Downtown High-Rise vs. Suburban Low-Rise Living: A Pilot Study on Urban Sustainability

Abstract

It is widely assumed that the “dense vertical city” is more sustainable than the “dispersed horizontal city.” This concept has certainly been a large factor in the unprecedented increase in the construction of tall buildings globally over the last few decades, especially in the developing world. The concentration of people in denser cities — sharing space, infrastructure, and facilities — is typically thought to offer much greater energy efficiency than the expanded horizontal city, which requires more land use, as well as a higher energy expenditure in infrastructure and mobility.

Though this belief in the sustainability benefits of ‘dense’ versus ‘dispersed’ living is driving the development of cities from Toronto to Tianjin and from Sau Paulo to Shanghai, the principle has rarely been examined at a detailed, quantitative level. Studies to date have been mostly based on large data sets of generalized data regarding whole-urban energy consumption, or large-scale transport patterns. Crucially, there are very few studies that also take into account a “quality of life” aspect to urban vs. suburban living, in addition to differences in energy use patterns.

Chicago, the city in which this research has taken place, is uniquely positioned for a study exploring density vs. sprawl from a sustainability point of view. The birthplace of the tall building and one of the main crucibles for experimentation in the typology in the century or more since then, Chicago also has an ever-growing suburban area that is typical of most US cities. And yet, again in line with many other cities around the world over the past decade or two, it has seen suburban growth alongside densification of its downtown area and a resurgence of people seeking high-rise urban living.

This research report offers a quantitative evaluation of long-held assumptions, and with sometimes surprising results. The ground-breaking study quantitatively investigates and compares the sustainability of people’s lifestyles in both urban and suburban areas from environmental and social perspectives, using detailed information directly collected from households and best available data from public resources. It fills significant research gaps in our knowledge of the sustainability of urban density compared to suburban sprawl. This is an indispensable resource for policy makers, developers, urban planners, architects, utilities, and anyone else with a stake in shaping the future of the built environment.

Full text

Peng Du & Antony Wood
Downtown
High-Rise vs.
Suburban
Low-Rise Living
A Pilot Study on Urban Sustainability
CTBUH Research Report

Bibliographic Reference: Du, P. & Wood, A. (2017) Downtown High-Rise vs. Suburban Low-Rise Living: A Pilot Study on Urban
Sustainability. Chicago: Council on Tall Buildings and Urban Habitat.
Principal Researchers / Authors: Peng Du & Antony Wood
Editorial Support: Jared Davis & Daniel Safarik
Layout: Jared Davis & Kristen Dobbins
© 2017 Council on Tall Buildings and Urban Habitat
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Front Cover: Clockwise from top left: Michigan Avenue Traffic © Ryan (cc-by-sa); Street in Oak Park © Jared Davis; Aerial
view of Chicago © Marchello74 | Dreamstime; Aqua Tower balconies © Steve Hall – Hedrich Blessing, Courtesy Studio Gang

Principal Researchers / Authors
Dr. Peng Du
Council on Tall Buildings and Urban Habitat
& Illinois Institute of Technology
Dr. Antony Wood
Council on Tall Buildings and Urban Habitat
& Illinois Institute of Technology
Contributors / Researchers
Dr. Brent Stephens
College of Engineering, Illinois Institute of Technology
Dr. Nicole Ditchman
Department of Psychology, Illinois Institute of Technology
Jared Davis
Council on Tall Buildings and Urban Habitat
Research Partners
Council on Tall Buildings and Urban Habitat
College of Architecture, Illinois Institute of Technology

| 5
Contents
Acknowledgements
Preface
0.0 Executive Summary
0.1 Introduction
0.2 Case Study Setting: Chicago
0.3 Demographics of Responding Residents
0.4 Summary of Key Findings
0.5 Research Limitations and Future Work
0.6 Next Steps
1.0 Introduction
1.1 Urbanization: Driver for Density
1.2 Objectives and Significance of Research
1.3 Case Study Setting: Chicago
2.0 Research Scope, Methodology and
Analysis of Data Sets
2.1 Sustainability Fields Assessed
2.2 Data Collection
2.3 Resident Involvement
2.4 Survey Response Summary
2.5 Demographics of Responding Residents
2.6 Housing Characteristics
2.7 Comparative Analysis and Summary
3.0 Building Operational Energy
3.1 Introduction
3.2 Analysis Methods
3.3 Energy Analysis: Suburban Low-Rise
3.4 Energy Analysis: Downtown High-Rise
3.5 Comparative Analysis and Summary
4.0 Building Embodied Energy
4.1 Introduction
4.2 Analysis Methods
4.3 Energy Analysis: Suburban Low-Rise
4.4 Energy Analysis: Downtown High-Rise
4.5 Comparative Analysis and Summary
5.0 Water Usage
5.1 Introduction
5.2 Analysis Methods
5.3 Water Usage: Downtown High-Rise
5.4 Water Usage: Suburban Low-Rise
5.5 Comparative Analysis and Summary
6.0 Mobility and Transport Movements
6.1 Introduction
6.2 Vehicle Ownership
07
09
10
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12
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25
26
27
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37
42
43
46
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56
57
60
60
61
63
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64
65
6.3 Bicycles
6.4 Travel Behavior
6.5 Comparative Analysis and Summary
7.0 Infrastructure Network Usage
7.1 Introduction
7.2 Considering Neighborhood
Population
7.3 Considering Road Networks
7.4 City Model and Study Areas
7.5 Population Analysis
7.6 Comparative Analysis and Summary
8.0 Public Open Space Usage
8.1 Introduction
8.2 Definitions and Data Sources
8.3 Analysis Methods
8.4 Comparative Analysis and Summary
9.0 Quality of Life
9.1 Introduction
9.2 Analysis Methods
9.3 Study Measures
9.4 Comparative Analysis and Summary
10.0 Conclusions, Limitations and Future
Work
10.1 Summary of Key Findings
10.2 Discussion Points
10.3 Comparison of Findings against
Published Studies
10.4 Research Limitations and Future Work
10.5 Next Steps
11.0 Appendices
A Research Questionnaire/Survey
B Degree Days Data
C Annual Operational Energy Data
D Water Usage Data
E Vehicle Types Data
F Population Data
G Public Open Space Data
References
Bibliography
About the Authors
About the Research Partners
CTBUH Organization & Members
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10 | Executive Summary
Executive Summary
0.0
0.1 Introduction
There has been a long-standing
debate on whether urban living
is more or less sustainable than
suburban living. Against the backdrop
of more than one million people
urbanizing on our planet every week
(UN, 2014), it has become generally
assumed that the “dense vertical” city
is more sustainable than the “dispersed
horizontal” city, which requires
more land usage as well as a higher
energy expenditure in infrastructure
and mobility.
Studies to date have, however, been
mostly generic, based on large data
sets of generalized data regarding
whole-urban energy consumption,
or large-scale transport patterns.
Crucially, there are very few studies
that also take into account a ‘quality of
life’ aspect to urban vs. suburban living,
in addition to the energy equation.
The fundamental objective of this
research project, then, is to investigate
and compare the sustainability of
people’s lifestyles in multiple key
areas from environmental and social
perspectives, using Chicago based
case studies. In doing this, though
it draws reference to large-scale
published studies, the emphasis
is placed on obtaining real quality
data wherever possible through, for
example, the obtaining of actual
home operational energy and water
bills, tracking transport movements
by all travel modes, or investigating
residents’ satisfaction with life and a
sense of community. The theoretical
framework for this study, including
all the topics embraced, is shown in
Figure 0.1.
The main vehicle for information
collection became an online
questionnaire which asked for
information such as the uploading of
energy bills, and took around 45-90
minutes to complete. The statistics on
questionnaire response rate is shown
in Figure 0.2.
0.2 Case Study Setting: Chicago
The research was undertaken based
on two case study sets. Households
in four residential towers spanning
two “downtown” Chicago areas (The
Loop and Lakeview) were selected
as the downtown case studies,
which resulted in 249 household
responses in the high-rise realm. A
similar sample size of 273 homes in
Oak Park, comprising single-family
detached homes and several duplex/
townhouses, comprise the suburban
case study. The geographic locations
and connected transportation systems
of the two case study sets are shown
in Figure 0.3, whilst Figure 0.4
shows more detail on the selected
case studies.
0.3 Demographics of Responding
Residents
Figure 0.5 shows the summarized
results of the resident and household
demographics. As can be seen in
the table, residents in both scenarios
were roughly evenly split by gender.
The majority of residents involved
in this study were ethnically white/
caucasian, at 88.6% of respondents in
Downtown high-rises and 88.4% of
respondents in Oak Park. The average
age of residents in the Downtown
high-rises was 51.1 years, significantly
higher than Oak Park, at 31.8 years. The
average household size of Downtown
residential towers (1.9) is comparable
to the US Census data (1.8 in the Loop
and 1.9 in Lakeview), but the average
household size of Oak Park low-rises
was significantly higher (3.4) than the
US Census data for Oak Park (2.4).
Respondents had a very high annual
household income in both urban and
suburban scenarios, at $220,541 per
year Downtown to $175,343 per year
in Oak Park, both significantly higher
than median household income in the
Chicago metropolitan area of $63,441
(CMAP, 2017).
Percentage of home ownership was
high from survey respondents, with
about 88% in both Downtown and
Oak Park. These results are likely due
to the survey targeting Downtown
condominium owners rather than
apartments, and mostly single-family
homes in Oak Park (percentage of
single family homes by Oak Park
respondents was high, at 75%).
Oak Park had more private parking
spaces per household, at 1.8,
compared to 1.4 Downtown, but
on a per-person basis, Downtown
high-rises actually had more private
parking spaces, at 0.6 spaces per
person compared to 0.5 in Oak Park.
Residences in Oak Park were larger
on average on a per-household basis,
with 226.4 m2 in gross floor area
compared to 147.1 m2 Downtown.
Interestingly, Downtown residents

Executive Summary | 11
Social
Environmental
Sustainability
Urban / Suburban
Infrastructure
Measurement
Mobility and Transport
Movements
Road
Assessment
of
Downtown
High-Rise
vs.
Suburban
Low-Rise
Living
Home Water
Consumpon
Energy
Consumpon Building (Home)
Operaonal Energy
(OE)
Embodied Energy
(EE)
Green Space
Plaza
Public Open Space
Infrastructure
Network
Walking / Bicycling
Public Transportaon
Automobile
Sasfacon with
Life Scale (SWLS)
Overall Residenal
Environment
Sense of Community
Index (SCI) Travel
Safety
Social Interacon
Accessibility
Quality of Life
(QoL)
Travel Behavior
Figure 0.1. Analytical framework of the factors affecting sustainability that were embraced in this research project.
Figure 0.2. Questionnaire response summary.
Downtown
High-Rise
Suburban
Low-Rise
Legacy Aqua Commonwealth
Plaza (2 Towers) All Four Towers Oak Park
Total No. of completed1 responses 41 40 31 112 123
Total No. of partially completed2 responses 76 29 32 137 150
Total No. of responses 117 69 63 249 273
Total No. of households contacted directly3357 264 375 996 565
Response rate 33% 26% 17% 25% 48%
Notes:
1 Considering that not all questions were compulsory, a “Completed” questionnaire has been considered as one in which 60-100% of questions were answered.
2 A “Partially Completed” questionnaire has been considered as one in which less than 60% of questions were answered.
3 The total number of households contacted directly in Aqua includes condominium units only (Note: Aqua has 738 units in the entire building, which includes 474 apartment units, 264
condominium households, and 332 hotel units). Due to legal issues raised by the building owner and management, only condo residents (264) were able to participate in the survey.
In Oak Park, this is the number of households the research team contacted personally and specifically, via direct mailing, local events, presentations, local government and school’s
assistance, personal connections, etc.

26 | Introduction
Introduction
1.0
1.1 Urbanization: Driver for Density
The United Nations forecasts that 66%
of the world’s projected 9.6 billion
inhabitants will live in urban areas
by the year 2050, up from 54% of
7.2 billion urbanized inhabitants as
of 2014 (UN, 2014). The enormity of
this total figure of 2.4 billion people
moving into cities over the next
several decades is perhaps more
clearly appreciated when converted
into an annual rate of nearly 67 million
people per year, or around 180,000
people per day. The human race will
need to build a new or expanded city
of more than one million people every
week for the next 40 years to cope
with this urban growth.
It is generally assumed that these
one million new urban dwellers every
week would be more sustainably
accommodated through the
densification of city centers, rather
than through the spread of suburban
low-rise “sprawl.” However, very few
studies have utilized building or
neighborhood-scale data sets to
evaluate major sustainability factors
associated with residents’ lifestyle
across both dense urban centers
and sprawled suburban areas. It
is even more critical to puncture
the assumptions on both sides of
the density vs. sprawl debate in
the USA, since the US population
has continued to simultaneously
urbanize as well as suburbanize.
As a share of total population, the
USA metropolitan population has
increased from 69% in 1970 to 80%
in 2000 (Hobbs & Stoops, 2002).
Within metropolitan areas, however,
the population has continued to
suburbanize. From 1970 to 2000, the
US suburban population more than
doubled, from 52.7 million to 113
million1. These dispersed, automobile-
oriented suburbanized patterns have
resulted in the occupation of vast
quantities of previously undeveloped
land, and increasing vehicle miles
traveled (VMT), which contribute
to increased energy usage and
greenhouse gas (GHG) emissions.
Specifically, passenger vehicle travel
on US highways has been increasing
at a much faster rate than either
population or developed land for
several decades (see Figure 1.1).
This phenomenon is especially
highlighted in Chicago, where there
has been a huge population shift from
city to suburbs over the 20th century
(see Figure 1.2). The population of the
City of Chicago peaked at 3.6 million
in 1950, containing 70% of the wider
metropolitan area residents. By 2000,
2.9 million Chicagoans made up
only 36% of the wider metropolitan
population (UIC, 2001), and the
remaining 64% were thus distributed
across suburbs. Actually, suburban
sprawl in Chicago is even greater than
imagined. A report released in 2014 by
Smart Growth America (SGA) analyzes
221 US Metropolitan Statistical Areas
(MSAs) and Metropolitan Divisions
with a population of at least 200,000,
and ranked cities from most dense
1 Source: US Census Bureau. Actually, the US Bureau of the Census does not identify a location as “suburban.” Metropolitan areas are divided into two classifications: (a) inside central
city and (b) outside central city; many researchers treat the latter areas as suburban (Giuliano, Agarwal, & Redfearn, 2008). This understanding is applied to the research in this paper.
Growth (1982 = 1.0)
Year
1982 1992 1997 2001 2003 2007
1.0
1.2
1.4
1.6
1.8
2.0
2.2
Vehicle Miles Traveled (VMT)
Developed Land
Fuel Use
Population
Real Displosable Personal Income
Figure 1.1. Growth in Real Disposable Personal Income, US Highway Passenger Vehicle Miles Traveled ( VMT),
Developed Land, Energy Consumption, and Population. Source: Transportation Research Board, 2009. Redrawn by CTBUH.

Introduction | 27
to most sprawling, based on four
factors: development density, land-
use mix, activity centering, and street
accessibility. Chicago was ranked 26th
on the densest cities list, even less
dense than Los Angeles, which has
been widely considered as one of the
most sprawling cities in the country
(SGA, 2014).
Location matters in terms of
environmental implications. Many
studies show a much lower energy
or carbon footprint per person in the
urban center than suburban areas, but
these results are typically generated
using a highly simplified equation, e.g.
“total energy consumption or carbon
emissions divided by total households/
population,” based on data sets at a
Figure 1.2. Developed Land in Chicago, 1900-2005. Source: CMAP, 2010, p. 66. Redrawn by CTBUH.
city or regional scale. The research
presented in this report moves beyond
these large generic data sets to study
actual household data at a much more
detailed level.
1.2 Objectives and Significance of
This Research
The fundamental objective of this
research project is to investigate and
compare the sustainability of people’s
lifestyles in multiple key areas from
environmental and social perspectives,
using Chicago based case studies. It is
expected to provide details on home
operational energy use; the embodied
energy of the dwelling; home water
consumption; mobility and transport
movements, including both private
and public transport; infrastructure
networks; public open space; and
quality of life, in both downtown
high-rise and suburban low-rise living,
using Downtown Chicago and the
suburban community of Oak Park
as case studies. Specifically, in both
cases, the study sought to evaluate
factors such as the actual monthly
energy consumption of the homes;
the embodied energy of the materials
that comprise the buildings in each
location; water usage by residential
buildings, for both indoor and outdoor
spaces; travel behavior via all modes
of transport including automobile,
public transport, walking, and biking;
infrastructure networks including
roads, highways, and alleys; and public
open space including parks and

32 | Research Scope, Methodology and Analysis of Data Sets
Research Scope, Methodology and
Analysis of Data Sets
2.0
2.1 Sustainability Fields Assessed
The fundamental objective of the
project is to quantitatively investigate
and compare the sustainability of
people’s lifestyles across high-rise
urban and low-rise suburban case
studies in seven key factors; (i) home
operational energy use, (ii) embodied
energy of the dwelling, (iii) home
water consumption, (iv) mobility
and transport movements, including
both private and public transport, (v)
infrastructure networks, (vi) public
open space, and (vii) quality of
life. Figure 2.1 shows the analytical
framework of the factors affecting
sustainability that are embraced within
this research. The key factors examined
are outlined in more detail below:
Building Operational Energy
Tracking the operational energy usage
of each residential unit (across both
high-rise and low-rise scenarios) was
one of the most important elements
of this project. Real energy bills were
collected over a 12-month period,
also taking into account, in the high-
rise case study, the energy required
for the common areas and facilities,
such as the lobby, corridors, elevators,
centralized cooling plant, services, etc.
(see Chapter 3).
Building Embodied Energy
This aspect of the research was
conducted based on an extensive
literature review of published
embodied energy studies in high-rise
and low-rise buildings. This study has
relied on the mean values of embodied
energy per floor area from existing
literature as a reasonable estimate for
the embodied energy of each building
type herein (see Chapter 4).
Water Usage
Water usage data is based on real
water bills from high-rise and low-
rise case studies for a 12-month
period. This included water usage for
both indoor and outdoor functions,
including swimming pools, irrigation,
toilets, clothes washing, showers,
etc. This data was used to determine
the average water consumption per
square meter, per household, and per
person in both Downtown and Oak
Park scenarios. (see Chapter 5).
Mobility and Transport Movements
Typical weekly mobility and transport
movements for each person in each
household were assessed through
questionnaires, and then this weekly
data extrapolated to annual values for
comparison. All modes of transport
were assessed, including by car,
on-foot, by bicycle, and by public
transport. Data recorded included travel
distance, journey frequency, mode of
transport, and travel time. In addition,
car ownership and the types of cars
were investigated (see Chapter 6).
Infrastructure Network Usage
The infrastructure network in this
study is based on the road networks
supporting the population in both
the urban center and suburbs. Since
many infrastructure networks follow
road networks (e.g. electricity, gas,
water and, of course, transport), both
area and length of road surfaces
were assessed in order to get some
appreciation of the relative amount
and density of infrastructure in both
scenarios. The amount of infrastructure
networks were assessed against the
total population in each area, including
a factor for daytime population gain/
loss through shifting work patterns. The
extent of “supporting” networks within
the “connecting area” neighborhoods
between city and suburb was also
considered (see Chapter 7).
Public Open Space Usage
Public open space in this study
included all the outdoor publicly-
accessible social spaces that support
interactions between people and their
neighborhood. The area of public
open space was measured, including
both publicly-accessible green space
and plaza space. This was also assessed
against the population in each area,
factoring in daytime population gain
and loss throughout the day and week
(see Chapter 8).
Quality of Life
This was perhaps the most difficult
aspect of the study to quantify, since
it normally relies on qualitative, rather
than quantitative, data. This factor
was assessed through comprehensive
questionnaires with the primary
responder in each residential
household across both case study
types. The questionnaire embraced
aspects such as life satisfaction, sense
of community, and satisfaction with
accessibility, safety, social interaction,
and mobility. (see Chapter 9).

Research Scope, Methodology and Analysis of Data Sets | 33
Social
Environmental
Sustainability
Urban / Suburban
Infrastructure
Measurement
Mobility and Transport
Movements
Road
Assessment
of
Downtown
High-Rise
vs.
Suburban
Low-Rise
Living
Home Water
Consumpon
Energy
Consumpon Building (Home)
Operaonal Energy
(OE)
Embodied Energy
(EE)
Green Space
Plaza
Public Open Space
Infrastructure
Network
Walking / Bicycling
Public Transportaon
Automobile
Sasfacon with
Life Scale (SWLS)
Overall Residenal
Environment
Sense of Community
Index (SCI) Travel
Safety
Social Interacon
Accessibility
Quality of Life
(QoL)
Travel Behavior
Figure 2.1. Analytical framework of the factors affecting sustainability that were embraced in this research project.
2.2 Data Collection
Though it also references large-
scale already-published studies, the
emphasis of this research project
was placed on obtaining real quality
data wherever possible. The main
data collection vehicle became a
comprehensive online survey created
using SurveyGizmo3 (see Appendix A
for the survey items). The study
launched in Oak Park in February 2014,
and Legacy, Commonwealth Plaza, and
Aqua in March, May, and June 2014,
respectively. The survey remained
open for approximately three months
in each case, though energy and water
bills for 12 months were collected.
Participants were recruited by a
combination of activities, including
advertising on the websites of
the buildings and their respective
community groups; email solicitations
to residents; advertising in the building
and/or community newsletters;
posting flyers in the buildings; mailing
letters to targeted households; and
giving presentations at social and
community events. Although it took
more than 45 minutes for a typical
resident to complete the survey, more
than 500 responses were received
from the 1,500 individuals contacted
directly. This 33% response rate can be
considered quite high.
3 SurveyGizmo is an online survey and form builder: www.surveygizmo.com. The authors would like to thank the Council on Tall Buildings and Urban Habitat (CTBUH) for its financial
support for this tool. (see Appendix A for the survey items)

46 | Building Operational Energy
Building Operational Energy3.0
3.1 Introduction
According to the US Energy Information
Administration (EIA), the building
sector (operations, construction and
materials) consumed nearly half (47.6%)
of all energy produced in the United
States in 2012, and building operations
specifically accounted for 41.7% of
this (Figure 3.1) (Architecture 2030,
2013). Therefore, the way buildings are
operated is a key factor in reducing
the total energy consumption of cities.
Operational energy (OE) is defined
for this study as an ongoing and
recurrent expenditure of energy that
is consumed to satisfy the demand
for day-to-day operations, including:
heating, cooling, lighting, ventilation,
appliances, equipment, etc.
3.2 Analysis Methods
For this research, the amount of annual
Operational Energy (OE) was gathered
from the participating buildings’
and individuals’ utility bills in both
downtown and Oak Park residences.
This included the following utilities:
• Electric
• Gas
• Chilled Water9 (in the high-rise
cases only)
The individual households in all
locations were asked to either submit
a copy of the most recent 12 months
of utility bills, including electric and/
or gas bills, or to enter the same data
directly into the online survey. In
addition, the management personnel at
the downtown residential towers were
asked to provide the most recent 12
months of utility bills10, including electric,
gas, and chilled water bills (if applicable),
for the entire building.
Aqua was unfortunately excluded
from this whole building operational
energy analysis because the energy
usage data received from its building
management was too limited to
be used to conduct a reasonable
OE analysis. Aqua is a mixed-use
building including condominiums,
apartments, and hotel spaces, with
all of the amenities accessible to all
permanent and temporary residents.
Unfortunately, its whole-building bills
reflected usage for the entire building,
and could not be broken down into
the needed space types, and thus
permanent condominium residents
could not be assigned individual unit
energy use.
Building Construction
and Materials
5.9%
Building Operations
41.7%
Industry
24.4%
Transportation:
Light Duty
(auto, SUV, pickup, minivan)
16.3%
Transportation:
Other
(rail, air, bus, truck, ship)
11.8%
Figure 3.1. US Energy Consumption by Sector. Source: Architecture 2030, 2013. Redrawn by CTBUH.
9 The chilled water in Aqua and Legacy is provided by the city’s district chilled water system, Thermal Chicago, which serves over 100 buildings within the city. It is one of the most
advanced, reliable, and efficient cooling systems in the world. The system includes five chilled water generation plants serving the Loop, West Loop, South Loop and River North areas.
Commonwealth Plaza has its own chillers, so does not have chilled water bills from Thermal Chicago. (International District Energy Association, 2014; Climate Control Middle East, 2011)
10 All the electric bills of the individual units/houses across both urban and suburban scenarios were ComEd bills, which typically show the past 13 months of consumption. So
residents only had to provide the latest electricity bill in order to provide 12 months’ data. See related survey questions in Appendix A.

Building Operational Energy | 47
The whole-building bills for different
residential towers covered different
operational categories and service areas.
For example, the whole-building bills at
Legacy covered electric, gas, and chilled
water usage for all public areas, plus
usage of heated and chilled water within
individual units. Conversely, the whole-
building bills in Commonwealth Plaza
covered electric and gas usage in public
areas as well as for cooking, heating,
and heated and chilled water within
individual units.
Since this study was predominantly
focused on a comparison across
building types with differing
energy-use systems, and was not
a commentary on the suitability of
those systems, all energy consumption
figures in the study are based on site
energy11. Energy units shown on all
utility bills (electric, gas, chilled water)
were all converted to megajoule or
gigajoule to enable comparisons across
energy types and buildings.
Because of slight differences in the
survey launch and completion dates
across the building case studies (see
Section 2.2, Chapter 2), the collected
utility data did not fall in the exact same
12-month period for all households.
Further, some of the collected utility data
did not cover a full 12-month period.
For example, the electricity usage data
provided by Home A may have covered
only 10 months from March 2013 to
December 2013, while the natural gas
usage data provided by Home B covered
11 months from May 2013 to April 2014.
Therefore, two approaches were taken
to provide a comparable 12-month
dataset for as many homes as possible:
(i) First, the 12-month period of April
2013 to March 2014 was chosen as the
common analysis period for annual OE
use, because it was the period of time
that contained the largest number of
overlapping utility bill responses.
(ii) Second, any missing data on
monthly energy use for individual
homes during any remaining months
in this 12-month period were
estimated by simple and/or multiple
linear regression models between
monthly energy use, monthly cooling
degree days (CDD), and/or monthly
heating degree days (HDD)12. The
regressions were constructed using
only the months for which there
were utility bill data. This approach,
emphasizing cooling degree days and
heating degree days, was considered
appropriate because heating and
cooling end-uses account for nearly half
of the annual energy use in a typical US
home, making space conditioning the
largest energy expense for most homes
(US EIA, 2014). Only those buildings/
households that provided at least eight
months of energy usage data across
all the applicable energy source types
(i.e., electric, gas, and chilled water
where applicable) were included in the
regression analysis.
For the cases that used electricity for
cooling and gas for heating, a linear
regression model was used to predict
the missing electricity usage associated
with CDD, and another linear regression
model was used to predict the missing
gas usage associated with HDD. For the
downtown residential towers that use
the city’s district chilled water system
for cooling, a linear regression model
was used to predict the missing chilled
water usage associated only with CDD,
based on the Equation Set 1 as shown
in Table 3.1.
In the cases that use electric energy for
both cooling and heating, a multiple
linear regression model was used to
predict the missing electric usage
associated with both CDD and HDD,
based on Equation Set 2 in Table 3.1.
The various site energy metrics from
the collected utility bills (i.e., “kWh” for
electricity bills, “therm” for gas bills, and
“ton-hour” for chilled water bills) were
all converted to gigajoule (GJ) using
Equation Set 3 in Table 3.1.
11 Site energy is considered as the energy directly consumed at a facility, typically measured with utility meters (i.e., the energy consumed directly by the buildings in their location).
Some studies consider “Source Energy,” which is the sum of the energy consumed at a facility as well as the energy required to extract, convert, and transport that useful energy to
the facility (Deru, 2007). The variance in Source Energy between a building using gas for heating/cooling or electricity for heating/cooling can be very high, so the focus in this study
became on site energy only.
12 Cooling degree days (CDD) is the number of degrees that a day’s average temperature is above 18°C (or 65°F), reflecting the demand for energy needed to cool a home. Heating
degree day (HDD) is the number of degrees that a day’s average temperature is under 18°C (or 65°F), reflecting the demand for energy needed to heat a home. See Appendix B for
monthly degree days in 2013 and 2014 for the City of Chicago and Oak Park.

54 | Building Embodied Energy
Building Embodied Energy4.0
4.1 Introduction
Embodied energy (EE) is the energy
consumed in all activities necessary
to support a process or produce
a product, and comprises a direct
and an indirect component (Baird
& Aun, 1983). Building embodied
energy typically consists of two main
elements: initial embodied energy
(EEi)18 and recurring embodied energy
(EEr)19. The building embodied energy
analysis in this study only accounted
for initial embodied energy, due to
the limited availability and reliability of
data for recurring embodied energy in
both low-rise and high-rise buildings.
4.2 Analysis Methods
The research did not undertake
a full detailed assessment of the
actual embodied energy in the case
study buildings, since the necessary
information for EE calculation (i.e.,
quantities and specifications of
materials used in the buildings) was
not available20. Instead, an extensive
literature review on published building
embodied energy studies was
conducted, in order to quantify typical
values for each type of construction.
Initial embodied energy varies with
location, but more significantly varies
with respect to the building materials
being supplied, rather than climate,
temperature and other operational
factors. Initial embodied energy mainly
consists of the energy consumed
in the acquisition, processing, and
manufacturing of raw materials into
building products, and in delivery and
construction on site. Also, it is worth
noting that embodied energy has
typically been estimated as a much
smaller contributor to the overall
life-cycle energy consumption for
residential buildings, compared to
operational energy use (Cole, 1998;
Keoleian et al., 2000; Ochoa et al., 2002;
Ramesh et al., 2010). Therefore, this
study has relied on the mean values
of EE per floor area from existing
literature as a reasonable estimate for
the EE of each building type herein.
The information collected across
previously published studies included:
building type; height (number of
floors); project location; area (m2);
structure/envelope material; research
method21; EE (GJ/m2); and source - see
tables to follow.
4.3 Energy Analysis: Suburban
Low-Rise
Table 4.1 shows an overview of
published research studies on building
EE for low-rise residential buildings. As
Figure 4.1 shows, estimated building
EE across each study varied from
as little as 2.9 GJ/m2 to as much as
15.2 GJ/m2, with variations driven
by a combination of differences in
estimation methodology and the case
study itself (e.g., different buildings
used different structural systems and
exterior walls, which required different
levels of embodied energy). Overall,
the average EE value of these low-rise
cases (1-2 stories) is 6.8 GJ/m2.
The single-detached house with
wood-frame structure dominated the
building characteristics and, as this
was also the dominant building type
in Oak Park, the average of the studies
(6.8 GJ/m2) was simply applied across
each home in our research study.
Therefore, this study relied on the
average value of EE (6.8 GJ/m2) of all
the cases in the published research
studies as a reasonable estimate for
the low-rise residential buildings in
Oak Park.
18 Initial embodied energy of a building is the energy use incurred during initial construction of the building.
19 Recurring embodied energy is the embodied energy in the materials used in the rehabilitation and maintenance of a building, since many of the materials used in building
construction/fit-out, etc. have a limited life span.
20 The original idea for the low-rise EE section of the research study was to apply different average EE values calculated from published research studies to the actual low-rise
residential buildings in Oak Park. The residents in Oak Park were thus asked to report their building information including building type (single-family house, duplex, townhouse,
apartment/condo building, or residential over retail), height (number of floors), construction system and exterior wall material (vinyl siding, stucco, brick, fiber cement, wood,
concrete block, or aluminum) in the survey. However in reality, the limited published research studies did not have such data and thus did not enable such an approach.
21 EE analysis methods include process analysis, input-output (I-O) analysis and hybrid analysis (Bullard, Penner, & Pilati, 1978; Treloar, O wen, & Fay, 2001; Treloar, Love, & Holt, 2001). A
process analysis has been defined as “the determination of the energy required by a process, and the energy required to provide inputs to the process, and the inputs to those processes,
and so forth. I-O analysis as “the use of national economic and energy data in a model to derive national average EE data in a comprehensive framework.” Hybrid analysis has been defined
as “the combination of process analysis and I–O analysis data”(Treloar, Love, & Holt, 2001). Hybrid analysis combines both process analysis and I-O analysis in order to reduce the errors
that are typically found among both. Hybrid EE analysis methods typically include process-based hybrid analysis (total energy intensities derived using I–O analysis are applied to product
quantities derived using process analysis) and I–O-based hybrid analysis (process analysis data is substituted into the I–O framework) (Treloar, Love, & Holt, 2001).

Building Embodied Energy | 55
Case
Study
Number
Type
No. of
Above-
Ground
Floors
Location Floor Area Structure Exterior Wall Embodied
Energy
Research
Method Source
1 Single-detached 1 Melbourne,
Australia 291.3 m2Wood-frame Brick veneer 13.4 GJ/m2Unknown (Crawford, 2012)
2 Single-detached 1 Melbourne,
Australia 42.5 m2Wood-frame Fiber cement
cladding 7.5 GJ/m2Process (Myer, Fuller, &
Crawford, 2012)
3 Single-detached 1 Melbourne,
Australia 42.5 m2Wood-frame Fiber cement
cladding 5.4 GJ/m2Process (Myer, Fuller, &
Crawford, 2012)1
4 Single-detached 1 Orebro, Sweden 130 m2Wood-frame Wood panelling 3.7 GJ/m2I-O (Adalberth, 1997)
5 Single-detached 1 Orebro, Sweden 129 m2Wood-frame Wood panelling 6.5 GJ/m2I-O (Adalberth, 1997)
6 Single-detached 2 Orebro, Sweden 138 m2Wood-frame Wood panelling 2.9 GJ/m2I-O (Adalberth, 1997)
7 Single-detached 2 Sweden 144 m2Unknown unknown 3.5 GJ/m2I-O-based
hybrid
(Gustavsson &
Joelsson, 2010)
8 Single-detached 1 Phoenix, USA 186 m2Unknown Wood Shingles 6.8 GJ/m2I-O-based
hybrid (Frijia, 2011)2
9 Single-detached 1 Phoenix, USA 186 m2Unknown Brick 6.8 GJ/m2I-O-based
hybrid (Frijia, 2011)2
10 Single-detached 1 Phoenix, USA 186 m2Unknown Painted Block 6.3 GJ/m2I-O-based
hybrid (Frijia, 2011)2
11 Single-detached 1 Phoenix, USA 186 m2Unknown Stucco 6.2 GJ/m2I-O-based
hybrid (Frijia, 2011)2
12 Single-detached 2 Phoenix, USA 186 m2Unknown Wood Shingles 5.4 GJ/m2I-O-based
hybrid (Frijia, 2011)2
13 Single-detached 2 Phoenix, USA 186 m2Unknown Brick 5.4 GJ/m2I-O-based
hybrid (Frijia, 2011)2
14 Single-detached 2 Phoenix, USA 186 m2Unknown Painted Block 5.1 GJ/m2I-O-based
hybrid (Frijia, 2011)2
15 Single-detached 2Phoenix, USA 186 m2Unknown Stucco 5 GJ/m2I-O-based
hybrid (Frijia, 2011)2
16 Single-detached 2Melbourne,
Australia 128 m2Unknown Brick veneer 14.1 G J/m2I-O-based
hybrid (Fay et al., 2000)
17 Single-detached 2Melbourne,
Australia 128 m2Unknown Brick veneer 15.2 G J/m2I-O-based
hybrid (Fay et al., 2000)1
18 Semi-detached 2Lingwood, UK 91 m2Wood-frame Larch cladding 5.7 GJ/m2Process (Monahan & Powell,
2011)3
19 Semi-detached 2Lingwood, UK 91 m2Wood-frame Brick veneer 7.7 GJ/m2Process (Monahan & Powell,
2011)3
20 Semi-detached 2Lingwood, UK 91 m2Masonry cavit y wall Brick cladding 8.2 GJ/m 2Process (Monahan & Powell,
2011)3
21 Single-detached 2Toronto, Canada Various Wood-frame Brick 4.6 GJ/m2I-O-based
hybrid
(Norman et al.,
2006)
22 Single-detached 2Ann Arbor, USA 228 m2Wood-frame Unknown 6.6 GJ/m2Process (Keoleian et al.,
2000)
23 Single-detached 2Ann Arbor, USA 228 m2Wood-frame Unknown 7.3 GJ/m2Process (Keoleian et al.,
2000)
24 Semi-detached 2Melbourne,
Australia 123 m2Wood-frame Brick veneer 6.8 GJ/m2I-O-based
hybrid
(Treloar, Love, &
Holt, 2001)
25 Detached 2Gothenburg,
Sweden Unknown Unknown Unknown 6.2 GJ/m2Process-based
hybrid (Thormark, 2002)4
26 Unknown Unknown Various Various Various Various 5.9 GJ/m2I-O (Pullen, 2000)5
27 Single-detached Unknown N/A 199.7 m2Wood-frame Unknown 6.4 GJ/m2I-O (EPA, 2013)
Average N/A 1.6 N/A 155 m2N/A N/A 6.8 GJ/m2N/A N/A
Notes:
1 Cases that were an energy-efficient model.
2 The models developed in this study used four different exterior wall materials across five different sizes including 139, 186, 228, 279 and 325 m2. Only the models with the
size of 186 m2 were included in this table since 186 m2 is considered to be the typical single-family house size in the US. According to the US Census, the average floor area
of a single-family house completed in the Midwest region from 1973 to 2010 was estimated to be 183 m2 (US Census, 2017).
3 This study was based on a low-energy affordable house (91 m2) constructed in 2008, and examined the embodied energy in three scenarios, by changing the structure
and wall material parameters.
4 This case study consisted of 20 apartments in four two-story rows. Each apartment has a net residential floor area of 120 m2.
5 This research was conducted using 25 houses as case studies, which ranged in size from 91 to 320 m2 and varied in structure/material. The EE in the table is the mean
value.
Table 4.1. Overview of published research studies on the embodied energy (EE) of low-rise residential buildings.

60 | Water Usage
Water Usage5.0
5.1 Introduction
Water is necessary for human
existence, but is, however, a finite
resource subject to ever-increasing
demand. Along with population and
urban growth, the demands on public
water supply have been increasing.
Global water use was found to have
grown at twice the rate of human
population within the last century
(UN Water, 2017). The United States
Geological Survey (USGS) states that
total water withdrawals for public
supply in the US in 2005 were 167.3
billion liters per day, 316% of the 53
billion liters per day withdrawal in 1950.
In the same period, the United States’
population has only increased 194%
from 150 million in 1950 to 295 million
in 2005 (US Census Bureau, 2017). This
means that water withdrawals in the US
grew 1.6 times more than population in
the same time period.
Public water supply is typically divided
into three usage categories: domestic,
commercial, and industrial. In the US,
domestic water supply, which includes
all uses at a residential level, including
potable drinking water, toilets, clothes
washing, showers, faucets, outdoor
(e.g. swimming pools, irrigation,
outdoor cleaning, etc.), leaks, and so
on, and it makes up the largest portion
of the three use categories, at 57%
(USGS, 2010). Figure 5.1 shows that
the largest domestic consumption in
Chicago of water is by outdoor uses,
followed by toilet usage, and cloth
washing (Sustainable Chicago, 2015).
5.2 Analysis Methods
The amount of annual water
consumption per household was
gathered from the participating
buildings’ and individuals’ water bills
in both downtown and Oak Park
residences. The downtown high-rises
included households in three existing
residential towers, the Legacy at
Millennium Park and Commonwealth
Plaza (2 towers)23. The water
consumption data for Legacy and
Commonwealth Plaza was provided
by each building’s management. Data
included the total water consumption
of both common areas and individual
units, within the whole buildings;
individual residences did not have
individual water bills. Thus, the whole-
building bills24 covered all water usage
for the high-rise examples.
Outdoors
30%
Toilets
19%
Clothes
Washing
15%
Showers
12%
Faucets for
Drinking,
Cooking, Etc.
11%
Leaks
9%
Other
4%
23 Aqua was unfortunately excluded from the water consumption analysis because the data received from its building management was too limited to be used to conduct a reasonable
water consumption analysis. Unfortunately, the whole-building water bills reflected usage for the entire building, and could not be broken down into the three space types, including
condominiums, apartments, and hotel, for this study. Thus permanent condominium residents could not be assigned individual unit water consumptions.
24 Both buildings reported a full 12-month water usage data for the required year-long time frame. Commonwealth Plaza pays bills on a bimonthly basis, thus receiving six bills per year,
while Legacy pays bills on a monthly basis, thus receiving 12 bills per year.
Figure 5.1. Residential Water Use. (Sustainable Chicago, 2015). Redrawn by CTBUH.

Water Usage | 61
The whole-building water data was
considered against the total floor
area of the buildings to determine
total water consumption per floor
area. It was then converted to a
per-household, and per-person basis,
based on the demographic data of
the towers, as seen in previous Table
2.8 on Page 42.
The water consumption data for the
Oak Park residences was collected
via the same online survey (see
Appendix A), as well as via the Oak
Park municipal government. The
individual households were asked
to either submit a copy of the most
recent four consecutive water bills25
or to enter the same data directly into
the online survey. Water data for each
household was used, in conjunction
25 Sixty-five households in Oak Park reported their full
12-month water data for the required year-long time
frame. Individual residences pay water bills on a quarterly
basis, thus receiving four bills per year.
26 In the survey the unit of water consumption was asked
in gallons, as the majority of the survey takers were
American. Gallons were then converted to 1,000 liters
(k.liters) for the calculation analysis in this chapter, in order
to apply a global standard to the results.
27 Due to different quarterly billing cycles for Oak Park
residences, water bills varied from an August 2012-July
2013 billing cycle to a October 2012-September 2013
billing cycle. Full details of quarterly water usage per
residence are shown in Appendix D.
“Total water withdrawals for public
supply in the US in 2005 were
316% of the per day withdrawal
in 1950. Water withdrawals in the
US have grown 1.6 times more
than population in the same
time period. ”
with the total floor area and household
size of each residence, to determine the
average water consumption per square
meter, per household, and per person
in Oak Park.
The common unit to express water
usage was per 1,000 liters of water
(k.liter)26. Similar to the operational
energy data, the collected household
data did not fall in the exact same
12-month period for all households,
because of differences in survey launch
and completion times. For Legacy,
water consumption was reported
in monthly bills from March 2013 to
February 2014. At Commonwealth
Plaza, water consumption was reported
in bimonthly bills collected from
November 2012 to October 2013. In
Oak Park, water consumption was
reported in quarterly bills covering
the period from August 2012 to
September 2013 (See Appendix D for
full individual household usage in Oak
Park)27. Because 70% of residential water
consumption is based on indoor usage
and not subject to seasonal changes, as
shown in Figure 5.1, and consumption
covered a full 12-month period with
all seasons, this slight mismatch in the
months covered was deemed to not
be a significant factor affecting the
collected water consumption data.
5.3 Water Usage: Downtown
High-Rise
Based on total water usage, whole
building area, average area of
household, and average household
size, the water usage in the high-rise

It is widely assumed that the “dense vertical city” is more sustainable than the
“dispersed horizontal city.” This concept has certainly been a large factor in the
unprecedented increase in the construction of tall buildings globally over the last
two decades, especially in the developing world. The concentration of people in
denser cities — sharing space, infrastructure, and facilities — is typically thought
to offer much greater energy efficiency than the expanded horizontal city, which
requires more land use, as well as a higher energy expenditure in infrastructure
and mobility.
Though this belief in the sustainability benefits of ‘dense’ versus ‘dispersed’ living
is driving the development of cities from Toronto to Tianjin and from Sau Paulo to
Shanghai, the principle has rarely been examined at a detailed, quantitative level.
Studies to date have been mostly based on large data sets of generalized data
regarding whole-urban energy consumption, or large-scale transport patterns. In
some cases, seminal studies are still informing policy that is now several decades
out of date. For instance, a study of 32 cities by Newman & Kenworthy in 1989
concluded that there was a strong link between urban development densities
and petroleum consumption (Newman & Kenworthy, 1989). This study is still
commonly cited, despite being 28 years old. Crucially, there are very few studies
that also take into account a “quality of life” aspect to urban vs. suburban living, in
addition to differences in energy use patterns.
Chicago, the city in which this research has taken place, is uniquely positioned
for a study exploring density vs. sprawl from a sustainability point of view. The
birthplace of the tall building and the main crucible for experimentation in the
typology in the century or more since then, Chicago also has an ever-growing
suburban area that is typical of most US cities. And yet, again in line with many
other cities around the world over the past decade or two, it has seen suburban
growth alongside densification of its downtown area and a resurgence of people
seeking high-rise urban living.
This research report offers a quantitative evaluation of long-held assumptions,
and with sometimes surprising results. The ground-breaking study quantitatively
investigates and compares the sustainability of people’s lifestyles in both urban
and suburban areas from environmental and social perspectives, using actual
energy bills collected from households, as well as other direct research methods..
It fills significant research gaps in our knowledge of the sustainability of urban
density compared to suburban sprawl, in terms of both environmental and social
sustainability. This is an indispensable resource for urban planners, architects,
utilities, developers, and anyone else with a stake in shaping the future of the built
environment.
Research Undertaken in Conjunction With: