the professional constructor - spring 2015

IN THIS ISSUE:

● Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project

● Characterizing Equipment Cost, Fuel Use, and Emissions for Earthwork Activities

● Analysis of Green Building Initiatives on U.S. University Campuses

● Adoption of Green Building Guidelines in USA, India, and China

● Solar Orientation for Low-Energy Residential Building in Pagosa Springs, Colorado

● Allhands Student Essays

THEPROFESSIONALCONSTRUCTORS P R I N G 2 0 1 5 | V O L U M E 3 9 | N U M B E R 0 1

JOURNAL OF THE AMERICAN INSTITUTE O F C O N S T R U C T O R S

Photo Credit: TXDOT, 7th Street Bridge Project in Ft. Worth by Sundt Construction

About the AIC:

Founded in 1971, the American Institute of Constructors mission is to promote individual professionalism and excellence throughout the related fields of construction. AIC supports the individual Constructor throughout their careers by helping to develop the skills, knowledge, professionalism and ethics that further the standing of the construction industry. AIC Members participate in developing, and commit to, the highest standards of practice in managing the projects and relationships that contribute to the successful competition of the construction process. In addition to membership, the AIC certifies individuals through the Constructor Certification Commission. The Associate Constructor (AC) and Certified Professional Constructor (CPC) are internationally recognized certifications in the construction industry. These two certifications give formal recognition of the education and experience that defines a Professional Constructor. For more information about the AIC please visit their website at www.professionalconstructor.org.

Our Mission:

▲ To promote individual professionalism and excellence throughout the related fields of construction.

▲ A qualifying body to serve the individual in construction, the Constructor, who has achieved a recognized level of professional competence;

▲ Opportunities for the individual constructor to participate in the process of developing quality standards of practice and to exchange ideas;

▲ Leadership in establishing and maintaining high ethical standards;

▲ Support for construction education and research;

▲ Encouragement of equitable and professional relationships between the professional constructor and other entities in the construction process; and

▲ An environment to enhance the overall standing of the construction profession.

AIC PAST PRESIDENTS 1971-74 Walter Nashert, Sr., FAIC

1975 Francis R. Dugan, FAIC

1976 William Lathrop, FAIC

1977 James A. Jackson, FAIC

1978 William M. Kuhne, FAIC

1979 E. Grant Hesser, FAIC

1980 Clarke E. Redlinger, FAIC

1981 Robert D. Nabholz, FAIC

1982 Bruce C. Gilbert, FAIC

1983 Ralph. J. Hubert, FAIC

1984 Herbert L. McCaskill Jr., FAIC

1985 Albert L Culberson, FAIC

1986 Richard H. Frantz, FAIC

1987 L.A. (Jack) Kinnaman, FAIC

1988 Robert W. Dorsey, FAIC

1989 T.R. Benning Jr., FAIC

1990 O.L. Pfaffmann, FAIC

1991 David Wahl, FAIC

1992 Richard Kafonek, FAIC

1993 Roger Baldwin, FAIC

1994 Roger Liska, FAIC

1995 Allen Crowley, FAIC

1996 Martin R. Griek, AIC

1997 C.J. Tiesen, AIC

1998-99 Gary Thurston, AIC

2000 William R. Edwards, AIC

2001-02 James C. Redlinger, FAIC

2003-04 Stephen DeSalvo, FAIC

2005-06 David R. Mattson, FAIC

2007-09 Stephen P. Byrne, FAIC, CPC

2009-11 Mark E. Giorgi, FAIC

2011-12 Andrew Wasiniak, FAIC, CPC

2012-13 Tanya Matthews, FAIC, DBIA

2013-14 David Fleming, CPC, DBIA

THEPROFESSIONALCONSTRUCTORJOURNAL OF THE AMERICAN INSTITUTE OF CONSTRUCTORS

http://www.professionalconstructor.org/

AIC BOARD OF DIRECTORS 2014|2015Paul Mattingly, CPC AIC National President BosseMattingly Constructors

Joe Rietman, CPC Vice President Westfield Development, Inc.

Greg Carender, CPC Treasurer Pricewaterhousecoopers

Bradley Monson, CPC Secretary State of Colorado

Paul Mattingly (Elected) (2012-2015) BosseMattingly Constructors, Inc.

Bradley Monson (Elected) (2014-2017) Colorado Department of Public Health and Environment

Brian Holley (Elected) (2014-2017) Rudolph & Sletten

Vincent Tatum (Elected) (2014-2017) Caesars Entertainment

Jason Lucas (Elected) (2014-2017) Clemson University

Mark Hall (Elected) (2012-2015) Hall Construction, Inc.

Joseph Rietman (Elected) (2013-2016) Westfield Development, Inc.

Jim Nissen (Elected) (2013-2016) Pepper Construction

Jim Hoskinson (Elected) (2013-2016)

David Jones (Elected) (2013-2016) ActionCOACH Business Coaching

Greg Carender (Elected) (2012-2015) Pricewaterhousecoopers

Saeed Goodman (Elected) (2012-2015) Washington Headquarters Service

Bernie Ashyk (Chapter Appointed – Northern Ohio) Shook Construction

Michael Cashen (Chapter Appointed - DC Metro) TMG Construction Company

David Dominguez (Chapter Appointed - Arkansas) Ryan Companies US, Inc.

Matt Conrad (Chair, Constructor Certification Commission) The Christman Company

Terry Foster (Chair, Professional Standards Committee) University of Nebraska

Tanya Matthews (Chair, Inter-Industry Committee) TMG Construction Corporation

Articles:

The Professional Constructor (ISSN 0146-7557) is the official publication of the American Institute of Constructors (AIC), 700 N. Fairfax St. Suite 510 Alexandria, VA 22314. Telephone 703.683.4999, Fax 703.683.5480, www.professionalconstructor.org.

This publication or any part thereof may not be reproduced in any form without written permission from AIC. AIC assumes no responsibility for statements or opinions advanced by the contributors to its publications. Views expressed by them or the editor do not represent the official position of the The American Professional Constructor, its staff, or the AIC.

The Professional Constructor is a refereed journal. All papers must be written and submitted in accordance with AIC journal guidelines available from AIC. All papers are reviewed by at least three experts in the field.

THEPROFESSIONALCONSTRUCTORJOURNAL OF THE AMERICAN INSTITUTE O F C O N S T R U C T O R S

S P R I N G 2 0 1 5 | V O L U M E 3 9 | N U M B E R 0 1

EDITORJason D. Lucas, Ph.D., Assistant Professor, Clemson University

Fran Dugan Memorial ............................................................................................5

Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project ............................................................................................6

Hazzard and Lewis

Characterizing Equipment Cost, Fuel Use, and Emissions for Earthwork Activities .............................................................................................................19

Lewis, Shan, Hajji, and Hazzard

Analysis of Green Building Initiatives on U.S. University Campuses ...................28

Bausman and Mueller

Adoption of Green Building Guidelines in USA, India, and China ........................36

Syal, Yang, Kumar, and Jackson

Solar Orientation for Low-Energy Residential Building in Pagosa Springs, Colorado ..............................................................................................................47

Hessman, Clevenger, Nobe, and Leigh

General Interest Articles from The AGC James L. Allhands Essay Competition .....59

First Place Article: “Building and Growing with Mobile Technology” ..................60

Chris Lierheimer

Second Place Article: “Using Mobile Technology for Managing Construction Projects” .............................................................................................................65

Paul Shaw

Spring 2015 — Volume 39, Number 01The American Institute of Constructors | 700 N. Fairfax St., Suite 510 | Alexandria, VA 22314 | Tel: 703.683.4999 | www.professionalconstructor.org

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MEMORIES OF FRANIt was with great sadness that I received the news of Fran Dugan’s passing. We were friends for many years. I got to know Fran when he became actively involved with the AIC Certification Commission, of which I am a member. I remember that Fran was the person that put on the raffle each year in order to raise money for some of AIC’s projects. He also served a term as Chair of the Certification Commission. I always felt very privileged to be invited to dinner with Fran, Ted Benning and Oz Pfaffmann who were and are some of the founders and leaders of this great organization. It has been my good fortune to know and work with these great men and to share their dreams for the future of AIC and Certification. Fran Dugan was one of the great leaders in our industry and will be missed by all who knew him.

David Dorsch, CPC

TMG is saddened by the passing of Fran Dugan, former CEO of Dugan & Meyers Construction Company of Cincinnati. A key player in our industry, he was generous with his time and wisdom. He was one of the founders of the American Institute of Constructors (AIC) and later founded the AIC’s Educational Foundation and its College of Fellows. Fran was devoted to advancing the field of construction and we will miss his indomitable spirit. Our prayers go out to Fran’s wife Jane and his large and loving family.

Fran was an AIC Member for nearly 45 years, CPC #93, and a Past President of the AIC. He made a lasting impact on the AIC and those who had the pleasure of knowing him.

IN MEMORY OF

Fran DuganJANUARY 31, 1927 - DECEMBER 26, 2014

http://www.professionalconstructor.org/Home/


6

Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project

Elizabeth Hazzard, EITAguirre & Fields, LP | [email protected]

Phil Lewis, PhD, PEOklahoma State University | [email protected]

Keywords: Economics, Emissions, Energy, Environment, Sustainability

INTRODUCTION

In order to build new, demolish old, or refurbish existing infrastructure, heavy duty diesel (HDD) equipment must be used. This equipment requires fossil fuel for energy and emits air pollutants that are harmful to the environment and human health. HDD equipment is a substantial contributor to this growing problem. New ways to quantify and characterize this pollution problem must be found in order to mitigate it and achieve sustainable, “lean and green” construction projects.

The economic, energy, and environmental impacts of HDD equipment used for the construction, maintenance, and rehabilitation of the infrastructure are inextricably related. This equipment consumes mass quantities of energy in the form of diesel fuel (at a significant cost to the project) and in turn produces harmful byproducts in the form of air pollution. Real world data is needed to truly understand these relationships. New metrics are needed to assess and estimate the energy and environmental footprint of infrastructure projects, along with their economic impact. These new metrics are a critical part of sustainable project planning and construction management.

This paper presents the results of a case study for an Oklahoma Department of Transportation (ODOT)

ABSTRACT: As the nation moves toward more sustainable energy and environmental standards, it is important to examine all sources of fuel consumption and pollution, including heavy-duty diesel (HDD) construction equipment. In order to quantify these sources at the project level, they must be identified with their respective activities. A case study was performed on an Oklahoma Department of Transportation (ODOT) bridge replacement project in order to establish a baseline estimate of real-world equipment activity, fuel use, and emissions data. These data were collected on a daily basis via jobsite visits and included specific information such as the equipment’s model year, engine horsepower, and hours worked. These data were used to estimate equipment fuel use and emissions based on calculations from the EPA’s NONROAD model. Using these estimates, traditional project management techniques were expanded to evaluate the economic, energy, and environmental impacts of the project. Cumulative frequency diagrams were developed to summarize the accumulation of fuel use and emissions for the project. These results were paired with the ODOT pay item quantities to define new fuel use and emissions estimating factors for project activities. Recommendations include using the new fuel use and emissions estimating factors to identify activities with high energy and environmental impacts and consider potential mitigation strategies.

Elizabeth Hazzard received a Bachelor of Science in Civil Engineering in 2012 and a Master of Science in Construction Engineering and Project Management in 2014, both from Oklahoma State University. Her thesis topic was “Quantifying the E3 Impact on a Bridge Re-placement Project.” She is an Engineer-In-Training and graduate engineer for Aguirre & Fields, LP in Fort Worth, TX.

Phil Lewis is an Assistant Professor in the School of Civil and Environmental Engineering at Oklahoma State University. His primary area of research is the economic, energy, and environmental impacts of construction. He teaches six graduate level courses related to con-struction engineering and project management.



mailto: [email protected]



7Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project

bridge replacement project. The project was located about seven miles west of Stillwater, OK on the eastbound lanes of SH 51 crossing over Harrington Creek. The scope of work included demolishing the existing bridge, building a new reinforced concrete box culvert, constructing and removing a detour, and an asphalt overlay on both highway approaches to the bridge. This project made an ideal case study because of the work represented and its short duration of three months, which ensured that the entire project was monitored. The research team worked closely with ODOT to acquire the data needed for the case study.

The purpose of the case study was to identify the relationships between the economic, energy, and environmental impacts of the project in the form of project cost, fuel use, and emissions, respectively. These relationships were quantified and characterized as new estimating factors that are useful for forecasting the energy and environmental impacts of future projects, as well as monitoring, tracking, and controlling costs, fuel use, and emissions for existing projects. Being able to measure and manage these impacts is the first step towards sustainable lean and green construction projects.

LITERATURE REVIEW

Diesel exhaust (DE) poses risks for humans and the environment (EPA 2003). For example, tiny particles found in DE, known as particulate matter (PM), may cause lung damage as well as aggravate existing respiratory diseases. DE also contains nitrogen oxides (NOx) and hydrocarbons (HC) which are precursors to ozone. Carbon monoxide (CO) is another air pollutant found in DE that adversely affects human health and may even cause death in high concentrations, although unlikely in ambient conditions(EPA 2014a). Approximately 99% of the carbon in diesel fuel is emitted in the form of carbon dioxide (CO2), a greenhouse gas that contributes to global warming and climate change (EPA 2014b).

PM, NOx, CO, and ozone are regulated by the United States Environmental Protection Agency (EPA) through the National Ambient Air Quality Standards (NAAQS) (EPA 2014c). If any pollutant exceeds these standards, that area is categorized as being in nonattainment with the standard and must try to

reacquire attainment status. EPA also enacted engine tier standards for nonroad diesel equipment (including HDD equipment used in construction) that establishes limits for the emission rates of NOx, HC, CO, and PM based on horsepower rating and model year (EPA 2012). Although these regulations have been helpful, more needs to be done at the operational level to further reduce DE and mitigate the resulting environmental and health problems.

HDD equipment plays a significant role in America’s air pollution problems. EPA estimates that the nonroad equipment source sector accounts for about 23% of national NOx emissions and 25% of CO emissions, making it the second highest source sectors for these pollutants. Nonroad equipment emits approximately 18% of national volatile organic compounds, including HC, which makes it the third highest source sector. Furthermore, nonroad equipment is the eighth highest source sector of PM, contributing approximately 6% of national particulate emissions (EPA 2015).

Numerous studies have been conducted to quantify the energy and environmental impacts of HDD construction equipment. Lewis et al. (2009a) outlined requirements and incentives for reducing air pollutant emissions from construction equipment. The authors also compared sources of emissions from various types of equipment. Based on those concepts, Lewis et al. (2009b) developed a fuel use and emissions inventory for a publicly-owned fleet of nonroad diesel construction equipment. This emissions inventory quantified emissions of NOx, HC, CO, and PM for the fleet for both petroleum diesel and B20 biodiesel. The results were categorized by equipment type and EPA engine tier standards. The impact on the inventory of different emissions reduction strategies were compared. Frey et al. (2010) followed up on this work by presenting the results of a comprehensive field study that characterized and quantified real-world emissions of NOx, HC, CO, and PM from nonroad diesel construction equipment. Average emission rates were developed for each equipment type and were presented on a mass per time and mass per fuel used basis for both petroleum diesel and B20 biodiesel. The methodology for the field data collection in these studies using a portable emissions measurement system was documented in detail by Rasdorf et al. (2010).

Other studies have focused on characterizing and quantifying fuel use and emissions on a project



8 Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project

basis. In particular, Marshall et al. (2012) presented a methodology for developing emissions inventories for commercial building projects. This methodology was used by Rasdorf et al. (2012) to conduct a case study for estimating equipment emissions on a real-world commercial building project. These studies used critical path scheduling and resource allocation techniques to estimate equipment fuel use and emissions over the entire duration of the project and also identify those activities that consumed the most fuel and emitted the most pollutants. Although the Marshall and Rasdorf methodology was used for a commercial building project, it was the basis for the bridge replacement case study presented in this paper.

The methodology and results presented here were developed as part of a research thesis by Hazzard (2014). The case study research used traditional construction project management techniques to characterize sustainability of construction projects, particularly the economic, energy, and environmental components. Lewis and Hazzard (2013) presented some of these results in a paper on using earned value management to quantify the economic, energy, and environmental impacts of construction activities. Likewise, preliminary results of the thesis case study were presented in Hazzard and Lewis (2014); however, these results were limited to costs, fuel use, and CO2 emissions. The work in this paper was expanded to include results for NOx, HC, CO, and PM in order to provide a more holistic view of the environmental impacts of an infrastructure project. Furthermore, this paper critically assesses how the energy (fuel use) and environmental (emissions) impacts relate to the economic (costs) impacts.

METHODOLGY

A real-world baseline of project costs, fuel use, and emissions was necessary to characterize the economic, energy, and environmental impacts of a construction project. An ODOT bridge replacement project was chosen to establish this baseline. The bridge was located in Payne County on state highway SH 51 over Harrington Creek west of Stillwater, OK. SH 51 is a four lane divided east-west highway. The two span bridge was located in the two eastbound lanes of SH 51. The overall project including repaving of the bridge roadway approaches was 0.36 miles long. In general,

the bridge replacement project may be considered a medium-sized project for ODOT.

The total cost of the project was $1,267,238. The costs of the roadway and bridge activities were $1,199,940 and included earthwork; construction of a reinforced concrete box culvert (RCBC) to replace the existing bridge; detour construction and removal; demolition of the existing bridge; asphalt paving over the RCBC; and erosion control. These activities required the use of HDD equipment and thus contributed to the economic, energy, and environmental impacts of the project. Other activities, such as mailbox installation and pavement striping, accounted for the remaining project costs but were not included in this analysis because they did not require HDD equipment.

The economic impact (costs) of the above mentioned activities were estimated using actual ODOT payment records. There were a total of 10 activities that represented each stage of the project. These activities included Excavation/Box Preparation, RCBC Construction, Detour Earthwork, Detour Asphalt, Remove Existing Bridge, Mainline Earthwork, Stabilize Subgrade, Asphalt Paving, Remove Detour, and Erosion Control. A summary of these activities is provided in Appendix A. The contract for the project stipulated 120 calendar days for completion but only 95 calendar days were used. Excluding adverse weather days and project downtime (which were not counted against the contractor’s schedule), the contractor used a total of 58 calendar days to complete the project, approximately one-half of the allotted time.

In order to measure the project’s energy and environmental impacts, an activity log and equipment inventory were taken daily during job site visits. For each item of HDD equipment that was on the job site for a particular day, the type, manufacturer, and model of the equipment was recorded. Since the project consisted of many different activities, the equipment and its time of use were recorded for each activity. In addition, a brief summary of the day’s activities, job information, and completed tasks was recorded. Pictures were taken throughout the project for a visual reference of what was accomplished. Once per week,



9Assessing the Economic, Energy, and Environmental Impacts of a Bridge Replacement Project

the research team met with the ODOT project inspector for a project progress report.

Equipment model year, engine horsepower rating, and hours of use were needed to calculate diesel fuel use and emission rates and, ultimately, the total project fuel use and emissions. The model year and engine horsepower rating for each item of equipment were obtained from the performing contractor’s records. A summary of equipment data is provided in Appendix B. The hours of use for the equipment, however, proved particularly problematic to acquire. Initially, the equipment operators were asked to record the equipment’s hour meter reading at the end of each work day for each item of equipment that was used. These readings were to be used to calculate the equipment daily hours of use by subtracting the previous day’s hour meter reading from the current day’s reading. This attempt proved futile for many reasons. In some instances, the operators were generally nonresponsive and did not collect the readings. Furthermore, the equipment owners were reticent to let non-project personnel on their equipment to gather the readings. In other cases, the equipment may not have had an hour meter or it may have malfunctioned and not recorded hours of use. To remedy this problem, the research team consulted with the ODOT project inspector and developed reasonable estimates of daily hours of use for each item of equipment. Based on these estimates, hours of use for each item of equipment typically ranged between four to eight hours per day.

In order to develop the fuel use and emissions inventory for this project’s HDD fleet, fuel use factors were needed for each item of equipment. These factors are estimates of the amount of fuel consumed by a particular item of equipment on a horsepower-hour basis. The factors used for this inventory were based on calculations and the methodology utilized by the EPA NONROAD model (EPA 2005). NONROAD predicts emissions for over 300 types of off-road equipment and further stratifies equipment types by horsepower rating. Fuel types include gasoline, diesel, compressed natural gas (CNG), and liquefied petroleum gas (LPG).

The model provides emissions estimates for NOx, PM, HC, CO, CO2, and sulfur oxides (SOx).

For fuel use, NONROAD uses brake specific fuel consumption (BSFC) reported in pounds per horsepower-hour (lb/hp-hr). The factors used by NONROAD were based on engine dynamometer test data and adjusted accordingly to account for in-use operation that differs from the typical test conditions. The emission factors (EF) are based on the following equation.

EFadj (BSFC) = EFss x TAF (1)where:EFadj = final fuel use factor used in NONROAD (lb/hp-hr)EFss = zero-hour, steady-state fuel use factor (lb/hp-hr)TAF = transient adjustment factor (unitless)

Emission factors for HC, CO, NOx, and PM were calculated using equations (2) and (3). These factors are unique to each type of equipment with its particular model year and age.

EFadj (HC, CO, NOx) = EFss x TAF x DF (2)where:EFadj = final emission factor used in model, after

adjustments to account for transient operation and deterioration (g/hp-hr)

EFss = zero-hour, steady state emissions factor (g/hp/hr)TAF = transient adjustment factor (unitless)DF = deterioration factor (unitless)

PM emissions depend on the sulfur content of the fuel being consumed by the engine, therefore equation (2) must be slightly modified as follows:

EFadj (PM) = EFss x TAF x DF x SPM adj (3)where:SPMadj = adjustment to PM emission factor to account for

variations in fuel sulfur content (g/hp-hr)

NONROAD computes CO2 directly by using in-use adjusted BSFC, as shown in equation (4). The carbon that goes into exhaust HC emissions is subtracted to correct the equation for unburned fuel.



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EFadj(CO2) = (BSFC x 453.6 – HC) x 0.87 x (44/12) (4)where:BSFC = in-use adjusted fuel consumption factor

(lb/hp-hr)453.6 = conversion factor from pounds to gramsHC = in-use adjusted hydrocarbon emissions

(g/hp-hr)0.87 = carbon mass fraction of diesel44/12 = ratio of CO2 mass to carbon mass

The individual fuel use values for each item of equipment were computed according to the methodology presented in Median Life, Annual Activity, and Load Factor Values for Nonroad Engine Emissions Modeling (EPA 2010) and the following equation:

BSFC = Pop × Power × LF × A × EFadj (BSFC) (5)where:BSFC = total fuel consumption for the specified

equipment (lb)Pop = equipment populationPower = engine rated horsepower (hp)LF = engine load factor (fraction of available power)A = equipment activity (hr)EFadj (BSFC) = BSFC factor (lb/hp-hr)

The total project fuel use values were calculated for each item of equipment by setting Pop = 1. The engine rated horsepower (Power) for each item of equipment was obtained from the contractor’s equipment, thus the individual and overall fuel use values were specific to this particular project. The engine rated horsepower is the maximum level of power that an engine is designed to produce at its rated engine speed. Nonroad equipment seldom operates at its rated power for extended periods and frequently operates at a variety of speeds and loads. NONROAD uses a load factor (LF) to indicate the average proportion of rated power used to account for the effects of operation at idle and partial load conditions. Equipment activity values were based on estimates from the ODOT project inspector. The total fuel use and emissions were tabulated for each item of equipment and the entire fleet on a daily basis, activity basis, and overall project basis.

FINDING

The contractor’s bid price for the project was $1,193,759. A change order was submitted to over-excavate the proposed RCBC site and fill it in with rip rap and small rock to stabilize the unanticipated unstable soil. This change added $73,480 to the project total. Other quantity over- and under-runs changed the final contract amount to $1,267,238. Of this contract value, HDD equipment contributed to approximately $1,200,000 of the total activity cost (95%); therefore, this amount was considered the overall economic impact of HDD equipment on the project and was used in the subsequent calculations for the energy and environmental impacts. Appendix A shows the fuel-consuming and pollutant-emitting activities and pay items associated with the HDD equipment in a total project cost breakdown.

The activities with the greatest economic impact were RCBC Construction and Asphalt. These two activities constituted approximately 70% of the HDD economic impact. The majority of RCBC Construction was completed during the first half of the project and most of Asphalt Paving was completed during the second half of the project.

Figure 1 shows the total cost accumulation of the HDD economic impact over the duration of the project. These costs follow an “s-curve” that is typically found in graphs of construction project costs versus time. Figure 1 also shows the accumulation of fuel use (energy impact) over the duration of the project. Note that this curve does not follow the common “s-curve” but it is a smoother curved line, indicating that fuel use was somewhat consistent throughout the project, although it accumulated at a slightly lower rate during the second half of the project. Overall, approximately 20,000 gallons of diesel fuel were consumed to produce approximately $1,200,000 of project value – an economic-energy rate (ratio of project value to fuel consumed) of $60 per gallon. Although this rate varies at different points on the curve, it typically ranges from $45 to $60 per gallon.




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Figure 1: Economic and Energy Impact of Project

Figures 2 and 3 show the total emissions (environmental impact) from HDD equipment accumulated during the project. Figure 2 shows the results for CO2 alone because it is emitted in much higher quantities compared to the other pollutants. It should be noted that the curve for CO2 accumulation is nearly identical to the curve for fuel use accumulation. This is because approximately 99% of the carbon in fossil fuels is emitted as CO2, thus, it is highly correlated with fuel consumption. In general, all of the pollutant emissions accumulated at a fairly constant rate during the project, accordingly with fuel use. Among the NAAQS criteria pollutants, PM had the highest total emissions for the project followed by CO, HC, and NOx. Of these pollutants, PM and NOx are of particular concern because they are emitted at higher rates from diesel engines compared to other pollutant sources.

Overall, the project emitted approximately 850 pounds of HC, 1,300 pounds of CO, 800 pounds of NOx, 1,600 pounds of PM, and 220 tons of CO2. Relating this to the economic impact of the project, the economic-environmental rates (ratio of project value to pollutant emitted) for the project were approximately $1,400/lb, $900/lb, $1,500/lb, $770/lb, and $5,500/ton, respectively. These rates provide a new metric for assessing sustainability issues of construction projects. For example, for each $5,500 of project value achieved through the use of HDD equipment, the environment is impacted by one ton of CO2 emissions. Of the NAAQS criterial pollutants, PM has the most severe environmental impact – only $770 of project value can be achieved per pound of PM emitted.

Figure 2: Economic and Environmental (CO2) Impact

Based on the observations of fuel use and emissions for the project, a closer examination of the individual activities was warranted. Figure 4 presents the economic, energy, and environmental impacts for each activity based on a percentage of cost, fuel use, and emissions, respectively. The economic impact was determined by dividing the activity cost by the total project cost affected by HDD equipment. The energy impacts were determined by dividing the individual activity’s fuel use by the total project fuel use. The environmental impact was determined by calculating the individual percentage contributions of HC, CO, NOx, PM, and CO2 for each activity; then, the individual pollutant percentages were averaged to represent the overall environmental impact of each activity.

Figure 3: Economic and Environmental (HC, CO, NOx, and PM) Impact

Some activities, such as RCBC Construction and Stabilize Subgrade, had a strong relationship between economic, energy, and environmental impacts; that is, all three impacts were either very high or very low. Some activities, such as Excavation/Box Prep and Remove Bridge, had a low economic impact but high energy and environmental impacts. Other activities, such as Detour Asphalt and Asphalt, had a




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high economic impact but energy and environmental impacts. These observations indicate that economic-energy rates and economic-environmental rates are needed for each activity for more accurate estimating.

Figure 4: Economic, Energy, and Environmental Impact of Activities

Figure 5 shows the accumulation of the economic, energy, and environmental impacts over the duration of the project on a percent complete basis. For example, when the project is 50% complete based on time, approximately 75% of the energy and environmental impacts have been achieved. While the energy and environmental impacts steadily accumulate, the economic impact does not. All three impacts trend at approximately the same rate up to about 40% project completion. At this point, the economic impact accumulates at a slower rate for the next 25% of the project but then rapidly increases again for the next 10% of time. For the final 25% of the project, all three impacts trend at approximately the same rate. This difference in accumulation of impacts is a result of which activity is in progress and the pay items associated with it. For instance, some activities have a high cost associated with labor and equipment and a low materials cost, resulting in high energy and environmental impacts but a low economic impact. Other activities may have a low labor and equipment cost but a high materials cost, which results in a high economic impact but low energy and environmental impacts.

Figure 5. Accumulated Economic, Energy, and Environmental Impacts

Based on these results, economic, energy, and environmental factors were developed to estimate and quantify fuel use and emissions from HDD equipment. These estimating factors are presented in Table 1. These rates were calculated by categorizing the project according to slightly different activities with specific, definable quantities assigned to them. The activity estimating factors were created by dividing the amount of fuel used or pollutant emitted per activity by the quantity of work associated with each activity. These factors may be applied to any type of project which requires these types of activities. For example, one gallon of fuel is required to excavate 3.5 cubic yards of earth; likewise, 310 cubic yards of earth is excavated per ton of CO2 emitted for the Earthwork activity. These results demonstrate how common production rate calculations can be extended to include energy and environmental components.

Table 1: Economic, Energy, and Emissions Estimating Factors

Ta b le 1 : Ec o no m ic , Ene rg y , a nd Em is s io ns Es t im a t ing Fa c t o rs

Estimate Item Fuel Use CO2 HC CO NOx PM

Total Project Cost $61/gal $5,400/ton $1,400/lb $900/lb $1,500/lb $770/lb

Earthwork 3.5 cy/gal 310 cy/ton 82 cy/lb 52 cy/lb 85 cy/lb 43 cy/lb

RCBC Construction 0.03 lf/gal 2.5 lf/ton 0.65 lf/lb 0.4 lf/lb 0.68 lf/lb 0.34 lf/lb

Detour Paving 3.1 lf/gal 280 lf/ton 56 lf/lb 43.00 lf/lb 79 lf/lb 39 lf/lb

Mainline Paving 2.1 lf/gal 190 lf/ton 48 lf/lb 32 lf/lb 54 lf/lb 31 lf/lb

Sodding 56 sy/gal 5,000 sy/ton 2,000 sy/lb 1,300 sy/lb 1,800 sy/lb 1,200 sy/lb

Detour Removal 3.5 lf/gal 320 lf/ton 96 lf/lb 60 lf/lb 87 lf/lb 56 lf/lb

Bridge Removal 0.05 lf/gal 4.7 lf/ton 1.1 lf/lb 0.72 lf/lb 1.32 lf/lb 0.64 lf/lb

CONCLUSIONS AND RECOMMENDATIONS Profe ss ional cons t ruct ors are ve ry familiar wit h t he economic impact of t he ir projec t s . They e s t imat e price and schedule based on known quant it ie s , his t orical dat a , and indus t ry s t andards . Economic impact s can also be monit ored and t racked t o de t e rmine whe t he r or not t he projec t is on schedule and wit hin budge t . Quant ifying and charact e riz ing t he ene rgy and environment al impact s of a projec t has recent ly become an increas ing conce rn. This case s t udy demons t rat e s a me t hodology for ident ifying and quant ifying t he se impact s for a real-world projec t . The pape r a lso deve loped new me t rics t hat re fle c t t he re la t ionship be t ween t he economic and ene rgy component s of a projec t , as we ll t he economic and environment al aspect s . Wit h furt he r re finement , t he se me t rics may prove use ful in e s t imat ing t he ove rall e conomic , ene rgy, and environment al foot print s of infras t ruct ure projec t s . The case s t udy of ODOT’s bridge replacement projec t has provided valuable ins ight t o t he fut ure of cons t ruct ion e s t imat ing . Not only can cons t ruct ors e s t imat e a projec t ’s cos t and schedule t o de t e rmine t he economic impact , t he ene rgy and environment al impact s ( in t he form of fue l use and emiss ions ) can be e s t imat ed in orde r t o quant ify t he ir impact on socie t y. Act ivit ie s wit h high labor and equipment cos t s but low mat e ria ls cos t s will gene rally re sult in large ene rgy and environment al impact s but low economic impact s . On t he o t he r hand, ac t ivit ie s wit h low labor and equipment cos t s but high mat e ria ls cos t s will re sult in a high economic impact but small ene rgy and environment al impact s . Us ing t he princip le s of re source a llocat ion and leve ling , cons t ruct ors can schedule ac t ivit ie s t o minimize t he ene rgy and environment al impact s of t he ir work. Even t hough t he economics of a projec t will like ly cont inue t o drive t he projec t bot t om line and schedule , it is now import ant t o a lso cons ide r sus t a inabilit y is sues during t he p lanning and cons t ruct ion phase s of a projec t .




13

CONCLUSIONS AND RECOMMENDATIONS

Professional constructors are very familiar with the economic impact of their projects. They estimate price and schedule based on known quantities, historical data, and industry standards. Economic impacts can also be monitored and tracked to determine whether or not the project is on schedule and within budget. Quantifying and characterizing the energy and environmental impacts of a project has recently become an increasing concern. This case study demonstrates a methodology for identifying and quantifying these impacts for a real-world project. The paper also developed new metrics that reflect the relationship between the economic and energy components of a project, as well the economic and environmental aspects. With further refinement, these metrics may prove useful in estimating the overall economic, energy, and environmental footprints of infrastructure projects.

The case study of ODOT’s bridge replacement project has provided valuable insight to the future of construction estimating. Not only can constructors estimate a project’s cost and schedule to determine the economic impact, the energy and environmental impacts (in the form of fuel use and emissions) can be estimated in order to quantify their impact on society. Activities with high labor and equipment costs but low materials costs will generally result in large energy and environmental impacts but low economic impacts. On the other hand, activities with low labor and equipment costs but high materials costs will result in a high economic impact but small energy and environmental impacts. Using the principles of resource allocation and leveling, constructors can schedule activities to minimize the energy and environmental impacts of their work. Even though the economics of a project will likely continue to drive the project bottom line and schedule, it is now important to also consider sustainability issues during the planning and construction phases of a project.

The data and new estimating factors presented here represent only one project. It is recommended that the methodology be expanded to include similar projects in order to refine the data and create more robust estimating metrics. Furthermore, other types

of projects should be studied to expand the breadth of this approach. This would result in more accurate and reliable economic, energy, and environmental estimating factors. After these estimating factors have been validated and documented, design professionals may use them during the project planning phase to estimate the economic, energy, and environmental footprints of future projects.

Scheduled activities with high anticipated fuel use and emissions should be closely examined in order to identify mitigation strategies. For example, HC and NOx react in the presence of sunlight and high temperatures to form ground-level ozone. If hot weather is forecasted and an activity with high HC and NOx emissions is scheduled during that time, the activity may be moved to a cooler time period when it would lessen the effects of ozone formation (provided the activity has adequate schedule float). If it is not feasible to reschedule the activity, low or no production “ozone days” may be included in the schedule to offset ozone forming activities. This is akin to the accounting of adverse weather days that are already a part of project scheduling. Furthermore, adjusting project start and finish dates to avoid ground-level ozone formation (particularly in ozone non-attainment areas) may be considered. Such considerations could become a matter of public policy, especially for publicly-owned projects.

High quality, real-world equipment use data is needed in order for the economic, energy, and environmental estimating factors to be effective. One of the challenges faced by the researchers was acquiring this data. Although improved research protocols may be developed to collect the field data, technology offers the best solution through the use of telematics (Moore 2012). Equipment telematics enables the collection of accurate, real-time equipment data including hours of use, engine load, and fuel use – all of which is needed for the new sustainability estimating factors. Not only can this data be used to predict fuel use and emission rates for future projects, it may also be used to monitor, track, and control fuel use and emissions during construction. This updated information permits constructors to constantly assess the energy and environmental impacts of the project on high resolution timescales, even on an hourly basis.




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In the past, most fleet owners and construction managers seldom concerned themselves with air pollution resulting from their projects. As the regulatory environment becomes more stringent, constructors can no longer afford to disregard the energy and environmental impacts of their work. They must be able to quantify the fuel use and emissions of their equipment in order to manage them. After identifying and characterizing the sources of air pollutant emission, mitigation strategies may be employed. For example, some fleet owners are investigating using alternative fuels, such as biodiesel, to reduce their dependence on traditional diesel fuel and reduce emissions of pollutants and greenhouse gases. Some public project owners are including pollution mitigation strategies in their contracts and specifications, such as limiting idle time of HDD equipment or requiring a minimum EPA engine tier standard for all equipment used on the project. Furthermore, fleet managers may consider alternative equipment and “right-sizing” strategies to match the most appropriate item of equipment with the specified task, rather than merely using whichever equipment is available or convenient.

REFERENCES

EPA (2003). “Diesel Exhaust in the United States,” U. S. Environmental Protection Agency, EPA420-F-03-022, Ann Arbor, MI.

EPA (2005). “Users Guide for the Final NONROAD2005 Model,” U. S. Environmental Protection Agency, EPA-420-R-05-013, Ann Arbor,

MI.

EPA (2010). “Median Life, Annual Activity, and Load Factor Values for Nonroad Engine Emissions

Modeling,” U. S. Environmental Protection Agency, EPA-420-R-10-016, Ann Arbor, MI.

EPA (2012). “Frequently Asked Questions from Owners and Operators of Nonroad Engines,

Vehicles, and Equipment Certified to EPA Standards,” U. S. Environmental Protection Agency, EPA-420-F-12-053, Ann Arbor, MI.

EPA (2014a). “National Clean Diesel Campaign: Basic Information,” United States Environmental

Protection Agency, www.epa.gov/cleandiesel/basicinfo. Information viewed on October 27, 2014.

EPA (2014b). “Overview of Greenhouse Gases: Carbon Dioxide Emission,” United States

Environmental Protection Agency, www.epa.gov/climatechange/ghgemissions/gases/co2. Information viewed on October 27, 2014.

EPA (2014c). “National Ambient air Quality Standards (NAAQS), Air and Radiation,” United

States Environmental Protection Agency, www.epa.gov/air/criteria, information accessed October 27, 2014.

EPA (2015). “Air Emission Sources,” United States Environmental Protection Agency, available at

www.epa.gov/air/emissions, information accessed on January 29, 2015.

Frey, H. C., Rasdorf, W., and Lewis, P. (2010) “Comprehensive Field Study of Fuel Use and

Emissions of Nonroad Diesel Construction Equipment,” Transportation Research Record: Journal of the Transportation Research Board, National Research Council, Washington, DC, 2158, 69-76.

Hazzard, E. (2014). “Quantifying the E3 Impact on a Bridge Replacement Project,” Master of Science

Thesis, Oklahoma State University, Stillwater, OK.

Hazzard, E. and Lewis, P. (2014). “Results of a Case Study on Quantifying Fuel Use and Emissions for

a Bridge Replacement Project,” Proceedings of the 2014 Construction Research Congress, American Society of Civil Engineers, Atlanta, GA.

Lewis, P. and Hazzard, E. (2013). “Using Earned Value Management to Quantify Economic, Energy,

and Environmental Sustainability in Construction Activities,” Proceedings of the Canadian Society of Civil Engineers 2013 Annual Conference and 4th Construction Specialty Conference, Montreal, QC.

Lewis, P., Rasdorf, W., Frey, H.C., Pang, S-H., and Kim, K. (2009a). “Requirements and Incentives

for Reducing Construction Vehicle Emissions and Comparison of Non-road Diesel Engine Emissions Sources,” Journal of Construction Engineering and Management, American Society of Civil Engineers, 135 (5), 341-351.

Lewis, P., Frey, H.C., and Rasdorf, W. (2009b). “Development and Use of Emissions Inventories for

Construction Vehicles,” Transportation Research Record: Journal of the Transportation Research Board, National Research Council, Washington, D.C., 2123, 46-53.




15

Marshall, S. K., Rasdorf, W., Lewis, P., and Frey, H.C. (2012). “A Methodology for Estimating Emissions

Inventories for Commercial Building Projects,” Journal of Architectural Engineering, American Society of Civil Engineers, 18(3), 251-260.

Moore, W. (2012). “Practical Telematics: The Basics of Using and Integrating Telematics to Make a

Noticeable Difference in Fleet Management,” Construction Equipment Magazine, available at www.constructionequipment.com/practical-telematics.

Rasdorf, W., Frey, H.C., Lewis, P., Kim, K., Pang, S-H., and Abolhassani, S. (2010). “Field Procedures

for Real-World Measurements of Emissions from Diesel Construction Vehicles,” Journal of Infrastructure Systems, American Society of Civil Engineers, 16 (3), 216-225.

Rasdorf, W., Lewis, P., Marshall, S. K., Arocho, I., and Frey, H.C. (2012). “Evaluation of On-Site Fuel Use

and Emissions over the Duration of a Commercial Building Project,” Journal of Infrastructure Systems, American Society of Civil Engineers, 18(2), 119-129.




16

APPENDIX A: Summary of Project Activities and Pay Items Using HDD Equipment

Activity Pay Item Quantity Unit Price

Total Item Price

Total Activity

Cost

Excavation & Box Prep

Clearing and Grubbing LSUM $3,300 $3,300

$32,844 Removal of Existing Pipe 90 LF $5 $405

Unclassified Excavation 3,993 CY $6 $21,962

Structural Excav. Unclass. 239 CY $30 $7,178

RCBC Construction

Class AA Concrete 833 CY $280 $233,240

$413,856 Type 1 Plain Riprap 1,037 TON $52 $54,098

TBSC Type D 402 TON $48 $19,382 Reinforcing Steel 148,800 LB $1 $107,136

Detour Earthwork

Unclassified Borrow 12,903 CY $9 $116,128

$126,349

Inlet (SMD Type 2) 2 EA $1,750 $3,500 Add’l Depth in Inlet 2 VF $350 $700

18” CGSP 42 LF $23 $966

24” CGSP 80 LF $29 $2,320

Standard Bedding Material 42 CY $47 $1,992 Trench Excavation 165 CY $5 $743

Detour Asphalt

Fly Ash 70 TON $62 $4,314

$124,140 TBSC Type E 96 TON $32 $3,072 Tack Coat 369 GAL $3 $962

Superpave Type S3 (64-22) 1,045 TON $75 $78,374

Superpave Type S4 (64-22) 425 TON $88 $37,418

Remove Bridge

Removal of Guardrail 328 LF $3 $820 $15,320 Removal of Bridge Items LSUM $7,000 $7,000

Removal of Existing Bridge LSUM $7,500 $7,500

Mainline Earthwork

Unclassified Borrow 6,452 CY $9 $58,064

$118,570

Inlet GPI Type 2 2 EA $2,350 $4,700

Add’l Depth in Inlet 1.5 VF $400 $600

36” RC Pipe Class III 542 LF $51 $27,642

36” CGSP 67 LF $39 $2,613 42” CGSP 69 LF $43 $2,967

Type D4 CET 4 EA $790 $3,160

Standard Bedding Material 246 CY $47 $11,551 Trench Excavation 671 CY $5 $3,021

Removal of Ditch Liner 945 LF $5 $4,253




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Activity Pay Item Quantity Unit Price

Total Item Price

Total Activity

Cost

Stabilize Subgrade Stabilized Subgrade 2,701 SY $2 $5,401 $5,401

Asphalt Paving

Agg Base Type A 9 CY $78 $722

$292,924

Fly Ash 32 TON $62 $1,958

TBSC Type E 470 TON $32 $15,036 Tack Coat 1,107 GAL $3 $2,888

Bituminous Binder 104 GAL $8 $866

Superpave Type S3 (70-28) 991 TON $80 $79,270

Superpave Type S3 (64-22) 1,292 TON $75 $96,899 Superpave Type S4 (70-28) 766 TON $88 $67,400

Cold Milling Pavement 5,044 SY $4 $20,934

Removal of Asphalt 556 SY $4 $2,281 Sawing Pavement 1,698 LF $3 $4,670

Remove Detour Removal of Asphalt 2,884 SY $4 $11,826 $11,826

Erosion Control

Solid Slab Sodding 28,000 SY $2 $47,600 $58,708 Class C Concrete 44 CY $250 $11,108

TOTAL PROJECT COST $1,199,939




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APPENDIX B: Summary of HDD Equipment Used on the Project

ENGINE DATA

HDD Equipment EPA Tier Horsepower Model Year Hours of Use Excavator 3 242 2007 298 Excavator 1 168 2002 72 Excavator 2 172 2003 20 Excavator 4T 194 2011 116 Bulldozer 3 115 2008 318 Bulldozer 2 75 2005 12 Backhoe Loader 1 80 1998 146 Wheel Loader 2 180 2005 62 Wheel Loader 1 63 2000 20 Off Road Truck 2 285 2004 176 Off Road Truck 1 335 1998 50 Forklift 1 78 1999 120 Forklift 0 80 1995 12 Crane 0 300 1986 86 Motor Grader 3 220 2008 104 Motor Grader 1 165 2002 16 Towed Scraper 3 190 2006 8 Skid Steer Loader 1 81 2003 64 Skid Steer Loader 4T 84 2013 16 Elevating Scraper 0 187 1995 28 Asphalt Layer 3 224 2010 28 Broom Sweeper 1 76 2003 64 Telescopic Handler 3 110 2008 8 Recycler 1 318 1999 18 Asphalt Conveyor 1 250 2002 8 Asphalt Conveyor 2 300 2004 4 Sod Roller 4T 84 2013 28 Roller Compactor 1 96 1999 142 Vibratory Roller 3 160 2010 16 Pneumatic Roller 3 123 2009 4 Pneumatic Roller 1 120 2002 24 Wheel Compactor 3 80 2009 24 Air Compressor 1 48 1998 32




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Characterizing Equipment Cost, Fuel Use, and Emissions for Earthwork Activities

Phil Lewis, PhD, PEOklahoma State University | [email protected]

Yongwei Shan, PhD, PEOklahoma State University | [email protected]

Apif Hajji, PhDState University of Malang (Indonesia) | [email protected]

Elizabeth Hazzard, MS, EITAguirre & Fields LP | [email protected]

Keywords: equipment, costs, fuel use, emissions, sustainability

INTRODUCTION

Earthwork activities are a major part of many construction projects. These activities, such as clearing, grubbing, excavation, hauling, and grading, may account for the majority of the total project cost. Furthermore, these activities are performed by heavy-

duty construction equipment that consume large quantities of diesel fuel and thus emit large quantities of pollutants and greenhouse gases. The economic, energy, and environmental impact of earthwork activities performed by construction equipment is significant.

Construction estimators have long been able to estimate the owning and operating (O&O) costs associated with construction equipment. Likewise, they are able

ABSTRACT: The objective of this paper is to examine the relationships between construction equipment costs, fuel use, and air pollutant emissions to make more informed decisions in construction planning and achieve more sustainable construction activity. This paper presents an estimating approach that combines both construction and environmental data to assess the relationships between equipment costs, fuel use, and emissions. To characterize these relationships, a case study is presented for a dozer performing a bulk excavation activity. Sensitivity analyses based on soil type, dozing distance, and engine horsepower rating are presented. Results indicate that there is little difference in the equipment total cost, fuel use, and emissions for sand and gravel, sandy clay and loam, and common earth but clay has the highest values of the four soil types. Other relationships indicate that total cost, fuel use, and emissions increase as dozing distance increases but equipment total cost decreases as engine horsepower increases. One of the key findings is that there is an inverted u-curve relationship between engine horsepower and fuel use and emissions. The main conclusion is that the selection of higher horsepower equipment may lead to lower total equipment costs, fuel use, and emissions for earthwork activities.

Phil Lewis is an Assistant Professor in the School of Civil and Environmental Engineering at Oklahoma State University. His primary area of research is the economic, energy, and environmental impacts of construction

Yongwei Shan is an Assistant Professor in the School of Civil and Environmental Engineering at Oklahoma State University. His primary area of research is characterizing and improving productivity in construction activities.

Apif Hajji, PhD is an Assistant Professor in the Department of Civil Engineering at the State University of Malang in Indonesia. He was a PhD student of Dr. Lewis and graduated in 2013.

Elizabeth Hazzard is an Engineer In Training for Aguirre & Fields in Ft. Worth, TX. She was a MS student of Dr. Lewis and graduated in 2014.




20 Characterizing Equipment Cost, Fuel Use, and Emissions for Earthwork Activities

to forecast the approximate quantity of fuel required and its impact on operating costs. Until recently, most construction estimators seldom concerned themselves with the environmental impact of their equipment and activities, especially air pollutant emissions; however, value systems are changing and paradigms are shifting to include more sustainable approaches to construction. As new environmental regulations, such as cap-and-trade and carbon taxes, appear on the horizon in other industries, construction professionals can no longer afford to disregard the environmental impacts of their work. They must go beyond estimating materials, labor, and equipment to merely determine production and cost.

The objective of this paper is to characterize the theoretical relationships between construction equipment costs, fuel use, and air pollutant emissions. A better understanding of these relationships will enable constructors to make more informed decisions in construction planning, thus leading to more sustainable construction activity. Although there are existing models that estimate emissions inventories of construction equipment, such as the EPA NONROAD model, these tools typically do not address construction costs because their focus is on environmental issues (EPA 2005). Conversely, construction cost estimating tools, such as RS Means, address equipment productivity and costs but not equipment emissions (RS Means 2010). This paper presents a synergistic approach that combines both construction and environmental data to assess the inextricable relationships between equipment costs, fuel use, and emissions.

In order to identify the relationships between equipment costs, fuel use, and emissions, this paper presents a case study of a dozer performing an excavation activity. Mathematical equations were developed to predict the production rate and unit costs of the dozer. A methodology for estimating fuel use and emissions is presented. Important relationships were examined including total cost versus dozing distance; fuel use and emissions versus dozing distance; total cost versus engine horsepower; and fuel use and emissions versus engine horsepower. Each of the relationships was evaluated for sensitivity to soil

type including clay, sand and gravel, sandy clay and loam, and common earth.

CONSTRUCTION EQUIPMENT AND THE ENVIRONMENT

Diesel exhaust is a complex mixture of pollutants and greenhouse gases. Some of these pollutants are regulated by the federal government and some are not. All of these pollutants, however, have an adverse impact on human health and the environment. This section provides a background of diesel exhaust pollution and current strategies aimed at reducing it.

Air Pollutants and Greenhouse Gases

Air pollutants found in diesel exhaust include nitrogen oxides (NOx), particulate matter (PM), hydrocarbons (HC), and carbon monoxide (CO). NOx, PM, and CO are criteria pollutants that are regulated by the Environmental Protection Agency’s National Ambient Air Quality Standards (NAAQS) (EPA 2014a). Although HC is not a criteria pollutant, it is a precursor to ozone (O3) which is a criteria pollutant. Another major constituent of diesel exhaust is carbon dioxide (CO2). CO2 is not considered an air pollutant but it is a greenhouse gas (GHG) that has significant global warming potential. CO2 emissions from transportation sources (including nonroad equipment) account for 32% of CO2 emissions (EPA 2014b). They are not formally regulated but there are many voluntary initiatives aimed at reducing GHG emissions from all sources.

Diesel emissions have numerous impacts on human health and the environment. Diesel exhaust may lead to serious health conditions, including asthma and allergies, and can worsen heart and lung disease, especially in vulnerable populations like children and the elderly. PM and NOx emissions lead to the formation of smog and acid rain which damage plants, animals, crops, and water resources. CO2 is a major GHG emission that leads to climate change, which affects air quality, weather patterns, sea level, ecosystems, and agriculture. Reducing GHG emissions from diesel engines through improved fuel economy and idle reduction strategies can help address climate change, improve the nation’s energy security, and strengthen the economy. Another concern with diesel emissions is



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environmental justice. It is possible that minority and disadvantaged populations receive disproportionate impacts from diesel emissions (EPA 2014c).

Air Pollution Reduction

Reducing air pollution from construction equipment has received much attention in recent years. Perhaps the greatest effort in this regard has been the EPA engine tier regulations. Engine tiers are emissions standards adopted by EPA for all new nonroad diesel engines (EPA 2012). These standards were phased in over time and required all nonroad diesel engine manufacturers to reduce the emission rates of NOx, HC, CO, and PM. CO2 is not a part of these standards. Diesel engines of a specific horsepower rating that are manufactured after a specified year must meet the performance levels specified in that standard. The EPA engine tier classifications include successive Tier 1, Tier 2, Tier 3, Tier 4 Transitional, and Tier 4 Final, which were implemented in a phased sequence from 1996 to 2013. Engines manufactured prior to implementation of the engine tier standards were designated as Tier 0 and do not meet any required emissions regulations.

Although new nonroad diesel engines are much cleaner now, construction equipment can easily remain in use for over 30 years; thus, much of the equipment that is in use today and in the near future may be unregulated or only meet minimum emissions standards. EPA (2014c) recommends many additional air pollution reduction strategies for construction equipment:• Install diesel retrofit devices with verified emissions

reduction technologies;• Maintain, repair, rebuild, or repower existing engines

in equipment;• Replace older vehicles and equipment in the current

fleet;• Use cleaner fuels including natural gas and propane;

and• Improve equipment operational strategies

The focus of this paper is to identify the relationships between construction equipment costs, fuel use, and emissions that will help improve operational strategies for construction equipment and reduce air pollution. Currently, the primary operational strategy for construction equipment is idle reduction. Lewis et al.

(2011; 2012a, b) documented a process for characterizing the impact of idle time and operational efficiency on diesel exhaust emissions from construction equipment. This paper characterizes equipment costs, fuel use, and emissions in order to consider a new pollution reduction strategy – improved activity analysis and equipment selection. This new strategy may be used in conjunction with other strategies to achieve the greatest pollution reduction results in construction.

METHODOLOGYIn order to assess the relationships between equipment costs, fuel use, and emissions, a simple earthwork activity involving one dozer performing bulk excavation was selected for a case study. The data for this activity was collected from RS Means Building Construction Cost Data 2010 (RS Means 2010), Item 31 23 16.46 Excavating, Bulk, Dozer. This item provides 72 total observations of dozer excavation activity based on six different engine horsepower (hp) ratings (80, 105, 200, 300, 460, and 700), three different haul distances (50’, 150’, and 300’), and four different soil types (sand & gravel, sandy clay & loam, common earth, and clay). The case study presents results for the carbon footprint of the activity based on CO2 emissions. Although a similar approach may be used to estimate quantities of other pollutants, only the results for CO2 are presented for brevity.

Estimating Equipment Productivity and Costs

Using the data from RS Means, models for estimating equipment productivity (P) and unit cost (UC) were developed through multiple linear regression (MLR) analysis. Similar studies (Sonmez 2004; Seung and Sinha 2006) have been successful at utilizing this deterministic statistical approach to estimate other parameters in construction activities. The MLR models for P and UC were expressed mathematically in the form of

Using the data from RS Means, models for estimating equipment productivity (P) and unit cost (UC) were developed through multiple linear regression (MLR) analysis. Similar studies (Sonmez 2004; Seung and Sinha 2006) have been successful at utilizing this deterministic statistical approach to estimate other parameters in construction activities. The MLR models for P and UC were expressed mathematically in the form of Y = β0 + β1X1 + … + βp-1Xn , where Y is the response variable (either P or UC), X are the predictor variables (horsepower rating, haul distance, and soil type), and β are coefficients. The predicted values for UC were expressed in terms of dollars per bank cubic yard ($/BCY) and in terms of bank cubic yards per hour (BCY/hr) for P. The purpose of the MLR models was to estimate continuous values for UC and P for the dozer based on engine horsepower ratings between 80 and 700 hp and dozing distances between 50 and 300 feet; therefore, estimates for UC and P were not limited to the values found in the RS Means tables for the specified predictor variables. UC for the 72 observations found in RS Means ranged from $1.30/BCY to $18.45/BCY and included the direct costs of labor and equipment plus overhead and profit for the performing contractor. These values are based on national averages and are unadjusted for time and location. RS Means also provided daily output (BCY/day) values for P for the bulk excavation activity. These values ranged from 65 BCY/day to 3,500 BCY/day and were converted to hourly production rates (BCY/hr) based on an eight hour work day under normal conditions. The MLR models address sensitivity to four different soil types including sand and gravel, sandy clay and loam, common earth, and clay. In order to estimate the equipment total cost (TC) for the bulk excavation activity, it was necessary to know the quantity of work (Q) to be performed. Q may typically be derived by a quantity takeoff of the project plans and specifications. In some cases, such as publicly-owned highway construction projects, Q may be provided by the owner in the list of bid items as part of a unit price contract. For the case study, it was assumed Q = 1,000 BCY. Equation 1 was used to estimate TC to perform the bulk excavation activity.

TC = UC x Q Equation 1

where:

TC = equipment total cost ($) UC = equipment unit cost ($/BCY) Q = quantity of work (BCY)

Estimating Equipment Fuel Use and Emissions In order to estimate the total fuel use (F) and total CO2 emissions (E) of the dozer, it was first necessary to estimate the duration of the activity. Activity duration (D) was determined by Equation 2.

D = Equation 2

where:

, where Y is the response variable (either P or UC), X are the predictor variables (horsepower rating, haul distance, and soil type), and



where:



D = Equation 2

where:

are coefficients. The predicted values for UC were expressed in terms of dollars per bank cubic yard ($/BCY) and in terms of bank cubic yards per hour (BCY/hr) for P.




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The purpose of the MLR models was to estimate continuous values for UC and P for the dozer based on engine horsepower ratings between 80 and 700 hp and dozing distances between 50 and 300 feet; therefore, estimates for UC and P were not limited to the values found in the RS Means tables for the specified predictor variables. UC for the 72 observations found in RS Means ranged from $1.30/BCY to $18.45/BCY and included the direct costs of labor and equipment plus overhead and profit for the performing contractor. These values are based on national averages and are unadjusted for time and location. RS Means also provided daily output (BCY/day) values for P for the bulk excavation activity. These values ranged from 65 BCY/day to 3,500 BCY/day and were converted to hourly production rates (BCY/hr) based on an eight hour work day under normal conditions. The MLR models address sensitivity to four different soil types including sand and gravel, sandy clay and loam, common earth, and clay.

In order to estimate the equipment total cost (TC) for the bulk excavation activity, it was necessary to know the quantity of work (Q) to be performed. Q may typically be derived by a quantity takeoff of the project plans and specifications. In some cases, such as publicly-owned highway construction projects, Q may be provided by the owner in the list of bid items as part of a unit price contract. For the case study, it was assumed Q = 1,000 BCY. Equation 1 was used to estimate TC to perform the bulk excavation activity.

TC = UC x Q Equation 1where:TC = equipment total cost ($)UC = equipment unit cost ($/BCY)Q = quantity of work (BCY)

Estimating Equipment Fuel Use and Emissions

In order to estimate the total fuel use (F) and total CO2 emissions (E) of the dozer, it was first necessary to estimate the duration of the activity. Activity duration (D) was determined by Equation 2.



where:



D = Equation 2

where: Equation 2

where:D = activity duration (hr)Q = quantity of work (BCY)P = production rate (BCY/hr)

Equation 3 was used to estimate the total fuel use (F) for the dozer performing the bulk excavation activity. Equation 2 is based on the common equipment fuel consumption equation found in many construction textbooks, including Peurifoy et al. (2011), Peurifory and Oberlender (2014), and Nichols and Day (2005). In order to account for the fact that construction equipment rarely operates at maximum engine load for sustained periods, an engine load factor (LF) was applied to adjust for idling and partial engine load activity. The appropriate engine load factor for any given activity may be highly subjective unless specific conditions are known; thus, for the case study LF = 0.59. This value is based on the engine load factor for dozers used by the EPA NONROAD model (EPA 2005). Furthermore, since the case study specified that a 200 hp dozer was used for the bulk excavation activity, HP = 200. Values for D are variable based on P.

D = activity duration (hr) Q = quantity of work (BCY) P = production rate (BCY/hr)


F = x LF x HP x D Equation 3

where:

F = total fuel use in gallons (gal) LF = engine load factor (%) HP = engine rated horsepower (hp) D = activity duration (hr)

Equation 4 was used to estimate the total CO2 emissions (E) for bulk excavation activity. Since CO2 emissions are highly correlated to fuel use (approximately 99% of the carbon in diesel fuel is emitted as CO2), a simple conversion factor is all that is needed to estimate E. This conversion factor was available from EPA (2004) and has been confirmed in field tests conducted by Frey et al. (2010). For diesel fuel, approximately 22.23 pounds of CO2 are emitted per gallon of diesel fuel consumed.

E = F x Equation 4

where:

E = total CO2 emissions in pounds (lb) F = total fuel use (gallons)

RESULTS This section presents the results and key findings of the case study analysis of the dozer bulk excavation activity. The MLR models for estimating P and UC are presented. Relationships for TC, F, and E versus soil type, dozing distance, and engine rated horsepower are represented graphically. Equipment Productivity, Costs, Fuel Use, and Emissions

Equation 3where:F = total fuel use in gallons (gal)LF = engine load factor (%)HP = engine rated horsepower (hp)D = activity duration (hr)


D = activity duration (hr) Q = quantity of work (BCY) P = production rate (BCY/hr)


F = x LF x HP x D Equation 3

where:

F = total fuel use in gallons (gal) LF = engine load factor (%) HP = engine rated horsepower (hp) D = activity duration (hr)


E = F x Equation 4

where:

E = total CO2 emissions in pounds (lb) F = total fuel use (gallons)

RESULTS This section presents the results and key findings of the case study analysis of the dozer bulk excavation activity. The MLR models for estimating P and UC are presented. Relationships for TC, F, and E versus soil type, dozing distance, and engine rated horsepower are represented graphically. Equipment Productivity, Costs, Fuel Use, and Emissions

Equation 4where:E = total CO2 emissions in pounds (lb)F = total fuel use (gallons)




23

RESULTS

This section presents the results and key findings of the case study analysis of the dozer bulk excavation activity. The MLR models for estimating P and UC are presented. Relationships for TC, F, and E versus soil type, dozing distance, and engine rated horsepower are represented graphically.

Equipment Productivity, Costs, Fuel Use, and Emissions

The MLR approach was successful in providing useable models for predicting P and UC for the dozer bulk excavation activity. Based on the results of the original regression analysis, the plot of residuals against the predicted values showed evidence of unequal variance. The unequal error variances and non-normality of the error terms frequently appear together. To remedy the non-normality in the data, a Box-Cox transformation on each response variables was performed (Minitab 2014). Based on the transformed regression equations, R2 = 0.93 for P (Equation 5) and R2 = 0.89 for UC (Equation 6), indicating that approximately 90% of the variability in the data was accounted for by the model equations. For both models, all parameters (including the intercept) had p-values < 0.0001 and were considered statistically significant. The following models for P and UC were produced:

P = (2.143 + 0.00152X1 – 0.0025X2 + 0.279X3 + 0.261X4 + 0.206X5)5 Equation 5

ln (UC) = 1.188 – 0.00085X1 + 0.0053X2 – 0.595X3 – 0.563X4 – 0.453X5 Equation 6

where:P = production rate (BCY/hr)UC = unit cost ($/BCY)X1 = rated engine horsepower (hp)X2 = hauling distance (feet)X3 = sand and gravel soil typeX4 = sandy clay and loam soil typeX5 = common earth soil type

Rated engine horsepower (X1) and hauling distance (X2) are project-specific variables that are usually known by the estimator. Soil types (X3, X4, and X5) are represented as indicator variables with a value of one if the soil type is present or zero if it is not. The base case soil type is clay, which is not represented in the model by a predictor variable. Only one soil type was assumed to be present for the activity. The estimator typically knows the soil type for the proposed activity.

Table 1 provides results for P, UC, D, TC, F, and E. These results are based on Equations 1 through 6. Results for all four soil types and haul distances ranging from 50 to 300 feet are presented to show the sensitivity to changes in site conditions.

The MLR approach was successful in providing useable models for predicting P and UC for the dozer bulk excavation activity. Based on the results of the original regression analysis, the plot of residuals against the predicted values showed evidence of unequal variance. The unequal error variances and non-normality of the error terms frequently appear together. To remedy the non-normality in the data, a Box-Cox transformation on each response variables was performed (Minitab 2014). Based on the transformed regression equations, R2 = 0.93 for P (Equation 5) and R2 = 0.89 for UC (Equation 6), indicating that approximately 90% of the variability in the data was accounted for by the model equations. For both models, all parameters (including the intercept) had p-values < 0.0001 and were considered statistically significant. The following models for P and UC were produced:

P = (2.143 + 0.00152X1 – 0.0025X2 + 0.279X3 + 0.261X4 + 0.206X5)5 Equation 5

ln (UC) = 1.188 – 0.00085X1 + 0.0053X2 – 0.595X3 – 0.563X4 – 0.453X5 Equation 6

where:

P = production rate (BCY/hr) UC = unit cost ($/BCY) X1 = rated engine horsepower (hp) X2 = hauling distance (feet) X3 = sand and gravel soil type X4 = sandy clay and loam soil type X5 = common earth soil type

Rated engine horsepower (X1) and hauling distance (X2) are project-specific variables that are usually known by the estimator. Soil types (X3, X4, and X5) are represented as indicator variables with a value of one if the soil type is present or zero if it is not. The base case soil type is clay, which is not represented in the model by a predictor variable. Only one soil type was assumed to be present for the activity. The estimator typically knows the soil type for the proposed activity. Table 1 provides results for P, UC, D, TC, F, and E. These results are based on Equations 1 through 6. Results for all four soil types and haul distances ranging from 50 to 300 feet are presented to show the sensitivity to changes in site conditions.

Table 1. Activity Estimates for Q = 1,000 BCY and HP = 200 hp

Distance (ft)

Soil Type

P (BCY/hr)

UC ($/BCY)

D (hr)

TC ($)

F (gal)

E (lbs)

50 Sand & Gravel 117 1.99 8.5 1,990 40 897 50 Sandy Clay & Loam 113 2.05 8.8 2,050 42 929 50 Common Earth 102 2.30 9.8 2,300 46 1,030 50 Clay 66 3.61 15 3,610 71 1,580

150 Sand & Gravel 71 3.39 14 3,390 66 1,480 150 Sandy Clay & Loam 68 3.48 15 3,480 71 1,580 150 Common Earth 60 3.90 17 3,900 80 1,790 150 Clay 38 6.14 27 6,140 127 2,850 300 Sand & Gravel 30 7.50 34 7,500 160 3,590 300 Sandy Clay & Loam 28 7.71 35 7,710 165 3,690 300 Common Earth 25 8.65 41 8,650 194 4,330 300 Clay 14 13.60 73 13,600 345 7,700

Table 1. Activity Estimates for Q = 1,000 BCY and HP = 200 hp




24

Trends in Equipment Costs, Fuel Use, and Emissions

Based on the results in Table 1, there is an inverse relationship between P and the parameters UC, D, TC, F, and E; that is, as P decreases, the other parameters increase. P also decreases with the excavation resistance based on soil type – sand and gravel has the highest production rate whereas clay has the lowest. Likewise, UC, D, TC, F, and E all increase as the soil resistance increases. Furthermore, for a specific soil type, P decreases as dozing distance increases; thus, UC, D, TC, F, and E all increase as the haul distance increases.

Economic impacts of an activity or project, particularly TC, have long been the primary concern for construction managers and estimators in decision making. Figure 1 shows how equipment TC relates to dozing distance for the case study activity. For each soil type, TC increases as dozing distance increases. The TC curves for each soil type has the same general shape and there is little difference in TC with respect to dozing distance for sand and gravel, sandy clay and loam, and common earth; there is virtually no difference in TC for sand and gravel and sandy clay and loam. The soil type with the highest TC based on dozing distance is clay. Although this relationship is somewhat intuitive based on the presumption that greater work effort leads to greater costs, it is a fundamental step towards assessing the interrelationships between costs, fuel use, and emissions. Furthermore, Figure 1 represents TC based on factors that the performing contractor has little-to-no control over. For example, a construction planner has some control in determining the optimum dozing distance based on site conditions but no control over the soil type at the activity site.

Figure 1. Total Cost versus Dozing Distance

Constructors are no longer beholden only to the economic impacts of their work. They must now concern themselves with sustainability issues, such as energy and environmental impacts. Figure 2 shows the relationship between CO2 emissions (E) and fuel use (F) based on dozing distance for the case study. Similarly to TC for this case study, there is little difference in E and F for sand and gravel, sandy clay and loam, and common earth and essentially no difference between sand and gravel and sandy clay and loam. Clay has the highest E and F for the case study. The curves for E and F versus dozing distance are nearly identical in shape to the curves for TC versus dozing distance; only the values and units on the vertical axes have changed. Figures 1 and 2, therefore represent the close relationships between the economic, energy, and environmental impacts of the case study, particularly with regard to factors over which the contractor has little control.

Figure 2. Fuel Use and Emissions versus Dozing Distance

Trends in Equipment Costs, Fuel Use, and Emissions Based on the results in Table 1, there is an inverse relationship between P and the parameters UC, D, TC, F, and E; that is, as P decreases, the other parameters increase. P also decreases with the excavation resistance based on soil type – sand and gravel has the highest production rate whereas clay has the lowest. Likewise, UC, D, TC, F, and E all increase as the soil resistance increases. Furthermore, for a specific soil type, P decreases as dozing distance increases; thus, UC, D, TC, F, and E all increase as the haul distance increases. Economic impacts of an activity or project, particularly TC, have long been the primary concern for construction managers and estimators in decision making. Figure 1 shows how equipment TC relates to dozing distance for the case study activity. For each soil type, TC increases as dozing distance increases. The TC curves for each soil type has the same general shape and there is little difference in TC with respect to dozing distance for sand and gravel, sandy clay and loam, and common earth; there is virtually no difference in TC for sand and gravel and sandy clay and loam. The soil type with the highest TC based on dozing distance is clay. Although this relationship is somewhat intuitive based on the presumption that greater work effort leads to greater costs, it is a fundamental step towards assessing the interrelationships between costs, fuel use, and emissions. Furthermore, Figure 1 represents TC based on factors that the performing contractor has little-to-no control over. For example, a construction planner has some control in determining the optimum dozing distance based on site conditions but no control over the soil type at the activity site.

Figure 1. Total Cost versus Dozing Distance

Constructors are no longer beholden only to the economic impacts of their work. They must now concern themselves with sustainability issues, such as energy and environmental impacts. Figure 2 shows the relationship between CO2 emissions (E) and fuel use (F) based on dozing distance for the case study. Similarly to TC for this case study, there is little difference in E and F for sand and gravel, sandy clay and loam, and common earth and essentially no difference

between sand and gravel and sandy clay and loam. Clay has the highest E and F for the case study. The curves for E and F versus dozing distance are nearly identical in shape to the curves for TC versus dozing distance; only the values and units on the vertical axes have changed. Figures 1 and 2, therefore represent the close relationships between the economic, energy, and environmental impacts of the case study, particularly with regard to factors over which the contractor has little control.

Figure 2. Fuel Use and Emissions versus Dozing Distance

Although the constructor has no control over soil type and perhaps only minimal control over dozing distance, there are some strategic choices to be made. For instance, the constructor may be able to choose the size of the dozer to complete the bulk excavation activity. Typically, a dozer with higher engine horsepower will have higher associated costs, consume more fuel, and thus emit more pollution; however, the higher horsepower rating of the machine generally enables a higher production rate and therefore a lower overall activity duration. According to Table 1, as P increases TC, F, and E decrease. The impacts of engine size are examined in Figures 3 and 4. Figures 3 and 4 present results for various size dozers ranging from 80 to 700 hp but with a constant dozing distance of 150 feet for each soil type. Figure 3 indicates a negative relationship between TC and HP; that is, as the rated horsepower of the dozer increases, TC decreases. The shape of the cost curves is the same for each soil type with clay having the highest overall TC. Once again, there is little difference between sand and gravel, sandy clay and loam, and common earth and basically no difference between sand and gravel and sandy clay and loam.




25

Although the constructor has no control over soil type and perhaps only minimal control over dozing distance, there are some strategic choices to be made. For instance, the constructor may be able to choose the size of the dozer to complete the bulk excavation activity. Typically, a dozer with higher engine horsepower will have higher associated costs, consume more fuel, and thus emit more pollution; however, the higher horsepower rating of the machine generally enables a higher production rate and therefore a lower overall activity duration. According to Table 1, as P increases TC, F, and E decrease. The impacts of engine size are examined in Figures 3 and 4.

Figures 3 and 4 present results for various size dozers ranging from 80 to 700 hp but with a constant dozing distance of 150 feet for each soil type. Figure 3 indicates a negative relationship between TC and HP; that is, as the rated horsepower of the dozer increases, TC decreases. The shape of the cost curves is the same for each soil type with clay having the highest overall TC. Once again, there is little difference between sand and gravel, sandy clay and loam, and common earth and basically no difference between sand and gravel and sandy clay and loam.

Figure 3. Total Cost (TC) versus Engine Horsepower (HP)

Figure 4 presents several interesting findings related to fuel consumption and emissions based on the horsepower rating of the dozer. Initially, F and E increase sharply as the horsepower rating increases and then begins to decrease; hence, the relationship takes the shape of an inverted u-curve. The inverted u-curves indicate that F and E increase as horsepower increases but only to a certain extent - in this case about 300 hp. At that point, F and E begin to decrease

as horsepower increases. The inverted u-curves show that a specific quantity of fuel use and emissions for a given soil type may occur at two different horsepower ratings. For example, when excavating in clay, a 100 hp and 700 hp bulldozer will both consume approximately 100 gallons of fuel and emit about 2,000 pounds of CO2; however, according to Figure 3, TC to complete the activity is approximately $6,700 for the 100 hp bulldozer and $4,000 for the 700 hp machine, which is an approximate 40% difference in cost. It can be determined, therefore, that a substantially lower TC can be achieved by using a larger dozer while still having the same F and E of a smaller dozer. This points towards a conclusion that selecting equipment based on lower economic impact may also lead to lower energy and environmental impacts.

Figure 4. Fuel use (F) and Emissions (E) versus Engine Horsepower

CONCLUSIONS AND RECOMMENDATIONS

This paper presents the results of a case study that examines the relationships between costs, fuel use, and emissions of a dozer performing a common excavation activity. The methodologies presented here can be used along with other common estimating approaches to gain an overall understanding of the economic, energy, and environmental footprint for a construction activity and ultimately an entire project. Although there are already means and methods for estimating production, costs, and emissions for construction equipment, there currently is not a proven methodology for doing all of these simultaneously. It is recommended that this methodology be used to develop a framework for evaluating sustainability metrics of construction projects including economic, energy, and environmental impacts.

Figure 3. Total Cost (TC) versus Engine Horsepower (HP)

Figure 4 presents several interesting findings related to fuel consumption and emissions based on the horsepower rating of the dozer. Initially, F and E increase sharply as the horsepower rating increases and then begins to decrease; hence, the relationship takes the shape of an inverted u-curve. The inverted u-curves indicate that F and E increase as horsepower increases but only to a certain extent - in this case about 300 hp. At that point, F and E begin to decrease as horsepower increases. The inverted u-curves show that a specific quantity of fuel use and emissions for a given soil type may occur at two different horsepower ratings. For example, when excavating in clay, a 100 hp and 700 hp bulldozer will both consume approximately 100 gallons of fuel and emit about 2,000 pounds of CO2; however, according to Figure 3, TC to complete the activity is approximately $6,700 for the 100 hp bulldozer and $4,000 for the 700 hp machine, which is an approximate 40% difference in cost. It can be determined, therefore, that a substantially lower TC can be achieved by using a larger dozer while still having the same F and E of a smaller dozer. This points towards a conclusion that selecting equipment based on lower economic impact may also lead to lower energy and environmental impacts.

Figure 4. Fuel Use (F) and Emissions (E) versus Engine Horsepower

CONCLUSIONS AND RECOMMENDATIONS This paper presents the results of a case study that examines the relationships between costs, fuel use, and emissions of a dozer performing a common excavation activity. The methodologies presented here can be used along with other common estimating approaches to gain an overall understanding of the economic, energy, and environmental footprint for a construction activity and ultimately an entire project. Although there are already means and methods for estimating production, costs, and emissions for construction equipment, there currently is not a proven methodology for doing all of these simultaneously. It is recommended that this methodology be used to develop a framework for evaluating sustainability metrics of construction projects including economic, energy, and environmental impacts. Multiple linear regression was an effective tool for estimating production rates and unit costs for the dozer excavation activity. The MLR models for productivity and unit cost accounted for approximately 90% of the variability in the data. Although there are construction equipment handbooks and estimating guides that provide some of this data, the MLR models allow the user to estimate production rates and unit costs over a range of values for horsepower, haul distance, and material type – including those that may not be specifically listed in the handbooks or guides. It is recommended to develop models for other equipment and activities, such as bulk excavation with a scraper, trenching activities with excavators, and loader and truck hauling operations. Based on the results of the case study, several trends were identified that are related to the economic, energy, and environmental impacts of the dozer excavation activity. For example, total cost, total fuel use, and total CO2 emissions all increase as the excavation resistance based on soil type increases. For instance, sand and gravel had the lowest equipment total cost, fuel use, and emissions, followed by sandy clay and loam, and common earth. Clay distinctly had the highest equipment total cost, fuel use, and emissions among the evaluated soil types. This is




26

Multiple linear regression was an effective tool for estimating production rates and unit costs for the dozer excavation activity. The MLR models for productivity and unit cost accounted for approximately 90% of the variability in the data. Although there are construction equipment handbooks and estimating guides that provide some of this data, the MLR models allow the user to estimate production rates and unit costs over a range of values for horsepower, haul distance, and material type – including those that may not be specifically listed in the handbooks or guides. It is recommended to develop models for other equipment and activities, such as bulk excavation with a scraper, trenching activities with excavators, and loader and truck hauling operations.

Based on the results of the case study, several trends were identified that are related to the economic, energy, and environmental impacts of the dozer excavation activity. For example, total cost, total fuel use, and total CO2 emissions all increase as the excavation resistance based on soil type increases. For instance, sand and gravel had the lowest equipment total cost, fuel use, and emissions, followed by sandy clay and loam, and common earth. Clay distinctly had the highest equipment total cost, fuel use, and emissions among the evaluated soil types. This is likely due to the fact that as the soil type becomes more difficult to excavate, the production rate of the dozer decreases and the total activity duration increases; thus, more fuel is consumed and more CO2 is emitted. Likewise, the production rate of the dozer decreases as the haul distance increases for a given dozer; ultimately, this results in higher total costs, higher fuel use, and higher CO2 emissions for the case study activity. It is highly recommended that the trends identified here be compared and contrasted to those for other equipment and activities to identify similarities and differences.

The case study revealed a negative relationship between total cost and the horsepower rating of the dozer; that is, the total cost of the activity decreased as the rated horsepower increased. With regard to fuel use and emissions, however, the relationship with horsepower takes the form of an inverted u-curve. The main conclusion here is that fuel use and emissions will increase as horsepower increases but only to a

certain point - then fuel use and emissions begin to decrease as horsepower continues to increase. This inverted u-curve relationship proves to be a useful tool for selecting the appropriate equipment engine size for an activity. Once the horsepower rating that produces the maximum fuel use and emissions is established, equipment managers should select a machine with a higher horsepower rating because it will likely produce lower fuel use and emissions values while also lowering the equipment total cost of the activity. Based on these results, it is recommended that equipment mangers consider the proposition that selecting equipment that have the lowest overall total activity cost may also yield the lowest fuel use and emissions for the activity.

More analysis of the data is needed to refine the results presented here and identify other trends. Additionally, these results - and eventually results for other activities and equipment, - should be validated by collecting and analyzing fuel use and emissions data from in-use equipment on actual job sites. In the absence of actual field data, other data sources such as the Caterpillar Performance Handbook (CAT 2014) may be used to validate the results presented in the case study and also develop new models for productivity and equipment unit cost. Likewise, future research should also focus on collecting productivity and unit cost data to accurately reflect the economic, energy, and environmental impact of other construction activities that utilize diesel powered construction equipment.

Although carbon footprints are a major concern for environmental impacts of construction activities, other air pollutants should be examined as well. These pollutants include HC, CO, NOx, and PM; the latter two are of particular interest for diesel-powered construction equipment because of their high emission rates compared to other mobile sources. Since these pollutants are the focus of the EPA Engine Tier emissions standards, including them in future analyses adds another level of complexity. It is recommended that emissions estimates account for each of the Tier 0 through Tier 4 Final standards. Including these pollutants in future analyses will enhance the overall picture of the environmental impact of construction activities.




27

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Environmental Protection Agency, www.epa.gov/climatechange/ghgemissions/gases/co2. Information viewed on October 27, 2014.

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28

INTRODUCTIONAs population and resource consumption continue to grow, global interest in conservation and sustainable development continues to intensify. In the United States, buildings represent 40% of energy consumption and 15% of water use (USGBC 2012). As the world’s population increases, and concern regarding pollution and resource use continues to heighten, an ever increasing number of individuals, businesses, and institutions are adopting sustainable building practices (WGBC 2013). Nationally there is growing recognition that sustainable building practices, or green building, can reduce building energy use by up to 50%, lower water consumption by 40%, and reduce solid waste by 70% (Galayda and Yudelson 2010).

Figure 1: Green Building Industry

The growth in building green has been phenomenal. In the US, the green building market is projected to experience greater than a 2000% growth rate over 15 years. As depicted in Figure 1, green building has grown from $10 billion in 2005 to a projected volume of $254 billion by 2020 (McGraw-Hill 2012, Earth911 2013). Within the next several years green building is

Analysis of Green Building Initiatives on U.S. University Campuses

Dennis C. Bausman, PhD, FAIC, CPCClemson University | [email protected]

Ben Mueller, MCSM Clemson University

ABSTRACT: As population expands and resource consumption grows, interest in sustainable practices continues to intensify. Universities and colleges in the U.S. have been leading the trend toward building certification and green initiatives to reduce energy consumption, lower water consumption, and recycle solid waste. This study investigates the extent to which green practices are implemented on new construction and the renovation of existing building stock on university campuses across the United States. The study also examines the financial analysis techniques institutions use to assess and prioritize green initiatives on new and existing facilities. The population selected for this study was two hundred facility managers at universities and colleges in the United States. The findings are that universities are committed to green building certification and practices that reduce energy and water consumption, but seldom support solar or geothermal initiatives which could provide onsite renewable energy sources for the university. Most institutions have sufficient funding for green initiatives when constructing new facilities, but funding shortfalls are common for the renovation of existing buildings. Universities typically evaluate the long-term financial impact of green initiatives utilizing life-cycle analysis to calculate a payback period and they prioritize green initiatives based upon operational savings.

Dennis C. Bausman is a Professor and Endowed Faculty Chair in the Construction Science and Management Department at Clemson University. He also serves on the Board of Governors for the Construction Certification Commission.

Ben Mueller is a graduate student in the Masters of Construction Science and Management program at Clemson University.


5 0 %, lower wat e r consumpt ion by 4 0 %, and reduce solid was t e by 7 0 % (Galayda and Yude lson 2 0 1 0 ) .

Fig ure 1 : Gre e n Build ing Ind us t ry The growt h in build ing green has been phenomenal. In t he US, t he green build ing marke t is projec t ed t o expe rience great e r t han a 2 0 0 0 % growt h ra t e ove r 1 5 years . As depic t ed in Figure 1 , g reen build ing has grown from $ 1 0 billion in 2 0 0 5 t o a projec t ed volume of $ 2 5 4 billion by 2 0 2 0 (McGraw-Hill 2 0 1 2 , Eart h9 1 1 2 0 1 3 ) . Wit hin t he next seve ral years green build ing is e s t imat ed t o comprise up t o 4 8 % of new non-re s ident ia l cons t ruct ion and it s share of t he build ing re t rofit marke t is expect ed t o rise t o 2 0 -3 0 % in t he Unit ed St at e s (USGBC 2 0 1 2 ) . Globally, g reen build ing has deve loped int o a t rillion dollar indus t ry (WGBC 2 0 1 3 ) . Unive rs it ie s (and colleges ) have been at t he fore front of t he t rend t oward sus t a inable init ia t ive s and have one of t he highes t concent rat ions of green build ings (USGBC 2 0 1 2 , Doughe rt y 2 0 1 0 ) . During t he pe riod from 2 0 0 2 t o 2 0 0 9 ins t it ut ions of highe r le arning comprised 1 5 % of a ll g reen ce rt ified build ing s t ock (Galayda and Yude lson 2 0 1 0 ) and in 2 0 1 1 t hey account ed for 4 0 % of a ll new applicat ions for LEED ce rt ified projec t s (Yude lson and Breunig 2 0 1 1 ) . By 2 0 1 2 almos t seven hundred (7 0 0 ) le ade rs of US unive rs it ie s and colleges had s igned the American College and University Presidents’ Climate Commitment. Wit h t he ir s ignat ure unive rs it y pre s ident s commit t ed t he ir ins t it ut ions t o a) deve lopment of a comprehens ive p lan t o achieve c limat e neut ralit y, and b) init ia t e t angible ac t ion t o reduce greenhouse gase s by t aking ac t ion on t wo or more front s inc luding build ing green, purchas ing ene rgy-e ffic ient product s , encouraging public t ransport a t ion, reducing ene rgy consumpt ion, and/ or was t e reduct ion. Wit h t he ir commit ment t he se ins t it ut ional le ade rs became t he firs t indus t ry sec t or wit h a p lan t o achieve c limat e neut ralit y (Mart in e l a l 2 0 1 2 ) . The re are a number of fac t ors t hat are driving t he g lobal t rend t oward green build ing . John Elkingt on groups t he drive rs int o t hree primary cons ide rat ions . In

0

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200

250

300

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ions

* projected




29Analysis of Green Building Initiatives on U.S. University Campuses

estimated to comprise up to 48% of new non-residential construction and its share of the building retrofit market is expected to rise to 20-30% in the United States (USGBC 2012). Globally, green building has developed into a trillion dollar industry (WGBC 2013).

Universities (and colleges) have been at the forefront of the trend toward sustainable initiatives and have one of the highest concentrations of green buildings (USGBC 2012, Dougherty 2010). During the period from 2002 to 2009 institutions of higher learning comprised 15% of all green certified building stock (Galayda and Yudelson 2010) and in 2011 they accounted for 40% of all new applications for LEED certified projects (Yudelson and Breunig 2011). By 2012 almost seven hundred (700) leaders of US universities and colleges had signed the American College and University Presidents’ Climate Commitment. With their signature university presidents committed their institutions to a) development of a comprehensive plan to achieve climate neutrality, and b) initiate tangible action to reduce greenhouse gases by taking action on two or more fronts including building green, purchasing energy-efficient products, encouraging public transportation, reducing energy consumption, and/or waste reduction. With their commitment these institutional leaders became the first industry sector with a plan to achieve climate neutrality (Martin el al 2012).

There are a number of factors that are driving the global trend toward green building. John Elkington groups the drivers into three primary considerations. In 1994 he developed a framework to categorize the benefits of sustainable building practices that he labeled the ‘Triple Bottom Line’. He purported that development decisions required a balance of economic, social, and environmental considerations to optimize outcome. Elkington’s decision framework suggests that ‘profit, people, and the planet’ be given equal consideration when evaluating sustainable building options (Elkington 1997). However, because of different financial timeframes, the difficulty of assigning value to each variable, and varying benefactors for each leg of his evaluation framework, it is often difficult to establish an equitable balance (WGBC 2013).

This challenge, coupled with the financial realities of the marketplace, has shifted the balance toward economic considerations as evidenced by McGraw-Hill industry studies in 2009 and 2012. In their 2009 study the top driver for going green was ‘doing the right thing’. Three years later, a 2012 study found that business considerations – client and market demand – were the primary reasons that owners were building green. Investment in sustainable initiatives was expected to provide business benefits by lowering operating costs and/or increasing building value (McGraw-Hill 2013). “The cost savings that green buildings produce over time, along with reduced environmental impacts, are the primary drivers behind the green building trend” (Galayda and Yudelson 2010, p2) and studies have shown that building green does have financial benefits. The World Green Building Council submits that there is a ‘compelling business case’ for going green. The Council purports that going green increases building sales and/or rental value, raises worker productivity, and reduces operating cost (WGBC 2013).

A recent study also found that economic considerations play a key role for implementation of sustainable building practices at universities and colleges in the United States. A 2014 study involving major institutions of higher learning found that economic and occupant considerations were the primary factors universities and colleges considered when evaluating green building alternatives. Economic and user concerns took precedence over social and environmental considerations during facility design and development (Bausman et.al 2014).

But if economic considerations drive the process, what are considered to be good investments and how are these decisions being made by leadership of U.S. universities and colleges? What sustainable building practices for both new buildings, and retrofits for existing, are viewed as good investments? Do universities and colleges have a systematic process to assess the financial investment in sustainable building practices? What process, if any, do they utilize to perform a financial analysis to evaluate the return and /or payback of green initiatives?



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STUDY OBJECTIVE AND METHODOLOGYStudy Objective

This study investigates the green initiatives universities and colleges are implementing for design and construction of both new buildings and the retrofitting, or renovation, of existing facilities on campus. This study will also examine the process which universities and colleges in the United States use to evaluate investment in green initiatives.

Population and Sample Selection

The population selected for this study was facility managers at universities and colleges in the United States. The sampling frame was APPA – Leadership in Educational Facilities membership. APPA is a professional organization engaged in the field of educational facilities management and its membership represents a broad cross-section of educational institutions across the United States. Four institutions were randomly selected from each state creating a sample size of 200. Survey Questionnaire

A detailed self-administered questionnaire containing seventy-five (75) questions was developed and distributed to the selected sample. The questionnaire consisted of four primary sections. The first section of the questionnaire solicited general information such as location, size, and building certification history for the institution. The second section asked how often their institution incorporated various green building practices on both new and renovated facilities. The next section examined university leadership and support for green initiatives. The final sections of the questionnaire investigated the financial analysis process they used to evaluate investments in green building initiatives. The general information collected in the first section of the questionnaire provided nominal data. Questions and response options for the remaining sections were typically structured to provide interval data using a 5-point Likert scale.

The lead facility manager at each institution in the sample was mailed a hardcopy of the questionnaire,

along with a cover letter, which provided a link for online completion of the survey if desired by the respondent. By the response cutoff date, fifty-two (52) usable surveys were received yielding a response rate of twenty-six percent (26%).

Data Analysis

Survey responses were subjected to statistical means testing using a confidence level of 95%. In addition, t-tests with an

S urv e y Que s t io nna ire A de t ailed se lf-adminis t e red ques t ionnaire cont aining sevent y-five (7 5 ) ques t ions was deve loped and dis t ribut ed t o t he se lec t ed sample . The ques t ionnaire cons is t ed of four primary sec t ions . The firs t s ec t ion of t he ques t ionnaire so lic it ed gene ral informat ion such as locat ion, s ize , and build ing ce rt ificat ion his t ory for t he ins t it ut ion. The second sec t ion asked how oft en t he ir ins t it ut ion incorporat ed various green build ing prac t ice s on bot h new and renovat ed fac ilit ie s . The next sec t ion examined unive rs it y le ade rship and support for green init ia t ive s . The final sec t ions of t he ques t ionnaire inves t igat ed t he financial analys is process t hey used t o evaluat e inves t ment s in green build ing init ia t ive s . The gene ral informat ion collec t ed in t he firs t s ec t ion of t he ques t ionnaire provided nominal dat a . Ques t ions and re sponse opt ions for t he remaining sec t ions we re t ypically s t ruc t ured t o provide int e rval dat a us ing a 5 -point Like rt s cale . The le ad fac ilit y manage r a t e ach ins t it ut ion in t he sample was mailed a hardcopy of t he ques t ionnaire , a long wit h a cove r le t t e r, which provided a link for online comple t ion of t he survey if de s ired by t he re spondent . By t he re sponse cut off dat e , fift y-t wo (5 2 ) usable surveys we re rece ived yie ld ing a re sponse ra t e of t went y-s ix pe rcent (2 6 %). Da t a Ana ly s is Survey re sponses we re subjec t ed t o s t a t is t ical means t e s t ing us ing a confidence leve l of 9 5 %. In addit ion, t -t e s t s wit h an σ = .0 5 (as suming unequal variances ) we re conduct ed be t ween various re spondent groups . FINDINGS & ANALYSIS Ge ne ra l Re s p o nd e nt Inf o rm a t io n Responses we re rece ived from fift y-t wo ins t it ut ions repre sent ing t hirt y-one (3 1 ) s t a t e s . Thirt y-five pe rcent (3 5 %) of t he re spondent s we re from privat e ins t it ut ions and s ixt y-five pe rcent (6 5 %) from public unive rs it ie s and colleges . St udent populat ion at t he ins t it ut ions ranged from 1 ,5 4 0 t o 5 0 ,0 0 0 wit h an ave rage of 1 7 ,1 1 9 s t udent s enrolled in unde rgraduat e and graduat e s t udie s .

= .05 (assuming unequal variances) were conducted between various respondent groups.

FINDINGS & ANALYSIS

General Respondent Information

Responses were received from fifty-two institutions representing thirty-one (31) states. Thirty-five percent (35%) of the respondents were from private institutions and sixty-five percent (65%) from public universities and colleges. Student population at the institutions ranged from 1,540 to 50,000 with an average of 17,119 students enrolled in undergraduate and graduate

studies. Figure 2: Minimum Certification Level

Seventy-three percent (73%), or 38 of 52, of the institutions seek green certification when constructing new buildings while only twenty-nine percent (29%) pursue certification when renovating existing facilities. Overall, an average of fifty-nine percent (59%) of the new buildings constructed were certified but less than nine percent (9%) of the renovations to existing stock attained certification. Ninety-five percent (95%)

Fig ure 2 : Minim um Ce rt if ic a t io n Le v e l Sevent y-t hree pe rcent (7 3 %), or 3 8 of 5 2 , of t he ins t it ut ions seek green ce rt ificat ion when cons t ruct ing new build ings while only t went y-nine pe rcent (2 9 %) pursue ce rt ificat ion when renovat ing exis t ing fac ilit ie s . Ove rall, an ave rage of fift y-nine pe rcent (5 9 %) of t he new build ings cons t ruct ed we re ce rt ified but le s s t han nine pe rcent (9 %) of t he renovat ions t o exis t ing s t ock at t a ined ce rt ificat ion. Nine t y-five pe rcent (9 5 %) of t he ins t it ut ions seeking ce rt ificat ion used LEED, but approximat e ly 1 0 % also used Green Globes and/ or Ene rgy St ar ce rt ificat ions . The year an ins t it ut ion’s firs t ce rt ificat ion was obt ained ranged from 2 0 0 4 t o 2 0 1 3 wit h an ave rage of 2 0 0 8 validat ing t hat green ce rt ificat ion is a re la t ive ly recent phenomenon. Of t he t hirt y-e ight ins t it ut ions regularly seeking ce rt ificat ion of new build ings , nine t y-t wo pe rcent (9 2 %) had e s t ablished a minimum LEED ce rt ificat ion leve l for t he ir unive rs it y (or college ) . The mos t common ce rt ificat ion leve l was s ilve r. The pe rcent age of ins t it ut ions seeking each leve l of ce rt ificat ion is shown in Figure 2 . Howeve r, when viewed in t he aggregat e , le s s t han fift y pe rcent (4 9 %) of a ll new build ings are ce rt ified and only seven pe rcent (7 %) of exis t ing fac ilit ie s are ce rt ified . Only fort y-t wo pe rcent (4 2 %) of t he ins t it ut ions had e s t ablished a t arge t dat e t o achieve a carbon-neut ral campus . The t arge t dat e e s t ablished by t he re spondent s ranged from 2 0 1 3 t o 2 0 5 0 wit h an ave rage t arge t of 2 0 3 4 , t went y years int o t he fut ure . Unive rs it ie s we re a lso asked t o indicat e t he pe rcent age of t he ir ene rgy needs t hat we re gene rat ed by t he unive rs it y from renewable ene rgy source s such as so lar and geot he rmal. In addit ion, survey re spondent s we re reques t ed t o indicat e what pe rcent age of t he ir ins t it ut ion’s so lid was t e was d ive rt ed from landfills t o recycling . Figure 3 : Renewable Ene rgy & Was t e Dive rs ion summarize s t he findings .

0% 10% 20% 30% 40% 50% 60% 70% 80%

Certified Silver Gold Platinum

12%

74%

14%

0%




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of the institutions seeking certification used LEED, but approximately 10% also used Green Globes and/or Energy Star certifications. The year an institution’s first certification was obtained ranged from 2004 to 2013 with an average of 2008 validating that green certification is a relatively recent phenomenon.

Of the thirty-eight institutions regularly seeking certification of new buildings, ninety-two percent (92%) had established a minimum LEED certification level for their university (or college). The most common certification level was silver. The percentage of institutions seeking each level of certification is shown in Figure 2. However, when viewed in the aggregate, less than fifty percent (49%) of all new buildings are certified and only seven percent (7%) of existing facilities are certified.

Only forty-two percent (42%) of the institutions had established a target date to achieve a carbon-neutral campus. The target date established by the respondents ranged from 2013 to 2050 with an average target of 2034, twenty years into the future.

Universities were also asked to indicate the percentage of their energy needs that were generated by the university from renewable energy sources such as solar and geothermal. In addition, survey respondents were requested to indicate what percentage of their institution’s solid waste was diverted from landfills to recycling. Figure 3: Renewable Energy & Waste Diversion summarizes the findings.

Figure 3: Renewable Energy and Waste Diversion On-s it e ene rgy product ion us ing renewable re source s me t le s s t hat 2 0 % of t he unive rs it y’s ene rgy needs for a vas t majorit y (8 2 %) of t he ins t it ut ions . Only e ight pe rcent of t he unive rs it ie s produced s ixt y pe rcent (6 0 %) or more of t he ir ene rgy consumpt ion requirement s and none of t he unive rs it ie s we re ‘ne t ze ro’. Solid was t e d ive rs ion programs had s ignificant ly highe r implement at ion. Howeve r, only t hirt y-seven pe rcent (3 7 %) of t he unive rs it ie s d ive rt ed 4 0 % or more of t he solid was t e t hat t he ins t it ut ion gene rat ed and only one unive rs it y was d ive rt ing great e r t hat 8 0 % of it s was t e . Gre e n Pra c t ic e s : Fre q ue nc y o f Us e In an e ffort t o ident ify t he sus t a inabilit y t hrus t of unive rs it ie s survey part ic ipant s we re asked t o ident ify t he frequency wit h which t hey employed se lec t ed green prac t ice s on bot h new and renovat ed fac ilit ie s . The re sponse opt ions available t o t he re spondent s we re 1 =no build ings , 2 =few build ings , 3 =some build ings , 4 =mos t build ings , and 5 =all build ings . Figure 4 : Frequency of Green Pract ice Use depic t s t he ave rage re sponse ra t ing for e ach green prac t ice . The highes t applicat ion was t he use of high e ffic iency light ing on mos t or a ll of an ins t it ut ion’s new and renovat ed fac ilit ie s . Occupancy light ing sensors , low flow plumbing fixt ure s , high e ffic iency fixt ure s and pe rformance monit oring also had wide use . Howeve r, t he use of t hird part ie s t o ident ify ene rgy saving poss ib ilit ie s was only ut ilized on some of t he ir build ings . Pass ive heat ing & cooling and solar ene rgy we re incorporat ed on few or none of t he ir new or renovat ed build ings . In addit ion, t he ins t a lla t ion of a green roof or geot he rmal was ut ilized on few of t he ir newly cons t ruct ed fac ilit ie s .

0

10

20

30

40

50

0-20% 20%-40% 40%-60% 60%-80% 80%-100%

# of

Inst

itutio

ns Energy

Waste

Figure 3: Renewable Energy and Waste Diversion

On-site energy production using renewable resources met less that 20% of the university’s energy needs for a vast majority (82%) of the institutions. Only eight percent of the universities produced sixty percent (60%) or more of their energy consumption requirements and none of the universities were ‘net zero’. Solid waste diversion programs had significantly higher implementation. However, only thirty-seven percent (37%) of the universities diverted 40% or more of the solid waste that the institution generated and only one university was diverting greater that 80% of its waste.

Green Practices: Frequency of Use

In an effort to identify the sustainability thrust of universities survey participants were asked to identify the frequency with which they employed selected green practices on both new and renovated facilities. The response options available to the respondents were 1=no buildings, 2=few buildings, 3=some buildings, 4=most buildings, and 5=all buildings. Figure 4: Frequency of Green Practice Use depicts the average response rating for each green practice. The highest application was the use of high efficiency lighting on most or all of an institution’s new and renovated facilities. Occupancy lighting sensors, low flow plumbing fixtures, high efficiency fixtures and performance monitoring also had wide use. However, the use of third parties to identify energy saving possibilities was only utilized on some of their buildings. Passive heating & cooling and solar energy were incorporated on few or none of their new or renovated buildings. In addition, the installation of a green roof or geothermal was utilized on few of their newly constructed facilities.




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A statistical comparison of the frequency of use of each practice for new building versus renovated buildings yielded several statistical differences. Occupancy lighting sensors, high efficiency glazing, performance monitoring capability, and solar energy were incorporated more often in new buildings.

Green Certification vs Institutions Not Seeking CertificationA statistical comparison of institutions that sought green certification on new and/or existing facilities versus those institutions that did not seek certification yielded somewhat surprising results. Institutions that did not seek certification on new buildings had similar frequency of use for high efficiency lighting, occupancy sensors, high efficiency windows/glazing, performance monitoring, green roofs, passive heating/cooling, and the use of third parties to identify energy savings. However, on new buildings they had less application of low flow fixtures, geothermal, and solar energy.

The difference in the frequency of implementation of green initiatives between institutions with certification programs and those without was even less on existing buildings. The only statistically significant differences were that institutions without certification programs were less likely to install solar, but interestingly, they were more likely to install high efficiency lighting in existing facilities.

University Support Universities provided weak support for the statement that ‘maintenance personnel receive adequate training regarding green materials and systems’. They more strongly supported that facilities personnel were encouraged to utilize ‘green’ replacement products at their institution, but felt that they provided insufficient incentives for facilities to integrate green products to reduce utility costs.

Universities that seek certification submit that their institution is very committed to sustainable initiatives on campus and that the university’s sustainability goals are widely communicated to students, faculty, and staff. Respondents from institutions that do not seek certification on new or existing projects were less committed to sustainable initiatives and were less likely to communicate sustainability goals.

Overall, universities do not indicate a lack of funding for green initiatives on new projects, but claim they will not sacrifice building space to incorporate sustainable materials and/or systems. However, they submit there is a lack of funding for green initiatives on existing building stock.

Financial Analysis of Green Initiatives Survey participants were asked a series of questions regarding the techniques they used to financially

Fig ure 4 : Fre q ue nc y o f Gre e n Pra c t ic e Us e A s t at is t ical comparison of t he frequency of use of e ach prac t ice for new build ing ve rsus renovat ed build ings yie lded seve ral s t a t is t ical d iffe rences . Occupancy light ing sensors , high e ffic iency g lazing , pe rformance monit oring capabilit y, and solar ene rgy we re incorporat ed more oft en in new build ings . Green Cert if icat ion v s Ins t it ut ions Not Seeking Cert if icat ion A s t a t is t ical comparison of ins t it ut ions t hat sought green ce rt ificat ion on new and/ or exis t ing fac ilit ie s ve rsus t hose ins t it ut ions t hat d id not seek ce rt ificat ion yie lded somewhat surpris ing re sult s . Ins t it ut ions t hat d id not seek ce rt ificat ion on new build ings had s imilar frequency of use for high e ffic iency light ing , occupancy sensors , high e ffic iency windows / g lazing , pe rformance monit oring , green roofs , pass ive heat ing / cooling , and t he use of t hird part ie s t o ident ify ene rgy savings . Howeve r, on new build ings t hey had le s s applicat ion of low flow fixt ure s , geot he rmal, and solar ene rgy. The d iffe rence in t he frequency of implement at ion of green init ia t ive s be t ween ins t it ut ions wit h ce rt ificat ion programs and t hose wit hout was even le s s on exis t ing build ings . The only s t a t is t ically s ignificant d iffe rences we re t hat ins t it ut ions wit hout ce rt ificat ion programs were le s s like ly t o ins t a ll so lar, but int e re s t ing ly, t hey we re more like ly t o ins t a ll high e ffic iency light ing in exis t ing fac ilit ie s . University Support

0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5

Geothermal

Green Roof

Solar Energy

Passive Hea>ng/Cooling

3rd Party ID Op>ons

Performance Monitors

High Efficiency Glazing

Low Flow Fixtures

Occupancy Sensors

High Efficiency Ligh>ng

New

Exist

Figure 4: Frequency of Green Practice Use




33

analyze green initiatives on new and existing facilities. The responses from universities seeking certification were statistically compared with those institutions that do not seek certification and there was no statistically significant difference in response on any of the survey metrics. Therefore the following findings apply to all universities, whether they certify or not.

The first grouping in this section of the questionnaire was a series of statements with response options ranging from 1=strongly disagree to 5=strongly agree. Table 1: Financial Analysis Techniques lists the analysis techniques investigated, the mean response for each, and whether or not there was statistical significance support for agreement or disagreement with the statement regarding the financial analysis technique.

Unive rs it ie s provided weak support for t he s t a t ement t hat ‘maint enance pe rsonne l rece ive adequat e t ra ining regarding green mat e ria ls and sys t ems’. They more s t rongly support ed t hat fac ilit ie s pe rsonne l we re encouraged t o ut ilize ‘green’ replacement product s a t t he ir ins t it ut ion, but fe lt t hat t hey provided insuffic ient incent ive s for fac ilit ie s t o int egrat e green product s t o reduce ut ilit y cos t s . Unive rs it ie s t hat seek ce rt ificat ion submit t hat t he ir ins t it ut ion is ve ry commit t ed t o sus t a inable init ia t ive s on campus and t hat t he unive rs it y’s sus t a inabilit y goals are wide ly communicat ed t o s t udent s , facult y, and s t aff. Respondent s from ins t it ut ions t hat do not seek ce rt ificat ion on new or exis t ing projec t s we re le s s commit t ed t o sus t a inable init ia t ive s and we re le s s like ly t o communicat e sus t a inabilit y goals . Ove rall, unive rs it ie s do not indicat e a lack of funding for green init ia t ive s on new projec t s , but c la im t hey will not sacrifice build ing space t o incorporat e sus t a inable mat e ria ls and/ or sys t ems . Howeve r, t hey submit t he re is a lack of funding for green init ia t ive s on exis t ing build ing s t ock. Financial Analysis of Green Initiatives Survey part ic ipant s we re asked a se rie s of ques t ions regarding t he t e chniques t hey used t o financially analyze green init ia t ive s on new and exis t ing fac ilit ie s . The re sponses from unive rs it ie s seeking ce rt ificat ion we re s t a t is t ically compared wit h t hose ins t it ut ions t hat do not seek ce rt ificat ion and t he re was no s t a t is t ically s ignificant d iffe rence in re sponse on any of t he survey me t rics . The re fore t he fo llowing findings apply t o a ll unive rs it ie s , whe t he r t hey ce rt ify or not . The firs t g rouping in t his sec t ion of t he ques t ionnaire was a se rie s of s t a t ement s wit h re sponse opt ions ranging from 1 =s t rongly d isagree t o 5 =s t rongly agree . Table 1 : Financial Analys is Techniques lis t s t he analys is t e chniques inves t igat ed , t he mean re sponse for e ach, and whe t he r or not t he re was s t a t is t ical s ignificance support for agreement or d isagreement wit h t he s t a t ement regarding t he financial analys is t e chnique .

Table 1: Financial Analysis Techniques Financial Analysis Technique Mean Statistically

Significant Ut ilize life -cycle cos t analys is 3 .9 0 Yes Mandat ory payback of 3 yrs or le s s 2 .2 7 Yes Evaluat e long-t e rm financial impact 4 .0 0 Yes Priorit ize funding based on payback pe riod

3 .6 1 Yes

Evaluat e payback pe riod 3 .8 5 Yes Priorit ize based upon ope rat ions savings

3 .6 0 Yes

Have int e rnal financial analys is 3 .0 1 No Ut ilize ext e rnal financial analys is 2 .8 5 No Life -cycle analys is mos t re liable 3 .4 4 Yes Simple payback not re liable 2 .8 5 No The findings are t hat unive rs it ie s submit t hat t hey evaluat e t he long-t e rm financial impact of green init ia t ive s . They be lieve t hat life cycle financial analys is of green init ia t ive s is t he mos t re liable financial analys is t ool. Unive rs it ie s fe lt t hat s imple payback analys is was unre liable . As a re sult , ins t it ut ions evaluat e life -cycle cos t in conjunct ion wit h payback pe riod t o financially analyze green init ia t ive s and priorit ize projec t funding . They do not have a mandat ory payback pe riod of 3 years or le s s for ene rgy savings init ia t ive s . As expect ed , because ope rat ing cos t is cons ide red wit h life -cycle analys is , re spondent s submit t hat projec t funding is a lso priorit ized based upon ope rat ional savings . Survey part ic ipant s we re a lso asked t o ident ify t he frequency of use for e ach financial analys is t ool. Respondent s we re provided re sponse opt ions ranging from 1 =neve r used t o 5 =always used t o analyze green init ia t ive s . Figure 5 : Financial Analys is Technique Frequency of Use pre sent s t he re sult s from t he survey. Cons is t ent wit h earlie r findings , life -cycle analys is , payback pe riod, and priorit iz ing init ia t ive s based upon ope rat ing savings had t he highes t leve l of use .

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

ESCO on retrofits Adj. internal rate of return

Prioritize based on donations Internal rate of return

3rd party identify/finance Savings/investment ratio

Discounted payback period 3rd party analysis

Use incentive packages Minimum payback period

Priortize per operating saving Simple payback

Life-cycle analysis

1=never, 2=seldom, 3=sometimes, 4=often, 5=always

The findings are that universities submit that they evaluate the long-term financial impact of green initiatives. They believe that life cycle financial analysis of green initiatives is the most reliable financial analysis tool. Universities felt that simple payback analysis was unreliable. As a result, institutions evaluate life-cycle cost in conjunction with payback period to financially analyze green initiatives and prioritize project funding. They do not have a mandatory payback period of 3 years or less for energy savings initiatives. As expected, because operating cost is considered with life-cycle analysis, respondents submit that project funding is also prioritized based upon operational savings.

Survey participants were also asked to identify the frequency of use for each financial analysis tool. Respondents were provided response options ranging from 1=never used to 5=always used to analyze green initiatives. Figure 5: Financial Analysis Technique Frequency of Use presents the results from the survey. Consistent with earlier findings, life-cycle analysis, payback period, and prioritizing initiatives based upon operating savings had the highest level of use. Conversely, contracting with an Energy Service Company (ESCO) to retrofit an existing building and finance the upgrades through the ESCO with the energy savings was seldom used for green initiatives. Universities seldom used ESCO’s or other third parties to identify and finance green initiatives on

Evaluat e payback pe riod 3 .8 5 Yes Priorit ize based upon ope rat ions savings

3 .6 0 Yes

Have int e rnal financial analys is 3 .0 1 No Ut ilize ext e rnal financial analys is 2 .8 5 No Life -cycle analys is mos t re liable 3 .4 4 Yes Simple payback not re liable 2 .8 5 No The findings are t hat unive rs it ie s submit t hat t hey evaluat e t he long-t e rm financial impact of green init ia t ive s . They be lieve t hat life cycle financial analys is of green init ia t ive s is t he mos t re liable financial analys is t ool. Unive rs it ie s fe lt t hat s imple payback analys is was unre liable . As a re sult , ins t it ut ions evaluat e life -cycle cos t in conjunct ion wit h payback pe riod t o financially analyze green init ia t ive s and priorit ize projec t funding . They do not have a mandat ory payback pe riod of 3 years or le s s for ene rgy savings init ia t ive s . As expect ed , because ope rat ing cos t is cons ide red wit h life -cycle analys is , re spondent s submit t hat projec t funding is a lso priorit ized based upon ope rat ional savings . Survey part ic ipant s we re a lso asked t o ident ify t he frequency of use for e ach financial analys is t ool. Respondent s we re provided re sponse opt ions ranging from 1 =neve r used t o 5 =always used t o analyze green init ia t ive s . Figure 5 : Financial Analys is Technique Frequency of Use pre sent s t he re sult s from t he survey. Cons is t ent wit h earlie r findings , life -cycle analys is , payback pe riod, and priorit iz ing init ia t ive s based upon ope rat ing savings had t he highes t leve l of use .

0.00 0.50 1.00 1.50 2.00 2.50 3.00 3.50 4.00

ESCO on retrofits Adj. internal rate of return

Prioritize based on donations Internal rate of return

3rd party identify/finance Savings/investment ratio

Discounted payback period 3rd party analysis

Use incentive packages Minimum payback period

Priortize per operating saving Simple payback

Life-cycle analysis

1=never, 2=seldom, 3=sometimes, 4=often, 5=always

Table 1: Financial Analysis Techniques


Figure 5: Financial Analysis Technique Frequency of Use



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campus. Internal rate of return and adjusted internal rate of return were the least utilized financial analysis techniques followed by savings/investment ratio and the discounted payback method which were seldom or sometimes used to assess green initiatives.

CONCLUSIONS

University Commitment to Green Certification & Carbon NeutralityA majority of universities (73%) seek green certification on new buildings constructed on campus, but only twenty-nine percent (29%) seek certification on renovation of existing facilities. When viewed in the aggregate, less than fifty percent (49%) of all new buildings attained a green certification and only seven percent (7%) of existing facilities were certified. Green certification on university campuses has gained prominence in a relatively short timeframe, but still has considerable room for growth, especially with regard to green certification of existing building stock.

Regarding carbon neutrality, only 42% of the institutions had made a commitment for their university to become carbon neutral within the next 20 years. In addition, for a vast majority of the institutions (82%) the use of renewable sources for onsite energy production met less than 20% of the university’s needs. Supportive of this statistic is the finding that solar and geothermal are seldom incorporated into new or renovation projects. Both of these findings do not appear to be supportive of a carbon-neutral goal which may identify the need for a future research effort.

The commitment of U.S. universities to green certification is strong, but it may be quite some time before university campuses are carbon neutral.

Implementation of Green Practices Universities incorporate high efficiency fixtures, occupancy lighting sensors, low flow plumbing fixtures, and performance monitoring on most or all of their new and renovated buildings. However, renewable energy sources, solar and geothermal, are seldom incorporated on new construction, and even less likely to be utilized on renovation projects. Frequency of green practice use is similar for institutions seeking green certification and those that do not have a certification program.

In summary, universities are committed to green building practices that reduce energy and water consumption, but seldom support solar or geothermal initiatives which could provide onsite renewable energy sources for the university.

University Support for Green Initiatives

University support for green initiatives appears to be mixed. Most institutions indicated that there was sufficient funding for green initiatives with the construction of new facilities, but there was a funding shortfall for the renovation of existing building stock. There is evidence for strong support of green initiatives with new buildings, but limited support for retrofits to existing stock.

Financial Analysis of Green InitiativesUniversities effectively evaluate the long-term financial impact of green initiatives. They typically use life-cycle analysis and calculate a payback period. They prioritize green initiatives based upon operational savings. Financial considerations are key drivers.

Most universities believe that they have the internal expertise to identify and assess green initiatives. Their financial analysis is normally performed internally. Universities seldom utilize a third party to identify, analyze, and/or finance green initiatives.

Summary of Findings and the Need for Future ResearchA majority (73%) of universities seek green certification on new construction and a limited number (29%) seek certification on renovated facilities. Universities are committed to building practices that reduce energy and water consumption and typically have an effective process to evaluate the financial viability of green initiatives.

Almost half (43%) of the universities have made a commitment to become carbon neutral. However, most universities do not incorporate the use of renewable sources for onsite energy production. Therefore, how do universities that have made a commitment to become carbon neutral intend to reach that objective? Seeking the answer to this question presents an opportunity for future research.




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REFERENCES

Bausman, Dennis, John Davis and Daniel Werts (2014), “The ‘Greening’ of American Universities:

An Evaluation of the Social, Economic, and Environmental Factors”, The International Journal of the Constructed Environment, Common Ground Publishing, 2014

Dougherty, Brooks (2010), The Role of the LEED® Green Building Rating System in Higher Education:

Recent Trends and Status, September 25, 2010 http://www.centerforgreenschools.org/Libraries/Resources_Documents/Role_of_LEED_in_Higher_Education.sflb.ashx

Earth911 (2013), Green Building Materials to Reach $254 Billion Market Value by2020, http://www.

earth911.com/tech/green-building-materials-market-value/, accessed July 20, 2014

Elkington, J. John 1997, Cannibals with Forks: The Triple Bottom Line of 21st Century Business, Oxford:

Capstone Publishing

Galayda, Jamie and Jerry Yudelson (2010), Green Building Trends in Higher Education, Yudelson

Associates, White Paper, April 2010, http://greenbuildconsult.com/pdfs/higher-ed.pdf

Martin, James and James Samels (2012), The Sustainable University: Green Goals and New Challenges for Higher

Education Leaders, The Johns Hopkins University Press, Baltimore, 2012

McGraw-Hill (2012), Green Building Outlook Strong for Both Non-Residential & Residential Sectors Despite Soft

Economy, www.construction.com, November 15, 2012

McGraw-Hill (2013), World Green Building Trends: Business Benefits Driving New and Retrofit Market

Opportunities in Over 60 Countries, Harvey Bernstein Editor, McGraw-Hill Construction, Bedford MA, 2013

USGBC (2012) Green Building Facts, published by the US Green Building Council, July 1, 2012 http://

www.usgbc.org/articles/green-building-facts

World Green Building Council (WGBC) 2013, The Business Case for Green Building, World Green

Building Council, www.worldgbc.org

Yudelson, Jerry and Breunig, Tom (2011), The Top 20 Green Building Trends for 2011, The Green

Economy Post, http://greeneconomypost.com/green-building-trends-12562.htm




36 Adoption of Green Building Guidelines in USA, India, and China

Adoption of Green Building Guidelines in USA, India, and China

Matt Syal, PhD, LEED APMichigan State University | [email protected]

Yunhui Yang, MSKunming Metallurgy College | [email protected]

Gayatri Kumar, LLM

The World Bank | [email protected]

Jawanda Jackson, MSMichigan State University/Hickory Construction | [email protected]

ABSTRACT: Green Building Guidelines (GBGs) have played a major role in the global efforts to develop environmentally responsible buildings and infrastructure. These guidelines serve as ratings tools to evaluate sustainable practices used in buildings’ design, construction, and operations. Although, the acceptance of these guidelines has begun to increase globally, only a few countries have seen their widespread adoption. The acceptance of GBGs is dependent upon various factors specific to the country and society in which they exist. USA, India, and China were selected to be the focus of this study since each of these countries present a unique set of societal attributes related to the green building movement. The main objective of this research is to evaluate and compare the GBGs and their adoption in these three countries. In each country, most accepted GBG was selected for analysis. Therefore, LEED-USA, LEED-India and GBL-China were selected for this study.

Matt Syal is a professor of Construction Management in the School of Planning, Design, and Construction at Michigan State University. His research interests are in Construction Project Management, Sustainable Built Environment, Housing, and International Project Management.

Yunhui Yang is a former Visiting Scholar in the School of Planning, Design, and Construction at Michigan State University. He currently serves as an Associate Professor in the Department of Construction Engineering at Kunming Metallurgy College in Kunming, China.

Gayatri Kumar is a former Visiting Scholar in the School of Planning, Design and Construction at Michigan State University. Shee currently serves as a consultant in the World Bank at Washington DC.

Jawanda Jackson is a former Graduate Research Assistant of Construction Management in the School of Planning, Design and Construction at Michigan State University. She currently serves as a project engineer for Hickory Construction in Alcoa, TN.

Keywords: Green Building Guidelines, Sustainable Buildings, Adoption, LEED, GBL, USA, India, China

INTRODUCTIONIn the wake of a rapidly urbanizing world, environmentally responsible building requirements must be considered in order to avoid the depletion of materials and natural resources. Green buildings and Green Building Guidelines (GBGs) have played

a major role in the global efforts to develop the built environment more responsibly. These guidelines serve as rating tools to evaluate sustainable practices used in buildings’ design, construction, and operations. GBGs are considered to be an innovative tool that has begun to change industry practices in architecture, engineering and construction. Although, the acceptance of these guidelines has begun to increase globally, only a few countries have seen their widespread adoption (Korkmaz et al. 2011, USGBC 2009).







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The acceptance of GBGs is dependent upon various factors specific to the country and society in which they exist. Governmental involvement in most countries seems to have a major influence on adoption of these guidelines (Potbhare et al. 2009a). Developed countries, such as USA, have seen higher level of adoption for their respective guidelines. On the other hand, the green building movements in developing countries, such as India and China, have recently begun to take hold. In both cases, adoption methods for GBGs are a growing focus. Potbhare et al. (2009b) stated that the need for recognized, uniform and internationally compatible sustainable building standards is more evident in developing countries.

The main objective of this research is to evaluate and compare the adoption of GBGs in USA, India, and China. The work scope consists of two main steps:• Overview and comparison of major green building

guidelines in USA, India and China; and• Comparative assessment of the adoption of GBGs in

these three countries.

GREEN BUILDING GUIDELINES (GBGS) IN USA, INDIA AND CHINA

Recent global environmental initiatives have urged the world to turn its focus to environmental issues including the building practices. USA, India and China have all developed green building guidelines in response to these global environmental initiatives. In 1987, the Brundlandt Report, also known as “Our Common Future,” discussed development in regards to environmental responsibility. The report defined sustainable development as “development that meets the needs of the present without compromising the ability of future generations to meet their own needs” (Brundlandt 1987).

For this study, most accepted GBG in each country was selected for analysis. Therefore, LEED-USA was selected for the USA, LEED-India was selected for India and Green Building label (GBL) was selected for China. During the discussion below for each country, other known GBGs in that country are also identified.

United State of America: LEED-USAIn 1993, the United States Green Building Council (USGBC) was formed, as a non-profit organization, with the objective of advancing the platform for sustainable design and green buildings. After identifying the industry’s need to evaluate and certify green buildings,

the USGBC formed a committee of professionals from diverse backgrounds with the goal to develop green building guidelines. In 1998, the committee unveiled the first “Leadership in Energy and Environmental Design” (LEED) green building guidelines. LEED guidelines serve as a rating system for developing sustainable built environments. It is voluntary in nature and has four levels of certification that can be achieved; Certified, Silver, Gold and Platinum. The evaluation process is administered by the Green Building Certification Institute (GBCI), a third party organization developed in 2008 in conjunction with the USGBC. Evaluation can take place as early as the completion of the design phase but certification can only be awarded after the building is completed (USGBC 2009).

There are several LEED rating systems each dealing with different sectors of the sustainable built environment. The LEED for New Construction (LEED-NC) rating system is the most commonly used rating system. It focuses on seven environmental categories; Sustainable Sites, Water Efficiency, Energy and Atmosphere, Material and Resources, Indoor Environmental Quality, Innovation in Design, and Regional Priority. Innovations in Design and Regional Priority categories give adopters the opportunity to earn additional points. Each environmental category contains credits where points are allocated depending upon the potential benefits and environmental impacts. While developers have the option to choose what credits to pursue, each category has several prerequisites that must be achieved. A maximum of 110 points can be earned for the LEED-NC certification (USGBC 2009).

Industry acceptance of the LEED system has increased substantially over the past decade (USGBC 2009). Although other guidelines exist in the US, namely Green Globes, Energy Star, ICC 700 - National Green Building Standards for residential buildings, and Society for Environmentally Responsible Facilities (SERF) guidelines, neither have had comparable success. LEED has been adopted internationally and has also influenced the development of rating systems in other countries. In a short period of only 15 years, as of November 2013, there are around 65,000 Commercial and Housing units that are LEED certified and 1.5-2 times of these are LEED registered (USGBC 2013a).

The latest available version of LEED, version 4.0, is a substantial improvement over the first version LEED




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1.0 released in 1998. LEED 2.0, 2.1, 2.2, and 3.0 have all proceeded the latest version, LEED 4.0 (USGBC 2009; USGBC 2013b). LEED 4.0 condenses nine different guidelines into five rating system families; Building Design & Construction, Interior Design & Construction, Existing Building: Operations & Maintenance, Neighborhood Development, and Homes. Among the five families, there will be a total of twenty-one specific guidelines (USGBC 2013c).

India: LEED-IndiaThe Indian Green Building Council (IGBC) launched LEED-India in 2003. It is based on LEED-USA with modifications to align with India’s unique construction needs. Also voluntary in nature, the LEED-India certification is a weighted market-driven system that has four levels of certifications with a maximum score of 69 that can be earned. The range of points for each certification level are 26-32 for Certified, 33-38 for Silver, 39-51 for Gold and 52 and above for Platinum. The LEED-India’s environmental categories where points can be earned include Sustainable Sites, Water Efficiency, Energy and Atmosphere, Materials and Resources, Indoor Environmental Quality, and Innovation and Design (IGBC 2013).

The Indian government has adopted another green building guideline developed specifically for India. It is called the Green Rating for Integrated Habitat Assessment (GRIHA), (TERI 2013). Despite the government’s support for GRIHA, LEED-India has become more popular (Arif et. Al 2009). LEED-India has been updated once and is currently operating as the LEED-India 2011 version. The IGBC currently has nine rating systems including LEED New Construction, LEED Core and Shell, IGBC Green Existing, IGBC Buildings (Operations & Maintenance), IGBC Green Homes, IGBC Green Townships, IGBC Green SEZ, IGBC Green Factory, IGBC Green Landscape. The IGBC serves as both the parent organization and the third party assessor. After a building’s design phase has been completed owners can seek evaluation for precertification but cannot earn certification until the completion of construction (IGBC 2013).

China: Green Building Label (GBL)The China Green Building Council and China’s Ministry of Housing and Urban-Rural Development (MOHURD) released the Green Building Label (GBL) in 2006. The Green Building Label, also known as the

“Three Stars System,” is a nationwide green building guideline that is voluntary in nature. The building evaluation process is overseen by the Green Building Label Management Office which is entrusted to manage, regulate, and promote the guidelines. China’s Green Building Label consists of two possible certification processes; the Green Building Design Label (GBDL) which is awarded at the end of the design phase and the Green Building Label which is awarded after one year of occupancy (CNGBN 2013).

The three levels of certification can be earned depending on a project’s sustainable performance; one-star, two-stars, or three-stars, hence the nickname “Three Stars System”. The requirements are 18-29 points for one-star, 30-39 points for two-stars, and 40 and above for the three-stars rating. Normally one star and two star ratings can be evaluated and certified by either the central or the local building administrations, whereas, a three star rating can only be evaluated and certified by the central government administration. In case of one and two star ratings, local governments are given some flexibility to accept variations in requirements in order to align with local and regional climate conditions. The environmental categories in GBL include, Land Savings and Outdoor Environment, Energy Savings, Water Savings, Materials Savings, Indoor Environmental Quality, Operations and Management, and Preference Items (CNS 2006). The Green Building Label provides separate evaluation standards for residential and commercial buildings. Considering the current construction market in China, these standards are mainly used for large multifamily residential buildings and public buildings that consume large amounts of energy and resources (CNGBN 2013).

Although the green building market is rapidly expanding, green buildings in China began slowly with only 4 registered LEED projects in 2004. In May 2013, MOHURD’s building energy-saving technology division released a list of green building projects from 2008 until 2012. During that time a total of 742 projects received the Green Building Label. Out of those 742 projects, the Green Building Design Label accounted for 694, Green Building Label accounted for 48, and only 34 projects received both. Among those 742 projects, 239 were one-star, 293 were two-star, and remaining 210 were three-star projects. In 2008, there were a total 6 certified projects, whereas, in 2012, the number jumped to 389 certified projects (Jianqing et al. 2012).




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COMPARISON OF GBGS IN USA, INDIA, AND CHINA

Many similarities exist between the Green Building Guidelines (GBGs) in USA, India and China. Each of the GBGs is a voluntary rating system that follows a building through the programming, design, construction, and operation phases of its life cycle. Each has several levels

of certifications and similar focuses on energy, water, materials, and indoor environmental quality. Third party evaluation including pre-construction evaluation is provided for each of the guidelines.

Other than the above-noted similarities, these GBGs differ in several aspects. A comparison matrix of these three GBGs is provided in Table 1.

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Ta b le 1 : Comparison of Green Build ing Guide line s (USGBC 2 0 0 9 ; IGBC 2 0 1 3 ; CNGBN 2 0 1 3 )

Description LEED - USA-NC (2009) LEED - India-NC (2011) GBL - China (2006) Parent Organization U. S. Green Building Council Indian Green Building Council Ministry of Housing Urban and

Rural Development and China Green Building Council

Type of Organization

Non-Profit Non-Profit Governmental

Market Orientation Private and Public Private and Public Mostly Public Year of Origin 2000 2003 2006 Weighting System Yes Yes Yes Levels of Certifications

Certified 40-49 Silver 50-59 Gold 60-79 Platinum 80 points and above

Certified 26-32 Silver 33-38 Gold 39-51 Platinum 52 points and above

1 Star: 18-29 2 Stars: 30-39 3 Stars: 40-49

Maximum Score 110 69 49 Environmental Categories

! Sustainable Sites ! Water Efficiency ! Energy and Atmosphere ! Materials and Resources ! Indoor Environment

Quality ! Innovation and Design

Regional Priority

! Sustainable Sites ! Water Efficiency ! Energy and Atmosphere ! Materials and Resources ! Indoor Environment

Quality ! Innovation and Design ! Regional Priority

! Land Savings and Outdoor Environment

! Energy Savings ! Water Savings ! Materials Savings ! Indoor Environmental

Quality ! Operations and

Management

Guidelines for Specific Building Sectors / Typologies

! LEED for New Construction

! LEED for Core & Shell ! LEED for Schools ! LEED for Retail ! LEED for Healthcare ! LEED for Homes ! LEED for Commercial ! Interiors ! LEED for Neighborhood

Development

! LEED for New Construction

! LEED for Core & Shell ! IGBC Green Existing ! Buildings (Operations &

Maintenance) ! IGBC Green Homes ! IGBC Green Townships ! IGBC Green SEZ ! IGBC Green Factory

Building ! IGBC Green Landscape

! Commercial ! Residential ! Industrial (new)

Third Party Evaluator

Green Building Certification Institute

Indian Green Building Council • Central Administration of Green Building Label Management Office (GBLMO)

• Local Provincial GBLMO Pre-construction evaluation

After completion of design phase



Certification Timing Immediately after building completion

Immediately after building completion

1 year after building occupancy and operation

Years Before Recertification

5 years 3 years 3 Years

Table 1: Comparison of Green Building Guidelines (USGBC 2009; IGBC 2013; CNGBN 2013)




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ADOPTION OF GBGS IN USA, INDIA AND CHINAGreen building guidelines are seen an as innovation and have begun to influence the contemporary principles of engineering, architecture, and construction (Korkmaz et al. 2011). An innovation is defined as “an idea, behavior or object that is perceived as new by its audience” (Robinson 2009, Rogers 2003). Green buildings are considered to be an innovation in the construction industry and therefore are subject to hesitancy of adoption. Societal adoption of green buildings is essential to the implementation of green guidelines. Potbhare et al. (2009a) identify three units of society that are key to this adoption. (1) Government, consisting of political leaders; state and local governments and related agencies; semi-governmental organizations; and the federal government. (2) Profit and Non-profit organizations, consisting of multi-national corporations; community groups; environmental groups; non-governmental organizations; educational institutions; universities; suppliers; manufactures; trade organizations; media; and large business houses. (3) Individuals including sustainable building consultants; developers; engineers; architects; customers; and general contractors.

According to the theory of the Diffusion of Innovations (Rogers 2003, Robinson 2009), an innovation is diffused among five different groups of adopters (Figure 1). The first group, “innovators,” consists of a small amount of imaginative and visionary individuals. Next, the “early adopters” become engaged after benefits start to become apparent. The “early majority” follows when tangible proof and results have been produced. The “late majority” cautiously wait until the innovation has been updated and fine-tuned. “Laggards”, the final group, remain apprehensive due to the high risk associated with the innovation. The theory is based on a normal distribution of innovation adoption and assumes that 50% of the potentially available market will be reached within a typical “10-year mean time” (Rogers 2003, Robinson 2009). For the purpose of this research, the research team will focus on the “innovators” and “early adopters” of green building guidelines and refer to them as “supporters” of the green building movement.

Figure 1: Categories of Adopters in “Diffusion of Innovation”

Adoption of green building guidelines is dependent upon cultural and societal attributes that can serve as either barriers or catalysts. Some factors that are considered as major barriers to the adoption of green building guidelines include little interest from clients, the nature of the construction industry, high up-front costs, lack of incentives, lack of training, absence of demonstration projects, unclear information about long term savings, local disincentives, and a lack of understanding of “green” technology. On the contrary, factors such as available incentives, cost-benefit information, accessibility to green building supply chain, available educational and training programs for various stakeholders act as a catalyst and help increase the adoption of green building guidelines. In order for adoption to occur, an information infrastructure that helps to build a knowledge base of professionals, must be in place. These above-noted barriers and catalysts for the adoption of green building guidelines are generally present in most countries, including USA, India and China (Potbhare et al. 2009a, Potbhare et al. 2009b, Arif et al. 2010).

When considering the methods of adoption for the green building guidelines, the governmental policies of a country also play key role. For example, countries that have well defined energy efficiency goals and related building codes provide a platform for GBGs adoption. Government directives, used in conjunction with these policies, can also encourage adoption of voluntary guidelines. For example, certain levels of adoption is ensured if the government-funded buildings are mandated to be green certified (Korkmaz et al. 2009).

Adoption in USAIn USA, several organizations and individuals have served as supporters of the green building movement. The federal government, many state and local

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Fig ure 1 : Ca t e g o rie s o f Ad o p t e rs in “Dif f us io n o f Inno v a t io n”

Adopt ion of green build ing guide line s is dependent upon cult ural and socie t a l a t t ribut e s t hat can se rve as e it he r barrie rs or cat a lys t s . Some fac t ors t hat are cons ide red as major barrie rs t o t he adopt ion of green build ing guide line s inc lude lit t le int e re s t from client s , t he nat ure of t he cons t ruct ion indus t ry, high up-front cos t s , lack of incent ive s , lack of t ra ining , absence of demons t rat ion projec t s , unclear informat ion about long t e rm savings , local d is incent ive s , and a lack of unde rs t anding of “green” t e chnology. On t he cont rary, fac t ors such as available incent ive s , cos t -bene fit informat ion, acce ss ib ilit y t o green build ing supply chain, available educat ional and t ra ining programs for various s t akeholde rs ac t as a cat a lys t and he lp increase t he adopt ion of green build ing guide line s . In orde r for adopt ion t o occur, an informat ion infras t ruct ure t hat he lps t o build a knowledge base of profe ss ionals , mus t be in p lace . These above -not ed barrie rs and cat alys t s for t he adopt ion of green build ing guide line s are gene rally pre sent in mos t count rie s , inc luding USA, India and China (Pot bhare e t a l. 2 0 0 9 a, Pot bhare e t a l. 2 0 0 9 b, Arif e t a l. 2 0 1 0 ) . When cons ide ring t he me t hods of adopt ion for t he green build ing guide line s , t he gove rnment al polic ie s of a count ry a lso p lay key ro le . For example , count rie s t hat have we ll de fined ene rgy e ffic iency goals and re la t ed build ing codes provide a p la t form for GBGs adopt ion. Gove rnment d irec t ive s , used in conjunct ion wit h t he se polic ie s , can also encourage adopt ion of volunt ary guide line s . For example , ce rt a in leve ls of adopt ion is ensured if t he gove rnment -funded build ings are mandat ed t o be green ce rt ified (Korkmaz e t a l. 2 0 0 9 ) . Ad o p t io n in US A In USA, seve ral organizat ions and individuals have se rved as support e rs of t he green build ing movement . The fede ral gove rnment , many s t a t e and local gove rnment s , s eve ral large c it ie s , unive rs it ie s , indus t ry organizat ions , and environment al g roups se rve as key support e rs . Supply chain and ce rt ificat ion of

Innovators 2.5%

Early Adopters

13.5%

Early Majority

34%

Late Majority

34%

Laggards 13.5%Laggards

16%




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governments, several large cities, universities, industry organizations, and environmental groups serve as key supporters. Supply chain and certification of sustainable building products and material is fairly well developed and this serves as a vital information source and support for the GBGs adoption (Green Seal 2013, Energy Star 2013). Another important resource that has operated as a hub for information and engagement in the green building movement is the USGBC website. Information regarding opportunities for engagement such as seminars, professional development and regional membership chapters can be found on this interactive website. Reports, peer-reviewed research and guideline explanations are all the major forms of literature that are used to promote the guidelines and communicate with stakeholders (USGBC 2013d).

Energy reduction goals are often established and enforced by local, state, and federal governmental agencies. For instance, the Environmental Protection Agency (EPA) requires that all agency buildings, both new and existing, reach “net zero” status for energy consumption by the year 2050 (EPA 2012). No legislation has been passed at the national level that mandates the adoption of green building guidelines but, as a result of various governmental directives, coupled with the growing market demand due to enhanced societal awareness, the GBGs are rapidly gaining acceptance (Kumar et al. 2010, USGBC 2009).

In 2012, the International Code Council released the “International Green Construction Code,” a building code that addresses sustainable commercial construction (ICC 2013). The adoption of building codes in USA varies based on the jurisdiction, because in most cases, municipalities have the freedom to adopt specific building policies and codes suitable for their local context (Cullingworth and Caves 2009). Some jurisdictions have been more proactive than others when developing sustainable goals and adopting related policies. For example, in 2008, California passed the “Green Building Standards Code” to guide sustainable development within the state (CSP 2013). Massachusetts, Maryland, and Oregon are examples of other states that have adopted sustainable building codes (GBPN 2013a).Since green building guidelines are voluntary in the United States, guidelines can only be enforced on building developers/owners that decide to seek the certification (USGBC 2013d). Several states and cities

have mandated that publically funded buildings, and in some instances, private commercial buildings, adopt LEED certification. Over time, many local governments have amended the mandate of LEED guidelines and now require compliance with GBGs requirements and not the certification (Silberman 2007). Incentives for green buildings in the form of tax rebates, grants, subsidies, expedited permitting, and floor area ratio are offered at federal, state, and city levels. These vary according to each municipality and their emphasis on sustainable efforts (USGBC 2013e).

Adoption in IndiaKey supporters in India include architects, engineers, sustainable building consultants, large business houses, multinational corporations, environmental groups, non-government organizations and the media. The Indian Green Building Council’s (IGBC) website provides access to key sources of information including workshops and seminars, education, periodicals, training courses, etc. (Potbhare et al. 2009a, Arif et al. 2010). The IGBC also cultivates the development of networks and the dissemination of information by providing summits, conferences, peer-reviewed research and reports. India’s green supply chain for sustainable building products and material is being supported by IGBC and is in its early stages of development (IGBC 2013).

India’s democratic republic governmental system is known for its emphasis on regulation and has issued numerous market-based standards and regulatory directives related to green buildings in the last 10-15 years. In 1998, India issued the “National Housing and Habitat Policy” that recognized the importance of energy efficiency in buildings and air pollution in the construction sector (Evans et al. 2009). In 2001, the “Energy Conservation Act” was passed by the federal government to provide for the establishment of state energy conservation agencies. As a result, in 2002, the Bureau of Energy Efficiency (BEE) was established. In 2005, the federal government issued the “National Building Code,” that incorporated many of the green and sustainable building measures. In 2006, the government’s Planning Commission issued the “Integrated Energy Policy.” Finally, in 2007, the BEE issued the “Energy Conservation Building Code” (ECBC), a code that focused on sustainable building practices (Kumar et al. 2010, TERI 2013). Eight of India’s twenty-eight states have already mandated to comply with the ECBC for commercial buildings. These states




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have large urban areas or metropolitan cities with high surges in population and urban construction. These eight states and their respective urban centers are: Delhi (New Delhi), Maharashtra (Mumbai), Uttar Pradesh (NOIDA), Haryana (Gurgaon), Tamil Nadu (Chennai), Andhra Pradesh (Hyderabad), Karnataka (Bangalore) and West Bengal (Calcutta) (IBNLive 2011). In addition, the Indian government made it mandatory for federal government buildings to be certified as green buildings. The nationally adopted GRIHA system is used for this purpose instead of the LEED-India rating system.

Indian industry professionals have identified lack of incentives as a critical barrier to the adoption of green building guidelines. While tax rebates and incentives are planned and announced with good intentions, their implementation has not occurred on a widespread level. It is uncertain how soon tax rebates and incentives will be implemented in a manner that can mobilize the green building industry. This uncertainty is mostly due to a general apprehension about doling out subsidies to the private sector (Arif et al. 2009, Arif et al. 2010, Potbhare et al. 2009a, Kumar et al. 2010).

Adoption in ChinaIn recent years, the Chinese government has been actively promoting several green building movement by implementing green building standards and guidelines (Hui-feng et al. 2012). The Green Building Label is administered by a governmental organization, therefore, the government is considered a strong supporter of the green building guidelines. In 1998, China’s Ministry of Science and Technology partnered with US Department of Energy to build an energy efficiency demonstration project in Beijing in order to guide China’s building industry toward energy efficient design and construction (PRC 2012). Subsequently, the government invested heavily in the construction of several demonstration projects. Two demonstration projects include the Office Building of Green Building Engineering Research Center of Shanghai, built in 2004, and the Shanghai Historic Protection Wenyuan Building at Tongji University, built in 2007 (Chinese Urban Studies 2009).

Similar to USA and India, China has been developing a system of administrative infrastructure to engage in green building education. China’s Green Building Council has numerous resources and seeks to conduct research, compile academic publications, provide consulting services, and organize education programs

and public outreach (China GBC 2013). China’s 12th Five Year Plan for sustainability speaks to the emerging nature of China’s green supply chain and identifies energy efficient products, services, and financing as a potential opportunity for improvement (KPMG 2012).

China’s socialist government structure influences the amount of government regulation in the green building movement. This can be seen in the nationwide energy goals that China has amended. By 2020, China plans to reduce its carbon emissions per unit of GDP by 40-45% of the 2005 levels. In 2005, the Ministry of Housing and Urban-Rural Development issued a building code at the national level called the “Design Standard for Energy Efficiency of Public Buildings.” The primary objective of the code was to ensure that buildings meet minimal energy performance (GBPN 2013b). In 2007, MOHURD released a stricter building code called the “Acceptance of Energy Efficient Building Construction” for all residential and commercial buildings (Miao et al. 2009).

China’s current policy toward adoption of green building guideline is to encourage rather than impose a mandatory requirement. Because the awareness of green buildings has not been formed in the market until recent years, the Chinese government has published a range of measures and incentives to encourage green building projects. Incentives in the form of tax rebates, discounted premiums, and floor area ratio increases have been offered to promote economic opportunities for energy-efficient building and green technology investments. Despite these instances, most developers have not shown strong interest in adopting green building guidelines mainly because China’s regular construction codes are considered less stringent than the green building codes (Jun 2006, Hui-feng et al. 2012, Miao et al. 2009).

COMPARISON OF GBGS ADOPTION IN USA, INDIA AND CHINA

There are many differences in the adoption of green building guidelines in each country as shown in Table 2. While there is evidence of the desired adoption elements, there are many gaps in the literature among the three countries with regards to the supporters and the infrastructure to support growing interest in green buildings. The green building councils in each country provide information where individuals can find educational tools and engage in communities related to the green building movement.




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Even with each guidelines being voluntary in nature, implementation methods in each country differed mainly due to the societal awareness and the government influence. India mandated that all federal government buildings be certified using the GRIHA system and some state and local governments also mandated the adoption of GBGs for publically funded buildings. China does not have any mandate for public buildings but has stricter

governmental goals and accompanying regulations. USA took a less regulatory approach at the federal level, but many state and local governments mandate implementation of green building guidelines and/or energy codes. Some jurisdictions in the United States adopted regulations that mandate the implementation of the LEED-USA system, although certification is not always mandated.

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Table 2 : Comparison of GBGs Adopt ion in USA, India , and China

Country USA India China

Green Building Guideline LEED LEED-India GBL

Date Adopted 2000 2003 2006

Parent Organization United States Green Building Council

Indian Green Building Council

Ministry of Housing Urban - Rural Development and China Green Building Council

Support

Green Building Supporters

• State and Local Governments

• Cities • Universities • Architects,

engineers, contractors

• Environmental groups

• Sustainable building consultants

• Architects and engineers

• Large businesses • Multinational

corporations • Environmental

groups • The media • Non-governmental

organizations

• Central Government • Provincial

Government • Architectural

Research Institute • Universities • Foreign Joint

Venture Companies

Infrastructure Education • Certification

• Seminars / Lectures

• Conferences

• Seminars/Lectures • Conferences • Classes • Workshops • Certification

• Degree Programs • Professional

Certification • Seminars/ Lectures • Conferences

Literature • Guidelines • Peer Reviewed

Research • Reports • Websites

• Periodicals • Magazines • Peer Reviewed

Research • Websites

• Peer Reviewed Research

Green Supply Chain Developed Developing Developing Implementation

Governmental Type Democratic Democratic Republic Socialist

National Sustainable Building Codes

International Green Construction Code

Energy Conservation Building Code

Design Standard for Energy Efficiency of public buildings

Selective Mandatory Adoption for Government Buildings

* Selected Government Funded Buildings

** All Federal Government Buildings

No mandate for government or publically funded buildings

Incentives Offered

• Tax rebates • Subsidies • Grants • Expedited

Permitting • Fee waivers • Floor Area Ratio

• Tax rebates • Subsidies • Grants • Fee waivers • Floor Area Ratio

• Tax rebates • Subsidies • Grants • Fee waivers

* Mandatory compliance with guidelines but certification not always required, ** Used with GRIHA rating system

Table 2: Comparison of GBGs Adoption in USA, India, and China




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With a growing need to implement sustainable building practices in developing and developed countries, the adoption of green building guidelines has become an important area of focus worldwide. As shown in Table 1, each country’s GBGs have a focus on indoor environmental quality and reduction of water, energy, and materials. Each offers the precertification that is evaluated at the end of the design phase and the final certification evaluation that is offered after the completion of construction. The methods of evaluation are where differences start to become apparent.

The LEED-USA and LEED-India systems share many similarities in the environmental categories that are different from GBL-China. Alternatively, the GBL has an unique focus on “Operations and Management” that the LEED systems do not have. Each system utilizes a third-party agency to carry out evaluations. The LEED-USA and LEED-India systems each have a non-profit organization assigned to this task, while the GBL has three governmental agencies. Finally, the LEED systems allow a building to be evaluated right after the building is completed, but the GBL requires occupancy and operation of a building for at least one year before a building can be evaluated.

CONCLUSIONS

Green building guidelines are considered to be an innovative tool for the spread of sustainable practices in the built environment industry. The theory of the Diffusion of Innovation identifies five different groups of adopters of an innovation; innovators, early adopters, early majority, late majority, and laggards. The individuals that serve as “innovators” and “early adopters” can vary in different societies. For this study, these two adoption groups were referred to as supporters of the green building movement. In India, sustainable building consultants, architects and engineers, large businesses, multinational corporation’s houses, environmental groups, the media, and non-governmental organizations act as supporters. State and local governments, cities, universities, architects, engineers, contractors, and environmental groups sever as supporters in the United States. In China, the main supporters are governmental agencies, universities, and foreign joint venture companies. Access to information infrastructure, individuals, and materials to support growing interests in the green building guidelines are important components of

adoption. Each country has supporting educational resources, communities, literature, and building materials to aid in implementation.

The voluntary nature of each of the guidelines only allows for enforcement of the voluntary adopters except in the case of a government mandate. Some jurisdictions in the United States have decided to make LEED compliance, rather than certification, mandatory for government-funded buildings. In India, the federal government created a policy that allows states to mandate that all government buildings be GRIHA certified. Eight states have already adopted this policy. In China, the government has set stricter green building goals and has issued corresponding regulations. All three countries offer incentives in the forms of grants, subsidies, and tax rebates.

This research provided an overview and comparison of major green building guidelines and their adoption in USA, India, and China. The research team chose these specific countries and associated green building guidelines (GBGs) because each presents a unique set of societal attributes related to the green building movement. Based on the evaluation and comparison of GBGs in these countries, following inferences can be made:• All major GBGs have key common elements towards

sustainable building design, construction, and operations. These include indoor environmental quality, reduction in water usage, energy efficiency, and responsible use of materials.

• LEED guidelines developed by USGBC have served as a catalyst for the development of GBGs in several countries

• A key factor for increasing the adoption of GBGs is the identification, nurturing, and expansion of supporters (innovators and early adopters)

• The pressure for adoption depends on a combination of societal awareness, building owners’ demands, and governmental incentives and/or requirements.

The adoption of green building guidelines can greatly influence the long term development plans of a country. The adoption of green building design, construction and operation practices is growing worldwide. If a country adopts green building practices, its society will use less energy, save more resources, cultivate healthier environments and leave a better planet for future generations.




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Solar Orientation for Low-Energy Residential Building in Pagosa Springs, Colorado

Torry D. Hessman, MSColorado State University | [email protected]

Caroline M. Clevenger, PhDColorado State University | [email protected]

MaryEllen C. Nobe, PhDColorado State University | [email protected]

Katharin Leigh, PhDColorado State University | [email protected]

ABSTRACT: This research compares the energy performance of 43 homes. Seven homes, constructed by a single builder using passive design principles, are the focus of the study. The remaining 36 homes, more conventionally built, establish a baseline for local residential energy performance. All of the homes are located within a six square-mile geographical region in Pagosa Springs, Colorado. Researchers collected utility data over a two year period, from September 2009 to August 2011. While other factors impact performance, for this study the dependent variable was energy consumption in British Thermal Units (BTUs) per square foot per season. The independent variable was solar orientation of largest glazing area for the seven passive design homes. The use of a single geographical area eliminated any influence of climate variation on energy performance.

When comparing test cases of passive houses to conventionally constructed homes, analysis of real-world data demonstrated solar orientation has significant impact on the homes’ energy performance. Specifically, the research provides evidence that proper solar orientation in similarly constructed homes provides benefits during all four seasons in the geographical region tested. The primary contribution of this research is to provide evidence for and to quantify the potential value of using a residential contractor with expertise in solar design in a designated cold-climate region. The research findings provide a model for other builders seeking evidence-based means to justify and highlight trade-offs and advantages of passive design and construction.

Torry Hessman is a residential designer and builder in Pagosa Springs, Colorado. He completed his bachelor’s degree at Kansas State University’s College of Architecture, Planning and Design in 1993 and completed a master’s degree from Colorado State University in Construction Management in spring, 2014. His passion for sustainable and passive design and use of natural resources to improve the performance of structures is evident in the homes he designs and builds.

Dr. Caroline M. Clevenger is an Assistant Professor of Construction Management at Colorado State University. Caroline’s background includes work as a professional consultant in sustainable design and construction. Her research focuses on developing theories, methods, and tools for multidisciplinary systems thinking in high-performance building. She is a Registered Architect and Licensed Engineer in the State of Colorado.

Dr. MaryEllen C. Nobe is an Assistant Professor at Colorado State University. Her primary areas of research are human dimensions of construction management, management of sustainable construction, land development, and construction economics.

Dr. Katharine Leigh is Professor in the Department of Design and Merchandising at Colorado State University. As a LEED Accredited Professional, her research encompasses sustainable practice through design and construction practices. Her primary research areas include sustainable practice, creativity, and evidence-based design.








48 Solar Orientation for Low-Energy Residential Building in Pagosa Springs, Colorado

Key Words: Solar Orientation, Passive Design, Residential Construction, Energy consumption

INTRODUCTION

Energy efficient buildings offer both tangible and intangible energy, economic, and environmental benefits. According to the United States Department of Energy, a significant correlation exists in building energy use and environmental pollutants (USDOE 2011). Energy use from U.S. residential buildings produces 17% or 1.12 billion metric tons of all CO， emissions per year (Howard 2008). While the marketplace does not guarantee, nor necessarily promote, energy efficient design and construction, operating costs of spaces built to higher energy efficiency standards are typically lower, resulting in a direct savings to homeowners (USDOE 2011). Passive solar design utilizes the sun’s energy, together with local climate characteristics and select building materials, to directly maintain thermally comfortable conditions within a built environment (Rabah 2004).

Passive design is defined as a well-insulated, air-tight building primarily heated by passive solar gain. Research findings support passive design is a significant contributor to thermal performance and resulting in higher energy efficiency (Givoni 1991). Heat from solar gain is a key factor in passive design withpassive standards provided by the Passive House Institute. A national leader in designing low energy buildings, the institute requires specific minimum energy limits. To meet Passive House standards, total primary energy use can be no greater than 38,000 Btu/ft²/yr (120 kWh/m²/year) for all energy needs, including water heating, lighting, and plug loads (Wilson 2010). More specifically, the performance criteria for Passive House certification allows for a maximum of 4,750 Btu/ft²/year for heating or cooling energy (Passive House Institute US 2011). The Passive House standards represent today’s highest energy standard with the potential to slash the heating energy consumption of buildings by 90% (Passive House Institute US2011). While Passive House standard is gaining momentum in Europe, it has been slower to catch on in the U. S. Furthermore, while Passive House performance is clearly defined and quantified, the impact of less stringent, market-driven passive solar design as currently built in various locations around the U. S. is not well-documented.

A review of energy use in the residential buildings by Sartori and Hestnes (2006) concludes when compared to an equivalent conventional building, a passive design required only slightly more embodied energy (the energy needed to manufacture and install building materials) to construct, while reducing the total energy needed to operate by a factor of three. A 1985 study on the benefits of solar orientation to reduce energy consumption by Andersson et al. found in northern climates in the United States, total energy loads were significantly lower when the structure’s primary glazing was orientated to the south. In the southern climates of the United States, glazing with primarily north orientation produced lower total loads than east, west, and south orientations. An Australian study by Morrisey, Moore, and Horene (2010) suggests design, orientation, and size of the dwelling all impact energy costs. Other research suggests building energy savings is in the range of 30%-70% for design solutions integrating high-performance building envelope components for roofs, walls, windows, and doors (Griffith et al. 2005). In the construction of low energy housing, the building envelope requires high thermal performance insulation material to reduce the structure’s heat loss. Further, air-tight construction methods such as caulking joints and gaps, and closing and insulating thermal breaks in the building envelope lower ventilation heat loss (Noguchi et al. 2008).

The greatest opportunities for integrating energy reducing strategies occur during conceptual design. Proper selection of design parameters such as shape, orientation, and envelope configuration can result in higher-quality buildings which can consume 40% less energy than low-quality ones (Wang, Rivard, & Zmeureanu 2006). The National Association of Home Buildings suggests glazing orientation that is within 15 degrees of true south is optimal; up to 30 degrees off, although less effective, still provides substantial solar contributions (NAHB 2010; USDOE 2000). This research seeks to test and quantify such impacts using real-world homes, constructed by a single contractor experienced in designing and building high performance residences for a cold climate.

This study compares actual utility and cost data to examine the effects of solar orientation for houses constructed with passive design to assess if, and to what extent, solar orientation impacts energy efficiency of the structure when compared to traditionally constructed



49

homes. Findings validate previous research but also, more importantly may assist local architects, designers and homeowners in determining the preferred glazing orientation. Specifically, the study will serve to validate and quantify the value of construction using passive design principles in the cold climate of Pagosa Springs, Colorado using today’s utility prices. Of note, a large portion of Pagosa Springs’ mountain views face north and east; and most residential designs, therefore, orient glazing on the north side of the structure to acquire the views. This study is meaningful because in such a region it is important for builders and homeowners alike to know the value of passive design and its associated southern orientation, particularly when it may require real-world trade-offs such as reduced access to desirable views. The seven test homes demonstrate a range of solar orientations (see Table 1), but generally face either north or south. The following sections present detailed characteristics of the houses and analysis of their actual performance.

Research QuestionThe research question motivating this study is: what is the impact of solar orientation on seven test homes constructed using passive design principles in Pagosa Springs, Colorado? Specifically, the study investigates how Btu/sqft/season energy usage for the test homes varies relative to an established baseline depending on the orientation of the primary glazing.

METHODOLOGY

The authors used a survey instrument to gather data about residential energy use. Colorado State University’s Internal Review Board (IRB) approved the protocol, and the authors collected data through voluntary participation from the seven test homeowners as well as a convenience sample of other community homeowners (living in more traditional houses) in Pagosa Springs, Colorado. All seven test home homeowners participated (100% response rate). 250 surveys were distributed through local churches, friends, acquaintances and co-workers. Thirty-six (36) local homeowners responded (17% rate of response); data was used to generate a generic profile for baseline energy use in the region. Orientation data was not collected for these 36 homes because the baseline is intended to be orientation agnostic. In other words, the study seeks to determine the value of passive design principles and associated orientation versus traditional

orientation which generally ignores orientation.

The surveys gathered information on utility data, and sought to identify the presence of energy consuming behaviors or activities by occupants with the potential to skew the energy use data (e.g., welding, pottery, window-opening, and above residential standard electrical equipment use). The survey contained questions about energy supply and relevant personal behaviors including wood-burning fireplaces, thermostat settings, and extended absences from the residence. Respondents for both the test homes and the baseline homes also provided copies of electric and propane utility bills for each month from September 2009 through August 2011.

During analysis, the information was parsed quarterly to reveal energy use during fourl seasons (fall, winter, spring, and summer) over the two year (24 month) study period. Energy use data was standardized to units of Btu’s by converting electric kilowatt hours (kWh) and propane gallons into Btu to determine total amount of Btu used in each residence test period. The U.S. Energy Information Administration conversion calculator assumes the amount of Btu’s in a gallon of propane to be 91,330 (20% less efficient at 7,000 feet in elevation equaling 73,064 Btu’s) and the amount of Btu’s in one kWh of electricity to be 3,412 (USEIA 2012). Next, energy usage in Btu’s was divided by living square feet to normalize data across different residence sizes. This net living square feet area excluded porches, patios, decks, garages, unfinished basements, and attic space. The Archuleta County assessor’s records were used to determine the living square foot of the baseline residences and an average square foot size was calculated. Finally, the mean Btu/sqft/season was generated and an analysis of variance (ANOVA) conducted.

LimitationsThe relatively small sample size and short duration of data collection, consisting of seven test homes and 36 traditional homes to define a baseline over a two year period, limits the establishment of statistical significance and generalizability of findings. The study includes only homes that use electricity and/or propane for their energy supply. Homes using natural gas were excluded in order to maintain consistency across energy type. Solar orientation and glazing information for the 36 baseline homes was excluded from the study; traditional home construction typically




50

does not take orientation into consideration. The authors acknowledge exclusion of the orientation of the traditional homes in the baseline profile may result in a small impact on findings with a number of traditional homes potentially facing north. However, based on the authors’ high degree of familiarly with the area, this bias was assessed to be of small significance.

A potentially significant factor is occupant behavior. Occupant behavior varies and can impact the setting and programming of thermostats, levels of light usage, hot water use patterns, and the use and number of electric devices (Vieira 2006). Such variability in occupant behavior can significantly influence energy consumption across households. Therefore, information was gathered concerning occupant behavior for both test and baseline homes. Specifically, the study collected information on the number, schedule, temperature preferences, and typical activities of the occupants in the test and baseline homes. However, the amount of firewood used in each home was not included in the energy usage calculations due to the irregularity of use by occupants and difficulty in calculating exact amounts of cordage in one year. In addition, insulation levels were not included in the analysis given the limitations in the scope of research. In conclusion, the authors acknowledge that a high number of unanalyzed factors may exist which influence the results of the research. The value of the research lies mainly in detailed reporting and discussion regarding the performance of several real world case studies with similar characteristics, built by the same builder in the same geographical area rather than the completion of an exhaustive statistical study of these buildings.

Climate ImpactClimate is the most significant factor determining how much heating and cooling a house will require (EIA 1994). Collecting performance data in one geographical region over the same two year period minimized variation in climate across residences. Pagosa Springs is defined by the Department of Energy as a cold region climate, Zone 6, experiencing between 5,400 and 9,000 heating degree days (65°F basis) annually (USDOE 2010). A degree-day is the difference in temperature between the mean (average) outdoor temperature over a 24-hour period and a given base temperature for a building space, typically 65°F (Pacific Northwest National Laboratories & Oakridge National Laboratories 2010). In the cold region of Pagosa Springs, heating the

home is the greatest energy use. The average building elevation is 6,000 to 10,000 feet (City-data 2011), the average precipitation for the area is 17.35 inches, with the average snowfall in town 67.4 inches (Pagosa Springs 2010). During the research period the average high temperature was 43.5°F with the warmest month July 2011 averaging 68.4°F. The average low temperature during the two year period was 30.31°F with the coldest month January 2011 averaging 8°F.

Sample DescriptionForty-three (43) residences in Pagosa Springs, Colorado, were studied encompassing thirty-six (36) traditional homes built by various builders over an unknown period of time and seven (7) test homes (referenced as T1, T2, T3, T4, T5, T6, and T7) built by a single builder and completed between 2003 to 2009. Pagosa Springs is a community experiencing an influx of second home-owners. Traditional homes used to represent the control group ranged in size from 600 sqft to 2,944 sqft, and included a mix of primary and secondary residences. In general, the traditional homes were constructed using 2x4 or 2x6 exterior envelope framing and a truss system on the roof leaving a cold vented opening between the roof and the ceiling. Exterior walls were typically filled with R-19 batt-insulation and the attic area contained either batt-insulation or blow-in cellulose insulation ranging in level from R-29 to R-35. Furthermore, theses traditional homes typically have a forced air heating system, no air conditioning unit, and a 30 gallon hot water heater.

The design and construction of each of the seven test homes varied in solar orientation and construction details. Of the seven test homes, six were designed by the builder and one by a local architect. T1, T2, and T3 were constructed with 2x6 exterior wood wall framing and BCI or truss roof framing. The exterior bays were filled with a polyurethane closed cell spray foam insulation with R-values roughly 6.0 per inch (Fomo Products Inc 2012) averaging an R30 in the roof and R19 in the exterior walls. T4, T5, and T6 were constructed using structural insulated panel (SIP) technique in the exterior walls and roof. SIPs are constructed of polyurethane class 1 insulation bonded and sandwiched between two 7/16” OSB, the panels are built specific to each home design to slide together with 2x4 wood splines for rigid construction with minimal thermal breaks or penetrations. The 6 ½” SIP provides an R41 and the 4 ½” SIP provides R27 in insulation value (Janzen Construction LLC 2008).




51

T7 uses a wood post and beam structure in-filled with 17” straw bale sealed with stucco and lime plaster, averaging a 2.38 per inch R-value (Building Green.com 2013) creating an R40 insulation value, the roof is framed using BCI and filled with R30 polyurethane spray foam insulation. These test homes represent leading materials and construction strategies for high quality passive design in cold climates.

Construction cost information was not available for the baseline homes; however, the contractor estimates the test homes had similar construction costs to the traditional homes since higher material costs (for SIPs) were generally off-set with lower labor requirements and costs. Table 1 summarizes the characteristics of the seven test homes including maximum glazing orientation, square foot of glazing, fireplace usage and the insulation value for walls and roofs.

Figu

re s 1 -7

illus tra t e t he

primary g lazed areas of t he seven t e s t homes s t udied .

House # Year Built

Orient-ation

Max Glazing SF

Living SF

Occup-ants

Temp Heat System Fireplace

Insu- lation Walls

Insu-lation Roof

T1 2007 SW 189 2677 2 68°

Radiant propane, not used

Foam R19

Foam R30

T2 2008 SE 246 2103 2 69°

Radiant wood, 1/2 cord/yr

Foam R20

Foam R30

T3 2007 N 200 2216 2 66°

ETS Air wood, 1/2 cord/yr

Foam R19

Foam R30

T4 2004 SE 249 2085 2 61°

Radiant propane, not used

SIP R41

SIP R41

T5 2009 S 147 2058 1 68°

Radiant wood, not used

SIP R41

Foam R30

T6 2005 N 258 1763 1

61° Forced

Air wood, 1 cord/yr

SIP R27

SIP R41

T7 2006 N 172 1722 2 69°

Radiant

wood, 1 1/2-2 cord/yr

Straw R40

Foam R30

Baseline Varies Varies Varies 2021 2 65° 13 out of 36 Varies Varies

Table 1. Building Characteristics of Test HomesFigures 1-7 illustrate the primary glazed areas of the seven test homes studied.

Figures 1-7 illustrate the primary glazed areas of the seven test homes studied.

Figure 1: House #1 (T1) Figure 2: House #2 (T2)

Fig ure 1 : Ho us e # 1 ( T1 )

















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FINDINGS This study sought to examine the impact of solar orientation for houses designed and constructed using passive design principles relative to each other and to the baseline profile of traditional hones in Pagosa Springs, Colorado. By studying seven test homes representing diverse passive design strategies, built by the same contractor in one climate, for a variety of residents who shared certain community-based similarities and expectations, the seven test homes

provide valuable, full scale, real-world evidence that can be used by builders and home-owners to support consumer decisions with regard to purchasing a home using passive design strategies. The following tables and figures provide a variety of comparisons between test and baseline home performance.

Table 2 shows the total energy usage normalized by sqft for the seven test homes and the average baseline home over the 24 month period recorded.

Figure 3: House #3 (T3)











































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Table 2. Normalized Btu/sqft Energy Use (24 month period)

Average consumption by season was compared in table 3 showing the average Btu/sqft/seasons for both baseline and test homes. The summer mean for the test home energy usage reflected a mean of 1178 Btu/sqft/season (SD = 655 Btu/sqft/season over a two-year period. Means for the test homes were consistently lower than summer baseline mean energy usage (M = 1980 Btu/sqft/season; SD=853 Btu/sqft/season). Analysis of variance (ANOVA) results indicated the differences for the summer season F(1, 43) = 5.512, p = .024, suggesting statistical significance. Specifically, the average energy usage for the test homes was 41% less during the summer season than the average energy usage for the baseline homes. This suggests an overall trend of test homes using less energy than the baseline homes year-round; only the summer months demonstrated statistical significance.

Table 3. Mean Btu/sqft Energy Use by Season and Percent Relative to Baseline Homes

Figure 8. Comparison of test homes and baseline Mean Btu/sqft/season energy use

Figure 9 depicts the median Btu/sqft/season energy performance of the seven test homes (according to orientation) and baseline.

Figure 9. Mean Btu/sqft energy for seven test homes and baseline by season)

Data indicate north facing T6 exhibited the lowest energy usage during spring and summer seasons. By contrast T3, also north facing, had very high energy use during spring and summer seasons suggesting occupant behavior may be influencing performance. Results also indicate south facing T5 had the lowest energy usage over three seasons except fall when the three north facing test homes demonstrated slightly lower than average energy usage. Test homes generally used less energy than baseline during every season during the data collection period with the exception of north facing T3 and T7 for specific seasons.

DISCUSSION

While seasonal variation exists in utility usage, data for the south facing T5 indicated having the primary glazing face south to be beneficial throughout the year. Specifically, the findings demonstrated substantial energy savings based on solar orientation were possible during summer and winter seasons. These findings begin to guide conclusions about optimal orientation for primary glazing in passive design for the particular geographic location and climate of this study.

In the cold climate of Pagosa Springs, where air conditioners are rarely used and energy sources, such as propane, are priced higher during the winter, a southern orientation to gain passive solar greater economies. The higher energy usage for the north facing

FINDINGS This s t udy sought t o examine t he impact of so lar orient at ion for houses de s igned and cons t ruct ed us ing pass ive de s ign princip le s re la t ive t o each ot he r and t o t he base line profile of t radit ional hones in Pagosa Springs , Colorado. By s t udying seven t e s t homes repre sent ing d ive rse pass ive de s ign s t ra t eg ie s , built by t he same cont rac t or in one c limat e , for a varie t y of re s ident s who shared ce rt a in communit y-based s imilarit ie s and expect at ions , t he seven t e s t homes provide valuable , full s cale , re al-world evidence t hat can be used by builde rs and home-owners t o support consumer decis ions wit h regard t o purchas ing a home us ing pass ive de s ign s t ra t eg ie s . The fo llowing t able s and figure s provide a varie t y of comparisons be t ween t e s t and base line home pe rformance . Table 2 shows t he t o t a l ene rgy usage normalized by sqft for t he seven t e s t homes and t he ave rage base line home ove r t he 2 4 mont h pe riod recorded. Ta b le 2 . No rm a liz e d Bt u/ s q f t Ene rg y Us e ( 2 4 m o nt h p e rio d )

House # Orientation Normalized Btu/sqft Energy Use (24 mo.)

T1 SW 25,974 T2 SE 23,620 T3 N 34,309 T4 SE 25,328 T5 S 12,650 T6 N 15,431 T7 N 26,052 Baseline Varies 29,133 Average consumpt ion by season was compared in t able 3 showing t he ave rage Bt u/ sqft / seasons for bot h base line and t e s t homes . The summer mean for t he t e s t home ene rgy usage re fle c t ed a mean of 1 1 7 8 Bt u/ sqft / season (SD = 6 5 5 Bt u/ sqft / season ove r a t wo-year pe riod . Means for t he t e s t homes we re cons is t ent ly lower t han summer base line mean ene rgy usage (M = 1 9 8 0 Bt u/ sqft / season; SD=8 5 3 Bt u/ sqft / season) . Analys is of variance (ANOVA) re sult s indicat ed t he d iffe rences for t he summer season F(1 , 4 3 ) = 5 .5 1 2 , p = .0 2 4 , sugges t ing s t a t is t ical s ignificance . Specifically, t he ave rage ene rgy usage for t he t e s t homes was 4 1 % le s s during t he summer season t han t he ave rage ene rgy usage for t he base line homes . This sugges t s an ove rall t rend of t e s t homes us ing le s s ene rgy t han t he base line homes year-round; only t he summer mont hs demons t rat ed s t a t is t ical s ignificance . Ta b le 3 . Me a n Bt u/ s q f t Ene rg y Us e b y S e a s o n a nd Pe rc e nt Re la t iv e t o Ba s e line Ho m e s Season Baseline Test Homes Btu/sqft M SD M SD p-value % Baseline Fall 2962 1887 2282 632 0.355 -23% Winter 5842 2988 4864 1531 0.406 -17%

FINDINGS This s t udy sought t o examine t he impact of so lar orient at ion for houses de s igned and cons t ruct ed us ing pass ive de s ign princip le s re la t ive t o each ot he r and t o t he base line profile of t radit ional hones in Pagosa Springs , Colorado. By s t udying seven t e s t homes repre sent ing d ive rse pass ive de s ign s t ra t eg ie s , built by t he same cont rac t or in one c limat e , for a varie t y of re s ident s who shared ce rt a in communit y-based s imilarit ie s and expect at ions , t he seven t e s t homes provide valuable , full s cale , re al-world evidence t hat can be used by builde rs and home-owners t o support consumer decis ions wit h regard t o purchas ing a home us ing pass ive de s ign s t ra t eg ie s . The fo llowing t able s and figure s provide a varie t y of comparisons be t ween t e s t and base line home pe rformance . Table 2 shows t he t o t a l ene rgy usage normalized by sqft for t he seven t e s t homes and t he ave rage base line home ove r t he 2 4 mont h pe riod recorded. Ta b le 2 . No rm a liz e d Bt u/ s q f t Ene rg y Us e ( 2 4 m o nt h p e rio d )

House # Orientation Normalized Btu/sqft Energy Use (24 mo.)

T1 SW 25,974 T2 SE 23,620 T3 N 34,309 T4 SE 25,328 T5 S 12,650 T6 N 15,431 T7 N 26,052 Baseline Varies 29,133 Average consumpt ion by season was compared in t able 3 showing t he ave rage Bt u/ sqft / seasons for bot h base line and t e s t homes . The summer mean for t he t e s t home ene rgy usage re fle c t ed a mean of 1 1 7 8 Bt u/ sqft / season (SD = 6 5 5 Bt u/ sqft / season ove r a t wo-year pe riod . Means for t he t e s t homes we re cons is t ent ly lower t han summer base line mean ene rgy usage (M = 1 9 8 0 Bt u/ sqft / season; SD=8 5 3 Bt u/ sqft / season) . Analys is of variance (ANOVA) re sult s indicat ed t he d iffe rences for t he summer season F(1 , 4 3 ) = 5 .5 1 2 , p = .0 2 4 , sugges t ing s t a t is t ical s ignificance . Specifically, t he ave rage ene rgy usage for t he t e s t homes was 4 1 % le s s during t he summer season t han t he ave rage ene rgy usage for t he base line homes . This sugges t s an ove rall t rend of t e s t homes us ing le s s ene rgy t han t he base line homes year-round; only t he summer mont hs demons t rat ed s t a t is t ical s ignificance . Ta b le 3 . Me a n Bt u/ s q f t Ene rg y Us e b y S e a s o n a nd Pe rc e nt Re la t iv e t o Ba s e line Ho m e s Season Baseline Test Homes Btu/sqft M SD M SD p-value % Baseline Fall 2962 1887 2282 632 0.355 -23% Winter 5842 2988 4864 1531 0.406 -17%

Fig ure 8 . Co m p a ris o n o f t e s t ho m e s a nd b a s e line Me a n

Bt u/ s q f t / s e a s o n e ne rg y us e

Figure 9 depic t s t he median Bt u/ sqft / season ene rgy pe rformance of t he seven t e s t homes (according t o orient at ion) and base line .

Fig ure 9 . Me a n Bt u/ s q f t e ne rg y f o r s e v e n t e s t ho m e s a nd b a s e line

b y s e a s o n

Spring 3773 2229 3345 1745 0.635 -11% Summer* 1980 853 1178 655 0.024 -41%





b y s e a s o n

Spring 3773 2229 3345 1745 0.635 -11% Summer* 1980 853 1178 655 0.024 -41%





b y s e a s o n

Spring 3773 2229 3345 1745 0.635 -11% Summer* 1980 853 1178 655 0.024 -41%




54

homes in the spring and summer seasons are likely due to cool evening temperatures in Pagosa Springs. During the study period the average low springtime temperature was 25.5°F with average springtime high temperature 37.8°F. Without solar gain to warm residence interiors, heaters would need to comfortable interior temperature levels. This study indicated energy consumption for north facing houses varied, inviting the need for future research to examine the impacts of construction type and occupant behavior with a range of solar orientations using passive designs.

During the process of compiling and comparing the normalized Btu/sqft/season usage of the seven test homes, T1 and T3 stood out as using large amounts of energy; T1 is the largest house by square footage withT3 the next largest. Both homes have similar construction material attributes, with the primary difference that T1 faces southwest and T3 faces north. T3 reports the highest Btu use/sqft/season and is the only home of the test homes using Electric Thermal Storage (ETS) heating system provided through the La Plata Electric Association (LPEA).

Energy use and energy cost profiles can differ based on energy type, time of usage, and utility rate structures. For example, by using electricity during off-peak hours (those times during the day and night when demand is lower), ETS units can provide heat at lower costs,

while consuming more units of energy, relative to other heating systems. During off-peak hours, the ETSs heating elements convert electricity to heat stored in high density ceramic bricks. The bricks are surrounded by high efficiency insulation which allows them to hold great amounts of heat for long periods of time. A fan evenly distributes the heat to the home during higher cost, on-peak hours (LPEA 2012). During on-peak usage, the rate per Btu is higher than during off-peak usage. However, the majority of energy consumption for T3 occurs during off-peak periods in order to minimize costs. Research findings confirm ETS systems can successfully provide the capability to shift electrical loads from high-peak to off-peak hours by reducing spikes in demand during the day. (Arteconi, Hewitt, & Polonara 2012). However, spikes (peak usage) are used by the utilities companies to determine rates. In Pagosa Springs, to encourage reduced spikes over a 24 hour period, LPEA charges significantly less for energy used during the night and off-peak hours.

As a result, the average cost for T3 energy consumption was .000048¢ per Btu, the other test homes average cost per Btu ranged from .000064¢ for T4 to .000086¢ for T5. Therefore T3 experienced similar overall costs for energy, within the average of the other test homes costs, although the total Btu/sqft consumption was 45% higher during the study period than the average Btu/sqft use of the other test homes.

e lement s conve rt e lec t ric it y t o heat s t ored in high dens it y ce ramic bricks . The bricks are surrounded by high e ffic iency insulat ion which allows t hem t o hold great amount s of heat for long pe riods of t ime . A fan evenly d is t ribut e s t he heat t o t he home during highe r cos t , on-peak hours (LPEA 2 0 1 2 ) . During on-peak usage , t he ra t e pe r Bt u is highe r t han during off-peak usage . Howeve r, t he majorit y of ene rgy consumpt ion for T3 occurs during off-peak pe riods in orde r t o minimize cos t s . Research findings confirm ETS sys t ems can success fully provide t he capabilit y t o shift e le c t rical loads from high-peak t o off-peak hours by reducing spike s in demand during t he day. (Art econi, Hewit t , & Polonara 2 0 1 2 ) . Howeve r, sp ike s (peak usage ) are used by t he ut ilit ie s companie s t o de t e rmine ra t e s . In Pagosa Springs , t o encourage reduced spike s ove r a 2 4 hour pe riod, LPEA charges s ignificant ly le s s for ene rgy used during t he night and off-peak hours . As a re sult , t he ave rage cos t for T3 ene rgy consumpt ion was .0 0 0 0 4 8 ¢ pe r Bt u, t he o t he r t e s t homes ave rage cos t pe r Bt u ranged from .0 0 0 0 6 4 ¢ for T4 t o .0 0 0 0 8 6 ¢ for T5 . The re fore T3 expe rienced s imilar ove rall cos t s for ene rgy, wit hin t he ave rage of t he o t he r t e s t homes cos t s , a lt hough t he t o t a l Bt u/ sqft consumpt ion was 4 5 % highe r during t he s t udy pe riod t han t he ave rage Bt u/ sqft use of t he o t he r t e s t homes .

Fig ure 1 0 . Av e ra g e t o t a l ut ilit y c o s t s o f t e s t ho m e s a nnua lly

Ta b le 4 . Te s t Ho m e s Ac t ua l Ene rg y Co s t s

$-

$500.00

$1,000.00

$1,500.00

$2,000.00

$2,500.00

$3,000.00

$3,500.00

T1(SW) T2(SE) T3(N) T4(SE) T5(S) T6(N) T7(N)

Test Homes Utility Cost per Year

2010 2011

House # Orie nt a t io n

Sep 2 0 0 9 – Aug 2 0 1 0

Sep 2 0 1 0 – Aug 2 0 1 1

Tot al 2 4 Mont h Ut ilit y

Normalize Ene rgy Cos t /

Figure 10. Average total utility costs of test homes annually




55

Figure 10 and Table 3 show actual expenditures for electrical and propane for the seven test homes. Actual normalized energy costs (Table 4) track fairly closely to normalized energy usage (Table 2). However, usage and cost trends demonstrate a higher degree of variability for houses with a primary northern exposure, but more consistently align with expectations for primary southern exposures. Additional observations include: T1 as noted was the largest by square footage and T3 used the ETS system which uses the most Btu/sqft but is the third most economical by cost/sqft. T5 had the lowest cost/sqft and 25% more economical than the next lowest consumer, T6. T6 is an all-electric home with an electric on-demand water heater; these units are tankless and use 220 voltages for heating. T7, the smallest square foot residence, has the highest cost/sqft, almost twice the cost as T5. The residents in T1 operate a welding shop in the lower level, a 95% efficient propane hot water heating system is used to heat the entire house including the lower level metal

shop. Great care was used to monitor only the living area by using an electric metering system during the study period to minimize the effect of the welding shop on the data. However, the higher Btu/sqft/season consumption may still be due to voltage overflow from the 1,800 square foot shop.

According to the Consumer Energy Center, Ponderosa pine, abundant in the Pagosa Springs area, produce 20 million Btu per cord (California Energy Commission 2013). The occupant in T6 indicated one cord of wood is used each year; therefore the overall Btu/sqft could include an additional 1,134 Btu/sqft energy use if the amount of wood were confirmed. The wood used for T7 could add an additional 1,742 Btu/sqft to the overall Btu consumption during the study period. Figure 11 presents the range of Btu/sqft use during each season, the lowest summer use is unobservable at 2 Btu/sqft attributed to T6, while the highest energy use occurs during the winter months for the baseline, 16,476 Btu/sqft.

e lement s conve rt e lec t ric it y t o heat s t ored in high dens it y ce ramic bricks . The bricks are surrounded by high e ffic iency insulat ion which allows t hem t o hold great amount s of heat for long pe riods of t ime . A fan evenly d is t ribut e s t he heat t o t he home during highe r cos t , on-peak hours (LPEA 2 0 1 2 ) . During on-peak usage , t he ra t e pe r Bt u is highe r t han during off-peak usage . Howeve r, t he majorit y of ene rgy consumpt ion for T3 occurs during off-peak pe riods in orde r t o minimize cos t s . Research findings confirm ETS sys t ems can success fully provide t he capabilit y t o shift e le c t rical loads from high-peak t o off-peak hours by reducing spike s in demand during t he day. (Art econi, Hewit t , & Polonara 2 0 1 2 ) . Howeve r, sp ike s (peak usage ) are used by t he ut ilit ie s companie s t o de t e rmine ra t e s . In Pagosa Springs , t o encourage reduced spike s ove r a 2 4 hour pe riod, LPEA charges s ignificant ly le s s for ene rgy used during t he night and off-peak hours . As a re sult , t he ave rage cos t for T3 ene rgy consumpt ion was .0 0 0 0 4 8 ¢ pe r Bt u, t he o t he r t e s t homes ave rage cos t pe r Bt u ranged from .0 0 0 0 6 4 ¢ for T4 t o .0 0 0 0 8 6 ¢ for T5 . The re fore T3 expe rienced s imilar ove rall cos t s for ene rgy, wit hin t he ave rage of t he o t he r t e s t homes cos t s , a lt hough t he t o t a l Bt u/ sqft consumpt ion was 4 5 % highe r during t he s t udy pe riod t han t he ave rage Bt u/ sqft use of t he o t he r t e s t homes .

Fig ure 1 0 . Av e ra g e t o t a l ut ilit y c o s t s o f t e s t ho m e s a nnua lly

Ta b le 4 . Te s t Ho m e s Ac t ua l Ene rg y Co s t s

$-

$500.00

$1,000.00

$1,500.00

$2,000.00

$2,500.00

$3,000.00

$3,500.00

T1(SW) T2(SE) T3(N) T4(SE) T5(S) T6(N) T7(N)

Test Homes Utility Cost per Year

2010 2011

House # Orie nt a t io n

Sep 2 0 0 9 – Aug 2 0 1 0

Sep 2 0 1 0 – Aug 2 0 1 1

Tot al 2 4 Mont h Ut ilit y

Normalize Ene rgy Cos t /

Table 4. Test Homes Actual Energy Costs

Figure 11. Minimum and maximum seasonal Btu/sqft energy use


Sep 2009-Aug 2010

OrientationHouse # Sep 2010-Aug 2011

Total 24 Month

Utility Cost

Normalize Energy Cost/

per sqft

Figure 1 0 and Table 3 show act ual expendit ure s for e lec t rical and propane for t he seven t e s t homes . Act ual normalized ene rgy cos t s (Table 4 ) t rack fa irly c lose ly t o normalized ene rgy usage (Table 2 ) . Howeve r, usage and cos t t rends demons t rat e a highe r degree of variabilit y for houses wit h a primary nort he rn exposure , but more cons is t ent ly a lign wit h expect at ions for primary sout he rn exposure s . Addit ional obse rvat ions inc lude : T1 as not ed was t he large s t by square foot age and T3 used t he ETS sys t em which use s t he mos t Bt u/ sqft but is t he t hird mos t e conomical by cos t / sqft . T5 had t he lowes t cos t / sqft and 2 5 % more economical t han t he next lowes t consumer, T6 . T6 is an a ll-e lec t ric home wit h an e lec t ric on-demand wat e r heat e r; t he se unit s are t ankle ss and use 2 2 0 volt ages for heat ing . T7 , t he smalle s t square foot re s idence , has t he highes t cos t / sqft , a lmos t t wice t he cos t as T5 . The re s ident s in T1 ope rat e a we lding shop in t he lower leve l, a 9 5 % e ffic ient propane hot wat e r heat ing sys t em is used t o heat t he ent ire house inc luding t he lower leve l me t al shop. Great care was used t o monit or only t he living area by us ing an e lec t ric me t e ring sys t em during t he s t udy pe riod t o minimize t he e ffec t of t he we lding shop on t he dat a . Howeve r, t he highe r Bt u/ sqft / season consumpt ion may s t ill be due t o volt age ove rflow from t he 1 ,8 0 0 square foot shop. According t o t he Consumer Ene rgy Cent e r, Ponde rosa p ine , abundant in t he Pagosa Springs area, produce 2 0 million Bt u pe r cord (California Ene rgy Commiss ion 2 0 1 3 ) . The occupant in T6 indicat ed one cord of wood is used each year; t he re fore t he ove rall Bt u/ sqft could inc lude an addit ional 1 ,1 3 4 Bt u/ sqft ene rgy use if t he amount of wood were confirmed. The wood used for T7 could add an addit ional 1 ,7 4 2 Bt u/ sqft t o t he ove rall Bt u consumpt ion during t he s t udy pe riod. Figure 1 1 pre sent s t he range of Bt u/ sqft use during

Cos t pe r sqft T1 SW $ 3 ,2 8 7 .5 2 $ 3 ,1 2 5 .4 1 $ 6 ,4 1 2 .9 4 $ 2 .4 0 T2 SE $ 2 ,0 8 1 .0 0 $ 2 ,4 8 9 .1 2 $ 4 ,5 7 0 .1 2 $ 2 .1 8 T3 N $ 2 ,1 0 0 .6 8 $ 1 ,9 2 1 .6 7 $ 4 ,0 2 2 .3 4 $ 1 .8 2 T4 SE $ 2 ,2 9 7 .3 6 $ 2 ,4 3 8 .4 2 $ 4 ,7 3 5 .7 8 $ 2 .2 8 T5 S $ 1 ,5 0 5 .2 8 $ 1 ,0 3 1 .5 5 $ 2 ,5 3 6 .8 2 $ 1 .2 4 T6 N $ 1 ,5 2 4 .4 5 $ 1 ,2 8 4 .9 4 $ 2 ,8 0 9 .3 9 $ 1 .6 0 T7 N $ 2 ,0 7 4 .9 5 $ 2 ,0 9 1 .0 8 $ 4 ,1 6 6 .0 4 $ 2 .4 2

Fall Winter Spring Summer Minimum 471 1104 490 2 Maximum 10898 16476 15390 4987

0 2000 4000 6000 8000

10000 12000 14000 16000 18000

Minimum

Maximum

Minimum and Maximum Btu Use



56

The three test homes (T4, T5, and T6) have similar floor plans, construction methods (SIPs), windows and doors, and similar occupancy. T4 has two occupants, T5 and T6 each have one occupant. They differ, however, in orientation. As a result, further analysis was performed to compare these similarly constructed homes. The southeast glazing of T4 produced the highest Btu/sqft every season, while T5 energy use remained relatively flat with the exception of the first fall season. The fall anomaly could be due to the end of the construction phase of T5 and the homeowner’s first season to become accustom to the test homes’ energy needs. North orientedT6 showed low energy use during the summer seasons with spikes during winter. This could be attributed to the all-electric, on-demand feature of the appliances. The systems have the ability to go dormant in the summers. Figure 12 suggests in the cold region climate of Pagosa Springs a structure oriented south will have lower energy use than structures facing alternative directions. Designing for northern mountain views may need to include year-round snow-shedding and covered decks. Nevertheless, limited but purposeful glazing on the north side can take advantage of the views desirable by homeowners. However, maintaining primary glazing orientation to the south can save homeowner cost over time.

CONCLUSIONS AND RECOMMENDATIONSThe study’s findings reflected differences in energy use occurring between test homes and baseline home data in Pagosa Springs during the summer months when energy use is at its lowest. In addition, the energy usage trends indicated the test homes used consistently less energy than baseline homes in all seasons with identified

exceptions. On average, compared to baseline energy usage, test homes usage was roughly 23% less during the fall, 17% less during winter, 11% less during spring, and 41% less during summer months. The findings are not statistically significant with the exception of the summer seasons. In addition, as previously noted, numerous additional factors may exist which could have influenced these results. Therefore, the authors do not claim to provide sufficient evidence to quantify the impact solar orientation in isolation. The findings do, however, provide further support for the claim that south facing passive design houses may have greater efficiencies based on actual performance in seven constructed houses. These findings are consistent with the Andersson et al. study (1985) with regard to solar orientation of glazing suggesting total energy usage for passive designs with glazing facing north is higher than for homes with glazing facing south. The findings, however, did not confirm smaller square footage homes when normalized still reflected less Btu/sqft/season energy consumption compared to larger homes, consistent with the study by Morrissey et al. (2010). Furthermore, additional findings suggest a high degree of variability may exist in energy efficiency for houses with northern orientations and merit further research.

These findings are meaningful providing provide expanded evidence regarding the impact of passive design strategies in a cold climate. Furthermore, while the sample size was small, the findings, while not generalizable, begin to quantify the potential impact in a specific climate providing evidence for both builders and homeowners regarding the potential benefits of implementing passive design strategies in cold climates. This research provides an example for builders to analyze the impact of their building

each season, t he lowes t summer use is unobse rvable a t 2 Bt u/ sqft a t t ribut ed t o T6 , while t he highes t ene rgy use occurs during t he wint e r mont hs for t he base line , 1 6 ,4 7 6 Bt u/ sqft .

Fig ure 1 1 . Minim um a nd m a xim um s e a s o na l Bt u/ s q f t e ne rg y us e

Fig ure 1 2 . Co m p a ris o n o f s im ila r T4 , T5 , T6

The t hree t e s t homes (T4 , T5 , and T6 ) have s imilar floor p lans , cons t ruct ion me t hods (SIPs ) , windows and doors , and s imilar occupancy. T4 has t wo occupant s , T5 and T6 each have one occupant . They diffe r, howeve r, in orient at ion. As a re sult , furt he r analys is was pe rformed t o compare t he se s imilarly cons t ruct ed homes . The sout heas t g lazing of T4 produced t he highes t Bt u/ sqft eve ry season, while T5 ene rgy use remained re la t ive ly fla t wit h t he except ion of t he firs t fa ll s eason. The fa ll anomaly could be due t o t he end of t he cons t ruct ion phase of T5 and t he homeowner’s firs t s eason t o become accus t om t o t he t e s t homes’ ene rgy needs . Nort h orient edT6 showed low ene rgy use during t he summer seasons wit h spike s during wint e r. This could be a t t ribut ed t o t he a ll-e lec t ric , on-demand feat ure of t he appliances . The sys t ems have t he abilit y t o go dormant in t he summers . Figure 1 2 sugges t s in t he cold reg ion c limat e of Pagosa Springs a s t ruc t ure orient ed sout h will have lower ene rgy use t han s t ruct ure s fac ing alt e rnat ive d irec t ions . Des igning for nort he rn mount ain views may need t o inc lude year-round snow-shedding and cove red decks . Neve rt he le s s , limit ed but purpose ful g lazing on t he nort h s ide can t ake advant age of t he views de s irable by homeowners . Howeve r, maint aining primary g lazing orient at ion t o t he sout h can save homeowner cos t ove r t ime . CONCLUS IONS AND RECOMMENDATIONS The s t udy’s findings re fle c t ed d iffe rences in ene rgy use occurring be t ween t e s t homes and base line home dat a in Pagosa Springs during t he summer mont hs when ene rgy use is a t it s lowes t . In addit ion, t he ene rgy usage t rends indicat ed t he t e s t homes used cons is t ent ly le s s ene rgy t han base line homes in a ll s easons wit h ident ified except ions . On ave rage , compared t o base line ene rgy usage ,

0

2000

4000

6000

FALL 2009 WINTER 2009 SPRINGS 2010 SUMMER 2010 FALL 2010 WINTER 2010 SPRING 2011 SUMMER 2011

ANNUAL MEAN BTU/SQFT/SEASON ENERGY USE

T4(SE) T5(S) T6(N)

Figure 12. Comparison of similar T4, T5, T6




57

practices building similar homes in similar climate zone, and the need for continued contact with owners to collect data useful in documenting performance objectives when making decision choices concerning passive solar implementation.

The goal of this study was to characterize the relationship between energy use and solar orientation in actual structures implementing passive design, specifically for seven homes built by one builder in Pagosa Springs, Colorado. Findings indicated energy savings are higher in Pagosa Springs for structures designed with primary glazing orientation to the south. Data analysis revealed potential anomalies as well as areas for more in-depth future investigation. The study also highlighted some of the challenges in obtaining and using data collected from real-world houses (i.e., variable occupancy, building characteristics) Perhaps most importantly, the study serves as a model for future studies that individual builders or companies could perform to provide evidence and support to guide consumer decisions towards passive building strategies. The authors recommend future research including a larger number of test homes with more varied orientation over an extended period of five or more years to further explore the relationship between solar orientation and energy use. In addition, this study should be repeated by builders or companies with similar goals across the country to contribute to a data base to support residential passive design and construction advantages.

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Arrives




59Allhands Essay Competition

Each year the Associated General Contractors Education and Research Foundation (AGCERF) sponsors the James L. Allhands Essay Competition. The competition is named for (and funded by) the late James L. Allhands, a founding member of the AGC who spent his career as a prolific writer of construction related books. The essay competition is open to any senior level student in a four or five year ABET or ACCE accredited university construction management or construction related engineering program.

This year’s topic, ‘Using Mobile Technology for Managing Construction Projects’, generated submissions from across the nation. Judging was conducted by AGCERF board members who are among the most esteemed leaders in the industry. The first place selection was Chris Lierheimer of Colorado State University, the second place selection was Paul Shaw of Texas A&M University, and third place was a tie between Devin Doster of Ball State University and David Dylan John of Georgia Southern University. The first and second place articles are published in this issue.

The 2016 competition will open in July, 2015 and essays are due in November. First place winners and their faculty sponsors are awarded cash prizes of $1,000 and $500, respectively, and will be invited as guests (all expenses paid) of the AGC Foundation to the March, 2015 convention. The second place winner is awarded $500 and third place, $300. The topic for the 2015/2016 competition is “Strategies for Reducing the Environmental Impacts of Construction.” For more information on submission guidelines please see www.agcfoundation.org.

With AGC’s permission, this issue of The American Professional Constructor is featuring the top two winning essays for 2015 in our general interest category. We trust that our readership will enjoy reviewing the work of these top performers who will soon be graduating and starting their construction careers.

General Interest Articlesfrom The AGC James L. Allhands Essay Competition



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USING MOBILE TECHNOLOGY FOR MANAGING CONSTRUCTION PROJECTS

Building and Growing with Mobile Technology

Chris LierheimerColorado State University

14 November 2014

ABSTRACT: Today’s construction managers have an arsenal of mobile technologies at their disposal, all of which make managing projects vastly more organized and efficient than ever before. In this paper, I will explore in detail three different mobile technologies that the modern contractor has at his or her disposal, their benefits, potential pitfalls that they may present, and my thoughts on the future of these tools. I will share personal experience with, and research based on topics ranging from building information modeling, to RFID chip tracking of resources, to cloud based programs that streamline information flow.

From Alexander Graham Bell’s first transmitted words in 1876, to Ray Tomlinson’s historic “electronic mail” in 1971, and Neil Papworth’s first SMS text message in 1992, the evolution of communication is a testament to the ingenuity of humankind. Today, nearly twenty years after that historic text, there exists an instantaneous exchange of ideas through mobile technology that is all but taken for granted. The construction industry is no exception. Mobile technology leads to more efficient collaboration between owners and contractors, accelerates project timelines, and allows for more efficient use of resources. This expediency comes at a price however; through an increasingly globalized and competitive market, razor thin margins, and instant price comparisons, industry members should be well aware of the risks associated with competing in the global area that is construction.

SELECTION OF MOBILE TECHNOLOGYIn today’s construction industry, a Project Manager (PM) will use an array of mobile technology for both Pre-Construction and Construction operations. Laptops, desktop computers and smartphones are now common on most job sites. As the industry continues to advance, certain mobile technologies are becoming more prevalent. The following is a selection of mobile technologies that I have found to be particularly exciting. For Pre-Construction, tablet computers with cloud based document sharing, as well as cost and time loaded building modeling transmitted via mobile

devices will help advance projects in their infancy. Once construction is under way, I believe it would be helpful to use the following devices in particular: Tablet computers with Building Modeling software, GPS enabled total stations and laser scanners, and passive RFID tags and readers. While I did not have much experience with the pre-construction process on my internship, I was exposed to the same type of software that the preconstruction department uses. In general, it seems that project management and document control software such as Prolog can and should be more readily available on iPads with PMs moving from one job to the next. PMs need to be in constant contact with the owner and have communication with subcontractors, architects, and engineers. The mobile technology required for these interactions goes beyond cellular communications. Contractors should have access to bid summaries, plans, and specifications to know exactly what someone else is talking about and respond appropriately. Tablets and cell phones with these capabilities make for an increasingly globalized world, and one that facilitates the flow of information from one point to the next. Software like BroadVu is one example of a mobile technology that enables instant information flow and sharing. Broadvu gives users access to real time document and digital file sharing, which keeps the entire project team in sync (Wood 2013). It is applications like this that would help a preconstruction team digitally manage bids and corresponding documentation.

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While mobile technologies like Prolog and BroadVu may have some benefit to pre-construction, larger benefits of mobile technology can be reaped when construction actually begins. With a variety of modern mobile technology available, it would be wise to narrow in on three major areas of construction operations that can be enhanced via mobile technology: Building Information Modeling (BIM), Scheduling, and Resource Tracking. 1. BIMComputer aided design is not a recent invention (think 1970s for some of the first iterations), but its application to the construction industry, via BIM is starting to gain mainstream acceptance. Like nearly every other kind of technology, BIM seems to adhere to Moore’s law. Moore’s law actually applies to the number of transistors in a circuit, and states that every two years, the number of transistors in a circuit will double thanks to advances in micro computing technology (Intel 2014). On a more abstract level, we can take this law to mean that computers will get twice as powerful every two years. In my own experience, it seems that over that same time period the cost of the technology will be cut in half. Thus, BIM is becoming more and more accessible to companies without a large amount of financial liquidity.

BIM has shown a tremendous potential in field applications, particularly with Mechanical-Electrical-Plumbing (MEP) and structural coordination. This tool for crafting a digital building before a physical one, has historically been confined to a desk. The future of modeling, however, could lie in liberating the model from indoor use. Already, there are programs like BIM 360 Glue, which allow users to take an iPad into the field, hold it up to a construction project in progress, and see an augmented reality via a mobile model of the building.

Davies and Harty (2013) explore this possibility by stating that mobile BIM has been shown to be a valuable addition to the collection of tools that site workers use. Having a building model available on a mobile device allows workers to access information pertaining to design and to capture work quality and progress data on-site (Davies and Harty 2013). However, BIM is more than just getting information into the field in a timely manner. In construction, there

is an overwhelming amount of material that must be relayed between multiple parties, in multiple forms. 2D drawings, 3D models, dimensions, and costs, are all part of a vast communication flow that needs to be uniformly managed. BIM, in conjunction with mobile tablets and cell phones, has the ability to get the right information to the right people at the right time. Having a centralized place where all the moving parts of a construction project can come together, from any place (jobsite, office, abroad) is a powerful tool.

It would also be helpful to tie the computer model of the project to a wireless device that would allow for a variety of tasks to be completed in the field. Tasks such as photo documentation, inputting scheduling data, or rerouting ducts/pipes could be done more quickly and with less transcription errors. This leads to a more efficient flow of information, higher levels of collaboration, faster project turnover, and less potential for litigation.

2. SchedulingScheduling is another project management task that could be greatly improved by mobile devices. According to Turkan et al. (2012), progress tracking is typically dependent on foreman daily or weekly reports, and these involve intensive manual data collection, and frequent transcription errors. To address these, Turkan et al. (2012) propose to have field workers track progress digitally, on mobile devices as work is installed. In addition to this, they propose a system of laser scanners and RFID trackers to simultaneously track the building’s progress digitally (Turkan et al. 2012). This system could have real value for project applications with tangible items being installed such as masonry, structural erection or earthwork. Much of a construction manager’s time is spent calculating what stage a project is at, and how much work is remaining.

Turkan et al. are not the only ones making this claim. Kim et al. (2013) also claim that there are efforts being made worldwide to apply sensing technology like total stations, GPS, digital photogrammetry and laser scanning to generate as-built drawings. For the project management team, this means less time catching up with the schedule, as- built drawings, and cost implications, and more time focusing on future coordination.




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At this point, I must insert a word of caution. While this system seems to provide a much-needed service to contractors, it does have limitations. Laser scanners cannot measure minute details like paint or drywall, or highly dense areas like wood or steel framing. Beyond that, lasers are incapable of calculating geometries. They take distances at face value. If there are ramps, angles, or curves, the distance measured is put into the model as an actual, when in reality the distance measured may be a hypotenuse or chord of a circle. Then, there is the issue of the marriage of digital technology and the end user. Ideas like laser scans and RFID tracking technology sound great in a board room as ways to become a more effective company, but will the workers on the field side actually be able to interpret and utilize the data that these technologies provide?

3. Resource TrackingAnother problem hindering the construction industry is the accurate tracking of resources. From tools, to heavy machinery, to concrete trucks, keeping track of a company’s physical resources is a time intensive task that should have been delegated to computers long ago. One example is the yard where a contractor’s tools and equipment are stored. As different teams request machinery for their job, it is the duty of the yard workers to keep track of every piece of equipment and which job it belongs to. RFID technology can be used to streamline this process. For example, as the yard worker checks out a piece of equipment for a project team to use, a small RFID tag can be applied to the tool, then passively scanned into the companies tracking database. When the tool reaches the jobsite, it can be scanned again as the specific project team accepts it. Costin et al. (2012) apply this technology to tracking a specific worker throughout a high- rise building to monitor productivity, but it could work just as well on the ground level. Specifically, tracking the hundreds of concrete trucks necessary to place a mat foundation consisting of thousands of cubic yards of concrete. While I was completing my internship, I was given the opportunity to track concrete trucks as a mass concrete pour was underway. After logging hundreds of individual trucks by hand, I can appreciate how much more efficient and accurate it would be to have a system of RFID tags on the truck that could be scanned as they leave the plant, and as they arrive on site. The result is a substantial amount of saved time and reduction in data entry errors.

Privacy concerns are, of course, among the disadvantages of this system. Furthermore, this tracking system is mobile in nature; it must be assembled and disassembled at each jobsite. Furthermore, the number of RFID readers required to accurately track resources might be high enough to be cost prohibitive.

BENEFITS OF MOBILE TECHNOLOGYAs discussed above, mobile technology will usher forth an age of building in which information can be shared faster and more efficiently. The benefits of mobile technology include increased collaboration and error detection, and devices with a “mobile model” will serve to centralize trade coordination and save time in meetings. Consolidated document control and project management software that can be downloaded to mobile computers in the form of apps will also enhance field workers’ ability to read and view plans while working. Above all, these mobile devices will lead to a more efficient worker, just so long as he/she can keep up with the technology.

PITFALLS OF TECHNOLOGYThe problem with mobile technology this advanced lies in its implementation. Support and troubleshooting is key, and if users don’t want to bother, they will wind up using tried and true methods because people are faster at what they are good at. People will not take time to figure out a new device when they have deadlines to meet.

Another issue that is also brought up by Davies and Harty (2013) is the resistance to technology and the resistance to change in general. Davies and Harty (2013) describe a common dilemma facing contractors. What happens when technology outpaces its users? Especially when those users are field operations personnel who may not be as technically inclined as IT personnel? The answer, claims Davies and Harty (2013), lies in the implementation of the new technology. Instead of generating long-winded procedural manuals, site workers should adopt the necessary technical skills in the field through “personal relationships rather than formal processes”.




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While I was working on internship this summer, I saw first-hand that there is a generation of aging site workers in this industry. Using data from the latest US Census, Sue Dong (2014) stated that the average age of construction workers has risen to nearly 41 years. This is illustrated in Figure 1, which shows the rise in construction worker age over the past thirty years. Furthermore, some of the superintendents, labor foremen, and laborers in the field did not receive a college education, and also have limited knowledge of computers. Given these, there is a generation of construction professionals that is accustomed to doing things “the old way.” Implementing something as complex as BIM on a mobile device may prove to be too much for these members of our community. While it is a sweeping generalization to state that the typical site worker in the field is technology illiterate, there is some truth to it. But this is changing, albeit slowly. No longer is it acceptable for a labor foremen to say, “I didn’t read that RFI because it was emailed to me.” To survive in a world where iPads and cell phones are now commonplace, the “field guys” need to start keeping up.

Figure 1 Average Age of Construction Workers Over Time. From: (Dong 2014)

CHANGES TO TRADITIONAL PROJECT MANAGEMENT

I must admit that I do not have much experience in what many would consider “Traditional Project Management.” The company I worked for in 2014 is fairly advanced. That being said, I have a few ideas of how mobile technology will be changing the traditional management model. A project manager using mobile technology that I have discussed, is going to have to spend a lot of time up front with his/her team, training them on the software he/she expects them to use.

After all, these mobile technologies are only as good as the person using those. A clear “standard operating procedure” should be implemented at the inception of a project and weekly updates should occur. Expectations need to be managed with subcontractors and suppliers as well. A PM in this new “mobile generation” needs to open clear lines of communication at the start that the project will be a “digital” project and that he/she expects all correspondence to be conveyed digitally.

MY EDUCATIONAL EXPERIENCECollege is not solely responsible for developing student’s abilities to use and manipulate mobile technology. Today’s students were raised in a world where it is common to see children as young as two or three years old playing on iPads and cell phones. Any student born within the last two decades has a considerable advantage with respect to technology over CM Professionals already in the industry. As a member of the Millennial generation, I am no exception to this statement.

At the institution I attend, there are no regular classes specifically designated for learning a software/technology. These programs are integrated into the classes. However, there are intensive courses offered in 6 week blocks that can help train students on CM specific software. So called “boot camps” were a tremendous asset to me, a student who had never hyperlinked an RFI in Bluebeam or applied a baseline in P6.

CONCLUSIONSIn just the past twenty-five years, digital and mobile technology has advanced at a breakneck pace. The construction industry is just one sector of a global market to benefit from mobile technology that keeps people just one click away from every bit of information they could ever need. When applied to construction, mobile technology can reduce data transcription errors, increase collaboration between all interested parties, and accurately keep track of the moving parts that comprise a construction project. As with most things, there will be growing pains that arise from implementing these new technologies. As the world of construction begins to adapt mobile technology

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and grow more efficient, it will allow us to focus our collective energy on new and innovative projects, which in turn will drive a new era of intelligent building.

BIBLIOGRAPHYCostin, Aaron, Nipesh Pradhananga, and Jochen Teizer. “Leveraging passive RFID technology for construction

resource field mobility and status monitoring in a high-rise renovation project.” Automation in Construction 24 (2012): 1-15. Print.

Davies, Richard, and Chris Harty. “Implementing ‘Site BIM’: A case study of ICT innovation on a large hospital

project.” Automation in Construction 30 (2013): 15-24. Print.

Dong, Xiuwen (Sue). “Longitudinal Study of Construction Worker Health Across the Lifespan.” CPWR. 1 Jan. 2014.

Web. 11 Nov. 2014.

Intel. “Moore’s Law and Intel Innovation.” Intel.com. 1 Jan. 2014. Web. 11 Nov. 2014. Kim, Changyoon, et al. “On-

site construction management using mobile computing technology.” Automation in Construction 35 (2013): 415-423. Print.

Turkan, Yelda, et al. “Automated progress tracking using 4D schedule and 3D sensing technologies.” Automation in

Construction 22 (2012): 414-421. Print.

Wood, Debra. “BroadVu Creates Mobile, Digital File System on an IPad.” Constructor 30 Jan. 2013: 66. Print.




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USING MOBILE TECHNOLOGY FOR MANAGING CONSTRUCTION PROJECTS

Using Mobile Technology for Managing Construction Projects

Paul ShawIndustrial Capstone | COSC 443-901

12 November 2014

ABSTRACT: This essay examines the use and application of emerging mobile technologies in the construction industry. Mobile phones and tablets are discussed in-depth, and can be used to replace office tools, to collaborate, and to bring building information modeling (BIM) technology out into the field. Next, wearable computing technology is discussed, including Google Glass and smart hard hats. This technology provides another avenue for construction information access in the field. Finally, unmanned aerial vehicles are discussed, along with their challenges and potential benefits. Increased technology use will absolutely improve efficiency and profitability in the construction industry.

When people are asked to think of an antiquated, backward-thinking, old-school industry, the construction industry is often mentioned. While anyone who has worked in construction knows this perception can sometimes be true, it is not always accurate. Many construction companies have, in recent years, began embracing emerging technologies as an answer to heightened competition among contractors and the increasing demands and expectations of owners. However, the construction industry still lags in technology adoption. A stark example of this is the statistic showing that construction companies spend on average only 1.1-1.6% of their annual revenue on information technology, as opposed to an average of 6% in other industries (Sacolick 1). In fact, the construction industry comes last in the cited study of fourteen industries. Is this acceptable? Many construction industry players, including members of the millennial generation, refuse to accept the “same old way” of going about business. This essay will discuss the role of mobile devices in the construction process and how mobile hardware and software can be used to improve the construction process.

The first and most obvious mobile devices to be discussed are mobile phones and tablets. In the past several years, mobile computing technology has exploded, and one can easily buy phones and tablets that are more powerful than the laptops of five years ago. Nearly every construction manager and superintendent has a smartphone, which is usedat minimum for phone calls, text messages, and email.

Tablets are present on many construction sites as well, and while they are less common, they are very beneficial for field personnel as they manage the day-to-day aspects of construction projects. Smartphones, by far the most prevalent and widely adopted mobile devices on construction sites, can be used in a multitude of ways above and beyond their standard uses. When equipped with the proper applications (also known as apps), smartphones can be used to replace office equipment like scanners and fax machines. An app called CamScanner lets the user scan, process, and upload or send documents using only the device’s camera. eFax is an app that allows the user to obtain a free fax number for use on a device in addition to the device’s standard phone number.

Other ways smartphones will become used in the construction industry is using a suite of applications not typically used by construction professionals, but used extensively by millennials and other young smartphone users. These applications provide increased coordination and collaboration between individuals, and could almost be considered “social media.” A key example of this is an app called GroupMe. GroupMe, owned by Microsoft, is used by many students and other young smartphone users to communicate in groups. It is effectively the text messaging version of a mass email or a chatroom. An initiating user can add desired parties to a group chat, and users can effortlessly communicate with the group instead of text messaging individuals.

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GroupMe users can form unlimited groups and variations of groups. An example of how this could be used in the construction industry would be as follows: A project manager creates one group chat for all of the people in the construction management team, and another group chat only containing members of the field supervision team. She could even create a group chat with the project decision-makers, including the owner’s representative and architect. Group messaging in this manner could prove invaluable during all phases of construction, including preconstruction bidding and project planning, as the ability to rapidly ask and answer questions increases the efficiency of collaboration. This type of communication is likely to become more widespread as more and more millennials move into roles in the construction industry.

Tablets are most commonly used by construction personnel to view drawings and to create punchlists. If properly configured, though, a tablet can be a full substitute for a PC in the field. Tablets can be set up with email and calendar applications, as well as apps that allow the user to view the full set of drawings and specifications or to create and share punchlist items. An extremely beneficial technology available as part of many applications is cloud storage. This feature allows data to be synced between connected devices and remote servers. Applications such as Dropbox and Box.net provide cloud storage capability, while many applications have built-in cloud storage for in-app data. Cloud storage is beneficial because it places data off-site and can create redundancy, with data saved both locally on the device and remotely on the server. Additionally, cloud storage can be used to automatically sync data, ensuring that all devices are always populated with current information. As any construction professional knows, having access to current drawings, specifications, and information is always a challenge, and many problems are avoided when all parties use current information.

Another emerging use of tablets using cloud technology is in the area of preconstruction. An application called Cloud Takeoff has made it possible for estimators to perform digital takeoffs on any device, from Mac or PC to tablets and iOS devices. These takeoffs are based digitally in the cloud, so users can collaborate or work on the documents from different devices. This application performs tasks that were previously only performed by heavy programs such as Onscreen

Takeoff. The collaboration and versatility offered by cloud-based programs like Cloud Takeoff will revolutionize preconstruction, allowing companies to collaborate more effectively and produce more accurate bids in a timelier manner than they can using traditional PC-based software.

A final emerging use of tablets is to access BIM (building information modeling) information in the field. Until the advent of tablet computers, access to BIM models was limited to PCs, which were not typically used in the field. When software like Autodesk’s BIM 360 Field and BIM 360 Glue are used, construction management personnel can have 3D models on hand in the field. This increased access to the project model can facilitate rapid problem solving and resolution of issues, and eventually may lead to 3-D model- driven construction. Model-driven construction (as compared to construction from 2-D drawings) may be the future standard in the industry, and tablet computing technology is certainly helping to enable research into this new project management procedure.

This discussion of smartphones and tablets, along with applications relevant to construction management, has covered many helpful uses of these devices in managing construction projects. Most of the technology discussed is already in place, and the only barriers to adoption of these technologies are cost and the disruptive change companies may face by embracing new construction management methods, procedures, and technology. The remaining devices and applications discussed in this paper will be more experimental, less accessible, and even hypothetical at this point in time. However, it is important to discuss these technologies, because rapid advances in both hardware and software bring about swift development of new technologies, and that which is discussed as hypothetical or prohibitively expensive this year may be used by millions of users in only a matter of years. One piece of hardware that may become widely used in the construction industry is a much talked about, yet rarely seen device: Google Glass. Google Glass is a glasses frame with an onboard mobile computer. Glass can be fitted with different lenses, including ANSI Z87.1 approved safety lenses (P, Josh 1). Glass’s mobile computer responds to voice commands, and can take pictures and video on command. Additionally, applications for Glass, called Glassware, are available.




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Well-known construction software companies including Procore and FieldLens have already created Glassware focused on streamlining construction management activities such as creating punchlist items and assigning responsibilities to different parties. Google Glass or other similar wearable devices can also be linked to other devices, which will be discussed in subsequent paragraphs.

An area that has not been discussed so far in this paper is safety. Construction is one of the most dangerous occupations in the United States, and in 2013 over one-fifth of workplace deaths occurred in the construction industry (Commonly Used Statistics 1). If technology can be used to improve other areas of the construction industry, can it also be used to improve safety? There are companies who have developed devices that answer that question with a resounding “yes”! One such company is DAQRI, an augmented reality developer who has developed the Smart Helmet, a hard hat with built-in features promoting safety and information accessibility and management. The Smart Helmet is manufactured with inertial sensors and 360 degree cameras, as well as a screen in the front evocative of the Google Glass interface. While still in its infancy, a smart hard hat like this can be used not only to display product information and 3-D information in the field, but to track the location of workers, identify and warn of potential dangers on the jobsite, and to automatically notify management if the helmet detects an accident or near miss involving the wearer. This is an excellent example of technology that will make the construction industry a safer place.

The final device discussed in this paper is a controversial topic in today’s world: Unmanned aerial systems, commonly referred to as drones or UASs, have a certain and expanding role in the construction industry. There are many opponents of and advocates for commercial drone use in the United States, but the Federal Aviation Administration (FAA) appears friendly to the idea of commercial drone use, and in October 2014 it loosened regulations for drones used for filmmaking purposes, clearing the way for more industry exemptions in the future. (O’Connor 1). At the time of writing, all other industries must fill out a Special Airworthiness Certificate and file it with the FAA in order to receive permission to use drones commercially. However, despite the procedural challenges that exist, the use of UASs in construction has been very beneficial for the

companies who have already adopted the devices, and use is likely to increase as legal barriers are removed and the technology becomes more common and inexpensive.

Unmanned aerial systems offer benefits to many work processes in construction. Generally, they are used for tasks involving photography, videography, and other data collection. UASs can be used to capture aerial photographs of construction sites much less expensively than costly third party aerial photographers using manned aircraft. In addition to capturing progress photographs, UASs can be used for aerial inspections of hard-to-access locations. In the future, as battery life improves, drones may be able to provide constant live feeds from construction sites. Remotely-located decision makers could pilot the drones to view job progress, providing them with up-to-the-minute information useful in managing the project. As mentioned earlier in this paper, wearable computing technologies like Google Glass have successfully been linked to video feed from UASs, providing the wearer with live video feed from the drone. This capability also certainly reduces safety risks compared to a worker suiting up with fall protection gear and working at great heights to examine aspects of the project.

As a future construction manager, the author anticipates utilizing all of the devices discussed above in preconstruction planning and day-to-day management of construction projects. The forces of change are so rapid that, in a few years, I would not be surprised if the technology described in this paper is used nearly universally. Companies who do not adapt may simply be driven out of business by companies who leverage the benefits of new technology in order to save time and money and work more safely. Some of these devices, such as mobile phones, simply replace old technologies, namely landlines and desktop PCs. However, applications utilizing cloud computing are quickly ushering in a new era of collaboration, where information is accessible anywhere at any time. Construction professionals today often face challenges rooted in the availability of information – a classic problem, for example, is when work is performed without referencing the newest drawings. This problem will be a thing of the past, though, when companies give their field personnel tablet computers which automatically sync whenever new documents are



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issued. Drones and UASs are another technology that will drastically change the construction management industry. UASs will be used in ways we cannot yet even fully imagine, from surveying and layout to material tracking and even, perhaps, performing actual construction tasks. In short, construction management as it has been known will rapidly evolve, and the industry may be nigh unrecognizable in five or ten years.

I cannot claim that my educational experience has formally prepared me to work with any of the emerging technologies discussed in this paper. However, as a millennial, I can say that my life so far has certainly prepared me to embrace new technologies and integrate them into every aspect of my life, including my future work. I have attended university at a time when cloud computing and storage sites like Dropbox and Google Drive are exploding in popularity, replacing technology like USB flash drives that was widely used only a few years ago. I have had a mobile phone since I was thirteen, and since high school I have walked around with the entire internet of information at my fingertips, or, more accurately, in my pocket. Members of my generation are excellent at using our resources to find information and solve problems: Even if I do not know the answer to a question, I can nearly always find the answer with a minute or two of tresearch. While I may not be trained in the use of UASs or Google Glass, I am firmly convinced of the merits of embracing new technology as soon as it is available and learning how to make it work for me. I believe that as today’s students graduate and move into the construction industry, we will serve as catalysts to introduce and promote new technologies in the workplace, which will greatly benefit the profession we all love and have chosen.

WORKS CITED“Commonly Used Statistics.” Commonly Used Statistics. Occupational Safety & Health

Administration, n.d. Web. 11 Oct. 2014. <https://www.osha.gov/oshstats/commonstats.html>.

O’Connor, William V., Chris J. Carr, and Joanna Simon. “United States: Drones: The FAA

Grants Hollywood The First Regulatory Exemptions Permitting The Commercial Use Of UAS.” Mondaq.com. Mondaq, 10 Oct. 2014. Web. 11 Oct. 2014. <http://www.mondaq.com/unitedstates/x/345786/Aviation/Drones%2BThe%2BF AA%2BGrants%2BHollywood%2BThe%2BFirst%2BRegulatory%2BExemption s%2BPermitting%2BThe%2BCommercial%2BUse%2BOf%2BUAS>.

P, Josh. “Amber Lens For Google Glass.” Glass Apps Source. N.p., n.d. Web. 11 Oct. 2014. <http://www.

glassappsource.com/google-glass-accessories/amber-lens- google-glass.html>.

Sacolick, Isaac. “Construction Industry Dead Last in IT Spend.” Construction, Building &

Engineering News: ENR. Engineering News Record, 28 Nov. 2012. Web. 11 Oct. 2014. <http://enr.construction.com/technology/construction_technology/2012/1203- gartner-stats-aec-dead-last-in-it-spend.asp>.



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