CHAPTER 2. ANALYTICAL FRAMEWORK

TABLE OF CONTENTS

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

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

2.2.1 Market Assessment .......................................................................................................... 2-4

2.2.2 Technology Assessment................................................................................................... 2-4

2.3 SCREENING ANALYSIS .............................................................................................. 2-4

2.4 ENGINEERING ANALYSIS .......................................................................................... 2-5

2.5 MARKUPS ANALYSIS ................................................................................................. 2-6

2.6 ENERGY USE ANALYSIS ............................................................................................ 2-6

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

2.8 SHIPMENTS ANALYSIS .............................................................................................. 2-7

2.9 NATIONAL IMPACT ANALYSIS ................................................................................ 2-9

2.10 CUSTOMER SUBGROUP ANALYSIS ....................................................................... 2-10

2.11 MANUFACTURER IMPACT ANALYSIS.................................................................. 2-10

2.12 EMISSIONS ANALYSIS .............................................................................................. 2-11

2.13 MONETIZING CARBON DIOXIDE AND OTHER EMISSIONS

REDUCTIONS .............................................................................................................. 2-13

2.14 UTILITY IMPACT ANALYSIS ................................................................................... 2-14

2.15 EMPLOYMENT IMPACT ANALYSIS ....................................................................... 2-14

2.16 REGULATORY IMPACT ANALYSIS ....................................................................... 2-15

FIGURE

Figure 2.1.1 Flow Diagram of Analyses for the Rulemaking Process ..................................... 2-2

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CHAPTER 2. ANALYTICAL FRAMEWORK

2.1 INTRODUCTION

Section 6313(a)(6)(A)(ii) of 42 United Standards Code (U.S.C.), requires the U.S. 

Department of Energy (DOE) to establish energy conservation standards that are technologically 

feasible and economically justified and will result in significant energy conservation. This 

chapter describes the general analytical framework that DOE uses in developing such standards, 

as well as aspects specific to the analysis of standards for small, large, and very large, 

commercial package air conditioning and heating equipment (also referred to in this notice as 

small, large, and very large air-cooled commercial unitary air conditioners, CUAC, and small, 

large, and very large air-cooled commercial unitary heat pumps, CUHP). The analytical 

framework summarizes the methodologies, analytical tools, and relationships among the various 

analyses that are part of a standards rulemaking. 

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

column labeled Approaches lists the methodologies DOE uses to perform the various steps and 

analyses in the process. The primary focus of the figure is the column labeled Analyses. The 

columns labeled Key Inputs and Key Outputs show how the analyses fit into the rulemaking 

process and how they relate to each other. Key inputs are the types of data and information that 

the analyses require. Some key inputs can be found in public databases; other inputs DOE 

collects from interested parties or experts having specialized knowledge. Key outputs are the 

analytical results that feed directly into the standards-setting process. Lines with arrows 

connecting analyses show the types of information that feed from one analysis to another. 

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Figure 2.1.1 Flow Diagram of Analyses for the Rulemaking Process

Utility Impact

Analysis 

Notice of Proposed Rulemaking (NOPR)

Final Rule

Approaches Key Inputs Analyses Key Outputs

Market and Technology

Assessment

Screening Analysis

Engineering Analysis

Product Price

Determination Life-Cycle Cost and 

Payback Period 

Analyses

National Impact

Analysis

Energy Use

Revise Preliminary

Analyses

Life-Cycle Cost 

Sub-Group Analysis

Manufacturer Impact 

Analysis

Shipments

Analysis

Employment Impact

Analysis 

Revise Analyses

• Product Classes

• Technology Options

• Industry Cash Flow

• Sub-Group Cash-Flow

• Direct Employment Impacts

• Competitive Impacts

• Cumulative Regulatory Burden

• Product Designs

• Life-Cycle Costs

• Payback Periods

• National Energy Savings

• Net Present Values

• National Employment Impacts

• Revised Results

• Characterize Industry

• Market Segmentation

• Non-Regulatory Programs

Framework Document

• Efficiency-Level Approach

• Design Option Approach

• Energy Prices

• Installation Costs

• Maintenance & Repair Costs

• Accounting Approach

• Backcast and Forecast

• Market Saturation

• Stakeholder Comments

• Demographics

• Manufacturer Interviews

• GRIM Analysis

• Emission Rates

• National Energy Savings

• Stakeholder Comments

• Identify Firms/Products 

• Historical Shipments

•Retail Price Collection and

Analysis

• Manufacturer Prices

• Average Costs

• Manufacturer Financial Data

Design Options

Product Classes

Retail 

Prices

Design Energy/ Use

Advance Notice of Proposed Rulemaking (ANO)

• Efficiency/Performance

• Commercial Products

Candidate

Standard 

Levels

• Analysis of Energy Use 

Data

Environmental

Assessment

Regulatory Impact

Analysis

Technology Options

• Emission Estimates

• Utility Load Factors

• National Energy Savings

• Non-Regulatory

Alternatives

• NEMS-BT

• ImSET

• NEMS-BT

• 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

• Analysis of Market Data

• Analysis of Product Data

• 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

Product Designs

Utility Impact

Analysis 

Notice of Proposed Rulemaking (NOPR)

Final Rule

Approaches Key Inputs Analyses Key Outputs

Market and Technology

Assessment

Screening Analysis

Engineering Analysis

Product Price

Determination Life-Cycle Cost and 

Payback Period 

Analyses

National Impact

Analysis

Energy Use

Analyses

Life-Cycle Cost 

Sub-Group Analysis

Manufacturer Impact 

Analysis

Shipments

Analysis

Employment Impact

Analysis 

Revise Analyses

• Product Classes

• Technology Options

• Industry Cash Flow

• Sub-Group Cash-Flow

• Direct Employment Impacts

• Competitive Impacts

• Cumulative Regulatory Burden

• Product Designs

• Life-Cycle Costs

• Payback Periods

• National Energy Savings

• Net Present Values

• National Employment Impacts

• Revised Results

• Characterize Industry

• Market Segmentation

• Non-Regulatory Programs

Framework Document

• Efficiency-Level Approach

• Design Option Approach

• Energy Prices

• Installation Costs

• Maintenance & Repair Costs

• Accounting Approach

• Backcast and Forecast

• Market Saturation

• Stakeholder Comments

• Demographics

• Manufacturer Interviews

• GRIM Analysis

• Emission Rates

• National Energy Savings

• Stakeholder Comments

• Identify Firms/Products 

• Historical Shipments

•Retail Price Collection and

Analysis

• Manufacturer Prices

• Average Costs

• Manufacturer Financial Data

Design Options

Product Classes

Retail 

Prices

Design Energy/ Use

Publication of Preliminary Analyses

• Efficiency/Performance

• Commercial Products

Candidate

Standard 

Levels

• Analysis of Energy Use 

Data

Environmental

Assessment

Regulatory Impact

Analysis

Technology Options

• Emission Estimates

• Utility Load Factors

• National Energy Savings

• Non-Regulatory

Alternatives

• NEMS-BT

• ImSET

• NEMS-BT

• 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

• Analysis of Market Data

• Analysis of Product Data

• 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

Product Designs

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The following analyses are performed for the notice of proposed rulemaking (NOPR). 

• A market and technology assessment to characterize the relevant equipment markets 

and technology options, including prototype designs. 

• A screening analysis to review each technology option and determine whether it is 

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

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

health and safety.

• An engineering analysis to develop cost-efficiency relationships for equipment 

designs that passed the screening analysis; the manufacturer’s production costs 

(material, labor, and factory overhead) for achieving increased efficiency are 

evaluated. 

• An energy use analysis to determine the annual energy use of the considered 

equipment at specific efficiency levels. 

• A markups analysis to convert the manufacturer costs estimated from the engineering 

analysis to consumer prices, which are then used in the life-cycle cost (LCC) and 

payback period analysis (PBP) and in the manufacturer impact analysis. 

• A life-cycle cost and payback period analysis to calculate, at the consumer level, the 

discounted savings in operating costs (minus maintenance and repair costs) 

throughout the estimated average life of the covered equipment, compared to any 

increase in the installed cost of the equipment likely to result directly from the 

imposition of the standard. 

• A shipments analysis to forecast equipment shipments, which then are used to 

calculate the national impacts of standards on energy consumption and costs, net 

present value (NPV), and future manufacturer cash flows. 

• A national impact analysis to assess the aggregate impacts nationwide of the NPV of 

total consumer LCC and national energy savings (NES). 

• A consumer subgroup analysis to evaluate variations in consumer characteristics that 

might cause a standard to affect the LCC for particular consumer sub-populations 

differently than for the overall population. 

• A manufacturer impact analysis to estimate the financial impacts of standards on 

manufacturers and to calculate effects on competition, employment, and 

manufacturing capacity.

• An emissions analysis to estimate the effects of amended energy conservation 

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

(NOX), and mercury (Hg).

• A monetization of emission reduction benefits resulting from reduced emissions of 

CO2 and NOX associated with potential amended standards. 

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

generation capacity and electricity generation of electric utilities.

• An employment impact analysis to assess the aggregate effects of standards on 

national employment.

• A regulatory impact analysis to evaluate alternatives to proposed amended energy 

conservation standards that could achieve substantially the same regulatory goal. 

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2.2 MARKET AND TECHNOLOGY ASSESSMENT

The market and technology assessment characterizes the relevant equipment markets and 

technology options, including prototype designs, for considered equipment. Chapter 3 of this 

TSD describes in detail the market and technology assessment for small, large, and very large, 

air-cooled CUAC and CUHP. 

2.2.1 Market Assessment

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

past industry structure and market characteristics for the equipment being studied. This activity 

assesses the industry and equipment, both quantitatively and qualitatively, based on publicly 

available information. As such, for the considered equipment, DOE addressed (1) manufacturer 

market share and characteristics; (2) current regulatory and nonregulatory initiatives for 

improving equipment efficiency; and (3) trends in equipment characteristics and retail markets. 

This information serves as resource material throughout the rulemaking. 

DOE reviewed equipment literature and interviewed manufacturers to develop an overall 

picture of the market for small, large, very large air-cooled CUAC and CUHP in the United 

States. Industry publications and trade journals, government agencies, and trade organizations 

provided the bulk of this information. The appropriate sections of this TSD, particularly chapter 

3, describe the resulting information as DOE used it in the analysis. 

 

2.2.2 Technology Assessment

DOE typically uses information relating to current and past technology options and 

prototype designs to determine what technologies manufacturers use to attain higher 

performance levels. In consultation with interested parties, DOE develops a list of technologies 

for consideration. Initially, the list encompasses all the technologies DOE believes are 

technologically feasible. 

 DOE developed a list of technologically feasible design options through consultation 

with manufacturers of components and systems, from trade publications and technical papers. 

Since many options for improving equipment efficiency are available in existing units, 

equipment literature and direct examination provided additional information. 

2.3 SCREENING ANALYSIS

 As described in section 2.2.2, DOE develops an initial list of efficiency enhancement 

options from the technologies identified as technologically feasible. Then DOE, in consultation 

with interested parties, reviews the list to determine whether those options (1) are technologically 

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

equipment utility or availability; or (4) have adverse impacts on health and safety. In addition, 

DOE removes from the list any technology options for which energy consumption data are 

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lacking as well as any for which the energy consumption cannot be measured adequately by 

DOE test procedures. Chapter 4 of this TSD describes the screening analysis. In the engineering

analysis, DOE further considers those efficiency enhancement options that were not eliminated

in the screening analysis. 

2.4 ENGINEERING ANALYSIS

In the engineering analysis (chapter 5 of this TSD), DOE evaluates a range of equipment 

efficiency levels and their associated manufacturing costs in order to establish the relationship 

between the cost and the efficiency of small, large, and very large, air-cooled CUAC and CUHP. 

This relationship serves as the basis for cost/benefit calculations related to individual consumers, 

manufacturers, and the nation. Chapter 5 discusses the equipment classes DOE analyzed, the 

representative baseline units, the incremental efficiency levels, the methodology DOE used to 

develop manufacturing costs, the methodology it used to develop the energy consumption model, 

the cost-efficiency curves, and the effect of efficiency improvements on the covered equipment. 

 

 The purpose of the engineering analysis is to estimate the incremental manufacturing 

production costs associated with increasing equipment efficiency above the level of the baseline 

model in each equipment class. The engineering analysis generally considers technologies not 

eliminated in the screening analysis, although certain technologies were not analyzed because 

they offered negligible incremental improvements to efficiency. DOE considers the remaining 

technologies, designated design options, in developing cost-efficiency curves, which 

subsequently are used for the LCC and PBP analysis. For each equipment class, DOE selected 

efficiency levels and obtained incremental cost data at each level. 

 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 the particular 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 teardowns of the equipment being analyzed. A supplementary method 

called a catalog teardown uses published manufacturer catalogs and supplementary component 

data to estimate the major physical differences between a piece of equipment that has been 

physically disassembled and another piece of similar equipment for which catalog data is 

available to determine the cost of the latter equipment.

DOE conducted the engineering analyses using the reverse-engineering approach. This 

approach involved the disassembly of units, analysis of the materials and manufacturing 

processes, and development of a spreadsheet cost model based on a clear and consistent 

manufacturing cost assessment methodology. DOE built a detailed cost assessment model that 

accurately predicts manufacturing costs. The model reports those costs in aggregated form to 

maintain confidentiality of the data. 

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2.5 MARKUPS ANALYSIS 

 In the markups analysis (chapter 6 of this TSD), DOE uses manufacturer-to-customer 

markups to convert the manufacturer selling price estimates from the engineering analysis to 

customer prices, which are then used in the LCC and PBP analysis and in the manufacturer 

impact analysis. Retail prices are necessary for the baseline efficiency level and all other 

efficiency levels under consideration. To develop markups, DOE identified distribution channels 

(i.e., how the equipment are distributed from the manufacturer to the consumer). After

identifying appropriate distribution channels, DOE utilized economic census data from the U.S.

Census Bureau and input from the industry to define how equipment are marked up from the 

manufacturer to the customer. 

2.6 ENERGY USE ANALYSIS

The energy use analysis (chapter 7 of this TSD) provides estimates of the annual energy 

consumption of small, large, and very large air-cooled CUAC equipment at the considered 

efficiency levels. DOE uses these values in the LCC and PBP analyses and in the NIA. DOE did 

not analyze air-cooled CUHP equipment because the energy modeling discussed in chapter 4

was performed only for air-cooled CUAC equipment. 

DOE developed energy consumption estimates only for the air-cooled CUAC equipment 

classes that have electric resistance heating or no heating. For equipment classes with all other 

types of heating, the incremental change in IEER for each efficiency level is identical to that for 

the equipment classes with electric resistance heating or no heating. Therefore, DOE estimated 

that the energy savings for any efficiency level relative to the baseline would be identical for 

both sets of equipment classes. In turn, the energy savings estimates for the efficiency levels 

associated with the equipment classes that have electric resistance heating or no heating were 

used by DOE in the LCC and PBP analysis and the NIA to represent both sets of equipment 

classes.

 

The energy use analysis for small, large, and very large air-cooled CUAC consists of two 

related parts. In the first part, DOE calculated energy savings for small, large, and very large aircooled CUAC at the considered efficiency levels based on modifications to the energy use 

simulations conducted for the 2004 ANOPR. These building simulation data are based on the 

1995 Commercial Building Energy Consumption Survey (CBECS). Because the simulation data 

reflect the building stock in 1995 that uses air-cooled CUAC equipment, in the second part, DOE 

developed a “generalized building sample” to represent the current installation conditions for the 

equipment covered in this rulemaking. This part involved making adjustments to update the 

building simulation data to reflect the building stock that uses air-cooled CUAC equipment in 

2011. 

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2.7 LIFE-CYCLE COST AND PAYBACK PERIOD ANALYSIS

The LCC and PBP analysis (chapter 8 of this TSD) analyzes the effects of potential 

amended energy conservation standards on customers of small, large, and very large air-cooled 

commercial package air conditioning and heating equipment by determining how a potential 

amended standard affects their operating expenses (usually decreased) and their total installed 

costs (usually increased). 

The LCC is the total customer expense over the life of the equipment, consisting of 

equipment and installation costs plus operating costs over the lifetime of the equipment 

(expenses for energy use, maintenance, and repair). DOE discounts future operating costs to the 

time of purchase using customer discount rates. The PBP is the estimated amount of time (in 

years) it takes customers to recover the increased total installed cost (including equipment and 

installation costs) of a more efficient type of equipment through lower operating costs. DOE 

calculates the PBP by dividing the change in total installed cost (normally higher) due to a 

standard by the change in annual operating cost (normally lower) that results from the standard. 

For any given efficiency level, DOE measures the PBP and the change in LCC relative to 

an estimate of the base-case efficiency level. The base-case estimate reflects the market in the 

absence of amended energy conservation standards, including the market for equipment that 

exceeds the current energy conservation standards. 

DOE analyzed the potential for variability and uncertainty by performing the LCC and 

PBP calculations on a representative sample of individual commercial buildings. The approach 

utilizes the sample of buildings developed for the energy use analysis and the corresponding 

simulations results. Within a given building, one or more air-conditioning units may serve the 

building’s space-conditioning needs, depending on the cooling load requirements of the building. 

As a result, DOE expresses the LCC and PBP results as the number of units experiencing 

economic impacts of different magnitudes. DOE models both the uncertainty and the variability 

in the inputs to the LCC and PBP analysis using Monte Carlo simulation and probability 

distributions. As a result, the LCC and PBP results are displayed as distributions of impacts 

compared to the base case conditions. 

DOE conducted an LCC and PBP analysis for the CUAC equipment classes. The energy 

savings estimates for the efficiency levels associated with the equipment classes that have 

electric resistance heating or no heating were used in the LCC and PBP analysis to represent the 

equipment classes with all other types of heating. DOE did not perform an LCC and PBP 

analysis for the CUHP equipment for the reasons discussed in section 2.6. 

2.8 SHIPMENTS ANALYSIS

Forecasts of shipments are required to calculate the national impacts of standards on 

energy consumption, NPV, and future manufacturer cash flows. To project shipments of small, 

large, and very large air-cooled CUAC and CUHP, DOE considered specific market segments, 

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the results for which are then aggregated to estimate total shipments. DOE accounted for three 

market segments: (1) shipments to new construction, (2) replacement shipments going into 

existing buildings, and (3) existing buildings acquiring new equipment for the first time. 

 For existing buildings replacing broken equipment, the shipments model uses a stock 

accounting framework. Given the equipment entering the stock in each year and a retirement 

function based on the lifetime distribution developed in the LCC analysis, the model predicts 

how many units reach the end of their lifetime in each year. For CUAC and CUHP, end of 

lifetime is generally associated with compressor failure. The customer has the choice of repairing 

the existing unit by installing a new compressor, thereby extending its life considerably, or 

purchasing a new unit. To model the repair vs. replacement decision, for the small and large 

CUAC and CUHP equipment classes DOE used a consumer choice model that estimates 

customer sensitivity to total installation cost. A sensitivity parameter was calculated using 

efficiency market share data for years 1999−2001, along with estimates of equipment prices and 

installation costs by efficiency level. DOE applied this sensitivity to the difference between the 

total installed cost of a new unit and the repair cost of the existing unit. For the very large 

CUAC and CUHP equipment classes, at the first failure DOE assumed that all customers repair 

the unit because the total installed cost of a new unit is so high. 

The repair/replace model is a binary choice model with two parameters, “alpha” and 

“gamma.” "Alpha" represents customer sensitivity to the efficiency-weighted average cost 

difference between total installed cost of replacement and repair costs. Since repair costs are 

generally lower than total installed costs of equipment, "gamma" is a scenario parameter that 

limits the number of repairs and can be thought of as representing "unknown replacements." 

For existing buildings acquiring new equipment for the first time, DOE first estimated 

saturation values (percentages of total floor space served by different cooling capacities or types 

of equipment) for the stock. DOE used a logistic regression procedure to fit the historical stock 

saturations to get a smooth time series of saturation estimates for the analysis period. Shipments 

for existing buildings acquiring new equipment for the first time in each future year are 

estimated by multiplying the difference in projected stock saturation values between the future 

year and the previous year with the estimated floor space without CUAC and CUHP equipment 

in the previous year. 

For new commercial buildings acquiring equipment, shipments are estimated by 

multiplying new construction floor space in each future year by saturation values (percentages of 

new floor space served by different cooling capacities or types of equipment). The shipments 

model relies on AEO for forecasts of new construction floor space. It assumes that the saturation 

value in new commercial buildings is the same as the stock-average saturation for each year.

The methods described above provide total shipments in each equipment class for each 

year. To estimate the market shares of the considered efficiency levels in future shipments, DOE 

developed a customer choice model. The model was calibrated by estimating values for two 

parameters, representing customer sensitivity to total installation cost and annual operating cost. 

To estimate values for the parameters, DOE used a non-linear regression approach that 

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minimized the sum of the squared difference between historical market shares and the model 

predicted values at each efficiency level. Starting in 2013, application of the parameters, along 

with data on the installed cost and operating cost at each efficiency level considering this 

rulemaking, determines the market shares of each efficiency level.

2.9 NATIONAL IMPACT ANALYSIS

The national impact analysis, described in chapter 10 of this TSD, assesses the NES and 

the national NPV of total customer costs and savings that would be expected to result from 

amended standards at specific efficiency levels. To make the analysis more accessible and 

transparent to all stakeholders, DOE prepared an NES spreadsheet model in Microsoft Excel to 

forecast energy savings and the national costs and savings resulting from amended standards. 

The NES spreadsheet model does not use probability distributions for inputs or outputs. To 

assess the effect of input uncertainty on the NES and NPV results, DOE can conduct sensitivity 

analyses by running scenarios on input variables that are of interest to stakeholders. 

The NIA calculations are based on the annual energy consumption and total installed cost 

data from the energy use analysis and the LCC analysis. DOE forecasted the lifetime energy 

savings, energy cost savings, equipment costs, and NPV of customer benefits for each equipment 

class for equipment sold from 2019 through 2048. 

 DOE evaluated the impacts of potential new and amended standards for small, large, and 

very large air-cooled commercial package air conditioning and heating equipment by comparing 

base-case projections with standards-case projections. The base-case projections characterize 

energy use and customer costs for each equipment class in the absence of new and amended 

energy conservation standards. DOE compared these projections with those characterizing the 

market for each equipment class if DOE were to adopt amended standards at specific energy 

efficiency levels (i.e., the standards cases) for that class.

 As stated in section 2.7, air-cooled CUHP were not analyzed in the LCC and PBP 

analysis. Nevertheless, DOE developed the inputs necessary for determining the 

NES and customer NPV that would result from higher CUHP efficiency levels. 

 The inputs for determining NES are (1) annual energy consumption per unit, (2) 

shipments, (3) equipment stock, (4) national energy consumption, and (5) site-to-source 

conversion factors. DOE calculated the national energy consumption by multiplying the number 

of units, or stock, of equipment (by vintage) by the unit energy consumption (also by vintage).a

DOE calculated national annual energy savings as the difference between national energy 

consumption in the base case (without new efficiency standards) and in each higher-efficiency 

standards case. Cumulative energy savings are the sum of the annual NES throughout the 

forecast period. 

a Vintage represents the age of the product. 

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DOE estimates energy consumption and savings based on site energy, then converts the 

electricity consumption and savings into primary energy (power sector consumption). DOE also 

uses full-fuel-cycle (FFC) measures of energy use based on multipliers derived using EIA’s 

National Energy Modeling System (NEMS).

 The stock of equipment depends on annual shipments and the lifetime of the equipment. 

DOE projected shipments under the base-case and for various standards cases. DOE determined 

that projected shipments were lower under the standards cases than under the base case, as the

higher installed costs would cause some consumers to forego equipment purchases. 

 The inputs for determining NPV are (1) total annual installed cost, (2) total annual 

operating cost savings, (3) discount factor, (4) present value of costs, and (5) present value of 

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

savings and the present value of increased total installed costs. It calculated net savings each year 

as the difference between total operating cost savings (including savings in electricity, repair, 

and maintenance costs) and increases in total installed costs (equipment price). DOE calculated 

savings over the life of the equipment, accounting for differences in yearly energy rates, and 

used a discount factor to discount future costs and savings to the present. 

DOE calculated increases in total installed costs as the product of the difference in the 

total installed cost between the base case and standards case and the annual shipments in the 

standards case. DOE expressed operating cost savings as decreases in operating costs associated 

with the lower energy consumption of equipment bought in the standards case compared to the 

base efficiency case. Total operating cost savings are the product of savings per unit and the 

number of units of each vintage surviving in a particular year.

2.10 CUSTOMER SUBGROUP ANALYSIS

The consumer subgroup analysis (chapter 11 of the TSD) evaluates economic impacts of 

standards on identifiable groups of consumers who might be disproportionately affected by new 

or amended energy efficiency standards. DOE evaluates the effects on particular subgroups of 

consumers in part by using the LCC spreadsheet model to analyze the LCC and PBP for those 

particular consumers. For the NOPR, DOE evaluated impacts on a small business subgroup 

using the LCC spreadsheet model. The customer subgroup analysis is discussed in detail in 

chapter 11 of the TSD. 

2.11 MANUFACTURER IMPACT ANALYSIS

The manufacturer impact analysis (MIA) assesses the impacts of new energy efficiency 

standards on manufacturers of small, large, and very large, air-cooled CUAC and CUHP. 

Potential impacts include financial effects, both quantitative and qualitative, that might lead to 

changes in the manufacturing practices for the equipment. DOE identifies those potential impacts 

through interviews with manufacturers and other interested parties. 

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As described in chapter 12 of this TSD, DOE conducted the MIA for the covered 

equipment in three phases, and further tailored the analytical framework based on stakeholder 

comments. In Phase I, DOE created a profile of the industry and analyzed publicly available 

financial information to derive preliminary inputs for the GRIM. In Phase II, an industry cash 

flow model and an interview questionnaire were prepared to guide subsequent discussions. In 

Phase III, manufacturers were interviewed, and the impacts of standards were assessed both 

quantitatively and qualitatively. DOE assessed industry and sub-group cash flow and NPV 

through use of the Government Regulatory Impact Model. Effects on competition, 

manufacturing capacity, employment, and cumulative regulatory burden were assessed based on 

feedback and discussions during manufacturer interviews. 

2.12 EMISSIONS ANALYSIS

 In the emissions analysis (chapter 13), DOE estimates the reduction in power sector 

emissions of carbon dioxide (CO2), nitrogen oxides (NOX), sulfur dioxide (SO2) and mercury 

(Hg) from potential energy conservation standards for the considered products. In addition, DOE 

estimates emissions impacts in production activities (extracting, processing, and transporting 

fuels) that provide the energy inputs to power plants. These are referred to as “upstream” 

emissions. Together, these emissions account for the full-fuel-cycle (FFC). In accordance with 

DOE’s FFC Statement of Policy (76 FR 51282 (Aug. 18, 2011)), the FFC analysis includes 

impacts on emissions of methane and nitrous oxide, both of which are recognized as greenhouse 

gases. 

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

latest version of EIA’s Annual Energy Outlook (AEO), supplemented by data from other sources. 

EIA prepares the Annual Energy Outlook using NEMS. Each annual version of NEMS 

incorporates the projected impacts of existing air quality regulations on emissions. The text 

below refers to AEO 2013, which generally represents current legislation and environmental 

regulations, including recent government actions, for which implementing regulations were 

available as of December 31, 2012. 

SO2 emissions from affected electric generating units (EGUs) are subject to nationwide 

and regional emissions cap and trading programs. Title IV of the Clean Air Act sets an annual 

emissions cap on SO2 for affected EGUs in the 48 contiguous states and the District of Columbia 

(D.C.). SO2 emissions from 28 eastern states and D.C. were also limited under the Clean Air 

Interstate Rule (CAIR), which created an allowance-based trading program that operates along 

with the Title IV program in those States and D.C. 70 FR 25162 (May 12, 2005). CAIR was 

remanded to EPA by the U.S. Court of Appeals for the District of Columbia Circuit (D.C. 

Circuit), but it remained in effect. See North Carolina v. EPA, 550 F.3d 1176 (D.C. Cir. 2008); 

North Carolina v. EPA, 531 F.3d 896 (D.C. Cir. 2008). On July 6, 2011 EPA issued a 

replacement for CAIR, the Cross-State Air Pollution Rule (CSAPR). 76 FR 48208 (August 8, 

2011). On August 21, 2012, the D.C. Circuit issued a decision to vacate CSAPR. See EME 

Homer City Generation, LP v. EPA, 696 F.3d 7, 38 (D.C. Cir. 2012). The court ordered EPA to 

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continue administering CAIR. AEO 2013 assumes that CAIR remains a binding regulation 

through 2040. 

 The attainment of emissions caps is typically flexible among EGUs and is enforced 

through the use of emissions allowances and tradable permits. Under existing EPA regulations, 

any excess SO2 emissions allowances resulting from the lower electricity demand caused by the 

adoption of an efficiency standard could be used to permit offsetting increases in SO2 emissions 

by any regulated EGU. In past rulemakings, DOE recognized that there was uncertainty about 

the effects of efficiency standards on SO2 emissions covered by the existing cap-and-trade 

system, but it concluded that no reductions in power sector emissions would occur for SO2 as a 

result of standards. 

 Beginning in 2015, however, SO2 emissions will fall as a result of the Mercury and Air 

Toxics Standards (MATS) for power plants, which were announced by EPA on December 21, 

2011. 77 FR 9304 (Feb. 16, 2012). In the final MATS rule, EPA established a standard for HCl 

as a surrogate for acid gas hazardous air pollutants (HAP), and also established a standard for 

SO2 (a non-HAP acid gas) as an alternative equivalent surrogate standard for acid gas HAP. The 

same controls are used to reduce HAP and non-HAP acid gas; thus, SO2 emissions will be 

reduced as a result of the control technologies installed on coal-fired power plants to comply 

with the MATS requirements for acid gas. AEO 2013 assumes that, in order to continue 

operating, coal plants must have either flue gas desulfurization or dry sorbent injection systems 

installed by 2015. Both technologies, which are used to reduce acid gas emissions, also reduce 

SO2 emissions. Under the MATS, NEMS shows a reduction in SO2 emissions when electricity 

demand decreases (e.g., as a result of energy efficiency standards). Emissions will be far below 

the cap that would be established by CSAPR, so it is unlikely that excess SO2 emissions 

allowances resulting from the lower electricity demand would be needed or used to permit 

offsetting increases in SO2 emissions by any regulated EGU. Therefore, DOE believes that 

efficiency standards will reduce SO2 emissions in 2015 and beyond. 

CAIR established a cap on NOX emissions in eastern States and the District of Columbia. 

Energy conservation standards are expected to have little or no physical effect on these emissions 

in those States covered by CAIR because excess NOx emissions allowances resulting from the 

lower electricity demand could be used to permit offsetting increases in NOx emissions. 

However, standards would be expected to reduce NOx emissions in the States not affected by the 

caps, so DOE estimates NOX emissions reductions from potential standards in the States where 

emissions are not capped.

 The MATS limit mercury emissions from power plants, but they do not include emissions 

caps and, as such, DOE’s energy conservation standards would likely reduce Hg emissions. DOE 

estimateD mercury emissions reduction using emissions factors based on AEO 2013, which 

incorporates the MATS. 

Power plants may emit particulates from the smoke stack, which are known as direct 

particulate matter (PM) emissions. NEMS does not account for direct PM emissions from power 

plants. DOE is investigating the possibility of using other methods to estimate reduction in PM 

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emissions due to standards. The great majority of ambient PM associated with power plants is in 

the form of secondary sulfates and nitrates, which are produced at a significant distance from 

power plants by complex atmospheric chemical reactions that often involve the gaseous 

emissions of power plants, mainly SO2 and NOx. The monetary benefits that DOE estimates for 

reductions in SO2 and NOx emissions resulting from standards are in fact primarily related to the 

health benefits of reduced ambient PM. 

2.13 MONETIZING CARBON DIOXIDE AND OTHER EMISSIONS

REDUCTIONS

DOE estimated monetary benefits likely to result from the reduced emissions of CO2 and 

NOX that are expected to result from each of the standard levels considered (see chapter 14 of the 

TSD).

 To estimate the monetary value of benefits resulting from reduced emissions of CO2, 

DOE uses the most current Social Cost of Carbon (SCC) values developed and/or agreed to by 

an interagency process. The SCC is intended to be a monetary measure of the incremental 

damage resulting from greenhouse gas (GHG) emissions, including, but not limited to, net 

agricultural productivity loss, human health effects, property damage from sea level rise, and 

changes in ecosystem services. Any effort to quantify and to monetize the harms associated with 

climate change will raise serious questions of science, economics, and ethics. But with full 

regard for the limits of both quantification and monetization, the SCC can be used to provide 

estimates of the social benefits of reductions in GHG emissions. 

 The Interagency Working Group on Social Cost of Carbon released an update of its 

previous report in 2013.b The most recent estimates of the SCC in 2015, expressed in 2012$, are 

$12.9, $40.8, $62.2, and $117 per metric ton of CO2 avoided. For emissions reductions that occur 

in later years, these values grow in real terms over time. Additionally, the interagency group 

determined that a range of values from 7 percent to 23 percent should be used to adjust the global 

SCC to calculate domestic effects, although DOE gives preference to consideration of the global 

benefits of reducing CO2 emissions. 

DOE multiplies the CO2 emissions reduction estimated for each year by the SCC value 

for that year in each of the four cases. To calculate a present value of the stream of monetary 

values, DOE discounts the values in each of the four cases using the discount rates that had been 

used to obtain the SCC values in each case.

 DOE recognizes that scientific and economic knowledge continues to evolve rapidly as to 

the contribution of CO2 and other GHG to changes in the future global climate and the potential 

resulting damages to the world economy. Thus, these values are subject to change. 

b Technical Update of the Social Cost of Carbon for Regulatory Impact Analysis Under Executive Order 12866. 

Interagency Working Group on Social Cost of Carbon, United States Government, May 2013. 

http://www.whitehouse.gov/sites/default/files/omb/inforeg/social_cost_of_carbon_for_ria_2013_update.pdf

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DOE also estimates the potential monetary benefit of reduced NOX emissions resulting 

from the standard levels it considers. Estimates of monetary value for reducing NOx from 

stationary sources range from 468 to $4,809 per ton in 2012$.c DOE calculates monetary benefits 

using a medium value for NOX emissions of $2,639 per short ton (in 2012$), and real discount 

rates of 3 percent and 7 percent. 

 

 DOE is evaluating appropriate valuation of avoided SO2 and Hg emissions. It did not 

monetize reduction in these emissions for the NOPR. 

2.14 UTILITY IMPACT ANALYSIS

To estimate the impacts of potential energy conservation standards con the electric utility 

industry, DOE uses a variant of the EIA’s National Energy Modeling System called NEMS-BT.d

 

NEMS is a large, multi-sectoral, partial-equilibrium model of the U.S. energy sector that EIA has 

developed over several years, primarily for the purpose of preparing the AEO. NEMS produces a 

widely recognized forecast for the United States through 2040 and is available to the public. 

The utility impact analysis is a comparison between the NEMS-BT model results for the 

base case and standard cases. The utility impact analysis reports the changes in installed capacity 

and generation that result from each standard level by plant type. DOE models the anticipated 

energy savings impacts from potential amended energy conservation standards using NEMS-BT 

to generate forecasts that deviate from the AEO Reference Case.

2.15 EMPLOYMENT IMPACT ANALYSIS

Energy conservation standards can affect employment both directly and indirectly. Direct 

employment effects are changes, resulting from produced by new standards, in the number of 

employees at the plants that produce covered equipment and at affiliated distribution and service 

companies. DOE evaluates direct employment impacts in the MIA. Indirect employment impacts 

may result if the imposition of standards causes expenditures to shift between goods (the 

substitution effect) and/or create changes in income and overall expenditure levels (the income 

effect). 

c U.S. Office of Management and Budget, Office of Information and Regulatory Affairs, 2006 Report to Congress 

on the Costs and Benefits of Federal Regulations and Unfunded Mandates on State, Local, and Tribal Entities, 

Washington, DC. 

d 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 (March 2000), available at: http://tonto.eia.doe.gov/ftproot/forecasting/05812000.pdf. 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” refers to DOE’s 

Building Technologies Program, under whose aegis this work is performed.)

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DOE utilizes Pacific Northwest National Laboratory’s 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 produced in buildings, industry, and transportation. In comparison 

with simple economic multiplier approaches, ImSET allows for more complete and automated 

analysis of the economic impacts of energy conservation investments. 

2.16 REGULATORY IMPACT ANALYSIS

In the NOPR stage, DOE prepared a regulatory impact analysis (RIA) pursuant to 

Executive Order 12866, Regulatory Planning and Review, 58 FR 51735, October 4, 1993, which 

is subject to review 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 equipment covered under this rulemaking. 

 DOE recognizes that voluntary or other non-regulatory efforts by manufacturers, utilities, 

and other interested parties can substantially affect energy efficiency or reduce energy 

consumption. DOE bases its assessment on the actual impacts of any such initiatives to date, but 

also considers information presented by interested parties regarding the impacts existing 

initiatives might have in the future.

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