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The U.S. construction industry accounts for approximately 4% of the gross domestic product. Although quantifying and analyzing the cumulative ecological resource consumption of the construction industry is of great importance, it has not been studied sufficiently. This paper aims to account for the total ecological resource consumption of the construction industry, including its supply chains. This analysis is achieved by using an ecologically based life-cycle assessment model. The impacts on the ecosystem were calculated on the basis of the economic data in terms of cumulative mass, energy, industrial exergy, and ecological exergy. U.S. construction sectors are holistically evaluated by using various sustainability metrics, such as resource intensity, efficiency ratio, and loading ratio. Total ecological exergy values were generally found to be larger for the sectors with higher economic output values. Heavy construction industry sectors, including construction and maintenance of highways, bridges, or pipelines, were generally found to use fewer renewable resources and to have higher emission intensity. DOI: 10.1061/(ASCE)CO.1943-7862.0000509. (C) 2012 American Society of Civil Engineers.
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Sustainability Assessment of U.S. Construction Sectors:
Ecosystems Perspective
Omer Tatari1and Murat Kucukvar2
Abstract: The U.S. construction industry accounts for approximately 4% of the gross domestic product. Although quantifying and analyzing
the cumulative ecological resource consumption of the construction industry is of great importance, it has not been studied sufficiently. This
paper aims to account for the total ecological resource consumption of the construction industry, including its supply chains. This analysis is
achieved by using an ecologically based life-cycle assessment model. The impacts on the ecosystem were calculated on the basis of
the economic data in terms of cumulative mass, energy, industrial exergy, and ecological exergy. U.S. construction sectors are holistically
evaluated by using various sustainability metrics, such as resource intensity, efficiency ratio, and loading ratio. Total ecological exergy values
were generally found to be larger for the sectors with higher economic output values. Heavy construction industry sectors, including
construction and maintenance of highways, bridges, or pipelines, were generally found to use fewer renewable resources and to have higher
emission intensity. DOI: 10.1061/(ASCE)CO.1943-7862.0000509.© 2012 American Society of Civil Engineers.
CE Database subject headings: Sustainable development; Environmental issues; Construction industry; System analysis; Ecosystems;
United States.
Author keywords: Sustainable development; Environmental issues; Construction industry; System analysis.
Introduction
The U.S. construction industry accounts for approximately $578
billion (4.1%) of the gross domestic product [Bureau of Economic
Analysis (BEA) 2010b]. Buildings contribute 38.9% of U.S.
total carbon dioxide emissions (EPA 2009). Buildings and infra-
structure systems account for approximately 30% of the raw
materials used annually in the United States (Committee on
Advancing the Competitiveness and Productivity of the U.S.
Construction Industry 2009). However, the environmental impacts
of such a large industry have not been studied sufficiently on an
industry-wide level (Sharrard 2007). Although there have been
numerous studies on the environmental effects of the industry,
the focus has been mostly on pollution control, whereas the reduc-
tion of resource use is new on the agenda (Bringezu 2002).
As the construction industry has been building the civil infra-
structure, many renewable and nonrenewable ecological resources
were harvested, extracted, and productively used. An excessive use
of resources is critical for the ecosystem not only because of the
depletion of resources, but because of other concerns, such as
the destruction and long-term change of natural habitats and
distortions of the potable water supply (Bringezu 2002). Little
attention has been given to the impact of the built environment
on the ecosystem, including oceans, rivers, lakes, ecosystems, raw
materials, the air, the soil, and the land [National Research Council
(NRC) 2009]. Because of all stated reasons, quantifying and
analyzing the cumulative ecological resource consumption of the
construction industry is of great importance. This analysis needs
to include the upstream flows of the industry as well, or it will
be insufficient (Bringezu 2002).
The current study aims to account for the total ecological
resource consumption of the construction industry, including its
supply chains, and uses sustainability metrics to reach to better
insights regarding the impact of the industry on the ecosystem. This
study can be regarded as a continuation of the study that was
conducted by Hendrickson and Horvath (2000). In their study,
Hendrickson and Horvath quantified several resources, including
fuel, electricity, ore, and water, by utilizing an economic input/
output life-cycle assessment model (EIO-LCA). On the other hand,
this study accounts not only for these resources, but it also includes
ecological goods and services, such as forest, land, biogeochemical
cycles, rain, and wind. This analysis is achieved by using an
ecologically based life-cycle assessment model (Eco-LCA); a
thermodynamic-based economic input/output life-cycle assessment
approach. The rest of the paper is organized as follows: First, the
method used in the paper is explained. Next, analysis results of U.S.
construction sectors are presented. Finally, discussion is presented,
the findings are summarized, and the limitations are pointed out.
Method
The Eco-LCA model is utilized to analyze U.S. construction sectors
because of its ability to quantify the ecological goods and services
described in Millenium Ecosystem Assessment framework
(Alcamo et al. 2003). The Eco-LCA environmental assessment tool
extends the system boundary to include not only the national
economy used in EIO-LCA but also ecological goods and services.
The Eco-LCA model uses the same economic input/output data as
EIO-LCA. It utilizes a thermodynamic input/output analysis
approach to account for the contribution of natural capital (Ukidwe
and Bakshi 2007). The Eco-LCA model mainly focuses on the con-
sumption of ecosystem goods and services, and it has the capability
1LEED AP, Assistant Professor, Civil Engineering Dept., Ohio Univ.,
Athens, OH 45701 (corresponding author). E-mail: tatari@ohio.edu
2Graduate Research Assistant, Civil Engineering Dept., Ohio Univ.,
Athens, OH 45701.
Note. This manuscript was submitted on September 29, 2010; approved
on November 3, 2011; published online on July 16, 2012. Discussion
period open until January 1, 2013; separate discussions must be submitted
for individual papers. This paper is part of the Journal of Construction
Engineering and Management, Vol. 138, No. 8, August 1, 2012. ©ASCE,
ISSN 0733-9364/2012/8-918922/$25.00.
918 / JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT © ASCE / AUGUST 2012
J. Constr. Eng. Manage. 2012.138:918-922.
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to aggregate the results on the basis of various levels such as mass,
energy, industrial exergy, and ecological exergy. These aggregation
levels provide further insight regarding the material and energy
intensity of the products being analyzed. It also provides the ability
to reach at different metrics that could be used for holistic assess-
ments. These aggregation metrics are as follows:
Cumulative mass consumption (mass) signifies the total materi-
al consumption of a product, a metrics that has been utilized in
material flow analysis (Brunner and Rechberger 2004;Low
2005). In this method, only mass is taken into account.
Cumulative energy consumption (energy) captures the total
energy consumed in the entire life cycle, a metric that has been
utilized in the net energy analysis (Bullard Peter and Clark
1978). Energy cannot account for materials and is calculated
in terms of J.
Industrial cumulative exergy consumption (ICEC) expands the
system boundary by considering all industrial processes utilized
to convert natural resources into the desired product (Hau and
Bakshi 2004a). ICEC represents the exergy consumption within
the industrial and economic system only. ICEC is calculated in
terms of J.
Ecological cumulative exergy consumption (ECEC) includes
the exergy consumed by ecological processes for raw material
production, emissions dissipation, and the functioning of indus-
trial processes (Hau and Bakshi 2004a). ECEC represents
exergy used in ecological services to support the industrial ac-
tivities. ECEC is calculated in terms of solar equivalent joules
(SEJ). ECEC considers the amount of exergy required by eco-
logical systems to make goods and services utilized by the
industrial system. To make this possible, the cumulative exergy
consumption of direct ecological inputs are calculated using
transformity values that were introduced by Odum for emergy
analysis (Hau and Bakshi 2004b;Odum 1996). In this case,
transformity refers to the available solar energy required to
make 1 J of a good or service and is measured in solar equivalent
joules per 1 J (SEJJ). Values for major ecological resources are
quantified by Odum (1996) and utilized by Hau and Bakshi
(2004a) in the Eco-LCA model by means of a systematic algo-
rithm utilizing network algebra.
Several sustainability metrics are utilized to gain more insights.
The ECEC/ICEC ratio, which is also known as the efficiency ratio,
reveals the magnitude of ecological links that are ignored by the
ICEC analysis. In addition, the loading ratio, defined as the ratio
of cumulative consumption of nonrenewable resources to those
from renewable resources, indicates the relative dependence of a
product on nonrenewable resources (Ukidwe and Bakshi 2007).
These ratios are important indicators in understanding the degree
of dependence on renewable and nonrenewable resources for each
pavement design.
Analysis of U.S. Construction Sectors
The economic output values of each U.S. construction sector were
obtained from the U.S. Department of Commerce input/output
table (BEA 2010a). Table 1lists 13 construction sectors along with
their North American Industry Classification System (NAICS)
codes and their 1997 economic outputs. The Eco-LCA online
model was used to identify the cumulative resource consumption
of U.S. construction sectors utilizing mass, energy, ICEC, and
ECEC. In this section, the analysis results are presented.
Cumulative Resource Consumption
According to the results of the study, RES1 was found to have high-
est resource consumption in terms of all units (see Table 2). Sectors
such as COMM and HWYT showed high resource utilization in
comparison with other construction sectors. Sectors with the lowest
Table 1. U.S. Construction Sectors and Their Total Industry Output
NAICS code Sector acronym Description
Total industry output
($ millions)
230110 RES1 New residential 1-unit structures, nonfarm 172,439
230120 MULT New multifamily housing structures, nonfarm 26,234
230130 RADD New residential additions and alterations, nonfarm 57,679
230140 FRMH New farm housing units and additions and alterations 5,429
230210 MANF Manufacturing and industrial buildings 27,487
230220 COMM Commercial and institutional buildings 190,818
230230 HWYT Highway, street, bridge, and tunnel construction 43,401
230240 WATP Water, sewer, and pipeline construction 17,207
230250 OTHR Other new construction 90,757
230310 MFRM Maintenance and repair of farm and nonfarm residential structures 36,384
230320 MNON Maintenance and repair of nonresidential buildings 56,012
230330 MHWY Maintenance and repair of highways, streets, bridges, and tunnels 12,411
230340 MOTR Other maintenance and repair construction 17,833
Table 2. Total Resource Consumption by Mass, Energy, Industrial Exergy,
and Ecological Exergy
Sector
acronym Mass (k) Energy (J) ICEC (J) ECEC (SEJ)
RES1 6:81E þ12 1:79E þ21 1:79E þ21 1:02E þ24
MULT 8:45E þ11 2:05E þ20 2:05E þ20 1:23E þ23
RADD 2:58E þ12 6:22E þ20 6:22E þ20 4:57E þ23
FRMH 2:12E þ11 5:87E þ19 5:87E þ19 4:21E þ22
MANF 7:33E þ11 6:96E þ19 6:96E þ19 9:95E þ22
COMM 5:35E þ12 9:99E þ20 9:99E þ20 4:76E þ23
HWYT 1:51E þ12 4:94E þ19 4:95E þ19 6:14E þ23
WATP 4:82E þ11 2:30E þ19 2:30E þ19 6:44E þ22
OTHR 2:27E þ12 2:00E þ20 2:00E þ20 2:22E þ23
MFRM 1:93E þ12 6:66E þ20 6:66E þ20 3:03E þ23
MNON 1:43E þ12 5:05E þ20 5:05E þ20 1:24E þ23
MHWY 4:98E þ11 3:01E þ19 3:01E þ19 2:35E þ23
MOTR 4:56E þ11 5:27E þ19 5:27E þ19 8:61E þ22
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ecological resource consumption were found to be FRMH and
WATP. Although the sector of COMM has the highest economic
output, sectors with lower economic output (RES1 and HWYT)
had higher ECEC values. This was the result of the fact that even
though some industrial sectors show high economic output, the
dominance of high-quality goods and services with lower trans-
formity values results in less ECEC. Also, the relative contributions
of the major ecological goods and services for construction sectors
were quantified (see Fig. 1).
Resource Intensity
HWYT and MHWY were found to have the highest amounts of
resource intensity, whereas COMM and MANF were found to have
the lowest amounts (see Table 3). The differences in resource
intensity could be attributed to the ecological resource intensity
difference of used resources such as iron, apatite, crushed stone,
and sand. Thus, even though the economic output of a sector
may not be the highest (such as MHWY), the high relative contri-
bution of resources that require substantial amounts of exergy
might make it the most resource intensive sector.
Sustainability Metrics
HWYT and MHWY were found to have the highest ECEC/ICEC
ratio. This result is because of the fact that these sectors a show
relatively higher dependency on nonrenewable resources, such
as crushed stone and sand, both of which require substantial exergy
to make them available in the ecological system. Sectors such as
MNON and COMM were found to have the lowest ECEC/ICEC
ratio because the relative contribution of high-transformity nonre-
newable resources was relatively lower. RES1 and COMM had
Fig. 1. Relative contribution of major ecological goods and services
Table 3. Resource Intensity by Mass, Energy, Industrial Exergy, and Ecological Exergy
Sector
acronym Mass (kg$) Energy (J$) ICEC (J$)
ECEC
(SEJ$)
ECEC/ICEC
ratio
Loading
ratio
RES1 3:95E þ01 1:04E þ10 1:04E þ10 5:92E þ12 5:69E þ02 18.15
MULT 3:22E þ01 7:80E þ09 7:80E þ09 4:69E þ12 6:02E þ02 16.94
RADD 4:47E þ01 1:08E þ10 1:08E þ10 7:92E þ12 7:35E þ02 23.93
FRMH 3:91E þ01 1:08E þ10 1:08E þ10 7:75E þ12 7:17E þ02 23.84
MANF 2:67E þ01 2:53E þ09 2:53E þ09 3:62E þ12 1:43E þ03 18.66
COMM 2:81E þ01 5:24E þ09 5:24E þ09 2:49E þ12 4:76E þ02 10.10
HWYT 3:48E þ01 1:14E þ09 1:14E þ09 1:42E þ13 1:24E þ04 84.89
WATP 2:80E þ01 1:34E þ09 1:34E þ09 3:74E þ12 2:79E þ03 21.34
OTHR 2:51E þ01 2:21E þ09 2:21E þ09 2:45E þ12 1:11E þ03 12.80
MFRM 5:31E þ01 1:83E þ10 1:83E þ10 8:32E þ12 4:54E þ02 18.17
MNON 2:56E þ01 9:02E þ09 9:02E þ09 2:21E þ12 2:45E þ02 13.42
MHWY 4:01E þ01 2:42E þ09 2:43E þ09 1:90E þ13 7:82E þ03 304.07
MOTR 2:56E þ01 2:95E þ09 2:96E þ09 4:83E þ12 1:63E þ03 76.81
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moderate ECEC/ICEC ratios, even though they had the highest
economic output. Thus, the degree of nonrenewable resource con-
sumption was independent of the total economic transaction.
HWYT, MHWY, and WATP had the highest values of loading
ratios because nonrenewable resources such as nonmetallic miner-
als and fossil fuels were contributing highly to the resource con-
sumption of these sectors. Utilizing high-transformity resources
led to a lower renewability ratio for those construction sectors.
Emissions
Emission intensity, defined as the total emissions to money ratio,
measures the total emissions generated for $1 of economic output.
Fig. 2shows that emission intensity was not highest for the con-
struction sectors with the highest economic activity. For example,
the total CO2emissions for $1 economic output are highest for
HWYT, which is not a sector with the highest economic output.
Results of emission intensities showed clearly that heavy construc-
tion sectors HWYT and MHWY emitted more emissions per $1
economic activity.
Discussion and Conclusion
The paper presented important findings regarding the total resource
consumption and emissions of 13 U.S. construction sectors. Total
ECEC consumption values were generally found to be larger for the
sectors with higher economic output values. Because the type of
materials and energy resources are more or less the similar for many
construction sectors, industries with a high reliance on nonrenew-
able natural capital consumed higher ecological exergy for their
industrial activities. These construction sectors, presented higher
ECEC/ICEC and loading ratios.
Heavy construction industry sectors, including construction and
maintenance of highways, bridges, or pipelines, were generally
found to use fwer renewable resources. Even though the residential
sector is the most intensive sector in terms of the total industrial and
ecological resource consumption, it demonstrated a lower loading
ratio. This result might be related to the higher use of renewable
resources such as wood in building construction as opposed to
heavy construction. However, the emission intensity shows clearly
that heavy construction sectors emitted more emissions per $1 of
economic activity.
It should be noted that the ecological impacts associated with
each construction sector is not limited to the study findings.
Ecological impacts related to many activities, including road con-
struction and maintenance activities, the use phase of major infra-
structures and residential buildings, and the dispersed ecological
effects of air pollution emissios, should be considered, as well.
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Greening construction processes using an input-output-based hybrid life cycle assessment model Industrial and ecological cumulative exergy consumption of the United States via the 1997 input-output benchmark model
  • A N Sharrard
  • B Bakshi
Sharrard, A. (2007). " Greening construction processes using an input-output-based hybrid life cycle assessment model. " Ph.D. thesis, Carnegie Mellon Univ., Pittsburgh. Ukidwe, N., and Bakshi, B. (2007). " Industrial and ecological cumulative exergy consumption of the United States via the 1997 input-output benchmark model. " Energy, 32(9), 1560–1592.