Chicagoland Single-Family 

Housing Characterization 

J. Spanier, R. Scheu, L. Brand, and J. Yang 

Partnership for Advanced Residential Retrofit 

(PARR) 

June 2012
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iii

Chicagoland Single-Family Housing Characterization

Prepared for: 

Building America

Building Technologies Program

Office of Energy Efficiency and Renewable Energy 

U.S. Department of Energy 

Prepared by: 

J. Spanier, R. Scheu, L. Brand, J. Yang

CNT Energy and Gas Technology Institute for

Partnership for Advanced Residential Retrofit

1700 South Mount Prospect Road

Des Plaines IL 60018

Technical Monitor: Stacey Rothgeb

Task Order KNDJ-0-40346-02

June 2012
iv

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v 

Contents

List of Figures ............................................................................................................................................ vi

List of Tables .............................................................................................................................................. vi

Executive Summary................................................................................................................................. viii

1 Introduction and Background ............................................................................................................. 1

1.1 Introduction..........................................................................................................................1

1.2 Background..........................................................................................................................1

1.3 History of Chicago Buildings..............................................................................................2

1.4 Relevance to Building America’s Goals..............................................................................2

1.5 Cost Effectiveness................................................................................................................3

1.6 Tradeoffs and Other Benefits...............................................................................................3

2 Objective................................................................................................................................................ 4

3 Approach............................................................................................................................................... 4

3.1 Data Collection ....................................................................................................................5

3.2 Data Cleaning and Manipulation .........................................................................................6

3.3 Development of Housing Groups ......................................................................................11

Group 1: Brick, 1978-Present, 1 to 1.5 stories (no split level) ................................................13

Group 2: Brick, 1978-Present, Split level (1.5 stories)............................................................13

Group 3: Brick, 1978-Present, 2 stories...................................................................................14

Group 4: Brick, 1942-1978, 1 to 1.5 stories (no split level)....................................................14

Group 5: Brick, Pre-1978, Split level (1.5 stories) ..................................................................15

Group 6: Brick, 1942-1978, 2 stories.......................................................................................15

Group 7: Brick, Pre-1942, 1 to 1.5 stories (no split level).......................................................16

Group 8: Brick, Pre-1942, 2 stories.........................................................................................16

Group 9: Frame, 1978-Present, 1 to 1.5 stories (no split level)...............................................17

Group 10: Frame, All years, Split level (1.5 stories)...............................................................17

Group 11: Frame, 1978-Present, 2 stories ...............................................................................18

Group 12: Frame, 1942-1978, 1 to 1.5 stories (no split level).................................................18

Group 13: Frame, 1942-1978, 2 stories...................................................................................19

Group 14: Frame, Pre-1942, 1 to 1.5 stories............................................................................19

Group 15: Frame, Pre-1942, 2 stories......................................................................................20

3.4 BEopt Modeling.................................................................................................................20

3.4.1 All Cases................................................................................................................20

3.4.2 As-Built Case Assumptions...................................................................................21

3.4.3 Today Case Assumptions.......................................................................................22

4 Results................................................................................................................................................. 23

4.1 Selection Criteria ...............................................................................................................25

4.2 Model Results....................................................................................................................26

4.3 Analysis..............................................................................................................................36

5 Conclusions ........................................................................................................................................ 38

References................................................................................................................................................. 40

Appendix I – Detail on Housing Group Characteristics........................................................................ 41

Appendix II – BEopt Modeling Assumptions Tables............................................................................. 45

Appendix III – Detailed Results Tables ................................................................................................... 51
vi

List of Figures

Figure 1. Natural gas utility service territories, Cook County, Illinois .................................................. 5

Figure 2. Distribution by floor area ........................................................................................................... 8

Figure 3. Distribution by year built............................................................................................................ 8

Figure 4. Source EUI from all scenarios - As-built, Today, CNT, BEopt Upgrade.............................. 24

Figure 5 Therms from all scenarios - As-built, Today, CNT, BEopt Upgrade..................................... 24

Unless otherwise noted, all figures were created by the PARR team.

List of Tables

Table 1. Cook County Assessor Data Snapshot...................................................................................... 6

Table 2. Characteristics of General Housing Population........................................................................ 7

Table 3. Energy Statistics (presented in site energy use) ...................................................................... 9

Table 4. Number of Stories......................................................................................................................... 9

Table 5. Statistics on Garage Type ......................................................................................................... 10

Table 6. Statistics on Attic Type.............................................................................................................. 10

Table 7. Statistics on Basement Type..................................................................................................... 10

Table 8. Statistics on Energy Use by Construction Type ..................................................................... 11

Table 9. Statistics on Energy Use by Year Built .................................................................................... 12

Table 10. Statistics on Energy Use by Number of Stories.................................................................... 12

Table 11. BEopt Today Case Model Results by Group Compared to CNT Data................................. 25

Table 12. Source EUI Reduction Percentage by Group ........................................................................ 37

Table 13. Final Rank by Group ................................................................................................................ 37

Unless otherwise noted, all tables were created by the PARR team.
vii

Definitions

BRC Building Research Council at the University of Illinois, a member of the 

Partnership for Advanced Residential Retrofit

BTU British Thermal Unit is a unit of heat. 100,000 BTU equal 1 therm.

CDD Cooling Degree Days

CNT Center for Neighborhood Technology, an implementer of the proposed 

plan, currently running a portfolio of energy efficiency programs

DOE U.S. Department of Energy, a sponsor

EUI Energy Use Intensity is a standardized comparison for benchmarking 

buildings, measured in kBtu per ft2 per year

FutEE Future Energy Enterprise, a member of the Partnership for Advanced 

Residential Retrofit

GTI Gas Technology Institute, an implementer

HDD Heating Degree Days

MEEA Midwest Energy Efficiency Alliance, a member of the Partnership for 

Advanced Residential Retrofit

MEL Miscellaneous Electrical Load

PARR Partnership for Advanced Residential Retrofit, a Building America team 

led by the Gas Technology Institute

RECS Residential Energy Consumption Survey

TO Task Order, referring to a time dependent work order
viii

Executive Summary

In this project, the PARR team identifies housing characteristics and energy use for fifteen 

single-family housing types (groups) in the Chicagoland region and specifies measure packages 

that provide an optimum level of energy savings based on a BEopt analysis. In its research, the 

team used property assessor data and actual energy consumption of 432,605 houses representing 

approximately 30% of the single-family home population. The optimum package of energy 

efficiency measures developed is based on a target of cost effectiveness at the measure level and 

30% source energy savings. Based on the BEopt result, the project identifies the three housing 

groups that provide the maximum energy savings potential as defined by annual source energy 

savings multiplied by the total number of houses in the sample population. The three groups 

based on construction characteristics (structural, vintage and size) and identified as having the 

greatest potential as a result of this analysis are:

1. Wood frame, pre-1942 construction, 1 to 1.5 stories

2. Brick (double brick), pre-1942 construction, 1 to 1.5 stories

3. Wood frame, 1942-1978 construction, 1 to 1.5 stories.

These three housing groups will be used in the next step in the project to evaluate the measure 

packages. The PARR team will work with installing contractors in the field to document the 

upgrades that have been done to the houses since they were built, determine the cost of 

performing the proposed set of upgrades, and identify techniques that can be used for low-cost 

implementation on a community scale.1

 

Homeowners and efficiency program implementers require meaningful peer groups and 

benchmark comparisons in order to make informed upgrade decisions, and to use realistic 

savings estimates based on performance of a large population of similar homes of comparable

size, vintage, and construction.

The segmentation methodology presented in this report is intended to be replicable in other parts 

of the country. Each region has varying yet distinct home characteristics (construction type, 

vintage and size), weather and energy regulatory environments that influence how much energy a 

home consumes, and upgrades that can offer the greatest energy savings. Coupling housing 

segmentation with measured energy data analysis for a large population of homes reduces the 

effect of outliers, and can significantly reduce program costs by eliminating the need for 

modeling each individual similarly constructed home. This replicable approach can dramatically

impact how broad-scale retrofit implementation programs are developed, implemented, and 

brought to scale.

 1 Peters, Jamie, EE Solution Package for Top 3 Housing Types – Field Tests from Chicagoland Housing (to be 

issued later in 2012)
1

1 Introduction and Background

1.1 Introduction

This project identifies housing characteristics and energy use for common homes in the

Chicagoland region and produces advanced efficiency measure packages that can be 

implemented in the region’s existing homes. The term “Chicagoland” is defined in this report as 

the city and the suburbs that make up Cook County, Illinois. Three housing types will be selected 

that show the best opportunity for energy savings using BEopt modeling of potential energy 

efficiency package options, with a target of 30% source energy savings. This savings is

equivalent to between $600 and $750 per home per year.

The U.S. Department of Energy’s (DOE) Building America program focuses on conducting 

research to improve the efficiency of new and existing homes. The program’s overall goal is to 

develop integrated systems solutions that can take advantage of economies of scale. 

The Partnership for Advanced Residential Retrofit (PARR) is a Building America team based in 

Chicago, researching energy efficiency solutions for residential housing with a focus on cold 

climate retrofits in the Midwest. PARR, led by GTI, represents a broad spectrum of residential 

building stakeholders including CNT Energy, Midwest Energy Efficiency Alliance (MEEA), 

Building Research Council at the University of Illinois (BRC), and Future Energy Enterprise 

(FutEE). These stakeholders are critical to designing, executing, and disseminating impactful 

research. PARR possesses strong experience in design, development, integration, and testing of 

advanced building energy equipment. PARR applies this experience in testing components and 

systems in laboratory and test house settings to improve performance, quality, and market 

acceptance of whole house residential energy efficiency retrofits in cold climates.

PARR was expressly created to make residential energy efficiency retrofits more cost effective 

and to demonstrate concepts that enable market transformation on a mass scale. PARR aims to 

increase the quality and uptake of residential retrofits in the midwest United States while 

providing Building America with systems, whole home, and community level solutions for the 

entire cold climate region. 

Toward this goal, PARR is performing a characterization of the top fifteen housing types 

(groups) in Chicagoland based on assessor data, utility billing history, and available data from 

prior energy efficiency programs. PARR will analyze the data and recommend the housing types 

to focus on for designing retrofit packages using cost effectiveness of energy savings for ranking. 

Following this, PARR will use BEopt modeling software, paired with local cost data, to design 

retrofit packages for the three building types to be implemented in the field by local contractors 

under another PARR project

.

1.2 Background

There are more than 3.3 million single-family homes in the seven-county Chicagoland area, 

which represents 63% of the population of the single-family homes in Illinois. This research 

focuses on Cook County, the most housing-dense county in the region, where there are nearly 2

million households and 1.1 million single-family homes. The median built year of the singlefamily housing stock is 1956, prior to implementation of energy codes requiring the installation 
2

of insulation. The region’s extreme weather - long, cold winters and shorter hot, humid summers

- combined with the older housing stock, makes homes in this region very energy intensive

(nearly twice the national average), with heating being the dominant energy expenditure. 

As energy costs increase, home energy improvements have the potential to keep housing 

affordable, improve comfort, and preserve the existing housing stock. There is significant need 

for cost-effective retrofit solutions that can be deployed at scale. Improving the efficiency of the 

region’s housing can save homeowners money, improve the workforce, and strengthen the local 

economy. This project will identify which housing types to target and what retrofit packages 

offer the most cost effective energy savings.

The single-family housing stock in Cook County consists of varying types, many dating back 

before the Great Chicago Fire of 1871. There are more than a dozen housing types, and a 

dominant one is the iconic Chicago bungalow. The bungalow is a deep single-story structure 

with narrow street exposure, high-pitched roof, and a dormered attic space that is often converted 

to additional living space. Nearly 80,000 bungalows were built in the region between 1910 and 

1940. These homes share similar construction features and they are ubiquitous in the region, with 

many blocks in neighborhoods described as part of a ‘bungalow belt.’ As a group, bungalows 

consume approximately 25% more energy per square foot than the median home in the region, 

and represent huge energy savings potential. Because of their similarity, bungalows tend to 

require similar retrofit upgrades, such as attic air sealing and insulation. The bungalow is an 

example of how prescriptive retrofit packages can be customized to a specific housing type.

1.3 History of Chicago Buildings

The city of Chicago began as a settlement at the mouth of the Chicago River at Lake Michigan in 

the 1780’s. Illinois reached statehood in 1818, and the city of Chicago was officially 

incorporated in 1832, followed by rapid growth. The great Chicago fire of 1871 destroyed the 

central business district and 18,000 buildings including one-third of all the residential structures. 

Strict building codes were instituted following the fire, favoring solid masonry construction in 

most commercial buildings and a large percentage of single-family and multifamily buildings

well into the next century. The bungalow building era was at the center of the building boom of 

the early 1900’s, and the current single-family building stock is significantly influenced by the 

construction boom in that era. Pre-1942 uninsulated wood frame and solid masonry buildings are 

the predominant type of construction, offering many challenges for energy efficiency retrofits.

According to 2010 U. S. census data, Cook County has a population of 5.2 million people 

occupying 2.2 million dwelling units. Multifamily housing accounts for 54% of the county’s

housing units, leaving 1.1 million single-family dwellings as the focus of this study.

1.4 Relevance to Building America’s Goals

“The goal of the U.S. Department of Energy's (DOE) Building America program is to conduct 

research to develop market-ready energy solutions that improve efficiency of new and existing 

homes in each U.S. climate zone, while increasing comfort, safety, and durability.”2

 2 http://www1.eere.energy.gov/buildings/building_america/program_goals.html
3

To develop retrofit packages geared towards homes in the Chicagoland region, it is essential to 

know more about the structural and energy use characteristics of the homes. As a colder humid 

continental climate, Chicago has an average of roughly 6,500 HDD and 800 CDD. Heating is the 

dominant energy end use, and heat load reduction typically offers the most energy-savings 

potential in this region.

Part of the motivation behind this project is to increase the visibility and use of large datasets to 

inform program decisions and retrofit activities. These goals naturally increase the scalability of 

retrofits, and would serve the larger goal of increased data and knowledge about the energy use 

of the residential building stock in the Chicago region. This work will also provide program 

decision-makers with information for targeting the most cost-effective housing types in terms of 

energy upgrades, improving performance of public dollars and heightening the value proposition 

for property owners.

Further motivation is based on the rollout of Home Performance with ENERGY STAR in 

Illinois. This project will provide the outline of retrofit packages by home types to be used as 

guidance for contractors taking homes through the program.

1.5 Cost Effectiveness

“Many energy efficiency programs rely on energy assessments that can cost $100 to $600 to 

identify the energy saving improvements for each participating household. A less costly option is

to forego an onsite home assessment, and use prescriptive approaches, offering a standard set of 

measures that are widely expected to save energy across a range of properties or within a specific 

type of targeted housing.”3

Large datasets help to reduce the transaction costs of analyzing and retrofitting a home. The 

ability to describe both the structural characteristics and energy use of a population of homes 

helps homeowners, assessors, contractors and policymakers make informed decisions regarding 

residential energy efficiency.

In addition, the data will enable modeling of a population of homes. Although customization of 

retrofit packages is required to retrofit an individual home, being able to do the first run of a 

model using data based on the population cuts down on the costs needed to model individual 

homes. It also enhances ability of marketers and related stakeholders to design programs that 

target buildings with the most potential for cost-effective energy savings.

Although the costs and savings associated with retrofitting individual homes will vary greatly 

depending on the measures administered to particular subjects in the sample, the retrofit 

packages will be cost effective as applied to the population of similar homes.

1.6 Tradeoffs and Other Benefits

The energy benchmarks for home types created from this research will aid in market 

transformation; a home with lower energy use or more potential for energy upgrades can be 

valued more than a comparable home without those attributes. 

 3 Delivering Energy Efficiency to Middle Income Single Family Households,” Zimring et al. Environmental Energy 

Technologies Division, Lawrence Berkeley National Laboratory, December 2011.
4 

In addition, these data can be used as reference for program design of future energy efficiency 

programs. While not included in the scope of this research, the data available can be used to 

spatially identify clusters of high energy use and inform targeted program design of certain 

geographies or communities. Through this type of characterization, it may be possible to offer 

energy upgrades to groups of homes without an audit; understanding from the typical energy 

signature how the building is built, what measures have likely already been applied, and which 

upgrades are cost effective going forward. 

2 Objective

The objective of this project is to identify which of the 15 housing types (groups) to target and 

what retrofit packages to apply for cost-optimized energy savings that will have the largest 

impact in the region. 

The PARR team intends to compare buildings on all of these dimensions simultaneously. 

The research questions to be addressed in this project are as follows: 

What are the most common housing types in Cook County? 

What are the energy use characteristics of these housing types? 

Can large datasets be used to identify cost-effective retrofit opportunities?

What are the types of housing to target for retrofit packages? 

Do identified databases provide sufficient detail for modeling inputs? 

What housing characteristics are most significant toward determining cost effectiveness 

of retrofit?

What is the relationship between housing type energy intensity and potential costeffective energy savings?

3 Approach

The approach to this project consists of four elements and the activities within each element:

• Data collection

• Data cleaning and manipulation 

• Development of housing groups 

• BEopt modeling. 

A discussion of each element is provided in the subsections below. 
5 

3.1 Data Collection

The research team gathered data from the three utilities serving the Chicago metropolitan 

region4. ComEd, the electric utility for northern Illinois, provided data for all residential accounts 

by address, including monthly kWh usage data. Integrys, the owner of People’s Gas in Chicago 

and North Shore Gas in parts of Cook and Lake Counties, provided data for all residential 

accounts by address, including monthly therms usage data. Nicor Gas, the natural gas utility for 

northern Illinois minus the territory covered by Integrys, provided data for all residential 

accounts by address, including annual therms usage data. 

Figure 1. Natural gas utility service territories, Cook County, Illinois

In addition, PARR compiled data on residential housing stock from the Cook County assessor. 

The research team focused on Cook County because the assessor data on the residential housing 

stock is comprehensive and robust. The Cook County property assessor collects 35 data points 

for each home, including housing characteristics that contribute to energy usage such as exterior 

construction, type of attic, basement, heating and cooling systems. 

 

4 The research team matched data for calendar year 2005 in Cook County.
6

Table 1 shows a snapshot of the data collected by the Cook County assessor.

Table 1. Cook County Assessor Data Snapshot

Variable Description

PIN 13-digit unique identifier

Address

City Mailing city

ZIP 5-digit zip code

Township Assessor township within Cook County

Assessor class Class is based on age, square footage, and number of units

Number of units Number

Square footage Measured as finished space

Year built

Bedrooms Number

Bathrooms (full) Number 

Bathrooms (half) Number

Exterior Construction Type of exterior construction

Roof Type of roof construction

Basement Type of basement

Attic Type of attic

Heating System Type of heating system

Air Conditioning Type of air conditioning system

Fireplace

Garage Number of spaces available

Garage (exterior construction) Exterior construction of garage

3.2 Data Cleaning and Manipulation

PARR separated base load energy use from heating and cooling load energy use using a 

regression model based on heating and cooling degree days. The heating and cooling energy use 

was then weather-normalized to ensure comparisons to future energy use or other normalized 

models was as accurate as possible. Other normalizations, such as for occupancy, were not done 

because of a lack of data at the household level.

Data including housing characteristics, electric, and natural gas data compiled by address, to 

create a complete dataset by individual home. Because of the unique address formatting styles 

particular to each dataset (ex. Ave vs. Avenue), address cleaning was required.

Address cleaning was performed through a series of Perl scripts making heavy use of the 

language’s regular expressions capabilities to identify, split, and extract complex character 

sequences. The output files from the cleaning process were imported into a MySQL database,

and queries to that database were used to match addresses across data sources.
7

This left a dataset of 464,745 homes, representing 43% of the population of nearly 1.1 million 

homes. Outliers were removed using the following criteria.

• Homes with missing data, including energy use, square footage, year built, or number of 

stories. If a home was missing at least one piece of data, it was excluded from analysis.

• Homes with assessor codes 211 and 212 were deleted, to exclude:

o 211: Two to six apartments, over 62 years

o Mixed commercial/residential building, six units or less, less than 20,000 sq. ft.

• Homes not meeting criteria for minimum energy usage were excluded:

o Less than 100 therms

o Less than 100 kWh

o An energy use intensity (kBtu/sqft/year) less than 30.

• The top 1% of homes in the energy use categories were excluded to minimize the impact 

of high-use outliers:

o More than 3,246 therms annually

o More than 28,244 kWh annually

o An energy use intensity (kBtu/sqft/year) more than 285.

After eliminating missing data and outliers, 432,605 homes were included in analysis.

A summary of the characteristics of the general population is presented in Table 2, below.

Figure 2 shows the distribution of housing by size.

Figure 3 shows the distribution by year of construction.

Table 3 provides energy statistics.

Table 2. Characteristics of General Housing Population

Variable Mean Std Dev Median Quartile Range

Square footage

Year built

Number of bedrooms

Number of full bathrooms

Number of half bathrooms

1426.8

1951.4

3.1

1.3

0.4

588.0

25.3

0.8

0.5

0.5

1248.0

1956.0

3.0

1.0

0.0

570.0

36.0

0.0

1.0

1.0
8 

Figure 2. Distribution by floor area 

Figure 3. Distribution by year built 

 
9

Table 3. Energy Statistics (presented in site energy use)

Variable Mean Std Dev Median Quartile Range

Energy Use Intensity (kBtu/sqft/yr)

kBtu

Therms

kWh

Baseload (therms)

Heating load (therms)

Baseload (kWh)

Cooling load (kWh)

130

171,465

1,392

9,466

307

1,085

8,523

943

44

52,077

446

4,508

125

368

4,255

884

125

164,589

1,329

8,697

287

1,027

7,742

722

58

64,883

553

5,602

143

446

5,177

1,039

Table 4 provides statistics on number of stories. The assessor categorizes stories as the number 

of floors above ground level with finished space. This includes 1-, 1.5-, and 2-story 

classifications. For example, the vernacular Chicago Bungalow, built with an unfinished attic on 

the second floor with a pitched roof and knee walls, is classified as a 1-story building in the 

assessor data. 

Table 4. Number of Stories

Stories Frequency Percent

1 296,170 68.46

1.5 44,087 10.19

2 92,348 21.35

Table 5, Table 6, and Table 7 provide statistics on garage types, attic types and basement types. 
10

Table 5. Statistics on Garage Type

Garage Type Frequency Percent

1 car attached 23470 5.45

1 car detached 47870 11.11

1.5 car attached 4696 1.09

1.5 car detached 26311 6.10

2 car attached 72190 16.75

2 car detached 170242 39.50

2.5 car attached 4047 0.94

2.5 car detached 14220 3.30

3 car attached 5671 1.32

3 car detached 1814 0.42

3.5 car attached 405 0.09

3.5 car detached 224 0.05

4 car attached 195 0.05

4 car detached 177 0.04

None 59479 13.80

Table 6. Statistics on Attic Type

Attic Type Frequency Percent

Full and Living Area 41,759 9.7%

Full and Unfinished 52,069 12.1%

None 274,063 63.6%

Partial and Living Area 14,309 3.3%

Partial and Unfinished 48,797 11.3%

Table 7. Statistics on Basement Type

Basement Type Frequency Percent

Crawl 20,459 4.8

Full and Rec Room 72,547 16.8

Full and Unfinished 194,065 45.0

Partial and Rec Room 57,896 13.4

Partial and Unfinished 31,942 7.4

Slab 54,102 12.5
11

3.3 Development of Housing Groups

The test plan outlined three segmentation methodologies to create the housing groups: statistical 

clustering, construction characteristics, and heating characteristics. After evaluating output 

results using the three methodologies, PARR decided on segmentation by construction 

characteristics to define the 15 housing groups.

The project’s initial goal was to cluster the homes into different architectural subtypes, so that 

the subtypes most fit for retrofitting would be identified. Statistical cluster analysis has several 

different methods for choosing seeds, the starting points for the cluster groups. Because of the 

large size of the dataset, k-means clustering was called for. K-means clustering initially 

randomly generates a cluster center and selects clusters for the data points based on lowest 

Euclidian distance. Once all data points are assigned, the cluster averages are used for the new 

centers in another round of clustering based on Euclidean distance. After the re-clustering and recentering process has been repeated enough times to meet the convergence criterion, the process 

is finished. Unfortunately, the data did not cluster into the different architectural subtypes as was 

hoped. This is largely due to the overlap of home attributes such as size, age, and frame type 

among different architectural styles. In the end, the clustering was based on the differences in 

energy use amongst the homes, which, while informative, did not group homes based on 

structural characteristics that would enable certain types of retrofits.

The final segmentation of housing groups is based on a three tiered system of characteristics, 

which are chosen based on previous program knowledge and identified contributions to energy 

use.

Tier 1) Construction type – either brick or not brick (includes frame and “frame and brick” 

houses). Table 8 provides statistics on energy use by construction type.

Table 8. Statistics on Energy Use by Construction Type

Construction 

Type

N Obs Variable (measure in site energy use) Mean Std Dev. Median Quartile 

Range

Brick 232306 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

125.5

1362.7

9750.7

45.6

439.7

4553.1

118.5

1302.0

8996.0

59.0

547.0

5706.0

Frame 200299 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

135.6

1425.3

9136.2

42.2

451.3

4431.4

131.3

1358.0

8357.0

54.2

558.0

5442.0

Tier 2) Year built: based on three categories:

Pre-1942 (the bottom of the bimodal histogram)

1942-1978 (1978 is the year that building codes changed to include insulation)

Post-1978.
12

Table 9 provides statistics on energy use by year built.

Table 9. Statistics on Energy Use by Year Built

Year built N Obs Variable (measure in site energy use) Mean Std Dev Median Quartile 

Range

Pre-1942 128751 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

150.0

1593.0

9500.6

47.6

487.3

4729.8

144.7

1541.0

8717.0

66.6

627.0

6006.0

1942-

1978

251544 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

129.3

1302.8

9100.5

38.2

390.3

4205.1

124.9

1253.0

8399.0

48.5

479.0

5218.0

Post-1978 52310 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

85.8

1323.2

11140.1

27.3

432.6

4949.5

80.6

1266.0

10252.0

33.4

520.0

6265.0

Tier 3) Number of stories: 

1

1.5

2.

Number of stories was used to segment groups by size of home. The dataset in Table 10 provided 

for the BEopt modeling included median square footage and median therms and kWh for each of 

the 15 housing groups. The number of stories informs BEopt modeling in terms of volume and 

layout of the home, rather than square footage which implies size but not the spatial distribution

of that size.

Table 10. Statistics on Energy Use by Number of Stories

Stories N Obs Variable (measure in site energy use) Mean Std Dev Median Quartile 

Range

1 296170 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

139.0

1330.0

8794.6

45.2

419.8

4155.6

133.8

1276.0

8117.0

59.5

528.0

5192.0

1.5 44087 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

128.9

1345.9

9658.0

33.6

358.9

3888.1

124.8

1298.0

9085.0

41.2

446.0

4802.0

2 92348 Energy Use Intensity (kBtu/sqft/year)

Therms

kWh

102.4

1611.2

11528.6

33.2

494.6

5183.2

97.8

1535.0

10717.0

44.3

635.0

6781.5

The 15 groups were assembled by using these three tiers and overlaying houses with similar 

energy use and structural characteristics. A short summary of each group with example photos 

follows. See Appendix I for more detailed information on characteristics of each housing group.
13

Group 1: Brick, 1978-Present, 1 to 1.5 stories (no split level)

2.5% of population

Mean Site EUI: 81.8

Mean therms: 1077

Mean kWh: 8887

Mean finished square footage: 1741

Group 2: Brick, 1978-Present, Split level (1.5 stories)

1.9% of population

Mean Site EUI: 112.6

Mean therms: 1205

Mean kWh: 10076

Mean finished square footage: 1404
14

Group 3: Brick, 1978-Present, 2 stories

4.7% of population

Mean Site EUI: 76.7

Mean therms: 1446

Mean kWh: 12482

Mean finished square footage: 2506

Group 4: Brick, 1942-1978, 1 to 1.5 stories (no split level)

17.9% of population

Mean Site EUI: 129.6

Mean therms: 1212

Mean kWh: 8859

Mean finished square footage: 1217
15

Group 5: Brick, Pre-1978, Split level (1.5 stories)

6.1% of population

Mean Site EUI: 131.5

Mean therms: 1344

Mean kWh: 9643

Mean finished square footage: 1299

 

Group 6: Brick, 1942-1978, 2 stories

4.8% of population

Mean Site EUI: 99.8

Mean therms: 1553

Mean kWh: 11714

Mean finished square footage: 2059
16

Group 7: Brick, Pre-1942, 1 to 1.5 stories (no split level)

11.6% of population

Mean Site EUI: 161.3

Mean therms: 1442

Mean kWh: 8927

Mean finished square footage: 1141

Group 8: Brick, Pre-1942, 2 stories

4.1% of population

Mean Site EUI: 117.3

Mean therms: 1757

Mean kWh: 11062

Mean finished square footage: 1884
17

Group 9: Frame, 1978-Present, 1 to 1.5 stories (no split level)

1.7% of population

Mean Site EUI: 91.8

Mean therms: 1217

Mean kWh: 9719

Mean finished square footage: 1801

 

Group 10: Frame, All years, Split level (1.5 stories)

2.1% of population

Mean Site EUI: 136.6

Mean therms: 1480

Mean kWh: 9321

Mean finished square footage: 1349
18

Group 11: Frame, 1978-Present, 2 stories

1.1% of population

Mean Site EUI: 73.8

Mean therms: 1749

Mean kWh: 14914

Mean finished square footage: 3178

Group 12: Frame, 1942-1978, 1 to 1.5 stories (no split level)

23.6% of population

Mean Site EUI: 135.3

Mean therms: 1268

Mean kWh: 8483

Mean finished square footage: 1185
19

Group 13: Frame, 1942-1978, 2 stories

3.8% of population

Mean Site EUI: 119.2

Mean therms: 1467

Mean kWh: 9802

Mean finished square footage: 1586

Group 14: Frame, Pre-1942, 1 to 1.5 stories

11.2% of population

Mean Site EUI: 158.9

Mean therms: 1608

Mean kWh: 9050

Mean finished square footage: 1254

 
20

Group 15: Frame, Pre-1942, 2 stories

2.9% of population

Mean Site EUI: 158.9

Mean therms: 1608

Mean kWh: 9050

Mean finished square footage: 2058

3.4 BEopt Modeling

The fifteen housing types (groups) identified through the data collection and analyses were then 

modeled using BEopt under three scenarios: 

• As-built, to establish a common baseline for all groups based on year of construction, 

and to identify the non-upgrade characteristics of the group. This scenario was developed 

to document the building construction before adding expected upgrades that bring the 

building in line with the measured EUI data. It was useful to establish a common 

construction practice between housing groups by year of construction.

• Today, to apply typical upgrades in insulation, infiltration and HVAC systems in order to 

match the EUI energy data provided for each group.

• Upgrade, to use the optimization routines in BEopt and determine the potential energy 

savings through upgrade.

The PARR BEopt analyst relied on many industry experts to develop the assumptions in each of 

the three scenarios: an expert group consisting of PARR team members with background in 

weatherization training, insulation products, HVAC, and field retrofit practices; a local insulation 

contractor; and members of the NREL BEopt team.

Appendix II contains the assumptions made in each of the scenarios. A discussion regarding 

these modeling assumptions is provided in Sections 3.4.1 through 3.4.3, below.

3.4.1 All Cases

In all cases, PARR used the property assessor and energy data from CNT Energy to model the 

buildings. Number of stories, type of foundation, finished or unfinished spaces, and square 

footage were followed. The type of garage, number of bedrooms and baths, and type of 

foundation were also followed for each vintage of house. General assumptions for all vintages 

and scenarios are provided in the list below and specific assumptions are provided in the sections 

that follow.
21

• Assumptions on the lot size and distance to neighbors were based on homeowner input 

from the PARR research team and information on the size of a standard city and 

suburban lot.

• In all cases, the heating setpoint was set at 70 and cooling setpoint was set at 72 and left 

unchanged.

• Windows were modeled as double-clear (window plus storm window) in all cases and 

left unchanged.

• Mechanical ventilation was modeled as none for pre-1942 and spot for other years.

• Average current appliances were chosen for the models as they were only significant in 

evaluating the energy use in the Today scenario.

• MEL’s were set at 1 for both gas (MGL) and electric.

3.4.2 As-Built Case Assumptions

Pre-1942 construction assumptions were as follows:

• Brick walls pre-1942 are double brick construction. The layers from outside to inside are: 

4 inch brick, 1 inch airspace (the weep space, largely mortar and bricks connecting the 

inside and outside layer), an inside brick layer, wood lath with no insulation in the spaces, 

and 5/8 inch drywall simulating plaster. A new Concrete Masonry Unit (CMU) case was 

developed for the weep space plus 4 inch interior brick.

• Wood frame walls pre-1942 were modeled from the outside to inside as siding, sheathing, 

2x4 uninsulated walls, and 5/8 inch drywall simulating plaster on the interior wall.

• Roofs and ceilings in both types of houses were modeled as uninsulated. Bungalows were 

modeled with finished attic space in the upper half story. Interzonal knee walls were 

modeled with no insulation and the roof above the living space was also modeled with no 

insulation in the As-built scenario.

• Basements were uninsulated. Crawl spaces and slabs are not common in Chicago 

construction.

• Infiltration assumptions were as shown: very leaky for 1 story and leaky for 2 stories. 

These assumptions were made based on the opinion of an expert panel without validation 

from field data other than the close match of the Today case with field energy use 

intensity. The Today scenario results supported increasing the level of house tightness for 

all 2-story houses in all vintages. BEopt calculates infiltration in terms of ratio of the 

effective leakage area of the living space to the floor area of the space for the living 

space, basement, and garage area. The ratios for very leaky, leaky, typical, tight, tighter, 

and tightest (respectively) are: 0.0009, 0.0007, 0.0005, 0.00036, 0.00018, and 0.0009.

• No clothes dryer was included—line drying is the assumption.

• Boilers were the most common for pre-1942 construction and 65% efficiency was 

assumed (LBNL study).

• No cooling was included in the As-built case.

• Pre-1942 gas water heating was assumed with an energy factor (EF) of 0.48 (Kelso).
22

1942-1978 construction assumptions were as follows:

• For brick walls, 1 inch of R3 fiberglass was added between the furring strips.

• For wood frame and interzonal walls, an R7 fiberglass batt was the typical insulation for 

that era.

• Ceiling and interzonal floor insulation was R11.

• Infiltration for 1 story was upgraded to leaky and 2 stories to typical.

• Furnaces replaced boilers in the average house in this time frame; an AFUE of 70% was 

assumed.

• In the As-built case, cooling was not assumed for this vintage.

• The gas water heater was assumed to have the same 0.48 EF as pre-1942.

Post-1978 construction assumptions were as follows:

• Brick walls became brick veneer—face brick on the outside of the house, followed by

wood sheathing and a 2x4 stud wall with R11 insulation. The interior wall was assumed 

to be 1⁄2 inch drywall.

• Wood frame walls were assumed to be the same as brick with the brick veneer replaced 

by white wood siding.

• Ceiling insulation was increased to R30 based on average IECC values. 

• Interzonal floor insulation was increased to R19.

• Interzonal wall insulation matched the exterior wall insulation at R 11.

• Cooling with an SEER of 10 was assumed.

• Infiltration for single story houses was set at typical and for 2-story houses was set at 

tight to match the results from BEopt Today measured data.

3.4.3 Today Case Assumptions

Each house was modified in BEopt with reasonable assumptions to reflect common energy 

upgrades likely made to houses over time. For example, the uninsulated pre-1942 groups had R7 

insulation added to unconditioned attics to reflect an average practice, keeping in mind that many 

of these buildings are still operating with no insulation in the attics and many have a much higher 

insulation level. In every case, the MEL level was increased to 1.5 to match electric energy 

consumption and the water heater EF was increased to 0.54. Another option is to provide a series 

of models to bracket the range of energy performance characteristics of each group, but that 

option was rejected in favor of a single representative building. When the project moves to the 

field in a later task, each building will require baseline modeling to assess improvement to EUI. 

In addition to the assumptions above, the following assumptions were made for each vintage of 

building:

Pre-1942 construction upgrade assumptions were as follows:

• Attic insulation increased to R7.

• A gas dryer was added (not line drying).

• Cooling was added—SEER of 10 representing window air conditioners.

• Boiler efficiency was increased to 80%, representing a 1980’s boiler.

1942-1978 construction upgrade assumptions were as follows:

• The attic insulation increased to R19.
23

• Furnace efficiency was increased to 78% AFUE, the original NAECA minimum.

• Central cooling was added with an SEER of 10.

Post-1978 construction upgrade assumptions were as follows:

Furnace was upgraded to 80% AFUE to reflect some homes upgrading to high-efficiency 

furnaces.

In addition to these changes, several special cases were identified to improve the accuracy of the 

Today model for certain groups:

• Group 1 – The median year of construction for Group 1 is 1990, 1-inch foam sheathing 

was added to the walls, the ceiling insulation was increased to R38, and infiltration was 

increased from typical to tight in both the As-built and Today cases.

• Group 4 – The majority of these houses had slab floors and that model was used only 

here. A later vintage bungalow, a floored attic was assumed with R19 roof insulation both 

in the As-built and Today cases.

• Group 7 – This group is a Pre-1942 bungalow style with an upper half story in the attic. 

A floored attic was assumed for As-built. That assumption was not changed for the 

Today case because floored attics are typically not insulated beneath the floor. In this 

case, there were very short interzonal walls that are inaccessible and therefore 

uninsulated. 

• Group 11 – This is the largest category of homes representing the lakeshore mansions. 

Electricity consumption was beyond that predicted at an MEL of 1.5. The MEL was 

increased to 2.0 presumably for the increased number of electronic devices.

• Group 14 – This is the only group with a full unfinished attic. A floored attic was 

modeled for the As-built case, typical for bungalows. For the Today case, R3 roof 

insulation was added to reflect an average insulation value that would be added if the 

attic were partially finished.

4 Results

The result of the BEopt modeling effort was that every group had a source EUI within 10% of 

the measured value provided by CNT Energy—the PARR team’s goal. It must be emphasized 

that some of the modeling assumptions were made with the 10% agreement goal in mind, but 

based on reasonable insights into the group construction detail. Figure 4 shows the EUI values 

across the As-built, Today, CNT Energy data, and the Upgrade cases. This figure shows good 

agreement between modeling results and CNT Energy data, the difference between the As-built 

assumption and the Today assumption, and the potential for energy savings in the Upgrade case.

Figure 5 shows similar comparisons for gas energy use, in therms. Gas energy use reduction 

drives the source EUI reduction in this cold climate.
24

Figure 4. Source EUI from all scenarios - As-built, Today, CNT, BEopt Upgrade

Figure 5 Therms from all scenarios - As-built, Today, CNT, BEopt Upgrade
25

Table 11, below, shows the percent difference between the modeled and CNT utility data on

Source EUI, Therms, and kWh. With this agreement, the project moved on to selection of the top 

three candidates for field implementation.

Table 11. BEopt Today Case Model Results by Group Compared to CNT Data

Source EUI, Btu/sq. ft. Gas in Therms Electricity in kWh

GROUP BEopt, 

Today

CNT 

Mean

Dev, 

%

BEopt, 

Today

CNT 

Mean

Dev, 

%

BEopt, 

Today

CNT 

Mean

Dev, 

%

1 132.7 126.2 5% 1161.5 1077.0 8% 9074.7 8887 2%

2 164.1 176.1 -7% 1146.5 1205.0 -5% 9159.2 10076 -9%

3 118.7 120.2 -1% 1502.9 1446.0 4% 11607.5 12482 -7%

4 196.4 192.3 2% 1215.7 1212.0 0% 9254.1 8859 4%

5 195.1 198.2 -2% 1350.6 1344.0 0% 9227.1 9643 -4%

6 155.2 147.7 5% 1712.9 1553.0 10% 11533.5 11714 -2%

7 224.7 227.8 -1% 1430.6 1442.0 -1% 8724.6 8927 -2%

8 177.1 169.3 5% 1940.9 1757.0 10% 10607.6 11062 -4%

9 132.0 135.7 -3% 1209.5 1217.0 -1% 9203.6 9719 -5%

10 193.9 199.1 -3% 1473.6 1480.0 0% 8771.6 9321 -6%

11 111.8 114.0 -2% 1706.0 1749.0 -2% 14733.4 14914 -1%

12 191.0 199.0 -4% 1204.6 1268.0 -5% 8256.8 8483 -3%

13 163.9 172.0 -5% 1395.6 1467.0 -5% 9367.3 9802 -4%

14 216.4 222.9 -3% 1578.7 1608.0 -2% 8624.4 9050 -5%

15 168.6 164.8 2% 2034.9 1913.0 6% 10869.8 11348 -4%

4.1 Selection Criteria

PARR identified three important criteria to use in identifying the top three housing groups to 

target for retrofit. They are:

• Largest potential for cost-effective retrofit

• Highest energy use intensity

• Frequency of the housing type.

The first criteria are met through the creation of BEopt retrofit packages. BEopt was given a 

standard list of potential retrofit measures for infiltration, ceiling or roof insulation, space heating 

efficiency, space cooling efficiency, and water heater efficiency. Wall insulation and window 

upgrades were considered but were not selected for any case due to the high cost of the measure. 

Space cooling efficiency upgrade was modeled for several cases but was not selected by BEopt, 

presumably because of the short cooling season in Chicago.

The second and third criteria are satisfied through calculating energy savings as a percentage of 

source EUI and using the number of houses in the calculation of total energy savings.
26

4.2 Model Results

A description of each house and the upgrades proposed from the BEopt modeling is provided in 

the remainder of this section.

Group 1: Brick, 1978-Present, 1 to 1.5 stories (no split level)

Mean finished square footage: 1741

BEopt Results: 

Category Today Upgrade

Infiltration Tight No change

Unfinished Attic Ceiling R38 Fiberglass Batts, Vented Ceiling R49 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 80% Furnace No change

Water Heater Gas .54 EF No change

Discussion:

For this group, BEopt chose increasing insulation levels in the attic as the only cost-effective 

upgrade, likely because this group represents the newest construction with low infiltration and 

good equipment efficiency. 

Group 2: Brick, 1978-Present, Split level (1.5 stories)

Mean finished square footage: 1404
27

BEopt Results: 

Category Today Upgrade

Infiltration Typical Tight

Unfinished Attic Ceiling R30 Fiberglass Batts, Vented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 80% Furnace No change

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this group, BEopt chose upgrading infiltration levels to tight (Group 2 was modeled as tight) 

because houses above 1 story best matched their EUI when modeled as typical. Increasing attic 

insulation levels slightly was cost effective (adding R8 to the existing batts) to a baseline of R38 

(as in Group 1) was also cost effective. Increasing water heater EF may have been chosen 

because of the low cost of the insulation upgrade.

Group 3: Brick, 1978-Present, 2 stories

Mean finished square footage: 2506

BEopt Results: 

Category Today Upgrade

Infiltration Typical Tight

Unfinished Attic Ceiling R38 Fiberglass Batts, Vented No change

Furnace/Boiler Gas, AFUE 80% Furnace No change

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this group, BEopt chose upgrading infiltration levels to tight (Group 3 was modeled as tight) 

because houses above 1 story best matched their EUI when modeled as typical. Increasing attic 

insulation levels slightly was not cost effective likely because the R38 baseline was modeled. 

Increasing the water heater EF may have been chosen because of the low cost of the infiltration 

upgrade. 
28

Group 4: Brick, 1942-1978, 1 to 1.5 stories (no split level)

Mean finished square footage: 1217

BEopt Results:

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic Ceiling R19 Fiberglass Blown-In, Vented

Roof R19 Fiberglass No change

Furnace/Boiler Gas, AFUE 78% Furnace No change

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this 1942–1978 group, BEopt chose upgrading infiltration levels one step to typical because 

a two-step upgrade was not considered realistic for this vintage and was not modeled. Bungalow 

attic insulation was modeled as part ceiling (where the attic was not covered by the finished attic 

space) and part roof. The roof insulation level was constrained by the roof construction but 

BEopt did not choose to increase ceiling insulation, likely because of the marginal returns for the 

small area. Further modeling will be done in this area. Increasing the water heater EF may have 

been chosen because of the low cost of the infiltration upgrade.

Group 5: Brick, Pre-1978, Split level (1.5 stories)

Mean finished square footage: 1299
29

BEopt Results:

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic Ceiling R19 Fiberglass Blown-In, Vented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 78% Furnace Gas, AFUE 92.5% Furnace

Water Heater Gas .54 EF No change

Discussion:

For this pre-1978 group, BEopt chose upgrading infiltration levels one step to typical because a 

two-step upgrade was not considered realistic for this vintage and was not modeled. Attic 

insulation was brought up to the R38 level as in some of the cases above. BEopt chose to 

increase the furnace efficiency in this case rather than the water heater efficiency possibly due to 

the large thermal envelope area compared to the floor area of the house.

Group 6: Brick, 1942-1978, 2 stories

Mean finished square footage: 2059

BEopt Results:

Category Today Upgrade

Infiltration Typical No change

Unfinished Attic Ceiling R19 Fiberglass Blown-In, Vented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 78% Furnace Gas, AFUE 92.5% Furnace

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this 1942-1978 2-story group, BEopt did not chose to upgrade infiltration but upgraded all 

other categories. Infiltration for this house best fit the EUI data when modeled as typical and 

BEopt did not chose to upgrade that level. Attic insulation was brought up to the R38 level as in 

some of the cases above. BEopt chose to increase the furnace efficiency in this case possibly due 

to the large thermal envelope area compared to the floor area of the house. Water heater 

efficiency was increased possibly because this is a larger house with more bedrooms and more 

occupants.
30

Group 7: Brick, Pre-1942, 1 to 1.5 stories (no split level)

Mean finished square footage: 1141

BEopt Results: 

Category Today Upgrade

Infiltration Very Leaky Leaky

Unfinished Attic Ceiling R7 Fiberglass Blown-In, Vented; R19 

Fiberglass Roof Insulation No change

Furnace/Boiler Gas, 80% AFUE Boiler Gas, 95% AFUE Boiler

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this pre-1942 bungalow-style house, the results were similar to the 1942-1978 bungalow 

above: infiltration upgraded one level, ceiling insulation unchanged due to the constraint in roof 

insulation and small area of ceiling insulation. In this case, all the equipment was upgraded. The 

boiler was likely upgraded because the walls are uninsulated and heating systems are a costeffective upgrade. Upgrading the water heater in this small house does not seem to be cost 

effective; PARR will investigate that upgrade further. 
31

Group 8: Brick, Pre-1942, 2 stories

Mean finished square footage: 1884

BEopt Results:

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic Ceiling R7 Fiberglass Blown-In, Vented Ceiling R30 Fiberglass Blown-In, Vented 

Furnace/Boiler Gas, 80% AFUE Boiler Gas, 95% AFUE Boiler

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this pre-1942 2 story, BEopt chose to upgrade all four categories. The infiltration upgraded 

one level because PARR believes a two-level upgrade is unreasonable and it was not modeled. 

The insulation was upgraded to R30 in this case instead of R38, possibly because of the poor 

performance of the insulation in the perimeter of the attic due to the low-slope roof. In this case, 

all the equipment was upgraded. The boiler was likely upgraded because the walls are 

uninsulated and heating systems are a cost-effective upgrade. Upgrading the water heater in this 

mid-size house may be cost effective due to the number of bedrooms.

Group 9: Frame, 1978-Present, 1 to 1.5 stories (no split level)

Mean finished square footage: 1801
32

BEopt Results:

Category Today Upgrade

Infiltration Typical No change

Unfinished Attic Ceiling R38 Fiberglass Batts, Vented No change

Furnace/Boiler Gas, AFUE 78% Furnace Gas, AFUE 92.5% Furnace

Water Heater Gas .54 EF No change

Discussion:

For this post-1978 house, BEopt chose to upgrade only the furnace. The typical infiltration level 

may be suitable for this house. The ceiling insulation level at R38 is a common optimum level as 

in the other groups. Increasing the furnace efficiency may be cost effective because of the higher 

cost of insulating the large attic. The water heater was not upgraded in this case likely because of 

the cost of increasing the furnace in this recent vintage house.

Group 10: Frame, All years, Split level (1.5 stories)

Mean finished square footage: 1349

BEopt Results: (note – BEopt does not draw split level houses for drawing at right)

Category Today Upgrade

Infiltration Very Leaky Leaky

Unfinished Attic

Ceiling R7 Fiberglass Blown-In, Vented 

Roof R19 Fiberglass

Ceiling R38 Fiberglass Blown-In, Vented

Roof R19 Fiberglass

Furnace/Boiler Gas, 80% AFUE Boiler Gas, 95% AFUE Boiler

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

Group 10 was modeled as a 1942 frame bungalow-style house because it best fit the EUI 

numbers from the field. Only the back half was modeled as a 1.5 story to match the split level 

description (note BEopt does not draw split-level houses). The results were similar to the 1942 

Group 7 bungalow above, except the insulation level was increased: The infiltration upgraded 

one level as constrained by the modelers and the ceiling insulation was upgraded, likely due to 

the large ceiling area in the front of the house that had only R7 insulation on it. Again, in this 
33

case, all the equipment was upgraded. The boiler was likely upgraded because the walls are 

uninsulated and heating systems are a cost-effective upgrade. Upgrading the water heater in this 

small house does not seem to be cost effective; PARR will investigate that upgrade further.

Group 11: Frame, 1978-Present, 2 stories

Mean finished square footage: 3178

BEopt Results: 

Category Today Upgrade

Infiltration Typical Tight

Unfinished Attic Ceiling R38 Fiberglass Batts, Vented No change

Furnace/Boiler Gas, AFUE 80% Furnace No change

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

Identical to Group 3, BEopt chose upgrading infiltration levels to tight because houses above 1 

story best matched their EUI when modeled as typical and only a 1-level increase was permitted. 

Increasing attic insulation levels slightly was not cost effective likely because the R38 baseline 

was modeled. Increasing the furnace efficiency was not cost effective due to the good insulation 

level in the thermal envelope. Increasing the water heater EF may have been chosen because of 

the low cost of the infiltration upgrade.
34

Group 12: Frame, 1942-1978, 1 to 1.5 stories (no split level)

Mean finished square footage: 1185

BEopt Results:

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic Ceiling R19 Fiberglass Blown-In, Vented Ceiling R49 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 78% Furnace No change

Water Heater Gas .54 EF No change

Discussion:

This 1942–1978 group was modeled as a single story to best match the EUI, unlike group 4. 

BEopt chose upgrading infiltration levels one step to typical because a two-step upgrade was not 

considered realistic for this vintage and was not modeled. BEopt chose a higher level of attic 

insulation due to the large flat ceiling area and partially insulated walls. The furnace was not 

upgraded in this case likely due to the lower load for this smaller house with good attic 

insulation. The water heater was likely not upgraded due to the lower occupancy numbers with 

fewer bedrooms.

Group 13: Frame, 1942-1978, 2 stories

Mean finished square footage: 1586
35

BEopt Results: 

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic

Ceiling R11 Fiberglass Blown-In, 

Vented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, AFUE 78% Furnace Gas, AFUE 92.5% Furnace

Water Heater Gas .54 EF No change

Discussion:

For this 1942-1978 2-story group, and unlike Group 6, BEopt upgraded all categories except the 

water heater. Infiltration was upgraded to typical as in most cases. Attic insulation was brought 

up to the R38 level as in many of the cases above. BEopt chose to increase the furnace efficiency 

in this case possibly due to the large thermal envelope area compared to the floor area of the 

house. The water heater was not upgraded in this case.

Group 14: Frame, Pre-1942, 1 to 1.5 stories

Mean finished square footage: 1254

BEopt Results:

Category Today Upgrade

Infiltration Very Leaky Leaky

Unfinished Attic Floored R3 roof insulation unvented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, 80% AFUE Boiler Gas, 95% AFUE Boiler

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this pre-1942 1-story house, infiltration was upgraded one level and ceiling insulation was 

increased due to the large flat mostly uninsulated ceiling. In this case, all the equipment was 

upgraded. The boiler was likely upgraded because the walls are uninsulated and heating systems 

are a cost-effective upgrade. Upgrading the water heater in this small house may be cost effective 

because wall insulation was not considered.
36

Group 15: Frame, Pre-1942, 2 stories

Mean finished square footage: 2058

BEopt Results:

Category Today Upgrade

Infiltration Leaky Typical

Unfinished Attic

Ceiling R7 Fiberglass Blown-In, 

Vented Ceiling R38 Fiberglass Blown-In, Vented

Furnace/Boiler Gas, 80% AFUE Boiler Gas, 95% AFUE Boiler

Water Heater Gas .54 EF Gas Premium (0.67 EF)

Discussion:

For this pre-1942 2 story, as in Group 8, BEopt chose to upgrade all four categories. The 

infiltration upgraded one level because PARR believes a two-level upgrade is unreasonable and 

it was not modeled. The insulation was upgraded to R38 in this case instead of R30, possibly 

because of the better performance of the insulation in the perimeter of the attic due to the hip 

roof design. In this case, all the equipment was upgraded. The boiler was likely upgraded 

because the walls are uninsulated and heating systems are a cost-effective upgrade. Upgrading 

the water heater in this mid-size house may be cost effective due to the number of bedrooms.

4.3 Analysis

The potential source energy reduction for each group was calculated using BEopt output reports

for gas and electric site energy reduction and converting the values to source energy using 

multipliers for Chicago. Table 12, below, provides the percentage source energy reduction by 

group and then ranked to identify the highest percentage reduction. Appendix III contains 

detailed tables and graphs showing energy savings in therms, source EUI, and kWh.

The top Source EUI energy-savings percentage by group are groups 14, 15, and 8 representing 

the Pre-1942 frame bungalow, pre-1942 frame 2 story, and the pre-1942 brick 2-story houses. 

This analysis reflects the first two criteria needed to determine the target groups for retrofit. 
37

Table 12. Source EUI Reduction Percentage by Group

Group Source EUI Reduction, %5 Rank

14 28% 1

15 22% 2

8 20% 3

10 19% 4

7 19% 5

6 11% 6

12 11% 7

13 11% 8

11 9% 9

5 9% 10

3 9% 11

4 8% 12

2 7% 13

9 6% 14

1 5% 15

The third criteria applies the optimal energy saving to the number of homes in a group and then 

by size of the home to arrive at an annual savings potential in millions of Btu for each group. 

Table 13, below provides the final rank by group using that metric. 

Table 13. Final Rank by Group

Group Number of homes Source EUI 

Savings %

Total Source 

Energy Savings

(million Btu)

Rank

14 48365 28% 3,718,320 1

12 101957 11% 2,471,892 2

7 50239 19% 2,409,359 3

4 77435 8% 1,369,018 4

8 17629 20% 1,179,926 5

15 12479 22% 950,418 6

6 20755 11% 738,176 7

5 26445 9% 638,185 8

3 20530 9% 535,369 9

13 16411 11% 474,008 10

10 9225 19% 445,641 11

11 4544 9% 140,783 12

1 10856 5% 132,042 13

 5 For later discussion: BEopt does not identify any cost-effective retrofit packages that will lead to 30% source 

savings.
38

Group Number of homes Source EUI 

Savings %

Total Source 

Energy Savings

(million Btu)

Rank

2 8417 7% 130,548 14

9 7318 6% 99,835 15

The result of the analysis then identifies the following groups as the top three groups in the 

Chicagoland area for retrofit:

1) Group 14: Frame, Pre-1942, 1 to 1.5 stories

2) Group 12: Frame, 1942-1978, 1 to 1.5 stories

3) Group 7: Brick, Pre-1942, 1 to 1.5 stories

These three groups include 46% of the housing stock in Cook County, and represent the potential 

for over 100 million therms of source energy savings per year6.

5 Conclusions

In this study, PARR identified 15 groups that cluster the Cook County, Illinois, single-family 

detached houses by vintage, construction detail, and energy use intensity. The team further 

characterized each group using assessor data and utility energy billing data, and used this data to 

build three BEopt cases for each group: As-built, Today, and with Upgrade using the most costeffective measures. The BEopt analysis predicts significant energy savings in three 1 to 1.5 story 

groups: pre-1942 brick, pre-1942 frame, and 1942-1978 brick construction. The groups save 

28%, 19%, and 11% of source energy respectively, and because of the large number of these 

houses across the geographic area, they represent the first, second, and third largest energy 

saving potential by housing type. PARR identifies these three groups as those best matching the 

criteria set forth in this study.

Next year, PARR will take these results into the field to improve the assumptions used, validate 

the model, gather data on the actual upgrades between the As-built and Today cases, and develop 

a better retrofit cost database for these buildings. PARR also expects to explore the cost

effectiveness of additional measures that could be used to achieve the 30% energy savings target 

for these homes, and to better define and document the costs and measured savings of singlefamily home retrofits. This will help: (1) increase visibility of the measures to energy efficiency 

portfolios of utility companies, (2) provide achievable savings predictions based on home type to 

single-family homeowners who are interested in cost-effective measures, and (3) create the most 

cost-effective retrofit package to market to those homeowners.

The following research questions were addressed in this project: 

What are the most common housing types in Cook County? Fifteen groups were 

identified and their populations are presented in this report.

What are the energy use characteristics of these housing types? Source and site 

energy use for each group are provided in this report.

 6 If every home in Cook County that is a part of the top three groups were to be retrofitted.
39

Can large datasets be used to identify cost-effective retrofit opportunities? PARR 

was successful in segmenting nearly 500,000 buildings into 15 groups and identifying

retrofit opportunities.

What are the types of housing to target for retrofit packages? This topic is covered in 

some depth in the Analysis section.

Do identified databases provide sufficient detail for modeling inputs? PARR was 

able to model the 15 groups to within 10% of measured EUI by making reasonable 

assumptions regarding construction characteristics and upgrades since construction.

What housing characteristics are most significant toward determining cost

effectiveness of retrofit? Through statistical analysis and three clustering techniques, the 

characteristics in the CNT Energy dataset found to be most significant are the home 

vintage, construction type, and size.

What is the relationship between housing type energy intensity and potential costeffective energy savings? PARR identified that the higher energy-intensive structures 

were the best opportunity for upgrade, but factoring in the cost to upgrade and the size of 

the population provided target groups that were not always the most energy intensive or 

the most cost effective. The outcome of this study is a methodology to customize 

prescriptive retrofit packages to distinct housing groups at scale.

Although the housing types presented here and the retrofit packages presented are specific to the 

cold climate of northern Illinois, the segmentation methodology presented in this report is 

intended to be replicable elsewhere. This approach can have dramatic impact on how broad-scale 

retrofit implementation programs are developed, implemented and brought to scale.
40

References

Cook County Assessor. http://cookcountyassessor.com/

ICC (2012). International Energy Conservation Code. Washington, D.C. International Code 

Council.

Kalensky, D. (2012) AHRI Furnace Shipments by Efficiency (internal GTI memorandum)

Kelso, J., (2003). U. S. Department of Energy. Incorporating Water Heater Replacement into the 

Weatherization Assistance Program, An Information Toolkit

LBNL Study on Appliance Efficiency Standards. http://ees.ead.lbl.gov/node/2

U. S. Bureau of the Census. http://www.census.gov/

U. S. Department of Energy. (2008). History of Federal Appliance Standards. Accessed March 

2012: http://www1.eere.energy.gov/buildings/appliance_standards/history.html.

Zimring et al. (2011) “Delivering Energy Efficiency to Middle Income Single Family 

Households.” Environmental Energy Technologies Division, Lawrence Berkeley National 

Laboratory.
41 

Appendix I – Detail on Housing Group Characteristics

This appendix provides the detail on housing group characteristics that were used for the basis of 

developing the 15 groups and then carried forward into the BEopt modeling assumptions. 

GROUP Construction Year Stories

1 Brick 1978-Present 1 to 1.5 (no split level)

2 Brick 1978-Present 1.5 - split level

3 Brick 1978-Present 2

4 Brick 1942-1978 1 to 1.5 (no split level)

5 Brick Pre-1978 1.5 - split level

6 Brick 1942-1978 2

7 Brick Pre-1942 1 to 1.5 (no split level)

8 Brick Pre-1942 2

9 Frame 1978-Present 1 to 1.5 (no split level)

10 Frame All 1.5 - split level

11 Frame 1978-Present 2

12 Frame 1942-1978 1 to 1.5 (no split level)

13 Frame 1942-1978 2

14 Frame Pre-1942 1 to 1.5 (no split level)

15 Frame Pre-1942 2

Square Footage

GROUP N Obs % of Population Mean Std Dev Median

1 10856 2.5% 1741 474 1720

2 8417 1.9% 1404 264 1368

3 20530 4.7% 2506 673 2425

4 77435 17.9% 1217 354 1136

5 26445 6.1% 1299 274 1256

6 20755 4.8% 2059 620 1987

7 50239 11.6% 1141 360 1072

8 17629 4.1% 1884 549 1784

9 7318 1.7% 1801 637 1641

10 9225 2.1% 1349 282 1303

11 4544 1.1% 3178 909 3146

12 101957 23.6% 1185 301 1114

13 16411 3.8% 1586 565 1427

14 48365 11.2% 1254 357 1176

15 12479 2.9% 2058 624 1962
42 

Year built Site EUI

GROUP Mean Std Dev Median Mean Std Dev Median

1 1991 7 1990 81.8 25 78.4

2 1987 6 1987 112.6 26.2 109.9

3 1992 7 1993 76.7 18.3 74.5

4 1959 8 1958 129.6 39.8 123.7

5 1968 6 1968 131.5 33.4 127.2

6 1962 11 1964 99.8 29.7 94.5

7 1917 14 1921 161.3 49.2 157.1

8 1911 16 1910 117.3 32.4 113.6

9 1992 8 1991 91.8 32.4 85.5

10 1966 8 1964 136.6 35.1 132.7

11 1996 6 1998 73.8 20.7 70.4

12 1958 7 1958 135.3 37.7 131.4

13 1951 7 1950 119.2 31.8 116.4

14 1924 10 1926 158.9 44.6 156.2

15 1922 14 1923 116 30.1 112.8

Therms kWh

GROUP Mean Std Dev Median Mean Std Dev Median

1 1077 351 1033 8887 4097 8122

2 1205 276 1174 10076 3771 9547

3 1446 406 1393 12482 4914 11721

4 1212 379 1161 8859 4065 8189

5 1344 360 1298 9643 3922 9041

6 1553 435 1499 11714 5003 10960

7 1442 433 1400 8927 4382 8265

8 1757 525 1696 11062 5213 10214

9 1217 409 1171 9719 4454 8903

10 1480 372 1449 9321 3860 8733

11 1749 502 1681 14914 5678 14209

12 1268 356 1228 8483 3910 7858

13 1467 424 1406 9802 4653 8952

14 1608 445 1570 9050 4463 8337

15 1913 549 1857 11348 5374 10460
43 

Central 

Gas 

Furnace

Central 

Gas 

Furnace

Gas 

Boiler

Gas 

Boiler

CentralAC CentralAC Window 

AC or 

None

Window 

AC or 

None

GROUP n % n % n % n %

1 10836 99.82% 20 0.18% 9401 86.60% 1455 13.40%

2 8413 99.95% 4 0.05% 6345 75.38% 2072 24.62%

3 20514 99.92% 16 0.08% 18375 89.50% 2155 10.50%

4 73861 95.38% 3574 4.62% 27032 34.91% 50403 65.09%

5 25504 96.44% 941 3.56% 14745 55.76% 11700 44.24%

6 19794 95.37% 961 4.63% 12982 62.55% 7773 37.45%

7 39810 79.24% 10429 20.76% 5342 10.63% 44897 89.37%

8 11696 66.35% 5933 33.65% 3800 21.56% 13829 78.44%

9 7295 99.69% 23 0.31% 6078 83.06% 1240 16.94%

10 8505 92.20% 720 7.80% 5528 59.92% 3697 40.08%

11 4529 99.67% 15 0.33% 4343 95.58% 201 4.42%

12 95745 93.91% 6212 6.09% 43400 42.57% 58557 57.43%

13 15511 94.52% 900 5.48% 6989 42.59% 9422 57.41%

14 25459 52.64% 22906 47.36% 5147 10.64% 43218 89.36%

15 5993 48.02% 6486 51.98% 2867 22.97% 9612 77.03%

GROUP Attic Description

Full and 

Apartment

Full and Living 

Area

Full and 

Unfinished

None Partial 

&Living 

Area

Partial and 

Unfinished

Total

1 0 385 93 9679 454 222 10833

2 0 9 15 8254 16 79 8373

3 0 79 305 19015 477 581 20457

4 0 6488 5799 52727 2652 9469 77135

5 0 27 444 22625 106 3190 26392

6 0 222 767 17321 302 2080 20692

7 7 13549 8843 19160 3212 5188 49959

8 3 1117 3331 8615 832 3620 17518

9 0 132 55 6725 181 210 7303

10 0 20 150 7934 52 1039 9195

11 0 39 101 4020 141 232 4533

12 0 8585 11280 68057 2028 11641 101591

13 0 150 972 13060 126 2055 16363

14 4 10277 17722 10484 3189 6564 48240

15 0 680 2192 6387 541 2627 12427
44 

GROUP Basement Description

Crawl Full and 

Apartment

Full and 

Rec 

Room

Full 

and 

Unfinished

Partial 

and 

Apartment

Partial 

and 

Rec 

Room

Partial 

and 

Unfinished

Slab Total

1 687 0 677 3756 0 712 2229 2772 10833

2 42 0 396 22 0 7707 183 23 8373

3 628 0 1484 11021 0 817 5267 1240 20457

4 11430 1 10330 18637 0 5378 6839 24520 77135

5 46 0 734 85 0 25205 247 75 26392

6 1311 0 2105 5093 0 3175 4755 4253 20692

7 1143 8 7548 27062 1 759 2305 11133 49959

8 261 0 2315 11279 0 421 1431 1811 17518

9 159 0 1063 3587 0 309 1016 1169 7303

10 9 0 437 27 0 8620 94 8 9195

11 38 1 851 2837 0 196 501 109 4533

12 4264 3 26130 59221 0 2607 4195 5171 101591

13 188 0 4972 8567 0 979 1194 463 16363

14 206 4 10890 34490 1 635 858 1156 48240

15 47 0 2598 8381 0 374 828 199 12427
45 

Appendix II – BEopt Modeling Assumptions Tables

As-built

Building

Lot size/distance to 

neighbor

Size Distance to 

Neighbor

Age Note

pre-1942 25 5 90 25x125 lot, house 20ft wide

1942-1978 50 10 50

post-1978 75 20 15

Beds/Baths and Garage

Group Garage Bed Bath

1 2 car attached 3 2.5

2 2 car attached 3 2.5

3 2 car attached 4 2.5

4 2 car detached 3 1

5 2 car attached 3 1.5

6 2 car attached 4 2.5

7 2 car detached 3 1

8 2 car detached 4 2.5

9 2 car attached 3 2.5

10 2 car detached 3 1.5

11 2 car attached 4 2.5

12 2 car detached 3 1

13 2 car detached 3 1.5

14 2 car detached 3 1

15 2 car detached 4 2.5

Operation Setpoint 

Heating

Setpoint 

Cooling

MEL MGL

pre-1942 70 72 Baseline (1.0) Baseline (1.0)

1942-1978 70 72 Baseline (1.0) Baseline (1.0)

post-1978 70 72 Baseline (1.0) Baseline (1.0)

Misc HW 

Loads

Natural Ventilation

pre-1942 Sink Aerators Benchmark

1942-1978 Sink Aerators Benchmark

post-1978 Sink Aerators Benchmark
46 

As-built

Walls/Ceilings/Roofs

Brick (outside to 

inside)

Wall construction

pre-1942 4 inch brick, 1 inch airspace, 4 inch brick, 1 inch lath (no insulation), 5/8 drywall

1942-1978 4 inch brick, 1 inch airspace, 4 inch brick, 1 inch lath (R3 fiberglass), 5/8 inch drywall

post-1978 (no CMU) 4 inch brick veneer, 1/2 inch wood sheathing, 2x4 stud wall with R-11 insulation, 1/2 drywall

Frame

Wall construction

pre-1942 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall no insulation, 5/8 inch drywall

1942-1978 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall R7 insulation, 5/8 inch drywall

post-1978 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall with R11 insulation, 1/2 inch 

drywall

Insulation Interzonal Interzonal

Levels Brick Wall Frame Wall Ceiling Insulation Walls Floors

pre-1942 0 0 0 0 0

1942-1978 3 7 11 7 11

post-1978 Brick vnr+R11 

stud 

11 30 11 19

Foundation/Floors Basement Crawl Slab

pre-1942 uninsulated unin/ventil

1942-1978 uninsulated unin/ventil uninsulated

post-1978 uninsulated unin/ventil

Windows & Shading

pre-1942 Double Clear (window+storm)

1942-1978 Double Clear (window+storm)

post-1978 Double Clear (window+storm)

Air Flow Infiltration Infil. - 2 story Mechanical Ventilation

pre-1942 Very Leaky Leaky None

1942-1978 Leaky Typical Spot

post-1978 Typical Tight Spot

Major Appliances Dryers

pre-1942 none

1942-1978 gas
47 

As-built

post-1978 gas

Space Conditioning

Heating (gas) System Ducts

pre-1942 boiler 65% None

1942-1978 forced air 70% Typical/uninsulated

post-1978 forced air 78% Typical/uninsulated

Cooling

pre-1942 none

1942-1978 none

post-1978 SEER 10

Water Heating (gas)

pre-1942 0.48

1942-1978 0.48

post-1978 0.49

Today

Building

Lot size/dist to 

neighbor

Size Dist to 

Neighbor

Age Note

pre-1942 25 5 90 25x125 lot, house 20ft wide

1942-1978 50 10 50

post-1978 75 20 15

Beds/Baths and 

Garage

Group Garage Bed Bath

1 2 car attached 3 2.5

2 2 car attached 3 2.5

3 2 car attached 4 2.5

4 2 car detached 3 1

5 2 car attached 3 1.5

6 2 car attached 4 2.5

7 2 car detached 3 1

8 2 car detached 4 2.5

9 2 car attached 3 2.5

10 2 car detached 3 1.5
48 

Today

11 2 car attached 4 2.5

12 2 car detached 3 1

13 2 car detached 3 1.5

14 2 car detached 3 1

15 2 car detached 4 2.5

Operation Setpoint Heating Setpoint 

Cooling

MEL MGL

pre-1942 70 72 1.5 Baseline (1.0)

1942-1978 70 72 1.5 Baseline (1.0)

post-1978 70 72 1.5 Baseline (1.0)

Misc HW Loads Natural Ventilation

pre-1942 Sink Aerators Benchmark

1942-1978 Sink Aerators Benchmark

post-1978 Sink Aerators Benchmark

Walls/Clgs/Roofs

Brick (outside to

inside)

Wall construction

pre-1942 4 inch brick, 1 inch airspace, 4 inch brick, 1 inch lath (no insulation), 5/8 drywall

1942-1978 4 inch brick, 1 inch airspace, 4 inch brick, 1 inch lath (R3 fiberglass), 5/8 inch drywall

post-1978 (no CMU) 4 inch brick veneer, 1/2 inch wood sheathing, 2x4 stud wall with R-11 insulation, 1/2 

drywall

Frame

Wall construction

pre-1942 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall no insulation, 5/8 inch drywall

1942-1978 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall R7 insulation, 5/8 inch drywall

post-1978 white wood siding, 1/2 inch wood sheathing, 2x4 stud wall with R11 insulation, 1/2 inch 

drywall

Insulation Interzon

al

Interzonal

Levels Brick Wall Frame Wall Attic 

Insulation

Walls Floors

pre-1942 0 0 7 Blown 0 0

1942-1978 3 7 19 Blown 7 11

post-1978 Brick vnr+R11 

stud 

11 30 11 19
49 

Today

Foundation/Floors Basement Crawl Slab

pre-1942 uninsulated unin/ventil

1942-1978 uninsulated unin/ventil uninsulated

post-1978 uninsulated unin/ventil

Windows & Shading

pre-1942 Double Clear (window+storm)

1942-1978 Double Clear (window+storm)

post-1978 Double Clear (window+storm)

Air Flow Infiltration Infiltr - 2 story Mechanical Ventilation

pre-1942 Very Leaky Leaky None

1942-1978 Leaky Typical Spot

post-1978 Typical Tight Spot

Major Appliances Dryers

pre-1942 gas

1942-1978 gas

post-1978 gas

Space Conditioning

Heating (gas) System Ducts

pre-1942 boiler, 80% 

AFUE

None

1942-1978 Furnace 78% 

AFUE

Typical/uninsulated

post-1978 Furnace 80% 

AFUE

Typical/uninsulated

Cooling

pre-1942 SEER 10 - window units

1942-1978 SEER 10

post-1978 SEER 10

Water Heating

pre-1942 0.54

1942-1978 0.54

post-1978 0.54
50 

Special 

Cases

Group 1 Median built 1990 - increase walls by 1" foam sheathing, infiltration to tight, and ceiling to R38.

Group 4 Slab construction fit. Changed to floored attic, R19 (42-78) in roof for both As-built and today.

Group 7 Bungalow with upper half story. Added floored attic, no insulation (pre-42). R0 interzonal 

walls.

Group 11 MEL = 2 to match electric load (lakefront mansion).

Group 14 Only building with full/unfinished attic. Added floored attic As-built and flooring + R3 roof for 

today.

Upgrade (options evaluated by BEopt)

Insulation Interzonal Interzonal

Levels Brick Wall Frame Wall Attic 

Insulation

Walls Floors

pre-1942 R30 or 38 

blown 

1942-1978 R30 or 38 

blown 

post-1978 R30 or 38 

blown 

Space Conditioning

Heating (gas) System

pre-1942 Boiler - 95% AFUE

1942-1978 Furnace - 92.5% AFUE

post-1978 Furnace - 92.5% AFUE

Cooling

pre-1942

1942-1978 SEER 13

post-1978 SEER 13

Water Heating

pre-1942 Premium 

(0.67EF)

1942-1978 Premium 

(0.67EF)

post-1978 Premium 

(0.67EF)
51 

Appendix III – Detailed Results Tables

BEopt results are presented in this appendix in the same format as the data in Appendix I in order 

to compare CNT data with modeling results. 

Square Footage

GROUP N Obs % of Population BEopt CNT Mean Dev, %

1 10856 2.5% 1740 1741 0%

2 8417 1.9% 1404 1404 0%

3 20530 4.7% 2500 2506 0%

4 77435 17.9% 1196 1217 -2%

5 26445 6.1% 1304 1299 0%

6 20755 4.8% 2064 2059 0%

7 50239 11.6% 1140 1141 0%

8 17629 4.1% 1872 1884 -1%

9 7318 1.7% 1800 1801 0%

10 9225 2.1% 1342 1349 -1%

11 4544 1.1% 3168 3178 0%

12 101957 23.6% 1176 1185 -1%

13 16411 3.8% 1584 1586 0%

14 48365 11.2% 1248 1254 0%

15 12479 2.9% 2064 2058 0%
52 

Source EUI (kBtu/SF)

GROUP BEopt, As Built BEopt, Today CNT Mean Dev, % BEopt Upgrade Savings %

1 127.3 132.7 126.2 5% 125.7 5%

2 156.7 164.1 176.1 -7% 153.0 7%

3 117.6 118.7 120.2 -1% 108.2 9%

4 179.0 196.4 192.3 2% 181.6 8%

5 189.1 195.1 198.2 -2% 176.6 9%

6 141.5 155.2 147.7 5% 137.9 11%

7 216.2 224.7 227.8 -1% 182.6 19%

8 199.3 177.1 169.3 5% 141.4 20%

9 126.3 132.0 135.7 -3% 124.4 6%

10 242.1 193.9 199.1 -3% 157.9 19%

11 111.9 111.8 114.0 -2% 102.1 9%

12 181.5 191.0 199.0 -4% 170.4 11%

13 154.0 163.9 172.0 -5% 145.7 11%

14 222.5 216.4 222.9 -3% 154.8 28%

15 190.4 168.6 164.8 2% 131.7 22%

Therms (100kBtu)

GROUP BEopt, As Built BEopt, Today CNT Mean Dev, % BEopt Upgrade Savings %

1 1230.5 1161.5 1077.0 8% 1052.6 9%

2 1217.1 1146.5 1205.0 -5% 1014.9 11%

3 1473.9 1502.9 1446.0 4% 1279.6 15%

4 1290.5 1215.7 1212.0 0% 1064.9 12%

5 1597.5 1350.6 1344.0 0% 1143.6 15%

6 1865.7 1712.9 1553.0 10% 1405.6 18%

7 1676.7 1430.6 1442.0 -1% 1017.9 29%

8 2699.8 1940.9 1757.0 10% 1355.6 30%

9 1289.1 1209.5 1217.0 -1% 1084.5 10%

10 2366.8 1473.6 1480.0 0% 1047.0 29%

11 1696.6 1706.0 1749.0 -2% 1436.6 16%

12 1334.5 1204.6 1268.0 -5% 1005.6 17%

13 1544.5 1395.6 1467.0 -5% 1161.5 17%

14 1950.7 1578.7 1608.0 -2% 928.9 41%

15 2854.9 2034.9 1913.0 6% 1379.6 32%
53 

kWh

GROUP BEopt, As Built BEopt, Today CNT Mean Dev, % BEopt Upgrade Savings %

1 7594.0 9074.7 8887 2% 9051.2 0%

2 7587.9 9159.2 10076 -9% 9059.9 1%

3 11577.9 11607.5 12482 -7% 11455.1 1%

4 6373.8 9254.1 8859 4% 9120.9 1%

5 6285.0 9227.1 9643 -4% 9102.6 1%

6 7692.5 11533.5 11714 -2% 11366.2 1%

7 5522.9 8724.6 8927 -2% 8468.5 3%

8 6817.1 10607.6 11062 -4% 10308.0 3%

9 7542.6 9203.6 9719 -5% 9203.6 0%

10 5791.1 8771.6 9321 -6% 8600.0 2%

11 14743.0 14733.4 14914 -1% 14588.0 1%

12 5902.6 8256.8 8483 -3% 8021.7 3%

13 6554.1 9367.3 9802 -4% 9074.7 3%

14 5637.0 8624.4 9050 -5% 8075.7 6%

15 7076.7 10869.8 11348 -4% 10488.3 4%
DOE/GO-102012-3604 ▪ June 2012

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