Balance between energy conservation and environmental impact: Life-cycle energy analysis and life-cycle environmental impact analysis

Balance between energy conservation and environmental impact: Life-cycle energy analysis and life-cycle environmental impact analysis

Energy and Buildings 140 (2017) 131–139 Contents lists available at ScienceDirect Energy and Buildings journal homepage:

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Energy and Buildings 140 (2017) 131–139

Contents lists available at ScienceDirect

Energy and Buildings journal homepage:

Balance between energy conservation and environmental impact: Life-cycle energy analysis and life-cycle environmental impact analysis Ming Hu ∗ School of Architecture, Planning and Preservation, University of Maryland, ARC 12-7, 3835 Campus Drive, College Park, MD 20742, USA

a r t i c l e

i n f o

Article history: Received 28 August 2016 Received in revised form 21 January 2017 Accepted 24 January 2017 Available online 4 February 2017 Keywords: Embodied energy Operational energy Adaptive reuse Environmental impact

a b s t r a c t A comprehensive case study life-cycle analysis(LCA) was conducted on a four-story National Register historic building with a projected 75-year life span located in Medina, New York. Three adaptive reuse options were compared: historic preservation, renovation, and new construction; six different energy performance targets were constructed and compared as well. The study comprises two parts: a life-cycle energy analysis and a life-cycle environmental impact analysis. In this life-cycle analysis, the building assembly group that consumes the most embodied energy was identified, related suitable renovation options were analyzed, and conclusions were drawn based on the results. The aim of the research was to address the balance between energy and environmental benefits and drawbacks for different adaptive reuse options. Four impact categories (global warming potential, ozone depletion potential, human health particulate potential, and smog potential) were measured and their correlation with primary energy demand was analyzed. © 2017 Elsevier B.V. All rights reserved.

1. Background Every year, buildings in the United States totaling approximately 1 billion square feet [1] are demolished and replaced with new construction. The Brookings Institution projects that some 82 billion square feet of existing space will be demolished and replaced between 2005 and 2030—roughly one-quarter of today’s existing building stock [1]. However, few studies to date have sought to examine the balance between the environmental impacts of razing old buildings and erecting new structures in their place, and the energy saved by building new buildings with advanced materials and efficient building systems. Globally, a number of studies have examined the relationship between the embodied energy (i.e., the energy utilized for the creation of the building [8]) and the operating energy of buildings within the buildings’ entire life cycle. Buildings consume energy directly or indirectly in all phases of their life cycle, from the cradle to the grave so to speak, and there is interplay between phases of energy use (both embodied and operating energy). Embodied energy is the total energy required for the extraction, processing, manufacture, and delivery of building materials to the building site. Hence, all of these components need

∗ Corresponding author. E-mail address: [email protected] 0378-7788/© 2017 Elsevier B.V. All rights reserved.

to be analyzed from a life-cycle perspective. Bekker [2] highlighted that in the building sector, a life-cycle approach is an appropriate method for analyzing the use of energy and other natural resources as well as the impact on the environment. Subsequently, Adalberth [3] presented a method for describing the calculation of energy use during the life cycle of a building. In a companion paper [4], he applied the method to gain insight into the total energy use of dwellings during their life cycle. In particular, that paper presented case studies of the total energy use of three single-unit dwellings built in Sweden. Adalberth found that 85% of the total energy usage occurred during the operation phase, while the energy used in manufacturing all the construction materials employed in construction, along with the construction itself and renovation, amounted to approximately 15% of the total energy use. The transportation and process energy used during construction and demolition of the dwellings comprised approximately 1% of the total energy requirement. Several other similar studies of residential buildings [5–8] and office buildings [9–11] are reported in the literature. Table 1 ). shows the range of life-cycle energy analysis (LCEA) and life-cycle environmental impact analysis (LCEIA) research conducted in the past 20 years globally. Various researchers (e.g., [12–17]) have studied final energy use in the entire life cycle of buildings and have shown that the operation phase contributes significantly to the life-cycle final energy use of buildings. Ramesh et al. [8] conducted a literature review study of


Table 1 Literature Review Summary. Case Study no.



Adlberth Keoleian et al. [12] Treloar et al. [13]

1–13 1 4

1997 2001 2001

Sweden USA Australia

2001 2001

Sweden France

2001 2001 2002 2002 2003 2006 2006 2007 2008 2008 2009 2009 2009 2010 2008

Johansson and Öberg [14] Peuportier [15] Adlberth et al .[16] Morrissey and Home [17] Marceau and Gajda [18] Thomark [19] Zacharia [20] Norman et al. [21] Sartori [22] Citherlet and Defaux [23] Xing et al. [24] Huberman and Pear [25] Utama and Gheewala [26] Shukla et al. [27] Blengini[28] Belusko and O’Leary[29] Ortiz-Rodrigue. Et al. [30]


Gustavsson and Joelsson [31]


Sweden Australia USA Sweden Canada Canada 9 Countries Switzerland China Israel Israel India Italy Australia Colombia and Spain Sweden

Carre Leckner and Zmerureanu [32] Lyer and Wong Aye et al. [33] Gong et al. [34] Monteiro and Feire [35] Säynäjoki et al. [36] Stephan et al. [37] Stephan et al. [38] Ji et al. [39] Islam et al. [40]

2011 2011 2012 2012 2012 2012 2012 2013 2014 2014 2015

Australia Canada Australia Australia China Portugal Finland Belgium Lebanon Korea –


60 3

8 1

Life-cycle energy (LCE)

Life-cycle Impact Assessment (LCIA)

Type of building

Building size

Life span

7600–8800 kWh/m2 Y Y

Y Y –

Res Res Res

– 2450 sq ft

50 50 40


Y –

Res Res

60 80

6100–9100 kWh/m2 Y Y 14,913 GJ – 92–109 MJ/m2 /year Y 40–580 MJ/m2 /year – Y – – 999 MJ/m2 /year – –

Y Y Y – – – Y – – – – – – – –

– – – – – Res Res Res Res – Res Res Res Res Res

50 30–75 100 50 35 50 – – 50 50 40 40 40 – 50



– – – –

7500–11500 KWh/m2 /year – – – –

23% of LCE 18% of LCE – –

800–1600 GJ/m2 /year 800–1600 GJ/m2 /year 800–1600 GJ/m2 /year 800–1600 GJ/m2 /year – –

Y – – – – – Y – – Y –

– Res (NZEH) Res Res Res Res Res Res Res Res –

– – 50–100 50 50 50 50 100 50 50 –

Embodied energy only (EE)

Y 10.7 GJ/m2 for 3-stories Account for 10–15% 10–30% of LCE Y Y 9.7% of LCE – Y

60% of LCE – – 7% of LCE –

45–60% of LCE

M. Hu / Energy and Buildings 140 (2017) 131–139


M. Hu / Energy and Buildings 140 (2017) 131–139

life-cycle final energy analyses of 73 residential and office buildings in northern and central Europe, Canada, tropical regions of Asia, and Australia. Their results suggested that final operation energy use contributes to about 80–90% of life-cycle energy use in residential buildings. Space heating of buildings, for example, is a substantial part of total operation energy. However, LCEA in the historic preservation context is very limited, with most studies focusing on new construction and some investigating extreme energy-efficient building, such as passive houses [52]. Only a few studies have identified which building assemblies group has the greatest environmental impact and contributes to the majority of life-cycle energy consumption. In the United States, there has been little research examining the balance between energy and environmental benefits and the drawbacks of different adaptive reuse options compared to other countries (see Table 1). Lack of transparent data and a clear mandate for the design/building and construction industry seem to be the biggest barriers to design teams wishing to evaluate adaptive reuse options and present quantifiable results to clients and the public in real practice (Figs. 1–3 On the other hand, the U.S. government has a clear set of policies for increasing energy efficiency and reducing greenhouse gas (GHG) emissions. The policies are expressed in the National Action


Plan for Energy Efficiency (NAPEE) [41]. In addition, in 2009, President Barack Obama announced new carbon emissions goals, to reduce emissions by 17% of the 2005 levels by 2020 [42]. Moreover, it is anticipated that these emissions goals may be accelerated as a result of the United Nations Summit on Climate Change (COP21), which took place in Paris in November 2015. Given that the building industry contributes around 39% of the GHG emissions [53] to the U.S. carbon signature, it must play a central role in reaching these targets through ever-greater energy efficiency and GHG emissions reductions (EPA 2012). The gap between the (clear) carbon emissions reduction goal and the (unclear) process and solution for the existing building stock could undermine these good intentions and make it even more difficult to reduce GHG from the building industry.

2. Research motivation 2.1. The need for adaptive reuse Sara Wilkinson points out that, over time, the usefulness of any building for its original function diminishes: “Four types of obsolescence take form: physical obsolescence, functional obsolescence,

Fig. 1. Total Embodied Primary Energy Summary Measure Chart by Assembly Group.


Embodied Primary Energy Consumption Comparison (MJ)

5000000 4000000 3000000 2000000 1000000 0 Existing Assembly Group Extra Basic Materials Foundation Walls


New Construction

Beams And Columns Floors Roofs

Fig. 2. Total Embodied Primary Energy Summary Measure Chart by Assembly Group.


M. Hu / Energy and Buildings 140 (2017) 131–139

Fig. 3. Comparison of Global Warming Potential by Life Cycle Stage (Embodied Effects).

economic obsolescence, and locational obsolescence. . ..” [43]. In fact, obsolescence affects a building at any location and at any time during its life cycle, and building users have to adapt the building to every changing condition beginning on the first day after the building’s completion. Ultimately, as Wilkinson says, all buildings will become obsolete at some stage and will need to be modified to adapt to changes in environmental, functional, locational, and economic conditions. On the other hand, historic buildings not only have cultural and historical significance, but preservationists also believe that such buildings carry environmental impact reduction benefits. For instance, a report published by Preservation Green Lab of the National Trust for Historic Preservation (“The Greenest Building: Quantifying the Environmental Value of Building Reuse”) included several relevant findings. In particular, the authors concluded as follows: “Significantly, even if it is assumed that a new building will operate at 30% greater efficiency than an existing building, it can take between 10 and 80 years for a new, energy-efficient building to overcome the climate change impacts that were created during construction” [44]. 2.2. The lack of quantitative research The most agreed-upon benefit of preserving existing and historic buildings is their cultural and social value. Among 45 documents related to historical preservation that were published by the Advisory Council on Historic Preservation between 1979 and 2016, only one, published in 1979, addresses the energy savings and environmental protection benefit and also uses a quantitative approach [45]. The underlying research upon which that report, and most embodied energy applications since 1976 to the present day, have been based is a 1976 report entitled “Energy Use for Building Construction” [46]. The research project was a collaboration between the University of Illinois at Urbana-Champaign and Richard Stein Associates, Architects, of New York City. The resulting report is the most thorough evaluation of the embodied energy of building materials and building types that has been produced in the United States to date. The material in the report was developed for new buildings and was based on construction industry data from 1967. This pioneering effort is still the most thorough evaluation of the embodied energy of building materials to have ever been produced

in the United States. Obviously, since 1967, there have been changes in the technologies that make the important components of buildings. Steel, concrete, glass, and so on and the total energy costs of building materials have changed dramatically. Steel beams, for example, are now made with continuous casting, avoiding the billet reheating of earlier times. Thus, the base number for embodied energy from the 1976 report is likely to be outdated and is derived from 50-year-old data. Currently, most LCAs in the building industry focus on building materials and depend on the accuracy of the LCI (life-cycle inventory). Current LCIs either come with computational analysis software (digital LCIs) or other inventory data that can be manually input into the calculation format. Currently, the most comprehensive U.S. LCI data is created and managed by the National Renewable Energy Laboratory (NREL), but that database does not have data on building materials and the construction industry that are comparable to the database used in the 1976 report. The lack of an updated database that is specific to the United States creates a substantial gap and constitutes a research urgency. For this reason, the author chose to use the database that comes with the Athena software, which includes a more comprehensive database for the building and construction industry and is North American–based (see Section 3.2 for more details). To the author’s knowledge, there is no comprehensive published embodied energy data by building type that is comparable to the data set provided in the 1976 report. In fact, the results of the current study, which uses a digital LCI and tools, illustrate a significant discrepancy between current embodied energy data for commercial buildings and the 1976 report data (see Section 4). The data produced in 1976 are, of course, not up-to-date. Since then, the technology for producing building materials and assemblies has undergone tremendous development; therefore, any life-cycle energy consumption and life-cycle environmental impact analysis based on that 50-year-old data set needs be examined again to provide a reliable baseline or benchmark. 2.3. Global trends Other developed countries have directed substantial expenditures to building adaption. For example, in the United Kingdom, more work is undertaken on adaption than on new building [49,50]: half of the total expenditures on construction were devoted

M. Hu / Energy and Buildings 140 (2017) 131–139

to existing buildings [51]. The high proportion and amount of annual expenditure on building adaption in European and national economies of other developed countries demonstrates the importance of adaption to business and commerce. However, in the United States, adaptive reuses still face myriad obstacles. 3. Case study: life-cycle analysis of Bent’s opera house 3.1. Study object Located in the heart of Medina, New York, Bent’s Opera House stands prominently at the corner of Main Street and Center Street. Completed in 1865, the Opera House was built from the nowfamous Medina sandstone, which can also be found in places such as Havana, Cuba, and was used for London’s Buckingham Palace [47]. The building has a total of four floors and comprises around 23,000 square feet. Named after the property’s original owner, Don Carlos Bent, the Opera House has a rich and varied history. Given the building’s name, it follows that its main feature historically was its performance space, which is located on the third floor. This space was home to a variety of uses, including plays, shows, commencements, elections, and other public functions. The building has also served as a gathering space for a local men’s fraternal order as well as a Bank of America branch. Over time, the building fell into disuse, but it is still considered a significant architectural landmark in Medina. In 1995, it was included in the National Register of Historic Places as a part of Medina’s Main Street historic district.


minum, fuels and fuel conversion, iron and steel, logistics, organic and inorganic chemicals, painting of automotive parts, Portland cement, and plastics and resins. Of those data sets, 207 are applicable to the building and construction industry [55]. So far, this is the largest database of building materials and components that is used for the United States in particular. The problem, however, is that the 207 data sets are far from comprehensive and do not cover the majority of building materials, assemblies, and technologies currently available on the market. For this reason, the author decided to use the LCI in the Athena IE4B software. Athena reports footprint data for the following environmental impact measures, consistent with the latest U.S. EPA TRACI methodology: global warming potential, acidification potential, human health respiratory effects potential, ozone depletion potential, smog potential, and eutrophication potential. The IE4B software is designed to aid the building community to make more environmentally conscious material and design choices. The tool achieves this by applying a set of algorithms to the extracted building material data in order to generate a bill of materials (BoM). This BoM then utilizes the Athena Life Cycle Inventory (LCI) database, version 5.0.0125, to generate a cradle-to-grave LCI profile for the building. In the current study, the IE4B model included resource extraction, manufacturing, on-site construction, occupancy/maintenance, demolition, and recycling/reuse. Using the formatted extracted material data, the IE4 B software generated a whole-building LCA model for Bent’s Opera House. Six models were generated based on material data and geometrical information from the same Revit model, and benchmarking energy efficiencies from the EPA’s Energy Star program [57] (see Table 1). These models were as follows:

3.2. Tools and data Two main software tools were utilized to complete this life-cycle analysis (LCA) study of building embodied energy: the Autodesk Revit model to extract the material data and the Athena Sustainable Materials Institute’s Impact (IE4B) to calculate embodied energy and operating energy consumption. As the quality of an LCA study is directly related to the quality of input LCI data, the database selection is based on three main criteria: (1) local data—for a study of North American buildings, the data set needs to be North American–based; (2) the dataset numbers need to be broad enough; and (3) the ease and flexibility allow users to create their own building assemblies using different materials. The IE4 B software was the only available application capable of meeting the requirements of this study. With respect to the building operational energy data, one database was used to benchmark the operational energy consumption: a database produced and managed by the Department of Energy that contains 2012 commercial building energy consumption (CBES) data [56]. North American governments began developing LCI data in the 1990s. Environment Canada funded three LCA data projects: the first, in 1991, was an investigation of building materials [54]. In the mid-1990s, the Canadian “Athena Project” made these data available as spreadsheets, and in 2002, the data were converted into what is now called the Athena Impact Estimator for Buildings (IE4B). This tool is widely used in LCAs for buildings in North America. In the United States, currently the most significant Department of Energy (DOE) involvement in LCA is the NREL’s hosting of the U.S. LCI database. The DOE and more recently the U.S. Department of Agriculture (USDA) have led data development. At the DOE, the LCAD database was first conceived in 1993 and became a part of the Pacific Northwest National Laboratory/Battele LifeCycle Advantage software suite in 1997; however, this software is no longer supported or available [54]. In 2003, the NREL created the U.S. Life Cycle Inventory Database, and today the database includes 1115 U.S. data sets [55] in a variety of software-compatible formats representing some agricultural and wood products, alu-

1) The historic building with current energy efficiency (very poor performance): 150 kBtu/sq ft/year 2) The historic building with a highly efficient mechanical system (standard performance, meeting current code): 78 kBtu/sq ft/year 3) The renovated building with renovated building envelope and standard energy-efficient HVAC, meeting building code: 78 kBtu/sq ft/year 4) The renovated building with renovated building envelope and highly energy-efficient HVAC to meet Energy Star standards: 39 kBtu/sq ft/year 5) The newly constructed building with renovated building envelope, contemporary building materials, and energy-efficient HVAC: 39 kBtu/sq ft/year 6) The newly constructed building with renovated building envelope, contemporary building materials, and highly energyefficient HVAC to be able to achieve site net zero: 18 kBtu/sq ft/year The IE4B software is designed to aid the building community in making more environmentally conscious material and design choices. The tool achieves this by applying a set of algorithms to the extracted building material data in order to generate a bill of materials (BoM). This BoM then utilizes the Athena Life Cycle Inventory (LCI) Database, version 5.0.0125, to generate a cradleto-grave LCI profile for the building. In this study, the IE4B model included resource extraction, manufacturing, on-site construction, occupancy/maintenance, demolition, and recycling/reuse. 3.3. System definition, boundaries, and building models Only the building itself (structure, envelope, interior, and backfill) is included in this analysis. The building life span used for this analysis is 75 years. It is assumed that the energy mix for heating, cooling and air conditioning, and electrical services, as well as the


M. Hu / Energy and Buildings 140 (2017) 131–139

content of material replacements through renovations, will be the same over the entire life span of the building. The Revit model was constructed based on survey drawings provided by a local architecture firm that has been working on the renovation of this historic building; the research team also conducted field measurements to verify the critical dimensions and some unidentified areas that were not indicated in the architectural drawings, such as additional storage rooms on the first floor. The research team first constructed the three-dimensional virtual model in Autodesk Revit and manually input all related materials properties that are not part of the default Revit template. Next, a material schedule was created within the Revit model, transferring three-dimensional data of materials into two-dimension quantitative numbers, including volume, weight, dimensions, layers, and assemblies. This material schedule was used as the baseline dataset. Then the material schedule was exported into an Excel-format file. The research team simplified the schedule to edit out the nonessential information and make a clear spreadsheet. The useful data included external walls, interior walls, columns, floors, roofs, and foundations. Finally, the data was manually input into Athena IE4 B (see Table 2). 3.3.1. Columns and beams The column and beam takeoffs were completed mainly using the Revit count condition. The floor-to-floor height and live load were taken from the Bero architect’s code analysis document. The supporting span and supported span are both 4 m (see Table 2). 3.3.2. Floors All floors within the building are wood truss with plywood panel on top. The surface area of the slab was computed using the area condition in Revit. The computed areas were then converted into rectangular slabs of equivalent surface area with spans of 4 m and 8 m, as those are close to the IE4B span limits. The length and span of the idealized rectangular slabs were then input into the IE4B. Multiple floor slabs measuring 20 m by 10 m resulted in an equivalent surface. The concrete strength and live load were taken from the code analysis document and entered into the IE4 B (see Table 2). 3.3.3. Roofs All roofs in Bent’s Opera House were assumed to be made of wood truss with plywood panel on top as well, because we could not get onto the rooftop. Decking thickness was assumed to be 15 mm with live load at 2.4 kPa. Those data were manually input into IE4B. We also assumed that the bitumen was standard modified, and the insulation was not added when the building was originally being constructed (see Table 2). 3.3.4. Foundation The concrete footing data extractions were completed mainly using area conditions in Revit. We assumed that there was only one assembly type and no rebar in the original construction. The thickness was 200 mm and flyash content was assumed to be average (see Table 2). 3.3.5. Walls The external wall types used in Bent’s Opera House were natural sandstone. The lengths of the external walls were calculated using a quantity schedule generated from the Revit model. There was no rebar in the exterior wall. Interior partition walls were excluded from the material takeoff due to the lack of historic documents on interior layout and multiple alterations over the years. The windows for all walls were modeled as being unclad wood window frames and double-glazed windows, even though many of the windows were, in fact, wood frames. The window schedule in the Revit model was used to find the number of windows related to

a specific wall; in the schedule the researcher was able to schedule window counts per each wall. The number of windows was then put into Athena with related square footage of a single window in order to compute the total window area related to a given wall. Like windows, the number of doors within each respective wall was calculated using the schedule function in the Revit model, and the resulting data then manually input into Athena. Exterior doors were assumed to be solid wood frame doors (see Table 2). 3.3.6. Modelling uncertainties It is important to note that there is some uncertainty related to the accuracy of the Bill of Materials, due to the assumptions described in the previous section. First, the roof material and construction was based on similar buildings built around same period, because it was not possible to get on the roof without professional equipment. Second, the live load assumption was based on the current building code. This might have caused overestimation of many of the live loads. This, in turn, likely led to a slight overestimation. Third, due to the lack of choice in Athena, all windows were chosen to be double-pane, which is different from actual single-pane glass. This led to overstatement of materials use and, ultimately, the environmental impact. 4. Results (embodied energy vs. operational energy) Energy and material demand results in all life-cycle phases will be illustrated first, followed by results of other selected environmental impacts (global warming potential, ozone potential, human health particular potential, smog potential) across all life-cycle phases for the six different scenarios (Tables 3 and 4). Overall, this historic building consumes more life-cycle energy at the condition meeting the current basic Building Energy Code (2012 ICC). New construction with an Energy usage intensity(EUI) target at 19 KBtu/sq ft/year is the best-performing option from a whole life-cycle energy perspective. This also means that the new construction needs to be very efficient and that it has the potential to be a net zero energy building. According to the New Building Institute’s “2014 Getting to Zero Status Update Report,” the average net zero building operational energy EUI is 26 KBtu/sq ft/year [48]. A renovated building with an EUI target of 19 KBtu/sq ft/year is the second-best-performing option from a whole life-cycle energy perspective. As for the embodied primary energy consumption among all building assemblies groups, in general the external walls of the historic Bent’s Opera House represented the highest total primary energy consumption, accounting for nearly 85% of the energy consumed through life-cycle stages A through C. The second-highest consumption was in floor assemblies, which accounted for 6%. In the renovation, external walls accounted for 78% of the total primary energy consumption, and the roof assembly rose to second place, consuming 12% of the total energy. In the new construction scenario, the external wall assemblies still ranked first; however, they only accounted for 54% of the total primary energy consumption. All other categories had substantial increases in percentage: beams and columns assembly ranked second, representing 32% of the consumption; and the roof assembly accounted for 8%, the third-highest energy consumption category. 5. Conclusion 5.1. Significance of this study The significant features of this life-cycle analysis, compared to previous life-cycle analyses of buildings, are the following:

M. Hu / Energy and Buildings 140 (2017) 131–139


Table 2 LCA Tool and Data Comparison (for Building and Construction Industry). Name



Envest2 EcoQuantum Athena LEGEP Ecoinvent GaBi SimaPro BEES

UK Australia Canada Germany Switzerland Germany Netherland US

Environmental Profiles data a UK and Netherland North America Germany, Switerland,France Worldwide Worldwide EU US


Main application

Eco Quantum consultancies Athena Sustainable Material Institute PE International GmbH University of Stuttgart, LBP-GaBi PRé sustainability National Institute of Standards and Technology

all building products all products building building all products all products all products and process building products/materials

Table 3 Energy Performance in LCA Models.

Energy Usage Intensity (kBtu/sq ft/year)

Building #1

Building #2

Building #3

Building #4

Building #5

Building #6







Table 4 Building Assemblies and Materials Included in LCA. Assemblies Makeup

Historic Building


New Construction


Natural solid sandstone


Unclad wood window frame double pane glaze no coating air Solid wood door Plywood decking @15 mm with 3.6 kPa Softwood lumber with live load 2.4 kPa Glulam Plywood decking @ 15 mm without insulation

Natural solid sandstone with additional fiberglass batt insulation (R30) PVC window frame double-glazed no coating air Solid wood door Plywood decking @15 mm with 3.6 kPa

Brick cladding concrete backing with air barrier and fiberglass batt insulation Fiberglass window frame double-glazed soft coated argon Fiberglass exterior door 50% glazing Concrete hollow core floor with live load 2.4 kPa Precast concrete with live load 2.4 kPa

Glulam Plywood decking @ 15 mm with R40 insulation and waterproofing

Concrete @ 200 mm with average flyash%

Concrete @ 200 mm with average flyash%



Softwood lumber with live load 2.4 kPa

• It uses a comprehensive and specific materials inventory based on actual design documents, historic records, and on-site measurement and investigations. • It specifies the most up-to-date energy performance targets, based on the most recent Energy Star and Commercial Building Energy Consumption Survey(CBECS) data. • It offers a comprehensive comparison of a historic building, a renovation, and new construction. • It quantifies the percentage of each major building assemblies group within the whole-building life-cycle energy consumption and life-cycle environmental impact potential.

5.1.1. Life-cycle energy analysis (LCEA) For the life-cycle energy analysis outcome, the most significant benefits (i.e., energy saving) are mainly related to improvements in the building envelope’s thermal properties (high-efficiency windows and the additional thermal insulation in the exterior wall and roof). Substitution of insulation, lighting, and glazing components provided particularly efficient solutions. In all the different scenarios, using high-efficiency HVAC and lighting systems also showed significant benefits in saving life-cycle energy consumption. Using highly energy-efficient window, door, and insulation materials increased the primary embodied energy. The building life span is 75 years, and operational energy accounted for more than the minimum 55% in all the different scenarios; moreover, the up-

Precast concrete Precast concrete decking with R40 insulation, EPDM cellulose, and drainage Concrete @ 200 mm with average flyash%

front additional primary embodied energy cost will most likely be offset by the saved operational energy. 5.1.2. Life-cycle environmental impact assessment (LCEIA) The environmental impacts of the six different scenarios do not follow the life-cycle energy consumption profile closely—in fact, quite the opposite: they are almost a mirror image of the energy performance. The four indicators are global warming potential (GWP), ozone depletion potential (ODP), smog potential (SP), and human health potential (HHP). As for GWP, new construction was much higher in product and end-of-life stages—in fact, almost two times higher. The renovated building had a slightly higher potential compared to the existing building and new construction. In the construction process stage, new construction also had a higher GWP potential. Overall, new construction had 1.35 times the GWP potential over baseline (i.e., the existing building), whereas the renovated building had 1.1 times the GWP potential over the baseline due to the fact that renovation adds materials in order to increase building efficiency. For HHP, the new building was 3.4 times higher than the existing building and 1.6 times higher than the renovated building, due to the advanced synthetic building materials. For ODP, the new building was 1.43 times higher than the existing building, and the renovated building had the lowest potential, due to the advanced synthetic building materials. For SP, if we exclude the beyondbuilding life stage, the new building was 1.43 times greater than the existing building. The renovated building had the lowest envi-


M. Hu / Energy and Buildings 140 (2017) 131–139

ronmental impact potential, due to the balance between advanced materials/system and natural organic materials. If we include the beyond-building life stage, then the historic building has the highest SP, around 1.43 greater than new construction and 1.16 more than the renovated building. Overall, new construction has a much greater environmental impact potential in all four categories: GWP, HHP, ODP, and SP. Even though new construction, particularly the second new construction scenario, could possibly achieve the on-site net zero energy goal, the environmental impact could not be offset within the building’s life span of 75 years. This raises a concern about how to balance the energy saving benefit from using advanced building materials and systems against the long-term environmental impact induced by those materials and systems.

5.1.3. Decision-making implications These case studies demonstrate that operating energy accounts for the major share (90–95%) of the life-cycle energy use of buildings, followed by embodied energy (5–10%), whereas demolition and other process energy has a negligible or small share. The operating energy of the buildings accounts for the largest share of life-cycle energy distribution; therefore, reducing it appears to be the most important aspect in the design of buildings that demand less energy throughout their life cycle. Accordingly, embodied energy should be addressed in the second instance. We also reached the preliminary conclusion that the existing building could consume up to 7.6 times the primary energy (i.e., embodied and operational energy) compared to construction of a new building, due to the large percentage of operational energy resulting from the original inefficient design. Based on our findings, we also reached the preliminary conclusion that new construction has a much higher environmental impact potential in all categories, from the product stage to endof-life. To find a balance between reducing primary energy (both embodied energy and operational energy) and reducing environmental impact potential, building renovation and retrofit appears to be the optimal choice. If the existing building is retrofitted with highly efficient insulation materials and a state-of-the-art efficient HVAC system, the renovated building could meet the current Building Energy Code while preserving at least 80% of the original primary embodied energy. Avoiding demolition could result in a 48% reduction in overall environmental impact potential. Among the different building scenarios—maintaining the existing building, renovating, and new construction—building exterior walls produces the most GWP, HHP, ODP, and SP. This indicates that research and development of energy-efficient exterior materials with less environmental impact could play an important role in reducing the overall environmental impact while also conserving energy.

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