NISTIR 7330 

A Collection of Homes to Represent 

the U.S. Housing Stock 

Andrew Persil), 

Bill/ding and Fire Research Laborato1)', NIJT 

Amy Musser 

Vandemllsser Des{l!,n LL.C 

Dennis Leber 

Iifonnation Technology Laborato1)', NUT 

Prepared for: 

U.S. Department of Housing and Urban Development 

Office of Healthy Homes and Lead Hazard Control 

W'ashin6>ton, DC 

August 2006 

U.S. DEPARTMENT OF COMMERCE 

Carlos ;\1. Gutierrez, Jecreta~)' 

TECHNOLOGY ADMINISTRATION 

Robert Cresanti, l:lldersecretol)' of Commerce/or TeclJll{j/~i}J 

NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY 

William A. Jeffrey, Director 
ABSTRACT 

In order to allow nationwide or regional analyses of ventilation and indoor air quality issues in 

residential buildings, a collection or "suite" of homes has been defined to represent the housing 

stock of the United States. This collection of dwellings is based on two residential housing 

surveys, the U.S. Department of Energy Residential Energy Consumptions Survey (RECS) and 

the U.S. Census Bureau American Housing Survey (AHS), both of which are conducted 

periodically to characterize the U.S. housing stock. The RECS dataset includes about 6000 U.S. 

residences, and the AHS covers about 60,000. Based on these datasets, just over 200 dwellings 

were defined that together represent 80 % of the U.S. housing stock. These dwellings are 

grouped into four categories: detached, attached, manufactured homes and apartments. This 

paper describes the RECS and AHS datasets and how they were used to define this collection. 

Among the key characteristics addressed in defining these dwellings are age, floor area, number 

of floors, foundation type and existence of a garage. In addition, this report describes multizone 

representations of the dwellings that were created in the airflow model CONT AM and are now 

available for analyses of residential ventilation, indoor air quality and energy issues. The report 

documents the data sources used to develop the models, describes each model, and summarizes 

the testing of the models to establish their validity. 

Keywords: database, housing, modeling, residential buildings, ventilation 
Table of Contents 

1. INTRODUCTION .......................................................................................... 1 

2. DATA SOURCES ............................................................................................ 1 

3. SAMPLE SELECTION ....................................................................................... 3 

4. MULTIZONE BUILDING REPRESENTATIONS ..................................................... 5 

5. CONTAM PROJECT FILES ................................................................................. 9 

6. CONCLUSIONS ........................................................................................... 11 

7. ACKNOWLEDGEMENTS .............................................................................. 12 

8. REFERENCES ............................................................................................ 13 

APPENDICES 

A. Exterior Leakage Data .............................................................................................................. 14 

B. House Characteristics .............................................................................................. 18 

BRAND NAME DISCLAIMER 

Certain trade names or company products are mentioned in the text to specify adequately the 

experimental procedure and equipment used. In no case does such identification imply 

recommendation or endorsement by the National Institute of Standards and Technology, nor 

does it imply that the equipment is the best available for the purpose. 
1. INTRODUCTION 

Concerns about residential indoor air quality (IAQ) have led to the consideration of a number of 

interventions to improve indoor environmental conditions, including mechanical ventilation, air 

cleaning and moisture control strategies. The U.S. Department of Housing and Urban 

Development (HUD) established the Healthy Homes Initiative (HUD 1999a) to "protect children 

from housing conditions that are responsible for multiple diseases and injuries" by addressing 

building deficiencies that contribute to these multiple hazards rather than dealing with one 

problem at a time. Included among the program activities are the following: demonstrating the 

effectiveness of mold and moisture remediation practices; demonstrating and evaluating housing 

repairs directed towards preventing asthma, lead poisoning and other threats to health and safety; 

conducting public education programs targeted to low and medium income households; and, 

- conducting research in support of the demonstration projects. Field studies and demonstration 

projects provide essential data on the potential IAQ impacts of such interventions in specific 

buildings. However, given the cost and complexity offield studies, simulation studies have also 

been used to investigate the impacts of various IAQ control measures (Emmerich et a1. 2003 and 

2005: Persily 1998; Emmerich and Persily 1996). This simulation work has also considered a 

relatively small number of buildings, making it difficult to draw general conclusions from the 

results. It is important to be able to assess the potential impact of IAQ controls on a larger scale, 

such as in a specific climate zone or even nationwide. Since determining such broad impacts 

through field testing would require an extensive and costly effort, modeling appears to be a more 

realistic option for drawing the types of conclusions on which policy decisions could be based. In 

order to obtain more reliable conclusions of a general nature and to support risk assessments, 

such modeling analysis needs to be performed on a set of buildings that is representative of the 

residential building stock. To this end, the National Institute of Standards and Technology 

(NIST) has undertaken an effort to define a representative collection of residential buildings 

based on a statistical analysis of the United States (US) housing stock. This paper describes the 

process by which these buildings were defined and their representation in the airflow and indoor 

air quality analysis program CONTAM (Walton and Dols 2005). Note that throughout this report 

the term "home" is used to describe individual housing units or dwellings, including apartment 

units within larger apartment buildings. 

2. DATA SOURCES 

In developing this collection of residential buildings, statistical analyses were performed on two 

residential building databases, the US Census Bureau's American Housing Survey (AHS) and 

the US Department of Energy's (DOE) Residential Energy Consumption Survey (RECS). Every 

other year the Census Bureau collects data via surveys and interviews to develop a housing 

inventory for HUD. The 1999 American Housing Survey is based on a representative sample of 

approximately 56,000 homes selected using a sampling method based on classifying all the 

counties in the US (HUD 1999b). The AHS is used to measure specific changes in the housing 

inventory and assess progress towards the goal of providing sustainable living conditions to all 

Americans. After collection of the survey data, the Census Bureau compiles all the data into a 

publicly available database on the American Housing Survey website, 

www.census.gov/hhes/www/housing/ahs/ahs.html. 

The US Department of Energy (DOE) Residential Energy Consumption Survey (RECS) is a 

collection of statistical information on housing units and their occupants in the United States, 

with emphasis on the consumption of and expenditures for energy (DOE 1999). The RECS 

survey is conducted by DOE roughly every three or four years and can be found at 

www.eia.doe.gov/emeulrecs/contents.htm1. The 1997 survey was used in this effort and 
incorporates data from approximately 5900 housing units. 

VARIABLE VARIABLE RANGES 

Unit Type Single, detached 

Single, attached 

Apartment 

Manufactured home 

Region Northeast 

Midwest 

South 

West 

Forced-air distribution Yes 

No 

Floor area * < 93 m2 (1000 ft2

) 

93 m2 t0186 m2 (1000 ft2 to 1999 fe) 

186 m2 to 279 m'" (2000 fe to 2999 ft2) 

> 279 m'" (3000 f!'") 

Occupants per household 1 

2 

3-4 

5-6 

7-10 

>10 

Central air conditioning Yes 

No 

Year built <1940 

1940-1949 

1950-1959 

1960-1969 

1970-1979 

1980-1989 

>1990 

Garage or carport ** Yes 

No 

Foundations type *** Basement 

Crawl space 

Slab 

Number of stories *** 1 

2 

~3 

* Does not Include apartment umts or SIngle, attached umts. 

** Does not include apartment units. 

Percenta.Ke 

AUS RECS 

72.4 62.9 

5.8 9.8 

16.1 21.1 

5.7 6.2 

16.6 19.4 

26.0 23.7 

34.2 35.4 

23.0 21.5 

63.2 53.4 

36.8 46.6 

14.0 29.0 

46.1 45.1 

21.7 13.0 

10.7 4.0 

24.3 25.2 

33.9 32.5 

31.6 32.2 

8.9 1O.11~51 

1.2 -- 0.1 -- 52.0 42.1 

48.0 57.9 

17.3 19.9 

7.4 9.3 

13.1 13.1 

14.4 14.9 

19.8 13.2 

6.4 6.2 

21.6 23.4 

56.4 53.7 

43.5 25.2 

44.6 32.7 

25.8 22.2 

28.7 22.6 

35.1 55.8 

35.1 39.8 

29.6 3.1 

*** RECS does not include apartment units, and both do not include manufactured homes. 

Table 1 Summary of data from AHS and RECS 

Given that the electronic format of the RECS database is easier to access and manipulate than the 

AHS database, the RECS data were used in the statistical analysis to define the representative 

suite of homes. However, the two surveys were compared to support the use of the AHS alone. 

The results of that comparison are shown in Table 1. Note that the two surveys differ in how they 

summarize the results for selected variables. For example floor area values in the AHS database 

2 
do not include apartments or attached homes. Therefore, to better compare the two datasets, 

some of the variables in Table 1 do not include all housing types as noted. Note also that for 

some of the variables, the total percentages do not add up to 100 % due to missing data. 

3. SAMPLE SELECTION 

The representative collection of homes was determined using a sampling scheme in which, for 

each of the four building types, a number of relevant building characteristics, or factors, in Table 

1 were considered over a discrete number of "levels". For example, housing unit floor area is a 

factor and different ranges of floor area constitute the levels. The factors and factor levels 

considered for each building type are listed in Table 2. For each building type, each factor level 

was crossed with all other factor levels resulting in a factorial layout of cells defining the 

"population" for each housing type. In other words, each cell is defined by a single level of each 

factor, for example a cell of detached homes is defined by whether or not it has a forced-air 

system, a floor area level, the year built, existence of a garage, foundation type and number of 

stories. The number of cells by building type are as follows: Single, Detached and Single, 

Attached - 432; Apartment Units - 400; and, Manufactured Homes - 16. The RECS database 

assigns a "weight" for each housing unit or cell that defines how many units it represents 

nationwide. These weights were aggregated across building characteristics to represent each 

housing unit, or cell, in the overall population of dwellings considered in this effort. The first 

step in the sampling process was, for each building type (e.g., single family), to sort the cells in 

descending order based on the cell's weight. Figure I shows the percentage of homes covered for 

each of the four housing types as a function ofthe number of cells included. Note that the 

percent coverage increases very quickly for the manufactured homes due to the smaller amount 

of variation among these buildings. For all housing types, increasing the number of cells reaches 

a point where increasing the sample size does not lead to a significant increase in coverage. 

100 I7--:---:::J~-:::::::::r=-:::::=+=~""":---, 

--Apartment 

-Attached 

ww,w,"" Detached 

- - - • Manufactured house 

~ 60 r.---~~~--------~--------~--------~-------4--------1 B 

r.r:: 

Ol) 

::: 

~ = 40'~~~ __ ~ ______ ~ ______ -r ______ -+ ______ -+ ____ --~ 

Q 

'-o 

-::: 

~ 

p 

Q.. o 20 Ht--~--~--------~--------~--------~------~--------I 

o ~------~------~------r-------~------~----~ o 50 100 150 

Sample Size 

200 250 

Figure I: Percentage coverage as a function of sample size 

300 

3 
VARIABLE RANGE 

VARIABLE OR LEVEL 

SINGLE F AMIL Y (attached and detache'!l 

Forced-air distribution Yes 

No 

Floor area, m2 (fe) < 149 (1600) 

149 to 223 (1600 to 2399) 

> 223 (2400) 

Year built <1940 

1940-1969 

1970-1989 

1990-1997 

Garl!&.e or carport Yes 

No 

Foundations type Basement 

Crawl~ce 

Slab 

Number of stories 1 

2 

~3 

APARTMENTS 

# of units in building 2-4 

5-9 

10-19 

20-39 

>40 

Floor area, mZ (fe) < 93 (1000) 

> 93 (1000) 

Year built <1940 

1940-1969 

1970-1989 

>1990 

Central heatil!g system Yes 

No 

MANUFACTURED HOMES 

Floor area, mZ (fe) < 149 i) 600) 

> 149 J160Ql 

Year built <1940 

1940-1969 

1970-1989 

>1990 

Central forced-air system Yes 

No 

Table 2 Cells for each housmg type 

The next step in the process was to select the cells, again for each of the four housing types, 

which encompass 80 % of the total number of units for that type. This approach led to unequal 

numbers of homes of each type, but comparable percentages of national coverage. Table 3 shows 

4 
the number of homes and the percent of the total represented for 80 % representation. Again, 

each home in the sample is defined by particular values of the variable levels in Table 2. 

Type of Housing Sample Size % Represented 

Single, detached 83 80.2 

Single, attached 53 80.2 

Apartments 69 80.4 

Manufactured homes 4 80.4 

Total 209 80.2 

Table 3 Summary of selected housing 

4. MULTIZONE BUILDING REPRESENTATIONS 

Once the 209 homes or dwellings were defined, floor plans were developed for subsequent entry 

into a CONTAM model of each house. These floor plans were based on the following variables 

from the AHS and RECS surveys: housing type, number of stories, heated floor area, year built, 

foundation type, garage, type of heating equipment, number of bedrooms, number of bathrooms, 

and number of other rooms. For apartment buildings, the total number of units in each building 

was also considered. The discussion below explains how each of these variables was considered 

in developing the multizone representation. 

Type of Household: The four household types are detached, attached, apartment buildings, and 

manufactured homes. Detached and manufactured homes are modeled as free standing 

structures. Each attached home is modeled as a single townhouse with no leakage paths in the 

sidewalls between units. This arrangement is consistent with a center unit that has no net airflow 

or contaminant gain or loss from the adjacent unit. While having no leakage between adjacent 

units is not necessarily a good assumption in all cases, it is a practical necessity given the lack of 

data describing the airtightness of these walls and in order to keep the models manageable. 

Apartment buildings are modeled as entire buildings made up of identical apartment units, with 

leakage between units included. 

Number of Stories: Attached and detached homes are listed in the surveys as one story, two or 

more stories, or "other". Homes in the "other" category are most commonly split level, and are 

modeled as such. To model a split-level home, it is necessary to include in the CONTAM model 

an extra level that is one-half story high. Each room is then modeled at its full height through the 

use of phantom zones, a CONTAM feature that allows a zone to extend through multiple 

building levels. Apartment buildings are divided into five height categories: 1, 2, 3-5, 6-15 and 

16+. One and two story buildings are modeled as such. The 3-5 story category is modeled as a 

four-story building, except for one case where a building with 6 units is modeled as three stories 

with two units on each floor. The 6-15 story category is modeled at a ten-story building, except 

in the case of one building with only 6 units, which was modeled as a 6-story building. The 16-

story building is modeled as 20 stories. All floors of multistory apartment buildings are modeled 

as identical, except for minor differences related to entrances on the first floors. All apartment 

buildings with four or more stories are modeled with elevators, except for the 6-story building 

with only one unit per floor. 

Heated Floor Area: In all of the models, the heated floor area corresponds to the above ground 

portion of the home. For apartment buildings, the heated floor area given is per unit, and a 

5 
reasonable amount of additional space for corridors, lobbies, etc. is added to the whole building 

model. The set of 209 dwellings are divided into either two or three floor area categories, 

depending on the type of dwelling. These categories are consolidated from a larger number of 

categories (usually four to five) in the original RECS data. The floor area used in the models of 

each floor plan is calculated as the weighted average of each included RECS category. RECS 

categories are represented by the mean of the upper and lower bound for each category. RECS 

categories with only an upper or lower hound (for example, greater than 149 m

2 (1,600 ft2

)) are 

represented by values 1 0 % greater than or 1 0 % less than the upper or lower bound given. The 

following example demonstrates this calculation, and the results for all of the housing types are 

summarized in Table 4. 

For example, the manufactured houses in the collection are all in the floor area category of "less 

than 148.5 m

2 (1,599 ft2)." This floor area category has been consolidated from three RECS 

categories: 92.9 m

2 to 145.8 m

2 (1,000 ft2 to 1,599 fr), which accounts for 35 % of houses in the 

group; 55.7 m

2 to 92.8 m

2 (600 fr to 999 ft2), which accounts for 48 % of houses in the group; 

and less than 55.7 mZ (600 ftz), which accounts for 17 % of houses. Representing the three RECS 

categories by 120.1 mZ, 74.3 m

2 and 50.2 m2 (1,300 ft2, 800 ft2 and 540 ft2

), respectively, yields a 

weighted average of 86.3 m

2 (929 ft2

) for the "less than 148.5 m2 (1,599 ft2)" category. 

Housing type Floor area category Floor area in 

m2 (fe) model m2 (fe) 

Less than 148.5 (1,599) 107.0 (1152) 

Detached 148.6 to 222.9 (1,600 to 2,399) 180.4 (1942) 

223.0 (2,400) or more 275.5 (2966) 

Less than 148.5 (1,599) 96.3 (1037) 

Attached 148.6 to 222.9 (1,600 to 2,399) 175.6(1891) 

223.0 (2,400) or more 261.3 (2813) 

Manufactured Less than 148.5 (1,599) 86.3 (929) 

Apartments, 2-4 units Less than 92.8 (999) 65.4 (704) 

92.9 (1000) or more 142.1 (1530) 

Apartments, 5 units or more 

Less than 92.8 (999) 65.4 (704) 

92.9 (1000) or more 130.0 (1399) 

Table 4 Weighted average floor area by housing type and category. 

Year Built: The year of construction is used to assign the exterior wall leakage based on data 

from two studies of airtightness on single-family homes (Sherman and Dickeroff 1998; Chan, et 

al. 2003 and 2005). Exterior wall leakage, in terms of the normalized leakage area, is defined as 

a function of both year built and house floor area as described in Appendix A and presented in 

Table 5. The normalized leakage (NL) values from this table are converted to an effective 

leakage area (ELA) for use in the house models using the following equation that defines NL 

(ASHRAE 2005): 

NL = 1000 ELA (!i.)O.3 

AI 2.5 

where, Af is the floor area in m

2 and H is the building height in m. 

6 

(1) 
Normalized leakage area (dimensionless) 

Year built Floor area less than Floor area greater than 

148.6 m2 (1600 rr) 148.6 m2 (1600 rr) 

Before 1940 1.29 0.58 

1940-1969 1.03 0.49 

1970-1989 0.65 0.36 

1990 and newer 0.31 0.24 

Table 5. Normalized leakage by construction year and floor area 

Foundation Type: Detached and attached homes have three foundation type options in the 

RECS database: concrete slab, crawl space and basement. All manufactured homes are modeled 

with crawlspaces, and all apartment buildings with concrete slabs. The concrete slab option is 

modeled with no leakage paths to the outdoors through the floor. The crawl space option is 

modeled with a 0.9 m (3 ft) high crawl space underneath the house that has ventilation openings 

to the outdoors. Four total openings are used for each house, located at the comers, and having 

openings to the outdoors totaling 11150 of the floor area of the crawlspace, which is a rule of 

thumb that has been used over many years. However, more recent guidance has questioned the 

desirability of any crawl space venting at all if a moisture-retardant ground cover is installed 

(ASHRAE 2003). The per area leakage between the crawlspace and the house is the same as the 

exterior wall leakage for the house. Basements are modeled as 2.4 m (8 ft) high spaces with the 

same footprint as the house (except for the case of an attached home with a garage and basement 

as described below). Unfinished basements are modeled as unconditioned space and are closed 

off from the upper part of the house with a closed door. If unfinished, they are assumed to have 

leakage to the outdoors at the top 0.6 m (2 ft) of each wall and to the floor of the conditioned 

house above. This leakage is the same as the exterior wall leakage for the exterior walls of the 

house. Finished basements are modeled with an open staircase to the upper floors, and the 

leakage per area of the basement-house interface is the same as the interior walls. Finished 

basements are modeled with leakage at the top 1.2 m (4 ft) of walls without doors to attached 

garages and with leakage on the entire 2.4 m (8 ft) of walls that have doors to a garage. 

Garage: Some of the detached and attached homes have attached garages, which are considered 

as unconditioned spaces. Detached homes are modeled with a two car garage, either 45.0 m

2 

or 

53.5 m2 (484 fe or 576 ft2

) in size depending on the floor plan, attached to the first story of the 

home. Attached homes are modeled with one or two car garages, which are 53.5 m

2

, 59.1 m

2 

or 

35.7 m2 (576 ft2

, 528 fe or 384 fe) in size depending on floor plan, on the lowest story of the 

home. Where an attached home is specified with an attached garage and basement, the garage 

and basement share the lowest level of the home. Garage (exterior) walls are modeled with 

leakage values two times that of the exterior walls. This is based on the findings of a study of the 

leakage of attached garages relative to houses (Emmerich et al. 2003). 

Type of Heating Equipment: Homes in the database have two heating system options: "Central 

system," which means forced-air distribution, and "other". Systems in the "other" category are 

assumed not to include forced air fans or outdoor air ventilation, and are thus not included in the 

airflow models. Homes with central systems are modeled with a simple air handling system that 

has balanced supply and return airflows of 6.1 Lis· m

2 (1.2 cfmlft2) of floor area (ASHRAE 

1989). No outdoor air ventilation is introduced by the systems for detached, attached or 

7 
manufactured houses. In some cases, the system model includes duct leakage. Homes with 

unconditioned basements are modeled with return duct leakage from the basement equal to 10 % 

of the total system flow. Ifthe basement is conditioned, no supply or return leakage is modeled. 

Houses with crawlspaces and slab-on-grade construction are modeled with a supply leak (equal 

to 10 % of the system flow) in the attic. If these houses also have a garage, an equivalent return 

leak is located in the garage; otherwise, no return leak is modeled. 

Apartment buildings with "central systems" are also modeled with simple air handling systems 

that supply the apartments with balanced supply and return airflows of 6.1 Lis· m

2 (1.2 cfmlft2) 

of floor area and no outdoor air or duct leakage. If the apartment building has fewer than 32 

units, each unit has its own air handling system. Buildings that have 32 or more units are 

modeled with all units on each floor sharing the same ai~handling system. All apartment 

buildings are also modeled with kitchen and bathroom exhaust fans that remove 47 Lis (100 cfm) 

per kitchen and 22 Lis (50 cfm) per bathroom. These exhausts are modeled using single simple 

air handling units with only returns; these returns are scheduled as "off' in the model, but can be 

scheduled to operate if desired. Apartments with corridors have 100 % outdoor air systems that 

supply 21 Lis (45 cfm) per unit opening onto each corridor. This airflow is intended to maintain 

pressurization of the building and to provide makeup air for unit exhaust fans. The duct system 

volumes are calculated as follows: supply ducts are assumed to be 20 cm (8 in) in diameter and 

twice the long dimension of the building or apartment unit, and return ducts are also assumed to 

be 20 cm (8 in) in diameter but half the long dimension of the building or unit. 

Number of Rooms: The RECS data set includes information on numbers of rooms in each home 

and apartment. For each of the 209 houses, the percentage of dwellings with each number ofthe 

following room types was determined: bedrooms, bathrooms, half baths, and others. From this 

data, a weighted average of the number of each room type reported for each of the 209 dwellings 

was calculated, which was then rounded to the nearest whole number and used to build the 

models. The tables in Appendix B summarize the number of rooms and other key modeling 

variables for the 209 dwellings. In translating the number of rooms to specific floor plans, 

several conventions were used. When only one bathroom is present, it is located centrally with 

access from a hallway. Halfbaths are located with access from the main living space. Additional 

bathrooms are modeled as master bathrooms and located in proximity to the largest bedroom. 

The number of other rooms in the models varies from one to five. The naming convention for 

"other" rooms is as follows: the first other room is labeled as the "kitchen", the second as the 

"living room", the third as the "dining room", the fourth as the "den" and the fifth as "storage." 

Number of Units: Buildings in the apartment category are assigned a number of units. There are 

five categories for this variable: 2-4, 5-9, 10-19,20-39, and 40+. The 40+ units category is 

modeled by a building with 20 units per floor. The 20-39 category is modeled with 32 units; the 

10-19 category is modeled with 16 units; the 5-9 category is modeled with 6 units; and the 2-4 

category is modeled with 4 units. These values were selected to provide conveniently divisible 

numbers of units so that most buildings could be modeled with identical floors. In a few cases, 

this was not possible, for example, a four story building with six total units. In that case, the 

building was modeled with two identical lower floors with two units each, and two identical 

upper floors with one unit each. 

Finished Basements: Survey data report that approximately 75 % of houses have some finished 

basement area that is included in the total floor area reported by the survey. Floor plans that 

include finished basements were selected from among the floor plans that include basements, so 

8 
that their percentage (when weighted according to the survey) was approximately 75 %. Floor 

plans that include finished basements have the entire basement finished, except in the case of 

attached housing with garages. In this case, the finished basement and the garage share the 

lowest level of the home. 

Inclusion of doors in the model: The effect of exterior doors on exterior wall leakage is 

included in the exterior wall leakage values cited above. However, one front exterior door is also 

included in each model, each with an effective leakage area of 12 cm2 (1.9 in2

). Basement doors 

are also included and modeled as open if the basement is finished and closed with a leakage of 

21 cm

2 (3.3 in2

) each if the basement is unfinished. If a garage is present, the door connecting 

the garage and house is modeled as closed with a leakage of21 cm

2 (3.3 in2

) each. These leakage 

values are the "best estimate" values from ASHRAE (2001) for single doors weatherstripped and 

not weatherstripped, respectively. Apartment buildings that include elevators have elevator doors 

modeled with a leakage of226 cm

2 (35 in2

) each. This is the average elevator door leakage from 

a study of seven buildings (Tamura and Shaw 1976). 

Attics: Unconditioned attics are included in the attached, detached and manufactured houses. 

Attics are also included in the models of one and two story apartment buildings with four units 

per building. The attic models have vents to ambient with a free area equal to 11150 ofthe floor 

area of the attic. The temperature of these spaces is the same as the indoor temperature, but can 

be changed if desired. 

Conditioned and unconditioned spaces: In the project files, attics, unconditioned basements, 

crawlspaces and garages are considered unconditioned spaces within CONTAM. This 

designation means that when CONTAM calculates a building air change rate, these spaces are 

not included in that calculation but are considered to be part of the ambient zone. In practice, this 

means that only the conditioned spaces are included in the building volume and only airflows 

into these spaces from outdoors or from non-conditioned spaces are included in the air change 

rate calculation. If desired, such spaces can be designated as conditioned within CONT AM and 

thereby included in the air change rate calculation within CONTAM. Apartment building 

corridors, stairs and elevators are consid~red part of the building'S conditioned space. 

5. CONTAM PROJECT FILES 

CONTAM project files describing the 209 dwellings discussed above have been created 

following the conventions described in the previous section. Appendix B summarizes the 209 

dwellings and identifies the corresponding project file name and associated floor plan. The 

project files and the floor plans are available for download at the CONTAM website 

www.bfrl.nist.gov/IAOanalysis under Case Studies. 

Project File Testing 

Four different tests were performed to verify the accuracy of the CON TAM project files. These 

include tests of wind pressure profiles, air handling unit flows, air change rates and building 

pressurization. Detailed results of these tests are contained in an Excel file titled "Suite of homes 

project file tests.xls," which is also available at the website noted above. 

The wind profile test checks that all exterior leakage paths are associated with a wind pressure 

profile and that the wall azimuth angle of each path is correct. The test is performed within the 

CONT AM interface using the "View ... wind pressure" command. 

9 
Air handling unit flows were tested by running a steady state simulation for ~ach pr~ject fi!e and 

verifying the total outdoor air, return air and exhaust airflow rates for each aIr handlmg umt. In 

the detached attached and manufactured homes, the outdoor air and exhaust airflow rates should , 2 2 'rfl be zero and the return airflow rate should be 6.1 Llsem (1.2 cfmlft ) of floor area, These aI ow 

rate tests are considered to be passed ifthe calculated airflows are within I % of the target value. 

In apartment buildings, it was also necessary to test the air handling units associated with 

corridors and exhaust fans. Exhaust fan flows are correct if the outdoor air, return air and exhaust 

air are all zero, since these are scheduled off. Corridor airflows are correct ifreturn and exhaust 

airflow rates are zero, and the outdoor airflow rate equals 21 Lis (45 cfm) per unit. 

":"- -.::: 

-~ 

-(': 

-

CJ 

c.t 

::: 

~ 

'" s.. .; 

c.t 

. : 

;g 

::: 

::: 

1.6 

1.4 

1.2 -

1.0 .-

O.S 

0.6 

0.4 

0.2 

0.0 

0.0 

• 

• Detached homes 

• Manufactured homes 

.. Attached homes • a 

• • Apartment buildings .. 

j .A 

" 

I .. 

I ! • t 

A ... 

• • t ~ .. • • I f • 

4 

• .. • 

, I I • .. 

• _. 

• • 

0.2 0.4 0.6 O.S 1.0 1.2 1.4 1.6 

Normalized leakage, NL (dimensionless) 

Figure 2 Building air change rate test results. 

Air change rate tests were conducted without the air handling systems operating (except those of 

the apartment building corridor systems). These tests involved running steady-state CONTAM 

simulations to calculate the building air change rates with the outdoor temperature 20°C (36 OF) 

lower than the indoor temperature and an outdoor wind speed of 5 mls (11 mph). Attics, 

unconditioned basements, crawlspaces and garages were not included in the building volume for 

these calculation. Apartment building corridors, stairs and elevators were considered part of the 

building's conditioned volume. Figure 2 presents the calculated building air change rates as a 

function of normalized leakage for the 209 dwellings under the defined test conditions. These 

results follow the expected trend based on normalized leakage and house design. Note that the 

apartment buildings divide into two general groups: one with no corridors and lower air change 

rates, and another with corridors and higher air change rates due to corridor ventilation. Table 3 

summarizes the minimum, maximum, and average air change rate by type of dwelling type. 

10 
House type Maximum Minimum Average 

Detached 1.43 0.18 0.59 

Attached 1.15 0.16 0.60 

Manufactured 0.89 0.28 0.57 

Apartment 0.76 0.17 0.46 

Table 6. Summary of building air change rate test results (in units ofh·l

) 

Simulated building pressurization tests were also performed to verify the exterior leakage of each 

house. This test is done in practice by pressurizing the conditioned volume of each building with 

an imposed airflow, and then measuring the airflow rate and pressure difference at this 

pressurized condition. Using the surface area of each house, the ELA for the building is then 

calculated and compared with the input value, as described in ASHRAE (2005). This test serves 

to verify that all required exterior wall leakage paths are present, and have the correct ELA and 

surface area input. CONTAM has a simulation mode that mimics a pressurization test, which 

was used for these model tests. Due to the presence of exterior doors and attached garages, attics 

and other spaces in the models, the input and calculated ELA do not always match exactly. 

Models were deemed acceptable if the ELA determined through the CONTAM simulations was 

within 0.2 cm2/m2 (0.003 in2

/ft2) of the input value. 

6. SUMMARY AND DISCUSSION 

This collection of homes has been developed to represent the U.S. residential building stock for 

use in residential ventilation and indoor air quality analysis. The development and availability of 

the corresponding CONTAM models of these buildings will enable nationwide analyses and risk 

assessments of residential ventilation and indoor air quality issues. 

One folloWllp activity that is currently in progress is to further characterize these 209 dwellings 

based on additional information contained in the RECS survey. To that end, a so-called 

"counting exercise" was performed in which the fractions of homes in the survey captured by 

each of the 209 dwellings was sorted by each of the following variables: 

Number of household occupants 

Number of occupants less than 1 year old, between 1 and 12 years old, greater than 65 years, 

and greater than 75 years 

Part of public housing projects (yes or no) 

Cooking fuel (3 options) 

Census division (8 options) 

Existence of a clothes dryer (yes or no) 

Main home heating equipment (12 options) and heating fuel (6 options) 

Use of stove as auxiliary heat (yes or no) 

Main water heating fuel ( 4 options) 

The results of this exercise will allow more detailed characterization of the 209 dwellings for use 

in future analyses of building ventilation, indoor air quality and exposure. For example, the 

information on distribution by census division is being used to generate a nationwide frequency 

distribution of ventilation rates. In this effort, nineteen U.S. cities have been identified to 

represent climatic variations within each census region, along with weighting factors that 

characterize the number of each dwelling type that exists in each city. Year-long CONT AM 

simulations will be run for each dwelling in each city to determine building ventilation rates for 

11 
eachnour ofthe year. These results will then be combined based on the house/city weighting 

factors to develop a national frequency distribution of ventilation rates. This distribution will be 

compared with other such ventilation rate distributions based on tracer gas measurements 

(Pan dian et al. 1998), but which were not based on a representative group of homes, as well as a 

California-specific ventilation rate database (Wilson et al. 1996). 

7. ACKNOWLEDGEMENTS 

This work was sponsored under an Interagency Agreement with the U.S Department of Housing 

and Urban Development, Office of Healthy Homes and Lead Hazards Control. 

12 
8. REFERENCES 

ASHRAE 1989. ASHRAE Pocket Guide for Air Conditioning, Heating, Ventilation, 

Refrigeration. American Society of Heating Refrigerating and Air-Conditioning Engineers. 

Atlanta, GA. 

ASHRAE. 2001. Handbook of Fundamentals. American Society of Heating Refrigerating and 

Air-Conditioning Engineers. 

ASHRAE. 2003. Handbook of HVAC Applications, Chapter 43 Building Envelopes. American 

Society of Heating Refrigerating and Air-Conditioning Engineers. 

ASHRAE. 2005. Handbook of Fundamentals. American Society of Heating Refrigerating and 

Air-Conditioning Engineers. 

Chan W, Price P, Sohn M, Gadgil A. 2003. Analysis of U.S. Residential Air Leakage Database. 

LBNL 53367. Lawrence Berkeley National Laboratory. 

DOE 1999. A Look at Residential Energy Consumption in 1997. DOE/EIA-0632(97). U.S. 

Department of Energy. 

Emmerich SJ, Howard-Reed C, Gupta A. 2005. Modeling the IAQ Impact ofHHI Interventions 

in Inner-City Housing. NISTIR 7212, National Institute of Standards and Technology. 

Emmerich S, Gorfain J, Huang M, Howard-Reed C. 2003. Air and Pollutant Transport from 

Attached Garages to Residential Living Spaces. NISTIR 7072, National Institute of Standards 

and Technology. 

Emmerich, SJ and AK Persily. 1996. Multizone Modeling of Three Residential Indoor Air 

Quality Control Options. NISTIR 5801, National Institute of Standards and Technology. 

HUD. 1999a. The Healthy Homes Initiative: A Preliminary Plan. U.S. Department of Housing 

and Urban Development, Office of Lead Hazard Control. 

HUD. 1999b. American Housing Survey for the United States. HI50/99. U.S. Department of 

Housing and Urban Development, U.S. Department of Commerce. 

Pandian MD, Behar JV, Ott WR, Wallace LA, Wilson AL, Colome SD, Koontz M. 1998. 

Correcting Errors in the Nationwide Data Base of Residential Air Exchange Rates. Journal of 

Exposure Analysis and Environmental Epidemiology. 8(4): 577-591. 

Persily A, Leber D. 2003. A Suite of Homes Representing U.S. Housing Stock. Ventilation, 

Humidity Control and Energy, Proceedings of the 24th Air Infiltration and Ventilation Centre 

(AIVC) Conference and Building Environment and Thermal Envelope Council (BETEC) 

Conference, Washington, DC, pp. 15-20. 

Persily AK. 1998. A Modeling Study of Ventilation, IAQ and Energy Impacts of Residential 

Mechanical Ventilation. NISTIR6162, National Institute of Standards and Technology. 

Sherman M, DickeroffD. 1998. Air-tightness of U.S. Dwellings. ASHRAE Transactions,104(2): 

1359-1367. 

Tamura G, Shaw J. 1976. Air Leakage Data for the Design of Elevator and Stair Shaft 

Pressurization Systems. ASHRAE Transactions. 82(2): 179-190. 

Wilson AL, Colome SD, Tian Y, Becker EW, Baker PE, Behrens DW, Billick IH, Garrison CA. 

1996. California Residential Air Exchange Rates and Residence Volumes. Journal of Exposure 

Analysis and Environmental Epidemiology. 6(3): 311-326. 

13 
APPENDIX A: Exterior Leakage Data 

Data for exterior envelope leakage as a function of building age were examined from two 

Lawrence Berkeley National Laboratory (LBNL) studies (Sherman and Dickeroff 1998, Chan et 

aI., 2003 and 2005). The older report provides data for a sample of approximately 1500 houses. 

The newer analysis contains leakage data as a function of building age and floor area for 

approximately 3500 houses. However, the floor area and age categories used to present these 

tabular data are not exactly the same as the categories used to develop the collection of homes 

described in the body of this report. 

Figure Al shows normalized leakage area plotted against year built from both LBNL reports. 

The Sherman and Dickeroff (S+D) data are shown in the same age ranges used to define the 

collection of homes. The Chan data are shown in slightly different age ranges. In the figure, the 

data from the earlier Sherman and Dickeroff study track the normalized leakage from the smaller 

two size ranges in the Chan study fairly well. Also, the similarity of these data sets suggests that 

the data from the Chan study could reasonably be extrapolated down to a "year built" of 1940. 

The larger three size ranges in the Chan study (those with floor areas above 139 m

2 (1,500 ft2

) 

have lower normalized leakage, but track one another fairly closely. 

1.75 

1.5 

-rI) 

'" .=! 

E 1.25 .~ 

c:: 

e 

:; 

--~ 

ell 

12 

~ 0.75 .=! 

-= ~ 

.~ 

~ 0.5 e 

'-

i0.25· 

0 

1940 

- S+D 1998 

-e- Chan: < 93 m2 (lOOO ff) 

- Chan: 93 m1 to 139 m2 (1000 rf to 1500 rf) 

Chan: 139 ml to 186 ml (1500 rf to 2000 ff) 

-'lIE- Chan: 186 m2 to 232 m1 (2000 rf to 2500 ff) 

Chan: > 232 m1 (2500 cal) 

1950 1960 1970 1980 1990 2000 

Year Built 

Figure Al Normalized leakage vs. Year built 

(Sherman and Dickeroff 1998; Chan et aI., 2003 and 2005) 

2010 

For t~is project, data from Chan et al. were adapted to the age ranges used to define the model 

d",:ell.mgs bas:,d on the trends noted above. The "before 1940" range was represented by houses 

bUllt In 1940, 1990 and newer" was represented by the year 1998, and the other categories were 

represented by the midpoint ?fthe category. For floor areas less than 148.5 m2 (1,599 ft2), the 

two smaller Chan categones were averaged, and least squares regression analysis was used to 

14 
obtaln-values for the ages needed. For floor areas greater than 148.6 m2 (1,600 ft2

), the three 

larger Chan categories were averaged and regressed against year built. Figure A2 shows the 

nonnalized leakage vs. year built for the two aggregated Chan floor area groups and the values 

used to develop the suite of homes. Table Al summarizes the values used for the suite of homes. 

Normalized leakage area (dimensionless) 

Year built Floor area less than Floor area less than 

148.6 m2 (1600 rr) 148.6 m2 (1600 rr) 

Before 1940 1.29 0.58 

1940-1969 1.03 0.49 

1970-1989 0.65 .0.36 

1990 and newer 0.31 0.24 

Table AI. Nonnalized leakage by construction year and square footage 

1.4,T""""'---------------------------, 

-- Chan: < 139 mZ (1500 ffl 

1.2 t----------------~ ., _ - Chan: > J39 m" t1500 ft") 

'" 

~ '" 

'<;j 

= = 1 +-------------~~-----~ • Suite: < 139 m

2 (1500 ftl) 

III Suite: > 139 m2 

~ (1500 fe) 

e 

~O.8·r-------------------------~~--------------------------~ 

~ CIt: 

~ 

~ 0.6 '~--_.r_--_,~-----------~~----------~ 

'0 

.~ 1 0.4 1------------===-......::;~::::::::::::=_=~,=_--___1 i: 

z: = 

0.2 t----------------------------------------------; 

o~--------------------------------------------------~ 

1930 1940 1950 1960 1970 

Year Built 

1980 1990 2000 2010 

Figure A2. Nonnalized leakage vs. Year built (values used to develop the suite of homes) 

-

The leakage of the exterior walls for the apartment buildings were determined from the leakage 

data for the houses in the collection with floor areas greater than 148.6 m

2 (1600 ft2). While the 

appropriateness of these data for apartment buildings is questionable, there are no large scale 

studies that provide age-related leakage data for this type of building. The leakage areas used are, 

however, compared with the limited data from apartment buildings in the literature (CEE 2004). 

Figures A3 and A4 show the ELA of the detached homes in the collection defined by this project 

and the apartment buildings in CEE (2004) plotted as a function of building square footage. 

These plots show that the ELA values for the two types of buildings have a similar range, though 

the larger apartment buildings are somewhat leakier than the largest houses. 

15 
0.12 

0.10 

CD 

~ 0.06 

.; 

CD 

-CD 

:E 0.04 

~ ~ 

i::! -

--:S 

'-' 

III 

CD 

:a 

(I) 

til 

IC 

~ (I) 

-CD 

> -..: 

... 

~ ~ 

0.02 

0.00 

500 

0.12 

0.10 

0.08 

0.06 

0.04 

0.02 

+. .. 1;.' 

~. 

r~ • 

•• + 

• + 

0.00 

° 

16 

+ 

+ 

+ 

+ 

+ 

• + 

+ 

+ 

+ 

-+-

+ 

+ 

+ 

1,000 

+ 

• 

• 

.+ 

+ + 

.+ 

50,000 

1,500 

* • 

: 

* • 

2,000 

Floor area (ff) 

1 inl/ft' '" 69.4 cm'/ml 

1 ft' '" 0.0929 m' 

+ 

+ 

+ 

* 

t 

2,500 3,000 

Figure A3 Detached home leakage 

1 in'/ft' = 69.4 cm'/m' 

1 ft' = 0.0929 m' 

.. 

• 

+ 

• 

3,500 

100,000 150,000 200,000 250,000 300,000 350,000 

Floor area (ff) 

Figure A4 Apartment building leakage 
Measured airflow rates at a 50 Pa indoor-outdoor pressure difference have been published for 

individual apartment units located in buildings of known age and number of units (CEE 2004), 

which can be compared with the results of a CONTAM simulation of a pressurization test for the 

apartment building models defined in this project. Unfortunately, the size of the apartment unit, 

its location within the building, and the distribution between indoor and outdoor leakage were 

not documented in the CEE effort. Table A2 compares the airflow rate required to pressurize the 

building to a pressure of 50 Pa (designated as Q50) measured in that study with that simulated in 

a similar building from this set of dwellings. For these six cases, the suite of homes has a higher 

Q50 value in four cases and a lower value in two cases. The two larger buildings do have lower 

measured Q50 values, however, the exact size ofthose units is not known. 

Suite of homes model MNCEE data 

Model Stories # of Year Single unit Q50, Building Median Q50, 

units Built LIs (cfm) descr~tion L/sJdml 

APT 67 1 16 1940-69 696 (1475) 1964 12plex 433 (917) 

APT 41 1 6 1970-89 867 (1836) 19708plex 476 (1008) 

APT 4 2 4 <1940 869 (1842) 1935 duplex 1118 (2368) 

APT 60 4 6 1990+ 225 (476) 20014 story 546 (1156) 

APT 36 10 200 1970-89 746 (1581) 1999 138 unit 314 (665) 

APT 36 10 200 1970-89 746 (1581) 1982 11 story 214 (454) 

Table A2 Comparison of Apartment Leakage Data 

REFERENCES 

Sherman M and DickeroffD. 1998. Air-tightness of U.S. Dwellings. ASHRAE Transactions. 

104(2): 1359-1367. 

Chan W, Price P, Sohn M, and Gadgil A. 2003. Analysis of U.S. Residential Air Leakage 

Database. Report Number 53367, Lawrence Berkeley National Laboratory. 

Chan, WR, NazaroffWW, Price PN, Sohn MD and Gadgil AJ. 2005. Analyzing a database of 

residential air leakage in the United States. Atmospheric Environment, 39: 3445-3455. 

CEE 2004. Reduction of Environmental Tobacco Smoke Transfer in Minnesota Multifamily 

Buildings Using Air Sealing and Ventilation Treatments. Report CEE/TR04-1-MF. Center for 

Energy and Environment. Minneapolis, MN. 

17 
18 

APPENDIX B: House Characteristics 

This appendix contains four tables that define the 209 dwellings, with one table for each housing 

type: detached (Bl), attached (B2), manufactured home (B3) and apartment (B4). The dwelling 

definitions in the table are in terms of the variables discussed in the body of the report. Other 

information related to the dwelling models, including the number of homes in the RECS survey 

represented by the model and the floor plan code for that dwelling, are also listed in the tables. 
..... 

\0 

Table B1. Modeling details - Detached Homes (83 total) 

Key to variables at end of table 

House Variable 

House # of Floor Year Found Garage Forced 

Number Floors area Built -ation -air 

DH-I 1 2 3 1 2 2 

011-2 1 1 2 3 2 2 

DH-3 I I 2 2 1 1 

DH-4 I 1 2 2 2 2 

DH-5 1 1 3 I 2 2 

DH-6 2 I 1 3 2 2 

DH-7 1 2 2 3 2 2 

DH-8 1 1 2 1 2 2 

DH-9 2 1 2 3 2 2 

DH-1O 2 2 3 3 2 2 

OIl-II I I 2 2 2 1 

DH-12 2 3 3 3 2 2 

DH-13 I 2 2 2 2 2 

DH-14 2 2 1 3 2 2 

DJf-15 2 3 4 3 2 2 

DH-16 1 I 2 2 1 2 

DJ-J-17 2 2 2 3 2 2 

DH-18 2 1 1 3 1 2 

DH-19 1 1 3 3 2 2 

DH-2O 2 2 1 3 2 1 

DH-21 I 1 2 1 I 2 

DH-22 2 3 3 1 2 2 

DII-23 2 1 1 3 2 I 

DII-24 2 2 3 I 2 2 

DH-25 I I 2 3 2 I 

DH-26 1 I 2 I I I 

DII-27 I I 2 3 I 2 

DlI-28 2 3 4 I 2 2 

011-29 I I I 2 I I 

RECSData Mean # of Rooms 

#of Weight Bed- Full Half Floor 

Homes rooms baths baths Other plan 

109 2185179 3 2 0 3 DH-B(l) 

111 1930684 3 1 0 3 DH-A(8) 

114 1730307 2 I 0 2 DH-A(l) 

83 1491818 3 1 0 3 DH-A(7) 

65 1306058 3 2 0 3 DH-A(2) 

66 1140420 3 1 0 3 DH-D(3) 

61 1107980 3 2 0 4 DH-B(5) 

56 1029268 3 2 0 3 DH-A(2) 

53 1022407 3 1 0 3 DH-D(3) 

55 1016922 4 2 1 4 DH-E(8) 

57 1016685 3 1 0 3 DH-A(7) 

59 1013802 4 2 1 5 DH-F(4) 

56 997221 3 2 0 3 DH-B(1) 

55 970354 3 1 1 4 DH-E(5) 

36 947526 4 ~ 1 5 DH-F(5) 

56 838556 3 1 0 3 DH-A(7) 

43 803384 3 2 1 4 DH-E(6) 

45 742844 3 1 0 3 DH-D(3) 

40 727963 3 1 0 3 DH-A(8) 

39 720815 4 1 0 4 DH-E(7) 

47 708504 3 1 0 3 DH-A(7) 

27 690163 4 3 I 5 DH-F(1) 

44 684661 3 1 0 3 DH-D(3) 

31 645193 4 2 I 4 DH-E(3) 

45 642330 3 I 0 3 DH-A(8) 

39 635246 2 1 0 2 DH-A(l) 

38 601468 3 I 0 3 DH-A(8) 

19 580448 4 3 I 4 DH-F(2) 

39 574063 2 1 0 3 DH-A(3) 
N 

o 

House 

Number 

011-30 

011-31 

011-32 

DII-33 

011-34 

011-35 

011-36 

DII-37 

OH-38 

OH-39 

011-40 

OH-41 

OH-42 

OH-43 

OH-44 

011-45 

OH-46 

011-47 

OB-48 

011-49 

OH-50 

OB-51 

OH-52 

OH-53 

011-54 

OH-55 

OB-56 

OH-57 

OH-58 

OH-59 

OH-60 

OH-61 

I OH-62_ 

# of Floor 

Floors area 

I 2 

1 1 

1 I 

1 3 

1 1 

I 2 

2 2 

1 2 

I 1 

I 2 

2 2 

2 2 

1 1 

2 2 

1 I 

2 2 

1 I 

1 1 

1 1 

I 1 

2 I 

2 3 

2 3 

1 2 

1 1 

1 1 

2 1 

1 2 

2 2 

2 3 

1 1 

1 1 

'-----~ 3 

House Variable 

Year Found Garage Built -ation 

3 2 2 

3 2 2 

4 1 2 

3 I 2 

3 1 1 

2 I 2 

4 I 2 

3 3 2 

3 2 I 

2 2 I 

3 2 2 

1 3 1 

3 2 1 

2 3 2 

1 3 2 

3 4 2 

2 1 2 

3 2 2 

4 2 1 

2 3 I 

I 3 1 

3 2 2 

1 4 2 

3 1 1 

1 2 1 

4 2 2 

2 3 1 

2 2 2 

4 3 2 

2 3 2 

3 4 2 

1 4 1 

1 3 2 

RECS Data Mean # of Rooms 

Forced #of Weight Bed- Full Half Floor 

-air Homes rooms baths baths Other plan 

2 31 571692 3 2 0 3 OH-B(1) 

2 32 565329 3 2 0 3 OH-A(2) 

2 20 552255 3 2 0 2 OH-A(6) 

2 27 549619 4 2 0 4 OH-C(l) 

2 31 524933 3 1 0 3 DH-A(7) 

2 29 520116 3 2 0 3 OH-B(l) 

2 20 519749 4 2 I 4 OH-E(3) 

2 27 511492 3 2 1 3 OH-B(4) 

2 30 497620 3 I 0 3 OH-A(7) 

2 30 469257 3 2 0 3 OH-BO) 

2 22 447207 4 2 I 4 OH-E(3) 

2 32 446950 3 1 0 4 DH-EO) 

1 27 442268 3 1 0 2 OH-A(4) 

1 26 410024 4 2 0 4 OH-E(2) 

2 26 409001 2 1 0 3 DH-A(9) 

1 30 398786 4 2 1 4 OH-I~f3) 

1 24 380772 2 1 0 2 OH-A(1) 

1 25 376507 3 1 0 3 OH-A(7) 

2 17 368757 3 2 0 3 DH-A(2) 

1 26 361389 3 1 0 3 OH-A(8) 

1 23 351778 3 1 0 3 OH-0(3) 

2 19 348213 4 2 I 4 OH-F(3) 

2 22 347787 4 2 1 4 OH-F(3) 

2 18 327779 3 2 0 3 OH-BO) 

2 19 323291 2 1 0 3 OH-A(3) 

2 14 320900 3 2 0 2 DH-A(6) 

2 21 314026 3 1 0 3 OH-O(3) 

1 18 309112 3 2 0 4 OH-B(3) 

2 17 299726 3 2 1 4 OH-Ei6) 

1 17 293015 4 2 1 5 DH-F(4) 

1 18 285825 3 1 0 3 OH-A(7) 

2 17 285549 2 1 0 2 OH-A(l) 

1 18 283742 4 2 1 5 DH-F(4) 
N 

..... 

House Variable RECSData Mean # of Rooms 

House #of Floor Year Found Garage Forced #of Weight Bed- Full Half 

Number Floors area Built -ation -air Homes rooms baths baths Other 

DH-63 2 1 2 4 2 1 23 282152 3 1 1 3 

DH-64 1 2 4 1 2 2 13 276193 3 2 0 3 

DH-65 I 1 1 4 1 1 20 273431 2 1 0 3 

DH-66 1 2 2 1 2 1 17 273259 3 1 0 3 

DH-67 1 1 1 2 2 2 13 270968 3 1 0 3 

DH-68 2 1 2 3 1 1 16 269052 3 1 0 3 

DH-69 2 3 3 4 2 1 16 265490 4 2 1 4 

DH-70 I 1 3 1 1 1 16 263674 2 1 0 2 

DH-71 2 1 3 1 2 2 15 263107 3 2 1 3 

DH-72 1 2 1 4 2 2 13 250826 3 2 0 4 

DH-73 2 1 3 4 2 2 13 244715 3 2 0 4 

DH-74 1 3 3 4 2 2 13 237998 3 2 1 5 

DlI-75 3 2 3 1 2 2 11 237637 4 2 1 3 

DH-76 I 1 4 4 2 2 11 235564 3 2 1 3 

DH-77 3 2 3 4 2 2 12 235357 3 2 1 4 

DH-78 I I 3 1 2 1 12 234540 3 1 0 3 

DH-79 1 2 3 2 1 2 14 234475 3 2 0 3 

DH-80 1 2 2 4 1 2 12 222802 3 2 0 4 

DH-81 2 2 1 4 1 1 13 206578 3 2 0 4 

DH-82 I 2 2 4 2 1 13 205183 3 2 0 3 

DH-83 1 1 3 3 1 2 13 204007 3 1 0 3 

Key for Table Bl: 

# of floors: 1 = one story; 2 = two story 

Floor area: 1 = less than 148.5 m

2 (l ,599 ft\ 2 = 148.6 m2 to 222.9 m

2 (1,600 ft2 to 2,399 ft2); 3 = 223.0 m

2 (2,400 ft2) or more 

Year Built: 1 = before 1940; 2 = 1940-69; 3 = 1970-89; 4 = 1990 and newer 

Foundation: 1 = concrete slab; 2 = crawl space; 3 = finished basement, 4 = unfinished basement 

Garage: 1 = none; 2 = attached garage 

Forced Air: 1 = other; 2 = central system present 

RECS datal# of Homes: number of each home in the RECS survey 

RECS data/Weight: weighting factor of each home for all US housing 

Floor 

plan 

DH-D(4) 

DH-B(l) 

DH-AJ.3) 

DH-BJ.2) 

DH-A(7) 

DH-D(3) 

DH-F(3) 

DH-A(l) 

DH-D(l) 

DH-B(3) 

DH-DJ.2) 

DH-C(2) 

DH-G(l) 

DH-A(5) 

DH-G(2) 

DH-A(7) 

DH-B(l) 

DH-B(3) 

DH-E(4) 

DH-B(l) 

DH-A(8) 
N 

t-.l 

TABLE B2. Modeling details - Attached Homes (53 total) 

Key to variables at end of table 

House Variable 

House # of Floor Year Found Garage Forced 

Number Floors area Built -ation -air 

AH-I 2 I I 3 I 2 

AII-2 2 I 3 I I 2 

AII-3 I I 3 I I 2 

AII-4 I I 3 I 2 2 

AII-5 2 I 2 3 I I 

AII-6 2 I 3 I 2 2 

AH-7 2 I 3 3 I 2 

AH-8 I I 2 I I I 

AH-9 2 I I 3 2 I 

AH-IO 2 I I 3 I 1 

All-II 2 I 2 3 I 2 

AII-I2 I I 4 I 2 2 

AII-13 2 I 2 I I 2 

AH-14 I I 2 I I 2 

AIl-15 2 2 3 1 2 2 

AII-16 2 I I 2 1 1 

AII-17 1 1 2 2 1 1 

AH-18 2 I 3 1 1 1 

AH-19 2 I 2 1 2 2 

AH-20 2 I 1 4 2 2 

AH-21 2 2 I 4 2 2 

AH-22 2 I 3 1 2 1 

AH-23 2 1 3 4 2 2 

AH-24 2 2 1 3 1 1 

AH-25 1 1 2 1 2 1 

I AH-26 2 1 4 1 1 2 

! AH-27 2 2 1 4 2 1 

AH-28 2 2 3 3 1 2 

AH-29 2 2 4 1 2 2 

AH-30 1 1 3 2 2 1 

RECS Data Mean # of Rooms 

# of Weight Bed- Full Half 

Homes rooms baths baths Other Floor plan 

35 578214 2 I 0 3 AH-C(ll) 

23 521245 2 2 I 3 AH-C(7) 

17 459153 2 I 0 2 AH-A(2) 

13 321363 2 I 0 3 AH-A(3) • 

14 316699 3 I 0 3 AH-C(l5) 

II 268691 2 2 I 3 AH-C(4) 

II 252037 3 2 I 3 AH-C(l6) 

16 233618 2 I 0 2 AH-A(2) 

II 231469 3 2 1 4 AH-C(17) 

15 220760 2 1 0 3 AH-C(II) 

15 212814 3 1 0 3 AH-C(l5) 

5 173022 2 1 0 2 AH-A(1) 

10 149352 2 2 1 2 AH-C(6) 

13 144284 2 1 0 2 AH-A(2) 

8 138425 3 1 0 3 AH-D(1) 

4 114912 2 1 0 2 AH-C(2) 

8 111713 1 1 0 2 AH-A(5) 

6 107467 2 1 0 2 AH-C(2) 

6 106839 2 1 0 3 AH-C(3) 

7 100827 3 1 0 3 AH-C(12) 

7 98706 3 I 0 3 AH-D(4) 

4 98643 2 2 I 2 AH-C(l) 

4 94223 3 2 1 3 AH-C(l3) 

6 91427 3 1 0 3 AH-D(5) 

6 91173 2 1 0 2 AH-A(1) 

3 90212 3 2 1 2 AH-C(5) 

5 89646 3 1 0 5 AH-D(6) 

4 85872 3 2 1 3 AH-D(7) 

2 83853 2 1 0 3 AH-D(2) 

6 80968 2 1 0 2 • __ AH-A(l) 
N 

V> 

House Variable RECS Data Mean # of Rooms 

House # of Floor Year Found Garage Forced # of Weight Bed- Full Half 

Number Floors area Built -ation -air Homes rooms baths baths Other Floor plan 

AH-31 1 1 2 3 1 2 4 80714 1 1 0 3 AH-A(7) 

AH-32 1 1 2 4 2 2 5 80666 2 1 0 3 AH-A(4) 

AH-33 1 1 1 3 1 2 4 79408 1 1 0 2 AH-A(6) 

AH-34 2 3 3 3 1 2 3 74965 4 3 2 4 AH-E(I) 

AII-35 2 1 2 1 1 1 5 73883 2 1 0 2 AH-C(2) 

AH-36 1 1 2 1 2 2 4 71401 2 1 0 2 AH-A(l) 

AH-37 1 1 2 2 2 1 4 68914 2 1 0 2 AH-A(l) 

AH-38 1 1 1 4 2 1 4 67275 2 1 0 3 AH-A(4) 

AH-39 1 1 4 1 1 2 3 65157 2 1 0 2 AH-A(2) 

AH-40 2 1 1 1 1 1 3 64445 1 1 0 1 AH-C(8) 

AH-41 2 2 2 3 1 2 3 63302 3 2 1 4 AH-D(8) 

AH-42 2 1 2 4 2 2 3 61601 2 1 0 3 AH-C(lO) 

AH-43 1 2 3 1 2 2 3 61587 3 1 0 3 AH-B(l) 

AH-44 1 1 3 2 1 1 4 60364 1 1 0 2 AH-A(5) 

AH-45 1 1 2 2 1 2 4 60074 2 1 0 2 AH-A(2) 

AH-46 2 1 2 2 1 2 2 59507 3 1 0 3 AH-C(9) 

AH-47 1 1 3 4 2 2 3 59499 3 2 1 3 AH-A(8) 

AH-48 2 1 3 2 1 2 5 54415 2 2 1 2 AH-C(6) 

AH-49 1 1 1 2 2 1 3 54145 2 1 0 2 AH-A(l) 

AH-50 2 1 3 2 2 2 3 53687 2 2 1 3 AH-C(4) 

AH-51 2 1 3 3 1 1 4 52821 2 1 0 3 AH-C(1l) 

AH-52 2 2 3 1 1 2 3 52106 3 2 1 4 AH-D(3) 

AH-53 1 1 4 2 1 2 3 51848 2 1 0 2 AH-A(2) - ---

Key for Table 

# of floors: 1 = one story; 2 = two story 

Floor area: 1 = less than 148.5 m2 (1,599 ft2); 2 = 148.6 m2 to 222.9 m

2 (1,600 ft2 to 2,399 ft2); 3 = 223.0 m2 (2,400 ft2) or more 

Year Built: 1 = before 1940; 2 = 1940-69; 3 = 1970-89; 4 = 1990 and newer 

Foundation: 1 = concrete slab; 2 = crawl space; 3 = finished basement, 4 = unfinished basement 

Garage: 1 = none; 2 = attached garage 

Forced Air: 1 = other; 2 = central system present 

RECS data/# of Homes: number of each home in the RECS survey 

RECS data/Weight: weighting factor of each home for all US housing 
~ 

TABLE B3. Modeling details - Manufactured Homes (4 total) 

Key to variables at end of table 

Model Floor Year Forced RECS: # of RECS: Mean # of Mean # 

Number area Built -air Homes Weil!ht Bedrooms of Baths 

MH-I 1 3 2 171 2664598 2 

MH-2 1 4 2 56 883158 3 

MH-3 1 3 I 39 595936 2 

MH-4 1 2 2 38 580199 2 

Key for Table 83: 

Floor area: 1 = less than 148.5 m

2 (1,599 fe); 2 = 148.6 m2 (1,600 ft2) or more 

Year Built: 1 = before 1940; 2 = 1940-69; 3 = 1970-89; 4 = 1990 and newer 

Forced Air: 1 = other; 2 = central system present 

RECS /# of Homes: number of each home in the RECS survey 

RECS /Weight: weighting factor of each home for all US housing 

1 

2 

I 

1 

Mean # of Mean # of 

Half baths Other rooms Floor plan 

0 2 MH-B(l) 

0 2 MH-A(l) 

0 2 MH-B(l) 

0 2 MH-B(l) 
N 

~I 

TABLE B4. Modeling details - Apartments (69 total) 

Key to variables at end of table 

House Variable 

Model #of # of Floor Year ForcedNumber Floors Units area Built air 

APT-I 2 3 1 3 2 

APT-2 3 3 1 3 2 

APT-3 4 5 1 3 1 

APT-4 2 I 1 1 1 

APT-5 2 1 1 2 1 

APT-6 2 2 1 3 2 

APT-7 2 1 1 2 2 

APT-8 2 2 2 3 2 

APT-9 2 1 I 3 2 

APT-IO 2 3 1 3 I 1 

APT-II 2 2 1 2 2 

APT-12 3 5 1 3 1 

APT-13 4 5 1 I 1 

APT-14 2 I 2 3 2 

APT-15 2 2 I 3 1 

APT-16 1 1 1 2 1 

APT-17 3 4 1 2 1 

APT-18 3 I 1 1 1 

APT-19 3 3 1 3 1 

APT-20 2 3 1 2 2 

APT-21 2 3 2 3 2 

APT-22 2 1 I 3 1 

APT-23 3 4 1 3 2 

APT-24 5 5 1 2 1 

APT-25 2 3 I 2 1 

APT-26 3 3 I 2 1 

APT-27 3 4 1 2 2 

APT-28 2 I 2 I 1 

APT-29 3 2 1 2 I 

APT-30 4 5 I 2 1 

RECS Data Mean # of Rooms 

# of Weight Bed- Full Half 

Homes rooms baths baths Other Floor plan 

42 664721 1 1 0 2 APT-2A(7) 

21 511570 2 1 0 2 APT-3A(7) 

37 489530 1 1 0 2 APT-4B(l) 

33 479427 1 1 0 2 APT-2A(l) 

27 459130 1 1 0 2 APT-2A(1) 

25 441017 1 1 0 2 APT-2A(4) 

19 389364 2 1 0 2 APT-2A(2) 

22 388484 2 2 0 2 APT-2B(3) 

19 344153 2 1 0 2 APT-2A(2) 

17 309964 I 1 0 2 APT-2A(7) 

14 285231 2 1 0 2 APT-2A(5) 

14 267078 1 1 0 2 APT-3A(lO) 

13 254804 1 1 0 2 APT-4B(l) ! 

13 246843 2 1 0 3 APT-2B(l) I 

17 245944 2 1 0 2 APT-2A(5) 

19 244120 2 1 0 2 APT-IA(2) 

16 223585 1 1 0 2 APT-3A(9) • 

19 213875 2 1 0 2 APT-3A(1) 

14 213350 2 1 0 2 APT-3A(7) 

16 209785 1 1 0 2 APT-2A(7) 

11 205202 2 I 0 2 APT-2B(6) 

14 204024 2 1 0 2 APT-2A(2) 

6 199294 1 1 0 2 APT-3A(9) 

14 174581 1 1 0 2 APT-5A(l) 

10 173628 1 1 0 2 APT-2A(7) 

11 170140 1 1 0 2 APT-3A(8) 

6 169678 1 1 0 2 APT-3A(9) I 

10 164628 3 1 0 3 APT-2B(2) 

14 160066 2 1 0 2 APT-3A(3) 

- , 12 156932 1 1 0 ~ _APT-4B(I) 
tv 

0\ 

Model 

Number 

APT-31 

APT-32 

APT-33 

APT-34 

APT-35 

APT-36 

APT-37 

APT-38 

APT-39 

APT-40 

APT-41 

APT-42 

APT-43 

APT-44 

APT-45 

APT-46 

APT-47 

APT-48 

APT-49 

APT-50 

APT-51 

APT-52 

APT-53 

APT-54 

APT-55 

APT-56 

APT-57 

APT-58 

APT-59 

APT-60 

APT-61 

APT-62 

,---APT-63 

# of 

Floors 

2 

2 

2 

3 

2 

4 

3 

2 

3 

2 

I 

3 

3 

3 

3 

3 

1 

3 

3 

3 

3 

4 

2 

2 

2 

2 

I 

2 

2 

3 

3 

2 

3 

# of 

Units 

2 

1 

5 

4 

2 

5 

5 

4 

4 

2 

2 

2 

3 

3 

5 

1 

1 

5 

5 

4 

I 

5 

5 

4 

2 

4 

2 

3 

2 

2 

2 

2 

5 

House Variable 

Floor Year Forcedarea Built air 

2 2 I 

1 I 2 

I 3 2 

1 1 I 

2 4 2 

I 3 2 

I 2 1 

I 3 2 

1 3 1 

1 2 1 

2 3 2 

I 1 1 

2 3 1 

I 1 1 

2 2 1 

1 2 1 

1 3 2 

1 1 1 

I 2 2 

2 3 2 

2 1 1 

1 2 2 

1 2 2 

I 3 1 

2 2 2 

1 2 I 

I 3 2 

2 2 1 

1 4 2 

1 4 2 

I 2 2 

1 4 1 

2 2 2 

RECS Data Mean # of Rooms I 

# of Weight Bed- Full Half I 

Homes rooms baths baths Other Floor plan i 

10 155497 2 1 0 2 APT-2B(4) I 

9 155420 1 1 0 3 APT-2A(3) I 

8 135934 1 1 0 2 APT-2A(10) 

8 132732 1 1 0 2 APT-3A(9) 

2 129848 2 1 1 2 APT-2B(5) 

11 129466 0 1 0 1 APT-4B(2) 

5 127308 1 1 0 2 APT-3A(l0) 

10 121922 1 I 0 2 APT-2A(8) 

9 120021 1 1 0 2 APT-3A(9) 

11 119872 2 I 0 2 APT-2A(5) 

6 116485 2 1 0 3 APT-IB(1) 

6 113702 2 1 0 3 APT-3A(4) 

7 113334 2 1 0 2 APT-3B(2) 

7 111144 1 1 0 2 APT-3A(8J 

5 109309 2 I 0 2 APT-3B(5) 

7 106822 2 1 0 3 APT-3A(2) 

7 106196 1 1 0 2 APT-lAO) 

8 105582 1 1 0 2 APT-3A(10) 

6 104279 1 I 0 2 APT-3A(10) 

2 100899 2 2 0 3 APT-3B(4) 

8 97205 3 1 0 3 APT-3B(1) 

3 96106 2 I 0 2 APT-4B(3) 

4 91792 2 I I 2 APT-2A(11) 

6 87866 2 1 0 2 APT-2A(9) 

4 86579 2 2 0 2 APT-2B(3) 

5 85183 1 1 0 2 APT-2A(8) 

5 83830 2 1 0 2 APT-IA(3) 

6 80915 2 1 0 2 APT-2B(6J 

3 74528 2 2 0 3 APT-2A(6) 

1 74274 2 I 1 2 APT-3A(S) 

3 73726 2 I 0 2 APT-3A(3) 

3 73558 1 1 0 2 APT-2A(4) 

3 71765 2 2 0 2 APT-3BJ61 
tv 

~l 

House Variable RECS Data Mean # of Rooms 

Model # of #of Floor Year Forced- #of Weight Bed- Full Half 

Number Floors Units area Built air Homes rooms baths baths Other Floor plan 

APT-64 2 3 I 4 2 4 71208 I I 0 2 APT-2A(7) 

APT-65 3 5 I 3 2 3 70356 1 1 0 2 APT-3AOO) 

APT-66 3 3 2 I 2 2 70066 2 I I 3 APT-3B(3) 

APT-67 I 3 I 2 I 3 69529 I 1 1 2 APT-IA(4) 

APT-68 3 2 1 3 1 3 66016 2 2 0 2 APT-3A(6) 

APT-69 4 2 -- I 4 -- 2 1 64924 ,- ~- 1 1 - 2 _ APT-4A(l) 

Key for Table B4: 

# of floors: 1 = 1 story; 2 = 2 story; 3 = 3 to 5 stories (modeled as 4); 4 = 6-15 stories (modeled as 10); 5 = 16+ stories (modeled as 10) 

# of units: 1 = 2 to 4 (modeled as 4); 2 = 5 to 9 (modeled as 6); 3 = 10 to 19 (modeled as 16); 4 = 20 to 39 (modeled as 32); 5 = 40+ 

units in building (modeled as 20 units per floor) 

Floor area: 1 = less than 92.8 m

2 (999 fe); 2 = 92.9 m2 (1,000 ft2) or more 

Year Built: 1 = before 1940; 2 = 1940-69; 3 = 1970-89; 4 = 1990 and newer 

Forced Air: 1 = other; 2 = central system present 

RECS data/# of Homes: number of each home in the RECS survey 

RECS data/Weight: weighting factor of each home for all US housing