.70 -28.49 -1.21 

8 17.0 -40.10 -0.84 -5.78 0.31 -5.93 0.06 -29.97 -1.48 

9 18.0 -40.86 -1.59 -5.84 0.25 -6.02 -0.03 -30.64 -2.15 

10 19.0 -41.91 -2.64 -5.98 0.11 -6.18 -0.18 -31.45 -2.96 

11 20.0 -43.25 -3.98 -6.21 -0.12 -6.39 -0.39 -32.40 -3.91 

12 21.0 -44.77 -5.50 -6.50 -0.41 -6.65 -0.65 -33.41 -4.92 

13 22.0 -45.56 -6.30 -6.67 -0.57 -6.79 -0.79 -33.91 -5.42 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

Table 10.5.9	 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Commercial Sector (3% 

Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.11 -0.11 0.00 -0.02 -0.02 0.00 -0.03 -0.03 0.00 -0.06 -0.06 0.00 

2 14.0 -0.49 -0.47 -0.02 -0.09 -0.09 0.00 -0.14 -0.14 -0.01 -0.28 -0.27 -0.01 

3 14.5 -0.99 -0.96 -0.03 -0.19 -0.19 0.00 -0.28 -0.27 -0.01 -0.55 -0.53 -0.02 

4 15.0 -1.73 -1.68 -0.06 -0.37 -0.36 -0.01 -0.47 -0.45 -0.02 -0.95 -0.92 -0.03 

5 15.5 -2.73 -2.64 -0.09 -0.62 -0.60 -0.01 -0.70 -0.67 -0.03 -1.49 -1.43 -0.05 

6 16.0 -3.89 -3.76 -0.14 -0.92 -0.90 -0.02 -0.96 -0.92 -0.04 -2.10 -2.02 -0.08 

7 16.5 -4.60 -4.40 -0.20 -1.11 -1.07 -0.04 -1.10 -1.05 -0.05 -2.48 -2.37 -0.11 

8 17.0 -4.66 -0.26 -1.13 -0.06 -1.12 -0.07 -2.51 -0.15 

9 18.0 -4.81 -0.40 -1.17 -0.09 -1.15 -0.10 -2.59 -0.23 

10 19.0 -4.98 -0.57 -1.21 -0.14 -1.19 -0.14 -2.69 -0.32 

11 20.0 -5.17 -0.76 -1.26 -0.18 -1.23 -0.18 -2.79 -0.42 

12 21.0 -5.36 -0.96 -1.31 -0.24 -1.27 -0.22 -2.90 -0.53 

13 22.0 -5.46 -1.05 -1.33 -0.26 -1.29 -0.24 -2.95 -0.58 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

10-77 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

Table 10.5.10 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Residential and Commercial 

Sectors (3% Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.76 -0.76 0.00 0.08 0.06 0.02 -0.04 -0.05 0.01 -0.93 -0.88 -0.05 

2 14.0 -4.14 -4.11 -0.03 0.10 0.00 0.10 -0.37 -0.41 0.03 -4.35 -4.14 -0.21 

3 14.5 -9.32 -9.25 -0.07 -0.37 -0.53 0.16 -1.07 -1.13 0.06 -8.71 -8.33 -0.38 

4 15.0 -16.86 -16.71 -0.15 -1.48 -1.69 0.22 -2.25 -2.33 0.07 -14.27 -13.70 -0.57 

5 15.5 -26.88 -26.59 -0.29 -3.28 -3.54 0.26 -3.95 -4.02 0.07 -21.04 -20.25 -0.79 

6 16.0 -38.02 -37.53 -0.49 -5.54 -5.81 0.27 -5.89 -5.95 0.06 -28.16 -27.13 -1.04 

7 16.5 -44.43 -43.67 -0.76 -6.89 -7.17 0.27 -7.01 -7.05 0.04 -32.18 -30.86 -1.32 

8 17.0 -44.77 -1.09 -6.91 0.25 -7.05 0.00 -32.48 -1.63 

9 18.0 -45.67 -1.99 -7.01 0.16 -7.17 -0.12 -33.23 -2.37 

10 19.0 -46.89 -3.22 -7.19 -0.03 -7.36 -0.31 -34.14 -3.28 

11 20.0 -48.41 -4.74 -7.47 -0.30 -7.62 -0.57 -35.19 -4.33 

12 21.0 -50.13 -6.46 -7.81 -0.64 -7.92 -0.87 -36.30 -5.44 

13 22.0 -51.02 -7.35 -8.00 -0.83 -8.08 -1.03 -36.86 -6.00 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

10-78 

EERE-2008-BT-STD-0006 COMMENT 54
-50 

-45 

-40 

-35 

-30 

-25 

-20 

-15 

-10 

-5 

0 

5 

1 2 3 4 5 6 7 8 9 10 11 12 13 

Candidate Standard Level 

National and Regional NPV (billion 2008$)

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.6	 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (3% discount rate) 

Tables 10.5.11 through 10.5.13 show the NPVs at a seven percent real discount rate for 

the CSLs analyzed for split system CACs for the Nation as a whole and for each of the three 

climate regions evaluated separately (the hot-humid, hot-dry, and rest of the Nation). Table 

10.5.11 shows the results for the residential sector only, Table 10.5.12 shows the results for the 

commercial sector only, and Table 10.5.13 shows the results for both sectors. Each table shows 

the breakdown of the NPV for coil-only units and blower coil units. Figure 10.5.7 depicts the 

total national and regional NPVs for each CSL. 

10-79 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Table 10.5.11 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Residential Sector (7% 

Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.37 -0.36 -0.01 0.00 -0.01 0.00 -0.03 -0.03 0.00 -0.39 -0.36 -0.02 

2 14.0 -1.95 -1.88 -0.07 -0.11 -0.13 0.02 -0.20 -0.20 0.00 -1.81 -1.71 -0.10 

3 14.5 -4.26 -4.13 -0.12 -0.42 -0.45 0.03 -0.51 -0.52 0.00 -3.61 -3.42 -0.18 

4 15.0 -7.46 -7.28 -0.18 -0.98 -1.01 0.04 -1.02 -1.02 0.00 -5.85 -5.58 -0.27 

5 15.5 -11.81 -11.55 -0.26 -1.85 -1.89 0.04 -1.75 -1.75 0.00 -8.67 -8.30 -0.36 

6 16.0 -17.06 -16.69 -0.37 -3.00 -3.03 0.04 -2.67 -2.66 -0.01 -11.88 -11.42 -0.46 

7 16.5 -20.51 -20.02 -0.50 -3.78 -3.81 0.02 -3.29 -3.26 -0.03 -13.96 -13.38 -0.58 

8 17.0 -20.67 -0.65 -3.80 0.01 -3.31 -0.05 -14.08 -0.70 

9 18.0 -21.07 -1.05 -3.86 -0.06 -3.37 -0.10 -14.38 -1.01 

10 19.0 -21.60 -1.58 -3.96 -0.15 -3.45 -0.19 -14.75 -1.37 

11 20.0 -22.25 -2.23 -4.09 -0.28 -3.56 -0.30 -15.17 -1.79 

12 21.0 -22.99 -2.97 -4.25 -0.45 -3.69 -0.43 -15.63 -2.25 

13 22.0 -23.45 -3.44 -4.36 -0.55 -3.78 -0.51 -15.91 -2.53 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

Table 10.5.12 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Commercial Sector (7% 

Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.06 -0.05 0.00 -0.01 -0.01 0.00 -0.01 -0.01 0.00 -0.03 -0.03 0.00 

2 14.0 -0.25 -0.24 -0.01 -0.06 -0.05 0.00 -0.06 -0.06 0.00 -0.14 -0.13 -0.01 

3 14.5 -0.49 -0.47 -0.02 -0.11 -0.11 0.00 -0.13 -0.12 -0.01 -0.26 -0.25 -0.01 

4 15.0 -0.81 -0.78 -0.03 -0.19 -0.19 -0.01 -0.20 -0.19 -0.01 -0.44 -0.42 -0.02 

5 15.5 -1.25 -1.21 -0.05 -0.31 -0.30 -0.01 -0.30 -0.29 -0.01 -0.67 -0.64 -0.03 

6 16.0 -1.81 -1.75 -0.07 -0.46 -0.45 -0.01 -0.43 -0.41 -0.02 -0.96 -0.93 -0.04 

7 16.5 -2.21 -2.12 -0.09 -0.57 -0.55 -0.02 -0.51 -0.49 -0.02 -1.17 -1.12 -0.05 

8 17.0 -2.24 -0.12 -0.58 -0.03 -0.51 -0.03 -1.19 -0.06 

9 18.0 -2.30 -0.18 -0.59 -0.05 -0.53 -0.04 -1.22 -0.10 

10 19.0 -2.38 -0.26 -0.61 -0.06 -0.54 -0.06 -1.26 -0.14 

11 20.0 -2.46 -0.34 -0.64 -0.09 -0.56 -0.08 -1.30 -0.18 

12 21.0 -2.55 -0.43 -0.66 -0.11 -0.58 -0.09 -1.35 -0.23 

13 22.0 -2.60 -0.48 -0.67 -0.12 -0.59 -0.11 -1.38 -0.26 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

10-80 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Table 10.5.13 Split System Central Air Conditioners: Discounted Cumulative National and 

Regional NPV Results from 2016-2046 for the Residential and Commercial 

Sectors (7% Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil Total** 

CoilOnly Blower 

Coil 

1 13.5 -0.43 -0.41 -0.02 -0.01 -0.02 0.00 -0.04 -0.04 0.00 -0.42 -0.39 -0.03 

2 14.0 -2.20 -2.12 -0.08 -0.17 -0.18 0.01 -0.26 -0.26 0.00 -1.95 -1.84 -0.11 

3 14.5 -4.74 -4.60 -0.14 -0.53 -0.56 0.02 -0.64 -0.64 0.00 -3.87 -3.67 -0.20 

4 15.0 -8.27 -8.06 -0.21 -1.17 -1.20 0.03 -1.22 -1.21 -0.01 -6.29 -6.00 -0.29 

5 15.5 -13.06 -12.75 -0.31 -2.16 -2.19 0.03 -2.05 -2.04 -0.01 -9.33 -8.95 -0.39 

6 16.0 -18.87 -18.44 -0.43 -3.46 -3.48 0.02 -3.10 -3.07 -0.03 -12.85 -12.35 -0.50 

7 16.5 -22.73 -22.14 -0.59 -4.35 -4.36 0.00 -3.80 -3.75 -0.05 -15.13 -14.50 -0.63 

8 17.0 -22.91 -0.77 -4.38 -0.02 -3.82 -0.07 -15.27 -0.77 

9 18.0 -23.37 -1.24 -4.46 -0.10 -3.89 -0.15 -15.60 -1.11 

10 19.0 -23.98 -1.84 -4.57 -0.22 -4.00 -0.25 -16.01 -1.51 

11 20.0 -24.71 -2.57 -4.73 -0.37 -4.12 -0.38 -16.47 -1.98 

12 21.0 -25.53 -3.40 -4.91 -0.56 -4.27 -0.52 -16.98 -2.48 

13 22.0 -26.05 -3.91 -5.03 -0.68 -4.37 -0.62 -17.29 -2.79 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

** Total NPV for 17 through 22 SEER reflects the Coil-Only energy savings at 16.5 SEER. 

10-81 

EERE-2008-BT-STD-0006 COMMENT 54
-30 

-25 

-20 

-15 

-10 

-5 

0 

1 2 3 4 5 6 7 8 9 10 11 12 13 

Candidate Standard Level 

National and Regional NPV (billion 2008$)

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.7	 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (7% discount rate) 

Central Air Conditioners—Single Package 

Table 10.5.14 shows the NPVs at a three percent real discount rate for the CSLs analyzed 

for single package CACs for the Nation as a whole and for each of the three climate regions that 

were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 

10.5.14 are also broken down by sector (i.e., residential and commercial). Figure 10.5.8 depicts 

the total national and regional NPVs for each CSL. 

10-82 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 10.5.14 Single Package Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 (3% Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 -0.62 -0.55 -0.07 -0.03 -0.02 -0.02 -0.07 -0.06 -0.02 -0.54 -0.50 -0.04 

2 14.0 -1.26 -1.12 -0.13 -0.10 -0.07 -0.03 -0.16 -0.13 -0.03 -1.05 -0.98 -0.07 

3 14.5 -2.32 -2.09 -0.23 -0.25 -0.20 -0.05 -0.32 -0.27 -0.06 -1.82 -1.69 -0.13 

4 15.0 -3.31 -2.98 -0.33 -0.42 -0.35 -0.08 -0.49 -0.41 -0.08 -2.49 -2.31 -0.18 

5 15.5 -4.53 -4.08 -0.45 -0.66 -0.56 -0.11 -0.70 -0.59 -0.11 -3.27 -3.03 -0.24 

6 16.0 -5.67 -5.11 -0.56 -0.91 -0.77 -0.14 -0.90 -0.77 -0.13 -3.97 -3.67 -0.30 

7 16.6 -6.37 -5.74 -0.63 -1.07 -0.91 -0.16 -1.02 -0.88 -0.15 -4.39 -4.05 -0.34 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

-7 

-6 

-5 

-4 

-3 

-2 

-1 

0 

1 2 3 4 5 6 7 

Candidate Standard Level 

National and Regional NPV (billion 2008$)

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.8	 Single Package Central Air Conditioners: Cumulative National and 

Regional NPV from 2016-2046 (3% discount rate) 

Table 10.5.15 shows the NPVs at a seven percent real discount rate for the CSLs 

analyzed for single package CACs for the Nation as a whole and for each of the three climate 

regions that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in 

Table 10.5.14 are also broken down by sector (i.e., residential and commercial). Figure 10.5.9 

depicts the total national and regional NPVs for each CSL. 

10-83 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 10.5.15 Single Package Central Air Conditioners: Discounted Cumulative National 

and Regional NPV Results from 2016-2046 (7% Discount Rate) 

CSL SEER 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 -0.33 -0.29 -0.04 -0.04 -0.03 -0.01 -0.05 -0.04 -0.01 -0.25 -0.23 -0.02 

2 14.0 -0.65 -0.58 -0.07 -0.09 -0.08 -0.02 -0.09 -0.08 -0.02 -0.47 -0.44 -0.04 

3 14.5 -1.15 -1.04 -0.11 -0.19 -0.16 -0.03 -0.18 -0.15 -0.03 -0.82 -0.76 -0.06 

4 15.0 -1.62 -1.46 -0.15 -0.28 -0.24 -0.04 -0.26 -0.22 -0.04 -1.11 -1.03 -0.08 

5 15.5 -2.21 -2.01 -0.21 -0.41 -0.36 -0.05 -0.36 -0.31 -0.05 -1.47 -1.36 -0.11 

6 16.0 -2.83 -2.57 -0.27 -0.56 -0.49 -0.07 -0.47 -0.41 -0.06 -1.83 -1.69 -0.14 

7 16.6 -3.27 -2.96 -0.31 -0.66 -0.58 -0.08 -0.55 -0.48 -0.07 -2.08 -1.92 -0.16 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

-3.5 

-3.0 

-2.5 

-2.0 

-1.5 

-1.0 

-0.5 

0.0 

1 2 3 4 5 6 7 

Candidate Standard Level 

National and Regional NPV (billion 2008$)

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.9 Split System Central Air Conditioners: Cumulative National and Regional 

NPV from 2016-2046 (7% discount rate) 

10-84 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

10.5.4.2 Heat Pumps 

The following sections provide the results of calculating net present value (NPV) based 

on a discount rate of seven percent for the candidate standard levels DOE analyzed for the two 

product classes of heat pumps, split system and single package. Results are cumulative to 2046. 

Heat Pumps—Split System 

Table 10.5.16 shows the NPVs at a three percent real discount rate for the CSLs analyzed 

for split system HPs for the Nation as a whole and for each of the three climate regions that were 

evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 10.5.16 are 

also broken down by sector (i.e., residential and commercial). Figure 10.5.10 depicts the total 

national and regional NPVs for each CSL. 

Table 10.5.16 Split System Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (3% Discount Rate) 

CSL SEER HSPF 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 0.34 0.37 -0.03 0.30 0.31 -0.01 0.09 0.09 -0.01 0.01 0.02 -0.01 

2 14.0 8.00 1.73 1.88 -0.15 1.55 1.60 -0.04 0.44 0.47 -0.03 0.05 0.12 -0.06 

3 14.5 8.15 3.12 3.40 -0.28 2.82 2.90 -0.08 0.81 0.86 -0.06 0.09 0.21 -0.12 

4 15.0 8.30 4.31 4.78 -0.47 4.01 4.16 -0.14 1.15 1.24 -0.09 0.06 0.26 -0.20 

5 15.5 8.45 5.28 6.04 -0.76 5.14 5.39 -0.25 1.47 1.61 -0.14 -0.05 0.26 -0.31 

6 16.0 8.60 6.27 7.45 -1.19 6.35 6.77 -0.42 1.81 2.03 -0.22 -0.19 0.29 -0.48 

7 17.0 9.10 7.12 9.14 -2.03 7.94 8.69 -0.75 2.27 2.62 -0.35 -0.63 0.18 -0.81 

8 18.0 9.60 6.07 9.00 -2.93 8.49 9.60 -1.11 2.46 2.96 -0.50 -1.64 -0.48 -1.16 

9 19.0 10.10 4.17 7.74 -3.57 8.21 9.58 -1.37 2.44 3.04 -0.60 -2.71 -1.30 -1.40 

10 19.5 10.30 3.70 7.37 -3.67 8.07 9.48 -1.41 2.41 3.02 -0.61 -2.94 -1.50 -1.44 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

10-85 

EERE-2008-BT-STD-0006 COMMENT 54
-3 

-2 

-1 

0 

1 

2 

3 

4 

5 

6 

7 

8 

9 

1 2 3 4 5 6 7 8 9 10 

Candidate Standard Level 

National and Regional NPV (billion 2008$) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.10 Split System Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (3% discount rate) 

Table 10.5.17 shows the NPVs at a seven percent real discount rate for the CSLs 

analyzed for split system HPs for the Nation as a whole and for each of the three climate regions 

that were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 

10.5.17 are also broken down by sector (i.e., residential and commercial). Figure 10.5.11 depicts 

the total national and regional NPVs for each CSL. 

10-86 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

Table 10.5.17 Split System Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (7% Discount Rate) 

CSL SEER HSPF 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 0.06 0.08 -0.02 0.08 0.08 -0.01 0.02 0.03 0.00 -0.02 -0.01 -0.01 

2 14.0 8.00 0.32 0.40 -0.08 0.39 0.42 -0.03 0.13 0.14 -0.02 -0.08 -0.05 -0.03 

3 14.5 8.15 0.57 0.72 -0.15 0.72 0.77 -0.05 0.23 0.26 -0.03 -0.16 -0.10 -0.06 

4 15.0 8.30 0.68 0.92 -0.24 0.97 1.06 -0.08 0.32 0.36 -0.04 -0.27 -0.18 -0.09 

5 15.5 8.45 0.61 0.98 -0.36 1.15 1.28 -0.13 0.38 0.45 -0.06 -0.45 -0.30 -0.14 

6 16.0 8.60 0.44 0.99 -0.55 1.30 1.51 -0.21 0.44 0.54 -0.10 -0.67 -0.45 -0.22 

7 17.0 9.10 -0.08 0.85 -0.92 1.41 1.78 -0.37 0.51 0.66 -0.15 -1.08 -0.72 -0.36 

8 18.0 9.60 -1.35 -0.02 -1.33 1.12 1.66 -0.53 0.47 0.69 -0.22 -1.73 -1.21 -0.51 

9 19.0 10.10 -2.92 -1.26 -1.66 0.59 1.26 -0.68 0.37 0.63 -0.27 -2.42 -1.78 -0.64 

10 19.5 10.30 -3.32 -1.60 -1.72 0.43 1.13 -0.70 0.33 0.61 -0.28 -2.59 -1.93 -0.66 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

-4 

-3 

-2 

-1 

0 

1 

2 

1 2 3 4 5 6 7 8 9 10 

Candidate Standard Level 

National and Regional NPV (billion 2008$) 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Figure 10.5.11 Split System Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (7% discount rate) 

10-87 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

Heat Humps—Single Package 

Table 10.5.18 shows the NPVs at a three percent real discount rate for the CSLs analyzed 

for single package HPs for the Nation as a whole and for each of the three climate regions that 

were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 

10.5.18 are also broken down by sector (i.e., residential and commercial). Figure 10.5.12 depicts 

the total national and regional NPVs for each CSL. 

Table 10.5.18 Single Package Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (3% Discount Rate) 

CSL SEER HSPF 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 -0.05 -0.02 -0.03 0.03 0.04 -0.01 0.01 0.01 0.00 -0.05 -0.04 -0.01 

2 14.0 8.00 -0.22 -0.14 -0.08 0.03 0.06 -0.03 0.01 0.03 -0.01 -0.16 -0.13 -0.03 

3 14.5 8.00 -0.58 -0.42 -0.16 -0.04 0.03 -0.06 0.00 0.03 -0.03 -0.35 -0.29 -0.06 

4 15.0 8.00 -0.94 -0.70 -0.24 -0.13 -0.03 -0.10 -0.02 0.02 -0.04 -0.51 -0.42 -0.09 

5 15.5 8.50 -1.35 -1.02 -0.33 -0.27 -0.14 -0.13 -0.05 0.00 -0.05 -0.67 -0.55 -0.12 

6 16.0 9.00 -1.86 -1.46 -0.40 -0.47 -0.31 -0.16 -0.10 -0.03 -0.07 -0.87 -0.72 -0.15 

7 16.4 9.00 -2.16 -1.73 -0.43 -0.60 -0.42 -0.18 -0.13 -0.06 -0.07 -0.99 -0.83 -0.16 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

10-88 

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National and Regional NPV (billion 2008$)

0.5 

0.0 

-0.5 

-1.0 

-1.5 

-2.0 

-2.5 

1 2 3 4 5 6 7 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

Candidate Standard Level 

Figure 10.5.12 Single Package Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (3% discount rate) 

Table 10.5.19 shows the NPVs at a three percent real discount rate for the CSLs analyzed 

for single package HPs for the Nation as a whole and for each of the three climate regions that 

were evaluated separately (the hot-humid, hot-dry, and rest of the Nation). NPVs in Table 

10.5.19 are also broken down by sector (i.e., residential and commercial). Figure 10.5.13 depicts 

the total national and regional NPVs for each CSL. 

Table 10.5.19 Single Package Heat Pumps: Discounted Cumulative National and Regional 

NPV Results from 2016-2046 (7% Discount Rate) 

CSL SEER HSPF 

Nation* (bill. 2008$) Hot-Humid (bill. 2008$) Hot-Dry (bill. 2008$) Rest of Cntry (2008$) 

Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. Total Resid. Comm. 

1 13.5 7.85 -0.05 -0.03 -0.01 -0.01 0.00 -0.01 0.00 0.00 0.00 -0.03 -0.02 0.00 

2 14.0 8.00 -0.18 -0.14 -0.04 -0.04 -0.03 -0.02 -0.01 0.00 -0.01 -0.09 -0.08 -0.01 

3 14.5 8.00 -0.42 -0.35 -0.08 -0.12 -0.09 -0.03 -0.02 -0.01 -0.01 -0.20 -0.17 -0.03 

4 15.0 8.00 -0.63 -0.52 -0.11 -0.20 -0.15 -0.05 -0.04 -0.02 -0.02 -0.29 -0.25 -0.04 

5 15.5 8.50 -0.87 -0.72 -0.15 -0.30 -0.23 -0.06 -0.06 -0.04 -0.02 -0.37 -0.31 -0.06 

6 16.0 9.00 -1.18 -0.99 -0.19 -0.43 -0.35 -0.08 -0.09 -0.06 -0.03 -0.48 -0.41 -0.07 

7 16.4 9.00 -1.38 -1.16 -0.21 -0.52 -0.43 -0.09 -0.11 -0.08 -0.03 -0.56 -0.48 -0.08 

* Reflects analysis conducted at national level. Regional values do not necessarily add up to national NPV. 

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EERE-2008-BT-STD-0006 COMMENT 54
National and Regional NPV (billion 2008$)

0.0 

-0.5 

-1.0 

-1.5 

Nation 

Hot-Humid 

Hot-Dry 

Rest-of-Country 

1 2 3 4 5 6 7 

Candidate Standard Level 

Figure 10.5.13 Single Package Heat Pumps: Cumulative National and Regional NPV from 

2016-2046 (7% discount rate) 

10-90 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

REFERENCES 

1	 Air-Conditioning, Heating and Refrigerator Institute. Historical shipments and shipmentweighted efficiency data submittal. December 2008. 

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

2009 with Projections to 2030. March 2009. U.S. DOE–EIA: Washington, D.C. DOE/EIA0383(2009). <http://www.eia.doe.gov/oiaf/aeo/pdf/0383(2009).pdf> 

3	 Office of Management and Budget. OMB Circular A-4, Regulatory Analysis. 2003. OMB: 

Washington, D.C. September 17, 2003. 

<www.whitehouse.gov/omb/assets/omb/circulars/a004/a-4.pdf> 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 11. LIFE-CYCLE COST SUBGROUP ANALYSIS 

TABLE OF CONTENTS
 

11.1 INTRODUCTION ............................................................................................................ 11-1
 

11.2 GENERAL APPROACH.................................................................................................. 11-1
 

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CHAPTER 11. LIFE-CYCLE COST SUBGROUP ANALYSIS 

11.1 INTRODUCTION 

The life-cycle cost (LCC) subgroup analysis evaluates impacts on any identifiable groups 

or customers who may be disproportionately affected by any national energy efficiency standard 

level. The U.S. Department of Energy (DOE) will conduct this analysis as one of the analyses for 

the notice of proposed rulemaking. DOE will accomplish this, in part, by analyzing the LCC and 

payback periods (PBPs) for those customers that fall into any identifiable groups. DOE plans to 

evaluate variations in regional energy prices and variations in energy use that might affect the net 

present value of a standard to customer subpopulations. To the extent possible, DOE will obtain 

estimates of each input parameter’s variability and will consider this variability in its calculation 

of customer impacts. DOE plans to perform sensitivity analyses to consider how differences in 

energy use will affect subgroups of customers. 

DOE will determine the impact on customer subgroups using the LCC spreadsheet 

model, which allows for different data inputs. The standard life-cycle cost and payback period 

analysis (described in the preliminary Technical Support Document (TSD) chapter 8) focuses on 

residential and light commercial consumers that use residential central air conditioners and heat 

pumps (CACs). DOE can use the LCC spreadsheet model to analyze the LCC for any subgroup 

by sampling only that subgroup. Model inputs used by the Department to determine LCC and 

PBPs are described in detail in the life-cycle cost and payback period analysis (see TSD chapter 

8). 

In the case of CACs, some possible consumer subgroups include low income consumers, 

households headed by older persons, and small businesses. 

11.2 GENERAL APPROACH 

For CACs, DOE estimates LCC savings and PBPs for consumers in the residential and 

light commercial sectors at the regional level. 

DOE will use the LCC spreadsheet model to evaluate impacts on consumer subgroups, 

especially low-income and small-business consumers. DOE can analyze the LCC for any 

subgroup by applying the LCC spreadsheet model to only that subgroup within individual 

regions. DOE is particularly sensitive to increases in the consumer price of the considered 

products, wishing to avoid a negative economic impact on any identified consumer subgroup 

with limited capacity to absorb price increases. The impacts on subgroups will be compared to 

impacts on the overall population. 

In the LCC subgroup analysis, DOE will examine a variety of consumer sub-populations. 

This analysis will determine whether any particular group of consumers would be adversely 

affected. 

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CHAPTER 12: PRELIMINARY MANUFACTURER IMPACT ANALYSIS 

TABLE OF CONTENTS 

12.1 INTRODUCTION .........................................................................................................12-1
 

12.2 METHODOLOGY ........................................................................................................12-1
 

12.2.1 Phase 1: Industry Profile.................................................................................... 12-2
 

12.2.2 Phase 2: Industry Cash-Flow Analysis and Interview Guide ............................ 12-2
 

12.2.3 Phase 3: Subgroup Analysis............................................................................... 12-2
 

12.3 PRELIMINARY MANUFACTURER IMPACT ANALYSIS RESULTS...................12-4
 

12.3.1 Industry Overview ............................................................................................. 12-5
 

12.3.2 Interview Topics and Preliminary Findings....................................................... 12-7
 

12.3.3 Overall Key Issues ........................................................................................... 12-10
 

LIST OF TABLES 

Table 12.3.1 Central Air Conditioner and Heat Pump Industry Employment and Earnings.... 12-5
 

Table 12.3.2 Central Air Conditioner and Heat Pump Industry Material and Payroll Costs .... 12-5
 

Table 12.3.3 Central Air Conditioner and Heat Pump Industry End-of-Year Inventory .......... 12-6
 

Table 12.3.4 Full Production Capacity Utilization Rates .......................................................... 12-6
 

Table 12.3.5 Central Air Conditioner and Heat Pump Industry Year 2007 Data as a Percentage of 

Revenue ............................................................................................................................ 12-7
 

Table 12.3.6 Other 2007 Financials........................................................................................... 12-7
 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

CHAPTER 12: PRELIMINARY MANUFACTURER IMPACT ANALYSIS
 

12.1 INTRODUCTION 

The purpose of the manufacturer impact analysis (MIA) is to identify and quantify the 

likely impacts of amended energy conservation standards on manufacturers. In the Notice of 

Proposed Rulemaking (NOPR) stage of analysis, the U.S. Department of Energy (DOE) 

considers a wide range of quantitative and qualitative industry impacts that might occur due to an 

amended energy conservation standard. For example, a particular standard level could require 

changes in manufacturing practices. DOE identifies and analyzes these impacts during the NOPR 

stage. To the extent that it is appropriate for this rulemaking, DOE applies this methodology to 

evaluate amended energy conservation standards for central air conditioners and heat pumps. 

DOE announced changes to the MIA format through a report issued to Congress on 

January 31, 2006 (as required by section 141 of the Energy Policy Act of 2005 (EPACT 2005), 

entitled “Energy Conservation Standards Activities.”1

 Previously, DOE did not report any MIA 

results until the notice of proposed rulemaking stage (NOPR). However, under this new format, 

DOE collects, evaluates, and reports preliminary information and data in the preliminary 

analysis. Such preliminary information includes efficiency and market data, key issues, 

production mixes, conversion costs, foreign competition, market shares, industry consolidation, 

and cumulative regulatory information. DOE solicited this information during the preliminary 

manufacturer interviews and reports the results in this chapter. Appendix 12A includes a copy of 

the interview guide that DOE distributed to manufacturers. 

12.2 METHODOLOGY 

DOE conducts the MIA in three phases. In Phase 1, DOE creates an industry profile to 

characterize the industry and conducts a preliminary MIA to identify important issues that 

require consideration. Section 12.3 of this chapter presents initial findings of the Phase 1 

analysis. In Phase 2, DOE prepares an industry cash flow model and an interview questionnaire 

to guide subsequent discussions with manufacturers. In Phase 3, DOE interviews manufacturers 

and assesses the impacts of amended energy conservation standards both quantitatively and 

qualitatively. DOE assesses industry and subgroup cash flow impacts and industry net present 

value (INPV) using the Government Regulatory Impact Model (GRIM). DOE then assesses 

impacts on competition, manufacturing capacity, employment, and regulatory burden based on 

manufacturer interviews and discussions. DOE will conduct Phase 2 and 3 for the NOPR stage of 

the rulemaking. 

1

 This report is available on the DOE website at 

www.eere.energy.gov/buildings/appliance_standards/2006_schedule_setting.html. 

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12.2.1 Phase 1: Industry Profile 

In Phase 1 of the MIA, DOE collects pertinent qualitative and quantitative financial and 

market information. This includes wages, employment, industry cost data, and capacity 

utilization rates for manufacturers of central air conditioners and heat pumps. Sources of 

information include reports published by industry groups, trade journals, the U.S. Census 

Bureau, and Securities Exchange Commission (SEC) 10-K filings. In addition, DOE relies on 

information from its market and technology assessment, engineering analysis, life-cycle cost 

analysis, and consumer price analysis to characterize the central air conditioner and heat pump 

manufacturing industry. 

12.2.2 Phase 2: Industry Cash-Flow Analysis and Interview Guide 

In Phase 2, DOE performs a preliminary industry cash-flow analysis and prepares written 

guidelines for interviewing manufacturers. 

12.2.2.1 Industry Cash-Flow Analysis 

DOE uses the GRIM to analyze the financial impacts of amended energy conservation 

standards. Amended energy conservation standards may require additional investment, increase 

production costs, and affect revenue through higher prices and possibly lower shipments. The 

GRIM uses several factors to determine a series of annual cash flows for the year that amended 

energy conservation standards become effective and for several years after implementation. 

These factors include annual expected revenues, costs of sales, selling and general administration 

costs, taxes, and capital expenditures. Inputs to the GRIM include financial information, 

manufacturing costs, shipment forecasts, and price forecasts developed in other analyses. The 

financial information is developed from publicly available data and confidentially submitted 

manufacturer information. DOE compares the results of the GRIM against baseline projections 

in which no amended energy conservation standards are in place. The financial impact of 

amended energy conservation standards is the difference between the two sets of discounted 

annual cash flows. 

12.2.2.2 Interview Guide 

DOE conducts interviews with 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, which occur in Phase 3, DOE 

distributes an interview guide to help identify the impacts of amended energy conservation 

standards on individual manufacturers or subgroups of manufacturers. Interview guide topics 

include: production costs; shipment projections and market share; product mix; conversion 

costs; markups and profitability; assessment of the impact on competition, manufacturing 

capacity, and other topics that are relevant to assessing the impacts of amended energy 

conservation standards on the central air conditioner and heat pump industry. 

12.2.3 Phase 3: Subgroup Analysis 

Phase 3 activities take place after publication of the preliminary analysis notice of public 

meeting. These activities include manufacturer interviews; revision of the industry cash-flow 

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analysis; a manufacturer subgroup analysis; an assessment of the impacts on industry 

competition, manufacturing capacity, direct employment and the cumulative regulatory burden; 

and other qualitative impacts. 

12.2.3.1 Manufacturer Interviews 

DOE conducts detailed interviews with manufacturers to gain insight into the potential 

impacts of amended energy conservation standards on sales, direct employment, capital assets, 

and industry competitiveness. Interviews are scheduled well in advance to provide every 

opportunity for key individuals to be available for comment. Although a written response to the 

questionnaire is acceptable, DOE prefers interactive interviews, which help clarify responses and 

provide the opportunity to identify additional issues not specifically addressed in the interview 

questionnaire. A non-disclosure agreement allows confidential or sensitive information to be 

considered in DOE’s decision-making process. However, confidential information will not be 

made available in the public record. At most, sensitive or confidential information may be 

aggregated and presented in industry-wide representations. 

DOE supplements the information gathered in Phase 1 and the cash flow analysis 

performed in Phase 2 with information gathered during manufacturer interviews. The interview 

process is critical to the MIA because it provides an opportunity for interested parties to privately 

express their views on important issues. 

12.2.3.2 Revised Industry Cash-Flow Analysis 

During the interviews, DOE requests information about profitability impacts, necessary 

plant changes, and other manufacturing impacts. Following the interview process, DOE revises 

its industry cash flow model based on the feedback it receives. 

12.2.3.3 Manufacturer Subgroup Analysis 

Using average cost assumptions to develop an industry cash flow estimate will not 

adequately assess differential impacts among manufacturer subgroups. Smaller manufacturers, 

niche players, and manufacturers exhibiting a cost structure that differs largely from the industry 

average could be more negatively affected. Ideally, DOE would consider the impact on every 

firm individually; however, it typically uses the results of the industry characterization to group 

manufacturers with similar characteristics. During the interviews, DOE discusses the potential 

subgroups that have been identified for the analysis. DOE asks manufacturers and other 

interested parties to suggest what subgroups or characteristics are most appropriate for the 

analysis. 

12.2.3.4 Competitive Impact Assessment 

Section 342 (6)(B)(i)(V) of the Energy Policy Act of 1992 (EPCA) directs DOE to 

consider any lessening of competition likely to result from imposition of standards. EPCA 

further directs the U.S. Attorney General to determine the impacts, if any, of any decrease in 

competition. DOE attempts to gather and report firm-specific financial information and impacts. 

The competitive impact assessment will be based on manufacturer cost data and information 

collected from interviews. The interviews will focus on assessing asymmetrical cost increases to 

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some manufacturers, the potential increase in business risks from an increased proportion of 

fixed costs, and potential barriers to market entry (e.g., proprietary technologies). The 

competitive analysis will also focus on assessing any differential impacts to smaller 

manufacturers. 

12.2.3.5 Manufacturing Capacity Impact 

One of the significant outcomes of amended energy conservation standards can be the 

obsolescence of existing manufacturing assets, including tooling and other investments. The 

manufacturer interview guide will have a series of questions to help identify impacts on 

manufacturing capacity, specifically capacity utilization and plant location decisions in North 

America with and without amended energy conservation standards; the ability of manufacturers 

to upgrade or remodel existing facilities to accommodate the new requirements; the nature and 

value of stranded assets, if any; and estimates for any one-time restructuring or other charges, 

where applicable. 

12.2.3.6 Employment Impact 

The impact of amended energy conservation standards on employment is an important 

consideration in the rulemaking process. To assess how domestic employment patterns might be 

affected, the interview will explore current employment trends in the central air conditioner and 

heat pump industry and solicit manufacturer views on changes in employment patterns that may 

result from increased standard levels. The employment impacts section of the interview guide 

will focus on current employment levels at production facilities; expected future employment 

levels with and without an amended energy conservation standard; differences in workforce 

skills; and employee retraining. 

12.2.3.7 Cumulative Regulatory Burden 

DOE seeks to mitigate the overlapping effects on manufacturers due to energy 

conservation standards and other regulatory actions. If possible, DOE will consider the impact 

on manufacturers of multiple, product-specific regulatory actions. 

12.3 PRELIMINARY MANUFACTURER IMPACT ANALYSIS RESULTS 

For the preliminary analysis, DOE conducted a preliminary evaluation of the impact of 

potential amended energy conservation standards on the central air conditioning and heat pump 

industry. A primary focus was to identify the cumulative burden that the industry faces from the 

overlapping effect of new or recent DOE energy conservation standards and/or other regulatory 

action affecting the same equipment or industry. 

The primary source of information for this analysis was interviews with manufacturers of 

central air conditioning and heat pump products, conducted during the spring of 2009. To 

maintain confidentiality, DOE only reports aggregated information here. DOE does not disclose 

company-specific information, nor does it identify the individual manufacturers that disclosed 

information. 

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12.3.1 Industry Overview 

The following section summarizes publicly available industry data. 

12.3.1.1 Industry Cost Structure 

DOE developed the central air conditioner and heat pump industry cost structure from the 

U.S. Census Bureau, Annual Survey of Manufacturers, Statistics for Industry Groups and 

Industries from 2002-2007. Residential Central Air Conditioner and Heat Pump manufacturing 

is classified under the North American Industry Classification System (NAICS) code 333415 

(AC, Refrigeration, and Forced Air Heating). 

Table 12.3.1 presents the central air conditioner and heat pump employment levels and 

earnings from 2002 to 2007. The statistics illustrate approximately an 8-percent decrease in the 

number of production workers and in the overall number of employees from 2002 to 2007. 

Table 12.3.1 Employment and Earnings for the Central Air Conditioner and Heat Pump 

Industry 

Year Production Workers All Employees Annual Payroll 

(thousand $) 

2002 80,400 108,252 3,815,129 

2003 77,471 104,646 3,775,799 

2004 73,559 99,669 3,707,969 

2005 76,011 102,354 3,942,808 

2006 74,909 98,097 4,019,813 

2007 73,993 100,284 3,975,785 

Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007 

Table 12.3.2 presents the costs of materials and industry payroll as a percentage of 

shipment value from 2002 to 2007. The cost of materials as a percentage of shipment value has 

steadily increased from 2002 to 2007. The cost of payroll for production workers and the cost of 

total payroll have declined by 17.3 percent and 16.1 percent, respectively. 

Table 12.3.2 Material and Payroll Costs for the Central Air Conditioner and Heat Pump 

Industry 

Year Cost of Materials 

(percent of shipment value) 

Cost of Payroll 

for Production Workers 

(percent of shipment value) 

Cost of Total Payroll 

(percent of shipment value) 

2002 49.36 9.83 15.85 

2003 50.59 9.53 15.39 

2004 51.81 8.99 14.57 

2005 53.78 8.52 13.78 

2006 53.17 8.87 13.80 

2007 55.52 8.12 13.29 

Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007 

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12.3.1.2 Inventory Levels 

Table 12.3.3 shows the end-of-year inventory for the central air conditioner and heat 

pump industry obtained from the U.S. Census Bureau, Annual Survey of Manufacturers, 

Statistics for Industry Groups and Industries from 2002 to 2007. The end-of-year inventory is 

defined as the The industry’s end-of-year inventory from 2002 to 2007 experienced an overall 

increase when expressed both in dollars and as a percentage of shipment value. 

Table 12.3.3 End-of-Year Inventory for the Central Air Conditioner and Heat Pump 

Industry 

Year End-of-Year Inventory 

(thousand $) 

End-of-Year Inventory 

(percent of shipment value) 

2002 2,302,012 9.57 

2003 2,376,827 9.69 

2004 2,473,932 9.72 

2005 2,687,441 9.39 

2006 2,887,139 9.91 

2007 3,011,358 10.07 

Source: U.S. Census Bureau. Annual Survey of Manufacturers, 2002-2007 

DOE obtained full production capacity utilization rates from the U.S. Census Bureau, 

“Current Industrial Reports,” Survey of Plant Capacity from 2002 to 2006. Table 12.3.4 presents 

production capacity utilization rates for NAICS code 333415. Full production capacity is defined 

as the maximum level of production an establishment could attain under normal operating 

conditions. In the Survey of Plant Capacity report, the full production utilization rate is a ratio of 

the actual level of operations to the full production level. 

Table 12.3.4 Full Production Capacity Utilization Rates for the Central Air Conditioner 

and Heat Pump Industry 

Year AC and Warm Air Heating and Commercial/Industrial Refrigeration 

Equipment Manufacturing (%) 

2002 60 

2003 62 

2004 60 

2005 66 

2006 63 

Source: U.S. Census Bureau. 2007 Current Industrial Reports: Table 1a - Full Production Capacity Utilization 

Rates by Industry: Fourth Quarters 2002 through 2006. November 2007 

12.3.1.3 Other Industry Data 

Table 12.3.5 shows various 2007 statistics for the central air conditioner and heat pump 

industry, as taken from Standard and Poor Annual Reports and manufacturer 10-K reports. 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 12.3.5 2007 Financial Data as a Percentage of Revenue for the Central Air 

Conditioner and Heat Pump Industry 

Measure Amount as a Percentage of Revenue 

Property, Plant, & Equipment, Net 20.0% 

Depreciation 1.7% 

R&D 2.5% 

Capex 2.2% 

Selling, General & Admin. Expense 13.2% 

Working Capital 6.6% 

Current Assets 34.0% 

EBIT 6.8% 

Source: Standard & Poor Annual Reports, 10Ks 

Table 12.3.6 presents the 2007 central air conditioner and heat pump industry data 

detailing the industry tax rate, real weighted average cost of capital, and manufacturer markup. 

The manufacturer markup is a factor that raises the manufacturer production cost (MPC) to the 

manufacturer selling price (MSP). It accounts for non-production costs such as SG&A, R&D, as 

well as profit. 

Table 12.3.6 Other 2007 Financials 

Tax Rate as a % of Earnings before Tax 26.4% 

Real WACC 10.3% 

Markup 1.32 

12.3.2 Interview Topics and Preliminary Findings 

The following section summarizes information gathered during interviews held during 

the first and second quarters of 2009 for the preliminary MIA. 

12.3.2.1 Market Shares and Industry Consolidation 

Amended energy conservation standards can alter the competitive dynamics of the 

marketplace, prompting companies to enter the market, exit the market, or merge with other 

companies. During preliminary MIA interviews, manufacturers were asked to share their 

perspectives on industry consolidation both in the absence of amended energy conservation 

standards and assuming amended standards at various efficiency levels. The need to assess anticompetitive effects of proposed amended energy conservation standards comes from the need to 

protect consumer interests. The interview questions focused on gathering information that 

assessed: 

 disproportionate cost increases to some manufacturers; 

 increased proportion of fixed costs potentially increasing business risks; and 

 potential barriers to market entry (e.g., proprietary technologies). 

During the interviews, DOE solicited information to determine whether amended energy 

conservation standards could result in disproportionate economic or performance penalties for 

particular consumer or user subgroups. Manufacturers were also asked if amended energy 

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conservation standards could result in products that would be more or less desirable to 

consumers due to changes in product functionality, utility, or other features. 

Market Shares: DOE inquired about current market shares of manufacturers in the 

central air conditioning and heat pump industry. DOE also asked how manufacturers expect their 

market share to change after an amended energy conservation standard. One manufacturer said 

that, under a new standard, some of their competitors may elect to only participate in a certain 

product segment, which would lower their overall market share. According to this manufacturer, 

some companies may choose to exit some regions or product categories due to a lower return on 

investment under the amended standards when compared to a potentially smaller market that 

could result from higher prices after amended standards. Another manufacturer said that 

standards favor larger companies, and the market share of smaller firms would not increase. 

Other manufacturers said that they expect no significant change in market share due to the 

adoption of the new standard, and that they see this market as a relatively level playing field. 

Industry Consolidation: DOE inquired about the potential for industry consolidation in 

the manufacturer interviews. One manufacturer said that industry consolidation is likely even in 

the absence of amended standards because the industry is currently too small to support seven 

major manufacturers. Most manufacturers indicated that amended energy conservation standards 

could accelerate this trend. Some manufacturers said that, depending on the complexities of 

products required after the adoption of the amended energy conservation standard, there could be 

some consolidation. Manufacturers stated that a continued decline in shipments and a relatively 

high level of financing to comply with the amended standard would harm the industry. Large 

capital required to comply with the standard could harm manufacturers in part because this 

financing cannot be accounted for until the actual standard level is public. Finally, one 

manufacturer indicated that if industry shipments are reduced due to higher prices of standardscompliant products, the industry would require less overall capacity. A lower diminished 

capacity could come through plant consolidation or company consolidation, but which one is 

unclear. They also claim that the greatest threat of consolidation comes from Asian firms, which 

would be potentially interested in buying an American manufacturer for increased access to 

distribution channels. 

12.3.2.2 Production and Product Mix 

DOE requested manufacturers’ feedback on what they perceived to be the possible 

impact of energy conservation standards on profitability. For instance, the capital and product 

conversion outlays needed to upgrade or redesign products before they have reached the end of 

their useful life may create significant conversion costs, resulting in reduced cash flow and 

stranded investments. Higher energy conservation standards could also result in higher per-unit 

cost that could cause consumers to shift to less expensive products. 

Product Mix: Manufacturers indicated that amended energy conservation standards 

would affect the product mix of central air conditioners and heat pumps. According to 

manufacturers, a reasonable energy conservation standard for central air conditioners and heat 

pumps would still allow for cost-effective, premium-efficiency products to be developed. One 

manufacturer said that a high energy conservation standard could result in a change in their 

product mix such that they may only offer products at the energy conservation standard. For that 

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manufacturer, a high energy conservation standard might result in the loss of the opportunity to 

create up-sells, because consumers may not choose a slightly more efficient unit. This 

manufacturer said that a high energy conservation standard increases the chances of market 

entrants, as producing a full range of products takes significant capital expenditures and entrants 

could focus only on the baseline level. The manufacturer also said that a more limited range of 

product offerings would create a commoditized market, which would hurt their profitability. 

Product Utility: Certain manufacturers expressed concern that amended energy 

conservation standards might require changes in product functionality, utility, and other features 

that would make products less desirable to consumers. Some manufacturers were concerned 

about the product size increases that would be associated with higher energy conservation 

standards. Due to the complexity and potential large size of central air conditioners and heat 

pumps at higher efficiency levels, manufacturers are concerned that installations will be far more 

difficult and could force many consumers to pay substantially higher installed costs if their 

replacement unit does not fit into their existing space. 

12.3.2.3 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 describes other significant product-specific regulations that could affect 

central air conditioner and heat pump manufacturers or their parent companies. 

Based on its own research and discussions with manufacturers, DOE identified several 

regulations relevant to central air conditioners and heat pumps, including: 

 Phase-out of hydrochlorofluorocarbon (HCFC) refrigerants 

 DOE’s gas furnace rulemaking 

 Other DOE regulations 

Refrigerant: Due to the phase-out of HCFCs, the central air conditioning and heat pump 

industry must transition to non-ozone-depleting refrigerants. As a result, the industry is 

transitioning to hydrofluorocarbon-based (HFC-based) refrigerants in central air conditioners and 

heat pumps. Several manufacturers noted that the transition from HCFC R-22 to HFC R-410A 

has resulted in the complete redesign of all central air conditioners and heat pumps. Some 

manufacturers stated that some business was lost due to the refrigerant switch. In addition to the 

switch from R-22 to R-410A, a manufacturer expressed concern about existing legislative 

proposals that would eliminate the use of HFCs. It said that this would require additional 

significant redesigns. See section 12.3.3.1 for additional details. 

Other Appliance Standards: Several central air conditioning and furnace 

manufacturers also produce other appliances that have existing or upcoming DOE energy 

conservation standards rulemakings. Some of these other appliances include residential furnaces, 

furnace fans, and direct heating equipment. Manufacturers stated that if these standards 

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rulemakings for other appliances result in modifications to their product designs or product 

offerings, then they could result in additional cumulative regulatory burdens. 

Other Regulatory Concerns: Potential changes to the DOE test procedure are a major 

concern for manufacturers. Additionally, several manufacturers said that commercial standards 

affect their overall regulatory burden because of the switch to HFC R-410A refrigerant for those 

commercial products, potentially increasing its price. Another manufacturer expects the total 

impact of those other regulations to be higher product costs for customers, reduced profitability 

for manufacturers, and further reduced domestic manufacturing employment. 

12.3.3 Overall Key Issues 

Perhaps the most important aspect of the preliminary MIA is the opportunity it creates for 

DOE to identify key manufacturer issues early in the development of amended energy 

conservation standards. During preliminary interviews, manufacturers identified several major 

issues that are detailed in the following sections. 

12.3.3.1 Refrigerant Switch 

The EPA has mandated a phase-out of HCFC refrigerants (i.e., R-22) for use in new 

equipment in January 2010. DOE is basing its engineering analysis on HFC-based refrigerants 

that comply with the EPA phase-out of HCFCs. During interviews, manufacturers discussed the 

possible impact of these new refrigerants on their existing central air conditioners and heat pump 

designs. The switch from HCFC R-22 refrigerant to HFC R-410A refrigerant was a major 

concern. Manufacturers said that HFC refrigerants would be significantly more expensive after 

the refrigerant switch because there would be no other viable alternatives. In addition, 

manufacturers pointed out that with higher SEER requirements, more refrigerant is needed due to 

larger coil sizes. Because of the need for more HFC refrigerants at higher SEER ratings and the 

lack of alternatives, manufacturers stated that amended energy conservation standards could 

cause a dramatic increase in the price of R-410A refrigerant. Manufacturers also noted that any 

alternative refrigerants to R-410A are unknown, which raises potential issues with uncertainty in 

the design of future systems, the research and development required, and the questionable 

availability of the necessary refrigerants. 

12.3.3.2 Regional Standards 

Several manufacturers expressed concerns about the potential adoption of regional 

standards. Manufacturers indicated that distribution channels and shipping would become more 

complicated and costly with regional standards. Manufacturers stated said that regional standards 

could potentially lower sales and increase requirements for testing, rating, labeling, etc. Some 

manufacturers stated that regional standards may cause dealers to stop buying certain products in 

certain regions. 

Most manufacturers indicated that they would prefer a single national standard, because 

regional standards could become very complicated. One manufacturer said that if a regional 

standard were set, then only two regions should be used because the distribution complexity 

greatly increases for each additional region. This manufacturer was concerned about the five 

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regions that have been previously suggested. Manufacturers also stated that if regional standards 

are set, the regions should be identical to the regions used for furnaces, contiguous, and use the 

same rating method for each region. 

During the interviews, DOE asked manufacturers whether regional standards would 

cause them to exit certain markets. Manufacturers said that the decision to offer products in a 

region depends on the stringency of the standards, market size, and profitability of offering those 

specific products in the region. Manufacturers said that it is highly unlikely that all 

manufacturers would participate in all regions, even if prices stabilized at a higher level. Also, 

manufacturers stated that they may elect not to offer products in certain regions if regional 

standards resulted in a significant change from the baseline product. Manufacturers stated that if 

regional standards are effective in an area with low market share relative to the return on 

investment required to meet the amended standards, manufacturers would be more likely to exit 

that region. 

Several manufacturers stated that their working capital, overhead costs, and research and 

development costs would have to be higher under regional standards. They said that there is also 

the potential for distribution consolidation. Some manufacturers stated that regional standards 

could cause transportation costs to increase, as they pay shipping as part of their factory 

distribution expenses. Finally, manufacturers were concerned that enforcement of regional 

standards could be difficult, and asserted that building codes would have to be the enforcement 

vehicle. 

12.3.3.3 Product Repairs versus Product Replacement 

Several manufacturers noted that an amended energy conservation standard could cause a 

trend to repair central air conditioners and heat pumps rather than replace them. Higher prices of 

new products after the effective date of the amended standard may make the repair option 

relatively more attractive to consumers. Additionally, some manufacturers stated that lower 

income households would be more likely to repair failed units or substitute room air conditioners 

for central air conditioners or heat pumps. These manufacturers pointed to the results of the 

switch from the 10 SEER to the 13 SEER standard, which increased repairs relative to 

replacements and decreased shipments. 

12.3.3.4 Shipments 

Shipment projections can be a significant factor in determining the impacts of amended 

energy conservation standards. The interviews provide an opportunity for manufacturers to share 

information that can help DOE quantify the magnitude of any changes in shipments resulting 

from amended energy conservation standards. In response to DOE inquiries about the potential 

change in shipments under a more stringent energy conservation standard, several manufacturers 

believed shipments would decrease at higher standard levels. These manufacturers said that one 

example of a decline in shipments was shown by the switch to the 13 SEER standard in their 

industry from the previous standard. Manufacturers stated that 2009 shipments were down more 

than 50 percent from 2005. 

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Some manufacturers said that based on the effects seen from the previous standard, the 

sales of room air conditioners would increase as a substitute. One manufacturer pointed out that 

higher efficiency products require more material, and higher material demand raises raw material 

cost. This would in turn increase the cost of the consumer products. Following this logic, the 

manufacturer said that this increase in the central air conditioner and heat pump prices would 

dampen demand. 

12.3.3.5 Impact on Manufacturer Outlook 

DOE interviewed manufacturers about any potential change in outlook that could arise 

from the new standard. One manufacturer said that there is a significant risk with higher 

minimum efficiency standards coupled with potential regional standards. They also said that the 

higher the standards are and the more complex the distribution is, the less affordable the units 

will become. Another manufacturer said that their outlook would not change with higher 

standard levels; that the necessary technology is available; and that having time to adjust to the 

standard is their only main outlook concern. 

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CHAPTER 13. UTILITY IMPACT ANALYSIS 

TABLE OF CONTENTS
 

13.1 INTRODUCTION ......................................................................................................... 13-1 

13.2 METHODOLOGY ........................................................................................................ 13-2 

13.3 RESULTS ...................................................................................................................... 13-2 

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CHAPTER 13. UTILITY IMPACT ANALYSIS 

13.1 INTRODUCTION
 

The U.S. Department of Energy (DOE) will analyze specific effects of its proposed 

standard levels on the electric utility industry as part of the notice of proposed rulemaking 

analyses, using a variant of the DOE/Energy Information Administration (EIA)’s National 

Energy Modeling System (NEMS). The NEMS is a large, multi-sectoral, partial equilibrium 

model of the U.S. energy sector. EIA uses NEMS to produce the Annual Energy Outlook 

(AEO).

1

 NEMS produces a widely recognized baseline energy forecast for the United States, and 

this energy forecast is available in the public domain. DOE will use a variant known as NEMSBT to provide key inputs to the analysis.a 

The utility impact analysis will consist of a comparison between model results for the 

base case and for policy cases in which proposed standards are in place. The use of NEMS-BT 

for the utility analysis offers several advantages. As the official DOE energy forecasting model, 

NEMS relies on a set of assumptions that are transparent and have received wide exposure and 

commentary. NEMS-BT allows an estimate of the interactions between the various energy 

supply and demand sectors and the economy as a whole. The utility impact analysis will report 

the changes in installed capacity and generation, by fuel type, that result for each trial standard 

level, as well as changes in electricity and natural gas sales to the residential and commercial 

sectors. 

DOE plans to conduct the utility impact analysis as a policy deviation from the 2010 

version of the AEO (AEO2010),1

 applying the same basic set of assumptions. For example, the 

operating characteristics (e.g., energy conversion efficiency, emissions rates) of future electricity 

generating plants are as specified in the AEO2010 reference case. DOE also will explore 

deviations from some of the reference case assumptions, to represent alternative futures. Two 

alternative scenarios use the high and low economic growth cases. (The reference case 

corresponds to medium growth.) The high economic growth case assumes higher projected 

growth rates for population, labor force, and labor productivity, resulting in lower predicted 

inflation and interest rates relative to the reference case and higher overall aggregate economic 

growth. The opposite is true for the low growth case. 

a For more information on NEMS, please refer to the U.S. Department of Energy, Energy Information 

Administration documentation. A useful summary is National Energy Modeling System: An Overview 2000, 

DOE/EIA-0581(2000), March 2000. 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 the model 

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 NEMS-BRS. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

13.2 METHODOLOGY 

The electric utility impact analysis will consist of NEMS-BT forecasts for generation, 

installed capacity, sales, and prices. NEMS provides reference case load shapes for several end 

uses. The model uses predicted growth in demand for each end use to build up a projection of 

the total electric system load growth for each region, which it uses in turn to predict the 

necessary additions to capacity. NEMS-BT accounts for the implementation of efficiency 

standards by decrementing the appropriate reference case load shape. DOE will determine the 

size of the decrement using data for the per-unit energy savings developed in the life-cycle cost 

and payback period analysis (Chapter 8) and the forecast of shipments developed for the national 

impact analysis (Chapter 9). 

The predicted reduction in capacity additions is sensitive to the peak load impacts of the 

standard. DOE will investigate the need to adjust the hourly load profiles that include this end 

use in NEMS-BT. 

 Since the AEO2010 version of NEMS forecasts only to the year 2035, DOE must 

extrapolate results to 2045. DOE conducts an extrapolation to 2045 to be consistent with the 

analysis period being used by DOE in the national impact analysis (NIA). It will not be feasible 

to extend the forecast period of NEMS-BT for the purposes of this analysis, nor does EIA have 

an approved method for extrapolation of many outputs beyond 2035. While it might seem 

reasonable in general to make simple linear extrapolations of results, in practice this is not 

advisable because outputs could be contradictory. For example, changes in the fuel mix implied 

by extrapolations of those outputs could be inconsistent with the extrapolation of marginal 

emissions factors. An analysis of various trends sufficiently detailed to guarantee consistency is 

beyond the scope of this work and, in any case, would involve a great deal of uncertainty. 

Therefore, for all extrapolations beyond 2035 DOE intends to use simple replications of year 

2035 results; in this way results are guaranteed to be consistent. As with the AEO reference case 

in general, the implicit assumption is that the regulatory environment does not deviate from the 

current known situation during the extrapolation period. Only changes that have been announced 

with date-certain introduction are included in NEMS-BT. 

For petroleum products, EIA uses the average growth rate for the world oil price over the 

years 2010 to 2025, in combination with the refinery and distribution markups from the year 

2025, to determine the regional price forecasts. Similarly, EIA derives natural gas prices from an 

average growth rate figure in combination with regional price margins from the year 2025. 

13.3 RESULTS 

Results of the analysis will include changes in residential and commercial electricity 

sales, installed capacity and generation by fuel type for each trial standard level, in five-year 

increments extrapolated to the year 2045 

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1 

REFERENCES 

U.S. Department of Energy-Energy Information Administration. Annual Energy Outlook 

2010 with Projections to 2035, March, 2010. Washington, DC. DOE/EIA-0383(2010). 

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CHAPTER 14. EMPLOYMENT IMPACT ANALYSIS 

TABLE OF CONTENTS
 

14.1 INTRODUCTION ............................................................................................................ 14-1 

14.2 ASSUMPTIONS............................................................................................................... 14-1 

14.3 METHODOLOGY ........................................................................................................... 14-1 

REFERENCES .......................................................................................................................... 14-3 

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CHAPTER 14. EMPLOYMENT IMPACT ANALYSIS 

14.1 INTRODUCTION 

The Department of Energy (DOE) intends the employment impact analysis to estimate 

national job creation or job elimination resulting from possible new standards, due to reallocation 

of the associated expenditures for purchasing and operating equipment. DOE will conduct this 

analysis as one of the analyses for the notice of proposed rulemaking (NOPR). DOE will 

estimate national impacts on major sectors of the U.S. economy, using publicly available data 

and incorporating different energy price scenarios that it will carry out as part of the analysis for 

the NOPR. DOE will make all methods and documentation available for review. 

The imposition of standards can impact employment both directly and indirectly. Direct 

employment impacts are changes in the number of employees at the plants that produce the 

covered equipment, along with the affiliated distribution and service companies, resulting from 

the imposition of standards. DOE will evaluate direct employment impacts in its manufacturer 

impact analysis, as described in chapter 12. Indirect 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.. 

14.2 ASSUMPTIONS 

DOE expects new equipment standards to decrease energy consumption, and therefore to 

reduce expenditures for energy. The savings in energy expenditures may be spent on new 

investment and other items. The standards may increase the purchase price of equipment, 

including the retail price plus sales tax, and increase installation costs. 

Using an input-output model of the U.S. economy, this analysis seeks to estimate the 

year-to-year effect of these expenditure impacts on net economic output and employment. A 

simple model might involve reduced expenditures for energy and reallocation of that money 

toward other sectors in the economy. DOE intends the employment impact analysis to quantify 

the indirect employment impacts of these expenditure changes. It will evaluate direct 

employment impacts in the manufacturer impact analysis step of the process. 

14.3 METHODOLOGY 

DOE developed Impact of Sector Energy Technologies (ImSET), a model of the 

U.S. economy that focuses on sectors most relevant to industrial, commercial, and residential 

building energy use.1 ImSET is a special-purpose version of the U.S. Benchmark National I-O 

model designed to estimate the national employment and income effects of energy-saving 

technologies deployed by the DOE Office of Energy Efficiency and Renewable Energy. 

Compared with previous versions of the model used in earlier energy conservation rulemakings, 

the current version allows for more complete and automated analysis of the essential features of 

energy efficiency investments in buildings, industry, transportation, and the electric power 

sectors. 

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14 CAC_PreNOPR_TSD_EMPLOYMENT IMPACT ANALYSIS_2010-03-23.doc 

EERE-2008-BT-STD-0006 COMMENT 54
 

The ImSET model includes structural coefficients to characterize economic flows among 

the multiple sectors. ImSET’s national economic I-O structure is based on the 2002 Benchmark 

U.S. table,2

 which is specially aggregated to 187 sectors. The time step of the model is annual 

and the time scale of the model is 100 years (2001-2099). 

The ImSET model allows a great deal of flexibility for analyzing types of energy 

efficiency effects. For example, certain economic effects of energy efficiency improvements 

require an assessment of inter-industry purchases, which is handled in the model. Some energy 

efficiency investments will not only reduce the costs of energy in the economy but also the costs 

of labor and other goods and services, which is accommodated through a recalculation of the I-O 

structure in the model. Output from ImSET can be used to estimate changes in employment, 

industry output, and wage income in the overall U.S. economy resulting from changes in 

expenditures in the various sectors of the economy. 

The following is an example of how the employment impact analysis might track impacts 

from a standard for CACs. Depending on the design options considered, one possible outcome is 

that the standards for these CACs would reduce energy expenditures and increase equipment 

prices in the residential and commercial sectors. These expenditure changes may reduce energy 

sector employment and either reduce or increase employment in selected commercial sectors. At 

the same time, the standard may increase investment in the residential and commercial sector and 

employment in other sectors. DOE designed the employment impact analysis to estimate the 

annual net national employment impact of these types of expenditure flows. 

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EERE-2008-BT-STD-0006 COMMENT 54
REFERENCES 

1. Scott M.J., O.V. Livingston, J.M. Roop, R.W. Schultz, and P.J. Balducci. 2009. Impact of 

Sector Energy Technologies Model Description and User’s Guide. Pacific Northwest 

National Laboratory, Richland, WA. PNNL-18412, 

2. Stewart, RL, JB Stone, and ML Streitwieser. 2007. U.S. Benchmark Input-Output Accounts, 

2002. Survey of Current Business October 2007. Accessed March 11, 2009 at 

http://www.bea.gov/industry/index.htm#benchmark_io. 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 15. ENVIRONMENTAL ASSESSMENT FOR PROPOSED ENERGY
 

CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT
 

PUMPS
 

TABLE OF CONTENTS
 

15.1 INTRODUCTION ......................................................................................................... 15-1 

15.2 METHODOLOGY ........................................................................................................ 15-2 

15.2.1 Air Emissions ................................................................................................................. 15-2 

15.2.2 Monetization of Emission Reductions Benefits ............................................................. 15-5 

15.3 RESULTS ...................................................................................................................... 15-7 

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CHAPTER 15. ENVIRONMENTAL ASSESSMENT FOR PROPOSED ENERGY
 

CONSERVATION STANDARDS FOR CENTRAL AIR CONDITONERS AND HEAT
 

PUIMPS
 

15.1 INTRODUCTION 

The U.S. Department of Energy (DOE) will conduct an environmental assessment as part 

of the notice of proposed rulemaking. DOE will assess the impacts of proposed energy 

conservation standards for central air conditioners and heat pumps on certain environmental 

indicators using a variant of the Energy Information Administration (EIA)’s National Energy 

1 Modeling System (NEMS).a

 EIA uses NEMS to produce the Annual Energy Outlook (AEO). 

DOE will use a variant known as NEMS-BT to provide key inputs to the analysis, based on the 

2010 version of the AEO (AEO2010). Results of the environmental assessment will be similar to 

those provided in AEO2010. 

The intent of the environmental impact assessment is to fulfill requirements to properly 

quantify and consider the environmental effects of all new Federal rules. DOE intends the 

environmental assessment to provide emissions results to policymakers and other stakeholders, 

and to fulfill requirements that the environmental effects of all new Federal rules be properly 

quantified and considered. 

The primary environmental effects of energy conservation standards for central air 

conditioners and heat pumps would be reduced power plant emissions resulting from reduced 

consumption of electricity; there are also reduced household emissions from gas appliances. The 

environmental assessment considers three pollutants— sulfur dioxide (SO2), nitrogen oxides 

(NOx), and mercury (Hg)—as well as carbon emissions. The only form of carbon emissions 

tracked by NEMS-BT is carbon dioxide (CO2), so the carbon discussed in this report is in the 

form of CO2. For each of the trial standard levels, DOE will calculate power sector emissions 

using NEMS-BT, using additional external analysis as needed. 

DOE notes that the Clean Air Act requires the U.S. Environmental Protection Agency 

(EPA) to set National Ambient Air Quality Standards for the following six common air 

pollutants, also know as “criteria pollutants”: (1) ozone, (2) particulate matter (PM), (3) carbon 

monoxide (CO), (4) nitrogen dioxide, (5) SO2, and (6) lead.2

 None of the “criteria pollutants” 

not already considered (i.e., ozone, PM, CO, and lead) are driven significantly by either electric 

utility power plants or fuel-fired appliances. Therefore, DOE does not intend on addressing them 

in the environmental assessment. In the case of ozone and particulate matter, other pollutants are 

precursors to their formation and atmospheric conditions are the driver behind their formation. 

Also, SO2 and NOx are the primary precursors to ozone and PM, respectively, and will already 

a For more information on NEMS, please 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. 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 the model as 

NEMS-BT (BT is DOE’s Building Technologies Program). NEMS-BT was previously called NEMS-BRS. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

be addressed by the environmental assessment. In the case of CO, electric utilities and fuel-fired 

appliances are not significant sources. Finally, with regard to lead, industrial processes (not 

electric utilities), including primary and secondary lead smelters and battery manufacturers, are 

responsible for most of the lead emissions. 

15.2 METHODOLOGY 

DOE plans to conduct the utility impact analysis as a policy deviation from the 2010 

version of the AEO (AEO2010),1 applying the same basic set of assumptions. For example, the 

emissions characteristics of an electricity generating plant will be exactly those used in 

AEO2010. The NEMS reference case and alternative growth scenarios are as described in the 

utility impact analysis (see Chapter 13 of the preliminary technical support document). Below 

are descriptions of the air emissions that DOE will analyze in the environmental assessment. 

15.2.1 Air Emissions 

Carbon Dioxide (CO2) 

Carbon dioxide (CO2) is not a regulated or criteria pollutant, but it is of interest because 

of its classification as a greenhouse gas (GHG). GHGs trap the sun’s radiation inside the Earth’s 

atmosphere and either occur naturally in the atmosphere or result from human activities. 

Naturally occurring GHGs include water vapor, CO2, methane (CH4), nitrous oxide (N2O), and 

ozone (O3). Human activities, however, add to the levels of most of these naturally occurring 

gases. For example, CO2 is emitted to the atmosphere when solid waste, fossil fuels (oil, natural 

gas, and coal), wood, and wood products are burned. During the past 20 years, about threequarters of anthropogenic (i.e., human-made) CO2 emissions resulted from burning fossil fuels. 

Concentrations of CO2 in the atmosphere are naturally regulated by numerous processes, 

collectively known as the “carbon cycle.” The movement of carbon between the atmosphere and 

the land and oceans is dominated by natural processes, such as plant photosynthesis. While these 

natural processes can absorb some of the anthropogenic CO2 emissions produced each year, 

billions of metric tons are added to the atmosphere annually. In the U. S., CO2 emissions from 

both energy generation and industrial processes account for 84.6 percent of total U.S. GHG 

emissions. 

In the absence of any Federal emissions control regulation of power plant emissions of 

CO2, a DOE standard is likely to result in reductions of these emissions. The CO2 emission 

reductions likely to result from a standard will be estimated using NEMS-BT and national energy 

savings estimates drawn from the NIA spreadsheet model. The net benefit of the standard is the 

difference between emissions estimated by NEMS-BT at each standard level considered and the 

AEO Reference Case. NEMS-BT tracks CO2 emissions using a detailed module that provides 

results with broad coverage of all sectors and inclusion of interactive effects. 

Sulfur Dioxide (SO2) 

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DOE has preliminarily determined that SO2 emissions from affected Electric Generating 

Units (EGUs) are subject to nationwide and regional emissions cap and trading programs that are 

likely to eliminate the standards’ impact on SO2 emissions. The costs of meeting such emission 

cap requirements are reflected in the electricity prices and forecasts used in DOE’s analysis of 

the standards. Title IV of the Clean Air Act sets an annual emissions cap on SO2 for all affected 

EGUs. SO2emissions from 28 eastern States and the District of Columbia (DC) are also limited 

under the Clean Air Interstate Rule (CAIR, published in the Federal Register on May 12, 2005. 

70 FR 25162 (May 12, 2005)), which creates an allowance-based trading program that will 

gradually replace the Title IV program in those States and DC. (The recent legal history 

surrounding CAIR is discussed below.) The attainment of the emissions caps is flexible among 

EGUs and is enforced through the use of emissions allowances and tradable permits. Under 

existing EPA regulations, any excess SO2 emission 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. However, if the standard resulted 

in a permanent increase in the quantity of unused emission allowances, there would be an overall 

reduction in SO2 emissions from the standards. While there remains some uncertainty about the 

ultimate effects of efficiency standards on SO2 emissions covered by the existing cap and trade 

system, the NEMS-BT modeling system that DOE plans to use to forecast emissions reductions 

currently indicates that no physical reductions in power sector emissions would occur for SO2. 

Even if there is no significant reduction in the overall emissions of SO2 that results from 

the standard, there may still be some economic benefit from reduced demand for SO2 emission 

allowances that is not fully reflected in the cost savings experienced by individual consumers. 

Electricity savings that decrease the overall demand for SO2 emissions allowances could lower 

allowance prices and thereby result in some economic benefits for all electricity consumers, not 

just those that reduced their electricity use as a result of an efficiency standard. DOE does not 

plan to monetize this particular benefit because the effect on the allowance price from any single 

energy conservation standard is likely small and highly uncertain. 

Nitrogen Oxides (NOX) 

 Nitrogen oxides, or NOX, are the generic term for a group of highly reactive gases, all of 

which contain nitrogen and oxygen in varying amounts. Many of the nitrogen oxides are 

colorless and odorless. However, one common pollutant, nitrogen dioxide (NO2), along with 

particles in the air can often be seen as a reddish-brown layer over many urban areas. NO2 is the 

specific form of NOX reported in this document. NOX is one of the main ingredients involved in 

the formation of ground-level ozone, which can trigger serious respiratory problems. It can 

contribute to the formation of acid rain, and can impair visibility in areas such as national parks. 

NOX also contributes to the formation of fine particles that can impair human health.3 

Nitrogen oxides form when fossil fuel is burned at high temperatures, as in a combustion 

process. The primary manmade sources of NOX are motor vehicles, electric utilities, and other 

industrial, commercial, and residential sources that burn fossil fuels. NOX can also be formed 

naturally. Electric utilities account for about 22 percent of NOX emissions in the United States.3 

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EERE-2008-BT-STD-0006 COMMENT 54
NEMS-BT has an algorithm for estimating NOX emissions from power generation. The 

impact of these emissions, however, will be affected by the CAIR, which the Environmental 

Protection Agency (EPA) issued on May 12, 2005. CAIR will permanently cap emissions of 

NOX in 28 eastern states and the District of Columbia. 70 FR 25162 (May 12, 2005).. 

Much like SO2 emissions, a cap on NOX emissions means that energy conservation 

standards may have little or no physical effect on these emissions in the 28 eastern States and DC 

covered by CAIR. Although CAIR has been remanded to the EPA by the DC Circuit, it will 

remain in effect until it is replaced by a rule consistent with the Court’s July 11, 2008, opinion in 

North Carolina v. EPA. 531 F.3d 896 (DC Cir. 2008); see also North Carolina v. EPA, 550 F.3d 

1176 (DC Cir. 2008). Because all States covered by CAIR opted to reduce NOX emissions 

through participation in cap-and-trade programs for electric generating units, emissions from 

these sources are capped across the CAIR region. 

Standards may produce an environmental-related economic benefit in the form of lower 

prices for emissions allowance credits. .As with SO2 emissions, a cap on NOX emissions means 

that equipment efficiency standards may have no physical effect on these emissions in the 28 

eastern States and DC covered by CAIR. While the emissions cap may mean that physical 

emissions reductions will not result from standards in those states covered by CAIR, standards 

could produce an environmental-related economic benefit in the form of lower prices for 

emissions allowance credits. 

As with SO2 allowance prices, DOE does not plan to monetize this particular benefit 

because the effect on the NOX allowance price from any single energy conservation standard is 

likely small and highly uncertain. 

Accordingly, DOE plans to use NEMS-BT to estimate the emissions reductions from 

possible standards in the 22 States where emissions are not capped. 

Mercury (Hg) 

Coal-fired power plants emit Hg found in coal during the burning process. While coalfired power plants are the largest remaining source of human-generated Hg emissions in the 

United States, they contribute very little to the global Hg pool or to contamination of U.S. 

waters. U.S. coal-fired power plants emit Hg in three different forms: oxidized Hg (likely to 

deposit within the United States); elemental Hg, which can travel thousands of miles before 

depositing to land and water; and Hg that is in particulate form. Atmospheric Hg is then 

deposited on land, lakes, rivers, and estuaries through rain, snow, and dry deposition. Once 

there, it can transform into methylmercury and accumulate in fish tissue through 

bioaccumulation. 

Americans are exposed to methylmercury primarily by eating contaminated fish. Because 

the developing fetus is the most sensitive to the toxic effects of methylmercury, women of 

childbearing age are regarded as the population of greatest concern. Children exposed to 

methylmercury before birth may be at increased risk of poor performance on neurobehavioral 

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tasks, such as those measuring attention, fine motor function, language skills, visual-spatial 

abilities, and verbal memory. 

Similar to emissions of SO2 and NOX, future emissions of Hg would have been subject to 

emissions caps. In May 2005, EPA issued the Clean Air Mercury Rule (CAMR). 70 FR 28606 

(May 18, 2005). CAMR would have permanently capped emissions of mercury for new and 

existing coal-fired power plants in all States by 2010. However, on February 8, 2008, the DC 

Circuit issued its decision in New Jersey v. Environmental Protection Agency, in which the DC 

Circuit, among other actions, vacated the CAMR. 517 F.3d 574 (DC Cir. 2008). EPA has 

decided to develop emissions standards for power plants under the Clean Air Act (Section 112), 

consistent with the DC Circuit’s opinion on the CAMR. See 

http://www.epa.gov/air/mercuryrule/pdfs/certpetition_withdrawal.pdf. Pending EPA's 

forthcoming revisions to the rule, DOE is excluding the CAMR from its Environmental 

Analysis. In the absence of CAMR, energy conservation standards would likely reduce Hg 

emissions, and DOE plans to use NEMS-BT to estimate these emission reductions. 

Particulate Matter 

DOE acknowledges that particulate matter (PM) impacts are of concern due to human 

exposures that can impact health. However, impacts of PM emissions reduction are much more 

difficult to estimate than other emissions reductions due to the complex interactions between 

PM, other power plant emissions, meteorology, and atmospheric chemistry that impact human 

exposure to particulates. Human exposure to PM usually occurs at a significant distance from the 

power plants that are emitting particulates and particulate precursors. When power plant 

emissions travel this distance, they undergo highly complex atmospheric chemical reactions. 

Although the EPA does keep inventories of direct PM emissions of power plants, in its source 

attribution reviews, the EPA does not separate direct PM emissions from power plants from the 

sulfate particulates indirectly produced through complex atmospheric chemical reactions. The 

great majority of PM emissions from power plants are of these secondary particles (secondary 

sulfates). Thus, it is not useful to examine how the amended standard impacts direct PM 

emissions independent of indirect PM production and atmospheric dynamics. Therefore, DOE is 

not planning to assess the impact of these standards on particulate emissions. Further, even the 

cumulative impact of PM emissions from power plants and indirect emissions of pollutants from 

other sources is unlikely to be significant. 

15.2.2 Monetization of Emission Reductions Benefits 

For those emissions for which real national emission reductions are anticipated (CO2, Hg, 

and NOX for 22 states), ranges of estimated economic values based on environmental damage 

studies of varying quality and applicability are available. Therefore, DOE plans on reporting 

estimates of monetary benefits derived using these values and plans to consider these benefits in 

weighing the costs and benefits of each of the standard levels considered. 

Carbon Dioxide (CO2) 

In order to estimate the monetary value of benefits resulting from reduced emissions of 

CO2 emissions, it is DOE’s intent to use in its analysis the most current Social Cost of Carbon 

15-5 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

(SCC) values developed and/or agreed to by interagency reviews. 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. 

At the time of this notice, the most recent interagency estimates of the potential global 

benefits resulting from reduced CO2 emissions in 2010 are $4.7, $21.4, $35.1, and $64.9 per 

metric ton in 2007 dollars. These values are then adjusted to 2009$ using the standard GDP 

deflator value for 2008 and 2009. For emissions (or emission reductions) that occur in later 

years, these 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 will be given to consideration of the global 

benefits of reducing CO2 emissions. To calculate a present value of the stream of monetary 

values, DOE will discount the values in each of the four cases using the discount rates that had 

been used to obtain the SCC values in each case. See appendix A of the Annex to this chapter 

for the full range of annual SCC estimates from 2010 to 2050. 

 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. 

Nitrogen Oxides (NOx) 

As discussed earlier, with respect to NOx the CAIR rule has been reinstated by the 

courts. Therefore, NOx emissions in those states covered by CAIR will be subject to a cap with 

corresponding annual allowances openly traded. 

For those states not covered by CAIR, DOE plans on estimating the monetized benefits 

of NOx emissions reductions in these states based on environmental damage estimates from the 

literature. Available estimates suggest a very wide range of monetary values for NOx emissions, 

ranging from $370 per ton to $3,800 per ton of NOx from stationary sources, measured in 2001$, 

(equivalent to a range of $447 to $4,591 per ton in 2009$).4 

Mercury (Hg) 

DOE plans on estimating the monetized benefits of Hg emissions reductions based on 

environmental damage estimates from the literature. For Hg emissions reductions, DOE has 

previously determined that the basic science linking mercury emissions from power plants to 

impacts on humans is considered highly uncertain. However, DOE identified two estimates of the 

environmental damages of mercury based on two estimates of the adverse impact of childhood 

exposure to methyl mercury on IQ for American children, and subsequent loss of lifetime 

economic productivity resulting from these IQ losses. The high-end estimate is based on an 

estimate of the current aggregate cost of the loss of IQ in American children that results from 

15-6 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

exposure to mercury of U.S. power plant origin─$1.3 billion per year in 2000$, which translates 

to $33.7 million per ton emitted per year in 2009$. 5 DOE derived the low-end estimate of $0.66 

million per ton emitted in 2004$, or $0.745 million per ton in 2009$, from a published evaluation 

of mercury control using different methods and assumptions from the first study, but also based 

on the present value of the lifetime earnings of children exposed to mercury.6 b 

For both NOX and Hg, DOE will conduct two calculations of the monetary benefits 

derived using each of the economic values used, one using a real discount rate of 3 percent and 

another using a real discount rate of 7 percent, in accordance with the U.S. Office of 

Management and Budget (OMB) guidance.c 

15.3 RESULTS 

The results for the environmental assessment are similar to a complete NEMS run, as 

published in the AEO2010. These include emissions for SO2, NOX, mercury, and CO2 in fiveyear forecasted increments, extrapolated to the year 2045. DOE will report the outcome of the 

analysis for each trial standard level as a deviation from the AEO2010 reference case results. 

b

 The estimate was derived by back-calculating the annual benefits per ton from the net present value of benefits 

reported in the study. 

15-7 

EERE-2008-BT-STD-0006 COMMENT 54
 

REFERENCES
 

1. Energy Information Administration, Annual Energy Outlook 2010 with Projections to 

2035, March 2010. Washington, DC. Report No. DOE/EIA-0383(2010). 

2. U.S. Environmental Protection Agency, National Ambient Air Quality Standards, 2008. 

(Last accessed March 11, 2008.) <http://www.epa.gov/air/urbanair/> 

3. U.S. Environmental Protection Agency, Nitrogen Oxides Health and Environmental 

Impacts of NOx (Posted May 26th, 2009) 

<http://www.epa.gov/air/urbanair/nox/hlth.html> 

4. 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, 2006. Washington, DC. 

<http://www.whitehouse.gov/omb/inforeg/2006_cb/2006_cb_final_report.pdf> 

5. Trasande, L., C. Schechter, K.A. Haynes, and P.J. Landrigan,, Applying Cost Analyses to 

Drive Policy That Protects Children : Mercury as a Case Study. Annals of the New York 

Academy of Sciences, 2006. 1076 

6. Ted Gayer and Robert Hahn, Designing Environmental Policy: Lessons from the 

Regulation of Mercury Emissions,” 2004. AEI-Brookings Joint Center For Regulatory 

Studies. A version of this paper was published in the Journal of Regulatory Economics in 

2006. 

15-8 

EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 16. REGULATORY IMPACT ANALYSIS FOR PROPOSED ENERGY
 

CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT
 

PUMPS
 

TABLE OF CONTENTS
 

16.1 INTRODUCTION ......................................................................................................... 16-1 

16.2 METHODOLOGY ........................................................................................................ 16-1 

LIST OF TABLES 

Table 16.1.1 Non-Regulatory Alternatives to Standards ........................................................ 16-1 

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CHAPTER 16. REGULATORY IMPACT ANALYSIS FOR PROPOSED ENERGY
 

CONSERVATION STANDARDS FOR CENTRAL AIR CONDITIONERS AND HEAT
 

PUMPS
 

16.1 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. DOE has identified seven major alternatives to standards as representing feasible policy 

options to reduce consumer product energy consumption. It will evaluate each alternative in 

terms of its ability to achieve significant energy savings at a reasonable cost, and will compare 

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 16.1.1. The technical support document (TSD) in support of DOE’s notice of 

proposed rulemaking will include a complete quantitative analysis of each alternative, the 

methodology for which is discussed briefly below. 

Table 16.1.1 Non-Regulatory Alternatives to Standards 

No new regulatory action 

Consumer tax credits 

Manufacturer tax credits 

Performance Standards 

Rebates 

Voluntary energy efficiency targets 

Early replacement 

Bulk government purchases 

16.2 METHODOLOGY 

DOE will use the national impact analysis (NIA) spreadsheet models for each of the two 

products to calculate the national energy savings and the net present value (NPV) corresponding 

to each alternative to the proposed standards. The NIA model for each of the two products is 

discussed in chapter 10 of the TSD. To compare each alternative quantitatively to the proposed 

energy conservation standards, DOE will need to quantify the effect of each alternative on the 

purchase and use of energy efficient room air conditioners and clothes dryers. Once it has 

quantified each alternative, DOE will make the appropriate revisions to the inputs in the NIA 

models. Key inputs that DOE may revise in these models are: 

• Energy prices and escalation factors; 

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EERE-2008-BT-STD-0006 COMMENT 54
 

•	 Implicit market discount rates for trading off purchase price against operating 

expense when choosing product efficiency; 

•	 Consumer purchase price, operating cost, and income elasticities; 

•	 Consumer price-versus-efficiency relationships; and 

•	 Product stock data (purchase of new products or turnover rates for inventories). 

The key measures of the impact of each alternative will be: 

•	 Energy use: Cumulative energy use of the product from the effective date of the new 

standard to the year 2045. DOE will report electricity consumption as primary energy. 

•	 National energy savings: Cumulative national energy use from the base case 

projection minus the alternative policy case projection. 

•	 Net present value: The value of future operating cost savings from products bought in 

the period from the effective date of the new standard 2016 to the year 2045. DOE 

will calculate the NPV as the difference between the present value of product and 

operating expenditures (including energy) in the base case, and the present value of 

expenditures in each alternative policy case. DOE will discount future operating and 

product expenditures to 2010 using a seven-percent and three-percent real discount 

rate. It will calculate operating expenses (including energy costs) for the life of the 

products. 

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EERE-2008-BT-STD-0006 COMMENT 54
CHAPTER 17. REGIONAL STANDARDS IMPACTS ON MARKET PARTICIPANTS
 

TABLE OF CONTENTS
 

17.1 Introduction..................................................................................................................... 17-1
 

17.1.1 Issues on Which DOE Seeks Comment .............................................................. 17-1
 

17.1.2 Regional Standards Overview ............................................................................. 17-2
 

17.1.2.1Regional Standards vs. National Standard............................................. 17-5
 

17.1.3 Discussion of Non Enforcement vs. Enforcement Issues.................................... 17-6
 

17.2 Market Participants ......................................................................................................... 17-7
 

17.2.1 Definition of Terms ............................................................................................. 17-7
 

17.2.1.1Distributors ............................................................................................ 17-7
 

17.2.1.2Contractors............................................................................................. 17-7
 

17.2.1.3Dealers ................................................................................................... 17-7
 

17.2.1.4Installers................................................................................................. 17-8
 

17.2.1.5Builders.................................................................................................. 17-8
 

17.3 Distribution Chain........................................................................................................... 17-8
 

17.3.1 Overview ............................................................................................................. 17-8
 

17.3.2 Vertical Integration.............................................................................................. 17-9
 

17.3.3 Distributors........................................................................................................ 17-10
 

17.3.3.1Market Overview ................................................................................. 17-10
 

17.3.3.2Distributor Business Model ................................................................. 17-10
 

17.3.4 Contractors ........................................................................................................ 17-13
 

17.3.4.1Market Overview ................................................................................. 17-13
 

17.3.4.2Business Model.................................................................................... 17-13
 

17.3.5 General Contractor ............................................................................................ 17-14
 

17.3.5.1Market Overview ................................................................................. 17-14
 

17.3.5.2Business Model.................................................................................... 17-14
 

17.3.6 Retailers............................................................................................................. 17-15
 

17.4 Discussion of Regional Standard Impacts .................................................................... 17-15
 

17.4.1 Distributor Impacts............................................................................................ 17-15
 

Non-enforcement Issues for Distributors .......................................................... 17-15
 

Enforcement Issues for Distributors.................................................................. 17-17
 

17.4.2 Contractor Impacts ............................................................................................ 17-18
 

Non-enforcement Issues for Contractors........................................................... 17-18
 

Enforcement Issues for Contractors .................................................................. 17-18
 

17.4.3 General Contractor Impacts............................................................................... 17-19
 

Non-enforcement Issues for General Contractors............................................. 17-19
 

Enforcement Issues for General Contractors..................................................... 17-19
 

17.5 Analysis of Regional Standard Impacts........................................................................ 17-19
 

17.5.1 Profitability Analysis of Regional Standard Impacts........................................ 17-20
 

17.5.1.1Data Sources ........................................................................................ 17-20
 

17.5.1.2Sample Inventory Calculation for Southeastern Border CACHP
 

Wholesaler......................................................................................................... 17-23
 

17.5.1.3CACHP Profitability Calculation ........................................................ 17-25
 

17.5.1.4Sample Furnace Inventory Calculation for Border Wholesalers......... 17-26
 

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17.5.1.5Furnace Profitability Calculation......................................................... 17-27
 

17.5.2 Preliminary Analysis of the Impacts of Regional Standards on Furnace and 

CACHP markups........................................................................................................... 17-28
 

17.5.2.1Furnace Markups ................................................................................. 17-28
 

17.5.2.2Firm Markups Far From the Border Region........................................ 17-28
 

17.5.2.3Border Region Markups....................................................................... 17-30
 

17.5.2.4Central Air Conditioners and Heat Pumps........................................... 17-32
 

17.6 Additional Distributor Data .......................................................................................... 17-32
 

17.7 Additional Contractor Data........................................................................................... 17-47
 

17.8 Additional General Contractors and Homebuilders Data ............................................. 17-57
 

LIST OF TABLES 

Table 17.1.1. States and Regions for Residential CACHP Rulemaking* ................................. 17-3
 

Table 17.6.13 Revenue and Cost Items, Typical CACHP Distributors, Hot-Humid Region and 

Table 17.6.14 Revenue and Cost Items, Typical CACHP Distributors, Hot-Dry Region and 

Table 17.1.2 States and Regions for Residential Furnaces Rulemaking* ................................. 17-4
 

Table 17.1.3 Border States by Region for CACHP Rulemaking............................................... 17-5
 

Table 17.1.4 Border States by Region for Furnaces Rulemaking.............................................. 17-6
 

Table 17.5.1 Typical Southeastern Wholesaler Assets, Liabilities, and Profitability.............. 17-22
 

Table 17.5.2 Border Wholesaler Required Inventory.............................................................. 17-24
 

Table 17.5.3 Profitability Impacts of CACHP Inventory Cost Increases............................... 17-26
 

Table 17.5.4 Return on Net Worth Impacts of CACHP Inventory Cost Increases ................ 17-26
 

Table 17.5.5 Number of Units of Inventory of Furnaces in the Border Region..................... 17-27
 

Table 17.5.6 Profitability Sensitivity Analysis for Furnaces in Border States ........................ 17-27
 

Table 17.5.7 Return on Net Worth Analysis for Furnaces in Border States............................ 17-28
 

Table 17.5.8 Northern Region Markups .................................................................................. 17-29
 

Table 17.5.9 Southern Region Markups .................................................................................. 17-29
 

Table 17.5.10 Saturation Rate of Condensing Furnaces in the Northern Border Region........ 17-30
 

Table 17.5.11 Saturation Rate of Condensing Furnaces in the Southern Border Region........ 17-31
 

Table 17.5.12 Border Region Markups.................................................................................... 17-31
 

Table 17.5.13 Central Air Conditioner and Heat Pump Markups ........................................... 17-32
 

Table 17.6.1 Distributor Enterprise Statistics for Hot-Humid Region (2002)........................ 17-33
 

Table 17.6.2 Distributor Enterprise Statistics for Hot-Dry Region (2002)............................. 17-33
 

Table 17.6.3 Distributor Enterprise Statistics for Rest of Country (2002) ............................. 17-34
 

Table 17.6.4 Establishments, Employment, and Payroll Trends in Hot-Humid Region........ 17-35
 

Table 17.6.5 Establishments, Employment, and Payroll Trends in Hot-Dry Region............. 17-35
 

Table 17.6.6 Establishments, Employment, and Payroll Trends in Rest of Country ............. 17-36
 

Table 17.6.7 Income Statement Items, Typical CACHP Distributors, Hot–Humid Region .. 17-37
 

Table 17.6.8 Balance Sheet, Typical CACHP Distributors, Hot-Humid Region................... 17-37
 

Table 17.6.9 Income Statement Items, Typical CACHP Distributors, Hot–Dry Region ....... 17-38
 

Table 17.6.10 Balance Sheet, Typical CACHP Distributors, Hot-Dry Region...................... 17-38
 

Table 17.6.11 Income Statement Items, Typical CACHP Distributors, Rest of Country ...... 17-39
 

Table 17.6.12 Balance Sheet, Typical CACHP Distributors, Rest of Country ...................... 17-39
 

Border States............................................................................................................................ 17-40
 

Border States............................................................................................................................ 17-40
 

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EERE-2008-BT-STD-0006 COMMENT 54
Table 17.6.15 Revenue and Cost Items, Typical CACHP Distributors, Rest of Country Region 

and Border States ..................................................................................................................... 17-41
 

Table 17.6.17 Geographic Area Series, Hardware, Plumbing, and Heating Equipment Merchant 

Table 17.7.1 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Humid 

Table 17.7.2 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Dry
 

Table 17.7.3 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Rest of 

Table 17.7.8 Mechanical Contractor Establishments, Employment, and Payroll Trends, HotTable 17.7.9 Mechanical Contractor Establishments, Employment, and Payroll Trends, Hot-Dry
 

Table 17.7.10 Mechanical Contractor Establishments, Employment, and Payroll Trends, Rest of 

Table 17.8.4 General Contractor Establishments, Employment, and Payroll Trends, Hot-Humid 

Table 17.8.5 General Contractor Establishments, Employment, and Payroll Trends, Hot-Dry
 

Table 17.8.6 General Contractor Establishments, Employment, and Payroll Trends, Rest of 

Table 17.6.16 Distributor Financial Data by HARDI Region for 2009.................................. 17-42
 

Wholesalers.............................................................................................................................. 17-45
 

Region...................................................................................................................................... 17-49
 

Region...................................................................................................................................... 17-50
 

Country .................................................................................................................................... 17-51
 

Table 17.7.4 Geographic Area Series, Plumbing and HVAC Constructors ........................... 17-52
 

Table 17.7.5 Enterprise Statistics on Mechanical Contractors in the Hot-Humid Region ..... 17-54
 

Table 17.7.6 Enterprise Statistics on Mechanical Contractors in the Hot-Dry Region .......... 17-54
 

Table 17.7.7 Enterprise Statistics on Mechanical Contractors in the Rest of Country........... 17-55
 

Humid Region.......................................................................................................................... 17-56
 

Region...................................................................................................................................... 17-56
 

Country Region........................................................................................................................ 17-57
 

Table 17.8.1 Enterprise Statistics on General Contractors in the Hot-Humid Region ........... 17-58
 

Table 17.8.2 Enterprise Statistics on General Contractors in the Hot-Dry Region ................ 17-59
 

Table 17.8.3 Enterprise Statistics on General Contractors in the Rest of Country................. 17-60
 

Region...................................................................................................................................... 17-61
 

Region...................................................................................................................................... 17-61
 

Country .................................................................................................................................... 17-62
 

Table 17.8.7 Revenue and Cost Items, Typical General Contractors, Hot-Humid Region 

.................................................................................................................................................. 17-63
 

Table 17.8.8 Revenue and Cost Items, Typical General Contractors, Hot-Dry Region........ 17-64
 

Table 17.8.9 Revenue and Cost Items, Typical General Contractors, Rest of Country ........ 17-65
 

LIST OF FIGURES 

Figure 17.3.1 Distribution Chain in Replacement Market........................................................ 17-9
 

Figure 17.3.2 Distribution Chain in New Construction Market ............................................... 17-9
 

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CHAPTER 17. MARKET AND TECHNOLOGY ASSESSMENT 

17.1 INTRODUCTION 

The Energy Policy and Conservation Act (EPCA), as amended by the Energy 

Independence and Security Act of 2007 (EISA; Pub. L. 110-140), directs the U.S. Department of 

Energy (DOE) to “consider the impact of additional regional standards on consumers, 

manufacturers, and other market participants, including distributors, dealers, contractors, and 

installers,” before establishing additional regional standards.” (42 U.S.C. 6295(o)(6)(D)(ii)) This 

technical support document (TSD) chapter represents an important step in DOE’s efforts toward 

fulfilling this statutory obligation. Specifically, the language of EPCA affects the current energy 

conservation standards rulemakings for residential central air conditioners and heat pumps 

(CACHP) and furnaces. The substance of this chapter will also be included in the furnaces TSD 

because the analysis generally applies to both the CACHP and furnaces rulemakings and DOE is 

evaluating regional standards for each rulemaking. Where indicated, the analysis is specific to 

either CACHP or furnaces. The purpose of this chapter is to establish a common framework and 

understanding of the HVAC distribution chain and market dynamics to facilitate discussion of 

regional standards among DOE and interested parties. This chapter also affords the early 

opportunity for stakeholders to comment on DOE’s understanding of key market factors as well 

as DOE’s initial analytical methodology and conclusions regarding the impacts of regional 

standards. 

This chapter is structured as follows: First, DOE provides an overview of the issues 

raised by regional standards as they relate to the market participants specified in EPCA. Second, 

DOE defines the market participants and the interaction of those participants the distribution 

chain. DOE examines the general business models of the key participants in the market 

independently. Next, DOE investigates how regional standards could affect those models based 

on industry research, initial discussions with manufacturers, distributors and contractors, and the 

comments received in response to the central air conditioner and heat pump framework 

document and public meeting. Lastly, when possible given data availability, DOE quantitatively 

assesses the impacts of regional standards on the analyzed market participants, conducting two 

analyses: (1) an investigation of the impact of changes in inventory holdings on distributor 

profitability and (2) a presentation of preliminary estimates of the impact of regional standards 

on distributor and contractor (installer) markups for central air conditioners, heat pumps and 

furnaces. The markups for these products are estimated for different regions of the country, and 

based on limited available data about the current distribution of equipment efficiency and 

projected changes to equipment efficiency. These estimates will be updated as more information 

becomes available. 

17.1.1 Issues on Which DOE Seeks Comment 

DOE is particularly interested in receiving comments and views of interested parties 

concerning the following issues: 

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1.	 The impacts of additional regional standards on distributors, mechanical 

contractors, and general contractors 

2.	 The impact of regional standards enforcement mechanisms on the HVAC 

distribution chain 

3.	 How regional standard impacts are different from the impacts resulting from 

amended national energy conservation standards 

4.	 How DOE can best capture incorporate the impacts identified above in its analysis 

5.	 The conclusions drawn in this chapter 

17.1.2 Regional Standards Overview 

DOE is considering regional standards for residential air conditioners and heat pumps for 

two multi-state regions (Hot-Humid and Hot-Dry) in addition to a base national standard that 

would prevail in states throughout the rest of the country. For impact analysis purposes in the 

CACHP rulemaking, the rest of the country is considered a third region called Rest of Country 

(called the “North” in this chapter for simplicity). By statute, the regions must include whole, 

contiguous states. (42 U.S.C. 6295(o)(6)(C)) The states are grouped such that the populations of 

the two hot regions generally experience more than 1200 annual cooling hours (CLH), and the 

Hot-Humid region has high relative humidity while the Hot-Dry region does not 

The boundary between Hot-Humid and Rest of Country is approximately at the 4500 annual 

heating degree-day (HDD) line. The states currently included in each region in the CACHP 

rulemakings are listed in Table 17.1.1. For reasons described below, DOE distinguishes between 

states that border other regions and those that do not. States that are on the border of two regions 

are italicized in the table. All states in the Hot-Dry region have at least one border with another 

region. 

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Table 17.1.1 States and Regions for Residential CACHP Rulemaking* 

Hot-Humid Hot-Dry Rest of Country 

Alabama Arizona Alaska 

Arkansas California Colorado 

Florida Nevada Connecticut 

Georgia New Mexico Delaware 

Hawaii Dist. of Col. 

Louisiana Idaho 

Mississippi Illinois 

North Carolina Indiana 

Oklahoma Iowa 

South Carolina Kansas 

Tennessee Kentucky 

Texas Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Missouri 

Montana 

Nebraska 

New Hampshire 

New Jersey 

New York 

North Dakota 

Ohio 

Oregon 

Pennsylvania 

Rhode Island 

South Dakota 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

* Italics indicate border state 

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DOE is also considering regional standards for residential furnaces — which is a separate 

rulemaking from CACHP — that would have two regions (North and South) for impact 

assessment purposes. 

The regional boundary for the states in the Furnaces rulemaking is approximately at the 

5,000 HDD line. The states included in each furnace rulemaking regions are listed in Table 

17.1.2. 

Table 17.1.2 States and Regions for Residential Furnaces Rulemaking* 

Furnaces-North Furnaces-South 

Alaska Alabama 

Colorado Arizona 

Connecticut Arkansas 

Idaho California 

Illinois Delaware 

Indiana Florida 

Iowa Georgia 

Kansas Hawaii 

Maine Kentucky 

Massachusetts Louisiana 

Michigan Maryland 

Minnesota Mississippi 

Missouri Nevada 

Montana New Mexico 

Nebraska North Carolina 

New Hampshire Oklahoma 

New Jersey South Carolina 

New York Tennessee 

North Dakota Texas 

Ohio Virginia 

Oregon 

Pennsylvania 

Rhode Island 

South Dakota 

Utah 

Vermont 

Washington 

West Virginia 

Wisconsin 

Wyoming 

* Italics indicate border state 

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17.1.2.1 Regional Standards vs. National Standard 

It is important to differentiate between the impacts of an amended national standard and 

the impact of introducing regional standards. The following sections do not assess the impact on 

market participants of more stringent energy conservation standards. Rather, this chapter focuses 

on the impacts on market participants in the HVAC distribution chain of having different 

standards affecting different geographic markets. For example, the impacts of physically larger 

HVAC units on distributors (due to a more stringent standard) are not discussed in this chapter 

because such an impact would occur under an increase in the base national standard as well. 

This chapter considers only the impacts of additional regional standards on these market 

participants. For example, the impact on a distributor of having to alter inventory systems to 

serve regions with differential efficiency levels is an impact that would be considered. 

Ultimately, DOE must determine whether regional standards are economically justified, after 

considering the impacts on market participants attributable to such standards. 

For firms located farther from the borders delineating applicability of the regional standards and 

serving only small areas, the impact of regional standards is expected to be very similar to the 

impact of a national energy conservation standard. However, firms located near the border 

between regions and serving two (or three, in the case of CACHP) regions are expected to be 

most strongly impacted because they may have to respond to different efficiency requirements 

for each region in which they operate. For example, distributors located near the border between 

standards regions may sell equipment meeting different standards in the different regions and 

need to carry more inventory or manage their inventory differently to meet the separate needs of 

customers in each region. Table 17.1.3 and Table 17.1.4 display the states on the borders of the 

CACHP and furnaces regions, respectively. 

Table 17.1.3 Border States by Region for CACHP Rulemaking 

CAC-CHP Hot-Humid CAC-CHP Hot-Dry CAC-CHP Rest of Country 

Arkansas Arizona Colorado 

North Carolina California Idaho 

Oklahoma Nevada Kansas 

Tennessee New Mexico Kentucky 

Texas Missouri 

Oregon 

Utah 

Virginia 

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Table 17.1.4 Border States by Region for Furnaces Rulemaking 

Furnaces North Furnaces South 

Colorado Arizona 

Idaho Arkansas 

Illinois California 

Indiana Delaware 

Kansas Kentucky 

Missouri Maryland 

New Jersey Nevada 

Ohio New Mexico 

Oregon Oklahoma 

Pennsylvania Tennessee 

Utah Virginia 

West Virginia 

17.1.3 Discussion of Non Enforcement vs. Enforcement Issues 

For the purposes of this chapter, DOE groups potential impacts of regional standards on 

market participants into two categories: (1) non-compliance issues and (2) compliance-related 

issues. Non-compliance issues are those that arise from regional standards regardless of the 

enforcement plan established by DOE. Compliance-related issues are those impacts that would 

vary depending on the enforcement path proposed by DOE (e.g., certification, verification, and 

labeling costs). 

At this stage, while DOE is considering various enforcement plans, no mechanisms or 

requirements are proposed here. As such, DOE does not attempt to quantify enforcement-related 

impacts in this chapter. EPCA requires DOE to begin an enforcement rulemaking not later than 

90 days after the issuance of a final rule establishing regional standards and complete the 

rulemaking not later than 15 months following the issuance of the rule. (42 U.S.C. 

6295(o)(6)(G)(ii)). 

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17.2 MARKET PARTICIPANTS 

17.2.1 Definition of Terms 

As discussed previously, EPCA directs DOE to consider the impacts of additional 

regional standards on market participants, including “distributors, dealers, contractors, and 

installers.” (42 U.S.C. 6295(o)(6)(D)(ii)) Based on DOE’s initial research and comments from 

stakeholders, some of the market participants enumerated in EPCA have overlapping or identical 

functions in the HVAC marketplace. Industry often uses the various terms interchangeably to 

describe the same market participant. Therefore, it is important to clarify what market roles are 

associated with each term for the purposes of this analysis. Below is a brief description of 

DOE’s understanding of each player in the distribution chain (for more detailed descriptions, 

refer to 17.3). 

17.2.1.1 Distributors 

Also known as ‘wholesalers,’ distributors purchase HVAC equipment directly from the 

original equipment manufacturers (OEMs). Distributors absorb short-term imbalances in supply 

and demand and sell equipment to contractors at a markup to cover operating expenses and 

profit. 

17.2.1.2 Contractors 

There are two basic types of contractors of relevance to the HVAC market: 

General contractors. In the new construction market, general contractors 

manage and oversee residential and commercial construction projects. General 

contractors often lack the necessary technical expertise to install and inspect 

HVAC systems. As a result, they hire HVAC trade specialists, or mechanical 

contractors, to install equipment. General contractors usually have no significant 

role in the residential replacement market, except for cases of major retrofits. 

Mechanical contractors. Mechanical contractors are specialized contractors that 

install and maintain HVAC systems, plumbing, wiring, etc. Mechanical 

contractors purchase HVAC systems from distributors and install them for their 

customers. Contractors often service existing HVAC systems as well. Again, in 

the new construction market, they are usually hired by general contractors. In the 

replacement market, they are hired by homeowners and are considered 

synonymous with dealers (below). 

17.2.1.3 Dealers 

Much like mechanical contractors, HVAC dealers purchase systems from distributors. 

Often they may have a more formal relationship with a manufacturer. Dealers resell the 

equipment to the end-user at a mark-up, nearly always installing the HVAC system as well. 

Dealers also inspect, maintain, and repair existing systems. 

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17.2.1.4 Installers 

The industry uses installers interchangeably with mechanical contractors and dealers. 

Because the HVAC market is very rarely a do-it-yourself market, DOE includes homeowners 

who install their own systems in this category. In general, the impact of regional standards on 

homeowners is assessed in the LCC analysis. 

17.2.1.5 Builders 

For the purposes of this chapter, builders serve the same function in the HVAC 

marketplace as general contractors. 

Given the above similarities and overlapping roles in the distribution chain, DOE 

believes that EPCA’s requirement to analyze the impacts on product distributors, dealers, 

contractors, and installers is satisfied by an analysis of the potential impact of regional standards 

on three categories of market participants: 

• Distributors 

• Mechanical contractors 

• General contractors 

The category of “mechanical contractors” includes dealers, mechanical contractors, and 

installers. The category of “general contractors” comprises builders and general contractors. In 

accordance with comments received and consistent with the markups analysis, DOE believes 

such a grouping is appropriate for this analysis and allows DOE to consider the economic impact 

of regional standards on the relevant market participants as required by EPCA. Impacts on 

manufacturers are assessed in the manufacturer impact analysis, while impacts on consumers are 

assessed in the life-cycle cost analysis. 

17.3 DISTRIBUTION CHAIN 

17.3.1 Overview 

A single distribution channel represents the vast majority of the HVAC market. Simply, 

the OEM assembles the system and sells it to a distributor; the distributor warehouses and sells 

the unit to a contractor; and the contractor sells the unit to the final consumer and performs the 

installation. The final consumer varies in the replacement and in the new construction market. 

In the replacement market, the final consumer is usually the home or business owner, as 

illustrated in Figure 17.3.1. In the new construction market, a builder or general contractor is 

effectively the final end-user, as shown in Figure 17.3.2. 

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Figure 17.3.1 Distribution Chain in Replacement Market 

Figure 17.3.2 Distribution Chain in New Construction Market 

After installation, mechanical contractors typically perform additional lifecycle service 

on the system, including inspection, maintenance, and repair. 

17.3.2 Vertical Integration 

In some cases, a single entity can perform one or more of the basic steps along the HVAC 

distribution channel. For example, most manufacturers own at least some distribution centers, 

which operate much like the independent distribution companies. In fact, all major manufacturers 

maintain at least some distribution capability in-house. In this distribution model, the OEM 

ships units to its own subsidiaries, which operate distribution centers and sell product to 

contractors. Manufacturers usually employ this strategy in areas where they have limited 

relationships with distributors for a given product line. 

Historically, the degree of vertical integration has ebbed and flowed with the economic 

well-being of the industry. In good times, OEMs have historically been more likely to acquire a 

distribution presence. Conversely, in bad times, they have been more likely to seek to shed the 

costs and risks associated with the distribution function. According to the U.S. Census Bureau, 

in 2002, 74 percent of HVAC sales went through independent distributors.1

 Currently, the 

percentage of the dollar value of HVACR products that go through independent distributors is 

estimated to be around 80 percent.2 

Lennox International Inc. (LII), a large equipment manufacturer, has one of the largest 

distribution presences in the industry. It owns several subsidiaries which operate as distributors 

and even as contractors, as is the case with LII subsidiary, Service Experts.3

 While Service 

Experts is a wholly owned subsidiary, it operates independently from LII’s manufacturing 

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operations. Service Experts carries heating and cooling equipment inventory and offers service 

for HVAC equipment from various manufacturers.4 

Importantly, while some entities may have a controlling interest over multiple steps in 

the distribution chain, the costs, markups, and business processes in the distribution chain 

ultimately remain relatively equivalent. That is, the distributor and contractor markups (and the 

resulting pricing) for the manufacturer-owned distributor and contractor businesses are roughly 

equivalent to the markups that occur where those businesses operate independently. 

The business models of distributors, contractors, and general contractors are described in 

greater detail below. 

17.3.3 Distributors 

17.3.3.1 Market Overview 

The HVAC distribution market is a well-established yet fragmented industry consisting 

of approximately 1,300 distribution companies. Independent distributors are responsible for the 

majority of the business in the industry, but all major manufacturers have some type of factoryowned distribution. The vast majority of independent distributors are small, private companies. 

In 2002, there were 5,468 total distribution branches, 5,156 of which were independent 

distribution branches and 312 of which were owned by manufacturers.5 

17.3.3.2 Distributor Business Model 

Distributors link the handful of CACHP/furnace manufacturers to the tens of thousands 

of contractors. Distributors receive shipments from manufacturers and resell the equipment to 

contractors at a markup that covers distributor operating expenses and profit. Manufacturers rely 

on distributors to consolidate and forecast product demand at the regional and local levels. 

Contractors rely on distributors to hold enough inventory and parts to meet their day-to-day 

business needs. As the only player along the distribution chain that holds significant inventory, 

distributors add value by absorbing short-term imbalances in supply and demand while still 

satisfying the needs of the homeowner (and, by extension, the contractor) for fast deliveries.6 

The distributor’s warehouse is usually the only stop for HVAC equipment on the way to the final 

installation site; however, in some markets distributors utilize regional distribution centers that 

supply secondary distribution warehouses. In either case, shipments are warehoused as 

distributor inventory until sold to customers. Although it can vary widely, typically sixty to 

seventy percent of revenue comes from unitary equipment, with the remainder coming from parts 

and other supplies. 

Distribution is a highly competitive and low-margin business. The critical driver of 

profitability is the ability to manage inventory efficiently. Traditionally, distributors tended to 

receive large-volume pre-season shipments from original equipment manufacturers (OEMs). 

However, the market has migrated away from that model as industry lead times (the time it takes 

to receive an order from the OEM) have fallen. Most distributors now operate in somewhat of a 

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blend between just-in-time supply and the traditional model. To streamline inventory 

management, distributors often conduct extensive demand forecasting to estimate the timing and 

quantity of their orders. Key factors include historical demand, new construction, OEM lead 

times, new products and lines, and weather patterns. The typical lead time of an average 

residential HVAC system is 2-3 weeks, although different parts or components, as well as more 

intricate HVAC systems, may have different lead times. Some of the more advanced coils, for 

example, can have lead times of 6-8 weeks. 

Financing and credit, closely related to inventory, play a critical role in the distribution 

business model. With the high working capital requirements due to inventory needs, short-term 

credit availability is the lifeblood of many small wholesalers. Distributors typically purchase 

equipment from manufacturers on credit, with the balance being paid within 30 days, often with 

discounts for early payment. Historically, OEMs have offered financing to their distributor 

clients, but have generally exited that business. Instead, most distributors now are financed 

through local banks. In turn, distributors often extend lines of credit to certain contractors based 

on the amount business volume, profitability of the relationship, and previous experience with 

the contractor. As a result, distributors incur the carrying costs associated with the difference 

between the financing terms that they receive from their creditors and the terms they extend to 

their contractor customers. Effectively, the distributor incurs as a cost the difference between 

these two rates over the period of time after the distributor pays the OEM for the unit and until it 

receives payment from the contractor. 

Because of this dynamic, a key financial metric driving profitability is days sales 

outstanding (DSOs), a measure of the number of days it takes a company to collect revenue after 

a sale has been made. DSOs in the industry average between 40-45 days; if they grow higher, 

the increased carrying costs can threaten the thin margins under which distributors operate. In 

extending credit to their customers, distributors also assume the risks involved with floating the 

receivables (i.e., the contractor goes out of business or otherwise fails to pay). 

Changes in market dynamics, which can lead to changes in the quantity and type of 

product demanded, may cause distributors to incur one-time costs associated with temporary 

increases in inventory, inventory obsolescence, or the opportunity costs represented by the 

failure to meet customer needs. Increased market uncertainty forces distributors to hold greaterthan-usual inventory to reduce the risk of not meeting customer needs.7

 Failure to do could mean 

losing customers to competition.8 However, if certain products do not sell, distributors absorb 

the costs of unsold inventory.9

 Typically, following an initial learning curve associated with 

these market changes, distributors adjust to their customers’ demands and are able to adjust 

inventory levels accordingly.10 

The increasing use of information technology in distribution has helped wholesalers 

adapt to market transitions. Sales and orders are usually made electronically at each step along 

the distribution chain. IT systems exist that allow distributors to forecast demand, source and 

purchase supplies, manage and track inventory, streamline the supply chain, and manage various 

sales channels.11 Many distributors give contractors the ability to place orders online after-hours 

so that the orders are ready for pickup the following morning, while others give some customers 

a direct link into a computer system for automatic inventory replenishment.12 

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At the distribution center, inventory is generally organized by model and 

SEER/HSPF/AFUE rating. Units are stacked vertically and, depending on their size, may be 

transported with forklifts. The layout of warehouse and placement of product affect order 

processing and inventory efficiency.13 It is important for distributors to organize inventory in a 

manner that minimizes the order cost and minimizes mistakes that lead to costly reprocessing. 

The average cost of processing an order, from receipt of the order until payment is received, is 

$35-$45.14 Cycle counts are performed frequently to minimize and document inventory 

shrinkage. 

Beyond the manufacturer selling price (cost of goods sold), the largest cost 

considerations are those that impact inventory and transportation costs. The size of an HVAC 

system impacts both. Larger, more efficient units require more warehouse space to inventory. 

The switch from 10 SEER to 13 SEER in 2006, for example, required 35-40% more floor space 

for every condensing unit.15 Fewer units can fit on trucks and forklifts, requiring more time per 

unit for transportation and handling, absent new and upgraded equipment.16 The larger units can 

require two people to offload them instead of one.17 

Manufacturer-to-Distributor Interactions 

The relationships between manufacturers and distributors are generally well-established, 

long-term relationships. In most markets, distributors are the exclusive carrier of a given 

manufacturer product. Distributors will often carry a second brand from the same manufacturer, 

which has a different price point targeting a second market segment. 

Most manufacturers will not allow distributors to carry products from a competitor, 

unless the manufacturer does not offer a product applicable to the market. In that case, 

distributors may partner with a second manufacturer. However, the terms of agreements can 

vary significantly depending on a wide range of factors, including sales volume, the extent of 

contractor relationships, strength of the brand in the area, and projected market growth. If a 

distributor carries a product line, it also has the parts business associated with that line. 

Manufacturers are generally responsible for getting the equipment to distributors’ 

warehouses and incur the associated costs, which they embed in their prices. Manufacturers 

usually hire a shipping company to transport the equipment and pass on these costs to the 

distributors in the sales price. Almost all inbound freight shipped to distributors is shipped FOB 

Origin Freight Prepaid, which means that once the manufacturer ships the freight, the distributor 

owns it.18 This can lead to problems when items are damaged or broken upon arrival, 

representing another risk in the distributor business model.19 

Distributor-to-Contractor Interactions 

Because there is relatively low manufacturer brand loyalty among consumer end-users, 

distributors compete actively over contractor customers. While OEMs focus on general brand 

awareness and product demand, distributors are frequently involved in providing multifunctional support to their contractors. To increase competitiveness and revenues, distributors 

are increasingly offering value-added services, such as business planning help, financial 

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management classes, and support for advertising, to their contractor customers beyond their 

supply function. This is also a strategy for increasing profitability—a contractor that is 

unprofitable cannot pay the distributor in a timely fashion, if at all. Thus, successful distributors 

are heavily invested in their contractors’ success.20 

In the vast majority of cases, contractors purchase the unit over the counter at the 

distributor’s warehouse. Because most contractors do not carry much or any inventory, the 

transaction will include a specific unit needed for a single job. The contractor can generally callin, order online, or fax in an order and go pick up the needed unit on the same day. At the 

warehouse, the distributor loads the unit onto the contractor’s truck (some distributors have 

“drive through” warehouses) and contractor can be on the way to the job site in minutes. While 

business is primarily done in this over-the-counter model, distributors also make onsite deliveries 

for their customers. 

17.3.4 Contractors 

17.3.4.1 Market Overview 

The HVAC contractor market is even more fragmented than the distribution industry. 

There are 36,345 HVAC branches that specialize 51 percent or more in HVAC, 25,496 of which 

specialize entirely in the industry.21 The large majority of contractors operate as small 

businesses, as defined by the U.S. Small Business Association (see Section 17.7 for more 

information on small business contractors). Partly due to the very low barriers to entry in the 

market, the industry has resisted consolidation. Approximately 60 percent of branches in the 

industry generate less than $500,000 in revenue annually and 76 percent generate less than 

$1,000,000 annually.22 Comfort Systems USA is the larger of two public HVAC contractor 

companies that DOE was able to find. Its 2008 revenues ($1,328,465,00023) accounted for 

approximately 3 percent of the $49,425,445,00024 HVAC contractor industry (although the 

company does provide ancillary services).25 Most independent contractors work with a variety 

of HVAC brands, although some specialize in one particular brand, or have a relationship as a 

licensed dealer of a specific manufacturer. 

17.3.4.2 Business Model 

HVAC contractors primarily install and service HVAC systems. Contractors are the 

interface with the end-users, installing new HVAC systems to their specifications as well as 

inspecting, servicing, or repairing existing systems. Contractors must balance two very different 

aspects of their business to be successful. First, contractors must fulfill the technical role of 

installing and servicing the HVAC systems. This requires a staff that is knowledgeable about 

HVAC principles in general and adept at installation and service on many different HVAC units. 

Second, contractors must also operate the commercial aspects of their business. Because of the 

high level of competition, advertising, customer service, and sales skills are integral aspects of 

the contractor’s business. Rarely do HVAC companies achieve sufficient scale to have staff 

specialize in a single business practice. 

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Contractors have the largest influence on which system a consumer will purchase.26 For 

their part, contractors tend to gravitate toward the products with which they are familiar.27 

Contractors often employ a good-better-best selling philosophy to up-sell consumers on premium 

products.28 The minimum SEER model is a “good” system; there is a “better” system that is 

rated a few SEER points higher; and finally, there is a “best” system which has a very high 

SEER rating.29 A sample good-better-best set of systems might be 13 SEER-16 SEER-20 SEER; 

however, this is dependent on minimum efficiency requirements.30 Customers are more likely 

than they used to be to purchase energy-efficient and environmentally friendly products, in spite 

of the higher cost associated with them, because they have become more sensitive to the 

environment and the cost of energy.31 Increasing tax credits and utility rebates can defray some 

of the higher incremental first cost as well. 

While some contractors have exclusive relationships with manufacturers, most compete 

by offering a large variety of product offerings and by being trained to install, inspect, service, 

and repair those offerings. As with distributors, the size and weight of HVAC systems affect the 

business of contractors. While the vast majority of inventory is held by distributors, some 

contractors do carry a small amount of inventory and could be likewise affected by larger units. 

Larger systems are also more difficult to transport from the distributor to the job site, possibly 

even requiring special precautions or equipment to load or unload the unit in extreme cases. 

A contractor’s labor costs related to the installation and service of HVAC systems remain 

relatively constant regardless of the HVAC systems that the company installs and services. 32 

Once the technicians are trained, the time spent installing an HVAC unit does not vary greatly 

from system to system.33 

17.3.5 General Contractor 

17.3.5.1 Market Overview 

As discussed above, for the purposes of this chapter and consistent with comments 

received DOE considers general contractors and homebuilders to have essentially the same role 

in the distribution chain. Thus, DOE believes the two will have similar concerns and face similar 

potential impacts from regional standards. As with mechanical contractors, the general contractor 

and builder market is highly fragmented and localized. According to the U.S. Census, there 

were more than 200,000 general contractor establishments in 2002.34 

17.3.5.2 Business Model 

General contractors manage new construction and significant renovation projects. When 

supervising a project, the general contractor hires a mechanical contractor to perform the 

installation. In this situation, the general contractor functions as the final step in the distribution 

chain. The general contractor may purchase the HVAC system from the distributor and hire the 

mechanical contractor to it or purchase the system from the installing mechanical contractor. 

When projects are larger—a townhouse development, for example—a distributor may seek to 

establish a supplying relationship with the general contractor and deliver the units in bulk. The 

general contractor would then hire a mechanical contractor to perform the installation. For a 

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custom-built home or renovation, the mechanical contractor may purchase the unit to the 

specifications requested by the general contractor. 

17.3.6 Retailers 

Retailers such as Home Depot, Lowe’s and Sears can also be involved in the distribution 

process. However, DOE’s understanding of these retailers is that they function mostly as a leadgenerating system for contractors, as the HVAC market is very rarely a do-it-yourself market. 

When the so-called “Big Box” retailers are involved, customers go to a retailer and ask to be put 

into contact with a contractor. A distributor usually still supplies a contractor, who still performs 

the installation. In the end, the costs and markups reflect those in the standard distribution 

model. Furthermore, DOE believes this reflects a small portion of overall unit sales. Therefore, 

for the purposes of this analysis, DOE does not consider the role of retailers in this analysis. 

17.4 DISCUSSION OF REGIONAL STANDARD IMPACTS 

Through public notices, public meetings, and interviews with industry trade groups, DOE 

has solicited comments on the impact of regional standards on CACHP and Furnace industry 

participants. This chapter discusses DOE’s understanding of the potential impacts on key 

players in the distribution chain. 

As noted in Section 17.1.2.1, it is important to differentiate the difference between the 

impacts of a higher base national standard and of regional standards. The following sections do 

not assess the impact on market participants of an increase in the base national efficiency 

standard. Rather, this chapter focuses on the impacts of having different standards affecting 

different geographic markets. 

The impacts of regional standards are separated here into two categories: nonenforcement issues and enforcement issues. Non-enforcement issues are those issues that arise 

irrespective of the actions taken to enforce the regional standards. Enforcement issues are those 

impacts and costs that are directly related to ensuring compliance or that arise from noncompliance. Because DOE has not established an enforcement plan for regional standards, DOE 

is not able to capture any enforcement impacts in this analysis. 

17.4.1 Distributor Impacts 

Non-enforcement Issues for Distributors 

In written comments and at the CACHP framework public meeting, Heating Air 

conditioning & Refrigeration Distributors International (HARDI) raised several concerns 

regarding the implementation of regional standards and the potential impact of those standards 

on their businesses. Their concerns center largely on the premise that there will be differences 

between regional standard boundaries and existing distribution boundaries. 

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HARDI noted that EPCA requires regional boundaries to be drawn along state lines, 

which are usually different from the market boundaries for central air conditioners, heat pumps, 

and furnaces. Existing market boundaries are determined by multiple factors, including utility 

service areas, composition of building types within an area, natural climatic regions, and 

localized microclimates. HARDI identified a range of negative impacts resulting from the 

incongruence of regional standards boundaries and existing distribution boundaries (HARDI, No. 

32 at pp. 5-6): 

• Increased costs due to increased inventory complexity 

• Increased costs due to lost economies of scale in purchasing 

• Reduced sales where cooling or heating demands are modest 

• Constraints on business growth near borders 

Based on its analysis and research, DOE believes that distributors that serve multiple 

regions will be impacted by additional (i.e., differentiated) regional standards. Distributors 

serving markets entirely within a single region will not experience non-enforcement impacts 

distinguishable from a national amended energy conservation standard. 

DOE understands there to be two types of distributors that will serve multiple standard 

regions and could be affected by the differentiated regional standards: (1) central distributors 

shipping to local distributors in multiple regions and (2) local distributors selling to contractors 

in multiple regions. In general, distributors located near borders are more likely to serve 

multiple standard regions 

DOE agrees that distributors serving multiple standard regions may be compelled to 

manage more variation in demand. Under a national standard, distributors could expect the bulk 

of demand to be at the base national level (e.g., 13 SEER for CACHP). Under regional 

standards, however, distributors near boundaries may experience bimodal demand, with the one 

large portion of shipments at the national standard efficiency level (e.g., 13 SEER) and a second 

large portion at a different regional efficiency level (e.g., 14 SEER). DOE believes that this 

bimodal demand does not signify a doubling of necessary inventory, but rather a more diverse 

inventory. The resulting change in product mix for distributors serving multiple regions could 

increase inventory management costs and increase overall investment in inventory, because more 

product models of equipment are required to meet demand. 

In Section 17.5.1, DOE performs a sensitivity analysis that investigates the impact of 

regional standards on inventory holdings and profitability. The analysis estimates a reasonable 

range of inventory increases based on industry data and then calculates the impact of those 

inventory changes on distributor profitability based on sample distributor financials. In general, 

the analysis finds that only small inventories changes would be required for distributors to meet 

product demand for multiple regions. Additionally, the sensitivity analysis finds the potential 

changes in inventory to have only small impacts on distributor profitability. See Section 17.5.1.3 

for more details. 

Another concern for the industry is that, with a wider variation in product, the number of 

particular product models purchased will be smaller, leading to fewer volume discounts. Along 

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the same vein, national and regional distributors stated that they would face decreases in 

economies of scale due to the smaller size of regional markets. (HARDI, No. 2 at p. 2) 

Specifically, if certain products could not be sold throughout the entire country, then the cost of 

those products would be driven up. (HARDI, No. 2 at p. 2) 

In response, DOE analyzes the impact of regional standards in reducing economies of 

scale for manufacturers and leading to higher cost of goods sold for all distributors (including 

those not serving multiple regions) in its markups and national impacts analyses for both 

CACHP and furnaces. The analysis assumes that those costs are passed on down the distribution 

chain to contractors and consumers. DOE will perform additional investigation on the cost 

impacts of smaller orders on distributors through interviews with manufacturers during the MIA 

process. 

Distributors also noted that sales in areas where cooling demands are more modest would 

likely be depressed since high-efficiency cooling equipment would not be as well justified. 

(HARDI, No. 32 at 4) These comments address the issues of elasticity of demand and the 

question of how customers “roll-up” or “shift” to different efficiency levels based on the 

economics they face, given a climate. In this respect, greater uncertainty about prospective sales 

is a not a function of having different standards by region, but simply having higher standards. 

The fact that cooling and heating demand varies by location is not exacerbated by regional 

standards. The question over the new efficiency distribution for each CACHP and furnace 

distributor is the same under national and regional standards. Optimizing inventory for the new 

demand distribution will be part of the transition cost in either standards case. 

In sum, DOE does expect the transition due to amended standards to inject uncertainty 

into the market, which could temporarily cause distributors to incur higher costs. However, 

DOE believes these costs are associated with a change in standards, not the advent of additional 

regional standards. 

Enforcement Issues for Distributors 

DOE understands that many distributors do business in more than one region. 

Furthermore, the contractors to whom these distributors sell often do business in more than one 

region. In light of these facts, it may be necessary for DOE to work with participants in the 

distribution chain to document the installation of CACHP and furnace units. If such reporting is 

used to support enforcement, it is possible that distributors will incur new compliance costs as a 

result additional record-keeping and reporting related to the regional standards. This would add 

some percentage to administrative labor costs of distribution channel participants, some of which 

could vary with the number of units sold and some of which could be fixed. Any additional 

costs would be incorporated in this analysis of the impacts of regional standards. 

At this time, however, DOE is not able to accurately assess impacts of compliance 

requirements on distributors. In the Preliminary Analysis for CACHP and in this chapter, DOE 

requests comment on appropriate measures for enforcement of regional standards for CACHP 

and furnaces. 

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17.4.2 Contractor Impacts 

Non-enforcement Issues for Contractors 

Air-Conditioning Contractors of America (ACCA) commented that larger units would 

cause higher transport and handling costs and, in many cases, would not fit in the residential 

space that housed the previous unit. (ACCA, Public Meeting Transcript, No. 23 at p. 252) 

In response, DOE notes that this issue is a function of higher standards, not differential 

regional standards. As such, problems with larger units are not considered in this chapter. To 

the extent that regional standards affect cost of goods sold, above and beyond a national 

standard, DOE expects incorporate that effect in its normal markups analysis. DOE is unaware 

of any other contractor concerns with regional standards that do not involve enforcement issues. 

Enforcement Issues for Contractors 

ACCA and HARDI stated that regional standards will increase non-compliance and 

would create a major competitive disadvantage for contractors that seek to comply. (ACCA, No. 

23 at p. 2; HARDI, No. 32 at p. 5) HARDI argued that this situation already exists in California 

after implementation of Title 24 requirements. Kent & O’Connor stated that splitting a 

metropolitan area with regional standards would have a significant competitive impact, 

particularly if a price difference exists between the higher regional efficiency and the national 

standard units. (Kent & O’Connor, No. 13 at p. 231) 

As with distributors, in general DOE believes that contractors near regional borders could 

potentially be impacted by enforcement-related competitive issues surrounding differential 

regions. DOE acknowledges that non-compliance can be a problem for contractors following the 

codes and licensing requirements, as there is an incentive for non-compliance in the form of 

being able to offer unknowing homeowners a lower price point for HVAC service. DOE 

recognizes that along border regions, differential standards could exacerbate this disadvantage 

for complying contractors, particularly if the price difference between the regional-compliant 

products is significant. 

DOE acknowledges that depending on the enforcement mechanisms put in place 

following a DOE rulemaking, contractors may incur additional administrative compliance costs 

associated with regional standards, including recording keeping or verification costs. However, 

as noted above, at this point DOE cannot accurately assess any impacts of compliance due to 

regional standards because no enforcement mechanisms and compliance requirements have yet 

been established. DOE seeks comment on potential compliance and enforcement options for 

regional standards. 

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17.4.3 General Contractor Impacts 

Non-enforcement Issues for General Contractors 

DOE received no comments on any non-enforcement related regional standard impacts 

on builders and general contractors, and is not aware of any impacts. DOE seeks comment on 

any non-enforcement impacts these market players may encounter under regional standards. 

Enforcement Issues for General Contractors 

The National Association of Home Builders (NAHB) commented that a general 

contractor usually will not have any special HVAC expertise. Therefore, if regional standards 

are implemented, a builder is likely to use more time and effort double-checking that units are 

compliant. The extra cost of this effort should be included in the payback analysis, the 

cumulative regulatory burden, the employment impact analysis, and the regulatory impact 

analysis. NAHB also commented that regional standards would affect home builders, most of 

which are small businesses; as such, a regulatory flexibility analysis would be necessary. 

(NAHB, No. 21 at pp. 1, 2) 

DOE recognizes that there may be impacts on general contractors operating in two 

different regions. For instance, DOE believes general contractors working on projects near 

regional standard borders may experience greater risk of mistakenly installing non-compliant 

systems—or hiring contractors who do so—and consequently incur greater cost under regional 

standards than they would under a single national standard. Although DOE expects this impact 

to be short run in nature as contractors adjust to the new standards, DOE seeks comment on the 

likelihood of this and other impacts due to operating in multiple regions. 

17.5 ANALYSIS OF REGIONAL STANDARD IMPACTS 

The focus of this section is the impact of regional standards on distributors, particularly 

those operating near boundary regions. DOE attempts to quantify the financial implications of 

imposing different efficiency standards in multiple geographic regions. As previously noted, 

until DOE has further developed the enforcement plan for regional standards, it is not possible to 

provide detailed analysis of enforcement impacts. Two primary analyses are presented here: 

•	 Analysis of inventory cost impacts under regional standards and the consequent 

impacts on profitability for CACHP and Furnaces Distributors 

•	 Preliminary Markups Analysis on Distributors and Contractors 

The inventory and profitability cost impact analysis provides a framework for 

understanding the magnitude of inventory changes that may result from regional standards and 

the impact of those cost changes on distributor profitability. As discussed in 17.3.3, DOE 

believes the key driver of distributor profitability is inventory. Therefore, this quantitative 

analysis only addresses changes in inventory costs. 

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The second analysis investigates the impact of regional standards on product markups. 

The analysis considers the impact of regional standards on product markups far from the border 

region and near the border region. For states where there will likely be a change in distributors’ 

product mix, the analysis anticipates what the new mix will be and analyzes markups in parts of 

the country that currently have that anticipated product mix. 

17.5.1 Profitability Analysis of Regional Standard Impacts 

The following analysis provides guidance on the potential impacts of regional standards 

on profitability for distributors serving more than one standard region. The analysis has two 

components. First, the change in inventory resulting from regional standards is calculated for a 

distributor serving two regions. Second, the impact of changes in inventory holdings on 

distributor profitability is calculated. The analysis is based on an example firm’s financial data, 

which is modeled after actual distributor data from HARDI. 

In general, DOE believes distributors operating in a single standard region will not see 

any inventory impacts that are different from the impacts resulting from a change in the national 

standard. However, distributors operating in multiple regions or that are near a border may have 

to adjust to business impacts that are unique to the introduction of multiple standard regions. 

This analysis finds that the inventory impacts resulting from regional standards are likely to be 

mild. A prototypical distributor that sells to two regions is modeled to have an increase in 

inventory of less than 2 percent. The resulting impact on distributor profitability is also mild at 

the expected levels of inventory change. 

17.5.1.1 Data Sources 

This analysis of the profitability impacts of distributors relies on three sources of 

information: Heating, Air conditioning and Refrigeration Distributors International 2009 Profit 

Report (2008 Data), 2002 Economic Census, and 2007 County Business Patterns. The 

following information can be obtained from these sources: 

•	 Number of firms; total and population-weighted average sales; total and average 

employment; and firm size distribution by revenue (2002 Economic Census and 2007 

County Business Patterns). 

These values are reported for the Nation and by State. It is possible to calculate these 

values for each of the regions affected by the standard (Hot-Humid, Hot-dry, and Rest of 

Country) and for each of the 17 states that borders these regions. 

•	 Number of small businesses as defined by the Small Business Administration (SBA). 

The SBA maximum threshold to qualify as a “small business” for NAICS 42373 is one 

hundred employees. In 2002, out of 2,773 firms with 5,942 individual establishments 

nation-wide, only five firms (0.2%) had one hundred or more employees. The nationallevel data shows that the distributors are overwhelmingly small businesses. Data is not 

available at the regional level, but regional analysis would be unlikely to show a different 

result. 

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•	 Typical cost structure and profitability (HARDI data, 2002 Census). Variation among 

firm sizes and types (HARDI data). 

The annual HARDI reports have detailed cost structure data for typical firms, including 

pro-forma income statements and balance sheets (see sample data in Table 17.5.1and Table 

17.1.1). Data related to costs and potential markups are available at the national level and for 

seven geographic regions. The HARDI geographic regions do not match with the rule-making 

regions. However, it is possible to assign the typical income statements to firms in each state in 

the HARDI regions and then develop weighted-average balance sheets for each rule-making 

region. 

Economic Census data is not as financially detailed but has greater geographic 

specificity. It is used to indicate variation of profitability around the regional averages, and 

whether border state establishments are significantly different than the regional average. 

To see how the impact of additional standards is calculated with an estimate of additional 

inventories, consider the model of a “typical” distributor in the Southeastern United States shown 

in Table 17.5.1. 

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Table 17.5.1 Typical Southeastern Wholesaler Assets, Liabilities, and Profitability 

Profit Margin Asset Turnover 

Profit before Taxes $457,467 Total Assets $9,842,389 

Net Sales $24,077,230 Net Sales $24,077,230 

Ratio 1.9% 2.45 

Income Statement Profit Before Taxes Assets Breakdown 

Cash and Marketable 

Net Sales $24,077,230 Securities $125,202 

Cost of Goods Sold $17,793,073 Accounts Receivable $2,783,329 

Gross Margin $6,284,157 Inventory $5,287,361 

Operating Expenses $5,874,844 Other $1,435,003 

Operating Profit $409,313 Total $9,630,895 

Other Income/Expenses $48,154 

Profit Before Taxes $457,467 

Financial Leverage Return on Net Worth 

Total Assets 

Total Net Worth 

$9,630,895 

$5,065,851 

Ratio 1.90 9.0% 

Original % of Asset 

Value Original Liabilities Modified Liabilities 

$2,224,736.75 

 $587,485 

 $760,841 

$3,573,062 

 $991,982 

 $4,565,044 

$5,065,851 

Accounts Payable 

Notes Payable 

Other Current 

Liabilities

Total Current Liabilities 

Long-Term Liabilities 

Total Liabilities 

Net Worth 

23.1% 

6.1%

 7.9% 

37.1% 

10.3% 

47.4%

52.6%

$2,224,737 

 $587,485

$760,841

$3,573,062 

$991,982

 $4,565,044

 $5,065,851 

SOURCE: HARDI Profit Report 2009 

The values in the shaded cells in Table 17.5.1 can be changed in percentage terms to 

estimate the sensitivity of profitability, as defined by return on net worth. Data are not currently 

available to perform comparable calculations on the costs of record-keeping and reporting 

activities (changes in operating expenses). 

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17.5.1.2 Sample Inventory Calculation for Southeastern Border CACHP Wholesaler 

A simple illustrative example follows in which a Southeastern border wholesaler 

financially looks like the typical firm in Table 17.5.1. The wholesaler makes half of its sales in 

its home region (Hot-Humid Region) and half in a different region (Rest of Country). The 

example border wholesaler is assumed to have the following characteristics: 

•	 Sales to dealers and contractors average 200 units a week, 100 in each region. 

•	 Sales of different efficiency products have the same approximate distribution as the 

national sales of split-system air conditioners. 

•	 Sales at each efficiency level follow a Poisson statistical distribution. 

•	 The wholesaler orders monthly from the manufacturer and keeps enough inventories on 

hand to meet quarterly sales forecasts. 

Based on Table 17.5.1, known manufacturer costs, and wholesale markups for CAC and 

CHP equipment, the assumed 200 units per week is close to the sales of a “typical” HARDI 

wholesaler in the southeastern United States in 2008. Based on HARDI information, an average 

order cycle of 4 weeks and forecast period of 14 weeks are reasonable. The average lead time 

from placement of order to receiving units for inventory is about 5.1 weeks. Wholesale markup 

factors are 1.37 and estimated delivered cost of a unit of inventory is $1,200. These values are 

consistent with observations that complete units constitute 70% of sales, that average stock 

turnover is 3.6 times per year, and the values of sales and inventories in Table 17.5.1. Sales are 

distributed as follows by efficiency level based on approximate national sales of split-system air 

conditioners (numerical results are somewhat affected by the percentages, but the general 

takeaway does not change with a different efficiency mix): 

•	 SEER 13: 81.0% 

•	 SEER 14: 6.0% 

•	 SEER 15: 5.0% 

•	 SEER 16: 5.0% 

•	 SEER 18 (above 16): 3.0% 

Sales at each efficiency level follow a Poisson statistical distribution. This distribution is 

commonly used in applied statistics to characterize the probability and number of comparatively 

rare observed events (for example, purchase of air conditioning units by a household) that occur 

in repeated samples (for example, weekly totals of sales). It is used frequently in studies of 

inventory and other logistics problems. A convenient attribute of a Poisson distribution is that the 

variance of the distribution equals its mean and therefore its standard deviation equals the square 

root of the mean. 

The wholesaler orders monthly from the manufacturer and keeps enough inventories on 

hand to meet quarterly sales forecasts. Because sales vary week to-week, the wholesaler’s 

“standard of service” is that it always carries enough inventory to meet a level of quarterly sales 

of any of its offered products at least two standard deviations above the mean, plus 1 unit. This 

gives the wholesaler a 98% chance of meeting any order. 

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Four cases showing different shifts in demand for CAC and CHP equipment are 

considered, driven by a SEER 14 minimum efficiency standard. 

•	 Case 1: SEER 14 is imposed in both regions. The result is a “rollup” of demand, which 

shifts all SEER 13 demand to SEER 14 without affecting weekly demand for SEER 15, 

16, or 18. SEER 14 sales change from 5 percent to 86 percent of sales in both regions 

after the shift. SEER 15, 16, and 18 sales are unaffected 

•	 Case 2: SEER 14 is imposed only in the Hot-Humid Region, while SEER 13 remains the 

standard in the Rest of Country region. The impact on demand is a “rollup” but only in 

the Hot-Humid region. 

•	 Case 3: Same as Case 1, but the percentages of sales at levels above SEER 14 are 

significantly affected (efficiency distribution shift). The average distribution in both 

regions after the SEER 14 standard is imposed are: 

o	 SEER 13: 0.0% 

o	 SEER 14: 49.0% 

o	 SEER 15: 23.0% 

o	 SEER 16: 15.0% 

o	 SEER 18: 13.0% 

•	 Case 4: Same as Case 3, but the new after-standard sales percentage percentages apply 

only in the Hot-Humid region. 

The results of this analysis for these four cases are shown in Table 17.5.2. 

Table 17.5.2 Border Wholesaler Required Inventory 

Scenario No. Units in Inventory 

Base Case 3380 

Case 1 3355 

Case 2 3400 

Case 3 3400 

Case 4 3425 

Impact of Regional Standards on Value of Inventories 

Rollup (Case 2 / Case 1) 1.3 % Increase 

Shift (Case 4 / Case 3) 0.7 % Increase 

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The base case scenario shows the inventory holdings required if there are no changes in 

the efficiency standard. The wholesaler must hold 3380 units in inventory in order to meet the 

“standard of service” conditions of the model. 

Case 1 shows the impact of a single national standard with a rollup scenario. In this case, 

SEER 13 units are no longer sold, and it is no longer necessary to stock them. There is some 

compensating increase in inventory for SEER 14 units, but the overall inventory service is 

simpler and the inventory stock drops. 

 Case 2 corresponds to a regional standard with a rollup scenario. It is still necessary for 

the border wholesaler to stock slightly more than half as many SEER 13 units as before to serve 

the Rest of Country, although these units can no longer be sold in the Hot-Humid region. In 

addition, more SEER 14 inventory must be carried to serve both regions. The net difference of 

Case 1 from the Base Case is 0.7 percent less inventory in this example due to the savings of 

SEER 13 inventory; however, Case 2 (regional standard) requires about 1.3 percent more 

inventory than Case 1 (national standard). 

Case 3 corresponds to a single national standard with a market shift scenario. The 

national standard in Case 3 spreads the increases in sales of efficient equipment over several 

efficiency levels that previously had low sales, so the overall required inventories go up slightly 

compared with the Base Case (about 0.6 percent). 

Case 4 corresponds to a regional standard with a market shift scenario. This case requires 

0.7 percent more inventory than Case 3. 

17.5.1.3 CACHP Profitability Calculation 

The increases in required physical units of inventory thus appear to be on the order of 1 

to 2 percent higher for a regional standard than with a national standard for distributors serving 

two regions. Table 17.5.3 and Table 17.5.4 present the modeled impacts of these inventory 

changes on ‘profit as a percentage of total sales’ and on ‘return on net worth,’ respectively. The 

tables also present the impacts of changes in inventory changes that are twice as large (4 percent 

increase) and five times as large (10 percent increase) to demonstrate the sensitivity of 

profitability to such changes. 

The values in Table 17.5.3 and Table 17.5.4 are derived from the model in Table 17.5.1 by 

assuming increases to inventory and the associated increase in interest expense necessary to 

finance that additional working capital. Additionally, for illustrative purposes, DOE applied a 

range of interest rates for the capital required to finance the additional inventory. 

Table 17.5.3 indicates that the impacts of additional inventory on profitability are not 

observable at one percent and two percent inventory change, except at the highest modeled 

interest rates. Table 17.5.3 also indicates that an inventory increase of 10 percent financed at 12 

percent interest could reduce pretax margins by approximately 20 basis points, a decline of 

approximately 10 percent. 

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Table 17.5.3 Profitability Impacts of CACHP Inventory Cost Increases 

Profit before Taxes (% of Sales) 

% Change in Inventory 

Interest Rate for Inventory 0% 1% 2% 4% 10% 

6% 1.9% 1.9% 1.9% 1.8% 1.8% 

8% 1.9% 1.9% 1.9% 1.8% 1.7%

10% 1.9% 1.9% 1.9% 1.8% 1.7%

12% 1.9% 1.9% 1.8% 1.8% 1.7%

 Table 17.5.4 shows the impact of inventory changes on distributor Return on Net Worth, 

which is calculated as pretax profit divided by net worth, where net worth equals assets less 

liabilities. At the expected one to two percent inventory change, impacts on return on net worth 

are again small. However, the impacts could be significant for distributors with high borrowing 

costs and where there are significantly higher inventory requirements. 

Table 17.5.4 Return on Net Worth Impacts of CACHP Inventory Cost Increases 

Return on Net Worth 

% Change in Inventory 

Interest Rate for Inventory 0% 1% 2% 4% 10% 

6% 9.0% 9.0% 8.9% 8.8% 8.4% 

8% 9.0% 8.9% 8.9% 8.7% 8.2%

10% 9.0% 8.9% 8.8% 8.6% 8.0%

12% 9.0% 8.9% 8.8% 8.5% 7.5%

17.5.1.4 Sample Furnace Inventory Calculation for Border Wholesalers 

Following the methodology above, it is possible to estimate changes in Furnace inventory 

in the border region resulting from both national and regional standards based on HARDI 

financial data. As shown in Table 17.5.5, this approach suggests that a regional standard will not 

significantly increase Furnace inventories. 

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Table 17.5.5 Number of Units of Inventory of Furnaces in the Border Region 

Base Case National Standard 

Case 

Regional Standard 

Case 

Condensing 852 1667 1667 

Non-Condensing 2476 1667 1667 

Total 3328 3334 3334 

Source: HARDI Profit Report 2009 , “Regional Analysis” distributors 

As the standard increases beyond 80% AFUE, there is a significant change in the inventory 

ratio of condensing to non-condensing furnace units. However, the introduction of regional 

standards does not require inventories that are different from a national standard. 

17.5.1.5 Furnace Profitability Calculation 

DOE conducted an additional sensitivity analysis of the impact of a change in 

distributors’ inventory needs. Based on Table 17.6.16 and Table 17.6.17, DOE estimated the 

financial expenditure and profit figures for furnace distributors operating in border states. Then, 

following the process outlined in Section 17.5.1.3 “CACHP Profitability Calculation,” the 

impact of inventory changes on firm profitability (measured as pretax income/sales and return on 

net worth) are examined at a range of interest rates. 

 Table 17.5.6 and Table 17.5.7 provide detailed estimates of the distributor profitability 

impact of inventory cost changes. Generally, this analysis suggests that carrying a slightly larger 

inventory may slightly decrease firm pre-tax profits and return on net worth in the short run. 

Table 17.5.6 Profitability Sensitivity Analysis for Furnaces in Border States 

Pretax Income (% of Sales) 

% Change in Inventory 

Interest Rate for Inventory 0% 1% 2% 4% 10% 

6% 1.7% 1.7% 1.7% 1.7% 1.6% 

8% 1.7% 1.7% 1.7% 1.7% 1.6%

10% 1.7% 1.7% 1.7% 1.6% 1.5%

12% 1.7% 1.7% 1.7% 1.6% 1.5%

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Table 17.5.7 Return on Net Worth Analysis for Furnaces in Border States 

Return on Net Worth 

% Change in Inventory 

Interest Rate for Inventory 0% 1% 2% 4% 10% 

6% 12.9% 12.8% 12.7% 12.6% 12.1% 

8% 12.9% 12.8% 12.7% 12.5% 11.8%

10% 12.9% 12.8% 12.6% 12.4% 11.5%

12% 12.9% 12.7% 12.6% 12.3% 11.3%

17.5.2	 Preliminary Analysis of the Impacts of Regional Standards on Furnace and CACHP 

markups 

17.5.2.1 Furnace Markups 

During the 2007 Furnace rulemaking, DOE proposed two regional standards for furnaces, 

divided between north and south. The Northern region represents those states with average HDD 

greater or equal to 5,000 and southern region represents those states with average HDD less than 

5,000. In the preliminary analysis, distributors and contractors in the furnace industry are divided 

into north, south and border region subgroups. The impact of regional standards is expected to be 

stronger on distributors and contractors located close to the border region than on firms located 

far from the border region. Thus, for the purpose of addressing the impact of differentiated 

regional standards, we focus on the change in markups to firms located (1) far from the border 

and (2) near the border. 

17.5.2.2 Firm Markups Far From the Border Region 

In the section, DOE analyzes how markups might change for firms located far from border 

regions. DOE first addresses such firms in the northern region and then looks at those in the 

southern region. According to a report published by Energy Center of Wisconsin in 1997, the 

percentage of high efficiency furnaces sold in Wisconsin was approximately 70% of all units 

1996.a

 The historical data from GAMA 2005 also supports this statement, indicating that 

Wisconsin has the highest average saturation rate of condensing furnaces in the country.b

 Since 

high efficiency furnaces currently dominate the Wisconsin market to a degree expected in the 

rest of the Northern Region following regional standards, markups in Wisconsin are used to 

predict markups in the rest of the Northern region. Table 17.5.8 below compares the weighted 

average baseline markup in the Northern region and in Wisconsin. 

a

 For this report, high efficiency furnace has an AFUE of at least 90%. 

b

 In GAMA report, condensing furnace is defined as those having an AFUE of at least 88%. 

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Table 17.5.8 Northern Region Markups 

Region Distributor 

Markup 

Mechanical Contractor 

Markup 

General Contractor 

Markup 

Northern Region 1.38 1.36 1.21 

Wisconsin 1.37 1.33 1.16 

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US 

Economic Census 

The average baseline markup in Wisconsin is lower than the baseline markup in the 

Northern region for distributors, mechanical contractors and general contractors. DOE assumes 

that Wisconsin has completed a transition from providing a mix of low and high efficiency 

furnaces in the past to providing primarily high efficiency furnaces today. As a result, 

Wisconsin firms have lower markups than firms in other Northern states. Assuming a future 

regional standard that requires high-efficiency furnaces in the north like those that exist in 

Wisconsin, DOE expects that all firms in the Northern region will have inventories and markups 

similar to those currently in Wisconsin. 

In Southern States, high efficiency furnaces are not as widely used as in Northern states. 

The condensing furnace saturation rate in the South already reaches 14% and this saturation rate 

is not expected to change after regional standards take effect.35 Thus, higher standards in the 

South are not expected to have a significant impact on firm inventories or markups in that region. 

Here Oklahoma is used as a reference case; 15% of the furnaces sold in Oklahoma are 

condensing furnaces, similar to the expected saturation of the South after regional standards take 

effect. Table 17.5.9 summarizes the results: 

Table 17.5.9 Southern Region Markups 

Region Distributor 

Markup 

Mechanical Contractor 

Markup 

General Contractor 

Markup 

Southern Region 1.35 1.35 1.24 

Oklahoma 1.35 1.35 1.24 

 Source: HARDI Profit Report 2008, “Regional Analysis” distributors and 2002 US Economic Census 

As shown above, there is currently no difference between markups in Oklahoma and the 

rest of the Southern region. This implies that regional standards are not likely to impose 

significant impacts on the Southern region because the existing mixture of condensing and noncondensing furnaces already sufficiently reflects the steady state of long run impact. 

We conclude that the regional standards will not greatly impact firms located in far from 

the border region. In both the Northern and Southern regions, this analysis indicates that 

standards will not require higher inventories and therefore are not likely to bring about changes 

in markups. 

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17.5.2.3 Border Region Markups 

Under regional standards, distributors located near the border between standards regions 

may have to sell equipment meeting different standards in the two regions and need to carry 

more inventories or manage their inventory differently to meet the separate needs of customers in 

each region. DOE highlights these impacts by assuming that firms located in the border region 

of each State have sales, inventories, and markup practices similar to those of firms in the rest of 

that State. 

Based on the data below, DOE assumes most of the firms in the northern part of the border 

region already maintain a mix of more high efficiency and less low efficiency furnaces, so 

regional standards are unlikely to impose any additional changes on inventory costs to these 

firms. Saturation rates of condensing furnaces in the Northern border region from GAMA Report 

2005 (Table 17.5.10) show that the sale of condensing furnaces in these States increased 

noticeably from 1997 to 2003. Therefore, the current markups in this region could be considered 

as the upper bound of the future markups because of the possible simplification of inventories 

resulting from regional standards. Only firms in the southern part of the border region are likely 

to be significantly affected by the standards. These firms currently sell mostly low efficiency 

furnaces and new regional standards could force them to carry a mix of more high efficiency (to 

serve their cross-border market) and fewer low efficiency furnaces, as shown in Table 17.5.11. 

As a result, they may incur higher inventory costs from storing more high efficiency furnaces. 

Table 17.5.10 Saturation Rate of Condensing Furnaces in the Northern Border Region 

State 1997 1998 1999 2000 2001 2002 2003 

PA 45.26% 46.79% 43.20% 45.54% 49.12% 50.45% 55.28% 

IN 25.69% 28.60% 27.51% 29.61% 35.83% 35.29% 44.87% 

IL 27.40% 26.91% 26.96% 23.71% 32.23% 32.50% 36.15% 

UT 30.41% 27.57% 26.68% 25.99% 29.93% 27.43% 28.24% 

KS 24.12% 23.64% 21.87% 23.86% 32.90% 26.11% 29.59% 

NJ 23.15% 25.11% 26.91% 23.52% 28.42% 31.96% 40.68% 

ID 22.14% 22.53% 23.90% 25.58% 30.18% 30.85% 35.58% 

OR 21.95% 22.18% 21.11% 20.88% 26.96% 27.04% 28.45% 

MO 27.63% 29.28% 29.11% 28.65% 4.11% 2.85% 2.46% 

CO 9.74% 9.07% 9.96% 9.70% 14.43% 15.96% 21.77% 

Source: GAMA Report 2005 

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Table 17.5.11 Saturation Rate of Condensing Furnaces in the Southern Border Region 

State 1997 1998 1999 2000 2001 2002 2003 

KY 34.00% 32.73% 32.09% 34.17% 39.86% 39.05% 46.72% 

AZ 8.73% 9.55% 8.33% 9.14% 10.71% 15.27% 15.67% 

CA 9.27% 6.34% 6.08% 6.33% 11.14% 11.19% 12.04% 

OK 4.55% 5.49% 6.91% 6.55% 10.09% 9.21% 10.39% 

NV 7.36% 5.45% 6.09% 5.12% 6.57% 10.45% 12.32% 

AR 5.21% 2.97% 2.77% 3.01% 4.86% 5.36% 6.27% 

NM 4.82% 2.86% 3.13% 1.77% 2.61% 3.18% 5.14% 

Source: GAMA Report 2005 

Table 17.5.12 Border Region Markups 

Region Distributor 

Markup 

Mechanical Contractor 

Markup 

General Contractor 

Markup 

Northern part of the 

border region 

1.38 1.36 1.21 

Southern part of the 

border region 

1.35 1.35 1.24 

Average border region 1.36 1.36 1.27 

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US 

Economic Census 

The average border region markups shown in Table 17.5.12 are the weighted average 

markups using the fractions of distributors and contractors located in the metropolitan areas 

within the designed border region in each border state. The numbers shown here reflect existing 

markups instead of predicted markups; however, the differences with northern border region 

markups and southern border regional markups provide a sense of what the potential impact will 

be in these two sub-border regions respectively. Based on the analysis above, markups in the 

Northern part of the border region are expected to remain the same as the rest of the current 

Northern region markups in the short run. As for the Southern part of the border region, markups 

are expected to increase due to higher inventory costs from having to serve a greater mix of 

product. In the long run, markups in both parts of the border are expected to converge to one 

single border markup. Markups in the Northern part of the border may stay at the current upper 

bound level or slightly decrease to the level that meets the long-term southern border region 

markups due to the possible product simplification in the North. Thus, the future border region 

markups are predicted to be bounded between current northern border markups and southern 

border markups. 

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17.5.2.4 Central Air Conditioners and Heat Pumps 

In the CACHP rulemaking, DOE described potential regional standards for three climatic 

regions: Hot-Humid, Hot-Dry and Rest of the country. Theoretically, an analogical method 

similar to that used for furnaces above could be adopted for CACHP. However, DOE lacks the 

regional CACHP efficiency data needed to conduct that analysis. DOE calculated regional 

markups for distributors, mechanical contractors and general contractors in the CACHP market, 

and the results are summarized in Table 17.5.13. DOE requests comment on how these markets 

will change for regional standards. 

Table 17.5.13 Central Air Conditioner and Heat Pump Markups 

Region Distributor 

Markup 

Mechanical Contractor 

Markup 

General Contractor 

Markup 

Hot-Humid 1.33 1.34 1.24 

Hot-Dry 1.37 1.37 1.22 

Rest of the country 1.37 1.36 1.23 

Source: HARDI Profit Report 1999, 2002, 2005, 2008, 2009, “Regional Analysis” distributors and 2002 US 

Economic Census 

17.6 ADDITIONAL DISTRIBUTOR DATA 

Tables detailing the number of establishments, total and average sales, and total and 

average employment (2002 Economic Census) follow for each region. Sample distributors data 

are shown in Table 17.6.16. Please note that the basis for the count of establishments and all 

other associated data concepts is based on self-reporting for the Economic Census, while there is 

some reliance on administrative records for County Business patterns. Thus these two data 

sources may report different values for the same data concept in the same year. For example, the 

Census Bureau notes that: “some large companies report different activities at the same location 

as separate profit centers. The County Business Patterns program treats each profit center as a 

separate establishment. The 2002 Economic Census may combine the profit centers into one 

establishment. This results in establishment count differences.” Thus, data for the number of 

establishments, employment per establishment, and payroll in Table 17.6.4 do not necessarily 

match those in Table 17.6.13 for 2002. Similar comparability issues arise in other tables where 

Economic Census and County Business Patterns data overlap. 

17-32 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 17.6.1 Distributor Enterprise Statistics for Hot-Humid Region (2002) 

Region Number of 

Establishments* 

Total Sales 

($1,000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Hot-Humid 

Region 

1,608 8,727,826 5,428 17,284 10.7 

Border States 916 6,528,439 7,127 11,762 12.8 

Texas 472 3,503,698 7,423 5,144 10.9 

Oklahoma 79 N/A N/A N/A N/A 

Arkansas 61 821,723 13,471 610 10.0 

Tennessee 152 1,422,277 9,357 4,042 26.6 

North Carolina 231 780,741 3,380 1,966 8.5 

*Because Alabama, Georgia and Oklahoma are incomplete data sets, they have been excluded from the total count of 

establishments. 

SOURCE: 2002 Economic Census 

Table 17.6.2 Distributor Enterprise Statistics for Hot-Dry Region (2002) 

Region Number of 

Establishments 

Total Sales 

($1,000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Hot-Dry 

region 

556 2,415,481 4,344 5,502 9.9 

Border 

States 

556 2,415,481 4,344 5,502 9.9 

Arizona 94 475,254 5,056 1,168 12.4 

California 391 1,707,447 4,367 3,777 9.7 

Nevada 46 172,035 3,740 430 9.3 

New 

Mexico 

25 60,745 2,430 127 5.1 

SOURCE: 2002 Economic Census 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 17.6.3 Distributor Enterprise Statistics for Rest of Country (2002) 

Region Number of 

Establishments* 

Total Sales 

($1,000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Rest of 

Country 

2,480 9,669,627 3,899 24,504 9.9 

Border 

States 

615 2,807,946 4,566 6,362 10.3 

Colorado 75 466,041 6,214 804 10.7 

Idaho 30 63,920 2,131 180 6.0 

Kansas 47 163,282 3,474 541 11.5 

Kentucky 87 364,016 4,184 1,045 12.0 

Missouri 122 709,542 5,816 1,407 11.5 

Oregon 50 354,704 7,094 562 11.2 

Utah 48 170,744 3,557 492 10.3 

Virginia 156 515,697 3,306 1,331 8.5 

*Because Iowa, Massachusetts, New Jersey, New Hampshire, North Dakota, and Rhode Island are incomplete data sets, they 

have been excluded from the total count of establishments. 

SOURCE: 2002 Economic Census 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 17.6.4 Establishments, Employment, and Payroll Trends in Hot-Humid Region 

Region Number of 

Establishments* 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Hot-Humid 

Region 

2,057 2,017 11 10 461 502 

Border States 1,007 1,032 13 10 570 552 

 Texas 532 498 12 12 550 674 

 Oklahoma 94 77 7 6 277 266 

 Arkansas 55 78 N/A 7 N/A 307 

 Tennessee 145 166 27 11 1,177 575 

North 

Carolina 

236 213 9 8 361 443 

*Because Arkansas is an incomplete data set, it has been excluded from the total count of establishments 

Table 17.6.5 Establishments, Employment, and Payroll Trends in Hot-Dry Region 

Region Number of 

Establishments* 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Hot-Dry region 544 545 10.1 11.9 508 636 

Border States 544 545 10.1 11.9 508 636 

Arizona 88 93 13.2 12.8 603 701 

California 415 387 9.5 10.9 493 608 

Nevada 41 43 10.1 21.8 463 835 

New Mexico 24 22 N/A 6.7 N/A 452 

*Because New Mexico is an incomplete data set, it has been excluded from the total count of establishments 

17-35 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 17.6.6 Establishments, Employment, and Payroll Trends in Rest of Country 

Region 

Number of 

Establishments* 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Rest of 

Country 

2857 2851 10.1 10.2 499 574 

Border States 657 606 10.1 10.8 470 577 

Colorado 83 70 10.9 10.7 537 614 

Idaho 31 24 6.6 8.8 237 164 

Kansas 56 56 10.8 12.0 508 434 

Kentucky 110 86 11.5 12.8 470 659 

Missouri 121 129 11.1 10.2 603 616 

Oregon 56 47 11.3 14.3 526 715 

Utah 42 48 9.5 11.9 439 573 

Virginia 158 146 8.1 8.7 352 432 

*Because Iowa, Massachusetts, New Jersey, New Hampshire, North Dakota, and Rhode Island are incomplete data sets, they 

have been excluded from the total count of establishments. 

Cost structure and profitability for distributors vary among the regions as shown in Table 17.6.7 

through Table 17.6.12 are derived from 2008 HARDI data. Variation also occurs within the 

regions among subareas, e.g. border states (2002 Census), as illustrated in Table 17.6.13 through 

Table 17.6.15. 

17-36 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

   

Table 17.6.7 Income Statement Items, Typical CACHP Distributors, Hot–Humid Region 

Income Statement 

Net Sales $21,818,352 

Cost of Goods Sold $16,094,671 

Gross Margin $5,723,681 

Operating Expenses $5,343,678 

Operating Profit $380,003 

Other Income/Expenses $109,092 

Profit Before Taxes $378,185 

Profit as a % of Sales 1.7% 

SOURCE: HARDI Data 

Table 17.6.8 Balance Sheet, Typical CACHP Distributors, Hot-Humid Region 

Assets Liabilities 

Cash $130,254 Accounts Payable $1,670,615 

Accounts Receivable $2,423,599 Notes Payable $1,036,908 

Inventory $4,854,516 Other Current Liabilities $633,707 

Other $162,451 Total Current Liabilities $3,341,230 

Total $8,781,157 Long-Term Liabilities $717,860 

Total Liabilities $4,059,090 

Net Worth $4,722,067 

Profit as a % of Net Worth 8.0% 

SOURCE: HARDI Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

   

Table 17.6.9 Income Statement Items, Typical CACHP Distributors, Hot–Dry Region 

Income Statement 

Net Sales $16,811,857 

Cost of Goods Sold $12,085,323 

Gross Margin $4,726,533 

Operating Expenses $4,309,599 

Operating Profit $466,529 

Other Income/Expenses $109,757 

Profit Before Taxes $416,093 

Profit as a % of Sales 2.5% 

SOURCE: HARDI Data 

Table 17.6.10 Balance Sheet, Typical CACHP Distributors, Hot-Dry Region 

Assets Liabilities 

Cash $219,485 Accounts Payable $835,161 

Accounts Receivable $1,666,602 Notes Payable $1,225,771 

Inventory $3,731,253 Other Current Liabilities $308,768 

Other $182,285 Total Current Liabilities $2,369,699 

Total $7,440,186 Long-Term Liabilities $370,149 

Total Liabilities $2,739,849 

Net Worth $4,700,338 

Profit as a % of Net Worth 8.9% 

SOURCE: HARDI Data 

17-38 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

   

Table 17.6.11 Income Statement Items, Typical CACHP Distributors, Rest of Country 

Income Statement 

Net Sales $28,362,901 

Cost of Goods Sold $20,506,377 

Gross Margin $7,856,524 

Operating Expenses $7,005,637 

Operating Profit $703,400 

Other Income/Expenses $198,540 

Profit Before Taxes $650,726 

Profit as a % of Sales 2.29% 

SOURCE: HARDI Data 

Table 17.6.12 Balance Sheet, Typical CACHP Distributors, Rest of Country 

Assets Liabilities 

Cash $208,790 Accounts Payable $1,391,081 

Accounts Receivable $2,913,118 Notes Payable $1,153,316 

Inventory $5,488,196 Other Current Liabilities $725,794 

Other $208,790 Total Current Liabilities $3,121,908 

Total $9,942,383 Long-Term Liabilities $60,648,537 

Total Liabilities $3,728,394 

Net Worth $6,213,989 

Profit as a % of Net Worth 10.472% 

SOURCE: HARDI Data 

17-39 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 17.6.13 Revenue and Cost Items, Typical CACHP Distributors, Hot-Humid Region 

and Border States 

Region Average Sales 

per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Average 

Operating 

Costs 

($1,000) 

Average 

Inventory 

($1,000) 

Hot-Humid Region 5,428 453 822 545 

Border States 7,127 553 1,035 664 

 Texas 7,423 496 982 584 

 Oklahoma N/A N/A N/A N/A

 Arkansas 13,471 396 663 300 

 Tennessee 9,357 1,112 2,077 1,528 

 North Carolina 3,380 342 557 352 

*Because Alabama, Georgia and Oklahoma are incomplete data sets, they have been excluded from the total count of 

establishments. 

SOURCE: Economic Census Data 

Table 17.6.14 Revenue and Cost Items, Typical CACHP Distributors, Hot-Dry Region and 

Border States 

Region Average 

Sales per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Average 

Operating 

Costs 

($1,000) 

Average 

Inventory 

($1,000) 

Hot-Dry region 4,344 483 810 520 

Border States 4,344 483 810 520 

Arizona 5,056 548 875 774 

California 4,367 490 837 478 

Nevada 3,740 409 687 467 

New Mexico 2,430 252 365 307 

SOURCE: Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 17.6.15 Revenue and Cost Items, Typical CACHP Distributors, Rest of Country 

Region and Border States 

Region Average 

Sales per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Average 

Operating 

Costs 

($1,000) 

Average 

Inventory 

($1,000) 

Rest of Country 3,899 450 755 437 

Border States 4,566 456 781 460 

Colorado 6,214 514 1,003 477 

Idaho 2,131 225 428 259 

Kansas 3,474 537 801 344 

Kentucky 4,184 435 721 365 

Missouri 5,816 614 1,018 640 

Oregon 7,094 478 854 664 

Utah 3,557 448 675 416 

Virginia 3,306 330 591 437 

*Because District of Columbia, Iowa, Massachusetts, Minnesota, New Jersey, New Hampshire, North Dakota, and Rhode Island 

are incomplete data sets, they have been excluded from the total count of establishments. 

SOURCE: Economic Census Data 

17-41 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table 17.6.16 Distributor Financial Data by HARDI Region for 2009 

South South 

North Eastern Mid-Atlantic Eastern Great Lakes Central Western Western 

Number of Firms Reporting 8 16 10 19 27 8 6 

Typical Sales Volume $19,851,509 $42,068,508 $24,077,238 $20,107,850 $28,362,901 $17,946,312 $16,762,766 

Sales Change (2007-2008) -0.60% -0.10% -2.60% 1.20% 0.50% 0.20% -3.70% 

Strategic Profit Model Ratios 

Profit Margin 1.00% 1.60% 1.90% 2.20% 3.10% 1.10% 3.10% 

Asset Turnover 2.9 3 2.5 2.5 2.4 2.6 2.2 

Return on Assets 2.90% 4.80% 4.70% 5.50% 7.40% 2.90% 6.80% 

Financial Leverage 2.3 2.2 1.9 2.1 1.6 1.9 1.5 

Return on Net Worth 6.70% 10.60% 8.00% 11.50% 11.80% 5.50% 10.20% 

Income Statement 

Net Sales 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 100.00% 

Cost of Goods Sold 70.3 73.9 73.9 72.2 72.3 74.3 70.7 

Gross Margin 29.7 26.1 26.1 27.8 27.7 25.7 29.3 

Payroll Expenses 

Executive Salaries & Bonuses 2.1 1.5 2.1 2.1 2.1 2.2 1.8 

Branch Manager Salaries & 

Bonuses 1.3 1.1 1.2 1.3 1.3 1.8 1.4 

Sales Executive Salaries & 

Commissions 0.8 0.5 0 0.3 0.3 0.9 0.5 

Outside Sales Salaries & 

Commissions 2.7 2.1 2.3 2.3 2.3 1.8 1.7 

Inside/Counter Sales Wages 2.1 2.5 2.9 2.8 2.6 2.2 2.9 

Purchasing Salaries/Wages 0.5 0.4 0.5 0.4 0.5 0.5 0.6 

Credit Salaries/Wages 0.3 0.2 0.1 0.1 0.2 0.2 0.2 

IT Salaries/Wages 0 0.2 0 0.1 0.2 0.1 0.2 

Warehouse Salaries/Wages 2.3 1.4 2.1 1.6 1.3 1.5 1.7 

Accounting Salaries/Wages 0.6 0.4 0.6 0.4 0.6 0.4 0.7 

Delivery Salaries/Wages 1.1 1.2 0.7 0.7 0.8 0.8 1 

All Other Salaries/Wages & 

Bonuses 0.8 0.9 0.6 0.8 0.6 0.7 0.5 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

 

 

 

 Total Salaries, Wages, 

Bonuses 14.6 12.6 13.1 12.9 12.8 13.1 13.2 

Payroll Taxes (FICA, unemp., 

workers' comp.) 1.5 1 1.2 1.1 1.1 1 1.1 

Group Insurance (medical, 

hospitalization, etc.) 1.2 1.5 1.1 1.2 1.1 1 1.2 

Benefit Plans (profit sharing, 

pension, etc.) 1 0.4 0.3 0.3 0.7 0.3 0.5 

Total Payroll Expenses 18.3 15.3 15.7 15.5 15.7 15.4 16 

Occupancy Expenses 

Utilities (heat, light, power, 

water) 0.5 0.4 0.4 0.5 0.4 0.4 0.4 

Telephone 0.3 0.3 0.4 0.4 0.3 0.3 0.5 

Building Repairs & 

Maintenance 0.3 0.2 0.2 0.4 0.2 0.2 0.2 

Rent or Ownership I Real 

Estate 2.6 2.6 2.3 2.6 2.6 2.4 3.1 

Total Occupancy 

Expenses 3.7 3.5 3.3 3.9 3.5 3.3 4.2 

Other Operating Expenses 

Sales Expenses 1.1 0.4 0.5 1 1 0.5 1 

Insurance 0.1 0.2 0.3 0.2 0.2 0.2 0.2 

Depreciation 0.5 0.3 0.2 0.4 0.3 0.3 0.3 

Vehicle Expenses 1.9 1.3 1.2 1.3 1.2 1.4 1.3 

Personal Property 

Taxes/Licenses 0.1 0.1 0.1 0.1 0.1 0.4 0.2 

Collection Expenses 0.2 0.2 0.2 0.3 0.2 0.3 0.6 

Bad Debit Losses 0.8 0.5 0.5 0.3 0.4 0.5 0.6 

Data Processing 0.1 0.1 0.2 0.3 0.1 0.2 0.3 

Employee Training 0.1 0 0.1 0.1 0 0 0 

All Other Operating Expenses 1.5 2.4 2.1 1.7 2 1.8 1.2 

Total Other Operating 

Expenses 6.4 5.5 5.4 5.7 5.5 5.6 5.7 

Total Operating Expenses 28.4 24.3 24.4 25.1 24.7 24.3 25.9 

Operating Profit 1.3 1.8 1.7 2.7 3 1.4 3.4 

Other Income 0.7 0.4 0.6 0.85 0.7 0.3 0.6 

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EERE-2008-BT-STD-0006 COMMENT 54
Interest Expense 0.7 0.6 0.4 0.9 0.6 0.6 0.9 

Other Non-operating Expenses 0 0 0 0.41 0 0 0 

Profit Before Taxes &
 

Discretionary Bonuses 1.3 1.6 1.9 2.2 3.1 1.1 3.1 

Owners' & Officers' 

Discretionary Bonus 0.3 0 0 0 0 0 0 

Profit Before Taxes 1.00% 1.60% 1.90% 2.20% 3.10% 1.10% 3.10% 

Source: HARDI Profit Report 2009 

17-44 

EERE-2008-BT-STD-0006 COMMENT 54
Table 17.6.17 Geographic Area Series, Hardware, Plumbing, and Heating Equipment 

Merchant Wholesalers 

State Number of 

establishments 

Sales 

($1,000) 

Annual 

payroll 

($1,000) 

Operating 

expenses 

($1,000) 

Beginning 

of Year 

Inventory 

($1,000) 

Alabama 306 1,223,718 126,231 219,926 163,992 

Alaska 31 184,756 18,121 30,881 17,215 

Arizona 344 1,555,529 144,201 262,373 207,328 

Arkansas 169 1,577,287 68,528 112,045 91,665 

California 2,093 9,770,865 1,035,007 1,859,068 1,255,661 

Colorado 322 1,593,598 158,231 279,359 163,671 

Connecticut 241 1,238,563 159,154 279,517 109,123 

Florida 1,280 3,918,873 421,244 760,139 578,251 

Hawaii 73 206,004 23,882 44,417 24,540 

Idaho 102 219,215 23,060 45,551 29,404 

Illinois 938 5,750,240 546,503 982,350 711,919 

Indiana 414 3,396,118 208,166 357,442 230,198 

Iowa 183 559,770 72,145 126,079 90,495 

Kentucky 211 738,568 81,571 141,007 72,962 

Louisiana 255 620,835 77,327 133,347 71,160 

Maine 78 280,267 33,846 50,711 36,874 

Maryland 343 1,440,771 175,311 300,946 157,414 

Massachusetts 418 1,626,690 230,519 372,701 205,585 

Michigan 624 2,455,784 307,000 554,638 346,760 

Minnesota 353 1,730,533 188,264 320,040 206,794 

Mississippi 142 290,404 32,238 53,345 33,450 

Missouri 373 1,904,740 190,634 342,332 204,189 

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EERE-2008-BT-STD-0006 COMMENT 54
Montana 60 188,933 22,151 37,160 25,178 

Nebraska 135 476,152 55,311 91,961 62,781 

Nevada 143 581,330 63,655 112,143 76,965 

New Mexico 97 222,570 24,992 40,809 26,685 

New York 1,150 3,890,419 477,194 827,149 490,905 

North Carolina 653 2,529,035 275,455 519,139 339,490 

North Dakota 51 246,502 19,359 33,087 29,214 

Ohio 797 3,506,149 411,644 772,598 470,068 

Oklahoma 259 1,811,538 114,841 163,518 89,065 

Oregon 232 1,024,631 95,172 179,566 103,318 

Pennsylvania 830 3,013,246 377,209 662,680 387,216 

Rhode Island 65 553,057 39,277 119,343 71,139 

South Carolina 275 1,469,195 105,672 218,044 150,214 

South Dakota 62 187,376 22,113 37,867 31,395 

Tennessee 379 2,315,179 275,360 482,817 285,502 

Texas 1,470 6,923,744 627,464 1,151,278 729,352 

Utah 172 659,361 75,092 122,588 56,829 

Vermont 43 145,259 15,814 31,678 22,770 

Virginia 444 1,696,293 173,599 334,708 184,142 

Washington 443 1,630,891 181,491 306,265 199,740 

West Virginia 90 216,126 23,579 42,842 30,321 

Wisconsin 349 2,175,191 199,934 380,668 233,187 

Wyoming 23 34,617 3,355 6,475 3,018 

Source: 2002 U.S. Economic Census, Geographic Area Series, Hardware, Plumbing & Heating Equipment & Supply Merchant 

Wholesalers 

17-46 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

17.7 ADDITIONAL CONTRACTOR DATA 

The analysis of general and mechanical contractors relies on the 2002 Economic Census 

and 2007 County Business Patterns as sources of information. As discussed previously, general 

contractors and mechanical contractors have different roles in the distribution channels for CAC 

and CHP equipment. Data is reported separately for general contractors and for mechanical 

contractors so that the economic impact of regional efficiency standards and their enforcement 

can be better judged for each contractor type. The following information can be obtained from 

these sources: 

•	 Total and average sales, total and average employment (2002 Census of Business and 

County Business Patterns). 

No industry-published equivalent of the HARDI data appears to exist for 

dealers/contractors/installers. These values are reported for the 2002 Economic Census 

and 2007 County Business Patterns for 2007 for the Nation, each region (Hot-Humid, 

Hot-dry, and Rest of Country), and for each of the 17 states that lie on the border of one 

region with another. 

Data from the 2002 Economic Census includes all plumbing, heating, and airconditioning contractors. The total industry accounted for $118,740,885,000 of business 

in 2002, of which $49,425,445,000 was attributed to the HVAC contractor subsector.36 

Data from the entire plumbing, heating, and air-conditioning contractors industry was 

used, as the 2002 Economic Census provided state-level data for this industry but not for 

the HVAC contractor subsector. The 2002 Economic Census state-level data for all of 

the construction industry (NAICS 2-digit level) shows, among other things, which states’ 

construction industry sales are in other states as compared with the home state 

(construction in Kentucky by Ohio construction establishments). This data is used to 

indicate where cross-border sales are important for the three CAC analysis regions. 

•	 Number of small businesses (SBA definition and size distribution). 

The SBA definition of small business defines $33.5 million in annual sales as the 

maximum for building contractors (both residential and commercial, which together are 

the general contractors of interest for CAC and CHP rulemaking) and $14 million in 

annual sales as the maximum for plumbing, heating, and A/C contractors. Among 

general contractors’ residential construction establishments counted nationally by the 

Census Bureau in 2002, only 3,648 establishments out of the total of 171,652 (2.1%) had 

more than $10 million in sales, one-third of the small business cutoff value. Residential 

builders are overwhelmingly small businesses. Among commercial builders, the figures 

are 4,415 out of 37,208 (11.9%) with sales more than $10 million. Clearly, commercial 

contractors also are predominantly small businesses, although not by as large a margin as 

residential construction firms. Mechanical contractors have a lower small business sales 

cutoff value, but nationally in 2002, only 1,832 out 87,501 mechanical contractors (2.1%) 

had sales of at least $10 million. As with general contractors, it is clear from the 

national-level data that the mechanical contractor sector is overwhelming composed of 

17-47 

EERE-2008-BT-STD-0006 COMMENT 54
small businesses. Regional analysis of this question is not possible, but it is also 

unnecessary, as DOE expects the same results. 

• Cost structure and profitability (2002 Census). 

The 2002 Economic Census provides some detail on the cost structure of construction 

firms, although in less detail than that provided by the HARDI data for wholesale 

distributors. Air Conditioning Contractors of America 2005 publication Financial 

Analysis for the HVACR Contracting Industry is another source for financial data for 

contractors that is less detailed than the 2002 Economic Census. The Economic Census 

data includes sales (value of business, value of construction work, net value of 

construction work), employment, payroll, costs of materials, costs of subcontractors, total 

rental costs, capital expenditures excluding land, and total value of assets. This data 

allows a rough computation of the profitability of construction firms (general and 

mechanical contractors) at the regional level, which can be compared with the more 

detailed industry data at the national level (see U.S. Census Bureau, 2002: Plumbing, 

Heating, and Air-Conditioning Contractors: 2002. Report EC02-231-238220, Table 4, 

Detailed Statistics for Establishments: 2002 and Commercial and Institutional Building 

Construction: 2002. Report EC02-231-236220, Table 4, Detailed Statistics for 

Establishments: 2002). Geographic Series data on NAICS subsectors do not include 

costs of selected purchased services and do not include depreciation. Profits cannot be 

computed directly. 

Selected basic supporting data is shown inTable 17.6.17. Selected data for General 

Contractors is shown in Table 17.7.4. 

17-48 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 17.7.1 Revenue and Cost Items, Typical CACHP Mechanical Contractors, HotHumid Region 

Region Average Value 

of Construction 

Work per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out 

($1,000) 

Rental Costs 

($) 

End of 

Year 

Gross 

Value of 

Assets 

($1,000) 

Hot-Humid 

Region 

1212 355 437 121 20 171 

Border 

States 

1253 373 452 122 20 174 

 Texas 1426 434 511 143 22 182 

 Oklahoma 783 222 295 67 12 117 

 Arkansas 765 201 292 63 13 137 

 Tennessee 1674 468 618 147 27 231 

North

 Carolina 

1085 334 379 114 19 166 

SOURCE: Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 17.7.2 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Hot-Dry 

Region 

Region Average Value 

of Construction 

Work per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out 

($1,000) 

Rental Costs 

($) 

End of 

Year 

Gross 

Value of 

Assets 

($1,000) 

Hot-Dry 

region 

1614 496 540 146 28 190 

Border 

States 

1614 496 540 146 28 190 

Arizona 1297 387 514 94 23 180 

California 1698 529 553 161 30 197 

Nevada 2195 653 705 157 34 184 

New Mexico 908 247 320 85 14 135 

SOURCE: Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 17.7.3 Revenue and Cost Items, Typical CACHP Mechanical Contractors, Rest of 

Country 

Region Average Value 

of Construction 

Work per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1,000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out 

($1,000) 

Rental Costs 

($) 

End of 

Year 

Gross 

Value of 

Assets 

($1,000) 

Rest of 

Country 

1367 421 439 152 22 168 

Border 

States 

1231 386 430 122 19 159 

Colorado 1168 374 408 117 20 138 

Idaho 920 287 356 80 15 116 

Kansas 1269 380 447 160 18 163 

Kentucky 1113 335 385 100 19 175 

Missouri 1398 442 468 152 18 174 

Oregon 1397 461 491 129 22 152 

Utah 1133 304 397 128 19 143 

Virginia 1192 393 422 100 19 157 

SOURCE: Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 17.7.4 Geographic Area Series, Plumbing and HVAC Constructors 

State* Number of 

Establishments 

Value of 

Business 

Done 

($1,000) 

Cost of 

Materials 

($1,000) 

Construction 

Work 

Subcontracted 

Out ($1,000) 

Total 

Payroll 

($1,000) 

Alabama 1,425 1,517,258 547,075 151,240 430,252 

Arizona 1,510 1,967,940 776,733 141,885 584,412 

Arkansas 1,045 809,435 305,198 65,491 209,991 

California 7,272 12,409,267 4,018,408 1,172,183 3,845,532 

Colorado 2,015 2,382,111 821,432 235,012 753,883 

Connecticut 1,321 1,593,622 505,340 156,607 466,149 

Delaware 306 464,881 150,096 42,001 156,056 

Florida 5,069 6,314,034 2,270,555 616,097 1,828,108 

Georgia 2,534 3,459,031 1,226,368 380,819 944,212 

Hawaii 280 363,486 129,870 36,053 96,844 

Idaho 594 558,889 211,341 47,466 170,635 

Illinois 3,848 6,135,124 1,770,254 605,868 2,054,379 

Indiana 1,867 2,993,560 869,816 418,904 991,316 

Iowa 1,066 1,216,575 428,842 133,934 371,492 

Kansas 966 1,236,292 431,331 155,011 367,519 

Kentucky 1,219 1,363,485 469,639 121,960 408,927 

Louisiana 1,469 1,448,482 497,169 174,283 419,948 

Maine 458 399,172 138,587 36,149 114,586 

Maryland 2,024 3,925,032 1,251,986 583,237 1,130,739 

Massachusetts 2,520 3,545,394 1,038,151 503,155 1,007,916 

Michigan 3,051 4,369,139 1,338,229 492,957 1,319,863 

Minnesota 1,635 2,893,239 958,849 280,556 838,879 

Mississippi 655 757,148 283,993 70,985 184,163 

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EERE-2008-BT-STD-0006 COMMENT 54
Missouri 1,816 2,559,173 849,770 276,621 802,027 

Montana 432 362,598 135,009 44,987 92,496 

Nebraska 683 825,160 321,124 90,582 236,196 

Nevada 498 1,098,147 350,851 78,259 325,164 

New Hampshire 531 540,005 179,259 52,209 179,570 

New Jersey 3,551 4,229,237 1,230,617 466,668 1,321,095 

New Mexico 599 546,210 191,757 51,116 148,012 

New York 5,750 7,601,402 2,335,220 949,038 2,308,194 

North Carolina 2,978 3,258,502 1,127,518 339,388 993,337 

North Dakota 272 293,910 105,405 34,971 87,633 

Ohio 3,514 4,646,807 1,470,907 502,061 1,442,425 

Oklahoma 1,158 913,670 341,921 77,207 256,922 

Oregon 1,031 1,459,251 506,559 132,523 475,266 

Pennsylvania 3,653 5,971,127 1,766,004 639,074 1,639,278 

Rhode Island 397 491,915 171,994 60,217 136,580 

South Carolina 1,472 1,401,320 518,386 111,394 461,409 

South Dakota 337 337,590 141,297 22,754 83,704 

Tennessee 1,370 2,301,759 846,426 201,748 641,092 

Texas 5,653 8,131,851 2,889,320 807,501 2,451,016 

Utah 892 1,014,532 353,958 113,775 270,911 

Vermont 282 210,388 77,251 19,987 62,090 

Virginia 2,547 3,068,896 1,074,309 254,085 1,000,173 

Washington 1,602 2,378,599 773,211 222,282 772,633 

Wisconsin 1,839 2,643,604 941,806 193,399 855,624 

Source: 2002 U.S. Economic Census, Geographic Area Series, NAICS: 2382 Plumbing and HVAC Constructors by State 

*Note: AK, DC, WV, WY are left out in this analysis because of limited data provided from Census. 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

Table 17.7.5 Enterprise Statistics on Mechanical Contractors in the Hot-Humid Region 

Region Number of 

Establishments 

Total Value of 

Construction 

Work Done 

($1000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Hot-Humid 

Region 

25,108 30,423,332 1,212 276,994 11.0 

Border States 12,204 15,291,654 1,253 139,797 11.5 

 Texas 5,653 8,061,607 1,426 72,778 12.9 

 Oklahoma 1,158 906,621 783 8,403 7.3 

 Arkansas 1,045 799,157 765 7,757 7.4 

 Tennessee 1,370 2,292,875 1,674 19,547 14.3 

North

 Carolina 

2,978 3,231,394 1,085 31,312 10.5 

SOURCE: 2002 Economic Census Data 

Table 17.7.6 Enterprise Statistics on Mechanical Contractors in the Hot-Dry Region 

Region Number of 

Establishments 

Total Value of 

Construction 

Work Done 

($1000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Hot-Humid 

Region 

25,108 30,423,332 1,212 276,994 11.0 

Border States 12,204 15,291,654 1,253 139,797 11.5 

 Texas 5,653 8,061,607 1,426 72,778 12.9 

 Oklahoma 1,158 906,621 783 8,403 7.3 

 Arkansas 1,045 799,157 765 7,757 7.4 

 Tennessee 1,370 2,292,875 1,674 19,547 14.3 

North

 Carolina 

2,978 3,231,394 1,085 31,312 10.5 

SOURCE: 2002 Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

Table 17.7.7 Enterprise Statistics on Mechanical Contractors in the Rest of Country 

Region Number of 

Establishments 

Total Value of 

Construction Work 

Done ($1000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Rest of 

Country 

52,019 71,109,956 1,367 546,642 10.5 

Border States 9,065 11,155,228 1,231 97,279 10.7 

Colorado 2,015 2,354,183 1,168 20,146 10.0 

Idaho 594 546,349 920 5,313 8.9 

Kansas 966 1,225,986 1,269 10,036 10.4 

Kentucky 1,219 1,357,063 1,113 12,557 10.3 

Missouri 1,816 2,538,706 1,398 19,847 10.9 

Oregon 1,031 1,440,390 1,397 11,598 11.2 

Utah 892 1,010,317 1,133 8,374 9.4 

Virginia 2,547 3,036,417 1,192 29,554 11.6 

SOURCE: 2002 Economic Census Data 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

Table 17.7.8 Mechanical Contractor Establishments, Employment, and Payroll Trends, 

Hot-Humid Region 

Region Number of 

Establishments 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Hot-Humid 

Region 

26,017 29,671 10 11 333 425 

Border States 12,922 13,981 11 11 349 449 

 Texas 5,866 6,384 12 12 400 510 

 Oklahoma 1,218 1,332 7 7 208 273 

 Arkansas 903 996 8 9 231 310 

 Tennessee 1,523 1,679 13 12 406 473 

 North Carolina 3,412 3,590 10 11 317 435 

Table 17.7.9 Mechanical Contractor Establishments, Employment, and Payroll Trends, 

Hot-Dry Region 

Region Number of 

Establishments 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Hot-Dry region 10,406 12,495 11.1 12.1 463.5 578.0 

Border States 10,406 12,495 11.1 12.1 463.5 578.0 

Arizona 1,610 2,062 11.0 12.7 363.2 489.1 

California 7,641 9,001 11.1 11.6 490.9 584.4 

Nevada 524 720 15.7 19.2 637.2 979.0 

New Mexico 631 712 7.7 9.1 243.5 349.2 

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Table 17.7.10 Mechanical Contractor Establishments, Employment, and Payroll Trends, 

Rest of Country Region 

Region Number of 

Establishments 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Rest of 

Country 

53,918 58,640 9.2 9.2 395.6 465.9 

Border States 11,470 12,923 9.3 11.9 392.9 486.3 

Colorado 2,064 2,339 9.1 8.4 362.1 388.2 

Idaho 606 831 7.5 8.0 245.3 286.0 

Kansas 1,006 1,049 8.9 10.3 352.7 421.0 

Kentucky 1,288 1,278 9.5 9.5 312.0 380.2 

Missouri 1,884 2,014 9.7 9.4 428.0 476.3 

Oregon 1,134 1,346 8.7 9.5 372.9 453.2 

Utah 936 1,209 7.9 8.4 276.9 348.5 

Virginia 2,552 2,857 10.6 11.3 375.1 490.3 

Cost structure and profitability vary among subareas (i.e., border states) for mechanical 

contractors. Selected data required to generate net operating profit estimates is not available on 

subsectors of construction at the regional level (specifically, Total Purchased Services, 

Depreciation), although the data is available nationally. 

17.8 ADDITIONAL GENERAL CONTRACTORS AND HOMEBUILDERS DATA 

Statistical tables follow for General Contractors in each region. Selected data for General 

Contractors are shown in Table 17.7.4. 

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Table 17.8.1 Enterprise Statistics on General Contractors in the Hot-Humid Region 

Region Number of 

Establishments* 

Total Value 

of 

Construction 

Work Done 

($1,000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

HotHumid 

Region 

58,480 168,947,696 2,889 484,826 8.3 

Border 

States 

32,894 96,197,405 2,924 277,605 8.4 

 Texas 9,625 39,038,019 4,056 95,829 10.0 

Oklahoma 

1,942 1,454,942 749 12,445 6.4 

Arkansas 

10,716 36,945,606 3,448 90,624 8.5 

Tennessee 

2,982 3,173,248 1,064 27,440 9.2 

North 

Carolina 

7,629 15,585,590 2,043 51,267 6.7 

*Because Mississippi is an incomplete data set, the state has been excluded from the total count of establishments 

SOURCE: 2002 Economic Census 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 17.8.2 Enterprise Statistics on General Contractors in the Hot-Dry Region 

Region Number of 

Establishments 

Total Value 

of 

Construction 

Work Done 

($1,000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Hot-Dry 

region 

28,405 84,436,053 2,973 255,534 9.0 

Border 

States 

28,405 84,436,053 2,973 255,534 9.0 

Arizona 3,574 13,737,839 3,844 33,276 9.3 

California 21,671 63,504,624 2,930 193,975 9.0 

Nevada 1,400 4,671,330 3,337 17,627 12.6 

New 

Mexico 

1,760 2,522,260 1,433 10,656 6.1 

SOURCE: 2002 Economic Census 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 17.8.3 Enterprise Statistics on General Contractors in the Rest of Country 

Region Number of 

Establishments* 

Total Value 

of 

Construction 

Work Done 

($1000) 

Sales per 

Establishment 

($1,000) 

Total 

Employment 

Average 

Employment 

per 

Establishment 

Rest of 

Country 

127,558 221,929,611 1,740 883,611 6.9 

Border 

States 

27,031 45,794,848 1,694 197,421 7.3 

Colorado 5,223 8,969,090 1,717 37,926 7.3 

Idaho 1,638 N/A N/A 8,412 5.1 

Kansas 2,185 3,792,200 1,736 13,467 6.2 

Kentucky 2,336 4,985,602 2,134 17,810 7.6 

Missouri 4,714 4,060,799 861 39,744 8.4 

Oregon 4,098 5,980,885 1,459 23,426 5.7 

Utah 2,200 2,251,069 1,023 15,178 6.9 

Virginia 6,275 15,755,203 2,511 49,870 7.9 

*Because Idaho and the District of Columbia are incomplete data sets, they have been excluded from the total count of 

establishments used in other calculations. 

SOURCE: 2002 Economic Census 

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Table 17.8.4 General Contractor Establishments, Employment, and Payroll Trends, HotHumid Region 

Region Number of 

Establishments 

Employment per 

Establishment 

Payroll per 

Establishment 

2002 2007 2002 2007 2002 2007 

Hot-Humid 

Region 

50,365 61,077 7.7 7.2 297 344 

Border States 23,783 27,140 7.6 7.4 296 359 

 Texas 9,686 10,914 9.1 8.9 402 474 

 Oklahoma 1,829 2,075 6.3 5.8 188 221 

 Arkansas 1,488 1,740 6.9 6.2 203 229 

 Tennessee 3,124 3,524 7.4 7.9 275 374 

 North Carolina 7,656 8,887 6.2 6.0 213 270 

Table 17.8.5 General Contractor Establishments, Employment, and Payroll Trends, HotDry Region 

Region Number of 

Establishments 

Employment per 

Establishment 

Payroll per 

Establishment 

($1,000) 

2002 2007 2002 2007 2002 2007 

Hot-Dry 

region 

28,374 34,143 7.9 8.4 343.7 443.8 

Border 

States 

28,374 34,143 7.9 8.4 343.7 443.8 

Arizona 3,752 4,729 8.3 9.3 337.7 476.2 

California 21,564 25,624 7.7 8.1 343.1 435.1 

Nevada 1,350 1,647 12.0 12.8 571.5 757.7 

New 

Mexico 

1,708 2,143 6.3 6.4 183.9 234.8 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

Table 17.8.6 General Contractor Establishments, Employment, and Payroll Trends, Rest 

of Country 

Region Number of 

Establishments

Employment per 

Establishment 

Payroll per 

Establishment 

 ($1,000) 

2002 2007 2002 2007 2002 2007 

Rest of 

Country 

131,205 145,679 6.0 5.8 249.9 288.9 

Border 

States 

29,265 34,360 6.1 5.8 240.3 283.6 

Colorado 5,121 5,598 6.4 6.2 290.3 327.5 

Idaho 1,759 2,661 2.6 4.8 75.1 164.7 

Kansas 2,153 2,288 6.4 5.7 218.1 232.4 

Kentucky 2,348 2,421 7.4 7.4 242.6 287.2 

Missouri 4,452 4,752 7.1 7.8 283.0 369.0 

Oregon 4,186 5,174 4.3 4.8 157.9 206.3 

Utah 2,633 3,224 5.4 6.2 183.7 247.2 

Virginia 6,613 8,242 7.0 6.4 271.1 308.0 

Cost structure and profitability varies among subareas (e.g. border states) for General 

Contractors. Selected data required to generate net operating profit estimates are not available on 

subsectors of construction at the regional level (Total Purchased Services, Depreciation), but 

they are available nationally. 

17-62 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

Table 17.8.7 Revenue and Cost Items, Typical General Contractors, Hot-Humid Region 

Region Average 

Value of 

Construction 

Work per 

Establishment 

($1,000)* 

Average 

Payroll 

Costs 

($1000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out ($1,000) 

Rental 

Costs 

($1,000) 

End of 

Year 

Gross 

Value 

of 

Assets 

($1,000) 

HotHumid 

Region 

2889 306 720 1,327 19 153 

Border 

States 

2924 313 742 1,367 19 158 

 Texas 4056 398 951 1,750 24 167 

Oklahoma 

749 183 531 882 13 117 

Arkansas 

3448 321 762 1,512 19 174 

Tennessee 

1064 335 598 1,222 21 149 

North 

Carolina 

2043 216 558 859 14 137 

*Because Mississippi is an incomplete data set, the state has been excluded from the total count of establishments used in other 

calculations. 

SOURCE: 2002 Economic Census 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

Table 17.8.8 Revenue and Cost Items, Typical General Contractors, Hot-Dry Region 

Region Average 

Value of 

Construction 

Work per 

Establishment 

($1,000) 

Average 

Payroll 

Costs 

($1000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out ($1,000) 

Rental 

Costs 

($1,000) 

End of 

Year 

Gross 

Value 

of 

Assets 

($1,000) 

Hot-Dry 

region 

2973 357 473 1,429 21 120 

Border 

States 

2973 357 473 1,429 21 120 

Arizona 3844 337 580 1,931 23 128 

California 2930 364 465 1,417 22 122 

Nevada 3337 534 493 1,350 16 121 

New 

Mexico 

1433 172 329 630 9 81 

SOURCE: Economic Census 

17-64 

EERE-2008-BT-STD-0006 COMMENT 54
 

Table 17.8.9 Revenue and Cost Items, Typical General Contractors, Rest of Country 

Region Average 

Value of 

Construction 

Work per 

Establishment 

($1,000)* 

Average 

Payroll 

Costs 

($1000) 

Cost of 

materials, 

components 

and Fuels 

Operating 

Costs 

($1,000) 

Cost of Work 

Subcontracted 

Out ($1,000) 

Rental 

Costs 

($1,000) 

End of 

Year 

Gross 

Value 

of 

Assets 

($1,000) 

Rest of 

Country 

1740 255 447 899 15 114 

Border 

States 

1694 262 492 947 15 117 

Colorado 1717 285 423 700 17 123 

Idaho N/A 149 416 666 9 84 

Kansas 1736 196 469 790 14 118 

Kentucky 2134 245 577 945 14 149 

Missouri 861 304 489 1,281 12 139 

Oregon 1459 201 350 703 10 64 

Utah 1023 232 576 1,057 17 112 

Virginia 2511 292 592 1,080 20 121 

*Because Idaho and the District of Columbia are incomplete data sets, they have been excluded from the total count of 

establishments used in other calculations. 

SOURCE: Economic Census 

17-65 

EERE-2008-BT-STD-0006 COMMENT 54
 

 

 

 

 

 

 

 

1

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3 http://www.alliedair.com/ (Last accessed: February 8, 2010) 

4 http://www.serviceexperts.com/Services/HVAC-Repair-Service.aspx (Last accessed: February
 

8, 2010) 

5

 IBID 1
 

6

http://www1.eere.energy.gov/buildings/appliance_standards/residential/pdfs/fb_fr_tsd/chapter_
 

7

 Hall, John R. “Consultants Address Inventory Issues: Adjusting Inventory Levels to Current 

Conditions Is the Name of the Game.” Air Conditioning, Heating & Refrigeration News July
 

2007: pp. 14. Web. 04 Nov. 2009. 

11 Maynard, Michael. “Standing Tall for Distributors.” HVACR Distribution Business Feb. 2008: 

pp. 22. Web. 04 Nov. 2009. 

12 Maynard, Michael. “National Presence, Local Service-Grainger Makes It Easy for the 

Customer.” HVACR Distribution Business June 2006: pp. 22-23. Web. 04 Nov. 2009. 

13 Trimbach, Jason. “Benchmarking Time Allocation for Warehouse Employees: Part 1: Use of 

Warehouse Capacity.” HVACR Distribution Business August 2007: pp. 44. Web. 04 Nov. 2009 

14 Stratman, Scott. “Cycle Counting: Penicillin for Distributors.” HVACR Distribution Business
 

April 2005: pp. 28. Web. 04 Nov. 2009. 

15 Peric’, Tom S. “A View from the Top.” HVACR Distribution Business Feb. 2006: pp. 48. 

Web. 04 Nov. 2009. 

5.pdf pp. 5-2 

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 IBID 7
 

9

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10 IBID 7
 

16 IBID 7
 

17 IBID 7
 

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EERE-2008-BT-STD-0006 COMMENT 54
 

 

18 Toler, Greg. “Inbound Freight: Are We Paying Close Attention?” HVACR Distribution 

Business Aug 2008: pp. 39. Web. 04 Nov. 2009. 

19 “Inbound Freight: Are We Paying Close Attention?” pp. 39 

20 Maynard, Michael. “Staying Ahead of the Technology Curve.” HVACR Distribution Business 

June 2007: pp. 17. Web. 04 Nov. 2009. 

21US Census Bureau. Plumbing, Heating, and Air-Conditioning Contractors: 2002. 

22 US Census Bureau. Plumbing, Heating, and Air-Conditioning Contractors: 2002. 

23 http://phx.corporateir.net/External.File?item=UGFyZW50SUQ9MzMyMTA2fENoaWxkSUQ9MzE0MzY5fFR5cG 

U9MQ==&t=1 pp. 55 

24 US Census Bureau, Plumbing, Heating, and Air-Conditioning Contractors: 2002. 

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U9MQ==&t=1 pp. 14 

26 “Sanyo HVAC Solutions is World-Class.” pp. 18. 

27 “Sanyo HVAC Solutions is World-Class.” pp. 18. 

28 Harris, Angela D. “Economics Challenge Contractors: Workforce Issues and Home Building
 

Slowdown.” Air Conditioning, Heating & Refrigeration News March 2007: pp. 20. Web. 04 

Nov. 2009. 

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30 “Economics Challenge Contractors: Workforce Issues and Home Building Slowdown.” pp. 28. 

31 “Staying Ahead of the Technology Curve.” pp. 17. 

32 Ciuffreda, Albert. “Getting a Handle on Your Overhead.” Air Conditioning, Heating &
 

Refrigerating News 237.16 (2009): pp. 20. Business & Company Resource Center. Web. 27 Oct. 

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33 “Getting a Handle on Your Overhead.” pp. 20. 

34 IBID 1
 

35 Sources from GAMA Report 2005 

36 US Census Bureau, Plumbing, Heating, and Air-Conditioning Contractors: 2002. 

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