### PNNL

- 22610 Rev 1

Prepared for the U.S. Department of Energy

u nder Contract DE

- AC05

- 76RL01830



# Building Energy Codes Program:

National Benefits Assessment,

1992

**-** 2040

OV Li vingston PC Cole

DB Elliott R Bartlett

M arch 2014

### PNNL

- 22610 Rev 1

### PNNL

- 22610 Rev 1



# Building Energy Codes Program:

National Benefits Assessment,

1992

– 2040

O V Livingston PC Cole

D B Elliott R Bartlett

March 2014

Prepared for

the U.S. Department of Energy

u nder Contract DE

- AC05

- 76RL01830

Pacific Northwest National Laboratory

Richland, Washington 99352

# Executive S ummary

Commercial and residential b uildings account for approximately 41% of all energy consumption and

72% of electricity usage in the United States. Building e nergy codes and standards set minimum

requirements for energy

- efficient design and construction for new and renovated buildings, assuring

reductions i n energy use and greenhouse gas emissions over the life of building s

. The U.S. Department of

Energy (DOE) , through the Buildi ng Energy Codes Program (BECP or the Program), supports the

improvement of energy efficiency in buildings . The BECP was founded i n 199 2 in response to the

Energy Policy Act (EPAct) of 1 992, which mandated that DOE participate in the model national codes

development process and help states adopt and implement more efficient energy codes. Since its

inception 20 years ago, BECP has be come the central information resource on national energy codes and

standards.

The BECP consists of an integrated portfolio of activiti es to increase energy efficiency in buildings.

As part of its code development activities, DOE participates in the development of model energy codes

and standards maintained by the International Code Council (ICC) and the America n S ociety of Heating,

Refrigerating and Air

- C onditioning Engineers (ASHRAE ). To help states adopt and implement

progressive energy codes, DOE provides : 1) technical assistance to state and local governments to help

facilitate the adoption process and 2) an array of resources to building industry stakeholders and

enforcement of ficials to improve code co mpliance , including compliance software tools, training

materials

, and technical support.

BECP periodically assesses the impacts of its activities by estimating historical and projected energy

savings, consumer savings, and avoide d emissions. The Pacific Northwest National Laboratory (PNNL)

conducted the codes benefits assessment in support of the BECP. Underlying the assessment is a series of

calculations that estimate and compare energy savings under two scenarios: “with BECP” and “without

BECP. ” The analysis covers the years 1992

- 2040 and includes comparing the nominal energy savings

(assuming 100 percent adoption and compliance) attributable to different code versions, determining the

applicable floor space (both residential and commercial) subject to the code, and estimating the final

energy savings by adjusting nominal energy savings for the applicable floor space according to the

estimated actual adoption and compliance levels. The resulting estimates of energy consumptio n for each

scenario are compared, and the difference equals the impact of BECP activities.

The results of the P rogram impacts are presented in terms of energy savings, consumer cost savings,

and avoided emissions. Energy savings include site, primary (s ource) and full

- fuel

- cycle (FCC) savings.

Table ES. 1 summarizes B ECP historical and projected energy savings and net present value of consumer

benefit s (energy cost s avings). Figure ES.1 shows the annual FFC energy savings from BECP activities

from 1992

- 2040

. A summary of emissions savings is presented in Table ES. 2

.

Since the inception of the Program 20 years ago, cumula tive FFC energy savings from 1992

- 2012

are estimated to be approximately 4.2 quads and cost savings to co nsumers have been more than

$ 44 billion. These savings have resulted primarily from the Program’s activities which upgrade the

model energy codes, accelerate their adoption by states and localities, and improve code compliance by

means of various software tools and other types of tra ining and technical support. The f ederal budgetary

cost of the Program over this same period (1992

- 2012) was estimated to be around $110 million

, resulting in a ratio of more than $400 in cost savings for each DOE program dollar spent.

iii

### The estimated cumul ative benefits from the Program through 2040 are also significant. The

cumulative energy savings attributed to the Program total nearly 46 quads of FFC energy in 2040 , or 44

quads of primary energy, equivalent to almost an entire year’s worth of primary e nergy consumption from

the U.S. residential and commercial sectors at current consumption rates. The Program is estimated to

save consumers up to $230 billion on their utility bills by 2040

. Annual carbon savings reach 36 million

tons at the end of 2012

, and the cumulative savings by 2040 are estimated at 3,478 million tons.

Table ES. 1 . Summary of Energy and Cost Savings from BECP Energy Code Activities

Site Energy

Savings, (a)

quads Primary Energy

Savings

, (b)

quads FFC Energy

Savings, (c)

quads Energy Cost

Savings

NPV,

billion 2012$

Historical

Annual in 2012 0.2 0. 48 0.5 5.0

Cumulative 1992

- 2012 2.0 4.0 4.2 44.6

Projected, 2013

- 2040 Construction

Annual in 2040 1.2 2.2 2.3 5

. 2

Cumulative 2013

- 2040 22.0 40.1 41.6 1 8 5 .7

BECP Total

Annual in 2040 1.2 2.2 2.3 5.2

Cumulative 1992

- 2040 24.0 44.1 45.7 230.3

(a) Site energy savings represent direct energy savings to the consumer. Site energy savings multiplied by the energy price

represent energy cost savings to the consumer.

(b) Following the analysis methodology used by DOE’s Appliance and Equipment Standards Program, site energy savings were

first converted to the source energy terms, which includes energy used in generation, transmission, and distribution (primary

energy).

(c ) Energy used further “upstream” in the mining, processing, and transportation of fuels cycle was calculated using the NIA

PLUS model and added to the primary energy savings to yield full

- fuel

- cycle ( FFC ) energy savings



### iv

### Figure ES. 1

. Annual Full

- Fuel

- Cycle Energy Sav ings from BECP Activities, 1992

– 2040

Table ES. 2 . Summary of Historical and Projected Emissions Savings

CO 2 (mmt) NO

x (kt) Mercury

( ton ) N 2 O

(kt) N 2 O

( mmt CO 2 eq) CH 4 (kt) CH 4 (mmt CO 2 eq) SO 2 (kt)

Historical

Annual in 2012 36 80 0.1 0.4 0.1 159 4 46

Cumulative 1992

– 2012 300 664 0.6 3.3 1.0 1,347 34 386

Projected, 2013

– 2040 Construction

Annual in 2040 185 194 0.4 1.8 0.5 796 20 116

Cumulative 2013

– 2040 3,178 3,855 6.9 32.1 9.6 14,095 352 3,489

BECP Total

Annual in 2040 185 194 0.4 1.8 0.5 796 20 116

Cumulative 1992

– 2040 3,478 4,519 7.6 35.4 10.5 15,441 386 3,875



### BECP’s cumulative FFC savings of emissions of the greenhouse gases of carbon dioxide ( CO 2 

### )

, nitrous oxide ( N 2 

### O ) , and methane ( CH 4 

### ) in CO 2



### - equivalents in Table ES.2 are almost3.9 billion metric

tons. That is equivalent to three

- quarters of all energy

- related emissions of the United States in 2012.

These benefits do not count the reduction of other energy

- relate d air pollutants shown in Table ES.2, or

billions of dollars in saved future investment in facilities to supply the natural gas, electricity, and fuel oil

to the residential and commercial sectors that would no longer be required

.

v

### Thi s analysis also estimated the potential energy savings for 2013

– 2040 for residential and

commercial code activities under ideal adoption and compliance conditions. The estimate represents the

energy, cost, and emissions that could be saved on new post

- 201 3 construction , as well as existing stock,

with immediate code adoption and 100% compliance

. Full cumulative site energy savings potential for

2013

– 2040 equals 42.6 quads, with residential and commercial energy code activities contributing

approximately 5 0% each. Primary energy savings potential is 77 quads, which translates to FFC energy

savings of nearly 80 quads. Cumulative energy cost savings potential equals approximately $330 billion

(2012$). Annual CO 2 

### savings potential reaches 461 million metric tons at the end of 2040, and the

cumulative potential carbon savings by 2040 are estimated at over 6.2 billion metric tons of CO 2 

### . For

more details of the energy savings potential, as well as potential cost and emissions reductions, refer to

Appendix A.

vi

# Acronyms and Abbreviations

AEO Annual Energy Outlook

ARRA American Recovery and Reinvestment Act

ASHRAE American Society of Heating, Refrigerating and Air

- Conditioning Engineers

BECP Building Energy Codes Program

CBECS Commercial Buildings Energy Consumption Survey

CH 4 

### methane

CO 2 

### carbon dioxide

CO 2 

### eq carbon dioxide equivalent

DOE U.S. Department of Energy

EIA Energy Information Administration

EUI energy use intensity

FFC full

- fuel

- cycle

Hg mercury

hh hou sehold

HVAC heating, ventilating, and air conditioning

ICC International Code Council

IECC International Energy Conservation Code

GDP gross domestic product

kt kiloton

kWh kilowatt

- hours

MCEC Model Code for Energy Conservation

MEC Model Energy Code

MHC McG raw

- Hill Construction

Mt metric ton

mmt million metric ton s

N 2 

### O nitrous oxide

NEMS National Energy Modeling System

NO

x 

### nitrogen oxide

NPV net present value

PNNL Pacific Northwest National Laboratory

quads quadrillion British thermal units

RECS Residential Energy Consumption Survey

TBtu trillion British thermal units

vii

# Contents

Executive Summary

................................ ................................ ................................ .............................. iii

Acronyms and Abbreviations

................................ ................................ ................................ ............... vii

1.0 Introduction

................................ ................................ ................................ ................................ .. 1.1

2.0 Methodology

................................ ................................ ................................ ................................ . 2.1

3.0 Commercial Assumptions and Estimated Results

................................ ................................ ........ 3.1

3.1 Commercial Energy Codes and Standards Performance

................................ ...................... 3.1

3.2 Commercial Floor Space Forecast

................................ ................................ ....................... 3.6

3.2.1 Historical Data for New Construction and Additions to Existing Buildings

............ 3.6

3.2.2 Projected Data for New Construction and Additions to Existing Buildings

............. 3.8

3.2.3 Alterations

................................ ................................ ................................ ................. 3.8

3.3 Adop tion of Commercial Energy Codes and Standards

................................ ....................... 3.9

3.3.1 Historical Explicit Adoption Rate Assumptions

................................ ....................... 3.10

3.3.2 Historical Implicit Adoption Assumptions

................................ ................................ 3.11

3.3.3 Future Adoption Assumptions

................................ ................................ ................... 3.14

3.3.4 Adoption Assumptions for t he Counterfactual Scenario

................................ ........... 3.15

3.4 Code Compliance

................................ ................................ ................................ ................. 3.18

3.5 Estimated Benefits of the BECP Commercial Activities

................................ ..................... 3.22

4.0 Residential Assumptions and Estimated Results

................................ ................................ .......... 4.1

4.1 Residential Energy Code Pe rformance

................................ ................................ ................. 4.1

4.2 Residential Floor Space Forecast

................................ ................................ ......................... 4.6

4.2.1 Historical Data for New Residential Construction

................................ .................... 4.6

4.2.2 Projected Data for New Construction and Additions to Existing Residential

Buildings

................................ ................................ ................................ ................... 4.7

4.2.3 Integration of Historical and Projected Residential Data

................................ .......... 4.8

4.3 Adoption of Residential Energy Codes

................................ ................................ ................ 4.8

4.4 Residential Energy Code Compliance

................................ ................................ .................. 4.14

4.5 Estimated Benefits of the Residential BECP Activities

................................ ....................... 4.15

5.0 National Energy, Economic, and Environmental Benefits

................................ ........................... 5.1

6.0 References

................................ ................................ ................................ ................................ .... 6.1

7.0 Bibliography

................................ ................................ ................................ ................................ . 7.1

Appendix

– Energy Savings Potential from More Rapid Code Adoption and Compliance, 2013

–

2040

................................ ................................ ................................ ................................ ... A.1

viii

# Figures

ES.1 Annual Full

- Fuel

- Cycle Energy Savings from BECP Activities, 1992

– 2040

........................... v

2.1 Analysis Methodology

................................ ................................ ................................ ............... 2.1

3.1 ASHRAE Standard 90.1 Improvement Index

................................ ................................ ........... 3.6

3.2 Historical and Projected Savings Streams

................................ ................................ ................. 3.22

4.1 IECC Residential Energy Improvement Index

................................ ................................ .......... 4.5



# Tables

ES.1 Summary of Energy and Cost Savings from BECP Energy Code Activities

.............................. iv

ES.2 Summary of Historical and Projected Emissions Savings

................................ .......................... v

3.1 Prototype Floor Area Assumptions

................................ ................................ ............................... 3.2

3.2 State Energy Code Performance Estima tes, Electricity

................................ ................................ 3.4

3.3 State Energy Code Performance Estimates, Natural Gas

................................ ............................. 3.5

3.4 Scaling Factors

................................ ................................ ................................ .............................. 3.8

3.5 St art Year for Crediting States with Commercial Energy Code Savings Based on the Newly

Adopted Code

................................ ................................ ................................ ............................... 3.10

3.6 Explicit and Implicit Adoption Years by State and Commercial Code

................................ ........ 3.1 2

3.7 State Classification for Future Commercial Energy Code Adoption

................................ ............ 3.14

3.8 Commercial Energy Code Adoption Assumptions for Scenario “with BECP”

............................ 3.16

3.9 Commercial Energy Code Adoption Assumptions for Scenario “without BECP”

....................... 3.17

3.10 Compliance Assumptions for Standard 90.1, “With BECP” Scenario

................................ ......... 3.19

3.11 P ercent Point Difference between Commercial Compliance Levels “with BECP” and

“without BECP”

................................ ................................ ................................ ............................ 3.21

3 .12 States Excluded from the BE CP Commercial Benefits Calculation

................................ ............. 3.22

3.13 BECP Comme rcial Site Energy Savings

................................ ................................ ..................... 3.24

3.14 BECP Commercial Primary and Full

- Fuel

- Cycle Energy Savings

................................ ............. 3.26

3.15 Summary of Energy and Cost Savings fr om the BECP Commercial Energy Code Activities

..... 3.27

3.16 Annual Emissions Savings from the BECP Commercial Activities, Full

- Fuel

- C ycle

................. 3.28

3.17 Summary of Emissions Savings from the BECP Commercial Energy Code Activities

............... 3.29

3.18 National Cumulative Benefits of the BECP Commercial Activities, 1992

- 2040

........................ 3.29

3.19 Cumulative Consumer Benefits from BECP Commercial Codes Activities

................................ 3.31

4.1 Residential Annual Energy Use for all IECC Regulated End

- Uses, Electr icity

........................... 4.3

4.2 Residential Annual Energy Use for all IECC Regulated End

- Uses, Natural Gas, and Heating

Oil

................................ ................................ ................................ ................................ ................. 4.4

4.3 Start Year for Crediting States with Residential Energy Code Savings Based on the Newly

Adopted Code

................................ ................................ ................................ ............................... 4.9

ix

### 4.4 Start of the Residential Savings Stream Base d on Explicit and Implicit Adoption

...................... 4.10

4.5 State Classifications for Future Residential Energy Code Adoption

................................ ............ 4.11

4.6 Residential Energy Code Adoption Assumptions for the Scenario “with BECP”

........................ 4.12

4.7 Residential Energy Code Adoption Assumptions for the Scenario “without BECP”

.................. 4.13

4.8 Residential Code Compliance Assumptions for “With BECP” Scenario

................................ ..... 4.14

4.9 Percent Point Difference between Residential Compliance Levels “with BECP” and

“without BECP” Scenarios

................................ ................................ ................................ ........... 4.14

4.10 States Excluded from the BECP Residential Benefits Calculation

................................ ............... 4.15

4.11 BECP Reside ntial Site E nergy Savings

................................ ................................ ....................... 4.16

4.12 BECP Residential Primary and Full

- Fuel

- Cycle Energy Savings

................................ ............... 4.18

4.13 Summary of Energy and Cost Savings from the BECP Residential Energy Code Activities

...... 4.19

4.14 Annual Emissions Savings from the BECP Residential Activities, Full

- Fuel

- Cycle

................... 4.20

4.15 Summary of Emissions Savings from the BECP Residential Energy Code Activities

................. 4.21

4.16 National Cu mulative Benefits of the BECP Residential Activities, 1992

– 2040

.......................... 4.21

4.17 Cumulative Consumer Benefits from BECP Residential Energy Code Activities

....................... 4.23

5.1 Summary of Energy and Cost Savings from BECP Energy Code Activities

............................... 5.1

5.2 Breakdown of BECP Energy and Cost Savings between Commercial an d Residential

Activities

................................ ................................ ................................ ................................ ....... 5.2

5.3 BECP Historical and Projecte d Primary Energy Savings

................................ ............................. 5.3

5.4 BECP Historical and Projected Full

- F uel

- Cycle Energy Savings

................................ ............... 5.4

5.5 Summary of Emissions Savings from BECP Energy Code Activities

................................ ......... 5.5

5.6 National Benefits from BECP Energy Code Activities, 1992

– 2040

................................ ............ 5.5

5.7 Consumer Cumulative Benefits of the BECP Activities, 1992

– 2040

................................ ........... 5.6

A.1 Base Case and Immediate Adoption Scenario, Commercial Energy Codes

.............................. A.2

A.2 Base Case and Immediate Adoption Scenario, Residential Energy Codes

............................... A.3

A.3 Summary of Energy and Cost Savings Potential

................................ ................................ ....... A.4

A.4 Potential Site, Primary , and FFC Energy Savings

................................ ................................ .... A.4

A.5 Summary of Emissions Reduction Potential

................................ ................................ ............. A.5

A.6 National Benefits Potential, 2013

– 2040

................................ ................................ .................... A.6

A.7 Consumer Cumulative Benefits Potential, 2013

– 2040

................................ .............................. A.6

A.8 Summary of Full Future Energy and Cost Savings Potential

................................ .................... A.7

A.9 Summary of Full Future Emissions Reduction Potential

................................ .......................... A.7

x

# 1.0 Introduction

Buildings account for approximately 41% of all energy consumption and 72% of electricity usage in

the United States. Building e nergy codes and standards set minimum requirements for energy

- efficient

design and construction for new and renovated buildings, assuring reductions in energy use and

greenhouse gas emissions over the life of building s

. The U.S. Department of Energy (DOE) , through the

Buildi ng Energy Codes Program (BECP or the Program ), supports the improvement of energ y efficiency

in buildings

. BECP was founded in 199 2 in response to the Energy Policy Act of 1 992 (EPAct 1992)

, which mandated that DOE participate in the model national codes development process and that DOE

help states adopt and implement progressive ene rgy codes. Since its inception 20 years ago, BECP has

become the central information resource on national energy codes and standards.

The BECP consists of an integrated portfolio of activiti es to increase energy efficiency in buildings.

As part of its c ode development activities, DOE participates in the development of model energy codes

and standards maintained by the International Code Council (ICC) and the America n S ociety of Heating,

Refrigerating and Air

- C onditioning Engineers (ASHRAE). To help stat es adopt and implement

progressive energy codes, DOE provides : 1) technical assistance to state and local governments to help

facilitate the adoption process and 2) an array of resources to building industry stakeholders and

enforcement officials to impro ve code co mpliance , including compliance software tools, training

materials

, and technical support.

BECP periodically assesses the influence of its activities by estimating historical and projected energy

savings, consumer savings, and avoided emissions. This technical report describes the impacts of BECP

energy code activities on the nation as a whole, expressed in terms of estimated site, primary (source)

, and

full

- fuel

- cycle (FFC) energy savings

, consumer energy cost savings, and emissions reductions

. The

analysis period included estimation of the historical (1992

– 

### 2012) and projected (2013

– 

### 2040) benefits of

these activities. T he methodology and assumptions used in the impacts analysis are discussed in detail in

this report

.

Impacts of the BECP are es timated under two different scenarios : “with BECP” and “without

BECP.” The difference between these two scenarios, in terms of energy, cost

, and emissions is a measure

of the P rogram ’s impact:

• The first scenario, “ w ith BECP,” is based on BECP having sup ported the development of more

efficient national energy codes, provided technical assistance and training to states and localities, and

developed and supported energy code

- related materials and software. All of these activities are

deemed to have improved the energy efficiency impact of the code requirements, and to have

increased adoption of and compliance with building energy codes beyond what would have been

likely without the P rogram.

• The second, “ w i thout BECP,” follows the same computational steps as the first scenario, but with an

alternative set of assumptions to describe what would have happened if the BECP had not been in

place (i.e., a counterfactual scenario)

. A s a result of other (i.e., non

- D OE ) code organizations that

support building energy codes and state

- and regionally

- funded activities to adopt and enforce the

codes, energy savings would still have occurred without the BECP , but at a slower pace and with a

lower compliance rate.

1.1

### T his report is organized into five sections

. Section 2 explains the impact analysis methodology

. Section s 3 and 4 include detailed discussion of the assumptions and estimation results for BECP

commercial and residential energy code activities , respectively

. Section 5 summarizes the national

energy and emissions savings, and economic benefits. Section 6 provides a list of re ferences, and

Section 7 provides a bibliography. The Appendix contains an estimate of the energy savings potential for

residential and c ommercial code activities assuming immediate adoption and full compliance.

1.2

# 2.0 Methodology

This section describes the methodology used by PNNL to assess the impact of BECP energy code

activities . Underlying the analysis is a series of calculations that estimate and compare the energy savings

under two adoption and compliance scenarios : “ w ith BECP” and “ w ithout BECP

. ”

The steps used to calculate the “w ith BECP ” scenario are as follows :

1. Select base (or refer ence) year.

2. Compare the nominal energy savings

. 3. Determine applicable floor space subject to the code.

4. Estimate the final energy savings by a djust ing nominal energy savings for the applicable floor

space according to the estimated actual adoption and compli ance levels.

These calculations rely on historical data or retrospective estimates, as well as future projections of

code efficiency, adoption

, and compliance to derive the energy consumption with the P rogram activities

taking place

. In the absence of re liable data or established analysis to use as bases for this analysis, the

impact estimates also rely on fundamental or enabling assumptions developed based on analyst or

Program experience and judgment.

To identify how much of the savings are attributable to the BECP, a second (counterfactual) scenario

was used to investigate the probable impact had the P rogram not been in place

. Th is second scenario,

“w ithout BECP, ” follows the same computational steps outlined above, but uses an alternat ive set of

assumptions to describe what might have occurred differently without the BECP. For this analysis, BECP

programmatic impacts are primarily defined as a) improvement of code energy efficiency, b) acceleration

of adoption and c ) increase in compli ance. T he nominal energy savings for the applicable floor area are

adjusted for “with BECP” and “without BECP” scenarios. They are further adjusted by a different set of

adoption and compliance rates. Figure 2

. 1 shows a brief outline of the computational steps for both

scenarios.

Figure 2

. 1

. Analysis Methodology

2.1

### The difference between estimates of energy consumption under the two scenarios determines the

BECP programmatic impact ( i.e., the portion of achieved energy savings that can be attributed to the

BECP )

.

BECP selected 1992 as the base year for the impact analysis mainly because the Program was

foun ded in 1992 in response to EPAct 1992. Other factors contribut ing to this decision include:

• The 1992 Model Energy Code ( MEC ) was mentioned in EPAct 1992 , establishing it as a reasonable

base year.

• Although many states had adopted ASHRAE Standard 90, the Model Code for Energy Conservation

(MCEC 1977), or the M EC by the early 1980s, and a case can be made for using any one of these

version years as the base year, lack of data on compliance with these codes and standards renders

them i nfeasible as reference points.

• The use of 1992 as the reference year eliminates the need to consider an additional code level in the

analysis of building practices less stringent than Standard 90A

- 1980. Additional code

- level analysis

would have added little to the accuracy o f the estimate s due to the aforementioned lack of data for

that period.

Although using 1992 as the base year for the historical analysis might omit some of DOE’s historical

impact on building codes, it can be argued that most of DOE’s influence on the technical requirements in

these standards has occurred since 1992. DOE was not active in preparing and submitting proposed

changes to the MEC during the 1980s. The majority of DOE’s technically focused energy codes and

standards activities in the 1980s targeted developing the technical foundation for ASHRAE

Standard 90.1

- 1989 (ASHRAE 1990)

. This standard was much more rigorous than Standard 90A

- 1980

and thus had a greater impact on energy efficiency as states began to adopt Standard 90.1

- 1989 in the

early 1990s.

For this analysis, estimated benefits were developed separately for commercial and residential energy

codes. As such, estimates of code

- to

- code savings, a pplicable floor area , code adoption

, and code

compliance assumptions we re developed separately as well. Section 3 contains detailed description s of

the logic, assumptions

, and estimation result s for the commercial code activities, while S ection 4

discusse s similar points for the residential analysis.

2.2

# 3.0 Commercial Assumptions and Estimated Results

This section discusses how the energy savings attributable to different commercial energy code

versions were compared

, how the applicable commercial floor space subject to the code was determined

, and what adoption and compliance assumptions were used in the analysis

.



## 3.1 Commercial Energy Co des and Standards Performance (Code

- to

C ode S avings)

PNNL assessed relative energy use for commercial buildings designed to meet building design

requirements found in the 2010, 2007, and 2004 versions of ASHRAE Standard 90.1

. PNNL also

evaluated the energy savings achieved by using Standard 90.1

- 2010 (ASHRAE 20 10) over its

predecessors, Standard 90.1

- 2007 (ASHRAE 2007)

, and Standard 90.1

- 2004 (ASHRAE 2004)

. The

estimated values were also used to infer the savings from earlier versions of the code.

The evaluation was conducted using computer simulations of prot otype buildings developed by

PNNL to support the quantitative analysis of DOE’s Determinations on ASHRAE Standard 90.1

. 1 

### The

annual energy use by fuel type and end use, extracted from the simulations, was converted to energy use

intensity (EUI)

, expressed in energy use per square foot. Using construction weighting factors by

building type and state, developed from 5 years of recent construction data, the energy use estimates were

aggregated for each revision of Standard 90.1, both by building prototype an d weighted across

building type.

The a nalysis of relative energy use and energy savings for the 2004, 2007

, and 2010 versions of

Standard 90.1 was conducted using 16 commercial building prototypes based on published Commercial

Prototype Building Models 2



### . Every prototype building was simulated in each of the 15 U.S. climate

zones used in the analyzed versions of Standard 90.1. For each climate zone, a most representative

location and corresponding typical meteorological year weather file w ere identified, resulting in

720 climate/prototype combinations. 3



### The 2004, 2007, and 2010 versions of Standard 90.1 contain tables that specify efficiency

requirements for heating, ventilating, and air conditioning ( HVAC ) and service water heating equipment.

Most, but not all, of the equipment classes shown in the Standard 90.1 tables have minimum f ederal

efficiency standards applied to them

. Because mandated equipment efficiency is enforced as a

manufacturing standard regardless of whether it is represented in Standa rd 90.1, the inclusion of the

requirement in the ASHRAE standard has no separate energy impact. Therefore, it is necessary to

exclude from the calculation the energy savings that would occur in new building construction due to

these mandated equipment eff iciency improvements

. Excluding credit for this equipment in the

quantitative analysis is consistent with the approach used in previous DOE D eterminations. Therefore,

1 For DOE’s Determinations, go to http://www.energycodes.gov/regulations

.

2 The models are available at: http://www.energycodes.gov/development/commercial/90.1_models

.

3 For a more detailed discussion of the prototypes, technical assumptions, analyzed addenda

, and aggregation

weights

, refer to the PNNL report

, Achieving 30% Goal: Energy and Cost Saving Analysis of ASHRAE/IES

Standard 90.1

- 2010 (Thornton et al. 2011).



### 3.1

### the code

- to

- code savings used in the BECP commercial benefits analysis explicitly exclu de savings

induced by the f ederal equipment efficiency standards.

The results of the Standard s 90.1

- 2004 and 90.1

- 2007 analysis reported in the Standard 90.1

- 2007

Determination (Halverson et al. 2011 a ) are based on equipment efficiency requireme nts in

Standard 90.1

- 2004. The results of the Standard s 90.1

- 2007 and 90.1

- 2010 analysis reported i n the

Standard 90.1

- 2010 Determination (Halverson et al. 2011 b ) are based on equipment efficiency

requirements in Standard 90.1

- 2007. Some of the equipment effici ency requirements are different

between 90.1

- 2004 and 90.1

- 2007. T o compare the saving impacts of the three standards ( i.e.

, 90.1

- 2004,

2007, and 2010 ) and exclude those differences that are not direct results of the standard improvement, the

energy savin g results of Standard 90.1

- 2004 were not directly taken from the 90.1

- 2007 Determination

report. The savings were calculated by subtracting the percentage differences between 90.1

- 2004 and

90.1

- 2007 reported in the 90.1

- 2007 Determination from results of 90.1

- 2007 reported in the 90.1

- 2010

Determination. The energy saving results of 90.1

- 2007 and 90.1

- 2010 from the 90.1

- 2010 Determination

were used i n this impact analysis without modification.

EUIs for each of the compared versions were analyzed by proto type and by climate location. For

each prototype building, the energy consumption for each standard was modeled based on

15 representative climate locations, covering all ASHRAE climate zones. It was assumed that the energy

consumption of a building at one of the climate locations c ould be represented by the same building at

another l ocation within the same ASHRAE c limate z one , resulting in 111 representative locations

. S imulated energy consumption across th e 111 locations and the building types was normalized by the

building floor area. Floor area assumptions for each of the prototypes used in the normalization are

included in Table 3

. 1

.

Table 3

. 1

. Prototype Floor Area Assumptions

Building Type Building Prototype Prototype Floor Area (ft 2 )

Office Small Office 5,502

Medium Office 53,628

Large Office 498,588

Retail Stand

- Alone Retail 24,692

Strip Mall 22,500

Education Primary School 73,959

Secondary School 210,887

Healthcare Outpatient Healthcare 40,946

Hospital 241,501

Lodging Small Hotel 43,202

Large Hotel 122,120

Warehouse Non

- Refrigerated Warehouse 52,045

Food Service Fast Food Restaurant 2,501

Sit

- Down Restaurant 5,502

Apartment Mid

- Rise Apartment 33,741

High

- Rise Apartment 84,320



### Resulting EUI s per square foot of floor area were weighted across building types and representative

climate locations to obtain the aggregate EUI s by state.

3.2

### To estimate the construction weights

, the disaggregated construction volume data were acquired from

the McGraw

- Hill Construction (MHC) Project Starts Database

. The MHC data base obtai ned covers the

time period 2003

– 2010, and depending upon the specific calculations , data from subsets of that time

period were used. T his MHC database was analyzed to develop detailed construction weights by climate

zones, subzones, and states using the methodology outlined in Jarnagin and Bandyopadhyay ( 2010 )

.

State

- level aggregation produced estimates of the energy performance for the 2004, 2007

, and 2010

versions of Standard 90.1 for two fuels ( electricity and natural gas ) , and two groups of end uses ( HVAC

and Lighting/O ther )

. The HVAC end use group includes heating, cooling, fan, pump

, and heat rejection.

Lighting/Other includes interior and exterior lighting, plug and process loads

, service hot water

, refrigeration, and generators. The estimates grouped by fuel type are presented in Table 3.2 and

Table 3

. 3

.

The impact analysis used s tate

- level EUIs as a foundation for estimating the energy performance of

the standards prior to Standard 90.1

- 2004 and following Standard 90.1

- 2010. For the versi ons predating

90.1

- 2004, the energy performance was estimated based on the commercial code improvement index

developed by PNNL

. The index is presented in Figure 3

. 1

.

The retroactive code performance scalars for versions between Standard 90A

- 1980 and

Standard 90.1

- 2001 were developed from this index using Standard 90.1

- 2004 as the base. For the

versions prior to Standard 90.1

- 2004, BECP is not credited with the energy improvements related to code

development. For Standards 90.1

- 2004, 2007, and 2010, BECP is credited with a third of the code

- to

code energy efficiency improvement based on the professional judgment of the PNNL staff supporting

code development. This mea ns that if there were an 18.5% reduction in the EUI between

Standards 90.1

- 2007 and 90.1

- 2010 in the “with BECP” scenario, we assumed that without DOE

assistance in place, the code would have instead advanced by about 13%.

For future standard versions aft er Standard 90.1

- 2010, the energy use was calculated for two

scenarios ( “with BECP” and “w ithout BECP ” ) with Standard 90.1

- 2010 as the base. It was assumed that

“ with BECP ” there w ould be a 7% improvement in the energy use, while a 6.3% improvement is

exp ected wi thout the DOE program in place, i.e., only 10% of the code

- to

- code energy efficiency

improvement is attributed to BECP. This attribution structure is based on the professional judgment of

the PNNL staff supporting code development and is consisten t with BECP focusing on code development

in the past and shifting more towards supporting improvement in code compliance in the future.

Nominal code

- to

- code savings were derived from the energy use estimates by comparing the code

version that was adopted in the state to the previously active code version. Nominal energy savings were

then adjusted by the compliance rates. Commercial adoption and compliance assumptions are described

in Sections 3.3 and 3.4

.

3.3

### Table 3

. 2

. State Energy Code Performance Estimates, Electricity (site kWh / ft 2



### - yr )

State Electricity

- HVAC Electricity

- Light/Other

STD2004 STD2007 STD2010 STD2004 STD2007 STD2010

Alabama 6.48 6.30 4.73 9.53 9.27 7.83

Alaska 5.12 4.92 3.68 9.83 9.49 8.21

Arizona 7.31 7.09 5.48 9.16 8.90 7.59

Arkansas 6.39 6.19 4.58 9.77 9.47 7.98

California 4.81 4.68 3.63 9.07 8.83 7.57

Colorado 4.51 4.37 3.30 9.57 9.29 8.00

Connecticut 4.82 4.65 3.54 9.54 9.24 7.94

Delaware 6.05 5.84 4.12 10.72 10.37 8.95

D istrict of Columbia 3.60 3.55 2.72 8.37 8.27 7.25

Florida 7.25 7.03 5.31 9.19 8.93 7.59

Georgia 6.07 5.91 4.44 9.22 8.97 7.57

Hawaii 10.08 9.91 7.91 9.12 8.92 7.91

Idaho 4.93 4.75 3.38 10.26 9.92 8.41

Illinois 5.16 4.99 3.69 9.97 9.67 8.44

Indiana 4.94 4.79 3.56 9.40 9.16 7.85

Iowa 4.58 4.44 3.41 9.56 9.31 7.88

Kansas 5.61 5.42 3.95 9.91 9.60 8.09

Kentucky 5.37 5.20 3.78 9.93 9.64 8.12

Louisiana 7.51 7.27 5.44 9.75 9.46 8.07

Maine 4.67 4.48 3.38 10.04 9.67 8.31

Maryland 4.73 4.60 3.40 9.16 8.94 7.68

Massachusetts 4.79 4.63 3.56 9.58 9.30 7.98

Michigan 5.02 4.83 3.63 10.11 9.76 8.26

Minnesota 4.77 4.62 3.48 9.81 9.53 8.36

Mississippi 7.22 7.02 5.28 9.89 9.63 8.25

Missouri 5.70 5.51 3.96 10.08 9.76 8.35

Montana 5.07 4.87 3.55 9.97 9.63 8.28

Nebraska 5.66 5.51 4.08 10.63 10.36 8.94

Nevada 5.91 5.77 4.54 9.72 9.48 8.29

New Hampshire 6.10 5.85 4.23 10.89 10.47 9.10

New Jersey 5.57 5.44 4.13 9.96 9.71 8.56

New Mexico 5.40 5.24 3.92 10.13 9.85 8.33

New York 4.27 4.16 3.37 8.94 8.73 7.85

North Carolina 5.96 5.78 4.27 9.66 9.38 8.03

North Dakota 5.65 5.46 4.08 10.33 10.03 8.70

Ohio 4.79 4.64 3.52 9.75 9.49 8.04

Oklahoma 6.56 6.36 4.66 9.85 9.58 8.10

Oregon 3.68 3.57 2.67 9.27 9.02 7.74

Pennsylvania 4.94 4.79 3.63 9.51 9.25 7.86

Rhode Island 4.37 4.18 3.18 8.99 8.64 7.14

South Carolina 5.72 5.51 3.99 9.20 8.89 7.44

South Dakota 4.42 4.30 3.36 9.90 9.64 8.20

Tennessee 5.78 5.61 4.12 9.70 9.44 8.08

Texas 6.74 6.56 4.91 9.36 9.12 7.77

Utah 3.75 3.62 2.76 8.85 8.59 7.23

Vermont 5.00 4.85 3.77 9.50 9.23 8.15

Virginia 5.41 5.27 3.93 9.63 9.38 8.15

Washington 3.81 3.70 2.75 9.30 9.05 7.82

West Virginia 5.11 4.95 3.84 9.95 9.63 8.05

Wisconsin 4.85 4.70 3.48 9.60 9.34 8.24

Wyoming 4.17 4.06 3.29 9.85 9.61 8.13



### 3.4

### Table 3

. 3

. State Energy Code Performance Estimates, Natural Gas (kBtu/ ft 2



### - yr )

State N atural Gas

- HVAC Natural Gas

- Light/Other

STD2004 STD2007 STD2010 STD2004 STD2007 STD2010

Alabama 9.66 8.95 5.35 10.21 9.57 9.57

Alaska 42.64 39.49 27.82 14.41 13.56 13.55

Arizona 4.89 4.64 3.29 8.75 8.28 8.28

Arkansas 10.46 9.62 5.24 8.19 7.62 7.62

California 5.80 5.50 3.99 8.25 7.74 7.74

Colorado 15.69 14.66 11.87 9.73 9.22 9.21

Connecticut 23.26 21.58 14.70 9.77 9.20 9.20

Delaware 20.09 18.66 10.33 6.43 6.06 6.05

D istrict of Columbia 11.38 10.08 6.28 4.97 4.60 4.59

Florida 6.10 5.76 3.66 7.65 7.22 7.21

Georgia 9.79 9.04 5.35 10.29 9.61 9.61

Hawaii 2.56 2.44 1.38 13.99 13.15 13.14

Idaho 17.63 16.35 13.15 8.81 8.32 8.31

Illinois 24.76 23.11 14.77 6.38 6.02 6.02

Indiana 23.24 22.05 15.05 10.21 9.70 9.69

Iowa 22.64 20.90 12.67 8.39 7.86 7.85

Kansas 17.13 15.76 8.53 8.74 8.16 8.16

Kentucky 17.17 16.04 9.41 7.90 7.50 7.50

Louisiana 7.95 7.48 4.64 9.55 9.00 9.00

Maine 29.12 26.68 16.85 11.24 10.54 10.54

Maryland 14.77 13.73 8.47 6.68 6.31 6.31

Massachusetts 22.04 20.40 13.32 7.23 6.81 6.81

Michigan 24.47 22.53 14.76 9.68 9.13 9.13

Minnesota 27.68 25.71 16.65 6.71 6.32 6.31

Mississippi 9.77 9.14 5.30 11.40 10.71 10.70

Missouri 18.20 16.90 9.62 7.78 7.33 7.33

Montana 21.61 19.99 13.47 11.69 11.00 10.99

Nebraska 24.99 23.28 13.94 9.95 9.36 9.35

Nevada 7.32 6.85 5.12 14.15 13.32 13.32

New Hampshire 28.86 26.59 17.71 10.29 9.70 9.69

New Jersey 21.44 19.98 11.94 14.41 13.56 13.55

New Mexico 10.59 9.88 7.59 11.09 10.39 10.38

New York 17.45 16.11 10.48 8.35 7.85 7.85

North Carolina 14.15 13.15 7.69 10.35 9.73 9.72

North Dakota 30.10 28.23 19.49 10.54 9.98 9.98

Ohio 23.21 21.54 13.21 8.76 8.22 8.22

Oklahoma 10.68 9.99 6.16 10.36 9.75 9.75

Oregon 13.91 13.07 9.37 9.47 8.89 8.89

Pennsylvania 22.40 20.74 13.10 11.42 10.70 10.69

Rhode Island 17.74 16.09 10.92 5.08 4.77 4.77

South Carolina 9.15 8.49 5.35 7.46 7.00 7.00

South Dakota 29.25 26.98 16.24 11.47 10.75 10.75

Tennessee 16.70 15.64 9.45 9.98 9.39 9.39

Texas 8.21 7.71 4.73 8.80 8.26 8.25

Utah 13.82 12.79 10.65 7.25 6.82 6.81

Vermont 28.37 26.47 18.52 16.88 15.87 15.86

Virginia 17.22 15.96 9.15 11.55 10.85 10.85

Washington 12.98 12.20 8.91 8.44 7.96 7.95

West Virginia 20.28 18.36 11.09 10.78 10.08 10.07

Wisconsin 29.24 27.59 18.76 10.27 9.71 9.70

Wyoming 22.72 20.66 12.15 14.07 13.10 13.10



### 3.5

### Figure 3

. 1

. ASHRAE Standard 90.1 Improvement Index



## 3.2 Commercial Floor S pace Forecast

Calculating the floor area attributable to new commercial buildings and additions to and renovations

of existing commercial buildings is integral to the analysis of energy codes becaus e the potential energy

savings are estimated on the basis of gross floor area. However , there are no publicly available sources of

these data for commercial buildings on a state

- by

- state basis. A further complication is that energy codes

and standards ap ply not only to new floor area, but also to the floor area associated with additions to and

renovations of existing buildings. The estimation of the code

- applicable floor space is discussed in detail

below.

Three sets of estimates

, historical floor space

, new floor space

, and alterations

, were combined to

form one time

- series floor space projection, in terms of millions of square feet that account ed for the

space associated with both newly

- constructed buildings and additions to existing buildings that is s ubject

to the commercial energy codes and standards.



### 3.2.1 Historical D ata for N ew C onstruction and A dditions to E xisting B uildings

For the years 199 2

– 

### 2002, the U.S. Census Statistical Abstract provides state

- level value of

construction contracts data . For the years 2003

– 

### 2010, construction contract data from MHC

- Dodge were

obtained. These data include valuations and floor space associated with new construction and additions to

existing buildings, as well as valuations (only ) for alterations of existing space.

3.6

### Several steps were taken to develop a consistent time

- series of incremental commercial floor space

subject to energy codes from 1992

– 

### 2010 :

1. T he c ensus data were converted from valuations to floor space by applying a state

- specific ratio

representing 2003

– 

### 2007 Dodge floor space added ( for new construction and additions) per $ 1,000

of construction value. T he c ensus data include d valuations not only for commercial new

construction and additions, but also for alterations and manufacturing. However, the application

of this MHC

- Dodge

- based ratio effectively yield ed floor space only for commercial new

construction and additions, under the implicit assumption that the portions of c ensus data that

represent alterations and manufacturing remain constant over time.

2. The resulting 1992

– 

### 2010, eac h state

- level time series was then scaled by a multiplicative factor

(scalar) so that their sum match ed the reported national annual added floor space totals in the

Census Statistical Abstract. This latter step correct ed for lower construction costs prior to the

2003

– 

### 2007 period associated with the multiplied MHC

- Dodge

- based ratio.

Two more adjustments were made to the resulting data :

1. A global scalar of 1.2 was applied to the state

- level results. This scalar adjust ed for

underreporting and more closely ma tch e d floor space reported by the Energy Information

Administration’s (EIA’s) Commercial Buildings Energy Consumption Survey (CBECS) (EIA

2006). T he growth in commercial floor space was analyzed using the national floor area square

footage data by year fr om MHC

- Dodge in a spreadsheet model. While MHC

- Dodge is a valuable

source for measuring the amount of new floor area additions, it does not cover all new

commercial building projects in the United States. MHC

- Dodge does not cover smaller projects

costing less than $100,000, and other projects are not captured simply because they are not put

out for bid by building contractors.

To account for this “undercoverage,” the spreadsheet model was calibrated u sing a floor area

survival function to yield similar growth rates in total U.S. commercial building floor space, as

reported in various editions of the CBECS

. As part of this calibration, the MHC

- Dodge figures

for total construction were factored up by 20% to account for underreporting of t he small er

projects

. 4 

### While underreporting is likely to vary across states, there are no data to support

differential adjustment factors by state; thus, the 20% factor was applied uniformly across all

states.

2. G iven that both the MHC

- Dodge data and the Ce nsus Statistical Abstract data represent contracts

to build rather than delivered space, lag factors were applied to the data. The lagged data were

used as the proxy for the historical floor space completions.

4 This adjustment is similar to that used by the Census Bureau to estimate private nonresidential construction in the

United States. The Census Bureau adjusts data from MHC

- Dodge up ward by 25% to account for undercoverage of

projects. (See the methodology description at http://www.census.gov/const/www/methodpage.html .) The smaller

adjustment factor in the current analysis provides a better calibration with the published floor space data in EIA ’s

C BECS

.



### 3.7

### 3.2.2 Projected D ata for N ew C onstruction and A ddi tions to E xisting B uildings

To project floor space through 2040, the c ensus and MHC

- Dodge data

, which covered the period

through 2010 , was combined with the EIA’s Annual Energy Outlook (AEO) 2012 ( DOE/EIA 2012)

, which provided the additional data through 2040. The AEO 2012 Reference Case forecasts commercial

floor space added by year and by the nine c ensus d ivisions. However, these floor space estimates were

not utilized directly. Rather

, the c e nsus d ivision and year

- specific growth rates implicit in the AEO floor

space forecast were applied to the previously developed historical data.

T he AEO forecast did not integrate seamlessly with the historical data, at least partially due to the

substantia l and prolonged impacts of the economic downturn in the roughly 2008

- 2011 timeframe. The

MHC

- Dodge

- based historical data show a much deeper contraction than the AEO 2012 data. As a result,

AEO 2012 growth rates, when applied to the 2010 historical data, would yield an unrealistically low long

term forecast of commercial floor space. To adjust for that, AEO growth rates were applied to an average

of the 2006

– 

### 2010 historical data, representing a more normal construction volume and higher base value

for the forecast, rather than simply extrapolating from the 2010 data.

Although applying the AEO growth rates to a higher base floor space value remedied the issue of an

unrealistically low forecast in the long

- term, it also create d an apparent short

- term spike i n the forecast.

As a result, the scaling factors in Table 3.4 were applied to the floor space results for the years 2011

– 

### 2014

to provide a more realistic transition from the depressed construction levels of 2010

.

Table 3

. 4

. Scaling Factors

Year Scaling Factor

2011 0.6306

2012 0.6203

2013 0.7544

2014 0.9011



### The resulting AEO

- derived data for the years 2011

– 

### 2040 are at the c ensus d ivision level. T o

apportion the c ensus d ivision estimates to the state level, MHC

- Dodge

- based 2006

– 

### 2010 state shares

were applied to each c ensus d ivision. T he purpose of using a multi

- year state average to smooth shares

was to avoid the distortions created by the economic downturn. S everal states ’ shares with in the ir

respec tive c ensus d ivision s deviated dramatically from historical norms near the construction industry’s

trough, with Nevada in 2010 being a key example

. The resulting smoothed state

- level data for

2011

– 

### 2040 were combined with the 199 2

– 

### 2010 data.



### 3.2.3 Alterations

New construction and additions to existing buildings are not the only means by which building

energy codes may provide energy savings. Alterations of existing space in buildings may also be subject

3.8

### to the codes. To incorporate alterations to existing spa ce, the analysis used state

- specific alterations

ratios, in combination with a renovation fraction 5 

### :

• The period 2003

– 

### 2007 was chosen to represent a period free from the distortions of the subsequent

recession.

• This period was used to calculate the altera tions ratios, which are the ratios of the average annual

valuation of alterations to the average annual valuation of new construction and additions to existing

buildings. The purchased MHC

- Dodge data provided the necessary values.

• The products of the stat e

- specific alterations ratios and the renovation fraction were multiplied by the

state

- level, annual floor space data associated with new construction plus additions, for the years

1992

– 

### 2040. This product yields estimates of state

- level, annual altered fl oor space subject to energy

codes.

• A key assumption associated with this method is that the per

- square foot cost of an energy

- code

impacting alteration across all relevant alteration types is on average close to the cost of newly

- added

or constructed space

.

The three sets of estimates combined (adjusted historical data, new floor space forecast, and

alterations) result ed in a floor space projection, in terms of millions of square feet, that account ed for the

space associated with both newly

- constructed buildings and additions to existing buildings that is subject

to the commercial energy codes and standards.



## 3.3 Adoption of Commercial Energy Codes and Standards

The adoption of model codes presents a significant opportunity to save energy in resi dential and

commercial buildings. The U nited States does not have a national energy code or standard, so energy

codes are adopted at the state and local levels of government. Through the BECP, DOE provides

technical assistance to state and local governments to help facilitate the acceleration of model energy

codes adoption

. The analysis aim ed to estimate the impact of BECP activities and DOE’s influence on

accelerating the rate of adoption of codes and standards and/or their adoption effective date

. 6



### Three types of adoption rate assumptions were used in the impact analysis to develop two scenarios

( “ with BECP ” and “ without BECP ” ) :

1. Histo rical Explicit

– adoption rates when a state explicitly adopts an energy code

.

2. Historical Implicit

– adoption rates where states do not explicitly adopt an energy code, but the

building practices are nevertheless changing under influence from within the s tate or surrounding

states

.

5 The renovation fraction is the fraction of renovation (by dollar value) that is assumed to be subject to the new

energy code. In other words, this is the fraction of renovations that impact energy

- related features of the space.

Such features may include HVAC, envelope, and lighting. The renovation fraction was assumed to be 0.7, the value

used in past analyses and based on professional judgment.

6 It is generally the case that there are two different dates associated with an energy code or st andard. One is the

date of adoption; that is when the document is officially “placed on the books.” The other is the effective date; that

is, the date when all commercial buildings are required to comply with what is adopted. Both are critical to energy

savings, but the savings do not technically start to accrue until the adopted document becomes effective and

required.



### 3.9

### 3. Future Adoption

– states are divided into three categories (aggressive, moderate, slow) based on

historical energy code adoption patterns, their respective regulatory review cycle

, and legislative

activity. Future adoption year s are projected based on each state’s applicable category.



### 3.3.1 Historical Explicit Adoption Rate Assumptions

C urrently

, 4 4 states have adopted some form of a statewide commercial building energy code. In t he

remaining states

, local municipalities and/or coun ties within those states are not precluded from adopting

local building energy codes. BECP recognizes that i n all cases, the energy code is effectively

implemented at the local jurisdiction level (county or city) where building construction and permitting

take place. For the purposes of this analysis, status of adoption wa s characterized at the state level.

Status of local jurisdictional adoption was not considered due to a lack of supporting data.

Because states typically adopt the International Energy Conservation Code ( IECC ) and then by

reference in the IECC automatically get Standard 90.1, the adoption assumption tables show the adopted

versions of the IECC and reference versions of Standard 90.1.

From 1992 until the publication of Standard 90 .1

- 1999/2001 , the BECP’s impact was attributable

primarily to efforts to accelerate the adoption of Standard 90.1

- 1989 or model energy codes based on the

standard and to provide materials to improve compliance with Standard 90.1

- 1989. Starting with

Standa rd 90.1

- 2004 , energy savings are also attributable to DOE efforts to improve the energy efficiency

of Standard 90.1 as states updated to Standards 90.1

- 2004 and 90.1

- 2007 or associated versions of the

IECC.

The years when states start ed receiving credit fo r savings induced by adopting the corresponding

version of the code are presented in Table 3

. 5

. T he dates in the table are not actual adoption years, but

rather show the first year when the code comes into effect and the state can be credited for the savings

. July is the cutoff point for crediting the states with saving s for the newly adopted code in a given year

. The cutoff point is consistent with the assumption that there is typically at least a 6

- month lag between the

issuance of the permit and commissioning of the building. Therefore

, if the code becomes effect ive

during July or after, the construction that f ollows will not typically be complete in time for savings to

occur in that calendar year.

Table 3

. 5

. Start Y ear for C rediting S tates with Commercial E nergy C ode S avings B ased on the N ewly

A dopted C ode

State M EC 92

- 95

90.1

- 1989 IECC 2000/2003,

90.1

- 1999/2001 IECC 2006

90.1

- 2004 IECC 2009

90.1

- 2007 IECC 2012

90.1

- 2010

Alabama 2013

Alaska

Arizona

Arkansas 1995 2005 2013

California 1992 2001 2006 2010

Colorado 2005 2008

Connecticut 1990 2005 2009 2012

Delaware 1996 2004 2010

District of Columbia 2000 2004 2010

Florida 1993 2005 2012



### 3.10

### Table 3

. 5 . (contd)

State MEC 92

- 95

90.1

- 1989 IECC 2000/2003,

90.1

- 1999/2001 IECC 2006

90.1

- 2004 IECC 2009

90.1

- 2007 IECC 2012

90.1

- 2010

Georgia 1996 2003 2008 2011

Hawaii 1995 2004 2010

Idaho 2005 2008 2011

Illinois 2006 2008 2010 2013

Indiana 1993 2010

Iowa 1993 2004 2007 2010

Kansas

Kentucky 2005 2007 2011

Louisiana 1999 2005 2007 2011

Maine 1990 2000 2005 2011

Maryland 1997 2005 2007 2010 2012

Massachusetts 1992 2001 2008 2010

Michigan 2009 2011

Minnesota 1999 2009

Mississippi 2013

Missouri

Montana 1996 2005 2010

Nebraska 2005 2012

Nevada 2005 2010 2012

New Hampshire 1999 2002 2007 2010

New Jersey 1997 2002 2007 2011

New Mexico 2004 2008 2012

New York 1991 2002 2008 2011

North Carolina 1996 2006 2009 2012

North Dakota 2011

Ohio 1995 2005 2008 2012

Oklahoma 2011

Oregon 1993 2001 2007 2010

Pennsylvania 2004 2007 2010

Rhode Island 1997 2004 2007 2010

South Carolina 1997 2005 2008 2013

South Dakota

Tennessee 2011

Texas 2001 2011

Utah 1995 2002 2007 2010

Vermont 1996 2001 2007 2012

Virginia 1997 2004 2006 2011

Washington 1994 2002 2005 2011 2013

West Virginia 2003 2010 2012

Wisconsin 1997 2008 2012

Wyoming



### 3.3.2 Historical Implicit Adoption Assumptions

Although some states have not yet adopted any statewide energy code applicable to commercial

buildings, it is unreasonable to believe that common building practice in these states remains at the level

of Standard 90A

- 1980. Building efficiency has improved nationwide because of more cost

- effective

technologies (e.g., electronic ballasts and T

- 8 lamps) and the transfer of knowledge of efficient

construction practices from states with building energy codes. The use of national or regional architect

engineering firms in states with building energy codes influences the level of common practice in other

3.11

### states

— a process characterized as a “spillover” effect. Some spillo ver is simply due to market forces, but

it also could be driven by the adoption of energy codes in other states. Spillover is also driven by

corporations that have properties in multiple states (hotels, retail stores, etc.) that have standardized

designs and typically meet the more stringent energy and buildings standards in their market

. Hence, it

can be argued that the BECP has indirectly influenced new building efficiency in these states as well,

even if the influence is difficult to quantify.

To recog nize that building practices in all states will eventually meet a given historical code level, the

approach in this analysis incorporate d the notion of an “implicit” adoption. For the historical scenario

( “ w ith BECP ” ), the analysis assumed that the effici ency levels implied by Standard 90.1

- 1989, even in

states and jurisdictions without a mandatory energy code, were reached by the late 1990 s at the latest. For

the 1999 and later versions of the ASHRAE standard

, this time lag was assumed to be 10 years

.

If a state skips one or more code cycles and then explicitly adopts a code version, then for the skipped

code versions the credit starts either in the implicit adoption year, or the year when the later code version

was explicitly adopted, whichever comes f irst. For example: North Dakota adopted the IECC 2009 (ICC

2009) in 2011

. 

### T h us, for IECC 2006 (ICC 2006) we show 2011, which is the lesser of the implicit

adoption year (2016) and the explicit adoption year for the next code version (2011).

The code ve rsions with a very small difference in EUIs were combined together for the analysis

purposes. For example, the 2000 and 2003 versions of the IECC (ICC 2000 ; ICC 2003) did not have a

significant difference in energy efficiency requirements (similar to Stan dards 90.1

- 1999 and 90.1

- 2001)

. For these combined code version s

, the 10

- year lag is added to the publication year of the first version in

the combination. Fo r ex ample, the implicit adoption year for the 2000/2003 IECC in Alaska is 2010,

not 2013.

In rea lity, knowledge spillover related to energy codes is gradual, with some practices and

technologies likely to be used in states without codes soon after a code has been adopted in a neighboring

state. Spillover would accelerate as more states adopt codes and regional design and construction firms

carry over efficiency measures to projects in states without codes (or without the most recent national

model code). This analysis did not incorporate the gradual nature of this process because of a lack of data

to justify selection of any particular smoothing method; rather, it assumed a sudden, 1

- year transition to

the newer, more energy

- efficient practices (code level) once states met the 10

- year threshold.

Table 3

. 6 shows the start of the savings stream for both explicit and implicit adoption years

. Implicit

adoption years are highlighted in orange.

Table 3

. 6

. Explicit and Implicit Adoption Years by State and Commercial Code

State MEC 92

- 95

90.1

- 1989 IECC 2000/2003,

90.1

- 1999/2001 IECC 2006

90.1

- 2004 IECC 2009

90.1

- 2007 IECC 2012

90.1

- 2010

Alabama 2002 2010 2013 2013

Alaska 2002 2010 2016

Arizona 2002 2010 2016

Arkansas 1995 2005 2013 2013

California 1992 2001 2006 2010

Colorado 2002 2005 2008

Connecticut 1990 2005 2009 2012



### 3.12

### Table 3.6 . (contd)

State MEC 92

- 95

90.1

- 1989 IECC 2000/2003,

90.1

- 1999/2001 IECC 2006

90.1

- 2004 IECC 2009

90.1

- 2007 IECC 2012

90.1

- 2010

Delaware 1996 2004 2010 2010

District of Columbia 2000 2004 2010 2010

Florida 1993 2005 2005 2012

Georgia 1996 2003 2008 2011

Hawaii 1995 2004 2010

Idaho 2002 2005 2008 2011

Illinois 2002 2006 2008 2010 2013

Indiana 1993 2010 2010 2010

Iowa 1993 2004 2007 2010

Kansas 2002 2010 2016

Kentucky 2002 2005 2007 2011

Louisiana 1999 2005 2007 2011

Maine 1990 2000 2005 2011

Maryland 1997 2005 2007 2010 2012

Massachusetts 1992 2001 2008 2010

Michigan 2002 2009 2011 2011

Minnesota 1999 2009 2009

Mississippi 2002 2010 201 3 2013 2013

Missouri 2002 2010 201 6

Montana 1996 2005 2010 2010

Nebraska 2002 2005 2012 2012

Nevada 2002 2005 2010 2012

New Hampshire 1999 2002 2007 2010

New Jersey 1997 2002 2007 2011

New Mexico 2002 2004 2008 2012

New York 1991 2002 2008 2011

North Carolina 1996 2006 2009 2012

North Dakota 2002 2010 2011 2011

Ohio 1995 2005 2008 2012

Oklahoma 2002 2010 2011

Oregon 1993 2001 2007 2010

Pennsylvania 2002 2004 2007 2010

Rhode Island 1997 2004 2007 2010

South Carolina 1997 2005 2008 2013

South Dakota 2002 2010 2016

Tennessee 2002 2010 2011

Texas 200 1 2001 2011 2011

Utah 1995 2002 2007 2010

Vermont 1996 2001 2007 2012

Virginia 1997 2004 2006 2011

Washington 1994 2002 2005 2011 2013

West Virginia 2003 2010 2012 2012

Wisconsin 1997 2008 2008 2012

Wyoming 2002 2010 2016



### 3.13

### 3.3.3 Future A doption Assumptions

The first step in projecting future code adoption was to c ateg orize the states based on historical

explicit adoption behavior and existing practices. Each category was then assigned a discrete period of

years representing the lag between the code version year and adop tion year i n order to forecast future

code adoption for this analysis . Each state was assigned to one of three categories:

1. A = Aggressive; a state that consistently adopts the most re cent published code OR within

1

– 3 years of published code ( a gap = ≤ 3 years )

Example : Maryland has consistently adopted the most recent published codes over the past decade.

The l ast adoption (of the 2012 IECC) occurred in 2012. Maryland is considered aggressive (adoption

< 3 years of published code).

Assumption of future adoption = 1 year is added after published code

2. M = Moderate ; a state that skips one published code cycle OR exceed s 3 years but less than

6 years be tween adoption (a gap = >3 years and < 6 years )

Example: Idaho adopted the 2009 IECC in 2010 and plan s to adopt the 2012 IECC in 2015 or later.

Idaho exceed s 3 years since previous adoption but not greater than 6 years.

A ssumption of future adoption = 4 years are added after published code

3. S = Slow; a state that skips more than one published code OR exceeds (in years) two published

codes (a gap > 6 years) OR a state without any statewide adoption

Example: Arkansas is categorized as slow, with an 8

- ye ar gap between adoption s even though it

adopted Standard 90.1

- 20 07/2009 IECC in 2013

. Arkansas’ adoption history assumes a long gap

before the next adoption.

A ssumption of future adoption = 7 years are added after published code

State classification s and future adoption lag are presented in Table 3

. 7

. There are six states whose

classification varies between residential and commercial: Kentucky, Louisiana, Utah, Vermont, Virginia,

and Wisconsin.

Table 3

. 7

. State Classification for Future Commercial Energy Code Adoption

Aggressive Moderate Slow

(code version year +1 year) (code version year +4 years) (code version year +7 years)

California Connecticut Alabama

Florida Delaware Alaska

Georgia District of Columbia Arizona

Illinois Idaho Arkansas

Iowa Kentucky Colorado

Maryland Louisiana Hawaii

Massachusetts Maine Indiana

New Hampshire Michigan Kansas

New York Montana Minnesota

North Carolina Nebraska Mississippi



### 3.14

### Table 3

. 7

. (contd)

Aggressive Moderate Slow

(code version year +1 year) (code version year +4 years) (code version year +7 years)

Oregon Nevada Missouri

Rhode Island New Jersey North Dakota

Utah New Mexico Oklahoma

Washington Ohio South Dakota

Pennsylvania Tennessee

South Carolina West Virginia

Texas Wyoming

Vermont

Virginia

Wisconsin



### 3.3.4 Adoption A ssumptions for the C ounterfactual (without BECP) S cenario

This analysis assume d that DOE efforts accelerate d the adoption of the most recently published

model energy code or standard (or equivalent). That is, with a favorable political and fiscal climate, some

states would generally adopt an updated model code or standard within a few years without federal

assistance. 7



### A more difficult issue is how to attribute benefits from the spillover process to the BECP

. Because

the analysis assume d that adoption occurs all at once in a state in a single year, the calculation

methodology d i d not account for spillover effects from other states for the state undergoing adoption in

that year

. However, the implicit adoption of codes is accelerated as a result of national codes and

standards development and deployment activities. Without the DO E activities, the spillover effect in

states without a statewide code would have occurred at a slower rate; therefore

, implicit adoption would

have been delayed as well.

T o develop effective adoption year estimates for the counterfactual analysis, each category of states

was assigned a discrete period of years . This was intended to capture the BECP influence on accelerating

the adoption of : a) an updated energy code or st andard where one existed, or b) a new energy code or

standard where one did not previously exist. To stay consistent with the state groupings for future code

adoption, three sets of lags were used to describe how adoption would likely evolve without BECP :

• For states with aggressive future adoption, one more year was added to the effective adoption year in

the “ w ith BECP ” scenario.

• For states with moderate future adoption, a lag of 6 years was added to the “ w ith BECP” adoption

year.

• For states with a slow adoption rate, only 3 years were added to the “ w ith BECP” adoption year.

A f ull set of adoption assumption s for both scenarios (with and without BECP) is included in

Table 3

. 8 and Table 3

. 9

. Projected adoption years are highlighted in grey.

7 This is typical for cases where the energy code is a component of an entire building regulatory package that

includes building, fire, electrical, mechanical, plumbing

, and other codes that are adopted on a regular 3

- year cycle

, generally 12 to 18 months after their publication by the organization publishing those codes.



### 3.15

### Table 3

. 8

. Commercial Energy Code Adoption A ssumptions for S cenario “ w ith BECP”

MEC

92

- 95,

90.1

-

1989 IECC

2000/2003,

90.1

-

1999/2001 IECC

2006

90.1

-

2004 IECC

2009

90.1

-

2007 IECC

2012

90.1

-

2010 IECC

2015

90.1

-

2013 IECC

2018

90.1

-

2016 IECC

2021

90.1

-

2019 IECC

2024

90.1

-

2022 IECC

2027

90.1

-

2025

S Alabama 2002 2010 2013 2013 2019 2022 2025 2028 2031 2034

S Alaska 2002 2010 2016 2016 2019 2022 2025 2028 2031 2034

S Arizona 2002 2010 2016 2016 2019 2022 2025 2028 2031 2034

S Arkansas 1995 2005 2013 2013 2019 2022 2025 2028 2031 2034

A California 1992 2001 2006 2010 2013 2016 2019 2022 2025 2028

S Colorado 2002 2005 2008 2016 2019 2022 2025 2028 2031 2034

M Connecticut 1990 2005 2009 2012 2016 2019 2022 2025 2028 2031

M Delaware 1996 2004 2010 2010 2016 2019 2022 2025 2028 2031

M District of

Columbia 2000 2004 2010 2010 2016 2019 2022 2025 2028 2031

A Florida 1993 2005 2005 2012 2013 2016 2019 2022 2025 2028

A Georgia 1996 2003 2008 2011 2013 2016 2019 2022 2025 2028

S Hawaii 1995 2004 2010 2016 2019 2022 2025 2028 2031 2034

M Idaho 2002 2005 2008 2011 2016 2019 2022 2025 2028 2031

A Illinois 2002 2006 2008 2010 2013 2016 2019 2022 2025 2028

S Indiana 1993 2010 2010 2010 2019 2022 2025 2028 2031 2034

A Iowa 1993 2004 2007 2010 2013 2016 2019 2022 2025 2028

S Kansas 2002 2010 2016 2016 2019 2022 2025 2028 2031 2034

M Kentucky 2002 2005 2007 2011 2016 2019 2022 2025 2028 2031

M Louisiana 1999 2005 2007 2011 2016 2019 2022 2025 2028 2031

M Maine 1990 2000 2005 2011 2016 2019 2022 2025 2028 2031

A Maryland 1997 2005 2007 2010 2012 2016 2019 2022 2025 2028

A Massachusetts 1992 2001 2008 2010 2013 2016 2019 2022 2025 2028

M Michigan 2002 2009 2011 2011 2016 2019 2022 2025 2028 2031

S Minnesota 1999 2009 2009 2016 2019 2022 2025 2028 2031 2034

S Mississippi 2002 2010 201 3 2013 2013 2022 2025 2028 2031 2034

S Missouri 2002 2010 201 6 201 6 2019 2022 2025 2028 2031 2034

M Montana 1996 2005 2010 2010 2016 2019 2022 2025 2028 2031

M Nebraska 2002 2005 2012 2012 2016 2019 2022 2025 2028 2031

M Nevada 2002 2005 2010 2012 2016 2019 2022 2025 2028 2031

A New Hampshire 1999 2002 2007 2010 2013 2016 2019 2022 2025 2028

M New Jersey 1997 2002 2007 2011 2016 2019 2022 2025 2028 2031

M New Mexico 2002 2004 2008 2012 2016 2019 2022 2025 2028 2031

A New York 1991 2002 2008 2011 2013 2016 2019 2022 2025 2028

A North Carolina 1996 2006 2009 2012 2013 2016 2019 2022 2025 2028

S North Dakota 2002 2010 2011 2011 2019 2022 2025 2028 2031 2034

M Ohio 1995 2005 2008 2012 2016 2019 2022 2025 2028 2031

S Oklahoma 2002 2010 2011 2016 2019 2022 2025 2028 2031 2034

A Oregon 1993 2001 2007 2010 2013 2016 2019 2022 2025 2028

M Pennsylvania 2002 2004 2007 2010 2016 2019 2022 2025 2028 2031

A Rhode Island 1997 2004 2007 2010 2013 2016 2019 2022 2025 2028

M South Carolina 1997 2005 2008 2013 2016 2019 2022 2025 2028 2031

S South Dakota 2002 2010 2016 2016 2019 2022 2025 2028 2031 2034

S Tennessee 2002 2010 2011 2016 2019 2022 2025 2028 2031 2034

M Texas 200 1 2001 2011 2011 2016 2019 2022 2025 2028 2031

A Utah 1995 2002 2007 2010 2013 2016 2019 2022 2025 2028

M Vermont 1996 2001 2007 2012 2016 2019 2022 2025 2028 2031

M Virginia 1997 2004 2006 2011 2016 2019 2022 2025 2028 2031

A Washington 1994 2002 2005 2011 2013 2016 2019 2022 2025 2028

S West Virginia 2003 2010 2012 2012 2019 2022 2025 2028 2031 2034

M Wisconsin 1997 2008 2008 2012 2016 2019 2022 2025 2028 2031

S Wyoming 2002 2010 2016 2016 2019 2022 2025 2028 2031 2034

State Classifications: A = Aggressive; M = Moderate; S = Slow



### 3.16

### Table 3

. 9

. Commercial Energy Code Adoption A ssumptions for Scenario “ w ithout BECP”

MEC

92

- 95

90.1

-

1989 IECC

2000/2003,

90.1

-

1999/2001 IECC

2006

90.1

-

2004 IECC

2009

90.1

-

2007 IECC

2012

90.1

-

2010 IECC

2015

90.1

-

2013 IECC

2018

90.1

-

2016 IECC

2021

90.1

-

2019 IECC

2024

90.1

-

2022 IECC

2027

90.1

-

2025

S Alabama 2005 2013 2016 2016 2022 2025 2028 2031 2034 2037

S Alaska 2005 2013 2019 2019 2022 2025 2028 2031 2034 2037

S Arizona 2005 2013 2019 2019 2022 2025 2028 2031 2034 2037

S Arkansas 1998 2008 2016 2016 2022 2025 2028 2031 2034 2037

A California 1993 2002 2007 2011 2014 2017 2020 2023 2026 2029

S Colorado 2005 2008 2011 2019 2022 2025 2028 2031 2034 2037

M Connecticut 1996 2011 2015 2018 2022 2025 2028 2031 2034 2037

M Delaware 2002 2010 2016 2016 2022 2025 2028 2031 2034 2037

M Distr ict of Columbia 2006 2010 2016 2016 2022 2025 2028 2031 2034 2037

A Florida 1994 2006 2006 2013 2014 2017 2020 2023 2026 2029

A Georgia 1997 2004 2009 2012 2014 2017 2020 2023 2026 2029

S Hawaii 1998 2007 2013 2019 2022 2025 2028 2031 2034 2037

M Idaho 2008 2011 2014 2017 2022 2025 2028 2031 2034 2037

A Illinois 2003 2007 2009 2011 2014 2017 2020 2023 2026 2029

S Indiana 1996 2013 2013 2013 2022 2025 2028 2031 2034 2037

A Iowa 1994 2005 2008 2011 2014 2017 2020 2023 2026 2029

S Kansas 2005 2013 2019 2019 2022 2025 2028 2031 2034 2037

M Kentucky 2008 2011 2013 2017 2022 2025 2028 2031 2034 2037

M Louisiana 2005 2011 2013 2017 2022 2025 2028 2031 2034 2037

M Maine 1996 2006 2011 2017 2022 2025 2028 2031 2034 2037

A Maryland 1998 2006 2008 2011 2013 2017 2020 2023 2026 2029

A Massachusetts 1993 2002 2009 2011 2014 2017 2020 2023 2026 2029

M Michigan 2008 2015 2017 2017 2022 2025 2028 2031 2034 2037

S Minnesota 2002 2012 2012 2019 2022 2025 2028 2031 2034 2037

S Mississippi 2005 2013 2016 2016 2016 2025 2028 2031 2034 2037

S Missouri 2005 2013 201 9 2019 2022 2025 2028 2031 2034 2037

M Montana 2002 2011 2016 2016 2022 2025 2028 2031 2034 2037

M Nebraska 2008 2011 2018 2018 2022 2025 2028 2031 2034 2037

M Nevada 2008 2011 2016 2018 2022 2025 2028 2031 2034 2037

A New Hampshire 2000 2003 2008 2011 2014 2017 2020 2023 2026 2029

M New Jersey 2003 2008 2013 2017 2022 2025 2028 2031 2034 2037

M New Mexico 2008 2010 2014 2018 2022 2025 2028 2031 2034 2037

A New York 1992 2003 2009 2012 2014 2017 2020 2023 2026 2029

A North Carolina 1997 2007 2010 2013 2014 2017 2020 2023 2026 2029

S North Dakota 2005 2013 2014 2014 2022 2025 2028 2031 2034 2037

M Ohio 2001 2011 2014 2018 2022 2025 2028 2031 2034 2037

S Oklahoma 2005 2013 2014 2019 2022 2025 2028 2031 2034 2037

A Oregon 1994 2002 2008 2011 2014 2017 2020 2023 2026 2029

M Pennsylvania 2008 2010 2013 2016 2022 2025 2028 2031 2034 2037

A Rhode Island 1998 2005 2008 2011 2014 2017 2020 2023 2026 2029

M South Carolina 2003 2011 2014 2019 2022 2025 2028 2031 2034 2037

S South Dakota 2005 2013 2019 2019 2022 2025 2028 2031 2034 2037

S Tennessee 2005 2013 2014 2019 2022 2025 2028 2031 2034 2037

M Texas 200 7 2007 2017 2017 2022 2025 2028 2031 2034 2037

A Utah 1996 2003 2008 2011 2014 2017 2020 2023 2026 2029

M Vermont 2002 2007 2013 2018 2022 2025 2028 2031 2034 2037

M Virginia 2003 2010 2012 2017 2022 2025 2028 2031 2034 2037

A Washington 1995 2003 2006 2012 2014 2017 2020 2023 2026 2029

S West Virginia 2006 2013 2015 2015 2022 2025 2028 2031 2034 2037

M Wisconsin 2003 2014 2014 2018 2022 2025 2028 2031 2034 2037

S Wyoming 2005 2013 2019 2019 2022 2025 2028 2031 2034 2037

State Classifications: A = Aggressive; M = Moderate; S = Slow



### 3.17

## 3.4 Code Compliance

Promoting greater compliance with building energy codes is an important element of the BECP. The

BECP conducts activities designed to increase compliance with the existing (or pending) energy code

adopted by a specific state or jurisdiction. Two aspects of compli ance were considered in this analysis : a )

legal compliance, which is defined as meeting all of the provisions of the code ; and b ) compliance in

energy terms, which accounts for energy savings in buildings that only partially meet the requirements of

the ne w energy code. Therefore, compliance in energy terms is defined as “current practice” or the

percentage of the code

- to

- code energy savings achievable from constructing to the level of the prevailing

energy code rather than the prior code

. Similar to the method used for adoption, reasonable alternative

scenarios had to be developed to analyze the difference in compliance levels (in the first year of the code

as well as subsequent years), both in the presence and absence of the BECP. These alternative scen arios

were developed based on the detailed review of several key commercial energy code compliance studies

(DOE 2010)

.

Code training and knowledge of new codes contribute significantly to the success and implementation

of energy codes and savings. Without training, most builders and code officials are un l ikely to change

their behavior , and training activities have been critical to disseminating the necessary information. The

availability of compliance software and materials also increases the succe ss of energy codes because the se

tools enable builders, designers, and code inspectors to assess the compliance of construction plans with

building energy codes.

Another potential reason that new code requirements disseminate

, especially in the commercial

sector

, is professional liability. Registered design professionals may be held to the “most current” design

standards even if their state or local jurisdiction is using an outdated energy code. In addition , more

progressive municipalities and builders c ould be expected to attempt to meet at least some of the more

well

- publicized requirements of the new code (e.g., references to newer lighting technologies) solely

based on their awareness that a new code is in effect. In the analytical framework, this ef fect is modeled

as an increase of code compliance over time.

The following logic was applied to developing compliance assumptions for this assessment

. Even

w ith BECP in place, legal compliance with all provisions of the new code was not assumed to occur in

full, at least not in the first year or two following the adoption of the new code. However, BECP

assistance with t raining, support materials

, and software tools increase s the rate of compliance in energy

terms ( i.e.

, the achieved fraction of nominal e nergy savings for all versions of ASHRAE Standard 90.1 )

. In the absence of the BECP, the legal compliance rates would have been lower

. Similarly, rates of

compliance in energy terms would be lower in the absence of BECP

. Both legal compliance and

compliance in energy terms would increase even without the BECP, but at a slower rate.

If no training or software tools were available to support compliance with the revised code, the initial

rate of compliance in energy terms w as assumed to be about 20

- 30 % lower than what is currently

observed. This particular range was derived based on the review of recent compliance studies and the

report by the American Council for an Energy

- Efficient Economy (ACEEE) (Misuriello et al. 2012)

. This range serves as the estimate of improvement in compliance as a result of training, software support,

technical assistance

, and other programmatic activities. It also provide d the basis for parameterizing

compliance assumptions for the alternative scenario (without BECP).

3.18

### As states become more experienced with building energy codes, the percentage of achieved energy

savings is expected to increase for subsequent versions of the code, even without DOE involvement in

code deployment and compliance su pport.

This logic is reflected in Table 3

. 10 , which shows compliance assumptions for the “with BECP”

scenario for each relevant version of Standard 90.1.

Table 3

. 10

. Compliance Assumptions for Standard 90.1 , “With BECP” Scenario

(a) (b) (c) (d) (e) (f)

Initially

C ompliant

B uildings Initially

N on

compliant

B uildings Weighted

Compliance,

Initial (Energy

Terms) Compl iant

B uildings

after 10

Y ears Non

compliant

B uildings

after 10

Y ears Weighted

Compliance,

After 10

Years

(Energy

Terms)

90.1

- 1989

Compliance in

legal terms 40% 60% 80% 20%

Compliance in

energy terms 1.0 0.5 70% 1.0 0.5 90%

90.1

- 1999

Compliance in

legal terms 40% 60% 80% 20%

Compliance in

energy terms 1.0 0.5 70% 1.0 0.5 90%

90.1

- 2004

Compliance in

legal terms 50% 50% 80% 20%

Compliance in

energy terms 1.0 0.5 75% 1.0 0.5 90%

90.1

- 2007, 90.1

- 2010 and future versions

Compliance in

legal terms 50% 50% 80% 20%

Compliance in

energy terms 1.0 0.5 75% 1.0 0.5 90%

( a ) Compliance in legal terms: percent of new construction fully meeting provisions of code change.

(b) Compliance in energy terms: achieved fraction of nominal code

- to

- code energy savings in buildings that only partially meet

the new code requirements (i.e., buildings that are noncompliant in legal terms).

Columns (c) and (f): Weighted aver age fraction of potential savings for both legally compliant and not legally compliant

buildings.



### For consistency with the end

- use categorization in the code

- to

- code savings analysis, the HVAC end

use group includes heating, cooling, fan, pump

, and heat r ejection, while Lighting/Other includes interior

and exterior lighting, plug and process load

, service hot water, refrigeration

, and generators. Compliance

rates presented in the table above apply to all modeled end

- use groups uniformly.

Examples follow to explain the compliance assumptions in Table 3.10

. As previously noted, t hese

alternative scenarios and assumptions were developed b ased on the detailed review of several key

commercial energy code compliance studies. The table shows two compliance rates in bold for

3.19

### Standard 90.1

- 1989 : weighted initial compliance and weighted compliance in 10 years from code

adoption. Initial weight ed compliance for this code version, shown as 70%, was calculated as follows:

• Given the outreach, training, information dissemination activities, and code compliance software

tools developed under DOE’s BECP at the time, the initial rate of compliance in l egal terms was 40 %.

This means that 40% of newly constructed buildings were assumed to fully comply with the new

energy code provisions. This portion of the buildings achieved a 1.0 fraction of nominal code

- to

- code

energy savings, i.e.

, the compliance in energy terms.

• The remaining portion of new commercial construction (60%) also achieved a fraction of the nominal

code

- to

- code savings (0.5 shown in column b).

• Weighting the compliance in energy terms by the compliance in legal terms prod uce d the initial

weighted compliance rate of 70% with the BECP in place.

As the building community gains experience, even without formal training, technical assistance,

software tools

, or other BECP supporting activities, the legal compliance rate is expe cted to increase over

time for a given code, but at a slower rate. BECP support accelerates improvement in compliance, but

learning remains a significant contributing factor. These learning and spillover effects were accounted for

by looking at legal com pliance rates 10 years from code adoption . For Standard 90.1

- 1989, the weighted

compliance rate in 10 years, shown as 90%, was calculated as follows:

• The legal compliance increases from 40% to 80% ( i.e.

, over 10 years )

, the fraction of the newly

construc ted buildings fully compliant with the code was assumed to double for the earlier code

versions.

• Compliance in energy terms remains the same (0.5 fraction of the nominal code

- to

- code savings is

achieved by the partially

- compliant buildings).

• The improveme nt in legal compliance brings the weighted

- average compliance to 90%.

The compliance rate for each analysis year was calculated by using initial compliance and weighted

compliance for the relevant code version as 10

- year anchor points, and interpolating th e intermediate

compliance rate based on how many years the adopted code version was in place.

As previously stated, for the “with BECP” scenario, the compliance rates wer e assumed to be uniform

across the U nited States

. For the alternative scenario (with out BECP )

, a set of compliance lags was

developed consistent with the classification of states based on code practices and adoption climate. This

assumption was structure d this way for several reasons :

• F or establishing the impact of th e P rogram, it is not the absolute level of compliance that drives the

assessment, but rather the relative difference in compliance rates between the two compared scen ar ios

( “ with BECP ” and “ without BECP ” ).

• It is very difficult to c ompar e absolute levels of com pliance across the states based on any particular

definition of compliance and compatible metric. Review of the available compliance studies revealed

the issues preventing meaningful cross

- comparison of even the most recent results. The principal

issues are differences in definitions of compliance and methods to measure/assess its level, as well as

the application of different compliance metrics.

3.20

### • I t was neither the intent nor the scope of this analysis to compare compliance rates at the state level.

The objective was to estimate the aggregate

, national energy savings induced by BECP activities.

Therefore, it was more important for this analysis to focus on the difference in compliance

attributable to programmatic activities, as opposed to providing a su rvey of compliance rates for each

state across the nation.

The compliance climate is believed to be strongly correlated with the adoption rates and code

practices in place. For the alternative scenario, compliance rates differ across states based on each state’s

adoption category. Also, the credit given to BECP for improving compliance with the older code

versions is lower than the credit for improving compliance with the future code versions. The compliance

difference between the “ with BECP ” and “ witho ut BECP ” scenarios is presented in Table 3

. 11

.

Table 3

. 11

. Percent P oint D ifference between Commercial Compliance L evels “ with BECP ” and

“ without BECP ”

Before 90.1

- 2004,

percentage points

difference After 90.1

- 2004,

percentage points

difference

Aggressive 5% 10%

Moderate 20% 30%

Slow 10% 20%



### This structure of compliance assumptions is consistent with BECP focusing on the development of

energy codes in the past, but switching towards improving compliance in the future.

Following the classification s described in S ection 3.3.3 , for the states with aggressive adoption rate s,

a smaller lag was assumed for adoption, and a smaller percentage point difference wa s assumed for

compliance (5 and 10 percentage points, respectively ). This means that under the alternative scenario

( “ without BECP ” ) , for example, for Standard 90.1

- 1999/200 1 , weighted initial compliance and weighted

compliance in 10 years will be 5 percentage points less than what is shown in Table 3

. 10

. For

Standard 90.1

- 2007, the compliance difference is 10 percentage points.

For the second group of states (with moderate adoption rate s ), it was assumed that without BECP ’s

compliance

- related activities

, compliance would de crease by 2 0% from the values shown in Table 3

. 10

for the code versions prior to Standard 90.1

- 2004, and by 30% for the consecutive code versions.

For states with slow adoption rate s

, the compliance rates would be 10 percentage points less than

what is assumed for the code versions prior to Standard 90.1

- 2004 and 20 percentage points less for the

code versions that follow. The i nitial intent was to not credit BECP with any compliance

- induced savings

in these states. However, American Recov ery and Reinvestment Act ( ARRA 2009) funding to states is

believed to have led to several states adopting and implementing more recent energy codes earlier than

they might have done without support . Therefore, although only a modest improvement is observe d in

this group of states, that improvement h as occurred under targeted BECP support.

3.21

## 3.5 Estimated Benefits of the BECP Comm e rcial Activities

This analysis assumed that BECP commercial energy code efforts improve code

- to

- code energy

efficiency by supporting code development, accelerat e the adoption of the most recent commercial

building energy codes and standards (or equivalent)

, and increas e compliance with the code provisions.

Note that energy savings achieved in C alifornia

, Florida, Oregon, and Washington were totally or

partially removed from the BECP benefits calculation as presented in Table 3

. 12

. 8



### Table 3

. 12

. States E xcluded from the BECP Commercial Benefits Calculation

State Commercial

C alifornia All years excluded

Florida All years excluded

Oregon Excluded 1992

– 2010

Washington Excluded 1992

– 2012



### The analysis period included estimation of the historical (1992

– 

### 2012) and projected benefits

(2013

– 

### 2040) of the BECP commercial energy code activities. Projected benefits included two segments

of savings as illustrated in Figure 3

. 2 : (1) energy savings that will occur in the future, attributable to the

energy code activities and construction to those codes in the past (construction occurring before 2013 but

savings continuing through 2040); and (2) future savings attributable to future energy code activities and

future construction (after 2013). Discussion of the estimation results follow s this structure.

Figure 3

. 2

. Historical and Projected Savings Streams

Following the analysis methodology used by DOE’s Appliance and Equipment Standards Program,

site energy savings were first converted to source terms, which include s energy used in generation,

transmission, and distribution (primary energy). Energy used fu rther “upstream” in the mining,

processing, and transportation of fuels was calculated using the NIA PLUS model (Coughlin 2012) 9 

### and

added to the primary energy savings to yield full

- fuel

- cycle (FFC) energy savings. E missions savings and

8 CA and FL have been exclud ed from this analysis due to their history of adopting their own advanced state

specific codes without direct assistance from BECP’s tools or resources. WA and OR have been partially excluded

due to their history of adopting their own state

- specific codes without direct assistance from BECP ’s tools or

resources, however, OR received state technic al assistance to implement its state

- specific code into COM check in

2010, and WA recently adopted a code based on the IECC.

9 Coughlin, K., Calculation of Full Fuel Cycle Multipliers for Energy Use i n Buildings . LBNL Paper , 2012.



### 3.22

### emissions monetiz ation were also calculated using the NIA PLUS model. Detailed explanations of

technical assumptions, scalars, and cost rates underlying this set of calculations are available (10 CFR 429

and 430)

.

The remainder of this section discusses estimated site, p rimary, and FFC energy savings, emissions

savings, emission mon etization, and consumer benefits.

BECP historical and projected energy savings (site or delivered energy) are presented in Table 3

. 13

.

For the historical portion of the P rogram savings, cumulative site energy savings between 1992 and 2012

totaled 1, 240 trillion British thermal units (TBtu), or about 1.2 quadr illion British thermal units ( quads ),

with the annual site energ y savings being approximately 15 1 TBtu at the end of 2012.

The amount of annual savings in 2012 (15 1 TBtu) from the pre

- 2012 construction continue s from

2013 until 2040 because of the implicit assumption that the average expected lifetime of a commercial

building exceeds the forecast horizon. This portion comprises the first stream of savings. Cumulative

savings from this stream (not shown in the table) equal 4 .2 quads in 2040.

Projected annual site savings from future code activities an d construction equal 556 TBtu in 2040.

Cumulative savings from this second savings stream equal 8 .3 quads by 2040.

When the stream of future savings from past construction and the stream of future savings f rom future

construction are combined, the annua l projected savings equal 707 TBtu at the end of 2040. Cumulative

site energy savings from commercial BECP activities for the period 1992 through 2010 reach 13.8 quads

.

3.23

### Table 3

. 13

. BECP Commercial Site E nergy S avings (TBtu)

Electricity Natural Gas Total Annual

Savings Total

Cumulative

Savings

1992 0.3 0.2 0.6 0.6

1993 0.8 0.6 1.4 2.0

1994 1.3 0.9 2.2 4.1

1995 2.5 1.6 4.2 8 .3

1996 4.5 2.6 7 15

1997 7 3.9 11 26

1998 9 5 15 41

1999 13 7 20 61

2000 16 9 26 86

2001 22 12 34 120

2002 31 16 47 167

2003 38 20 57 224

2004 45 23 69 293

2005 52 27 79 372

2006 61 31 91 463

2007 69 35 104 567

2008 78 40 117 684

2009 84 43 127 812

2010 89 45 134 946 Post 2012 construction only

2011 94 49 143 1,089 Annual Cumulative

2012 100 52 151 1,240 Site TBtu Site TBtu

2013 108 56 164 1,404 13 13

2014 114 60 175 1,579 23 36

2015 122 65 187 1,766 36 72

2016 138 74 211 1,978 60 132

2017 151 82 232 2,210 81 213

2018 163 89 253 2,462 101 315

2019 183 100 283 2,745 131 446

2020 200 110 310 3,055 159 605

2021 218 120 338 3,393 187 792

2022 235 129 364 3,758 213 1,005

2023 251 138 389 4,146 237 1,242

2024 266 146 413 4,559 261 1,504

2025 281 154 435 4,994 283 1,787

2026 294 161 455 5,448 303 2,090

2027 307 167 474 5,923 323 2,413

2028 320 174 495 6,418 344 2,757

2029 333 181 514 6,931 363 3,120

2030 345 187 533 7,464 382 3,501

2031 358 194 552 8,016 400 3,902

2032 370 200 571 8,587 420 4,321

2033 384 207 591 9,178 440 4,761

2034 395 213 609 9,786 457 5,218

2035 407 220 627 10,414 476 5,694

2036 420 226 646 11,060 495 6,189

2037 430 232 661 11,721 510 6,699

2038 440 237 677 12,398 525 7,225

2039 450 242 692 13,090 541 7,765

2040 460 248 707 13,797 556 8,321



### 3.24

### Detailed estimates for primary energy, upstream supply chain

, and full

- fuel

- cycle are presented in

Table 3.14

. Primary energy savings from commercial energy code activities over the 1992

– 2012 period

equaled 2.7 5 quads, with annual savings reaching 0.3 quads in 2012. The amount of annual savings from

the pre

- 2012 construction (0.3 quads) are assumed to continue from 2013 until 2040 (projected savings,

Stream 1). Cumulative savings from this stream (not in the ta ble) equals 9. 4 quads for 2013

– 2040.

Projected annual primary savings from future code activities (projected savings Stream 2) equal

almost 1 quad in 2040. Cumulative savings from this second savings stream equal approximately

14.8 quads for 2013

– 2040.

When the stream of future primary savings from past construction and the stream of future primary

savings from future code activities are combined (Stream 1 + Stream 2), the annual projected savings

equal 1.3 quads by 2040. Cumulative projected savings from commercial BECP activities between 2013

and 2040 exceed 24. 2 quads by 2040.

Combining 2.7 5 quads of cumulative historical savings with 24. 2 quads of cumulative projected

savings brings the total BECP primary energy savings from commercial code activ ities to almost 27

quads for 1992

– 

### 2040.

FFC energy savings from commercial energy code activities over the 1992

– 

### 2012 period equaled

2

. 8 quads , with annual savings reaching 3 4 6 TBtu in 2012. The amount of annual savings from the pre

2012 construction ( 3 4 6 TBtu) are assumed to continue from 2013 until 2040 (projected savings

, S tream 1 )

. Cumulative savi ngs from this stream (not shown in the table) equal almost 9. 7 quads for

2013

– 

### 2040

.

Projected annual FFC energy savings from future code activities (projected savings S tream 2) equal

almost 1 quad in 2040. Cumulative savings from this second savings stream equal 1 5. 3 quads for 2013

–



### 2040

.

When the stream of future savings from past construction and the stream of future savings f rom future

code activ ities are combined ( S tream 1 + S tream 2) , the annual projected savings exceed 1 .3 quads by

2040. Cumulative projected savings from commercial BECP activities between 2013 and 2040 equal

25 quads by 2040.

Combining almost 2. 8 quads of cumulative historical savings with 2 5 quads of cumulative projected

FFC savings brings the total BECP savings from commercial code activities to

27.8 quads for 1992

– 

### 2040.

Historical and projected site energy savings were then used to calculate total commercial energ y cost

savings. For 1992

– 

### 2012 savings, EIA historical electricity and natural gas prices for the commercial

sector 10 

### were converted to 2012 dollars based on the gross domestic product ( GDP ) chain

- type price

index 11 

### to calculate the annual and cumulative cost savings. Annual cost savings reached $ 3. 3 billion in

2012. Cumulative savings between 1992 and 2012 equaled $ 29 billion.

10 U.S. Energy Information Administration. Form EIA

- 826 Database Monthly Electric Utility Sales and Revenue

Data (EIA

- 826 Sales and Revenue Spreadsheets). Select Table: Sales and Revenue Data by State, Monthly Back to

1990 (Fo rm EIA

- 826). (Last accessed June 25, 2013.) < www.eia.gov/electricity/data.cfm#sales >. U.S. Energy

Information Administration. Average Price of Natural Gas Sold to Commercial Consumers

- by S tate . 2012. (Last

accessed June 26, 2013.) < www.eia.gov/oil_gas/natural_gas/data_publications/natural_gas_monthly/ngm.html >

11 Federal Reserve Economic Dat a, Gross Domestic Product: Chain

- type Price Index (GDPCTPI), Index 2005=100,

Annual, Seasonally Adjusted. Economic Research Division, Federal Reserve Bank of St. Louis,

http://research.stlouisfed.org/fred2



### 3.25

### Table 3

. 14

. BECP Commercial Primary and Full

- Fuel

- Cycle E nergy S avings ( TBtu)

Primary Upstream

Supply Chain FFC , Annual FFC,

Cumulative

1992 1.2 0.0 1.2 1.2

1993 2.9 0.1 3.0 4.3

1994 4.5 0.1 4.7 9

1995 9 0.3 9 18

1996 15 0.5 16 34

1997 23 0.7 24 58

1998 32 1.0 33 91

1999 43 1.3 45 135

2000 56 1.7 57 193

2001 73 2.2 76 268

2002 104 3.0 107 375

2003 127 3.7 131 506

2004 152 4.4 157 663

2005 176 5.0 181 843

2006 203 5.8 209 1,053

2007 232 6.6 238 1,291

2008 261 7.5 269 1,560

2009 283 8.1 291 1,851

2010 299 8.6 307 2,158 Post 2012 construction

2011 318 9.0 327 2,485 FFC, FFC,

2012 336 9.8 346 2,831 Annual Cumulative

2013 364 10 374 3,205 29 29

2014 387 11 398 3,603 52 80

2015 414 12 425 4,028 80 160

2016 466 13 480 4,508 134 294

2017 511 15 526 5,034 180 474

2018 555 16 571 5,605 225 699

2019 621 18 638 6,243 293 992

2020 681 20 700 6,944 355 1,347

2021 692 21 713 7,657 367 1,714

2022 746 23 768 8,425 423 2,136

2023 795 24 820 9,244 474 2,610

2024 845 25 871 10,115 525 3,135

2025 891 27 917 11,032 571 3,706

2026 859 28 887 11,919 541 4,248

2027 897 29 926 12,845 580 4,828

2028 936 30 966 13,811 620 5,448

2029 972 31 1,003 14,815 658 6,106

2030 1,008 32 1,041 15,856 695 6,801

2031 1,008 34 1,042 16,898 696 7,497

2032 1,044 35 1,079 17,977 733 8,230

2033 1,081 36 1,117 19,094 771 9,001

2034 1,114 37 1,151 20,244 805 9,806

2035 1,1 47 38 1,185 21,430 840 10,646

2036 1,183 39 1,222 22,651 876 11,522

2037 1,210 40 1,251 23,902 905 12,427

2038 1,238 41 1,279 25,181 934 13,360

2039 1,266 42 1,308 26,490 963 14,323

2040 1,294 43 1,337 27,827 991 15,314



### 3.26

### T he NIA PLUS model was used to calculate the net present value ( NPV ) of projected future cost

savings. AEO 2013 reference case prices were converted to 2012 dollars and a 7% discount rate was

applied. The NPV of annual projected savings in 2040 for S tream 1 equal s $ 0.6 billion. The NPV of

cumulative cost saving s for S tream 1 exceed s $ 44 billion. The NPV of annual projected savings in 2040

for S tream 2 equal s $ 2. 3 billion. The NPV of cumulative cost savings for S tream 2 equal s $ 61.7 billion.

Combined, the NPV of projected future energy cost savings equal s approximately $ 106 billion and the

grand tota l from 1992

– 

### 2040 is $135 billion

. A s ummary of the cost savings along with the FFC energy

savings is presented in Table 3

. 15

.

Table 3

. 15

. Summary of Energy and Cost Savings from the BECP Commercial Energy Code Activities

Site Energy

Savings

,

TBtu Primary Energy

Savings

,

TBtu FFC Energy

Savings

,

TBtu Energy Cost

Savings NPV,

billion 2012$

Historical

Annual in 2012 151 336 346 3.31

Cumulative 1992

- 2012 1,240 2,751 2,831 29.01

Projected, Stream 1

Annual in 2040 151 336 346 0.63

Cumulative 2013

- 2040 4,236 9,408 9,682 44.33

Projected, Stream 2

Annual in 2040 556 958 991 2.30

Cumulative 2013

- 2040 8,321 14,818 15,314 61.72

BECP Total

Annual in 2040 707 1,294 1,337 2.93

Cumulative 1992

- 2040 13,797 26,977 27,827 135.1



### Emissions savings were estimated for carbon dioxide ( CO 2 

### )

, nitrogen oxide ( NO

x 

### )

, m ercury ( Hg )

, nitrous oxide ( N 2 

### O )

, methane ( CH 4 

### )

, and sulfur dioxide ( SO 2 

### )

. Detailed annual results for the emissions

savings are included in Table 3.16

. A s ummary of historical and projected emissions savings is presented

in Table 3

. 17

.

Cumulative emissions reduction s between 1992 and 2040 include more than 2

. 1 b illion metric tons

(Mt) of CO 2 

### , 2

. 7 million tons of SO 2 

### , 2

. 7 million tons of NO

x 

### , and 4. 8 tons of Hg.

The value of the FFC CO 2 

### emission reductions is $ 1.2 to $ 4. 0 billion based on 2013 domestic social

carbon values and a 5% discount rate

, or about $ 17 billion based on 2013 global social cost of carbon

(SCC), while NO

x 

### savings contribute almost another $ 0. 7 

### b illion ( a t $ 468 per ton in 2012$ ) . Energy cost

savings presented in Table 3.15

, combined with monetized emission savings presented in Table 3

. 18

, capture consumer benefits to the nation from the commercial BECP activities. Combined consumer

benefits from commercial BECP ac tivities are shown in Table 3

. 19

. Depending on the price of CO 2 

### and

NO

x 

### , the NPV of overall consumer benefits can range between $ 153 and $ 359 billion ( 2012$ ) . Out of

that total, the energy cost savings constitute $135 billion (2012$).

3.27

### Table 3

. 16

. Annual Emissions Savings from the BECP Commercial Activities , Full

- Fuel

- Cycle

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt ton kt mmt CO 2 eq kt mmt CO 2 eq kt

1992 0.1 0.2 0.00 0.0 0.00 0.4 0.0 0.1

1993 0.2 0.5 0.00 0.0 0.00 1.0 0.0 0.3

1994 0.3 0.7 0.00 0.0 0.00 1.5 0.0 0.4

1995 0.7 1.5 0.00 0.0 0.00 2.9 0.1 0.9

1996 1.1 2.5 0.00 0.0 0.00 4.9 0.1 1.5

1997 1.8 3.9 0.00 0.0 0.01 7.5 0.2 2.3

1998 2.4 5.2 0.01 0.0 0.01 10 0.3 3.1

1999 3.2 7.1 0.01 0.0 0.01 14 0.3 4.3

2000 4.2 9.1 0.01 0.0 0.01 18 0.4 5.5

2001 5.5 12 0.01 0.1 0.02 23 0.6 7.3

2002 7.8 17 0.02 0.1 0.03 33 0.8 10

2003 10 21 0.02 0.1 0.03 40 1.0 13

2004 11 25 0.03 0.1 0.04 47 1.2 15

2005 13 29 0.03 0.2 0.05 55 1.4 18

2006 15 33 0.04 0.2 0.05 63 1.6 21

2007 17 38 0.04 0.2 0.06 72 1.8 23

2008 20 43 0.05 0.2 0.07 81 2.0 26

2009 21 47 0.05 0.2 0.07 88 2.2 29

2010 22 49 0.05 0.3 0.08 93 2.3 30

2011 24 52 0.06 0.3 0.08 98 2.4 32

2012 25 56 0.06 0.3 0.08 104 2.6 34

2013 27 60 0.06 0.3 0.09 109 2.7 37

2014 29 63 0.07 0.3 0.09 116 2.9 39

2015 31 67 0.07 0.3 0.09 126 3.1 41

2016 35 76 0.08 0.3 0.10 141 3.5 46

2017 38 83 0.09 0.4 0.11 154 3.9 51

2018 41 90 0.09 0.4 0.12 167 4.2 55

2019 46 101 0.10 0.5 0.14 186 4.7 61

2020 51 110 0.11 0.5 0.15 203 5.1 67

2021 49 45 0.11 0.6 0.16 220 5.5 210

2022 53 48 0.11 0.6 0.18 235 5.9 226

2023 56 52 0.12 0.6 0.19 250 6.2 241

2024 60 55 0.13 0.7 0.20 264 6.6 256

2025 63 57 0.14 0.7 0.22 277 6.9 270

2026 66 66 0.13 0.8 0.23 290 7.2 51

2027 69 69 0.14 0.8 0.23 302 7.6 53

2028 72 72 0.15 0.8 0.24 316 7.9 56

2029 75 75 0.15 0.8 0.25 328 8.2 58

2030 78 78 0.16 0.9 0.26 341 8.5 60

2031 86 85 0.20 0.9 0.27 353 8.8 51

2032 89 88 0.20 0.9 0.28 366 9.2 53

2033 93 92 0.21 1.0 0.29 380 9.5 55

2034 95 94 0.22 1.0 0.30 391 9.8 56

2035 98 97 0.22 1.0 0.31 402 10.0 58

2036 101 100 0.23 1.1 0.32 414 10.4 60

2037 104 102 0.24 1.1 0.32 424 10.6 61

2038 106 105 0.24 1.1 0.33 434 10.9 63

2039 108 107 0.25 1.1 0.34 445 11.1 64

2040 111 109 0.25 1.2 0.34 455 11.4 65

Total 2,138 2,699 4.75 23 6.88 8,945 224 2,742



### 3.28

### Table 3

. 17

. Summary of Emissions Savings from the BECP C ommercial E nergy C ode A ctivities

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt ton kt mmt CO 2 eq kt mmt CO 2 eq kt

Historical

Annual in 2012 25 56 0.1 0.3 0.1 104 2.6 34

Cumulative 1992

- 2012 206 453 0.5 2.4 0.7 857 21 277

Projected, Stream 1

Annual in 2040 25 56 0.1 0.3 0.1 104 2.6 34

Cumulative 2013

- 2040 706 1,555 1.6 7.6 2.3 2,911 73 946

Projected, Stream 2

Annual in 2040 86 54 0.2 0.9 0.3 351 8.8 32

Cumulative 2013

- 2040 1,226 691 2.6 13.1 3.9 5,176 129 1,519

BECP T otal

Annual in 2040 111 109 0.3 1.2 0.3 455 11 65

Cumulative 1992

- 2040 2,138 2,699 4.8 23.1 6.9 8,945 224 2,742



### Table 3

. 18

. National Cumulative Benefits of the BECP Commercial Activities, 1992

- 2040

Energy Savings

Primary quads 26.98

Upstream quads 0.85

Full

- Fuel

- Cycle (total) quads 27.83

Economic Impacts

Historical Energy Cost Savings billion 2012$ 29.01

Projected Energy Cost Savings billion 2012$ 106.05

Total Energy Cost Savings billion 2012$ 135.07

Emissions Savings (physical)

Primary

CO 2 m mt 2,030

NO

x kt 1,209

Hg t on 4.7

N 2 O kt 22.3

N 2 O mmt CO 2 eq 6.6

CH 4 kt 156

CH 4 mmt CO 2 eq 3.9

SO 2 kt 2,723

Upstream

CO 2 m mt 108

NO

x kt 1,489

Hg t on 0.1

N 2 O kt 0.8

N 2 O mmt CO 2 eq 0.2

CH 4 kt 8,788

CH 4 mmt CO 2 eq 220

SO 2 kt 19

Full

- Fuel

- Cycle (total)

CO 2 m mt 2,138

NO

x kt 2,699

Hg t on 4.8

N 2 O kt 23.1

N 2 O mmt CO 2 eq 6.9

CH 4 kt 8,945

CH 4 mmt CO 2 eq 224

SO 2 kt 2,742



### 3.29

### Table 3

. 18

. (contd)

Emissions Savings (monetized)

Primary

CO 2 (global)

5% discount rate, average billion 2012$ 16.5

3% discount rate, average billion 2012$ 67.7

2.5% discount rate, average billion 2012$ 106.9

3% d iscount r ate , 95th %ile billion 2012$ 205.9

CO 2 (domestic)

5% discount rate, average billion 2012$ 1.2 to 3.8

3% discount rate, average billion 2012$ 4.7 to 15.6

2.5% discount rate, average billion 2012$ 7.5 to 24.6

3% discount rate, 95th %ile billion 2012$ 14.4 to 47.4

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.4

At 2,639 2012$/ton billion 2012$ 2.1

At 4,809 2012$/ton billion 2012$ 3.8

Upstream

CO 2 (global)

5% discount rate, average billion 2012$ 0.9

3% discount rate, average billion 2012$ 3.6

2.5% discount rate, average billion 2012$ 5.7

3% d iscount r ate , 95th %ile billion 2012$ 11.0

CO 2 (domestic)

5% discount rate, average billion 2012$ 0.1 to 0.2

3% discount rate, average billion 2012$ 0.3 to 0.8

2.5% discount rate, average billion 2012$ 0.4 to 1.3

3% discount rate, 95th %ile billion 2012$ 0.8 to 2.5

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.3

At 2,639 2012$/ton billion 2012$ 1.7

At 4,809 2012$/ton billion 2012$ 3.1

Full

- Fuel

- Cycle (total)

CO 2 (global)

5% discount rate, average billion 2012$ 17.3

3% discount rate, average billion 2012$ 71.3

2.5% discount rate, average billion 2012$ 112.6

3% discount rate, 95th %ile billion 2012$ 216.8

CO 2 (domestic)

5% discount rate, average billion 2012$ 1.2 to 4

3% discount rate, average billion 2012$ 5 to 16.4

2.5% discount rate, average billion 2012$ 7.9 to 25.9

3% discount rate, 95th %ile billion 2012$ 15.2 to 49.9

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.7

At 2,639 2012$/ton billion 2012$ 3.8

At 4,809 2012$/ton billion 2012$ 6.9



### 3.30

### Table 3

. 19

. Cumulative Consumer Benefits from BECP Commercial Codes Activities

NPV

Consumer Energy Cost Savings billion 2012$ 135

Consumer & Emissions Value

Consumers + CO 2 (1st) + NO

x (Low) billion 2012$ 153

Consumers + CO 2 (2nd) + NO

x (Med) billion 2012$ 210

Consumers + CO 2 (3rd) + NO

x (Med) billion 2012$ 251

Consumers + CO 2 (4th) + NO

x (High) billion 2012$ 359



### Each of the c onsumer and e missions v alue estimates above represents a combination of consumer

energy cost savings and corresponding scenarios for monetized reduction of CO 2 

### and NO

x 

### . For example,

Consumers + CO 2 

### (1st) + NO

x 

### (Low) means that savings from the first scenario of CO 2 

### (5% discount rate,

average , global SCC ) were combined with savings from the low NO

x 

### cost scenario (at $468 per ton in

2012$) and added to th e consumer energy cost savings.

3.31

# 4.0 R esidential Assumptions and Estimated Results

This section discusses how the energy savings attributable to different residential energy code

versions w ere compared; how the applicable residential floor space subject to the code was dete rmined;

and what adoption and compliance assumptions were used in the analysis

.



## 4.1 Residential Energy Code Performance ( C ode

- to

- C ode S avings)

Required by the Energy Conservation and Production Act (ECPA, Public Law 94

- 385), as modified

by the Energy Policy A ct of 1992 (EPAct 1992), DOE must determine whether the most recent edition of

a national model code (e.g., IECC for residential buildings ) will save energy when compared to its prior

edition. This “determination” process occurs with every new version of the IECC released. Results of

the determination analysis are published in the Federal Register

. If the analysis shows that the revised

code is more energy efficient than the earlier code, each state is required to certify that it has reviewed its

residen tial building energy code regarding energy efficiency and made a decision as to whether it is

appropriate for that state to update its residential building code at or above the revised code. Results of

the D etermination provide the foundation for estimati ng energy savings in this report.

A methodology has been established for evaluating the energy performance of the newest residential

energy codes by comparing with its prede cessors (Taylor et al. 2012). PNNL evaluates the residential

code s as a whole to establish expected energy savings by simulating the effects of the code change(s) on

typical

, new residential buildings, assuming both code provisions are implemented fully and correctly.

Code

- to

- code energy savings used in the residential benefits estimation are results of this analysis

aggregated to the state level.

The most recent analysis 12 

### evaluated the energy savings and economic impacts of the 2009 and 2012

IECC compared to the 2006 IECC, as well as the 2012 IECC compared to the 2009 I ECC. Energy usage

was modeled using DOE’s EnergyPlus software for two residential building prototypes:

1. Single

- Family: A two

- story detached home with a 30

- ft by 40

- ft rectangular shape, 2,400 ft 2 

### of

conditioned floor area

, and a 15% window

- to

- floor ratio, with the window area equally

distributed to the four cardinal directions

.

2. Multifamily: A three

- story building with 18 apartment units (6 units per floor), each with a

conditioned floor area of 1,200 ft 2 

### and a window

- to

- floor ratio of approximately 10%, w ith the

window area equally distributed on all sides of the building.

The prototypes used in the simulations were intended to represent, respectively, a typical new one

- or

two

- family home or townhouse, and a low

- rise multifamily building, such as an apart ment, cooperative,

or condominium. Four foundation types were examined for each prototype building: vented crawlspace,

slab

- on

- grade, heated basement with wall insulation, and unheated basement with insulation in the floor

above the basement. All buildi ngs were evaluated with central air conditioning and each of four heating

system types: gas furnace, oil furnace, heat pump, and electric furnace.

12 Detailed characteristics of the prototypes used in DOE’s analyses and detailed weighting factor information are

discussed in Taylor et al. (2012)

.



### 4.1

### To facilitate climate

- specific energy estimates, PNNL used a set of weather locations that resulted in

broad climate coverage at both the climate zone and state level. One weather location per climate zone in

each state was selected, including all unique combinations of the zone (temperature

- oriented zone

designation in the IECC), moisture regime (moist, dry, m arine), and warm

- humid designation (equivalent

to ASHRAE’s definition of warm

- humid climates). This resulted in a set of 119 weather locations

, which

was then used to simulate the energy performance of each building energy model.

Energy simulation results for a given location were first weighted across the foundation type, system

type, and building type variables, using foundation shares, heating system shares

, and new housing starts

data

, respectively. The weighted

, location

- specific results were then ag gregated to the state level using

new construction starts data.

State

- level estimates of the energy code performance for the 2006, 2009

, and 2012 versions of the

IECC were obtained for three fuels (electricity, natural gas

, and heating oil) and four groups of end uses

(heating, cooling, water heating, and lighting/other). These estimates grouped by fuel type are presented

in Table 4

. 1 i n terms of site energy use per household

.

The analyzed IECC versions contain provisions that overlap with federal appliance efficiency

standards for heating, air conditioning, water heating, and lighting equipment. Because the mandated

efficiency will be enforced as a manufacturing standard regardless of whether it is stipulated in the IECC,

the inclusion of these requirements in the IECC has no separate energy impact. Therefore, code

- to

- code

savings used in the BECP residential benefits analysis explici tly excluded savings induced by the federal

equipment efficiency standards for heating, air conditioning, and water heating. The only exception is

lighting. Savings from high

- efficacy lighting requirements in the 2009 and 2012 IECC were included

because they were an integral part of the building simulations conducted for this analysis. The following

lighting efficiency requirements are present in all cases as follows:

1. 2006 IECC: Lighting per Building America benchmark.

2. 2009 IECC: 2006 IECC with 50% hig h

- efficacy lighting.

3. 2012 IECC: 2006 IECC with 75% high

- efficacy lighting.

It should be noted that the benchmark (2006 IECC) has a 34% high

- efficacy lighting provision. So,

the only overlap is the increase from that benchmark level to meet 50% and 75% re quirements for the

2009 and 2012 versions of the IECC.

Simulated energy performance estimates presented in Table 4

. 1 and Table 4

. 2 were used as a basis for

calculating energy performance of the code versions before the 2006 IECC and after the 2012 IECC

. For

residential code versions predating the 2006 IECC, the energy performance was estimated based on the

residential IECC improvement index developed by PNNL

. The index is presented in Figure 4

. 1

.

4.2

### Table 4

. 1

. Residential Annual Energy Use for all IECC Regulated End

- Uses , Electricity (site kWh/ HH )

Electr.Heating Electr.Cooling Electr.DomHotWater Electr.Other

State IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012

Alabama 3,041 2,655 1,454 4,391 3,664 3,148 2,140 2,140 1,925 1,812 1,516 1,296

Alaska 10,416 9,232 5,807 317 319 388 1,874 1,874 1,686 1,948 1,629 1,393

Arizona 902 798 518 8,856 7,410 6,425 532 532 478 1,922 1,608 1,375

Arkansas 4,264 3,693 2,033 3,904 3,388 2,852 1,624 1,624 1,462 1,678 1,404 1,201

California 909 775 338 1,655 1,281 1,344 1,131 1,131 1,017 1,653 1,383 1,182

Colorado 2,806 2,478 1,567 1,673 1,607 1,609 900 900 809 1,826 1,527 1,306

Connecticut 1,817 1,606 1,048 1,902 1,819 1,739 465 465 418 1,788 1,495 1,279

Delaware 8,314 7,079 3,994 2,653 2,545 2,212 3,051 3,051 2,746 1,908 1,595 1,364

Distr ict of Columb ia 4,068 3,488 2,087 1,957 1,886 1,691 2,407 2,407 2,165 1,127 945 807

Florida 803 719 477 6,927 5,787 5,084 1,930 1,930 1,737 1,815 1,518 1,298

Georgia 3,959 3,428 1,857 4,367 3,659 3,128 2,525 2,525 2,271 1,895 1,584 1,355

Hawaii 48 43 13 8,597 7,682 6,205 2,050 2,050 1,845 1,773 1,483 1,268

Idaho 2,821 2,488 1,588 2,049 1,960 1,898 884 884 795 1,914 1,600 1,369

Illinois 3,054 2,685 1,691 2,396 2,287 2,105 854 854 769 1,622 1,358 1,160

Indiana 3,109 2,721 1,687 2,667 2,542 2,331 870 870 782 1,769 1,479 1,265

Iowa 6,897 6,027 3,650 2,572 2,442 2,246 1,719 1,719 1,547 1,806 1,511 1,292

Kansas 4,803 4,121 2,374 3,270 3,117 2,649 1,554 1,554 1,399 1,797 1,503 1,285

Kentucky 6,771 5,775 3,304 2,598 2,500 2,199 2,572 2,572 2,314 1,788 1,495 1,279

Louisiana 2,672 2,382 1,541 5,510 4,592 4,020 1,510 1,510 1,359 1,935 1,618 1,384

Maine 2,706 2,384 1,465 1,214 1,169 1,184 535 535 482 1,978 1,654 1,415

Maryland 6,427 5,473 3,101 2,689 2,576 2,241 2,844 2,844 2,560 1,748 1,462 1,250

Massachusetts 1,902 1,670 1,060 1,730 1,656 1,615 459 459 412 1,765 1,476 1,262

Michigan 4,509 3,949 2,420 1,691 1,615 1,559 993 993 894 1,882 1,574 1,346

Minnesota 8,359 7,349 4,431 1,656 1,576 1,497 1,841 1,841 1,657 1,734 1,451 1,241

Mississippi 3,291 2,872 1,671 4,824 4,024 3,482 2,145 2,145 1,930 1,881 1,573 1,345

Missouri 4,556 3,925 2,299 3,214 3,068 2,647 1,501 1,501 1,350 1,729 1,447 1,237

Montana 3,337 2,948 1,858 1,250 1,200 1,207 933 933 840 1,724 1,442 1,233

Nebraska 5,396 4,727 2,937 2,784 2,637 2,386 1,613 1,613 1,451 1,716 1,435 1,227

Nevada 1,616 1,399 760 5,847 4,955 3,991 647 648 582 1,891 1,582 1,352

New Hampshire 2,156 1,914 1,240 1,622 1,552 1,503 489 489 440 1,821 1,523 1,303

New Jersey 2,949 2,549 1,522 2,269 2,175 1,966 941 941 847 1,667 1,395 1,193

New Mexico 2,086 1,812 1,052 3,280 2,992 2,638 778 778 700 1,913 1,600 1,368

New York 3,546 3,086 1,847 1,637 1,575 1,515 999 999 898 1,629 1,363 1,165

North Carolina 4,203 3,618 2,014 3,533 3,163 2,725 2,622 2,622 2,359 1,808 1,512 1,293

North Dakota 8,769 7,746 4,739 1,366 1,311 1,270 1,811 1,811 1,629 1,530 1,281 1,094

Ohio 2,839 2,496 1,579 2,050 1,959 1,868 888 888 799 1,798 1,504 1,286

Oklahoma 5,697 4,908 2,560 4,496 3,796 3,116 1,712 1,712 1,540 1,882 1,574 1,346

Oregon 2,800 2,482 1,621 1,353 1,303 1,327 1,389 1,389 1,250 1,830 1,530 1,309

Pennsylvania 3,875 3,402 2,119 2,516 2,394 2,177 1,035 1,035 931 1,933 1,616 1,383

Rhode Island 1,957 1,725 1,112 1,862 1,783 1,726 473 473 426 1,877 1,570 1,342

South Carolina 3,566 3,082 1,607 4,743 4,008 3,346 2,495 2,496 2,245 1,941 1,623 1,388

South Dakota 7,635 6,663 3,942 2,148 2,044 1,898 1,758 1,758 1,582 1,764 1,476 1,262

Tennessee 4,339 3,713 2,114 3,704 3,477 2,991 2,281 2,280 2,053 1,742 1,458 1,246

Texas 2,400 2,125 1,306 5,537 4,644 4,019 1,437 1,437 1,293 1,796 1,502 1,284

Utah 2,351 2,081 1,347 2,815 2,584 2,382 815 815 733 1,818 1,521 1,300

Vermont 2,611 2,286 1,410 1,416 1,354 1,346 510 510 459 1,850 1,547 1,323

Virginia 5,401 4,621 2,632 3,328 3,182 2,731 2,768 2,768 2,491 1,860 1,555 1,330

Washington 3,318 2,916 1,863 1,009 980 1,040 1,432 1,432 1,288 1,780 1,489 1,273

West Virginia 7,683 6,690 4,036 2,177 2,095 1,896 3,045 3,045 2,740 1,788 1,496 1,280

Wisconsin 4,669 4,120 2,545 1,755 1,667 1,571 980 980 882 1,724 1,442 1,233

Wyoming 3,620 3,167 1,891 1,136 1,094 1,114 937 937 843 1,742 1,457 1,247



### 4.3

### Table 4

. 2

. Residential Annual Energy Use for all IECC Regulated End

- Uses

, Natural Gas

, and Heating

Oil ( therm/HH )

Gas Heating Gas DomHotWater Oil Heating Oil DomHotWater

State IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012 IECC

2006 IECC

2009 IECC

2012

Alabama 100 89 46 49 49 44

- - - - - -

Alaska 949 841 519 162 162 145 3 3 2 1 1

-

Arizona 136 123 73 112 112 101

- - - - - -

Arkansas 232 202 107 84 84 75

- - - - - -

California 107 92 34 108 108 96

- - - - - -

Colorado 518 456 270 168 168 150 1 1 1

- - -

Connecticut 422 372 223 118 118 107 230 202 122 64 64 58

Delaware 148 128 71 38 38 34 1 1

- - - -

Dist rict of Col umb ia 73 63 36 31 31 29

- - - - - -

Florida 17 16 10 27 27 24

- - - - - - Georgia 78 69 36 33 33 29

- - - - - -

Hawaii

- - - - - - - - - - - -

Idaho 538 472 279 166 166 149 1 1 1

- - -

Illinois 561 494 296 151 151 136 4 3 2 1 1 1

Indiana 573 505 300 153 153 137 4 3 2 1 1 1

Iowa 538 474 281 120 120 108 2 2 1

- - -

Kansas 405 350 195 110 110 99 2 1 1

- - - Kentucky 195 170 95 56 56 51

- - - - - -

Louisiana 149 134 83 79 79 71

- - - - - -

Maine 607 534 308 133 133 119 331 291 168 72 72 65

Maryland 119 102 56 36 36 32 1 1

- - - -

Massachusetts 452 395 227 117 117 105 246 215 124 64 64 57

Michigan 807 712 426 171 170 154 6 5 3 1 1 1

Minnesota 627 552 327 126 126 114 2 2 1

- - - Mississippi 109 96 54 49 49 43

- - - - - -

Missouri 386 335 189 108 108 96 2 1 1

- - -

Montana 632 557 333 173 173 155 2 2 1

- - -

Nebraska 435 383 232 114 114 103 2 2 1

- - -

Nevada 269 234 113 129 129 116 1 1

- - - - New Hampshire 480 424 255 123 123 110 262 231 139 67 67 61

New Jersey 472 410 233 134 134 121 32 27 16 8 8 8

New Mexico 388 335 174 149 149 133 1 1

- - - -

New York 544 476 278 141 141 126 36 32 19 10 10 9

North Carolina 81 71 36 34 34 30

- - - - - -

North Dakota 605 534 320 125 125 112 2 2 2

- - -

Ohio 537 473 286 156 156 140 3 3 2 1 1 1

Oklahoma 308 267 135 87 87 78

- - - - - - Oregon 322 282 164 127 127 114 1 1 1

- - - Pennsylvania 587 518 309 145 145 130 39 34 21 10 10 9

Rhode Island 456 400 234 120 120 108 249 219 128 65 65 59

South Carolina 69 62 29 33 33 30

- - - - - -

South Dakota 565 497 288 122 122 110 2 2 1

- - -

Tennessee 133 115 63 51 51 47

- - - - - -

Texas 133 119 70 76 76 68

- - - - - -

Utah 424 373 218 155 155 139 1 1 1

- - -

Vermont 585 515 301 127 127 115 319 281 164 70 70 63

Virginia 99 86 46 36 36 32 1

- - - - - Washington 376 329 193 130 130 116 1 1 1

- - - West Virginia 122 108 64 38 38 34 1 1

- - - -

Wisconsin 798 706 419 169 169 151 5 4 3 1 1 1

Wyoming 673 589 333 173 173 155 2 2 1

- - -



### 4.4

### Figure 4

. 1

. IECC Residential Energy Improvement Index

The retroactive code performance scalars for versions between the 1989 MEC and the 200 3 IECC

were developed from this index using 200 6 IECC simulated EUIs as the base. For the code versions prior

to the 2006 IECC , BECP is not credited with the energy improvements related to code development. For

the 2006, 2009 and 2012 IECC

, BECP is credited with 75%, 30%

, and 30% of the code

- to

- cod e energy

efficiency improvement, respectively. These internal estimates are based on the professional judgment of

staff involved in code support

. This means that if there were a 24% reduction in the EUI between the

2009 IECC and the 2006 IECC in the “with BECP” scenario, we assumed that without the DOE

assistance in place the code would have advanced by about 1 6 % instead.

Consistent with BECP shifting from a focus on code developmen t in the past to more support for

improvement in code implementation in the future, only 0. 5% of the code

- to

- code energy efficiency

improvement wa s attributed to BECP for the code versions after the 2012 IECC

. It was assumed that in

the “ with BECP ” scenar io there would be a 5 % improvement in the energy use per code cycle , while a

4.5 % improvement is expected without the DOE program in place

.

Nominal code

- to

- code energy savings were derived from the code energy performance estimates by

comparing the code version that is adopted in the state to the previousl y active code version. Nominal

energy savings were then adjusted by the compliance rates. Residential adoption and compliance

assumptions are described in S ections 4.3 and 4.4

.

4.5

## 4.2 Residential Floor S pace Forecast

Calculating new floor space is integral to the analysis of building energy codes because the potential

energy savings are estimated by square foot. However , there are no publicly available data sources that

show annual new floor space of residen tial buildings constructed by state. A further complication is that

building codes apply not only to new square footage, but also to additions and major alterations.

The estimates for household stock additions via new construction of single

- family and l ow

- rise

multifamily buildings, and floor space additions (in terms of household equivalents) to existing single

family homes were combined into one time

- series of code

- relevant housing additions . Only newly

- added

space wa s included; no impacts associated with alterations to existing floor space we re incorporated in the

estimate

. 13 

### The code

- to

- code savings we re then applied to this housing projection for calculating the

national energy benefits of the BECP residential activities. The estimation of the code

- applicable floor

space is discussed in detail below.



### 4.2.1 Historical D ata for N ew Residential C onstruction

Census residential building permit data , for the years 1992 through 2012, were used to develop a

time

- series of estimated historical completions. Permit data were used, rather than actual c ensus

completion data, because permits are available at the state level, whereas completion data are only

available at the c e nsus r egion level. The c ensus provides the permit data categorized into the following

living unit

- based categories:

• 1 unit

• 2 units

• 3 and 4 units

• 5 units or more.

State

- level estimates of s ingle

- family and low

- rise multi family units are required. For mu ltifamily

units, r esidential building codes only apply to low

- rise buildings, i.e., buildings having three or fewer

stories above grade , so it is necessary to estimate the fraction of units in the “5 units or more” category

that are in low

- rise buildings. To accomplish this , several steps were taken:

• Utilized the data from the 2009 Residential Energy Consumption Survey ( RECS Table HC2.1 ). This

table categorizes multifamily units, in buildings with five or more units, into various “number of

floor” categories.

• A ssumed that 60% 14 

### of the units in the “3

- 4 Floors” category were in three

- floored buildings.

• Add ed the resulting number of units in three

- floored buildings to those in the “1

- 2 Floors” category,

and then divid ed by the total number of units, which yielded a fraction of units in

five

- plus unit buildings that are classified as low

- rise.

• Applied t his fraction to the annual c ensus permit data in order to derive state

- level estimates of

single

- family and low

- rise multifamily units.

13 Based on analysis of the American Housing Survey, alterations acco unted for about 0.1% of the existing floor

space, with energy

- significant alterations comprising only a fraction of that.

14 Based on the analysis of RECS and CBECS.



### 4.6

### Additionally , the fraction of multifamily units classified as low

- rise was also estimated by applying

the fraction discu ssed in the previous paragraph to 10 years (2003

- 2012) of the c ensus permit data. This

result was later applied to the AEO

- derived multifamily household data to extract an estimate of low

- rise

multifamily households.

To account for the lag between the per mitting and completion of a building, c ensus permit data were

converted to estimated completions by introducing a lag of 6 months

. 15



### 4.2.2 Projected D ata for N ew C onstruction and A dditions to E xisting

Residential B uildings

The AEO 2012 Reference Case forecasts residential stock (in terms of households) by housing type

(single

- family, multifamily, and manufactured home) and the nine c ensus d ivisions. Annual residential

stock survival factors from EIA’s National Energy Modeling System (NEMS) residential documentation

(EIA 2013) were applied to the stock to derive a forecast of additions to residential stock. The survival

facto rs are:

Single

- family stock survival factor: 0.996

Multifamily stock survival factor: 0.999

Manufactured home stock survival factor: 0.976



### Given that the AEO multifamily data include both low

- rise and high

- rise multifamily households, it

was necessary to apply the fraction of multifamily units classified as low

- rise discussed in Section 4.2.1

. Adding the resulting low

- rise multifamily data to the single

- family data provided a forecast of household

additions to stock potentially impact ed by the residential energy codes.

New construction is not the only means by which building energy codes may provide energy savings.

Additions to existing homes are also subject to the energy codes. Estimates of floor space additions due

to expansions of existing single

- family homes are necessary to capture such impacts. Key steps,

assumptions, and details include d in this estimation were as follows:

• It was assumed that expansion of existing homes only occurs in the case of single

- family, rather than

m

ultifamily, homes.

• The single

- family stock survival factor was used to calculate surviving stock.

• Based on information included in the NEMS residential documentation , it was assumed that 1% of

the surviving, existing single

- family stock receives a 600

- ft 2 

### addition in a given year.

• The results were converted to household equivalents, obtained by dividing the added floor space by

the size of a prototype single

- family home. This prototype

, single

- family home was assumed to

contain 2,400 ft 2 

### (Taylor et al. 2012, Table 2.1).

• Year

- specific ratios of added floor space (in terms of household equivalents) to households added via

new construction were calculated. The national

- level ratios were later used as scalar s to convert

state

- level new cons truction numbers to values that include additions to existing single

- family homes.

15 For more detailed data on the typical lag between starts and completions

, see c ensus statistics available at

http://www.census.gov/constructio n/nrc/lengthoftime.html

.



### 4.7

### 4.2.3 Integration of H istorical and Project ed Residential D ata

Census

- based historical data and the AEO

- derived forecast combined into a single time

- series serve d

as an estimate o f the housing stock impacted by the residential energy codes. The c ensus data are at the

state level, and provide data for the years 1992 through 2012. The AEO data are at the c ensus d ivision

level, and include data for the years 2005 through 2040. T o g enerate consistent

, state

- level time

- series

data through 2040, the following steps were taken:

• Census d ivision

- level growth rates embedded in the AEO data were applied to the state

- level c ensus

data, with the 2012 c ensus data used as the base. This step r elied on the implicit assumption that

states ’ shares within each c ensus d ivision remain constant at 2012 levels.

• Expansions of surviving, single

- family homes, in terms of household equivalents, were then added to

the forecast.

• Previously mentioned national, year

- specific scalars were applied to the state

- level additions to stock

data to integrate additions of space to existing homes.

The resulting estimates represent additions to household stock via new construction of single

- family

and low

- rise multifamily buildings, and additions of floor space (in terms of household equivalents) to

existing single

- family homes. Only newly added space was included; no impacts associated with

alterations to existing floor space we re incorporated in the estimate. The code

- to

- code savings were

applied to this housing projection for calculating national energy benefits of the residential BECP

activities.



## 4.3 Adoption of Residential Energy Codes

The same methodology developed for the commercial analysis was u sed for residential (see S ection

3.3). However, the historical explicit, implicit, future adoptions, and counterfactual scenario assumptions

for residential energy codes differ from the commercial analysis. Some states adopt residential codes on a

differ ent code cycle than commercial or have no code cycle in place for residential but might for

commercial. Currently, 43 states have adopted a residential building energy code. The following tables

present the residential energy code adoption assumptions an d categorizations.

Table 4

. 4 s hows the start of the residential savings stream for both explicit and implicit adoption

years. Implicit adoption years are highlighted in orange.

Although the same approach for categorization is used in both the residential and commercial

analys e s, BECP tracks adoption for commercial and residential energy codes separately. Therefore

, the

state allocation across the adoption groups is different as presented in Table 4

. 5

. There are six states

whose classification varies between residential and commercial: Kentucky, Louisiana, Utah, Vermont,

Virgini a, and Wisconsin.

4.8

### Table 4

. 3

. Start Year for Crediting States with Residential Energy Code Savings Based on the Newly

Adopted Code

State MEC 92

- 95 IECC 1998/2000 IECC 2003 IECC 2006 IECC 2009 IECC 2012

Alabama 2013

Alaska

Arizona

Arkansas 1995 2005

California 1994 2003 2006 2010

Colorado 1996 2005 2008

Connecticut 1999 2005 2009 2012

Delaware 1996 2004 2010

District of Columbia 2000 2004 2010

Florida 1993 2002 2005 2012

Georgia 1996 2004 2008 2011

Hawaii 1997 2010

Idaho 2003 2005 2008 2011

Illinois 2010 2013

Indiana 1993 2012

Iowa 1993 2004 2007 2010

Kansas

Kentucky 1997 2005 2007 2012

Louisiana 2011

Maine 2005 2011

Maryland 1997 2001 2005 2007 2010 2012

Massachusetts 1998 2001 2008 2010

Michigan 2009 2011

Minnesota 2000 2009

Mississippi

Missouri

Montana 1993 2005 2010

Nebraska 2005 2012

Nevada 2005 2010 2012

New Hampshire 1999 2002 2007 2010

New Jersey 1997 2002 2007 2011

New Mexico 1994 2004 2008 2012

New York 1992 2002 2008 2011

North Carolina 1993 2002 2006 2009 2012

North Dakota 2011

Ohio 1995 2002 2005 2009 2013

Oklahoma 2011

Oregon 1992 2003 2005 2008 2011

Pennsylvania 2004 2007 2010

Rhode Island 1997 2002 2004 2007 2010

South Carolina 1998 2001 2005 2009 2013

South Dakota

Tennessee 2009 2011

Texas 2001 2012

Utah 1995 2002 2004 2007

Vermont 1998 2005 2012

Virginia 1993 2004 2006 2008 2011

Washington 1994 2002 2005 2007 2011 2013

West Virginia 2003 2006 2012

Wisconsin 1999 2009

Wyoming



### 4.9

### Table 4

. 4

. Start of the Residential S avings S tream B ased on E xplicit and I mplicit A doption

State MEC 92

- 95 IECC 1998/2000 IECC 2003 IECC 2006 IECC 2009 IECC 2012

Alabama 2002 2008 2013 2013 2013

Alaska 2002 2008 2013 2016

Arizona 2002 2008 2013 2016

Arkansas 1995 2005 2005 2016

California 1994 2003 2006 2006 2010

Colorado 1996 2005 2005 2008

Connecticut 1999 2005 2005 2009 2012

Delaware 1996 2004 2010 2010 2010

District of Columbia 2000 2004 2010 2010 2010

Florida 1993 2002 2005 2012 2012

Georgia 1996 2004 2008 2008 2011

Hawaii 1997 2008 2010 2010

Idaho 2002 2003 2005 2008 2011

Illinois 2002 2008 2010 2010 2010 2013

Indiana 1993 2008 2012 2012 2012

Iowa 1993 2004 2004 2007 2010

Kansas 2002 2008 2013 2016

Kentucky 1997 2005 2007 2007 2012

Louisiana 2002 2008 2011 2011

Maine 2002 2005 2005 2011 2011

Maryland 1997 2001 2005 2007 2010 2012

Massachusetts 1998 2001 2008 2008 2010

Michigan 2002 2008 2009 2011 2011

Minnesota 2000 2008 2009 2009

Mississippi 2002 2008 2013 2016

Missouri 2002 2008 2013 2016

Montana 1993 2005 2005 2010 2010

Nebraska 2002 2005 2005 2012 2012

Nevada 2002 2005 2005 2010 2012

New Hampshire 1999 2002 2007 2007 2010

New Jersey 1997 2002 2002 2007 2011

New Mexico 1994 2004 2004 2008 2012

New York 1992 2002 2008 2011 2011

North Carolina 1993 2002 2006 2009 2012

North Dakota 2002 2008 2011 20 11 2011

Ohio 1995 2002 2005 2009 2013

Oklahoma 2002 2008 2011 2011 2011

Oregon 1992 2003 2005 2008 2011

Pennsylvania 2002 2004 2004 2007 2010

Rhode Island 1997 2002 2004 2007 2010

South Carolina 1998 2001 2005 2009 2013

South Dakota 2002 2008 2013 2016

Tennessee 2002 2008 2009 2011

Texas 200 1 2001 2012 2012 2012

Utah 1995 2002 2004 2007

Vermont 1998 2005 2012 2012 2012

Virginia 1993 2004 2006 2008 2011

Washington 1994 2002 2005 2007 2011 2013

West Virginia 2002 2003 2006 2012 2012

Wisconsin 1999 2008 2009 2009

Wyoming 2002 2008 2013 2016



### 4.10

### Table 4

. 5

. State Classification s for Future Residential Energy Code Adoption

Aggressive M oderate Slow

(code version year +1 year) (code version year +4 years) (code version year +7 years)

California Connecticut Alabama

Florida Delaware Alaska

Georgia District of Columbia Arizona

Illinois Idaho Arkansas

Iowa Kentucky Colorado

Maryland Maine Hawaii

Massachusetts Michigan Indiana

New Hampshire Montana Kansas

New York Nebraska Louisiana

North Carolina Nevada Minnesota

Oregon New Jersey Mississippi

Rhode Island New Mexico Missouri

Virginia Ohio North Dakota

Washington Pennsylvania Oklahoma

South Carolina South Dakota

Texas Tennessee

Utah

Vermont

West Virginia

Wisconsin

Wyoming



### The f ull set of residential code adoption assumption s for both scenarios ( “ with BECP” and “ without

BECP ” ) is included in Table 4

. 6 and Table 4

. 7

. Proje cted adoption years are highlighted in grey.

4.11

### Table 4

. 6

. Residential Energy Code Adoption A ssumptions for the S cenario “with BECP”

MEC

92

- 95 IECC

1998/2000 IECC

2003 IECC

2006 IECC

2009 IECC

2012 IECC

2015 IECC

2018 IECC

2021 IECC

2024

S Alabama 2002 2008 2013 2013 2013 2019 2022 2025 2028 2031

S Alaska 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

S Arizona 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

S Arkansas 1995 2005 2005 2016 2016 2019 2022 2025 2028 2031

A California 1994 2003 2006 2006 2010 2013 2016 2019 2022 2025

S Colorado 1996 2005 2005 2008 2016 2019 2022 2025 2028 2031

M Connecticut 1999 2005 2005 2009 2012 2016 2019 2022 2025 2028

M Delaware 1996 2004 2010 2010 2010 2016 2019 2022 2025 2028

M Dist r ict of

Columbia 2000 2004 2010 2010 2010 2016 2019 2022 2025 2028

A Florida 1993 2002 2005 2012 2012 2013 2016 2019 2022 2025

A Georgia 1996 2004 2008 2008 2011 2013 2016 2019 2022 2025

S Hawaii 1997 2008 2010 2010 2016 2019 2022 2025 2028 2031

M Idaho 2002 2003 2005 2008 2011 2016 2019 2022 2025 2028

A Illinois 2002 2008 2010 2010 2010 2013 2016 2019 2022 2025

S Indiana 1993 2008 2012 2012 2012 2019 2022 2025 2028 2031

A Iowa 1993 2004 2004 2007 2010 2013 2016 2019 2022 2025

S Kansas 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

M Kentucky 1997 2005 2007 2007 2012 2016 2019 2022 2025 2028

S Louisiana 2002 2008 2011 2011 2016 2019 2022 2025 2028 2031

M Maine 2002 2005 2005 2011 2011 2016 2019 2022 2025 2028

A Maryland 1997 2001 2005 2007 2010 2012 2016 2019 2022 2025

A Massachusetts 1998 2001 2008 2008 2010 2013 2016 2019 2022 2025

M Michigan 2002 2008 2009 2011 2011 2016 2019 2022 2025 2028

S Minnesota 2000 2008 2009 2009 2016 2019 2022 2025 2028 2031

S Mississippi 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

S Missouri 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

M Montana 1993 2005 2005 2010 2010 2016 2019 2022 2025 2028

M Nebraska 2002 2005 2005 2012 2012 2016 2019 2022 2025 2028

M Nevada 2002 2005 2005 2010 2012 2016 2019 2022 2025 2028

A New Hampshire 1999 2002 2007 2007 2010 2013 2016 2019 2022 2025

M New Jersey 1997 2002 2002 2007 2011 2016 2019 2022 2025 2028

M New Mexico 1994 2004 2004 2008 2012 2016 2019 2022 2025 2028

A New York 1992 2002 2008 2011 2011 2013 2016 2019 2022 2025

A North Carolina 1993 2002 2006 2009 2012 2013 2016 2019 2022 2025

S North Dakota 2002 2008 2011 2011 2011 2019 2022 2025 2028 2031

M Ohio 1995 2002 2005 2009 2013 2016 2019 2022 2025 2028

S Oklahoma 2002 2008 2011 2011 2011 2019 2022 2025 2028 2031

A Oregon 1992 2003 2005 2008 2011 2013 2016 2019 2022 2025

M Pennsylvania 2002 2004 2004 2007 2010 2016 2019 2022 2025 2028

A Rhode Island 1997 2002 2004 2007 2010 2013 2016 2019 2022 2025

M South Carolina 1998 2001 2005 2009 2013 2016 2019 2022 2025 2028

S South Dakota 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

S Tennessee 2002 2008 2009 2011 2016 2019 2022 2025 2028 2031

M Texas 200 1 2001 2012 2012 2012 2016 2019 2022 2025 2028

S Utah 1995 2002 2004 2007 2016 2019 2022 2025 2028 2031

S Vermont 1998 2005 2012 2012 2012 2019 2022 2025 2028 2031

A Virginia 1993 2004 2006 2008 2011 2013 2016 2019 2022 2025

A Washington 1994 2002 2005 2007 2011 2013 2016 2019 2022 2025

S West Virginia 2002 2003 2006 2012 2012 2019 2022 2025 2028 2031

S Wisconsin 1999 2008 2009 2009 2016 2019 2022 2025 2028 2031

S Wyoming 2002 2008 2013 2016 2016 2019 2022 2025 2028 2031

State Classifications: A = Aggressive; M = Moderate; S = Slow



### 4.12

### Table 4

. 7

. Residential Energy Code Adoption A ssumptions for the S cenario “with out BECP”

MEC

92

- 95 IECC

1998/2000 IECC

2003 IECC

2006 IECC

2009 IECC

2012 IECC

2015 IECC

2018 IECC

2021 IECC

2024

S Alabama 2005 2011 2016 2016 2016 2022 2025 2028 2031 2034

S Alaska 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

S Arizona 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

S Arkansas 1998 2008 2008 2019 2019 2022 2025 2028 2031 2034

A California 1995 2004 2007 2007 2011 2014 2017 2020 2023 2026

S Colorado 1999 2008 2008 2011 2019 2022 2025 2028 2031 2034

M Connecticut 2005 2011 2011 2015 2018 2022 2025 2028 2031 2034

M Delaware 2002 2010 2016 2016 2016 2022 2025 2028 2031 2034

M District of Columbia 2006 2010 2016 2016 2016 2022 2025 2028 2031 2034

A Florida 1994 2003 2006 2013 2013 2014 2017 2020 2023 2026

A Georgia 1997 2005 2009 2009 2012 2014 2017 2020 2023 2026

S Hawaii 2000 2011 2013 2013 2019 2022 2025 2028 2031 2034

M Idaho 2008 2009 2011 2014 2017 2022 2025 2028 2031 2034

A Illinois 2003 2009 2011 2011 2011 2014 2017 2020 2023 2026

S Indiana 1996 2011 2015 2015 2015 2022 2025 2028 2031 2034

A Iowa 1994 2005 2005 2008 2011 2014 2017 2020 2023 2026

S Kansas 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

M Kentucky 2003 2011 2013 2013 2018 2022 2025 2028 2031 2034

S Louisiana 2005 2011 2014 2014 2019 2022 2025 2028 2031 2034

M Maine 2008 2011 2011 2017 2017 2022 2025 2028 2031 2034

A Maryland 1998 2002 2006 2008 2011 2013 2017 2020 2023 2026

A Massachusetts 1999 2002 2009 2009 2011 2014 2017 2020 2023 2026

M Michigan 2008 2014 2015 2017 2017 2022 2025 2028 2031 2034

S Minnesota 2003 2011 2012 2012 2019 2022 2025 2028 2031 2034

S Mississippi 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

S Missouri 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

M Montana 1999 2011 2011 2016 2016 2022 2025 2028 2031 2034

M Nebraska 2008 2011 2011 2018 2018 2022 2025 2028 2031 2034

M Nevada 2008 2011 2011 2016 2018 2022 2025 2028 2031 2034

A New Hampshire 2000 2003 2008 2008 2011 2014 2017 2020 2023 2026

M New Jersey 2003 2008 2008 2013 2017 2022 2025 2028 2031 2034

M New Mexico 2000 2010 2010 2014 2018 2022 2025 2028 2031 2034

A New York 1993 2003 2009 2012 2012 2014 2017 2020 2023 2026

A North Carolina 1994 2003 2007 2010 2013 2014 2017 2020 2023 2026

S North Dakota 2005 2011 2014 2014 2014 2022 2025 2028 2031 2034

M Ohio 2001 2008 2011 2015 2019 2022 2025 2028 2031 2034

S Oklahoma 2005 2011 2014 2014 2014 2022 2025 2028 2031 2034

A Oregon 1993 2004 2006 2009 2012 2014 2017 2020 2023 2026

M Pennsylvania 2008 2010 2010 2013 2016 2022 2025 2028 2031 2034

A Rhode Island 1998 2003 2005 2008 2011 2014 2017 2020 2023 2026

M South Carolina 2004 2007 2011 2015 2019 2022 2025 2028 2031 2034

S South Dakota 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

S Tennessee 2005 2011 2012 2014 2019 2022 2025 2028 2031 2034

M Texas 200 7 2007 2018 2018 2018 2022 2025 2028 2031 2034

S Utah 1998 2005 2007 2010 2019 2022 2025 2028 2031 2034

S Vermont 2001 2008 2015 2015 2015 2022 2025 2028 2031 2034

A Virginia 1994 2005 2007 2009 2012 2014 2017 2020 2023 2026

A Washington 1995 2003 2006 2008 2012 2014 2017 2020 2023 2026

S West Virginia 2005 2006 2009 2015 2015 2022 2025 2028 2031 2034

S Wisconsin 2002 2011 2012 2012 2019 2022 2025 2028 2031 2034

S Wyoming 2005 2011 2016 2019 2019 2022 2025 2028 2031 2034

State Classifications: A = Aggressive; M = Moderate; S = Slow



### 4.13

## 4.4 Residential Energy Code Compliance

The logic applied in developing residential energy code compliance assumptions was similar to that

used for the commercial compliance assumptions

. It is the relative difference in compliance rates

between the two scenarios, rather than the absolute level of compli ance, that drives the estimation. Very

little comparable information exists on state

- by

- state compliance rates

. Therefore

, uniform

, national

compliance rates parameterized based on the review of the available compliance studies were applied for

the “with BECP” scenario. These compliance rates are presented in Table 4

. 8

.

Table 4

. 8

. Residential Code Compliance Assumptions for “With BECP” Scenario

(a) (b) (c) (d) (e) (f)

Initially

C ompliant

B uildings Initially

N on

compliant

B uildings Weighted

Compliance,

Initial

(Energy

Terms) Compliant

B uildings

after

10 Years Non

compliant

B uildings

after

10 Y ears Weighted

Compliance,

a fter 10 Years

(Energy

Terms)

MEC 92

– 200 IECC

Compliance in legal terms 60% 40% 80% 20%

Compliance in energy

terms 1.00 0.40 76% 1.00 0.40 88%

2003 IECC

Compliance in legal terms 65% 35% 80% 20%

Compliance in energy

terms 1.00 0.50 83% 1.00 0.50 90%

2006 IECC

Compliance in legal terms 70% 30% 90% 10%

Compliance in energy

terms 1.00 0.50 85% 1.00 0.50 95%

2009 IECC and after

Compliance in legal terms 50% 50% 80% 20%

Compliance in energy terms 1.00 0.40 70% 1.00 0.40 88%

( a ) Compliance in legal terms: percent of new housing units fully meeting provisions of code change.

(b) Compliance in energy terms: achieved fraction of nominal code

- to

- code energy savings in buildings that only partially meet

the new code requirements (i.e., buildings that are noncompliant in legal terms).

Columns (c) and (f): Weighted average fraction of potential savings for both legally compliant and not legally compliant

buildings.



### Compliance rates presented in the table above apply to all modeled end

- use groups uniformly.

Similar logic discussed in S ection 3.4 is applied here. Compliance assumpt ions f or the scenario “ without

BECP ” were developed based on the state categorization. The percentage point difference in compliance

between scenarios “ with BECP ” and “ without BECP ” is presented in Table 4

. 9

.

Table 4

. 9

. Percent P oint D ifference b etween Residential C ompliance L evels “ with BECP ” and “ without

BECP ” Scenarios

Before 2006

IECC 2006 IECC

and after

Aggressive 5% 10%

Moderate 20% 30%

Slow 10% 20%



### 4.14

## 4.5 Estimated Be nefits of the Residential BECP A ctivities

This analysis assumed that BECP residential energy code efforts improve code

- to

- code energy

efficiency by support ing code development, accelerating the adoption of the most recent residential

building energy codes (or equivalent)

, and increasing compliance with the code provisions. Note that

energy savings achieved in C alifornia , W ashington, Oregon, and F lorida were totally or partially removed

from the BECP benefits calculation as presented in Table 4

. 10

. 16



### Table 4

. 10

. States Excluded from the BECP Residential Benefits Calculation

State Residential

C alifornia All years excluded

F lorida Excluded 1992

– 2011

Oregon All years excluded

Washington Excluded 1992

– 2012



### Following the analysis methodology used by DOE’s Appliance and Equipment Standards Program, site

energy savings were first converted to source terms, which includes energy used i n generation,

transmission, and distribution (primary energy). Energy used further “upstream” in the mining, processing,

and transportation of fuels was calculated using the NIA PLUS model (Coughlin 2012) 17 

### and added to the

primary energy savings to yield full

- fuel

- cycle (FFC) energy savings. E missions savings and emissions

monetization were also calculated using the NIA PLUS model. Detailed explanations of technical

assumptions, scalars, and cost rates un derlying this set of calculations are available (10 CFR 429 and 430).

The remainder of this section discusses estimated site and primary energy savings, FFC savings,

emissions savings, emission s mon etization

, and consumer benefits.

BECP historical and pro jected energy savings (site or delivered energy) are presented in Table 4

. 11

.

For the historical portion of the P rogram savings, cumulative site energy savings betwe en 1992 and 2012

totaled 7 19 TBtu, with the annual site energy savings being approximately 81 TBtu at the end of 2012.

The amount of annual savings ( 81 TBtu) in 2012 from the pre

- 2012 construction is assumed to

continue from 2013 until 2040 because of the implicit assumption that the average expected lifetime of a

residential building exceeds the forecast horizon. This portion comprises the first stream of savings.

Cumulative savin gs from this stream equal 2

. 3 quads in 2040.

Projected annual site savings from future code activities and construction equal 458 TBtu in 2040 and

c umulative savings from this second savings stream equal 7.2 quads from 2013 through 2040.

When the stream of future savings from past constru ction and the stream of future savings for future

construction are combined, the annual projected savings equal 539 TBtu by 2040. Cumulative savings

from residential BECP activities reach 10 .2 quads by 2040.

16 CA and OR ha ve been excluded from this analysis due to their history of developing their own advanced state

specific residential code without direct assistance from BECP’s tools or resources. WA and FL have been partially

exclud ed due to their history of adopting their own state

- specific codes without direct assistance from BECP’s tools

or resources; however, WA and FL received technical assistance within the past 3 years to implement their state

specific codes into RES check . WA : implemented its residential code into RES check in 2013. FL: implemented its

residential state code into RES check in 2011.

17 Coughlin, K., Calculation of Full Fuel Cycle Multipliers for Energy Use in Buildings . LBNL Paper , 2012.



### 4.15

### Table 4

. 11 . BECP R e sidential Site Energy Savings (TBtu)

Electricity Natural Gas Heating Oil Total, Annual Total, Cumulative

TBtu TBtu TBtu TBtu TBtu

1992 0.10 0.26 0.02 0.4 0.4

1993 0.68 0.76 0.03 1.5 1.9

1994 0.88 1.18 0.03 2.1 3.9

1995 1.31 2.07 0.04 3.4 7.4

1996 2.09 3.13 0.05 5.3 13

1997 2.90 4.41 0.08 7.4 20

1998 3.72 5.72 0.16 10 30

1999 4.61 7.18 0.25 12 42

2000 5.62 8.82 0.32 15 56

2001 7.47 10.71 0.42 19 75

2002 11 15 0.58 27 102

2003 14 19 0.69 34 136

2004 19 23 0.84 43 179

2005 22 28 1.03 51 229

2006 25 32 1.20 58 288

2007 27 35 1.35 63 351

2008 29 37 1.45 68 419

2009 31 39 1.51 71 490

2010 32 40 1.59 73 563

2011 33 41 1.65 75 638 Annual Cumulative

2012 36 43 1.73 81 719 Post 2012 construction only

2013 41 48 1.94 91 811 10 10

2014 46 52 2.10 99 910 18 29

2015 51 56 2.28 109 1,019 28 56

2016 61 67 2.72 131 1,150 50 106

2017 71 77 3.05 151 1,300 70 176

2018 79 86 3.38 169 1,469 87 263

2019 91 102 3.82 197 1,666 116 379

2020 103 118 4.22 224 1,891 143 523

2021 114 133 4.61 251 2,142 170 693

2022 124 146 4.94 274 2,416 193 886

2023 133 158 5.25 297 2,713 216 1,102

2024 143 171 5.55 319 3,032 238 1,340

2025 151 180 5.79 337 3,369 256 1,596

2026 159 188 6.01 353 3,723 272 1,868

2027 167 197 6.22 370 4,092 289 2,157

2028 174 205 6.41 385 4,477 304 2,461

2029 181 213 6.61 401 4,878 320 2,780

2030 188 221 6.80 416 5,294 335 3,115

2031 195 228 6.97 430 5,724 349 3,464

2032 201 235 7.13 444 6,168 363 3,827

2033 208 243 7.29 457 6,625 376 4,203

2034 213 249 7.43 469 7,094 388 4,591

2035 219 255 7.57 481 7,575 400 4,991

2036 224 261 7.71 493 8,068 412 5,403

2037 230 267 7.84 504 8,572 423 5,826

2038 235 273 7.97 516 9,088 435 6,261

2039 240 279 8.09 528 9,616 447 6,708

2040 246 285 8.21 539 10,155 458 7,166



### 4.16

### Detailed estimates for primary energy, upstream supply chain

, and FFC energy savings are presented

in Table 4.12 . Energy and cost savings from the BECP residential activities are summarized in

Table 4

. 13

. Accumul ated primary energy savings from residential energy code activities over the period

of 1992

– 

### 2012 equal 1. 3 quads, with annual savings reaching 0. 15 quads in 2012 ( Table 4

. 13 ). The

amount of annual savings (0. 15 quads in 2012) from the pre

- 2012 construction wa s assumed to continue

from 2013 until 2040 (projected savings, Stream 1). Cumulative savings from this stream equal 4.2 quads

for 2013

– 

### 2040 ( Table 4

. 13 ).

Projected annual primary savings from future code activities (projected savings

, Stream 2) equal

0.7 quad in 2040. Cumulative savings from this second savings stream equal approximately 11.7 quads

for 2013

– 

### 2040. When the stream of future primary savings from past construction and the stream of

future primary savings from future code activities are combi ned (Stream 1 + Stream 2), the annual

projected primary savings equal 0.9 quad by 2040. Cumulative projected primary savings from

residential BECP activities between 2013 and 2040 equal 15.9 quads by 2040.

Combining 1. 3 quads of cumulat ive historical sav ings (1992

– 2012) with 15.9 quads of cum ulative

projected savings (2013

– 2040) brings the total BECP primary energy savings from residential code

activities to 17.2 quads for 1992

– 

### 2040 (not shown in the table).

FFC energy savings from residential energy cod e activities over the 1992

– 2012 periods equal

1. 35 quads, with annual savings reaching 155 TBtu in 2012. The amount of annual savings from the pre

2012 construction ( 155 TBtu) continue from 2013 until 2040 (projected savings, Stream 1). Cumulative

saving s from this stream (not shown in the table) equal 4.3 quads for 2013

– 2040.

Projected annual FFC savings from future code activities (projected savings

, S tream 2) equal 0.8 quad

in 2040. Cumulative F F C savings from this second savings stream equal 12.2 quads for 2013

– 2040.

When the stream of future savings from past construction and the stream of future savings from future

code activities are combined ( S tream 1 + S tream 2), the annual projected future savings equal 0. 9 quads

by 2040. Cumulative projec ted FFC savings from residential BECP activities between 2013 and 2040

reach 16.5 quads by 2040.

Combining 1

. 3 quads of cumulative historical savings with 16.5 quads of cumulative projected

savings

, brings the total BECP FFC savings from residential code activities to 17.9 quads for 1992

– 2040.

Historical and projected site energy savings were then used to calculate energy cost savings. For

1992

– 2012 savings, EIA historical electricity and natural gas prices for the residential secto r were

converted to 2012 dollars based on the GDP chain

- type price index 18 

### to calculate the annual and

cumulative cost savings.

As shown in Table 4

. 13 , annual histori cal cost savings reach $1.7 billion in 2012 and cumulative

savings between 1992 and 2012 equal $15.6 billion.

18 Federal Reserve Economic Data, Gross Domestic Product: Chain

- type Price Index (GDPCTPI), Index 2005=100,

Annual, Seasonally Adjusted. Economic Research Division, Federal Reserve Bank of St. Louis,

http: //research.stlouisfed.org/fred2



### 4.17

### Table 4

. 12 . BECP Residential Primary and Full

- Fuel

- Cycle Energy Savings (TBtu)

Primary Upstream

Supply Chain FFC

, Annual FFC

, Cumulative

1992 0.6 0.0 0.6 0.6

1993 2.7 0.1 2.8 3.5

1994 3.7 0.2 3.9 7

1995 6 0.3 6 13

1996 9 0.4 10 23

1997 13 0.6 13 36

1998 17 0.8 17 54

1999 21 1.0 22 75

2000 25 1.2 26 102

2001 32 1.5 34 136

2002 47 2.2 50 185

2003 61 2.7 63 249

2004 77 3.4 81 330

2005 92 4.0 96 425

2006 106 4.6 110 536

2007 114 5.0 119 655

2008 122 5.4 127 782

2009 127 5.6 133 915

2010 132 5.8 138 1,053 Post 2012 construction

2011 136 5.9 142 1,195 FFC

, FFC

, 2012 149 6.4 155 1,350 Annual Cumulative

2013 168 7 175 1,525 20 20

2014 184 8 192 1,717 37 57

2015 203 8 211 1,928 56 113

2016 245 10 255 2,183 100 212

2017 282 11 293 2,476 138 351

2018 315 13 328 2,803 173 523

2019 367 15 381 3,185 227 750

2020 415 17 432 3,617 277 1,027

2021 434 19 453 4,069 298 1,324

2022 473 21 494 4,563 339 1,663

2023 511 22 533 5,096 378 2,041

2024 549 24 573 5,669 418 2,459

2025 580 25 605 6,274 450 2,909

2026 584 26 610 6,884 455 3,364

2027 611 27 638 7,522 483 3,848

2028 637 28 666 8,188 511 4,358

2029 663 29 692 8,880 538 4,896

2030 689 30 720 9,600 565 5,460

2031 702 32 734 10,334 579 6,039

2032 725 33 757 11,091 602 6,642

2033 748 34 781 11,872 626 7,268

2034 767 34 801 12,674 646 7,914

2035 786 35 822 13,495 667 8,581

2036 806 36 842 14,337 687 9,268

2037 825 37 862 15,199 707 9,975

2038 844 38 882 16,081 727 10,702

2039 864 38 902 16,983 747 11,449

2040 883 39 922 17,905 767 12,216



### 4.18

### Table 4

. 13

. Summary of Energy and Cost Savings from the BECP Residential Energy Code Activities

Site Energy

Savings

,

TBtu Primary Energy

Savings

,

TBtu FFC Energy

Savings

,

TBtu Energy Cost

Savings NPV

, billion 2012$

Historical

Annual in 2012 81 149 155 1.7

Cumulative 1992

– 2012 719 1,293 1,350 15.6

Projected, Stream 1

Annual in 2040 81 149 155 0.3

Cumulative 2013

– 2040 2,270 4,160 4,339 23.8

Projected, Stream 2

Annual in 2040 458 734 767 2.0

Cumulative 2013

– 2040 7,166 11,700 12,216 55.8

BECP Total

Annual in 2040 539 883 922 2.3

Cumulative 1992

– 2040 10,155 17,153 17,905 95.2



### For projected savings, the NIA PLUS model was used to calculate the NPV of the future cost savings.

AEO 2013 reference case prices were converted to 2012 dollars and a 7% discount rate was applied. The

NPV of annual projected savings in 2040 for Stream 1 equals $0.3 billion. The NPV of cumulati ve cost

saving for Stream 1 equals $2 3 .8 billion. The NPV of annual projected savings in 2040 for Stream 2

equals almost $2 billion. The NPV of cumulative cost savings for Stream 2 equals $55.8 billion.

Combined, the NPV of projected energy cost savings equals almost $80 billion. Total accumulated cost

savings to consumers from the BECP residential energy code activities for 1992

– 2040 equal $95.2 billion.

Emissions savings were estimated for CO 2 

### , NO

x 

### , Hg, N 2 

### O, CH 4 

### , and SO 2



### . Detailed annual results fo r

the emissions savings are included in Table 4

. 14

. A s ummary of historical and projected emissions

savings is presented in Table 4

. 15

.

The c umulative emissions reduction between 1992 and 2040 include s 1. 3 billion metric tons (Mt) of

CO 2 

### , 1.8 million tons of NO

x 

### , 2.8 tons of Hg

, and 1. 1 million tons of SO 2



### .

The value of the CO 2 

### emission s reduction is $ 0.7 to 2.4 bi llion (2012 $) 

### based on 2013 domestic social

carbon values and a 5% discount rate

, or about 10.6 billion based on global SCC, while NO

x 

### savings

contribute at least another $ 0. 4 billion ( a t $ 4 68 per ton in 2012$ ) . Energy cost savings presented in

Table 4

. 13

, combined with monetized emission s savings presented in Table 4

. 16

, capture consumer

benefits to the nation from the residential BECP activities. Combined consumer benefits from residential

BECP ac tivities are shown in Table 4

. 17

. Depending on the price of CO 2 

### and NO

x 

### , the NPV of overall

consumer benefits can range between $ 1 06 and 235 billion ( 2012$ ) . Out of that total, the energy cost

savings constitute $ 9 5 billion ( 2012$ )

.

4.19

### Table 4

. 14

. Annual Emissions Savings from the BECP Residential Activities , Full

- Fuel

- Cycle

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt ton kt mm t CO 2 eq kt mmt CO 2 eq kt

1992 0.0 0.1 0.00 0.00 0.00 0.26 0.0 0.0

1993 0.2 0.4 0.00 0.00 0.00 1.00 0.0 0.2

1994 0.3 0.6 0.00 0.00 0.00 1.43 0.0 0.3

1995 0.4 0.9 0.00 0.00 0.00 2.36 0.1 0.5

1996 0.7 1.5 0.00 0.01 0.00 3.64 0.1 0.7

1997 0.9 2.1 0.00 0.01 0.00 5.08 0.1 1.0

1998 1.2 2.7 0.00 0.01 0.00 7 0.2 1.3

1999 1.5 3.3 0.00 0.01 0.00 8 0.2 1.6

2000 1.8 4.1 0.00 0.02 0.01 10 0.3 2.0

2001 2.3 5.3 0.00 0.02 0.01 13 0.3 2.6

2002 3.4 7.7 0.01 0.03 0.01 18 0.5 3.9

2003 4.4 9.9 0.01 0.04 0.01 23 0.6 5.1

2004 5.6 12.7 0.01 0.06 0.02 29 0.7 6.6

2005 6.6 15.0 0.01 0.07 0.02 35 0.9 7.8

2006 7.6 17.3 0.01 0.08 0.02 40 1.0 9.0

2007 8.2 18.6 0.01 0.08 0.02 43 1.1 9.6

2008 8.8 19.9 0.02 0.09 0.03 46 1.2 10.3

2009 9.2 20.8 0.02 0.09 0.03 48 1.2 10.8

2010 9.5 21.6 0.02 0.10 0.03 50 1.3 11.2

2011 9.8 22.3 0.02 0.10 0.03 51 1.3 11.5

2012 10.8 24.5 0.02 0.10 0.03 55 1.4 12.7

2013 12.2 27.5 0.02 0.12 0.03 60 1.5 14.5

2014 13.3 29.8 0.02 0.12 0.04 65 1.6 15.8

2015 14.7 32.9 0.02 0.13 0.04 72 1.8 17.2

2016 17.8 39.8 0.03 0.16 0.05 86 2.2 20.9

2017 20.4 45.7 0.03 0.18 0.05 99 2.5 24.0

2018 22.8 50.9 0.04 0.21 0.06 110 2.7 26.8

2019 26.6 59.2 0.05 0.24 0.07 128 3.2 31.0

2020 30.0 66.9 0.05 0.27 0.08 145 3.6 34.9

2021 30.4 34.9 0.06 0.30 0.09 162 4.0 41.8

2022 33.2 37.8 0.06 0.33 0.10 176 4.4 45.5

2023 35.8 40.8 0.07 0.36 0.11 189 4.7 49.0

2024 38.4 43.6 0.07 0.38 0.11 203 5.1 52.5

2025 40.6 45.8 0.08 0.41 0.12 213 5.3 55.6

2026 44.4 52.6 0.08 0.43 0.13 224 5.6 25.3

2027 46.5 54.9 0.08 0.45 0.13 234 5.8 26.5

2028 48.5 57.1 0.09 0.46 0.14 244 6.1 27.7

2029 50.5 59.3 0.09 0.48 0.14 253 6.3 28.8

2030 52.5 61.6 0.09 0.50 0.15 264 6.6 30.0

2031 58.9 68.4 0.14 0.52 0.15 273 6.8 40.2

2032 60.8 70.7 0.15 0.53 0.16 282 7.0 41.6

2033 62.8 73.0 0.15 0.55 0.16 291 7.3 42.9

2034 64.4 74.7 0.16 0.56 0.17 298 7.4 44.0

2035 66.0 76.4 0.16 0.58 0.17 305 7.6 45.1

2036 67.6 77.5 0.16 0.59 0.18 312 7.8 46.3

2037 69.3 79.3 0.17 0.60 0.18 319 8.0 47.4

2038 70.9 81.1 0.17 0.62 0.18 327 8.2 48.5

2039 72.5 82.8 0.18 0.63 0.19 334 8.4 49.7

2040 74.1 84.6 0.18 0.64 0.19 342 8.5 50.8

Total 1,339 1,821 2.8 12.3 3.66 6,497 162 1,133



### 4.20

### Table 4

. 15

. Summary of Emissions Savings from the BECP R esidential E nergy C ode A ctivities

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt ton kt mm t CO 2 eq k t mmt CO 2 eq kt

Historical

Annual in 2012 11 24 0.0 0.1 0.0 55 1.4 13

Cumulative 1992

- 2012 93 211 0.2 0.9 0.3 490 12 109

Projected, Stream 1

Annual in 2040 11 24 0.0 0.1 0.0 55 1.4 13

Cumulative 2013

- 2040 301 685 0.5 2.9 0.9 1,529 38 355

Projected, Stream 2

Annual in 2040 63 60 0.2 0.5 0.2 287 7.2 38

Cumulative 2013

- 2040 945 925 2.1 8.5 2.5 4,479 112 669

BECP T otal

Annual in 2040 74 85 0.2 0.6 0.2 342 9 51

Cumulative 1992

- 2040 1,339 1,821 2.8 12.3 3.7 6,497 162 1,133



### Table 4

. 16 . National Cumulative Benefits of the BECP Residential Activities, 1992

– 2040

Energy Savings

Primary quads 17.2

Upstream quads 0.8

Full

- Fuel

- Cycle (total) quads 17.9

Economic Impacts

Historical Energy Cost Savings billion 2012$ 15

Projected Energy Cost Savings billion 2012$ 80

Total Energy Cost Savings billion 2012$ 95

Emissions Savings (physical)

Primary

CO 2 mmt 1,263

NO

x kt 744

Hg t on 2.8

N 2 O kt 11.8

N 2 O mmt CO 2 eq 3.5

CH 4 kt 84

CH 4 mmt CO 2 eq 2.1

SO 2 kt 1,123

Upstream

CO 2 mmt 76

NO

x kt 1,077

Hg t on 0.0

N 2 O kt 0.5

N 2 O mmt CO 2 eq 0.1

CH 4 kt 6,413

CH 4 mmt CO 2 eq 160

SO 2 kt 10

Full

- Fuel

- Cycle (total)

CO 2 mmt 1,339

NO

x kt 1,821

Hg t on 2.8

N 2 O kt 12.3

N 2 O mmt CO 2 eq 3.7

CH 4 kt 6,497

CH 4 mmt CO 2 eq 162

SO 2 kt 1,133



### 4.21

### Table 4

. 16

. (contd)

Emissions Savings (monetized)

Primary

CO 2 (global)

5% discount rate, average billion 2012$ 10.0

3% discount rate, average billion 2012$ 41.9

2.5% discount rate, average billion 2012$ 66.2

3% discount rate, 95th %ile billion 2012$ 128.0

CO 2 (domestic)

5% discount rate, average billion 2012$ 0.7 to 2.3

3% discount rate, average billion 2012$ 2.9 to 9.6

2.5% discount rate, average billion 2012$ 4.6 to 15.2

3% discount rate, 95th %ile billion 2012$ 9 to 29.4

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.2

At 2,639 2012$/ton billion 2012$ 1.1

At 4,809 2012$/ton billion 2012$ 2.0

Upstream

CO 2 (global)

5% discount rate, average billion 2012$ 0.6

3% discount rate, average billion 2012$ 2.5

2.5% discount rate, average billion 2012$ 4.0

3% discount rate, 95th %ile billion 2012$ 7.7

CO 2 (domestic)

5% discount rate, average billion 2012$ 0 to 0.1

3% discount rate, average billion 2012$ 0.2 to 0.6

2.5% discount rate, average billion 2012$ 0.3 to 0.9

3% discount rate, 95th %ile billion 2012$ 0.5 to 1.8

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.2

At 2,639 2012$/ton billion 2012$ 1.2

At 4,809 2012$/ton billion 2012$ 2.1

Full

- Fuel

- Cycle (total)

CO 2 (global)

5% discount rate, average billion 2012$ 10.6

3% discount rate, average billion 2012$ 44.4

2.5% discount rate, average billion 2012$ 70.2

3% discount rate, 95th %ile billion 2012$ 135.7

CO 2 (domestic)

5% discount rate, average billion 2012$ 0.7 to 2.4

3% discount rate, average billion 2012$ 3.1 to 10.2

2.5% discount rate, average billion 2012$ 4.9 to 16.1

3% discount rate, 95th %ile billion 2012$ 9.5 to 31.2

NO

x (7% discount rate)

At 468 2012$/ton billion 2012$ 0.4

At 2,639 2012$/ton billion 2012$ 2.3

At 4,809 2012$/ton billion 2012$ 4.1



### 4.22

### Table 4

. 17 . Cumulative Consumer Benefits from BECP Residential Energy Code Activities

NPV

Consumer Energy Cost Savings billion 2012$ 95

Consumer and Emissions Value

Consumers + CO 2 (1st) + NO

x (Low) billion 2012$ 106

Consumers + CO 2 (2nd) + NO

x (Med) billion 2012$ 142

Consumers + CO 2 (3rd) + NO

x (Med) billion 2012$ 168

Consumers + CO 2 (4th) + NO

x (High) billion 2012$ 235



### Each of the consumer and e missions v alue estimates above represents a combination of consumer

energy cost savings and correspondin g scenarios for monetized reduction of CO 2 

### and NO

x 

### . For example,

Consumers + CO 2 

### (1st) + NO

x 

### (Low) means that savings from the first scenario of CO 2 

### (5% discount rate,

average , global SCC ) were combined with savings from the low NO

x 

### cost scenario (at $468 per ton in

2012$) and added to th e consumer energy cost savings.

4.23

# 5.0 National Energy, Economic

, and Environmental Benefits

T his analysis defines DOE BECP impact as improving energy efficiency of the national building

model codes and standards, accelerating the adoption of the most recent code (or equivalent), and

increasing compliance with the code provisions.

BECP historical and projected energy savings are presented in Table 5

. 1 . For the historical portion of

the P rogram savings, cumulative primary energy savings between 1992 and 2012 total 4quads , with the

annual energy savings being approximately 0.5 quads in 2012. For the projected program savings,

accumulated primary energy savings from 2013 through 2040 reach 40.1 quads , with the annual savings

of 2. 2 quads in 2040. The cumulativ e energy savings attributed from the Program total nearly 46 quads of

FFC energy , or 44 quads of primary energy. The Program may save consumers up to $230 billion on

their utility bills by 2040

. Table 5

. 2 provides the breakdown of energy and cost savings between

commercial and residential activities.

Table 5

. 1

. Summary of Energy and Cost Savings from BECP Energy Code Activities

Site Energy

Savings

, (a)

quads Primary Energy

Savings

, (b)

quads FFC Energy

Savings

, (c)

quads Energy Cost

Savings

NPV,

billion 2012$

Historical

Annual in 2012 0.2 0.5 0.5 5.0

Cumulative 1992

- 2012 2.0 4.0 4.2 44.6

Projected, 2013

- 2040 Construction

Annual in 2040 1.2 2.2 2.3 5

. 2

Cumulative 2013

- 2040 22.0 40.1 41.6 1 8 5 .7

BECP Total

Annual in 2040 1.2 2.2 2.3 5.2

Cumulative 1992

- 2040 24.0 44.1 45.7 230.3

(a) Site energy savings represent direct energy savings to the consumer. Site energy savings multiplied by the energy price

represent energy cost savings to the consumer.

(b) Following the analysis methodology used by DOE’s Appliance and Equipment Standards Program, site energy savings were

first converted to the source energy terms, which includes energy used in generation, transmission, and distribution (primary

energy).

(c ) Energy used further “upstream” in the mining, processing, and transportation of f uels cycle was calculated using the NIA

PLUS model and added to the primary energy savings to yield full

- fuel

- cycle ( FFC ) energy savings

.



### 5.1

### Table 5

. 2

. Breakdown of BECP Energy and Cost Savings between Commercial and Residential

Activities ( quads )

Site Energy

Savings

, (a)

quads Primary Energy

Savings, (b)

quads FFC Energy

Savings, (c)

quads Energy Cost

Savings

NPV,

billion 2012$

Historical

Annual in 2012

Commercial 0.2 0.3 0.3 3.3

Residential 0.1 0.1 0.2 1.7

Cumulative 1992

- 2012

Commercial 1.2 2.8 2.8 29.0

Residential 0.7 1.3 1.4 15.6

Projected

Annual in 2040

Commercial 0.7 1.3 1.3 2.9

Residential 0.5 0.9 0.9 2.3

Cumulative 2013

- 2040

Commercial 12.6 24.2 25.0 106.1

Residential 9.4 15.9 16.6 79.6

BECP Total

Annual in 2040

Commercial 0.7 1.3 1.3 2.9

Residential 0.5 0.9 0.9 2.3

Cumulative 1992

- 2040

Commercial 13.8 27.0 27.8 135.1

Residential 10.2 17.2 17.9 95.2

(a) Site energy savings represent direct energy savings to the consumer. Site energy savings multiplied by the energy price

represent energy cost savings to the consumer.

(b) Following the analysis methodology used by DOE’s Appliance and Equipment Standards Program, site energy savings were

first converted to the source energy terms, which includes energy used in generation, transmission, and distribution (primary

energy).

(c ) Energy used further “u pstream” in the mining, processing, and transportation of fuels cycle was calculated using the NIA

PLUS model and added to the primary energy savings to yield full

- fuel

- cycle ( FFC ) energy savings

.



### Detailed annual primary energy savings and FFC energy savi ngs are presented in Table 5

. 3 and

Table 5

. 4 , respectively.

5.2

### Table 5

. 3

. BECP Historical and Projected Primary Energy Savings ( quads )

Annual

Primary Cumulative Primary

quads quads

1992 0.00 0.00

1993 0.01 0.01

1994 0.01 0.02

1995 0.01 0.03

1996 0.02 0.05

1997 0.04 0.09

1998 0.05 0.14

1999 0.06 0.20

2000 0.08 0.28

2001 0.11 0.39

2002 0.15 0.54

2003 0.19 0.73

2004 0.23 0.96

2005 0.27 1.23

2006 0.31 1.54

2007 0.35 1.88

2008 0.38 2.26

2009 0.41 2.67

2010 0.43 3.11

2011 0.45 3.56 Annual Cumulative

2012 0.48 4.04 Post 2012 construction only

2013 0.53 4.58 0.05 0.05

2014 0.57 5.15 0.09 0.13

2015 0.62 5.76 0.13 0.27

2016 0.71 6.47 0.23 0.49

2017 0.79 7.27 0.31 0.80

2018 0.87 8.14 0.39 1.19

2019 0.99 9.13 0.50 1.69

2020 1.10 10.22 0.61 2.30

2021 1.13 11.35 0.64 2.94

2022 1.22 12.57 0.73 3.68

2023 1.31 13.87 0.82 4.50

2024 1.39 15.27 0.91 5.41

2025 1.47 16.74 0.99 6.39

2026 1.44 18.18 0.96 7.35

2027 1.51 19.69 1.02 8.38

2028 1.57 21.26 1.09 9.46

2029 1.64 22.90 1.15 10.61

2030 1.70 24.59 1.21 11.83

2031 1.71 26.30 1.23 13.05

2032 1.77 28.07 1.28 14.34

2033 1.83 29.90 1.34 15.68

2034 1.88 31.78 1.40 17.08

2035 1.93 33.72 1.45 18.53

2036 1.99 35.70 1.50 20.03

2037 2.04 37.74 1.55 21.58

2038 2.08 39.82 1.60 23.18

2039 2.13 41.95 1.65 24.83

2040 2.18 44.13 1.69 26.52



### 5.3

### Table 5

. 4

. BEC P Historical and Projected Full

- Fue l

- Cycle Energy Savings ( quads )

Annual FFC Cumulative FFC

quads quads

1992 0.0 0.0

1993 0.0 0.0

1994 0.0 0.0

1995 0.0 0.0

1996 0.0 0.1

1997 0.0 0.1

1998 0.1 0.1

1999 0.1 0.2

2000 0.1 0.3

2001 0.1 0.4

2002 0.2 0.6

2003 0.2 0.8

2004 0.2 1.0

2005 0.3 1.3

2006 0.3 1.6

2007 0.4 1.9

2008 0.4 2.3

2009 0.4 2.8

2010 0.4 3.2

2011 0.5 3.7 Total, Annual Total, Cumulative

2012 0.5 4.2 Post 2012 construction only

2013 0.5 4.7 0.0 0.0

2014 0.6 5.3 0.1 0.1

2015 0.6 6.0 0.1 0.3

2016 0.7 6.7 0.2 0.5

2017 0.8 7.5 0.3 0.8

2018 0.9 8.4 0.4 1.2

2019 1.0 9.4 0.5 1.7

2020 1.1 10.6 0.6 2.4

2021 1.2 11.7 0.7 3.0

2022 1.3 13.0 0.8 3.8

2023 1.4 14.3 0.9 4.7

2024 1.4 15.8 0.9 5.6

2025 1.5 17.3 1.0 6.6

2026 1.5 18.8 1.0 7.6

2027 1.6 20.4 1.1 8.7

2028 1.6 22.0 1.1 9.8

2029 1.7 23.7 1.2 11.0

2030 1.8 25.5 1.3 12.3

2031 1.8 27.2 1.3 13.5

2032 1.8 29.1 1.3 14.9

2033 1.9 31.0 1.4 16.3

2034 2.0 32.9 1.5 17.7

2035 2.0 34.9 1.5 19.2

2036 2.1 37.0 1.6 20.8

2037 2.1 39.1 1.6 22.4

2038 2.2 41.3 1.7 24.1

2039 2.2 43.5 1.7 25.8

2040 2.3 45.7 1.8 27.5



### A s ummary of emissions savings from BECP e nergy code activities calculated based on the FFC

analysis is presented in Table 5

. 5

.

5.4

### Table 5

. 5

. Summary of E missions Savings from BECP E nergy C ode A ctivities

CO 2 (mmt) NO

x (kt) Hg

( ton ) N 2 O

(kt) N 2 O

(mmt

CO 2 eq) CH 4 (kt) CH 4 (mmt

CO 2 eq) SO 2 (kt)

Historical

Annual in 2012 36 80 0.1 0.4 0.1 159 4 46

Cumulative 1992

– 2012 300 664 0.6 3.3 1.0 1,347 34 386

Projected, 2013

- 2040 Construction

Annual in 2040 185 194 0.4 1.8 0.5 796 20 116

Cumulative 2013

– 2040 3,178 3,855 6.9 32.1 9.6 14,095 352 3,489

BECP Total

Annual in 2040 185 194 0.4 1.8 0.5 796 20 116

Cumulative 1992

– 2040 3,478 4,519 7.6 35.4 10.5 15,441 386 3,875



### Cumulative emissions reduction s between 1992 and 2040 include almost 3.5 bill ion metric tons (Mt)

of CO 2 

### , 4.5 million tons of NO

x 

### , 7.6 tons of Hg

, and 3.9 million tons of SO 2



### .

The value of the CO 2 

### emission reductions is $ 2

. 0 to $ 6.4 billion ( 2012 $) based on 2013 domestic

social carbon values and a 5% discount rate, or $28 billion based on 2013 global SCC, while NO

x 

### savings

contribute at least another $ 1.1 b illion of savings ( at $ 468 per ton in 2012$ ) . Energy cost savings

presented in Table 5.1

, combined with physical and monetized emission savings presented in Table 5.5

, captur e consumer benefits to the nation from the BECP energy code activities.

Combined consumer benefits from BECP activities are shown in Table 5

. 6 and Table 5

. 7

. Depending

on the price of CO 2 

### and NO

x 

### , the NPV of overall consumer benefits can range between $ 259 and almost

$ 594 billion ( 2012$ ) . Out of that total, the energy cost savings constitute $ 23 0 billion ( 2012$ )

.

Table 5

. 6

. National Benefits from BECP Energy Code Activities, 1992

– 2040

Cumulative Results Units Commercial (1992

- 2040) Residential (1992

- 2040) Total BECP

(1992

- 2040)

Energy Savings

Site quads 13.8 10.2 24.0

Primary quads 27.0 17.2 44.1

Full

- Fuel

- Cycle (total) quads 27.8 17.9 45.7

Economic Impacts

Energy Cost Savings billion 2012$ 135 95 230

Emissions Savings (physical)

Full

- Fuel

- Cycle (total)

CO 2 m mt 2,138 1,339 3,478

NO

x kt 2,699 1,821 4,519

Hg t on 4.8 2.8 8

N 2 O kt 23.1 12.3 35

N 2 O mmt CO 2 eq 6.9 3.7 11

CH 4 kt 8,945 6,497 15,441

CH 4 mmt CO 2 eq 224 162 386

SO 2 kt 2,742 1,133 3,875



### 5.5

### Table 5

. 6

. (contd)

Cumulative Results Units Commercial (1992

- 2040) Residential (1992

- 2040) Total

BECP

(1992

- 2040)

Emissions Savings (monetized)

Full

- Fuel

- Cycle (total)

CO 2 (global)

5% d iscount r ate , average billion 2012$ 17.3 10.6 28.0

3% d iscount r ate , average billion 2012$ 71.3 44.4 115.7

2.5% d iscount r ate , average billion 2012$ 112.6 70.2 182.8

3% d iscount r ate , 95th %ile billion 2012$ 216.8 135.7 352.6

CO 2 (domestic)

5% d iscount r ate , average billion 2012$ 1.2 to 4 0.7 to 2.4 2 to 6.4

3% d iscount r ate , average billion 2012$ 5 to 16.4 3.1 to 10.2 8.1 to 26.6

2.5% d iscount r ate , average billion 2012$ 7.9 to 25.9 4.9 to 16.1 12.8 to 42

3% d iscount r ate , 95th %ile billion 2012$ 15.2 to 49.9 9.5 to 31.2 24.7 to 81.1

NO

x (7% d iscount r ate )

At 468 2012$/ton billion 2012$ 0.7 0.4 1.1

At 2,639 2012$/ton billion 2012$ 3.8 2.3 6.0

At 4,809 2012$/ton billion 2012$ 6.9 4.1 11.0



### Each one of the c onsumer and e missions v alue estimates shown in Table 5

. 7 represent a combination

of consumer energy cost savings, and corresponding scenarios for monetized reduction of CO 2 and NOx

. 

### For example, Consumers + CO 2 

### (1st) + NO

x 

### (Low) means that savings from the first scenario of CO 2 

### ( 5%

discount rate, average , global SCC ) were combined with savings from the low NO

x 

### cost scenario ( at $ 468

per ton in 2012$) and added to the consumer energy cost savings.

Table 5

. 7

. Consumer Cumulative Benefits of the BECP Activities, 1992

– 2040

Cumulative Results Com mercial

(1992

– 2040) Residential

(1992

– 2040) Total BECP

(1992

– 2040)

NPV

Consumer Energy Cost Savings billion 2012$ 135 95 230

Consumer and Emissions Value

Consumers + CO 2 (1st) + NO

x (Low) billion 2012$ 153 106 259

Consumers + CO 2 (2nd) + NO

x (Med) billion 2012$ 210 142 352

Consumers + CO 2 (3rd) + NO

x (Med) billion 2012$ 251 168 419

Consumers + CO 2 (4th) + NO

x (High) billion 2012$ 359 235 594



### The estimated cumulative benefits from the Program through 2040 are significant. The cumulative

energy savings attributed from the Program total nearly 46 quads of FFC energy, or 44 quads of primary

energy, equivalent to almost an entire year’s worth of primary energy consumption from the U.S.

residential and commercial sectors at current consumption rates. The Program may save consumers up to

$230 billion on th eir utility bills by 2040 . Annual carbon savings reach 36 million tons at the end of 2012

and the cumulative savings by 2040 are estimated at 3, 478 million tons.

5.6

### Finally, BECP’s cumulative FFC savings of emissions of CO 2 

### , N 2 

### O, and CH 4 

### in CO 2



### - equivalents in

Table ES. 2 are almost 3.9 billion metric tons. That is equivalent to three

- quarters of all energy

- related

emissions of the United States in 2012. These benefits do not count the reduction of other energy

- related

air pollutants shown in Table ES. 2 , or billions of dollars in saved future investment in facilities to supply

the natural gas, electricity, and fuel oil to the residential and commercial sectors that would not be needed.

BECP efforts clearly make a difference to the economy and citizens of the United States.

5.7

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Technology Division, San Francisco, California.

Energy Information Administration (EIA). 2007. Residential Energy Consumption Survey 2005

. Detailed tables, accessed at: http://www.eia.gov/consumption/residential/data/2005/, file alltables[1].pdf

.

Energy Policy and Conservation Act. 1975. (EPAct 1975) Public La w 94

- 163 (PL

- 94

- 163).

December 22, 1975.

GDS Associates (GDS). 2012. New Hampshire Energy Code Compliance Roadmap

– Volume 2,

Achieving 90% Compliance with the 2009 International Energy Conservation Code . GDS Associates,

Inc., Manchester, New Hampshire

.

GDS Associates and ENTECH Engineering. 2000. Survey of Commercial New Construction Activities in

New Hampshire. Provided to the New Hampshire Commercial Construction Study Group. Man chester,

New Hampshire.

Georgia Environmental Finance Authority (GEFA). 2012. Building Department Pilot Study: Guidance

on Effective Enforcement of Georgia’s Energy Code . Completed by the Building Codes Assistance

Project, the Southeast Energy Efficiency Alliance, and Southface.

7.2

### Hadley DL and MA Halverson. 1993. Energy Conservation Potential of the U.S. Department of Energy

Interim Commercial Buildings Standards . PNL

- 7967, Pacific Northwest National Laboratory, Richland,

Washington.

Harper B. 2012. T he New York Energy Code Compliance Study. Prepared by the Vermont Energy

Investment Corporation for The New York State Energy Research and Development Authority,

Burlington, Vermont.

International Code Council (ICC). 2012. International Energy Conservat ion Code 2012 . Country Club

Hills, Illinois.

Kennedy M. 1997. Energy Consequences of Non

- Compliance with the 1994 Washington Nonresidential

Energy Code. Washington State University, Richland, Washington.

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Compliance . Report #E12

- 251, Cadmus Group, Inc. for Northwest Energy Efficiency Alliance, Portland,

Oregon.

Lee A, B Standen, S Donohue, M Desu, and A Wood. 2013. Idaho Residential Energy Code

Compliance. Report #E12

- 250, Cadmus Group, Inc. for Northwest Energy Efficiency Alliance, Portland,

Oregon.

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Buildings

– Technical Support Document. PNNL

- 18806, Pacific Northwest National Laboratory,

Richland, Washington.

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– Volume I. In

- Field Residential Energy Code Compliance

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Inspection Training . Britt/Makela Group, LLC.

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. Newport Partners LLC for Maryland Energy Administration.

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. Southwest Energy

Efficiency Project, Boulder, Colorado.

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Residential and Non

- Residential Buildings in Illinois Against the 2009 International Energy Conservation

Code ”

. Association of Professional Energy Consultants, Inc. for Midwest Energy Efficiency Alliance,

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Publicly

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7.3

### Richman EE, DB Belzer, and DW Winiarski. 2005. Texas State Building Energy Code: Analysis of

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. Government Printing Office, Washington

, D.C.

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.

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.

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. NMR Group, Inc. for Vermont Public Service Depar tment, Somerville,

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Alberta, Canada.

7.4

# Appendix

– Energy Savings Potential from More Rapid Code Adoption

and Compliance, 2013

– 2040

# Appendix

Energy Savings Potential from More Rapid Code Adoption

and Compliance , 2013

– 2040

This appendix contains an estimate of the potential energy savings for residential and commercial

code activities assuming immediate adoption and full compliance for 2013

– 2040. The objective of this

analysis wa s to estimate energy, cost , and emissions that could be saved on post

- 2013 construction under

ideal adoption and compliance conditions. We model ed this situation with an “immediate adoption ”

scenario, which also include d 100% immediate compliance. The stream of future savings in this scenario

correspond ed to S tream 2 in the projected savings presented in the results section of th e main report

(Section 5, Table 5

. 1 )

.

The methodology for estimating the potential is the same as outlined in Section 2.0 of the report in the

sense that we compare d two scenarios. Potential savings we re calculated as a difference between energy

consumption in a base case scenario and energy consumption in the immediate adoption scenario.

Separate sets of adoption and compliance assumptions were developed to characterize the base case and

immediate ado ption scenarios.

The common starting point for adoption for both scenarios wa s the most recent energy code version

adopted in each state (explicitly or implicitly) in 2013. In the base case it wa s assumed that no further

code versions were adopted therea fter.

The immediate adoption scenario assume d that for all code versions starting with IECC 2012/90.1

- 2007, the adoption occur red in the year following the publication year of the c ode (code version + 1 year

lag)

. Thus, the IECC 2012 code would be adopte d in 2013. This means that the ideal “immediate”

adoption path wa s compared against the adoption status at the beginning of the analysis period. The c ode

adoption assumptions for commercial and residential energy codes are summarized in Table A

. 1 and

Table A

. 2

.

In the immediate adoption scenario, initial c ompliance was set at 100% for all states in the year of

adoption , including the states with no statewide code and home

- rule states. This wa s consistent with the

context of this analysis where the ideal compliance path wa s compared with the compliance status at the

beginning o f the analysis period.

In the base case scenario, compliance with the adopted code wa s assumed to be lower/delayed. In the

base case

, the same state classifications were used for commercial and residential energy codes as shown

in Table 3

. 7 of Section 3 and Table 4

. 5 of Section 4. As a result, base case assumptions for initial

c ompliance were set to equal compliance rates for the “without BECP” scenario outlined in Table 3

. 10

and Table 3

. 11 of Section 3, and Table 4

. 8 and Table 4

. 9 of Section 4.

California, Florida, Oregon, and Washington were included in this analysis because energy savings

potential wa s attribution

- free and represent ed total savings available from code activities between 2013

and 2040

.

A.1

### Table A

. 1 . Base Case and Immediate Adoption Scenario, Commercial Energy Codes

Starting Point Base case Immediate Adoption *

Code in Effect in 2013 90.1

-

2010 * 90.1

-

2013 * 90.1

-

2016 * 90.1

-

2019 * 90.1

-

2022 * 90.1

-

2025 *

Alabama 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Alaska 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

Arizona 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

Arkansas 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

California 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Colorado 90.1

- 2004 No Change 2013 2016 2019 2022 2025 2028

Connecticut 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Delaware 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

District of Columbia 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Florida 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Georgia 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Hawaii 90.1

- 2004 No Change 2013 2016 2019 2022 2025 2028

Idaho 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Illinois 90.1

- 2010 No Change 2013 2016 2019 2022 2025 2028

Indiana 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Iowa 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Kansas 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

Kentucky 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Louisiana 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Maine 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Maryland 90.1

- 2010 No Change 2012 2016 2019 2022 2025 2028

Massachusetts 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Michigan 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Minnesota 90.1

- 2004 No Change 2013 2016 2019 2022 2025 2028

Mississippi 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

Missouri 90.1

- 2010 No Change 2013 2016 2019 2022 2025 2028

Montana 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Nebraska 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Nevada 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

New Hampshire 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

New Jersey 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

New Mexico 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

New York 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

North Carolina 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

North Dakota 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Ohio 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Oklahoma 90.1

- 2004 No Change 2013 2016 2019 2022 2025 2028

Oregon 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Pennsylvania 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Rhode Island 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

South Carolina 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

South Dakota 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

Tennessee 90.1

- 2004 No Change 2013 2016 2019 2022 2025 2028

Texas 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Utah 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Vermont 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Virginia 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Washington 90.1

- 2010 No Change 2013 2016 2019 2022 2025 2028

West Virginia 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Wisconsin 90.1

- 2007 No Change 2013 2016 2019 2022 2025 2028

Wyoming 90.1

- 1999/2001 No Change 2013 2016 2019 2022 2025 2028

* Because states typically adopt the IECC and then by reference in the IECC automatically get Standard 90.1, the adoption assum ption tables

show the adopted versions of the IECC for residential and reference versions of Standard 90.1 for commercial

. A o ne y ear lag is added to the

IECC code version year. Thus Standard 90.1

- 2010 would be adopted in 2013.



### A.2

### Table A

. 2

. Base Case and Immediate Adoption Scenario, Residential Energy Codes

Starting Point Base case Immediate Adoption

Code in Effect in

2013 IECC

2012 IECC

2015 IECC

2018 IECC

2021 IECC

2024

Alabama IECC 2009 No Change 2013 2016 2019 2022 2025

Alaska IECC 2003 No Change 2013 2016 2019 2022 2025

Arizona IECC 2003 No Change 2013 2016 2019 2022 2025

Arkansas IECC 2003 No Change 2013 2016 2019 2022 2025

California IECC 2009 No Change 2013 2016 2019 2022 2025

Colorado IECC 2006 No Change 2013 2016 2019 2022 2025

Connecticut IECC 2009 No Change 2013 2016 2019 2022 2025

Delaware IECC 2009 No Change 2013 2016 2019 2022 2025

District of Columbia IECC 2009 No Change 2013 2016 2019 2022 2025

Florida IECC 2009 No Change 2013 2016 2019 2022 2025

Georgia IECC 2009 No Change 2013 2016 2019 2022 2025

Hawaii IECC 2006 No Change 2013 2016 2019 2022 2025

Idaho IECC 2009 No Change 2013 2016 2019 2022 2025

Illinois IECC 2012 No Change 2013 2016 2019 2022 2025

Indiana IECC 2009 No Change 2013 2016 2019 2022 2025

Iowa IECC 2009 No Change 2013 2016 2019 2022 2025

Kansas IECC 2003 No Change 2013 2016 2019 2022 2025

Kentucky IECC 2009 No Change 2013 2016 2019 2022 2025

Louisiana IECC 2006 No Change 2013 2016 2019 2022 2025

Maine IECC 2009 No Change 2013 2016 2019 2022 2025

Maryland IECC 2012 No Change 2012 2016 2019 2022 2025

Massachusetts IECC 2009 No Change 2013 2016 2019 2022 2025

Michigan IECC 2009 No Change 2013 2016 2019 2022 2025

Minnesota IECC 2006 No Change 2013 2016 2019 2022 2025

Mississippi IECC 2003 No Change 2013 2016 2019 2022 2025

Missouri IECC 2003 No Change 2013 2016 2019 2022 2025

Montana IECC 2009 No Change 2013 2016 2019 2022 2025

Nebraska IECC 2009 No Change 2013 2016 2019 2022 2025

Nevada IECC 2009 No Change 2013 2016 2019 2022 2025

New Hampshire IECC 2009 No Change 2013 2016 2019 2022 2025

New Jersey IECC 2009 No Change 2013 2016 2019 2022 2025

New Mexico IECC 2009 No Change 2013 2016 2019 2022 2025

New York IECC 2009 No Change 2013 2016 2019 2022 2025

North Carolina IECC 2009 No Change 2013 2016 2019 2022 2025

North Dakota IECC 2006 No Change 2013 2016 2019 2022 2025

Ohio IECC 2009 No Change 2013 2016 2019 2022 2025

Oklahoma IECC 2009 No Change 2013 2016 2019 2022 2025

Oregon IECC 2009 No Change 2013 2016 2019 2022 2025

Pennsylvania IECC 2009 No Change 2013 2016 2019 2022 2025

Rhode Island IECC 2009 No Change 2013 2016 2019 2022 2025

South Carolina IECC 2009 No Change 2013 2016 2019 2022 2025

South Dakota IECC 2003 No Change 2013 2016 2019 2022 2025

Tennessee IECC 2006 No Change 2013 2016 2019 2022 2025

Texas IECC 2009 No Change 2013 2016 2019 2022 2025

Utah IECC 2006 No Change 2013 2016 2019 2022 2025

Vermont IECC 2009 No Change 2013 2016 2019 2022 2025

Virginia IECC 2009 No Change 2013 2016 2019 2022 2025

Washington IECC 2012 No Change 2013 2016 2019 2022 2025

West Virginia IECC 2009 No Change 2013 2016 2019 2022 2025

Wisconsin IECC 2006 No Change 2013 2016 2019 2022 2025

Wyoming IECC 2003 No Change 2013 2016 2019 2022 2025



### Table A

. 3 through Table A

. 7 show potential projected energy savings, energy cost savings, emissions

reductions, and monetized emissions savings assuming immediate adoption and 100% compliance.

A.3

### Potential code

- induced ene rgy savings and energy cost savings are presented in Table A.3.

Cumu lative site energy savings potential equals 36 quads, with residential and commercial energy code

activities contributing approximately 50% each. Primary energy savings potential is 64.7 quads, which

translates to FFC energy savings of 67 quads. Cumulative energy cost savings potent ial equals

approximately $261.5 billion (2012$).

Table A

. 3 . Summary of Energy and Cost Savings Potential

Site Energy

Savings, quads Primary Energy

Savings, quads FFC Energy

Savings, quads Energy Cost

Savings NPV,

billion 2012$

(7% discount

rate)

Potential Savings, Commercial

Annual in 2040 

### 1.6 2.9 3.0 6.6

Cumulative 2013

– 2040 

### 18.9 36.3 37.4 134.5

Potential Savings, Residential

Annual in 2040 

### 1.3 2.1 2.2 5.4

Cumulative 2013

– 2040 

### 17.2 28.3 29. 6 127.1

Potential Savings, Total

Annual in 2040 

### 2.8 5.0 5.2 12.0

Cumulative 2013

– 2040 

### 36.1 64.7 67.0 261.5

Detailed annual site energy savings potential

, primary energy savings potential, and FFC energy

savings potential are presented in Table A

. 4

.

Table A

. 4

. Potential Site, Primary, and FFC Energy Savings (quads)

Site Annual,

quads Site Cumulative,

quads Primary

Annual,

quads Primary

Cumulative,

quads FFC Annual,

quads FFC

Cumulative,

quads

2013 0.04 0.04 

### 0.08 0.08 0.1 0.1

2014 0.09 0.13 

### 0.18 0.25 0.2 0.3

2015 0.15 0.28 

### 0.29 0.54 0.3 0.6

2016 0.23 0.50 

### 0.44 0.99 0.5 1.0

2017 0.30 0.81 

### 0.60 1.59 0.6 1.6

2018 0.38 1.19 

### 0.76 2.35 0.8 2.4

2019 0.47 1.67 

### 0.94 3.30 1.0 3.4

2020 0.56 2.23 

### 1.12 4.42 1.2 4.6

2021 0.65 2.88 

### 1.22 5.64 1.3 5.8

2022 0.75 3.62 

### 1.41 7.04 1.5 7.3

2023 0.84 4.47 

### 1.59 8.64 1.7 8.9

2024 0.94 5.41 

### 1.79 10.42 1.8 10.8

2025 1.05 6.46 

### 2.00 12.42 2.1 12.9

2026 1.16 7.63 

### 2.07 14.50 2.2 15.0

2027 1.27 8.90 

### 2.27 16.76 2.4 17.4

2028 1.38 10.28 

### 2.47 19.24 2.6 19.9

2029 1.50 11.78 

### 2.68 21.92 2.8 22.7

2030 1.61 13.39 

### 2.88 24.80 3.0 25.7

2031 1.72 15.12 

### 3.01 27.81 3.1 28.8

A.4

### Table A.4

. (c ontd )

Site Annual,

quads Site Cumulative,

quads Primary

Annual,

quads Primary

Cumulative,

quads FFC Annual,

quads FFC

Cumulative,

quads

2032 1.84 16.96 

### 3.22 31.03 3.3 32.2

2033 1.96 18.91 

### 3.42 34.45 3.6 35.7

2034 2.08 20.99 

### 3.64 38.09 3.8 39.5

2035 2.20 23.19 

### 3.86 41.95 4.0 43.5

2036 2.33 25.52 

### 4.08 46.04 4.2 47.7

2037 2.46 27.98 

### 4.31 50.35 4.5 52.2

2038 2.58 30.56 

### 4.54 54.89 4.7 56.9

2039 2.71 33.27 

### 4.77 59.65 4.9 61.9

2040 

### 2.84 36.11 4.99 64.65 5.2 67.0

A summary of emissions reduction potential calculated based on the FFC analysis is presented in

Table A

. 5

.

Table A

. 5 . Summary of Emissions Reduction Potential

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt t on kt mmt CO 2 eq kt mmt CO 2 eq kt

Potential Reduction, Commercial

Annual in 2040 252 243 0.6 2.7 0.8 1,005 25.1 151

Cumulative 2013



### – 2040 2,980 3,069 6.7 32.4 9.6 12,118 303 3,180

Potential Reduction, Residential

Annual in 2040 174 200 0.4 1.5 0.4 809 20.2 118

Cumulative 2013



### – 2040 2,251 2,790 4.9 20.1 6.0 10,971 274 1,711

Potential Reduction, Total

Annual in 2040 426 443 1.0 4.2 1.2 1,814 45 269

Cumulative 2013



### – 2040 5,230 5,859 11.6 52.5 15.6 23,089 577 4,891



### Cumulative emissions reductions potential between 2013 and 2040 includes over 5.2 billion metric

tons (Mt) of CO 2 

### , nearly 5. 9 million tons of NO

x 

### , 11.6 tons of Hg, and nearly 4.9 million tons of SO 2



### .

The value of the CO 2 

### emission s reductions is $ 2.7 to $8.8 billion (2012$) based on 2013 domestic

social carbon values and a 5% discount rate, or 38.5 billion (2012$) based on global SCC . W hile at the

low

- end of a range of values

, NO

x 

### savings contribute at least another $ 0.9 b illion of savings ( at $468 per

ton in 2012$)

. Energy cost savings potential presented in Table A

. 3 , combined with the physical and

monetized emission savings potential presented in Table A

. 6 , capture potential consumer benefits to the

nation from the energy code activities between 2013 and 2040, assuming immediate adoption and full

compliance.

The combined consumer benefits potential is shown in Table A

. 7 . Depending on the social cost of

CO 2 

### and NO

x 

### , the NPV of potential consumer benefits can range between $ 301 and nearly $ 796 billion

(2012$). Out of that total, the energy cost savings potential exceeds $261 billion (2012$).

Each one of the consumer and emissions value estimates shown in Table A

. 7 represent a combination

of consumer energy cost savings, and corresponding scenarios for monetized reduction of CO 2 

### and NO

x 

### . For example, Consumers + CO 2 

### (1st) + NO

x 

### (Low) means that savings from the first scenari o of CO 2 

### (5%

A.5

### discount rate, average , global SCC ) were combined with savings from the low NO

x 

### cost scenario ( at

$468 per ton in 2012$) and added to the consumer energy cost savings.

Table A

. 6 . National Ben efits Potential, 2013

– 2040

Cumulative Results Units Commercial

(2013

- 2040) Residential (2013

- 2040) Total BECP ( 2013

- 2040)

Energy Savings

Site quads 36.3 28.3 64.6

Primary quads 1.1 1.3 2.4

Full

- Fuel

- Cycle (total) quads 37.4 29.6 67.0

Economic Impacts

Potential Energy Cost Savings

, 7 % discount rate billion 2012$ 134.5 127.1 261.5

Emissions Savings (physical)

Full

- Fuel

- Cycle (total)

CO 2 mmt 2,980 2,251 5,230

NO

x kt 3,069 2,790 5,859

Hg ton 6.7 4.9 12

N 2 O kt 32.4 20.1 53

N 2 O mmt CO 2 eq 9.6 6.0 16

CH 4 kt 12,118 10,971 23,089

CH 4 mmt CO 2 eq 303 274 577

SO 2 kt 3,180 1,711 4,891

Emissions Savings (monetized)

Full

- Fuel

- Cycle (total)

CO 2 (global)

5% d iscount r ate , average billion 2012$ 21.8 16.7 38.5

3% d iscount r ate , average billion 2012$ 96.7 73.4 170.1

2.5% d iscount r ate , average billion 2012$ 153.1 116.1 269.2

3% d iscount r ate , 95th %ile billion 2012$ 298.8 226.6 525.4

CO 2 (domestic)

5% discount rate, average billion 2012$ 1.5 to 5 1.2 to 3.8 2.7 to 8.8

3% d iscount r ate , average billion 2012$ 6.8 to 22.2 5.1 to 16.9 11.9 to 39.1

2.5% d iscount r ate , average billion 2012$ 10.7 to 35.2 8.1 to 26.7 18.8 to 61.9

3% d iscount r ate , 95th %ile billion 2012$ 20.9 to 68.7 15.9 to 52.1 36.8 to 120.8

NO

x (7% d iscount r ate )

At 468 2012$/ton billion 2012$ 0.47 0.4 0.9

At 2,639 2012$/ton billion 2012$ 2.6 2.5 5.1

At 4,809 2012$/ton billion 2012$ 4.8 4.5 9.3



### Table A

. 7 . Consumer Cumulative Benefits Potential, 2013

– 2040

Cumulative Results Commercial (2013

- 2040) Residential (2013

- 2040) Total BECP (2013

- 2040)

NPV

Consumer Energy Cost Savings billion 2012$ 134.5 127.1 261.5

Consumer and Emissions Value

Consumers + CO 2 (1st) + NO

x (Low) billion 2012$ 157 144 301

Consumers + CO 2 (2nd) + NO

x (Med) billion 2012$ 234 203 437

Consumers + CO 2 (3rd) + NO

x (Med) billion 2012$ 290 246 536

Consumers + CO 2 (4th) + NO

x (High) billion 2012$ 438 358 796



### A.6

### Combining potential energy savings from new post

- 2013 construction with code

- induced savings

from existing stock that keep occurring in 2013

– 2040 represents the full future potential of the energy

codes activities. These results are summarized in Table A

. 8 and Table A

. 9

.

Table A

. 8 . Summary of Full Future Energy and Cost Savings Potential

Site Energy

Savings, quads Primary Energy

Savings, quads FFC Energy

Savings, quads Energy Cost

Savings NPV,

billion 2012$

(7% discount

rate)

Potential Savings, Commercial

Annual in 2040 

### 1.7 3.2 3.3 7.2

Cumulative 2013

– 2040 

### 23.1 44.8 46. 2 178.8

Potential Savings, Residential

Annual in 2040 

### 1.4 2.2 2.3 5.8

Cumulative 2013

– 2040 

### 19.5 32.2 33. 8 150.9

Potential Savings, Total

Annual in 2040 

### 3.1 5.4 5.6 13.0

Cumulative 2013

– 2040 

### 42.6 77 .0 80.0 329.7

Table A

. 9 . Summary of Full Future Emissions Reduction Potential

CO 2 NO

x Hg N 2 O N 2 O CH 4 CH 4 SO 2

mmt kt Ton kt mmt CO 2 eq kt mmt CO 2 eq kt

Potential Reduction, Total

Annual in 2040 

### 461 479 1.1 4.5 1.3 1,962 49 291

Cumulative 2013



### – 2040 

### 6,189 7,178 13.7 62.3 18.6 27,280 682 6,140

Full cumulative site energy savings potential for 2013

– 

### 2040 equals 42.6 quads, with residential and

commercial energy code activities contributing approximately 50% each. Primary energy savings

potential is 77 quads, which translates to FFC energy savings of nearly 80 quads. Cumulative energy cost

savings po tential equals approximately $330 billion (2012$). Annual carbon savings potential reaches

461 million tons at the end of 2040, and the cumulative potential carbon savings by 2040 are estimated at

nearly 6.2 billion tons.

A.7