Content uploaded by Peng Du
Author content
All content in this area was uploaded by Peng Du on Feb 22, 2016
Content may be subject to copyright.
Buildings 2015, 5, 1003-1024; doi:10.3390/buildings5031003
buildings
ISSN 2075-5309
www.mdpi.com/journal/buildings/
Article
Life-Cycle Energy Implications of Downtown High-Rise vs.
Suburban Low-Rise Living: An Overview and Quantitative
Case Study for Chicago
Peng Du 1,*, Antony Wood 1, Brent Stephens 2 and Xiaoyu Song 3
1 Council on Tall Buildings and Urban Habitat/College of Architecture, Illinois Institute of
Technology, 3360 South State Street, Chicago, IL 60616, USA; E-Mail: awood@ctbuh.org
2 Department of Civil, Architectural and Environmental Engineering, Illinois Institute of Technology,
3201 South Dearborn Street, Chicago, IL 60616, USA; E-Mail: brent@iit.edu
3 College of Architecture and Urban Planning, Tongji University, Shanghai 200092, China;
E-Mail: s-xyu@163.com
* Author to whom correspondence should be addressed; E-Mail: pdu@hawk.iit.edu;
Tel.: +1-312-567-3588.
Academic Editor: Kheir Al-Kodmany
Received: 30 June 2015 / Accepted: 25 August 2015 / Published: 7 September 2015
Abstract: It is commonly accepted that the concentration of people in high-density urban
city centers, which are typically dominated by medium- and high-rise buildings located
close to public transit systems, offers greater overall energy efficiency and lower life-cycle
greenhouse gas emissions than lower-density expanded suburbs, which are dominated by
low-rise single-family buildings and larger per-person automobile travel requirements.
However, few studies have combined quantitative analyses of the life-cycle energy use of
both buildings and transportation in both urban and suburban areas, especially in American
cities. This work uses a variety of data sources to provide a quantitative comparison of the
life-cycle energy consumption associated with residential life (including buildings,
transportation, and supporting infrastructure) in prototypical downtown high-rises and
suburban low-rises in and around Chicago, IL. We estimate that downtown high-rise living
in Chicago, IL accounts for approximately 25% more life-cycle energy per person per year
than suburban low-rise living, on average, contrary to some common beliefs (best
estimates were ~141 and ~113 GJ/person/year, respectively). Building operational energy
use was found to be the largest contributor of the total life-cycle energy in both the
OPEN ACCESS
Buildings 2015, 5 1004
downtown high-rise and suburban low-rise cases, followed by vehicle operational energy.
Keywords: life cycle assessment (LCA); high-rise; energy; embodied energy;
infrastructure; Chicago
1. Introduction
The U.S. population has continued to urbanize and suburbanize in recent decades. As a share of
total population, the metropolitan population increased from 69% in 1970 to 80% in 2000 [1]. Within
metropolitan areas, however, the population has mostly continued to suburbanize. From 1970 to 2000,
the suburban population in the United States more than doubled, from 52.7 million to 113 million [2].
This phenomenon is especially highlighted in Chicago, IL, where there has been a large population
shift from the city to the suburbs over the last half of the 20th century. According to the U.S. Census
Bureau, the population of the City of Chicago peaked at 3.6 million in 1950 and contained
approximately 70% of metropolitan area residents. By 2000, 2.9 million people in the City of Chicago
made up only 36% of the region’s population [3]. Actually, U.S. 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, and they
are so treated in this paper [3].
It is widely accepted that the concentration of people in high-density downtown city centers, which
are dominated by medium- and high-rise buildings located close to a variety of public transit systems,
offers greater overall energy efficiency and lower life-cycle greenhouse gas emissions than
lower-density expanded suburbs, which are dominated by low-rise single-family buildings and larger
per-person automobile travel requirements [4–7]. To account for the total life-cycle energy use and
greenhouse gas emissions of a particular living area, one must consider both the embodied and
operating energy consumed during all phases of the life-cycle of two key sectors: buildings and
transportation. A number of studies have examined the energy use and/or greenhouse gas emissions
associated with low-rise residential buildings (i.e., single-family homes or small multi-family
buildings) from a life-cycle perspective. A common finding for low-rise residential buildings has been
that energy requirements for building operations tend to dominate overall life-cycle energy
consumption compared to the embodied energy required for construction [8–11]. Unfortunately, very
little data are available in the literature on either the embodied or operational energy use of high-rise
buildings, which limits many direct comparisons of high-rise and low-rise buildings [12].
Further, many studies have explored the energy impacts of varied travel behaviors and have indicated
that neighborhood characteristics such as density, levels of mixed land use, accessibility to public transit
services, and the presence of pedestrian-friendly environments can contribute to a less car-dependent
environment and lead to energy savings and reduced greenhouse gas emissions for transportation purposes
alone [4,13]. For example, a study of 32 cities by Newman and Kenworthy concluded that there was a
strong link between urban development densities and petroleum consumption [4].
However, few studies have combined quantitative analyses of the life-cycle energy use and/or
greenhouse gas emissions of both buildings and transportation in both urban and suburban areas.
Buildings 2015, 5 1005
A few recent studies that have done so for cities such as Helsinki, Finland; Halifax, Canada; and
Adelaide, Australia suggest that high-density urban areas may not actually lead to more energy- or
carbon-efficient lifestyles [14–17], contrary to common beliefs. However, we are not aware of any
similar comparisons in U.S. cities. Therefore, this work examines the life-cycle energy implications of
downtown high-rise living compared to suburban low-rise living based on two distinct case studies in
and around Chicago, IL using a variety of data sources and estimation methods. We specifically
consider the following components of residential living: (1) the embodied and operational energy use
of a prototypical code-compliant residential building of recent construction in each location
(e.g., a high-rise in downtown Chicago, IL, and a low-rise residence in suburban Aurora, IL),
(2) the embodied and operational energy for vehicle transport for multiple modes of transport
including automobile, bus, train, and others based on average travel patterns in each location, and
(3) the embodied and operational energy for transportation infrastructure for multiple modes of
transport including automobile, bus, and train.
2. Case Studies
The research was based on two study areas in Chicago: Chicago Loop as a downtown high-rise
case, and Aurora as a suburban low-rise case. Their geographic locations are shown in Figure 1.
Figure 1. Site locations and transportation systems including Chicago Transit Authority
(CTA) train lines, Metra lines, and major highways.
Chicago has a long history at the forefront of skyscraper development. In the downtown Chicago Loop
area, high-density residential communities and tall buildings dominate the housing type and all public
transportation, including train lines and numerous bus lines, are easily accessible to a number of
communities. Conversely, in Aurora, low-density residential communities and single-family homes
dominate the housing type (single-family homes make up ~74% of homes in Aurora [18]). Aurora is the
final stop of the Metra’s Burlington Northern Santa Fe (BNSF) Line connecting to downtown Chicago, and
also operates a Pace suburban bus system connecting to the surrounding cities, although most travel occurs
Buildings 2015, 5 1006
via automobile. Figure 2 shows the distinctly different urban layouts of typical residential communities in
the two study areas.
Table 1 outlines the basic characteristics of the two study areas with data culled from a variety of
sources. Generally, the Chicago Loop area indeed has a higher population density, lower household (HH)
size, and lower vehicle miles traveled (VMT) than Aurora.
(a)
(b)
Figure 2. Urban layouts of typical residential communities in the (a) downtown Chicago
Loop and (b) suburban Aurora.
Table 1. Basic characteristics of the two study areas.
Basic Characteristics
Chicago Loop
Aurora
Urban Pattern
Downtown area
Suburb area
Population [18]
28,614
198,726
Distance to Downtown
Walkable
Avg. 50 miles
Avg. HH Size [18]
1.6
3.2
Avg. Floor Area Occupied per Person (m2) *
66
66
Avg. Annual VMT per HH [18]
6406 miles
20,150 miles
Avg. Annual VMT per Person *
4004 miles
6297 miles
Public Transportation All CTA Lines, All Metra
Lines, and Multiple Bus Lines
Metra BNFT Line and
Pace Buses
Note: * Calculated by the authors. Specifically, there is no data available indicating the average floor area of
either a unit of downtown high-rises in Chicago or a single-family house in Aurora. According to the US
Census, the average floor area of a single-family house completed in Midwest in 2010 was 210 m2 [19], and
the average floor area of a multi-family unit completed in Midwest in 2010 was 106 m2 [20], which is
assumed to be representative of an average floor area of a unit in downtown high-rises.
3. Methodology
3.1. LCA Analysis: An Overview
Life cycle assessment (LCA) involves quantifying environmental impacts throughout a product’s life,
from raw material acquisition through production, use, and disposal (i.e., cradle-to-grave) [21]. By
including the impacts throughout the product’s life cycle, LCA provides a comprehensive view of the
environmental aspects of the product or process and a more accurate picture of the true environmental
trade-offs in product and process selection. Therefore, the life-cycle energy of a particular building or
transportation network can be expressed as the sum of embodied energy (EE) + operational energy (OE) +
Buildings 2015, 5 1007
demolition energy (DE) (Demolition energy is required to demolish a building and transport the waste
materials to landfill sites and/or recycling plants). However, this study does not account for demolition
energy due to the very limited data availability and relatively minimal contribution of the life-cycle energy
in residential buildings [10].
Embodied energy (EE) is the energy consumed in all activities necessary to support a process, and
comprises both a direct and an indirect component [22]. Embodied energy in buildings typically
consists of two main elements: initial embodied energy (Initial embodied energy of a building is the
energy incurred for initial construction of the building) and recurring embodied energy (Recurring
embodied energy is the embodied energy in the materials used in the rehabilitation and maintenance of
a building, since some of the materials used in building construction may have a life span). The
building embodied energy analysis in this work only accounts 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. Compared to embodied energy, operational energy (OE) is an ongoing and recurrent
expenditure of energy that is consumed to satisfy the demand for day-to-day operation process. The
operational energy of a building is consumed to satisfy the demand for heating, cooling, lighting,
ventilation, appliances, equipment, etc.
3.2. Research Scope and Analysis
The research phases involve estimating the embodied and operational energy for the two case study
buildings in Chicago and Aurora, vehicle embodied and operational energy, and transportation
infrastructure embodied and operational energy via multiple modes of transport including automobile,
CTA bus, Pace bus, school bus, CTA train, and Metra. Table 2 outlines the research framework
including research phase, scope, and data sources, and the subsequent subsections describe our
methods for gathering data for each outcome. Throughout the paper, source (i.e., primary) energy is
used for inputs and outputs to provide an equivalent comparison across all domains.
Table 2. Research phase, scope, and data sources.
Research Phase
Research Scope
Data Sources
Building EE
Initial EE
Existing literature
Building OE
OE of the entire building facility
US DOE prototype building models
Transportation
EE and OE
Vehicle and supporting
infrastructure of automobile, CTA
bus, Pace bus, school bus, CTA
train, and Metra
US Census, 2011 American Community Survey,
Chicago Metropolitan Agency for Planning
(CMAP), Illinois Secretary of State, The
Transportation LCA Database (tLCAdb) [23]
3.2.1. Building Operational Energy
Building operational energy (OE) varies with climate zone, envelope materials and thermal
properties, vintage, equipment, occupancy, and many other parameters. We have relied on a
comparison of prototypical code-compliant residential buildings of recent construction in each location,
including a high-rise residential building in Chicago and a low-rise residence in Aurora. For simplicity, we
use the U.S. Department of Energy’s prototype single-family detached residential house [24] and high-rise
Buildings 2015, 5 1008
apartment buildings [25] as case studies for each location (Table 3). We consider the annual operating
energy for each building as the modeled source energy per conditioned building area reported from
their original simulations. We gathered predicted operating energy use for four variations of the
high-rise apartment building model (meeting ASHRAE Standard 90.1 version 2004, 2007, 2010 and 2013)
and three variations of the single-family model (meeting International Energy Conservation Code
(IECC) 2006, 2009, and 2012) to gain a broader representation of typical energy use in prototypical
residences over the last 10 years or so. We should note that there is no Aurora-based low-rise
residential prototype model from the U.S. Department of Energy (DOE), so the one located in Peoria,
IL was chosen, which is the closest location to Chicago in this series of prototype models. These
prototype buildings are primarily chosen to illustrate a common building type that is generally
representative for each location and are not meant to take into account the wide variations in energy
consumption of each building type typically observed across the building stock.
Table 3. Characteristics of the high-rise and low-rise residential prototype models.
Characteristics
High-Rise
Low-Rise
Type *
High-rise apartment building
Single-family detached house
Location
Chicago, IL
Peoria, IL
Number of floors
10
N/A
Conditioned Building Area (ft2)
75,992
2,401
Energy simulation program
EnergyPlus Version 8.0
EnergyPlus Version 5.0
Annual OE (MJ/m2)
1843 (STD 2004)
1802 (STD 2007)
1663 (STD 2010)
1559 (STD 2013)
1246 (IECC 2006)
1187 (IECC 2009)
998 (IECC 2012)
Note: * The function of high-rise models was relatively simple. Each floor has eight apartments except the
ground floor, which included seven apartments and one lobby with equivalent apartment area. The
single-family detached model with gas furnace heating system and unheated basement was chosen, because
this is the most common type of single-family house in the Midwestern region of the United States [26]. In
the statistics for new single-family houses completed in the United States, the other heating system types
included electric resistance, oil furnace, and heat pump, and the other foundation types include slab,
crawlspace, and heated basement.
As Table 3 shows, the prototypical high-rise buildings are predicted to consume more annual
operational energy than low-rise buildings per conditioned floor area. The average OE across the four
high-rise cases was 1717 MJ/m2/year (standard deviation (SD) = 130) and 1143 MJ/m2/year
(SD = 130) across the three low-rise cases. The ratio of high-rise OE to low-rise OE was approximately
1.5, on average. In a comparison of high-rise vs. low-rise end use OE using the most recent code-built
models (see Figure 3), it is clear that heating energy is much higher in the low-rise model compared to
the high-rise model, as expected given a greater exposed enclosure area, but all other end uses are
lower for a number of reasons (e.g., towers required more cooling, more fan energy, more lighting, and
more water systems on an area-normalized basis than do low-rises).
The ratio of high-rise OE to low-rise OE being greater than 1 based on the digital prototype modes
is also supported by data on existing buildings from the Building Performance Database (BPD), which
is currently the largest publically available source of actual measured building energy performance
Buildings 2015, 5 1009
data [27]. According to BPD, residential buildings containing five units or more consumed an average
of 1678 MJ/m2/year in Climate Zone 5A (Cool-Humid, represented by Chicago, IL) while
single-family homes consumed only 889 MJ/m2/year on average in the same climate zone (for a ratio
of high-rise OE to low-rise OE of 1.89). Thus we consider these OE estimates appropriate for the
analysis herein. We should note that we did not use data from the BPD because the sample sizes, when
limited to Chicago alone, were too small to yield a meaningful comparison (There is no data available
for residential buildings containing 5 units and more in Chicago, IL, so the data was collected from a
larger area—5A Cool-Humid (Chicago, IL) climate zone. Specially, the sample was 17 for residential
buildings containing 5 units and more, and 2497 for single-family houses).
Further, we also estimated OE on a per person basis using both the average floor area occupied per
person and the average floor area of each home type (i.e., 210 m2 for a typical low-rise home and
106 m2 for a typical high-rise unit, as reported in Table 1). In this manner, residents in the prototypical
high-rise model are assumed to consume approximately 112.9 GJ/person/year (SD = 8.6) and residents
in the low-rise home are assumed to consume approximately 75.9 GJ/person/year (SD = 8.6).
Figure 3. High-rise (STD 2013) vs. low-rise (IECC 2012) building end use operational
energy (OE) for the U.S. DOE prototype building models.
3.2.2. Building Embodied Energy
Next, rather than undertaking a full assessment of the actual embodied energy in the two
prototypical case study buildings, we instead conducted a literature review on building embodied
energy (EE) in order to quantify typical values for each type of construction. Initial embodied energy
mainly consists of the energy consumed in the acquisition, processing, and manufacturing of raw
materials. Unlike operational energy, initial embodied energy varies primarily with respect to the type
and quantity of building materials used, rather than climate zone or other operational factors. Also,
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 [8–11]. Therefore,
we simply rely on the mean value of EE per floor area from the existing literature as a reasonable
estimate for each building type herein. The information collected across published previous studies
includes building type, height (number of floors), project location, structure, life cycle quantification
0
100
200
300
400
500
0
5
10
15
20
25
30
35
40
45
50
Building OE (MJ/m2)
Building OE (kBtu/ft2)
High-rise
Low-rise
Buildings 2015, 5 1010
method EE (kBtu/ft2 and GJ/m2) (EE analysis methods include process analysis, input-output (I-O)
analysis and hybrid analysis [28–30]. A process analysis is 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”; and hybrid analysis as “the
combination of process analysis and I-O analysis data” [30]. 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) [30], the EE literature includes
various case studies across different countries, so the metrics they used vary. The authors converted all
the Imperial and US customary units to SI units. However, both kBtu/ft2 and GJ/m2 units are presented
in embodied and operational energy comparison charts for different audiences) and source.
Table 4 shows an overview of existing building EE literature for low-rise residential buildings and
Figure 4 shows the estimated building EE from each study. Low-rise residential building EE is
estimated to vary from as little as 2900 MJ/m2 to as much as 15,200 MJ/m2, with differences driven by
a combination of differences in estimation methodology (e.g., I-O, I-O-based hybrid, or process) and
the case study itself (e.g., different buildings use different structures and exterior walls, which require
different levels of embodied energy). Overall, the average value of EE of these low-rise cases
(1–2 stories) is approximately 7007 MJ/m2 (SD = 3356). It is likely most appropriate to focus on
estimates made using only similar estimation methods, but we use an average across all case studies
given the relatively small sample sizes involved. Further, Figure 5 shows that there is no correlation
between estimated EE and building height for the low-rise cases.
Table 4. Overview of literature on embodied energy (EE) of low-rise residential buildings.
Case
No.
Type No. of
Floors *
Location Structure Method Source
1
Single-detached
1
Australia
Wood-frame
I-O-based hybrid
[31]
2
Single-detached
1
Australia Wood-frame Process [32]
3 **
Single-detached
1
4
Single-detached
1
Sweden
Wood-frame
Process [33]
5
Single-detached
1
Sweden
Wood-frame
6
Single-detached
2
Sweden
Wood-frame
7
Single-detached
2
Sweden
N/A
I-O
[34]
8
Single-detached
1
USA
N/A
I-O-based hybrid [35] ***
9
Single-detached
1
USA
N/A
10
Single-detached
1
USA
N/A
11
Single-detached
1
USA
N/A
12
Single-detached
2
USA
N/A
13
Single-detached
2
USA
N/A
14
Single-detached
2
USA
N/A
15
Single-detached
2
USA
N/A
16
Single-detached
2
Australia
N/A
I-O-based hybrid [36]
17 **
Single-detached
2
Australia
N/A
Buildings 2015, 5 1011
Table 4. Cont.
Case
No.
Type No. of
Floors *
Location Structure Method Source
18
Semi-detached
2
UK
Wood-frame
Process [37]
19
Semi-detached
2
UK
Wood-frame
20 Semi-detached 2 UK Masonry
cavity wall
21
Single-detached
2
Canada
Wood-frame
I-O-based hybrid
[7]
22
Single-detached
2
USA
Wood-frame
Process [9]
23 **
Single-detached
2
USA
Wood-frame
24
Semi-detached
2
Australia
Wood-frame
I-O-based hybrid
[30]
25
Detached
2
Sweden
N/A
Process-based hybrid
[38]
26
N/A
N/A
N/A
N/A
I-O
[39] ****
27
Single-detached
N/A
N/A
Wood-frame
I-O
[40]
Note: * Number of stories above ground. ** The second case was an energy efficient model. *** The models developed
in the research 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 approximately 186 m2 is considered a
typical single-family house in the United States. **** The 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 was the mean value.
Figure 4. Embodied energy (EE) of low-rise building case studies in the literature.
Figure 5. Correlation between embodied energy (EE) and building height for low-rise case
studies in the literature.
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
0
200
400
600
800
1000
1200
1400
1600
1234567891011 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27
Low-rise building EE (MJ/m
2
)
Low-rise building EE (kBtu/ft
2
)
Case Number
Mean = 7007 MJ/m
2
R² = 0.0094
0
2000
4000
6000
8000
10000
12000
14000
16000
18000
0
200
400
600
800
1000
1200
1400
1600
0123
Low-rise building EE (MJ/m
2
)
Low-rise building EE (kBtu/ft
2
)
Height (Number of floors)
Buildings 2015, 5 1012
Fewer published studies have estimated the embodied energy of tall buildings, largely due to the
complexity of projects and limited data availability. However, one of the many criticisms leveled at tall
buildings is the high quantities of structure and materials required to support, clad, and service them,
coupled with energy intensive construction at height [41]. We surveyed the existing literature review
and summarize several studies in Table 5. A number of estimation methods have been used in these
cases as well. We should note that there are numerous definitions of what constitutes a “high-rise” or
“tall building”. The Council on Tall Buildings and Urban Habitat (CTBUH) considers 14 or more stories,
or a height of more than 50 m (165 ft), as a reasonable threshold for defining a “tall” building, although
they also claim that there is actually no absolute definition of what constitutes a tall building [42].
ASHRAE classifies a tall building as a building taller than 100 m (328 ft), which was increased from
their previous reference of 91 m (300 ft) [43]. The National Fire Incident Reporting System (NFIRS)
defines a “high-rise” building as having a height above ground of seven or more stories [44].
Due to the limited availability of published EE studies on high-rise buildings, we rely on the more
conservative NFIRS definition of a tall building in order to gather as much data as possible from
the literature.
Table 5. Overview of literature on embodied energy (EE) of high-rise buildings.
Case
No.
Type No. of
Floors *
Location Structure Method Source
1
Office
7
Australia
Reinforced concrete
I-O-based hybrid [45]
2
Office
15
Australia
Reinforced concrete
3
Office
42
Australia
Reinforced concrete
4
Office
52
Australia
Reinforced concrete
5
Office
7–9
Japan
N/A
I-O
[46] **
6 Office 8 Japan Steel reinforced concrete
+ Steel
I-O [47]
7
Office
8
Japan
Steel reinforced concrete
8
Office
18
Japan
Steel
9
Office
25
Japan
Steel
10
Office
31
Japan
Steel
11
Residential
15
Canada
N/A
I-O
[7]
12 Education 19 China N/A Process-based
hybrid
[48]
13
Office
38
Thailand
Concrete
I-O-based hybrid
[49]
14
Residential
40
Hong Kong
N/A Process-based
hybrid
[50]
15
Residential
40
Hong Kong
Note: * Number of stories above ground. ** Ten office buildings were examined in the study, including 8
seven-story buildings, 1 eight-story building, and 1 nine-story building. The building size varied from 1253
to 22,982 m2. Six of the buildings were reinforced concrete structures, three were reinforced concrete and
steel, and one was steel. The EE in the table was the mean value of these 10 buildings. The height was
assumed to be seven floors in the correlation analysis between EE and building height shown in Figure 7.
The average value of estimated embodied energy of high-rise buildings (seven stories or higher)
was found to be approximately 10,451 MJ/m2 (SD = 3356) (see Figure 6), which is indeed higher than
Buildings 2015, 5 1013
the average for low-rise residences (by approximately 50%). Interestingly, there was also a very weak
correlation between EE and building height in these high-rise cases (see Figure 7).
Figure 6. Embodied energy (EE) of high-rise building case studies in the literature.
Figure 7. Correlation between embodied energy (EE) and building height for high-rise
case studies in the literature.
For simplicity’s sake, we took only the mean values from these data and, assuming population statistics
from the Chicago Loop and Aurora (Table 1), used them to estimate the embodied energy (EE) for both
types of construction. We estimate that the EE for the prototypical high-rise building would be
approximately 687 GJ/person (SD = 278) and approximately 465 GJ/person (SD = 223) for the
low-rise building. Thus, we assume that high-rise construction requires about 50% more EE per person
than low-rise construction, on average. We also use the standard deviation as a measure of uncertainty
in this parameter later in our analysis.
3.2.3. Transportation Embodied and Operational Energy
Next, we quantified the life-cycle energy requirements per person for transportation in the Chicago
Loop and in Aurora based on a survey of mobility via different transportation modes including
0
2500
5000
7500
10000
12500
15000
17500
20000
0
200
400
600
800
1000
1200
1400
1600
1800
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
Hihg-rise building EE (MJ/m
2
)
High-rise building EE (kBtu/ft
2
)
Case Number
Mean = 10451 MJ/m
2
R² = 0.0423
0
2500
5000
7500
10000
12500
15000
17500
20000
0
200
400
600
800
1000
1200
1400
1600
1800
010 20 30 40 50 60
High-rise building EE (MJ/m
2
)
High-rise building EE (kBtu/ft
2
)
Height (Number of floors)
Buildings 2015, 5 1014
automobile, CTA/Pace/school bus, CTA train, and Metra. These publically available data are reported
in the Chicago Regional Household Travel Inventory from the Chicago Metropolitan Agency for
Planning (CMAP) [51]. Part of this transportation section was previously presented in a recent
conference paper by the authors [52], but the data was updated in CMAP in March 2015 and changes
are reflected here [18]. According to these data, the total mileage traveled per person by public
transportation modes was calculated and shown in Table 6. Due to the limited open data about travel
behavior via public transportation modes at the neighborhood scale, the study assumed that the share
of total mileage of travel by mode in the Loop is the same as in the “Central Chicago” area, and Aurora
is the same as the “Eastern Kane county” area in which Aurora is located.
Table 6. Annual mileage traveled per person (miles/person/year) by different
transportation modes in the two study areas.
Study Area
Automobile
CTA/Pace Bus
School Bus
CTA Train
Metra
Chicago Loop
4004
764.8
24.1
572.6
144.2
Aurora
6297
7.3
103.2
0.0
574.9
Next, data from Table 6 were used with data from the transportation LCA database (tLCAdb) [23]
to estimate the life-cycle embodied and operational energy use for each mode of transportation in each
location for the average household. Table 7 outlines the system boundary of analysis with life cycle
groupings and generalized life cycle components for each of the transportation modes. As Table 7
shows, the embodied energy of vehicle includes the energy consumed in vehicle manufacturing and
maintenance process, and the embodied energy of infrastructure includes the energy consumed in the
construction and maintenance process for the infrastructure.
For each component in a transportation mode life cycle, the average energy performance was
calculated and then normalized on a per passenger-mile-traveled (PMT) basis, using estimates from the
transportation LCA database (tLCAdb) [23]. Data on three typical categories of automobiles (sedan,
SUV and pick-up truck) were available in the transportation LCA database (tLCAdb). The tLCAdb
selected the most typical vehicles representing these three automobile categories—A sedan presented
by Toyota Camry, an SUV presented by Chevrolet TrailBlazer, and a pick-up truck presented by Ford
F-Series [53]. We used the data on sedan from tLCAdb to present the average automobile in our study.
The travel modes have different life-cycle energy profiles, as shown in Table 8, which outlines the
estimated energy usage per PMT of four different transportation modes including automobile, bus,
CTA train, and Metra. The vehicle operational energy portion of each mode clearly consumes more
operational energy than its embodied energy per PMT, but the infrastructure of each mode requires
more embodied energy than operational energy per PMT. Further, the energy required for vehicle
operation shares the largest portion in each mode, especially for automobile (OE makes up ~71.3% of
total energy) and bus (OE makes up ~82.8% of total energy).
Based on the data in Tables 6 and 8, the average life-cycle energy associated with annual mileage
traveled per person via different transportation modes across the two locations was estimated (shown
in Table 9 and Figure 8). The results show that the average Aurora resident is estimated to consume
approximately 28 GJ/person/year for transportation (vehicle + infrastructure), which is about 1.3 times
greater than the estimate for the average Chicago Loop resident (approximately 21.2 GJ/person/year).
Buildings 2015, 5 1015
Intuitively, we estimate that Loop residents consume approximately 4.3 GJ/person/year for public
transport, about 2.8 times greater than Aurora, but only 16.9 GJ/person/year for private transport, which is
far less than the estimate of 26.5 GJ/person/year in Aurora.
Table 7. Life-cycle assessment of the system boundary. HVAC: Heating, ventilating, and
air conditioning
LCA
Component
Automobile CTA/Pace/School Bus CTA Train/Metra
Vehicle
Manufacturing
Manufacturing
Manufacturing
Manufacturing
Maintenance Typical Maintenance Tire
Replacement
Typical Maintenance
Tire Replacement
Routine Maintenance
Flooring Replacement
Operation Propulsion Propulsion
Idling
Propulsion
Idling
HVAC
Infrastructure
Construction Roadway
Parking Roadway
Station
Station Parking
Track
Maintenance Parking Roadway
Station
Station Parking
Track
Operation Roadway Lighting Roadway Lighting
Station Lighting
Station Parking Lighting
Station Escalators
Station Train Control
Station miscellaneous
Table 8. Assumptions of energy use per passenger-mile-traveled (MJ/PMT) for multiple
transportation modes from tLCAdb.
LCA Energy Component
Automobile
Bus
CTA Train
Metra
Value
Percent
Value
Percent
Value
Percent
Value
Percent
Vehicle EE
0.55
13.1%
0.45
12.0%
0.07
3.7%
0.17
8.9%
Vehicle OE
3.00
71.3%
3.10
82.8%
1.13
60.1%
1.07
55.7%
Infrastructure EE
0.62
14.7%
0.19
5.1%
0.62
33.0%
0.42
21.9%
Infrastructure OE
0.04
1.0%
0.002
0.1%
0.06
3.2%
0.26
13.5%
Total life-cycle energy (MJ/PMT)
4.21
100%
3.74
100%
1.88
100%
1.92
100%
Note: Data was calculated based on the transportation LCA database (tLCAdb) [23].
As Figure 8 shows, although the life-cycle energy for public transport for an average resident in the
Chicago Loop is estimated to be greater than Aurora in each of the four categories, the total life-cycle
energy required for auto transport in Chicago Loop is estimated to be far less than Aurora in each of
the four categories, especially for vehicle operational energy use. The total life-cycle energy in
Chicago Loop for transportation (vehicle + infrastructure) is approximately 75% of the total life-cycle
energy in Aurora (approximately 21.2 compared to 28.0 GJ/person/year). This confirms the benefits of
Buildings 2015, 5 1016
transit-oriented development (TOD) for reducing travel energy requirements, and also demonstrates
that reducing automobile usage and new roadway construction is a key component in lowering the
energy required for transportation purposes.
Table 9. Estimates of annual embodied and operational energy (GJ/person/pear) by vehicle
and supporting infrastructure for all transportation modes across the two study locations.
LCA Energy
Component
Loop
Aurora
Auto Bus CTA
Train
Metra Total Auto Bus CTA
Train
Metra Total
Vehicle EE
2.20
0.36
0.04
0.02
2.62
3.46
0.05
0
0.10
3.61
Vehicle OE
12.01
2.45
0.65
0.15
15.26
18.89
0.34
0
0.62
19.85
Infrastructure
EE
2.48 0.15 0.36 0.06 3.05 3.90 0.02 0 0.24 4.16
Infrastructure
OE
0.16 0.002 0.03 0.04 0.23 0.25 0 0 0.15 0.40
Total life-cycle
energy
(GJ/person/year)
16.86 2.95 1.08 0.27 21.16 26.51 0.41 0 1.10 28.02
Figure 8. Estimated annual embodied and operational energy (GJ/person/year) for all
transportation modes across the two study locations.
3.3. Overall Life-Cycle Energy Comparison of Downtown High-Rise vs. Suburban Low-Rise Living
Finally, we combine the buildings and transportation energy data to make a direct comparison of the
overall life-cycle energy requirements associated with typical residential life in the downtown
high-rise and suburban low-rise locations. This involved summing the results of all six categories
including building embodied energy, building operational energy, vehicle embodied energy, vehicle
operational energy, infrastructure embodied energy, and infrastructure operational energy on a per-person
per-year basis (e.g., GJ/person/year was used as the functional unit for an equivalent comparison).
0
5
10
15
20
25
30
Auto Bus CTA
Train
Metra Auto Bus CTA
Train
Metra Total Total
Loop Aurora Loop Aurora
Annual energy requirements for transportation
(GJ/person/year)
Vehicle EE Vehicle OE Infrastructure EE Infrastructure OE
Buildings 2015, 5 1017
In order to convert the one-time initial embodied energy required for building construction to an
annualized value for comparison to the other measures, we assumed that the lifespan of high-rises is
100 years and that the lifespan of low-rises is 50 years. Although there is not much data available to
verify this assumption, we consider these to be reasonable. For one, the American Housing Survey
from the Oregon Department of Environmental Quality (DEQ) [54] reported that the service life of a
non-residential wood structure was 51.6 years. This life span was adopted as a proxy for the lifespan of
U.S. single-family homes because of the similarity between the non-residential wood structures and
U.S. single-family homes in the use of wood as the dominant construction material [40]. It is more
difficult to estimate the life span of a typical high-rise building, but 100 years is considered as a
reasonable estimate based on the authors’ knowledge of existing high-rise building construction
around the world and in Chicago. Thus, it was calculated that high-rises account for approximately
6.9 GJ/person/year in initial embodied energy when annualized over its lifespan and the low-rises
account for approximately 9.3 GJ/person/year.
As Figure 9 and Table 10 show, the average resident living in a typical Chicago downtown high-rise
of recent construction is estimated to account for approximately 141 GJ/person/year in overall
life-cycle energy use, while those in Aurora low-rises account for only 113 GJ/person/year, yielding a
ratio of downtown high-rise to suburban low-rise of approximately 1.25 (i.e., 25% greater for
downtown high-rise living).
Figure 9. Annual life-cycle energy (GJ/person/year) associated with residential life in
high-rises in the downtown Chicago Loop and low-rise residences in suburban Aurora, IL.
These data suggest that when accounting for building construction, building energy use,
transportation infrastructure, and travel modes across these two locations, downtown high-rise living is
estimated to account for approximately 25% more life-cycle energy use than suburban low-rise living
based on the methods and best estimates of inputs used herein. This result is in conflict with some
early studies by Norman et al. and Perkins et al. [7,55], but generally in line with others [15,16].
0
20
40
60
80
100
120
140
160
High-rise (Loop) Low-rise (Aurora)
Annual life-cycle energy (GJ/person/year)
Infrastructure OE
Infrastructure EE
Vehicle OE
Vehicle EE
Building OE
Building EE
Buildings 2015, 5 1018
Interestingly, building operational energy use was estimated to be the largest contributor of the total
life-cycle energy in both the downtown high-rise and suburban low-rise cases (even when accounting
for uncertainty in building OE for these building types), followed by vehicle operational energy.
Building OE accounted for approximately 80.1% and vehicle OE for 10.8% of the total life-cycle
energy in the downtown high-rise scenario, while building OE accounted for 67.1% and vehicle OE for
17.5% of the total life-cycle energy in suburban low-rise scenario. Thus, the combined operational
energy of building, vehicles, and infrastructure dominates the overall life-cycle energy usage in both
downtown high-rise (91.1%) and suburban low-rise (85.0%) scenarios compared to relatively low
values of embodied energy.
In comparison to previous studies, we should note that building operational energy, which has been
widely confirmed as one of the largest contributors of the total life-cycle energy associated with
residential life, did not account for as large of a portion of overall energy use in the studies by
Norman et al. and Perkins et al. [7,55] as it did in our study. This difference drives most of the
differences in findings between our study and theirs. This difference may be attributable in part to
methodological differences in our studies (e.g., Norman et al. [7] used country-wide average data for
specific building cases in Toronto and Perkins et al. [55] used data collected via interviews with residents).
Table 10. Annual life-cycle energy (GJ/person/year) associated with residential life in
high-rises in the downtown Chicago Loop and low-rise residences in suburban Aurora, IL.
LCA Energy Component
High-Rises in Loop
(Downtown)
Low-Rises in Aurora
(Suburb)
Value
Percent
Value
Percent
Building EE
6.9
4.9%
9.3
8.2%
Building OE
112.9
80.1%
75.9
67.1%
Vehicle EE
2.6
1.9%
3.6
3.2%
Vehicle OE
15.3
10.8%
19.8
17.5%
Infrastructure EE
3
2.2%
4.2
3.7%
Infrastructure OE
0.2
0.2%
0.4
0.4%
Total life-cycle energy
(GJ/person/year)
141.0 100% 113.1 100%
4. Discussion and Conclusions
This work provides a quantitative comparison of life-cycle energy consumption associated with typical
residential life in downtown high-rises and suburban low-rises in and around Chicago. The comparisons
were made using a variety of data sources and estimation methods, but the findings of this study provide a
reasonably complete understanding of overall life-cycle energy consumption by different residential types
in terms of residents’ life (building, transportation, and supporting infrastructure) in Chicago and
surrounding suburbs. The key findings and conclusions are summarized below.
4.1. Building Embodied Energy
Based on an extensive literature review, we estimate that high-rise residential buildings account for
more initial embodied energy than low-rise residential buildings (on both per area and per person basis)
Buildings 2015, 5 1019
due to the high quantities of structure and materials required for high-rise construction. However, if we
assume that the life span of high-rises is longer, high-rises actually consume less initial embodied
energy when annualized over their lifespan. Although this result was based on limited studies on
high-rise embodied energy with a limited research scope and data availability, as well as the authors’
assumptions on building lifespan, it still provides a reasonably complete understanding of the factors
that contribute to building embodied energy, as well as a greater potential of tall building’s embodied
energy in terms of an even longer lifespan (According to CTBUH Skyscraper Center database, only
four skyscrapers (taller than 150 m) have been demolished in the last 50 years: the Singer Building in
New York (187 m), the Morrison Hotel in Chicago (160 m), the Deutsche Bank in New York (158 m)
and the One Meridian Plaza in Philadelphia (150 m)). Moreover, the results herein also show that
embodied energy in building construction is not a large contributor to overall life-cycle energy
consumption. Building EE was estimated to account for only 4.9% of the overall annual life-cycle
energy of downtown high-rises and only 8.2% of suburban low-rises on a per person basis. We should
note that there was considerable variability in the values for building EE reported in Figures 4 and 6,
so the mean values may not be the most suitable for our case study buildings in and around Chicago.
As an estimate of the sensitivity of our results to this variation, if the upper ends of the ranges for both
high-rise and low-rise building EE are used, building EE would account for 8.3% and 16.2% of the
overall annual per-person life-cycle energy use of downtown high-rises and suburban low-rises,
respectively. Similarly, if the lower ends of the reported ranges are used, building EE would account
for only 1.8% and 3.5% of the overall annual per-person life-cycle energy use of downtown high-rises and
suburban low-rises, respectively. While our building EE results are quite sensitive to this input parameter,
building OE still dominates life-cycle energy use regardless of the assumption for building EE.
We should also note that we only consider initial embodied energy according to the limited availability
and reliability of data for recurring embodied energy buildings. However, recurring embodied energy could
be a major factor that increases the portion of embodied energy of the overall life-cycle energy from the
perspective of a long-term lifespan of buildings, especially for tall buildings. Unfortunately, there are no
data available for recurring embodied energy of tall buildings, as far as we are aware. The literature on
embodied energy of low-rise buildings in this study shows that the ratio of recurring embodied energy to
initial embodied energy in a 50-year lifespan ranges from 13.5% [38] to 94% [40].
4.2. Building Operational Energy
Our results show that the prototypical high-rise building case study used herein was estimated to
consume approximately 112.9 GJ/person/year in building operational energy while the low-rise model
was estimated to consume only 75.9 GJ/person/year. This is contrary to the common belief that
high-rises should be more energy efficient in the operation phase because of a smaller surface area of
envelope per floor area for heat losses and gains and higher density occupancy. However, there are
many other energy end uses in relatively densely populated high-rises that lead to higher energy
requirements overall per area and per person. These data also demonstrate that building operational
energy is the single greatest contributor of the overall life-cycle energy for both urban and suburban
locations investigated herein. Building OE was estimated to account for approximately 80.1% of the
overall annual life-cycle energy of downtown high-rises and 67.1% of suburban low-rises on a per
Buildings 2015, 5 1020
person basis. This indicates that improving the energy efficiency of the building operation is the key to
reduce the overall life-cycle energy usage in terms of the residents’ lifestyle for these case studies.
We should also note that the residential prototype building cases in this study were relatively
simplified digital models. The high-rise case only included one small lobby on the ground floor, but
many residential tall buildings in cities actually include multiple larger-size common areas such as a
package room, gym, party room, laundry, and others, which would tend to increase the estimate of
operational energy. Therefore, residents who live in downtown high-rises might consume even more
operational energy by sharing the energy usage by the common areas from this point of view. We also
do not explore the wide variety of building operational energy use that exists beyond the averages used
for the prototypical case studies. A case study on energy efficient construction would yield different
results than the cases used herein, as would a case study on older vintage construction in each area.
4.3. Transportation Embodied and Operational Energy
The estimated life-cycle energy consumed by the downtown high-rise residents was estimated to be
lower than for those who live in suburban low-rises in all transportation categories. Specifically,
downtown high-rise residents were estimated to consume 2.6 GJ/person/year for vehicle embodied
energy, 15.3 GJ/person/year for vehicle operational energy, 3 GJ/person/year for infrastructure
embodied energy, and 0.2 GJ/person/year for infrastructure operational energy. Conversely, suburban
low-rise residents consumed 3.6 GJ/person/year for vehicle embodied energy, 19.8 GJ/person/year for
vehicle operational energy, 4.2 GJ/person/year for infrastructure embodied energy, and 0.4 GJ/person/year
for infrastructure operational energy. Vehicle operational energy was estimated to be the second
greatest contributor to the overall life-cycle energy in both locations, accounting for 10.8% of the
overall annual life-cycle energy of the downtown high-rise case study and 17.5% of the suburban
low-rise case study on a per person basis. Moreover, the total transportation sector (vehicle +
infrastructure) was estimated to account for 15.0% of the overall annual life-cycle energy of downtown
high-rises and 24.8% of suburban low-rises.
We should note that we did not explore the wide variety of automobile vehicle type and ownership
that exists beyond the averages used for travel data. For example, suburban low-rise residents might
tend to own larger automobiles than downtown high-rise residents, but we were unable to obtain this
information from our data sources. The automobile data used for the transportation section in this work
was based solely on a regular sedan type (representative of the average vehicle), but a study on
different vehicle types and ownerships across the two residential locations would likely yield different
results for both embodied energy and operational energy for vehicles and infrastructure. This should be
taken into account in future work.
Overall, this paper provides a reasonably complete understanding of the average life-cycle energy
consumption for downtown high-rise and suburban low-rise living in and around Chicago, IL. Future
work should focus on improving limited public data availability, collecting actual energy and travel
data from individual occupants, and accounting for other life-cycle environmental impact categories
such as greenhouse gas (GHG) emissions and global warming potential (GWP).
Buildings 2015, 5 1021
Acknowledgments
The authors gratefully acknowledge financial support from the Council on Tall Buildings and
Urban Habitat (CTBUH).
Author Contributions
As the primary author, Peng Du initiated the study, performed the majority of the analysis, and
wrote the main body of this paper. Antony Wood supervised the study and provided advice on the
research scope and methodology. Brent Stephens contributed in editing and structuring the paper,
advising on data analysis, and proofreading the manuscript. Xiaoyu Song contributed to the literature
review and the initial process of data collection and analysis.
Conflicts of Interest
The authors declare no conflict of interest.
References
1. Gomez-Ibanez, D.J.; Boarnet, M.G.; Brake, D.R. Driving and the Built Environment: The Effects
of Compact Development on Motorized Travel, Energy Use, and CO2 Emissions; Oak Ridge
National Laboratory: Oak Ridge, TN, USA, 2009.
2. University of Illinois at Chicago. Metropolitan Decentralization in Chicago; University of Illinois at
Chicago: Chicago, IL, USA, 2001.
3. Giuliano, G.; Agarwal, A.; Redfearn, C. Metropolitan Spatial Trends in Employment and Housing
Literature Review; University of Southern California: Los Angeles, CA, USA, 2008.
4. Newman, P.W.G.; Kenworthy, J.R. Gasoline consumption and cities. J. Am. Plann. Assoc. 1989,
55, 24–37.
5. Ewing, R.; Rong, F. The impact of urban form on U.S. residential energy use. Hous. Policy
Debate 2008, 19, 1–30.
6. Nichols, B.G.; Kockelman, K. Urban Form and Life-Cycle Energy Consumption: Case Studies at
the City Scale. In Proceedings of Transportation Research Board 94th Annual Meeting,
Washington, DC, USA, 11–15 January 2015.
7. Norman, J.; MacLean, H.L.; Kennedy, C.A. Comparing high and low residential density:
Life-cycle analysis of energy use and greenhouse gas emissions. J. Urban Plan. Dev. 2006, 132, 10–21.
8. Cole, R.J. Energy and greenhouse gas emissions associated with the construction of alternative
structural systems. Build. Environ. 1998, 34, 335–348.
9. Keoleian, G.A.; Blanchard, S.; Reppe, P. Life-cycle energy, costs, and strategies for improving a
single-family house. J. Ind. Ecol. 2000, 4, 135–156.
10. Ochoa, L.; Hendrickson, C.; Matthews, H.S. Economic input-output life-cycle assessment of U.S.
residential buildings. J. Infrastruct. Syst. 2002, 8, 132–138.
11. Ramesh, T.; Prakash, R.; Shukla, K.K. Life cycle energy analysis of buildings: An overview.
Energy Build. 2010, 42, 1592–1600.
Buildings 2015, 5 1022
12. Optis, M.; Wild, P. Inadequate documentation in published life cycle energy reports on buildings.
Int. J. Life Cycle Assess. 2010, 15, 644–651.
13. Lang, R. Residential Density and Energy Conservation; York University: Toronto, Canada, 1986.
14. Heinonen, J.; Junnila, S. A carbon consumption comparison of rural and urban lifestyles.
Sustainability 2011, 3, 1234–1249.
15. Heinonen, J.; Junnila, S. Implications of urban structure on carbon consumption in metropolitan
areas. Environ. Res. Lett. 2011, 6, doi:10.1088/1748-9326/6/1/014018.
16. Heinonen, J.; Kyrö, R.; Junnila, S. Dense downtown living more carbon intense due to higher
consumption: A case study of Helsinki. Environ. Res. Lett. 2011, 6, doi:10.1088/1748-9326/6/3/034034.
17. Wilson, J.; Spinney, J.; Millward, H.; Scott, D.; Hayden, A.; Tyedmers, P. Blame the exurbs, not
the suburbs: Exploring the distribution of greenhouse gas emissions within a city region. Energy
Policy 2013, 62, 1329–1335.
18. Community Data Snapshots. Available online: http://www.cmap.illinois.gov/data/metropulse/
community-snapshots (accessed on 10 August 2015).
19. Median and Average Square Feet of Floor Area in New Single-Family Houses Completed by
Location. Available online: https://www.census.gov/construction/chars/pdf/medavgsqft.pdf (accessed
on 10 August 2015).
20. Median and Average Square Feet of Floor Area in Units in New Multifamily Buildings
Completed. Available online: http://www.census.gov/const/C25Ann/mfu_medavgsqft.pdf (accessed
on 10 August 2015).
21. American National Standards Institute. Environmental Management—Life Cycle Assessment—
Principles and Framework; ANSI/ISO 14040; American National Standards Institute:
Washington, DC, USA, 1997.
22. Baird, G.; Aun, C.S. Energy Cost of Houses and Light Construction Buildings; New Zealand
Energy Research and Development Committee: Auckland, New Zealand, 1983.
23. Transportation Life-Cycle-Assessment. Available online: http://www.transportationlca.org/index.php
(accessed on 23 June 2015).
24. Building Energy Codes Program: Residential Prototype Building Models. Available online:
https://www.energycodes.gov/development/residential/iecc_models (accessed on 5 July 2015).
25. 90.1 Prototype Building Models High-Rise Apartment. Available online: https://www.energycodes.gov/
901-prototype-building-models-high-rise-apartment (accessed on 5 July 2015).
26. Characteristics of New Housing. Available online: https://www.census.gov/construction/chars/
completed.html (accessed on 23 June 2015).
27. Building Performance Database. Available online: https://bpd.lbl.gov/ (accessed on 3 July2015).
28. Bullard, C.W.; Penner, P.S.; Pilati, D.A. Net energy analysis: Handbook for combining process
and input-output analysis. Resour. Energy 1978, 1, 267–313.
29. Graham, J.; Owen, T.C.; Fay, R. Environmental assessment of rammed earth construction systems.
Struct. Surv. 2001, 19, 99–106.
30. Treloar, G.J.; Love, P.E.D.; Holt, G.D. Using national input/output data for embodied energy
analysis of individual residential buildings. Constr. Manag. Econ. 2001, 19, 49–61.
Buildings 2015, 5 1023
31. Crawford, R. An As-Occupied Life Cycle Energy Assessment of a Residential Building.
In Proceedings of 46th Annual Conference of the Architectural Science Association, Gold Coast,
Australia, 14–16 November 2012.
32. Myer, F.; Fuller, R.; Crawford, R.H. The Potential to Reduce the Embodied Energy in
Construction through the Use of Renewable Materials. In Proceedings of 46th Annual Conference
of the Architectural Science Association, Gold Coast, Australia, 14–16 November 2012.
33. Adalberth, K. Energy use during the life cycle of single-unit dwellings: Examples. Build. Environ.
1997, 32, 321–329.
34. Gustavsson, L.; Joelsson, A. Life cycle primary energy analysis of residential buildings. Energy
Build. 2010, 42, 210–220.
35. Frijia, S. Energy Use and Greenhouse Gas Emissions in Residential Neighborhoods in the
Southwest: A Built Environment Life-Cycle Assessment. Master’s Thesis, Arizona State
University, Phoenix, AZ, USA, August 2011.
36. Fay, R.; Treloar, G.; Iyer-Raniga, U. Life-cycle energy analysis of buildings: A case study. Build.
Res. Inf. 2000, 28, 31–41.
37. Monahan, J.; Powell, J.C. An embodied carbon and energy analysis of modern methods of
construction in housing: A case study using a lifecycle assessment framework. Energy Build. 2011,
43, 179–188.
38. Thormark, C. A low energy building in a life cycle—Its embodied energy, energy need for
operation and recycling potential. Build. Environ. 2002, 37, 429–435.
39. Pullen, S.F. Energy used in the construction and operation of houses. Archit. Sci. Rev. 2000, 43,
87–94.
40. Analysis of the Life Cycle Impacts and Potential for Avoided Impacts Associated with Single-Family
Homes. Available online: http://www.epa.gov/wastes/conserve/imr/cdm/pdfs/sfhomes.pdf
(accessed on 10 August 2015).
41. Oldfield, P. Embodied Carbon and High-Rise. In Proceedings of CTBUH 9th World Congress,
Shanghai, China, 19–21 September 2012.
42. CTBUH Height Criteria. Available online: http://www.ctbuh.org/HighRiseInfo/TallestDatabase/
Criteria/tabid/446/language/en-GB/Default.aspx (accessed on 10 August 2015).
43. Simmonds, P. ASHRAE Design Guide for Tall, Supertall, and Megatall Building Systems; American
Society of Heating, Refrigerating, and Air-Conditioning Engineers: Atlanta, GA, USA, 2015.
44. High-Rise Building Fires. Available online: http://www.nfpa.org/research/reports-and-statistics/
fires-by-property-type/high-rise-building-fires (accessed on 10 August 2015).
45. Treloar, G.J.; Fay, R.; Ilozor, B.; Love, P.E.D. An analysis of the embodied energy of office
buildings by height. Facilities 2001, 19, 204–214.
46. Suzuki, M.; Oka, T. Estimation of life cycle energy consumption and CO2 emission of office
buildings in Japan. Energy Build. 1998, 28, 33–41.
47. Oka, T.; Suzuki, M.; Konnya, T. The estimation of energy consumption and amount of pollutants
due to the construction of buildings. Energy Build. 1993, 19, 303–311.
48. Chang, Y.; Ries, R.J.; Lei, S. The embodied energy and emissions of a high-rise education
building: A quantification using process-based hybrid life cycle inventory model. Energy Build.
2012, 55, 790–798.
Buildings 2015, 5 1024
49. Kofoworola, O.F.; Gheewala, S.H. Life cycle energy assessment of a typical office building in
Thailand. Energy Build. 2009, 41, 1076–1083.
50. Chen, T.Y.; Burnett, J.; Chau, C.K. Analysis of embodied energy use in the residential building of
Hong Kong. Energy 2001, 26, 323–340.
51. The Chicago Metropolitan Agency for Planning. Chicago Regional Household Travel Inventory:
Mode Choice and Trip Purpose for the 2008 and 1990 Surveys; The Chicago Metropolitan
Agency for Planning: Chicago, IL, USA, 2010.
52. Du, P.; Wood, A.; Stephens, B. Life Cycle Assessment of Urban vs. Suburban Residential Mobility
in Chicago. In Proceedings of the ARCC 2015 Conference, Chicago, IL, USA, 6–9 April 2015.
53. Chester, M.V. Life-Cycle Environmental Inventory of Passenger Transportation in the United
States; University of California: Berkeley, CA, USA, 2008.
54. A Life Cycle Approach to Prioritizing Methods of Preventing Waste from the Residential
Construction Sector in the State of Oregon. Available online: http://www.deq.state.or.us/lq/pubs/
docs/sw/ResidentialBldgLCA.pdf (accessed on 10th August 2015).
55. Perkins, A.; Hamnett, S.; Pullen, S.; Zito, R.; Trebilcock, D. Transport, housing and urban form:
The life cycle energy consumption and emissions of city centre apartments compared with
suburban dwellings. Urban Policy Res. 2009, 27, 377–396.
© 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article
distributed under the terms and conditions of the Creative Commons Attribution license
(http://creativecommons.org/licenses/by/4.0/).
