10-i 

CHAPTER 10. NATIONAL IMPACT ANALYSES

TABLE OF CONTENTS

10.1 INTRODUCTION ................................................................................................... 10-1

10.2 NATIONAL ENERGY SAVINGS ......................................................................... 10-2

10.2.1 PRIMARY ENERGY SAVINGS ............................................................................ 10-2

10.2.2 FULL-FUEL-CYCLE ENERGY SAVINGS .......................................................... 10-5

10.2.3 NATIONAL ENERGY SAVINGS INPUTS .......................................................... 10-6

10.2.3.1 Shipments and Operating Stock Shipped during the Analysis Period ......... 10-6

10.2.3.2 Average Unit Energy Consumption ............................................................. 10-6

10.2.3.3 Site-to-Power Plant Conversion Factor ....................................................... 10-8

10.2.3.4 Primary Energy to Full-Fuel-Cycle Multipliers ........................................... 10-8

10.2.3.5 Rebound Rate Factor.................................................................................... 10-9

10.3 NATIONAL NET PRESENT VALUE ................................................................... 10-9

10.3.1 DEFINITION ........................................................................................................... 10-9

10.3.2 NET PRESENT VALUE INPUTS ........................................................................ 10-10

10.3.2.1 Total Annual Installed Cost Increases ....................................................... 10-10

10.3.2.2 Total Annual Operating Cost Savings ....................................................... 10-13

10.3.2.3 Discount Factor .......................................................................................... 10-16

10.4 RESULTS .............................................................................................................. 10-16

10.4.1 NATIONAL ENERGY SAVINGS RESULTS ..................................................... 10-16

10.4.2 NET PRESENT VALUE RESULTS..................................................................... 10-20

10.4.3 ALTERNATIVE ANALYSES RESULTS............................................................ 10-23

10.4.3.1 Overview .................................................................................................... 10-23

10.4.3.2 Alternative Scenario National Energy Savings Results ............................. 10-24

10.4.3.3 Alternative Scenario Net Present Value Results ........................................ 10-26

LIST OF TABLES

Table 10.1.1 Summary of NES and NPV Inputs .................................................................... 10-2

Table 10.2.1 Rebound Rate Scenarios for GSFL and IRL...................................................... 10-9

Table 10.4.2 Cumulative NES for GSFLs and IRLs, for All CSCs, Best Estimate.............. 10-17

Table 10.4.3 Cumulative Net Present Value for GSFL and IRL (billion 2011$) ................. 10-20

Table 10.4.4 Cumulative Equipment Cost Increase, Best Estimate (billion 2011$) ............ 10-20

Table 10.4.5 Cumulative Energy Cost Savings, Best Estimate (billion 2011$) ................... 10-21

Table 10.4.6 Alternative Scenario Variables ........................................................................ 10-23

Table 10.4.7 Cumulative Full-Fuel-Cycle NES, Alternative Scenarios (quads) .................. 10-25

Table 10.4.8 Cumulative NPV for Alternative Scenarios, 3% Discount Rate (billion 

2011$) .............................................................................................................. 10-27

Table 10.4.9 Cumulative NPV for Alternative Scenarios, 7% Discount Rate (billion 

2011$) .............................................................................................................. 10-27
10-ii

LIST OF FIGURES

Figure 10.2.1 Site-to-Power Plant Conversion Factor for Electricity ...................................... 10-8

Figure 10.3.1 Annual Electricity Prices by Sector (2011$) ................................................... 10-15

Figure 10.4.1 NES for GSFL and IRL Combined, All CSL 1 and Max CSL, Best 

Estimate............................................................................................................ 10-18

Figure 10.4.2 Full Fuel Cycle NES by Product Class Grouping, All CSL 1, Best 

Estimate............................................................................................................ 10-19

Figure 10.4.3 Full Fuel Cycle NES by Product Class Grouping, Max CSL, Best Estimate .. 10-19

Figure 10.4.4 GSFL Net Present Value, All CSL 1, Best Estimate ....................................... 10-21

Figure 10.4.5 GSFL NPV, Max CSL, Best Estimate ............................................................. 10-22

Figure 10.4.6 IRL NPV, All CSL 1, Best Estimate................................................................ 10-22
10-1 

CHAPTER 10. NATIONAL IMPACT ANALYSES 

10.1 INTRODUCTION

This chapter describes the method the U.S. Department of Energy (DOE) used to

estimate the national impacts of candidate standards cases (CSCs) for covered general service 

fluorescent lamps (GSFLs) and incandescent reflector lamps (IRLs). In the national impact 

analysis (NIA), DOE assesses the cumulative national energy savings (NES) of products shipped 

during a 30-year analysis period (2017 – 2046) and the net present value (NPV) of the total 

consumer economic impacts, by comparing the CSC to a base case, in which standards remain at 

the current level. As described in chapter 9 of this technical support document (TSD), a CSC is 

defined by setting the candidate standard level (CSL) for each product class, and the impact on 

any given product class depends on the levels set for other substitutable products. The CSCs 

considered in this preliminary analysis were defined in chapter 9 of this TSD. In addition to 

NES and NPV, this chapter reports DOE’s estimate of the monetary value to the nation of the 

cumulative energy savings and the total cumulative change in equipment costs resulting for the 

CSCs.

DOE performs all NIA calculations using a Microsoft Excel® spreadsheet which are 

available on regulations.gov, docket number EERE–2011–BT–STD–0006 at 

www.regulations.gov/#!docketDetail;D=EERE-2011-BT-STD-0006. Details regarding, and 

instructions for using, the NIA spreadsheet are provided in appendix 10A.

Table 10.1.1 summarizes the inputs to the NIA spreadsheet model. A brief description of 

the data is given for each input.
10-2 

Table 10.1.1 Summary of NES and NPV Inputs

Input Data Description

Shipments Annual shipments from the GSFL and IRL shipments model (see chapter 9 of 

this TSD) 

Stock of lamps Modeled from historical data and shipments projections (see chapter 9 of this 

TSD)

Effective date of standard 2017

Analysis period For products shipped from 2017 through 2046

Lamp and ballast 

characteristics

Wattage, first cost, installation cost, disposal cost (see chapter 9 of this TSD) 

Lamp Prices Annual price of lamps adjusted for price learning (see chapter 9 of this TSD) 

Projected electricity prices From AEO2012 to 2035 and extrapolated beyond 2035 (see chapter 9 of this 

TSD)

Site-to-primary electricity

conversion

Generated by the NEMS version corresponding to the 2012 AEO (to 2035)

and extrapolated beyond 2035

Rebound effect 0 percent of total energy savings in the commercial and residential sector in 

the reference case

Discount rate Real 3 and 7 percent 

Present year Future costs and savings are discounted to the year 2013

The following sections describe in detail the methodology and inputs for the NIA. 

Section 10.2 discusses DOE’s calculation of national energy consumption in the base-case and

standards case, and the resulting NES between these cases. Section 10.3 discusses the NPV 

calculation. Section 10.4 presents the NES and NPV results for the different CSCs, and under 

various scenarios. 

10.2 NATIONAL ENERGY SAVINGS

This section describes DOE’s calculation of the NES for the two categories of lamps 

(GSFL and IRL) under the four CSCs considered in this preliminary analysis. 

10.2.1 Primary Energy Savings 

 The annual NES quantifies the difference in energy use between the base case and a 

candidate standards case in a given year:

NES(y) = �AEC base(y) − AEC std(y)� × RF

Eq. 10.1 

 Where:
10-3 

NES(y)= national energy savings in year ya

AECbase(y)= base case annual national energy consumption at the power plant for all 

product classes combined in year y (quads), 

(quads),

AECstd(y)= standards case annual national energy consumption at the power plant for all 

product classes combined in year y (quads), and 

RF = rebound rate factor = 1- rebound rate (see appendix 10C). 

Positive values of NES correspond to a net energy savings following standards implementation, 

in other words, annual energy consumption (AEC) in the standards case is less than AEC in the 

base caseb

. 

 As discussed in chapter 9 of this TSD, for the purpose of computing the NES, it is not 

necessary to compute the total installed stock, S(y), of lamps and lamp-and-ballast systems in 

the United States. The only portion of the stock that is relevant to this calculation is the operating 

stock shipped during the analysis period (OSSDAP), denoted S′

(y), with the assumption that 

S′

(yrule − 1) = 0, where yrule= 2017, the compliance year of the new rule, is the first year of 

the analysis period. Eq. 10.1 can therefore be expressed as follows:

NES(y) = (AEC′

base(y) − AEC′std(y)) × RF 

 Eq. 10.2 

Where:

AEC′

base(y)= base case annual national energy consumption of the OSSDAP at 

the power plant for all product classes combined in year y (quads), and 

AEC′

std(y)= standards case annual national energy consumption of the OSSDAP at the 

power plant for all product classes combined in year y (quads). 

The cumulative national energy savings is the sum of each NES(y) for all operating stock 

shipped during the 30-year analysis period (2017 – 2046). The analysis tracks the energy use of 

the stock shipped during the analysis period until the last unit is assumed to be retired, in 2080. 

The cumulative NES is computed as follows: 

NEScum = � NES(y)

y

Eq. 10.3

Where:

NEScum = cumulative national energy savings (quads). 

 

a Note that the time variable y is a discrete variable representing any year between 2017-2080 and is not continuous. 

For quantities that depend on y, the notation f(y) is used, instead of fy, to avoid confusion with other subscripts. b Following the example of the 2011 fluorescent lamp ballast final rule and for reasons given therein, DOE is 

assuming that heating, ventilating, and air conditioning (HVAC) interactions on NES are negligible. 
10-4 

DOE computes the AEC for IRLs by summing over the OSSDAP of each lamp option, as 

reflected in the following equation: 

AECIRL

′ (y) = �� Sl,IRL

′ (y) × UECl,IRL(y)

l

� × SP(y)

Eq. 10.4

Where:

Sl,IRL

′ (y) = the OSSDAP of IRL option l in year y (number of units), 

UECl,IRL(y) = the annual unit energy consumption of IRL option l in year y, as described 

in section 10.2.3.2 (kWh), and 

SP(y) = time variable site-to-power-plant energy conversion factor that converts site 

electricity use (kWh) to primary energy consumed at the power plant 

(quads/kWh).

As discussed in chapter 9 of this TSD, DOE computes shipments and stock of GSFLs 

disaggregated according to a set of national-average ballast types, to which the lamps are 

coupled. Each GSFL product class grouping in the model is composed of one or several ballast 

types. DOE calculated the AEC for GSFL by summing over all of the ballast types:

AECGSFL

′ (y) = �AECj,GSFL′ (y)

j

Eq. 10.5

Where:

AECj,GSFL

′ (y) = the annual energy consumption by the OSSDAP of GSFLs that are 

installed on ballasts of type j in year y (quads). 

The AEC of GSFLs installed on each ballast type is computed in turn by summing over 

the energy consumption of the various lamp options that are installed on that ballast, as shown by 

the following equation: 

AEC′

j,GSFL(y) = �� S′j(y) × φl,j(y) × UECl,j,GSFL(y)

l

� × SP(y)

Eq. 10.6 

Where: 

S′

j(y)= the OSSDAP of GSFL installed on ballasts of type j, in year y, calculated by the 

shipments model (number of units), 
10-5 

φl,j(y)= the fraction of the OSSDAP of GSFL installed on ballast type j that is 

represented by lamp option, l,

c

UECl,j,GSFL(y) = average unit energy consumption of lamp option l installed on ballast 

type j in year y, as described in section 

calculated by the shipments model,

10.2.3.2 (kWh), and 

SP(y) = time variable site-to-power-plant energy conversion factor that converts site 

electricity use (kWh) to primary energy consumed at the power plant 

(quads/kWh).

10.2.2 Full-Fuel-Cycle Energy Savings 

 DOE has historically presented the NES computed based on the primary energy savings

at the power plant, as described in the previous section. Per DOE’s 2011 Statement of Policy for 

Adopting Full Fuel Cycle Analyses, DOE now uses full-fuel-cycle (FFC) measures of energy use 

and emissions in its energy conservation standards analyses.1

 In addition to the primary energy 

used at the power plant to supply electricity to the site of use and account for transmission and 

distribution losses, the FFC analysis also accounts for energy consumed up-stream of the power 

plant in extracting, processing, and transporting or distributing the primary fuels to the power 

plant, as described in appendix 10B.

 As shown in Eq. 10.7, the FFC national energy savings (NESFFC) are obtained by 

multiplying the primary energy savings (Eq. 10.2) by the FFC multiplier computed for the same 

year, μ(y): 

 

NESFFC(y) = (AEC′

base(y) − AEC′std(y)) × RF × μ(y)

Eq. 10.7 

 Where:

μ(y)= the FFC multiplier and

all other variables were defined in Eq. 10.1 and Eq. 10.2. 

 The cumulative FFC energy savings are calculated by summing the annual savings from 

2017 through 2080: 

NES′FFC,cum = � NES′FFC(y)

Eq. 10.8 

 

c The lamp options include all lamp types for all CSLs (see chapter 9 of this TSD).
10-6 

10.2.3 National Energy Savings Inputs 

As described in the preceding sections, the following inputs are used for calculating the national

energy savings:

• shipments and operating stock shipped during the analysis period, 

• average unit energy consumption (UEC),

• site-to-power-plant conversion factor (SP), 

• primary energy to full fuel cycle multipliers (μ), and 

• rebound rate factor (RF).

These inputs are further discussed in the following sections. 

10.2.3.1 Shipments and Operating Stock Shipped during the Analysis Period

 The shipments model, described in chapter 9 of this TSD, calculated the shipments of the 

representative product class groupings for each year of the 30-year shipments analysis (2017 

through 2046). Based on that analysis, the model developed a description of the OSSDAP and of 

the surviving stock shipped during the analysis period through to the end of its lifetime. 

10.2.3.2 Average Unit Energy Consumption 

DOE calculates the average annual UEC for each GSFL and IRL option by multiplying 

the average lamp power consumption by the average annual hours of use for that lamp in the 

sector under consideration. For IRLs, this is simply the rated lamp wattage multiplied by the 

annual hours of use: 

UECl,IRL = 

Wl,IRL × u�IRL

1000

Eq. 10.9 

Where:

UECl,IRL = the annual UEC of IRL option l (kWh), 

Wl,IRL = the rated wattage of IRL option l, corrected for the impact of dimmers, as 

discussed in chapter 9 of this TSD (W), and

u�IRL = the average annual hours of use for an IRL in the sector being considered 

(hours), as presented in chapter 6 of this TSD. 

 For GSFL, the UEC depends also on the average ballast factor for lamps in the product 

class grouping being considered: 

UECl,j,GSFL = Wl,GSFL × BFj × u�GSFL

1000

Eq. 10.10 

Where:
10-7 

UECl,j,GSFL = the annual UEC of GSFL option l, when it is coupled to a ballast of type j 

(kWh),

Wl,GSFL= the rated wattage of GSFL option l (W), 

BFj = the national average ballast factor of ballasts of type j, as presented in chapter 9 of 

this TSD, and 

u�GSFL= the average annual hours of use for a GSFL in the sector being considered

(hours), as presented in chapter 6 of this TSD. 

 To compute the average hours of use for GSFL and IRL, DOE computed the averages 

of the sector-specific hours-of-use distributions presented in chapter 6 of this TSD. When 

analyzing GSFLs in the combined commercial and industrial sectors, DOE weighted these 

sectors’ distributions using weighting factors computed as described in chapter 9 of this TSD. 

DOE assumed that lighting controls are installed on an increasing fraction of lamps in 

the commercial and industrial sectors as a result of building codes (see appendix 9A of this 

TSD), and assumed a 75 percent compliance rate. To account for the impact of lighting controls 

on the NES, DOE reduced the UEC by a fixed 30 percent in the stock of lighting in which 

switching-based controls were assumed to operate, where the savings estimate was based on a 

meta-analysis of field measurements of energy savings from commercial lighting controls by 

Williams et al. (2012).2 DOE’s projection of the penetration of lighting controls was described 

in appendix 9A. 

DOE included two projections of controls adoption. In the reference case, which is 

DOE’s best estimate, controls penetration grows year-by-year in the commercial and industrial 

sector, as driven by building codes and shown in appendix 9A. In the second case, controls 

penetration was assumed to remain fixed at the same level as the first year in the analysis 

period. The latter was included to determine the impact of controls on the estimated energy 

savings from the rulemaking; DOE does not consider the fixed case scenario realistic given the 

strong driving factors for controls adoption. 

For each lamp option (whether IRL or GSFL and regardless of ballast type), the lighting 

controls impact was computed in the following way: 

UECl(y) = UECl × �1 − LCadopt(y) + LCadopt(y) × LCeffect�

Eq. 10.11 

 Where:

 

UECl(y)= weighted average annual electricity consumption (kWh) of the lamp option, 

UECl= annual unit electricity consumption (kWh) of lamp option l, computed using the 

previous equations, 

LCadopt(y)= the lumen capacity fraction of lighting estimated to be operating under 

switch-based lighting controls in year y, and 
10-8 

LCeffect = a parameter describing the effect of switch-based lighting controls on energy 

consumption, taken to be 0.7. 

10.2.3.3 Site-to-Power Plant Conversion Factor 

 To estimate the energy used at the power plant in order to supply the electricity used onsite by the two categories of lamps, DOE multiplied the site electricity, UECl(y), by a site-topower-plant conversion factor,d

 which accounts for average losses associated with the 

generation, transmission, and distribution of electricity from the fleet of U.S. power plants to the 

point of use. DOE used annual site-to-source conversion factors based on the version of the 

National Energy Modeling System (NEMS) that corresponds to the Energy Information 

Administration’s Annual Energy Outlook 2012 (AEO2012).3

Figure 10.2.1

The factor changes over time in 

response to projected changes in generation sources (the types of power plants projected to 

provide electricity to the country). shows how the site-to-power plant conversion 

factor is expected to change during the NES and NPV analysis period. 

Figure 10.2.1 Site-to-Power Plant Conversion Factor for Electricity

10.2.3.4 Primary Energy to Full-Fuel-Cycle Multipliers

For this preliminary analysis, DOE calculated FFC energy savings using a methodology 

described in appendix 10B. As discussed previously, the FFC energy savings are obtained by 

 

d In previous rulemakings the site-to-power-plant conversion factor has been referred to as the site-to-source 

conversion factor. The terminology is modified here to clarify that the analysis only accounts for the energy used at 

the power plants, but not energy used upstream of the power plants to provide that service. The latter is incorporated 

in the full-fuel-cycle analysis.
10-9 

multiplying the primary energy savings at the power plant by the FFC multiplier. The estimated 

FFC multiplier (μ) is essentially constant, ranging between 1.040 and 1.045 from 2017 to 2080. 

10.2.3.5 Rebound Rate Factor

DOE generally accounts for the direct rebound effect in its estimates of the NES. As 

discussed in chapter 2 of this TSD, DOE received public comment regarding the rebound rates 

proposed in the framework and performed additional analyses to reevaluate the proposed rates 

based on the most recent available data. Presented in appendix 10C, that analysis reveals no 

current evidence for lighting rebound in the United States. Therefore, for its best estimate, DOE 

assumes no lighting rebound. However, DOE conducted sensitivity analyses for two additional 

scenarios to determine the potential impact of alternative assumptions on the rulemaking. In the 

first alternative scenario, DOE conducted the analysis using the assumptions for rebound rates 

proposed in the framework document. In its second alternative scenario, DOE assumed the 

values used for lighting rebound in NEMS. As described in appendix 10C, the latter were based 

on an estimate of the average rebound rate for a suite of appliances, and the lighting data 

contained therein were from the early 1990s. The values used in the different best estimate and 

alternative scenarios are summarized in Table 10.2.1. 

Table 10.2.1 Rebound Rate Scenarios for GSFL and IRL

Rebound Scenario Commercial 

Rebound Rate

Residential 

Rebound Rate

Best Estimate 0% 0%

Framework assumption 1% 8.5%

NEMS 15% 15%

10.3 NATIONAL NET PRESENT VALUE

10.3.1 Definition

The NPV is the difference between the present value of savings (PVS) in operating cost 

resulting from the use of more efficient appliances under the standard and the present value of 

increased total installed costs (PVC) of those appliances. The NPV is described by the following 

equation: 

NPV = PVS − PVC

Eq. 10.12 

Where:

PVS= present value of savings in operating cost (including costs for energy, repair, and 

maintenance in 2011$); and 

PVC= present value of increase in total installed cost (including costs for equipment and 

installation in 2011$). 
10-10 

DOE determined the PVS and PVC according to the following expressions: 

PVS = �OCS(y) × DF(y)

y

Eq. 10.13

PVC = �ECI(y) × DF(y)

y

Eq. 10.14 

Where:

OCS(y)= total annual operating cost savings realized in the OSSDAP in year y, relative 

to the base case (2011$), 

ECI(y)= total annual equipment cost increase for shipments in year y, relative to the base 

case (2011$), and 

DF(y)= discount factor in each year (defined in section 10.3.2.3).

 DOE calculated PVC from 2017 to 2046 (the duration of the shipments analysis period), 

and PVS from 2017 to 2080 (to account for the full lifetime off all stock shipped during the 

analysis period). The contributions to PVC and PVS for each year were discounted to 2013. The 

following sections describe how DOE derives the variables in Eq. 10.13 and Eq. 10.14

10.3.2 Net Present Value Inputs

 The inputs to DOE’s calculation of the NPV of costs and savings for the nation are:

• total annual installed cost (TIC) in the base case and the standards cases,

• total annual operating cost (TOC) for the OSSDAP in the base case and the standards 

cases, and

• discount factor (DF). 

The computation of these inputs from the outputs of upstream analyses is detailed in the 

following sections. 

10.3.2.1 Total Annual Installed Cost Increases 

DOE calculated the total annual equipment cost increase of using more efficient lamps in 

the standards cases relative to the base case as the difference between the TIC in the standards 

case and the base case:

ECI(y) = TICstd(y) − TICbase(y)

Eq. 10.15 

 Where:
10-11 

TICstd(y) = the total installed cost of equipment shipped in year y in the standards case 

(2011$), and

TICbase(y) = the total installed cost of equipment shipped in year y in the base case

(2011$).

Due to the higher cost of more efficacious products in the standards case versus the base 

case, cost increases appear as negative values in the NPV.

For IRLs, the per-unit installed cost includes the lamp first cost and the lamp installation 

cost. Thus, the TIC is given by the following equation:

TICIRL(y) = � sIRL,l(y) × �pIRL,l(y) + ICIRL�

l

Eq. 10.16 

Where:

sIRL,l(y) = total shipments of IRL option l in year y (number of units),

pIRL,l(y) = purchase price of IRL option l in year y, including corrections for learning 

(2011$/unit), and 

ICIRL = installation cost of IRLs (2011$/unit). 

The computation of the variables in Eq. 10.16 is described in chapter 9 of this TSD. 

For GSFLs, the total annual installed cost is described by summing over the ballast types:

TICGSFL(y) = �TICGSFL,j(y)

j

Eq. 10.17 

Where:

TICGSFL,j(y)= total installed cost for l lamps and ballasts shipped for installation in lampand-ballast systems of ballast type j, in year y (2011$). 

Eq. 10.17 is used to compute either the TIC for all GSFLs, by summing over all ballast 

types, or to compute the TIC for GSFLs in a particular product class grouping, by summing only 

over the ballast types within that grouping. 

In the case of GSFLs, for lamps installed on new ballasts, DOE accounts for the first cost 

of the lamp, the first cost of the ballast, and the ballast installation cost. For ballast replacements,
10-12 

DOE also accounts for the disposal cost of the retired lampe. For lamp replacements on existing 

ballasts, DOE accounts for the disposal cost of the retired lamp and the first cost of the new

lamp. For each product class grouping j, the total annual installed cost is described by the 

following equation: 

TICj(y) = sB,j(y) × �pB,j(y) + ICB,j� +

sGSFL,j(y) × ��[MSl,j(y) ×

l

pGSFL,l,j(y)] + ICGSFL,j� + DCGSFL,j

Eq. 10.18 

Where:

sB,j(y)= total shipments of ballasts of type j in year y (number of units), 

pB,j(y)= purchase price of ballasts of type j in year y, including corrections for learning 

(2011$/unit), 

ICB,j(y)= installation cost of ballast type j (2011$/unit), 

sGSFL,j(y)= shipments of GSFLs coupled to ballasts of type j in year y (number of units),

MSl,j(y)= market share of lamp option l among new lamps coupled to ballasts of type j 

in year y, 

pGSFL,l,j(y)= purchase price of lamp option l in year y, including corrections for learning 

and any rare earth oxide price impacts (2011$/unit), 

ICGSFL,j= installation cost of GSFLs coupled to ballasts of type j (2011$/unit), and

DCGSFL,j= disposal cost of GSFLs coupled to ballasts of type j (2011$/unit). 

The calculation of the variables in Eq. 10.18 is described in chapter 9 of this TSD. 

The annual disposal cost in product class j, DCGSFL,j(y), is calculated using the following 

equation: 

DCGSFL,j(y) = ADCGSFL,j × �[sGSFL,j(v)

y−1

v=y0

 × PLBR,j(y − v)] 

Eq. 10.19 

 Where:

ADCGSFL,j= average disposal cost for retired GSFLs installed on ballasts of type j, which 

is taken to be 30 percent of the individual lamp disposal cost, since DOE assumes 

 

e As discussed in chapter 9, DOE assumes that old lamps are disposed of upon ballast replacements so that all new 

ballasts are coupled with new lamps when they are installed. 
10-13 

that 30 percent of consumers pay this cost, as discussed in chapter 8 of this TSD 

(2011$/unit),

sGSFL,j(v) = shipments of GSFLs installed on ballasts of type j, in vintage year v

(number of units), and

PLBR,j(y − v)= the probability that a lamp or its ballast is retired in year y − v of the 

lamp’s life, for lamp-and-ballast systems of ballast type j, as presented in chapter 

9 of this TSD. 

To establish the per-unit installed cost, DOE based installation costs on 

nationally representative values for each lamp design or each lamp-and-ballast system. 

See chapter 8 of this TSD for further descriptions of installation costs, and chapter 7 of 

this TSD and appendix 7A of this TSD for lamp and ballast prices. 

10.3.2.2 Total Annual Operating Cost Savings 

 

DOE expresses savings in operating costs as cost reductions associated with the lower 

energy consumption of products shipped in the standards case compared to the base case. DOE 

calculated the total annual operating cost savings as the difference between the TOC in the 

standards case and the base case. As for the computation of the NES, the TOC need not be 

computed for the total stock S, but only for the OSSDAP, S′: 

OCS(y) = TOC′

base(y) − TOC′std(y)

Eq. 10.20 

Where:

OCS(y) = the total operating cost saving of OSSDAP in year y (2011$), 

TOCbase

′ (y) = the total operating cost of the OSSDAP in year y in the base case (2011$), 

and

TOCstd

′ (y) = the total operating cost of the OSSDAP in year y in the standards case 

(2011$). 

The only component of annual operating cost for lamps is the cost of electricity 

consumption. As described in the life-cycle cost (LCC) and payback period (PBP) analysis 

(chapter 8 of this TSD), DOE calculates total annual operating costs based on national average 

electricity prices. DOE used the reference-case, sector-specific electricity price projections from 

AEO2012 to establish all electricity prices. As AEO2012 only projects prices through 2035, 

electricity prices in later years were extrapolated based on the 2025 through 2035 sector-specific 

trends, up through 2060, after which prices were assumed to remain constant. As discussed in 

chapter 9 of this TSD, when jointly analyzing lamps in the commercial and industrial sectors, 

DOE used a weighted average of the commercial and industrial electricity price projections, 

based on the fraction of the total stock that is installed in the industrial sector for each ballast 

type. 
10-14 

DOE calculated annual TOC for IRLs by summing over the operating costs of all lamp 

options in the OSSDAP, according to the following expression: 

TOC′IRL(y) = pE(y) × �[S′

l,IRL(y) × UECl,IRL(y)]

l

Eq. 10.21 

Where:

pE(y)= the price of electricity, in year y, as forecasted in the AEO2012 reference 

scenario (2011$/kWh), 

Sl,IRL

′ (y) = the OSSDAP of IRL type l in year y (number of units), and

UECl,IRL(y) = the average unit energy consumption of IRL type l in year y, as 

computed using Eq. 10.11 (kWh/unit). 

For IRLs, DOE uses the forecast of national-average commercial and residential 

electricity prices for its analysis in the commercial and residential sectors, respectively.

 To compute the annual TOC for GSFLs, DOE sums the operating costs of lamps installed 

on all ballast types from the shipments analysis:

TOC′GSFL(y) = �TOCj,GSFL(y)

j

Eq. 10.22 

Where:

TOCj,GSFL(y) = the annual total operating costs of lamps installed on ballasts of type j in 

year y (2011$). 

 The TOC for lamps installed on a particular ballast type is given by a sum over the 

OSSDAP fractions of the lamp options that can be installed on that ballast: 

TOC′j,GSFL(y) = Sj,GSFL

′ (y) × pE(y) × �[φl,j(y) × UECl,j,GSFL(y)]

l

Eq. 10.23 

Where:

Sj,GSFL

′ (y) = the OSSDAP of GSFLs installed on ballasts of type j in year y

(number of units), 

pE(y)= the price of electricity, in year y, as forecasted in the AEO2012

reference scenario (2011$/kWh), 
10-15 

φl,j(y) = the fraction of the OSSDAP of lamps installed on ballasts of type j that are 

lamp option l, and

UECl,j,GSFL(y) = the annual unit energy consumption of lamp option l installed on ballast 

type j, as computed using Eq. 10.11 (kWh/unit). 

For 4-foot medium bipin (MBP) lamps installed on residential ballasts, DOE used the 

projection of national average residential electricity prices. For all other GSFLs in the stock, 

DOE used a weighted average of the electricity price projections in the commercial and 

industrial sectors, as described in chapter 9 of this TSD. 

 To understand the importance of uncertainty in these projections, DOE performed 

sensitivity analyses using the high- and low-economic growth scenarios from AEO2012 to 

establish electricity prices. Figure 10.3.1 shows annual electricity price projections used as inputs 

for the high-, reference-, and low-economic growth scenarios, for all sectors. Note that there is 

not a consistent relationship over time between the economic growth scenario and its impact on 

electricity prices. In the early years of the analysis period, the low-economic growth scenario in 

the residential sector results in higher electricity prices than the high growth scenario. The 

opposite is true in later years. 

Figure 10.3.1 Annual Electricity Prices by Sector (2011$) 
10-16 

 As discussed in section 10.2.3.5, DOE has included in this preliminary analysis scenarios 

that include rebound effects to adjust its estimates of NES. In principle, the rebound effect also 

affects the energy costs to consumers in the standards case. However, the take-back in energy 

consumption associated with the rebound effect provides consumers with increased value (e.g.,

improved lighting quality). As described in the 2012 residential furnace fan NIA4

10.3.2.3 Discount Factor 

, DOE believes 

that, if it were able to monetize the increased value to consumers of the rebound effect, this value 

would be similar in value to the foregone energy savings. Therefore, the economic impacts on 

consumers with or without the rebound effect are the same, so DOE does not adjust operating 

cost savings in the NIA, based on rebound effects. 

DOE multiplied monetary values in future years by a discount factor to determine the 

present value. The DF is described by the equation: 

DF = 1

(1 + r)(y−yp)

Eq. 10.24 

Where:

r = discount rate, 

y = year of the monetary value, and 

yP = year for which the present value is being determined.

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. DOE defined the present year as 2013. 

10.4 RESULTS 

This section summarizes the NES and NPV modeling results for the four candidate 

standards cases and the results of the alternative analyses used to determine uncertainties and the 

impacts of key variables.

10.4.1 National Energy Savings Results 

Table 10.4.2 presents DOE’s best estimates of the cumulative NES relative to the base 

case for GSFLs and IRLs, for the four CSCs. Results are shown for both full-fuel-cycle NES and 

primary (at the power plant) NES. 
10-17 

Table 10.4.1 Cumulative NES for GSFLs and IRLs, for All CSCs, Best Estimate

National Energy Savings* (quads)

Analysis Type Scenario All 

CSL1

All CSL1

Except 

T5=Baseline

Max CSL

Max CSL

Except

T5=Baseline

Standard Best Estimate

GSFL 0.94

(0.90) 

0.61

(0.59) 

4.52 

(4.34) 

4.21

(4.05) 

IRL 0.14 

(0.13)

0.14

(0.13)

0.14 

(0.13)

0.14

(0.13)

*Results shown are for full-fuel-cycle NES. Results in parentheses are for primary NES. 

 As discussed in chapter 9 of this TSD, the shipments analysis implements a consumer 

choice model to project shipments. Therefore, a fraction of the NES (and NPV) of each CSC 

derives from consumer product switching in response to the new standard. GSFLs offer a 

significantly larger potential for energy savings than IRLs for both All CSL 1 and Max CSL. This 

is expected as the base case electricity consumption for GSFLs is much greater than the IRL 

electricity consumption and, therefore, has a higher potential for energy savings. Note that, 

because IRLs have only one CSL, and no product switching occurs, the NES for IRLs is the 

same for all considered CSCs.

The CSCs in which T5 efficacy standards are held at their baseline levels, while T8 

standards are updated to All CSL 1 or to Max CSL, lead to a reduced NES relative to the CSCs in 

which updated standards are applied to both T8s and T5s. In the All CSL 1 standards case, the 

NES reduction is substantial, at approximately 30 percent. The reduction is more modest in the 

Max CSL standards case, at the level of a few percent. Because standards that exclude T5s do not 

save additional energy, DOE did not pursue these options further in the NES of this preliminary

analysis. 

Figure 10.4.1 shows the combined (GSFL and IRL) best estimate of annual site NES for 

the All CSL 1 CSC and Max CSL CSC. The NES for both CSCs show an increase during the first 

years of the analysis period but are later reduced as incursion of lighting using light-emitting 

diodes (LEDs) into the GSFL and IRL markets reduces energy use and, thus, energy savings. The 

modeling of the incursion of LEDs into the GSFL and IRL market is described in chapter 9 of 

this TSD. Energy savings also go down after 2046 as the stock of lamps installed during the 30-

year shipments analysis period diminishes due to lamp retirements. 
10-18 

Figure 10.4.1 NES for GSFL and IRL Combined, All CSL 1 and Max CSL, Best Estimate

Figure 10.4.2 and Figure 10.4.3 show the FFC NES by product class grouping, for both 

GSFL and IRL, for All CSI 1 and Max CSL, respectively. The NES derived from 4-foot MBP 

lamps far outweighs savings from any other product class grouping, as these products have the 

largest market share and base energy consumption. Negative energy savings are seen in a few 

product class groupings (e.g., T5 standard output (SO)), because the standard drives increased 

shipments of such lamps in the standards case as consumers switch away from less efficacious 

products (e.g., 4-foot MBP T8s). This switching yields an overall energy savings, even though 

the savings for individual product class groupings may be negative. 
10-19 

Figure 10.4.2 Full Fuel Cycle NES by Product Class Grouping, All CSL 1, Best Estimate

Figure 10.4.3 Full Fuel Cycle NES by Product Class Grouping, Max CSL, Best Estimate
10-20 

10.4.2 Net Present Value Results

Table 10.4.3 shows the cumulative NPV for GSFLs and IRLs for the four CSCs, 

calculated assuming both a 3- percent and a 7- percent discount rate. The CSCs that exclude T5s

lead to a reduced NPV, compared to their corresponding All CSL 1 and Max CSL standard levels, 

because of the reduced NES described in the previous section. Therefore, DOE did not pursue 

these options further in this preliminary analysis. 

Table 10.4.2 Cumulative Net Present Value for GSFL and IRL (billion 2011$) 

Table 10.4.4 and Table 10.4.5 show estimated cumulative equipment cost increases and 

the cumulative energy cost savings, respectively, for GSFLs and IRLs shipped during the 

analysis period, for the two remaining CSCs.

Table 10.4.3 Cumulative Equipment Cost Increase, Best Estimate (billion 2011$) 

All CSL 1 Max CSL

3% Discount 

Rate

7% Discount 

Rate

3% Discount 

Rate

7% Discount 

Rate

GSFL Equipment Cost Increase 3.1 1.9 2.0 1.2

IRL Equipment Cost Increase 0.51 0.52 0.51 0.52

Total Equipment Cost Increase 3.6 2.4 2.5 1.7

3% Discount Rate

Analysis 

Type Scenario

Product Class 

Grouping

All CSL 1

GSFL

All CSL1 Except 

T5=Baseline

Max CSL

Max CSL Except

T5=Baseline

Standard Best 

Estimate

GSFL 2.0 1.3 23 22

IRL 0.040 0.040 0.040 0.040

Total* 2.0 1.3 23 22

7% Discount Rate

Standard Best 

Estimate

GSFL 0.83 0.58 13 13 

IRL -0.17 -0.17 -0.17 0.17

Total* 0.65 0.40 13 12 

*Totals may not add due to rounding
10-21 

Table 10.4.4 Cumulative Energy Cost Savings, Best Estimate (billion 2011$) 

All CSL 1 Max CSL

3% Discount 

Rate

7% Discount 

Rate

3% Discount 

Rate

7% Discount 

Rate

GSFL Energy Cost Savings 5.0 2.7 25 14

IRL Energy Cost Savings 0.55 0.34 0.55 0.34

Total Energy Cost Savings* 5.5 3.0 25 14

*Totals may not add due to rounding

Figure 10.4.4 and Figure 10.4.5 show the estimated annual NPV at All CSL 1 and Max 

CSL for GSFLs, respectively. The solid lines represent NPV assuming a 3-percent discount rate, 

while the dashed lines represent NPV assuming a 7-percent discount rate. 

Solid lines: 3% discount rate; dashed lines: 7% discount rate

Figure 10.4.4 GSFL Net Present Value, All CSL 1, Best Estimate
10-22 

Solid lines: 3% discount rate; dashed lines: 7% discount rate

Figure 10.4.5 GSFL NPV, Max CSL, Best Estimate

Figure 10.4.6 shows the estimated annual NPV for IRLs at All CSL 1. The reduction in 

equipment cost savings and NPV in the beginning of the analysis period is due to purchases of 

high-priced, long-lived lamps for CSL 1, relative to the base-case. 

Solid lines: 3% discount rate; dashed lines: 7% discount rate

Figure 10.4.6 IRL NPV, All CSL 1, Best Estimate
10-23 

10.4.3 Alternative Analyses Results

10.4.3.1 Overview

 To gauge the importance of various assumptions and uncertainties in the NIA, DOE 

carried out the NIA for several alternative scenarios and compared the NES and NPV results to 

the best-estimate scenario. Table 10.4.5 summarizes the model inputs used to: 

a) conduct uncertainty analyses based on rare earth oxide (REO) prices and economic 

growth scenarios, 

b) determine the impact of different rebound rate assumptions, 

c) determine the impact of growing LEDs and controls penetration into the GSFL and IRL 

lighting markets, and 

d) test the effect of manufacturers meeting an IRL standard at CSL 1 using short-life lamps. 

These alternative analyses, listed in Table 10.4.6, are discussed below. The scenario 

variables are described in chapter 9 of this TSD. 

Table 10.4.5 Alternative Scenario Variables

Scenario Variables

Analysis Type Scenario 

AEO2012 

Economic 

Growth

Rebound 

Rate

Rare 

Earth 

Price

LED

Controls 

Adoption

Short IRL 

Life

(a) Uncertainty 

Analyses

REO High Ref Ref* High Ref Ref No

REO Low Ref Ref Low Ref Ref No

High Economic 

Growth High Ref Ref Ref Ref No

Low Economic 

Growth Low Ref Ref Ref Ref No

(b) Rebound 

Scenarios

Framework Rebound Ref Framework** Ref Ref Ref No

NEMS Rebound Ref NEMS† Ref Ref Ref No

(c) Impact 

Determination

Fixed Controls Ref Ref Ref Ref Fixed No

No LED Ref Ref Ref Fixed Ref No

(d) Alternative 

Technology

Scenario

IRL Short Life Ref Ref Ref Ref Ref Yes

* Reference rebound rates are as follows: Commercial 0% and Residential 0%.

** Framework rebound rates are as follows: Commercial 1% and Residential 8.5%

† NEMS rebound rates are as follows: Commercial 15%, Residential 15%.

Uncertainty Analyses. As discussed in chapter 9 of this TSD, DOE developed alternative 

scenarios for high and low REO prices reflecting the highest price observed during the 2011 
10-24 

spike in REO prices and the much lower prices that had been common prior to that spike. 

Uncertainty in the future price of REOs leads directly to uncertainty in the NPV of an updated 

standard, because these prices impact the first cost of GSFLs. Such price uncertainty can also 

lead indirectly to uncertainty in the NES and NPV, because the different first costs, and 

operation and maintenance (O&M) costs of lamps and lamp-and-ballast systems will lead to 

different projected market shares for lamps and lamp-and-ballast systems. Note that REO price 

uncertainty is not applicable to IRLs, because IRLs do not contain REOs. 

 Economic growth uncertainty, reflected by uncertainty in future electricity prices, leads 

to uncertainty in the NPV of an updated standard, as discussed in section 10.3.2.2. 

Rebound Scenarios. The rebound rate scenarios are discussed in section 10.2.3.5 and 

appendix 10C. As explained earlier in this chapter, rebound rates are assumed to affect NES, but 

not operating cost savings, therefore the NPV is not sensitive to rebound rate. 

Impact Determination. Regarding the penetration of LED lighting products and lighting 

controls into the GSFL and IRL lighting markets, as discussed in chapter 9 of this TSD, DOE 

made two key assumptions about changes in the market and usage patterns for lamps over the 

analysis period. Solid-state lighting products (such as LEDs) were assumed to capture an 

increasing fraction of the current market for GSFL and IRL products, rising to roughly 70 

percent of the market by the end of the analysis period. Similarly, an increasing fraction of lamps 

were assumed to be subject to automatic lighting controls in the commercial and industrial 

sectors, owing to building codes requiring such controls. Both of these assumptions will reduce 

the NES and NPV outputs from the NIA because they reduce the number of covered lamps and 

their energy consumption, respectively. DOE determined the impact of these two assumptions by 

running two shipments and NIA scenarios in which the LED market share and prevalence of 

lighting controls were each held fixed in turn at their present-day values. 

Alternative Technology Scenario. DOE investigated an alternative technology scenario 

for IRLs meeting CSL 1. This scenario, discussed in chapter 9 of this TSD, represents a situation 

in which, rather than eliminating baseline technologies in favor of more efficacious ones, lamp 

manufacturers modify baseline IRLs to be more efficacious in a manner that reduces lamp 

lifetimes and increases lumen output. 

10.4.3.2 Alternative Scenario National Energy Savings Results

Table 10.4.6 presents the cumulative full-fuel-cycle NES estimates for the alternative 

analyses that affect NES. In each CSC, the scenario result for the alternative analyses should be 

compared to the best-estimate CSC to determine the impact. The main results are summarized 

below: 

• The uncertainty introduced by volatile REO prices is small given the assumed price 

bounds. Fractional deviations from the reference-scenario NES were at or below 5 

percent in all CSCs. 
10-25 

• The impact on the NES of the different rebound assumptions is straightforward: there is a 

fractional reduction in energy savings equal to the rebound rate in each sector. As GSFLs 

are used mostly in the commercial and industrial sector and IRLs are used mostly in the 

residential sector,5

 the overall impact of the framework rebound assumptions is greater 

for IRLs than for GSFLs; GSFLs see a reduction in NES of approximately 1 percent, 

while the reduction in NES for IRLs is closer to the residential rate of 8.5 percent. In the 

case of NEMS rebound assumptions, the NES reduction is 15 percent for both products. 

• The impact of growth in the LED market was substantial by all measures. For all CSCs, 

LED incursion into the market roughly halved the potential NES of an updated GSFL 

standard and reduced it by approximately 80 percent for IRLs. 

• The impact of lighting controls was generally more modest. Growth of lighting controls 

reduced the potential NES for GSFL standards by approximately 14 percent in all CSCs. 

The impact of controls on the NES for IRLs was negligible, because most use of IRLs

occurs in the residential sector, where DOE assumed the use of controls to be constant 

over the analysis period. 

• Finally, the alternative IRL lifetime scenario reduces the calculated NES at CSL 1 for 

IRLs by more than 50 percent. 

Table 10.4.6 Cumulative Full-Fuel-Cycle NES, Alternative Scenarios (quads)

National Energy Savings 

Analysis Type Scenario 

All CSL 1 Max CSL

IRL

GSFL

Total 

Rulemaking 

IRL

GSFL

Total 

Rulemaking 

Standard Best Estimate 0.138 0.938 1.08 0.138 4.52 4.65 

Uncertainty Analyses REO High 0.138 0.925 1.06 0.138 4.30 4.44

REO Low 0.138 0.941 1.08 0.138 4.59 4.73 

Rebound Scenarios

Framework Rebound 

Rate 0.127 0.928 1.06 0.127 4.47 4.59

NEMS Rebound 0.118 0.797 0.915 0.118 3.83 3.96 

Impact 

Determination

Fixed Controls 0.138 1.09 1.23 0.138 5.28 5.42 

No LED 0.689 1.79 2.48 0.689 7.78 8.47

Alternative 

Technology Scenario IRL Short Life 0.0543 0.938 0.992 0.0543 4.52 4.57 
10-26 

10.4.3.3 Alternative Scenario Net Present Value Results

This section presents the alternative analyses that affect the NPV. Table 10.4.8 and Table 

10.4.9 document the estimated cumulative NPV for the alternative scenarios, assuming a 3- and 

7-percent discount rate, respectively. The main results are summarized below.

• Similar to the NES alternative scenario results, REO prices have an impact of less than 2 

percent on the NPV for all CSCs. 

• Uncertainties in electricity prices resulting from differences in AEO economic growth 

projections have a small effect on the NPV of a GSFL energy conservation standard: the 

high-economic growth scenario increases NPV and the low-economic growth scenario 

reduces NPV by less than 10 percent in any of the considered CSCs. The effect of 

economic growth uncertainty on the NPV of an IRL standard is similar, at 11 percent or 

less.f

 

• Reductions in NPV from LED incursion were significant for GSFLs, at roughly 35 to 50 

and percent when assuming a 3-percent discount rate, and roughly 30 to 40 percent when 

assuming a 7-percent discount rate. For IRLs, the impact of LED incursion on NPV was 

even larger: the NPV of an updated standard was significantly negative in the absence of 

LED incursion, regardless of the assumed discount rate. In the reference scenario, by 

contrast, the NPV for an IRL standard is near zero but barely positive at a 3-percent 

discount rate and more modestly negative at a 7-percent discount rate. 

• Lighting controls growth led to a reduction in NPV for GSFLs by about 10 to 30 percent, 

but to a minimal NPV reduction for IRLs. 

• Finally, in the alternative IRL lifetime scenario, due to increased relamping costs from 

lamps with shorter lifetimes, the NPV of an IRL standard in this scenario is substantially 

negative, regardless of whether the assumed discount rate is 3 or 7 percent. 

 

f Notably, however, the NPV of an energy conservation standard for IRLs is increased over the best estimate in both 

the high and the low economic growth scenarios. An increased NPV is possible in the low-economic growth 

scenario, because, as shown in Figure 10.2.1, although electricity prices are lower than the reference scenario in the 

long term, they are higher in the near term. If most of the energy savings are realized early in the analysis period, the 

NPV of an energy conservation standard can increase. 
10-27 

Table 10.4.7 Cumulative NPV for Alternative Scenarios, 3% Discount Rate (billion 2011$) 

Analysis Type Scenario

All CSL 1 Max CSL

IRL GSFL Total 

Rulemaking IRL GSFL Total Rulemaking

Standard Best 

Estimate 0.0403 1.95 1.99 0.0403 22.9 22.9

Uncertainty 

Analyses

REO High 0.0403 1.97 2.01 0.0403 22.5 22.6

REO Low 0.0403 1.94 1.98 0.0403 23.0 23.0

High 

Economic 

Growth

0.0449 2.12 2.16 0.0449 23.7 23.7

Low 

Economic 

Growth

0.0408 1.80 1.84 0.0408 22.2 22.3

Impact 

Determination

Fixed 

Controls 0.0409 2.66 2.70 0.0409 26.8 26.8

No LED -0.00398 3.80 3.79 -0.00398 35.5 35.5

Alternative 

Technology 

Scenario

IRL Short 

Life -0.352 1.95 1.59 -0.352 22.9 22.5

Table 10.4.8 Cumulative NPV for Alternative Scenarios, 7% Discount Rate (billion 2011$) 

Analysis Type Scenario

All CSL 1 Max CSL

IRL GSFL Total 

Rulemaking IRL GSFL Total Rulemaking

Standard Best 

Estimate -0.177 0.832 0.655 -0.177 12.8 12.6

Uncertainty 

Analyses

REO High -0.177 0.850 0.673 -0.177 12.7 12.6

REO Low -0.177 0.829 0.652 -0.177 12.8 12.6

High 

Economic 

Growth

-0.175 0.904 0.729 -0.175 13.1 13.0

Low 

Economic 

Growth

-0.175 0.774 0.599 -0.175 12.5 12.3

Impact 

Determination

Fixed 

Controls -0.177 1.17 0.996 -0.177 14.7 14.5

No LED -0.600 1.42 0.823 -0.600 17.6 17.0

Alternative 

Technology 

Scenario

IRL Short 

Life -0.341 0.832 0.491 -0.341 12.8 12.4
10-28 

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 Williams, A., B. Atkinson, K. Garbesi, E. Page, and F. Rubinstein (2012). Lighting controls in 

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2012. Washington, DC. Report No. DOE/EIA-0383(2012). <http://www.eia.doe.gov/oiaf/aeo/> 

4

 U.S. Department of Energy-Office of Energy Efficiency and Renewable Energy, Energy 

Conservation Program for Consumer Products: Preliminary Analysis Technical Support 

Document: Energy Efficiency Standards for Consumer Products and Certain Commercial and 

Industrial Equipment: Residential Furnace Fan. July 2012. Washington, D.C. 

5

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