Greening Construction Processes Using an Input-Output-Based ...

Greening Construction Processes Using an Input-Output-Based Hybrid Life Cycle Assessment Model By

Aurora Luscher Sharrard Master of Science in Civil and Environmental Engineering, 2004 Carnegie Mellon University, Pittsburgh, PA Bachelor of Science in Civil Engineering, 2001 Tulane University, New Orleans, LA

A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF Doctor of Philosophy in Civil and Environmental Engineering

Department of Civil and Environmental Engineering Carnegie Mellon University Pittsburgh, Pennsylvania April 2007

Creative Commons Copyright, Some Rights Reserved 2007, Aurora Luscher Sharrard

2007, Aurora Luscher Sharrard This work is licensed under the Creative Commons Attribution-Noncommercial-No Derivative Works 2.5 License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/2.5/. You are free to copy and distribute this work in its original form for noncommercial purposes.

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For Jesse Sharrard, my loving husband, who will someday have his own tome for Corduroy Orange

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ACKNOWLEDGMENTS This research was funded by Grant #0328074, “Collaborative Research: (TSE03L) Assessment and Redesign of Processes for Sustainable Construction,” from the National Science Foundation (NSF). The opinions expressed herein are those of the authors and not of NSF. As I near completion of this dissertation, words of thanks go to my advisor, Dr. H. (as in Howard) Scott Matthews, whose vision, programming skill, funding, and humor helped us move through the last four years together. I truly appreciate the vast knowledge, support, guidance, and friendship he has provided throughout my research. I would also like to thank the rest of my thesis committee—Dr. Robert Ries, Dr. Chris Hendrickson, and Dr. Arpad Horvath—for their support. From the very beginning, Rob has helped by asking fundamental questions about life cycle assessment and green building. Chris has provided construction industry knowledge, input-output LCA insights, and valuable assistance regarding the Ochoa case study. Arpad’s keen instinct for delving to the root of the issue has also helped light the way. Countless acknowledgements also go to my research partner, Melissa Bilec, who has been a great colleague, motivator, and friend. Especially in the past few months of finishing this document and its accompanying research, she has been an excellent mirror and sounding board. Melissa also co-authored parts of Section 3.3.2 and parts of Appendix B. Speaking of Appendix B and the construction sector map (CSM), many Bureau of Economic Analysis employees deserve recognition for creating the input-output tables and other data on which EIO-LCA and the CSM are based. Specifically, thank you Mark Planting, Conrad Roesch, Mary Streitwieser, and Thomas Howells for answering my random questions about the construction industry with patience and providing me advice on how to balance the CSM. In terms of the case studies supplied for my research, I am extremely thankful that Donn Williams and Ken Burkhalter of RAND Facilities Services were so willing to provide case study data on their new Pittsburgh space. Recognition is also due to Ralph Horgan, Linda McFadden, and the rest of the Carnegie Mellon University (CMU) Campus Design and Facility Development (CDFD) staff, whose immediate buy-in to the concept of this research came at a time when many other prospective case study suppliers had let me down. The data CMU CDFD supplied was invaluable to this project and I appreciate their genuine interest in the results. Thanks also goes to Dr. Luis Ochoa of the Universidad Michoacana de San Nicolás de Hidalgo for providing his raw data for the Ochoa residential case study analysis and to Dr. Angela Guggemos of Colorado State University for providing the raw data for the Junnila / Guggemos U.S. commercial office building case study. Behind the scenes, there were two summer research students who supported this project (and who were also supported by NSF). Michael Roth provided vital additions to the on-site energy discussions contained in Section 3.3.1 and Ashley Nikithser waded through the endless websites of state Departments of Transportation to help extract publicly bid case studies for me; Ashley also worked diligently to discern connections

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between Pittsburgh air quality data and construction activity. Without both of them, this research would not be as comprehensive. Special appreciation is also due to Chris Weber, whose Matlab version of EIOLCA was very helpful in the early stages of my model-building. Additional thanks to Chris for providing his calculations regarding purchaser and producer cost ratios for each I-O sector, as well as for giving me random economic and EIO-LCA advice over the past few years. I would also like to thank past and present members of the Green Design Institute (GDI), Department of Civil and Environmental Engineering (CEE), and Department of Engineering and Public Policy (EPP) for being so supportive throughout this process. Specific recognition goes to Deanna Matthews, Cortney Higgins, Allison Harris, Shahzeen Attari, Heather Wakeley, Damian Helbling, Maxine Leffard, Deborah Lange, Cliff Davidson, Larry Cartwright, Jim Campbell, Dave Dzombak, and the CEE office staff. Special thanks also goes to Troy Hawkins, Paulina Jaramillo, and Joe Marriott for encouragement in life and research, as well as to their significant others: Carin Hawkins, Nestor Gomez, and Chandra Marriott, for unwavering support. I am also extremely grateful to my parents, Robert and Diana Luscher, for always instilling in me two very important things: 1) speak up, whether with questions, for yourself, or for others, and 2) environmental living is not a choice, but a way of life. Even though they; my sister, Julia; and my in-laws (Clara Lee, Jim, Johanna, Jeremy, Amanda, and Eric) might not have had any idea what my research was really about, they feigned interest when necessary and have been extremely understanding for the past four years. Johanna, especially, has been an irreplaceable cohort and collaborator in times of need. Most importantly, none of this would have been possible had I not been well fed, humored, and buttressed every step of the way by my wonderful husband, Jesse Sharrard. Words do no justice to the sacrifices someone must make when their significant other is working towards a PhD; he has been extremely understanding, helpful (even, and especially, while recovering from a broken ankle), and afforded me great patience throughout this entire process.

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ABSTRACT This research uses a life cycle assessment (LCA) framework to create a more specific and accurate estimate of the environmental impacts of construction processes. The construction industry is spatially and economically diverse, yet fragmented because of it depends on various specialized contractors, is always changing, and is occurring everywhere. Because the construction industry is so complex, modeling construction processes is required in order to better understand the specific environmental implications of these activities; this goal would be best achieved with the process LCA approach, though process LCAs are data intensive and time consuming given the unique nature of every construction project. Conversely, the input-output (I-O) LCA approach allows for a more inclusive view of the construction industry (i.e., on-site construction activities and its supply chain), which can be used to identify processes of principal concern. A combination of both approaches allows capitalization on each method’s strengths. Consequently, a hybrid LCA framework produces a comprehensive analysis that includes the economy-wide effects of construction while addressing on-site construction activities. The I-O-based hybrid LCA framework selected for this research is based on Carnegie Mellon University’s (CMU) Economic Input-Output Life Cycle Assessment (EIO-LCA) modeling tool. The I-O-based hybrid model was created by combining a new “Hybrid” feature that uses the EIO-LCA interface with updated and reformulated environmental effect vectors for EIO-LCA’s thirteen construction sectors. The final stage of this research models a variety of construction case studies on the I-O-based hybrid LCA framework; these case studies demonstrate the model’s broad applicability and which environmental impact categories significantly increased with the hybrid framework (e.g., gasoline, particulate matter, and global warming potential). The I-Obased hybrid LCA model for construction is intended to help decision-makers make more informed decisions regarding the construction industry, adding environmental quality and sustainable development as goals instead of unintentional benefits. The model’s focus on construction site and supply chain activities helps identify improvement opportunities that may otherwise be missed; it also provides a holistic assessment that identifies priority areas for future research regarding construction’s environmental impacts. - vi – Chapter 1

TABLE OF CONTENTS ACKNOWLEDGMENTS ____________________________________________________________ IV ABSTRACT _______________________________________________________________________ VI TABLE OF CONTENTS_____________________________________________________________VII LIST OF TABLES ___________________________________________________________________ X LIST OF FIGURES _________________________________________________________________ XI ABBREVIATIONS ________________________________________________________________ XIV CHAPTER 1: INTRODUCTION ________________________________________________________1 1.1 MOTIVATION ____________________________________________________________________1 1.2 RESEARCH OBJECTIVES ____________________________________________________________3 1.2.1 The Construction Industry ______________________________________________________6 1.2.1.1 Impact of the U.S. Construction Industry _______________________________________________ 6 1.2.1.2 Construction Industry Data Sources ___________________________________________________ 7 1.2.1.2.1 National-Level Air Emissions ___________________________________________________ 9 1.2.1.2.2 Vehicle Inventory and Use Survey________________________________________________ 9 1.2.1.3 Framing Construction in an Environmental Context _____________________________________ 10 1.2.1.4 Construction and LEED ___________________________________________________________ 11

1.3 THESIS OUTLINE _________________________________________________________________13 CHAPTER 2: LIFE CYCLE ASSESSMENT _____________________________________________15 2.1 BACKGROUND __________________________________________________________________15 2.2 PROCESS LIFE CYCLE ASSESSMENT __________________________________________________16 2.2.1 Existing Pure Process LCA Tools’ Applicability to Construction _______________________17 2.2.1.1 BEES__________________________________________________________________________ 2.2.1.2 GaBi __________________________________________________________________________ 2.2.1.3 SimaPro________________________________________________________________________ 2.2.1.4 ATHENATM Environmental Impact Estimator__________________________________________ 2.2.1.5 NREL LCI Database ______________________________________________________________ 2.2.1.6 Summary of Existing Process LCA Software/Data’s Construction Applicability _______________

18 18 20 21 22 22

2.3 INPUT-OUTPUT LIFE CYCLE ASSESSMENT _____________________________________________22 2.3.1 EIO-LCA Background ________________________________________________________23 2.3.1.1 EIO-LCA and the Construction Industry ______________________________________________ 24 2.3.1.1.1 Support Sectors for the Construction Industry ______________________________________ 25 2.3.1.1.2 EIO-LCA Construction Sector Issues_____________________________________________ 32

2.4 HYBRID LIFE CYCLE ASSESSMENT ___________________________________________________33 2.4.1 Why Hybrid Life Cycle Assessment for Construction? _______________________________35 2.4.2 Hybrid Life Cycle Assessment Background ________________________________________36 2.4.2.1 Boundary Issues _________________________________________________________________ 37

2.4.3 Past Construction-Related LCA Research _________________________________________38 2.5 DISCUSSION ____________________________________________________________________39 CHAPTER 3: HYBRID LCA MODEL FOR CONSTRUCTION _____________________________41 3.1 INTRODUCTION __________________________________________________________________41 3.2 OPTIMAL CONSTRUCTION INDUSTRY INCLUSIONS IN HYBRID MODEL ________________________41 3.3 RESEARCH NEEDS _______________________________________________________________43 3.3.1 On-Site Energy and Electricity Demand, Use, and Generation_________________________44 3.3.1.1 Estimating Construction Energy Use by Category _______________________________________ 3.3.1.2 Effects of EPA Nonroad Diesel Rules ________________________________________________ 3.3.1.3 Construction Nonroad Diesel Engine Emissions ________________________________________ 3.3.1.4 Emissions from On-Road and Generator Engines Used for Construction _____________________ 3.3.1.5 Effects for On-Site Generators ______________________________________________________ 3.3.1.6 “Hybrid” Engine Discussion________________________________________________________

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47 51 52 53 54 57

3.3.1.7 On-Site Energy Conclusions________________________________________________________ 60

3.3.2 Construction Sector Map ______________________________________________________62 3.3.2.1.1 Introduction to the Bureau of Economic Analysis and Census Bureau ___________________ 64 3.3.2.1.2 Data Relationship between EIO-LCA, the BEA and the Census Bureau _________________ 65 3.3.2.1.3 Input-Output Sectors and NAICS Industries _______________________________________ 73

3.4 DISCUSSION ____________________________________________________________________73 CHAPTER 4: REFORMULATION & UPDATE OF EIO-LCA ENVIRONMENTAL EFFECT VECTORS _________________________________________________________________________74 4.1 EXISTING EIO-LCA ENVIRONMENTAL EFFECT VECTOR __________________________________74 4.2 CONSTRUCTION SECTOR REFORMULATED & UPDATED ENVIRONMENTAL EFFECT VECTORS _______75 4.2.1 Energy Environmental Effect vector _____________________________________________76 4.2.1.1 Existing Energy Environmental Effect vector __________________________________________ 4.2.1.2 Updated and Reformulated Energy Environmental Effect vector ___________________________ 4.2.1.2.1 2002 Economic Census Energy Expenditure Data___________________________________ 4.2.1.2.1.1 Creating Estimates for Census-Withheld Data__________________________________ 4.2.1.2.1.2 Converting 2002 Economic Census Data to Physical Unit Consumption _____________ 4.2.1.2.2 Use Estimates for Electricity, Natural Gas, Motor Gasoline, & Distillate Fuel_____________ 4.2.1.2.3 Compiled Updated and Reformulated Energy Environmental Effect vector _______________

76 77 78 78 79 81 83

4.2.2 Global Warming Potential Environmental Effect vector ______________________________88 4.2.3 Conventional Air Pollutant Environmental Effect vector _____________________________92 4.2.3.1 Existing Conventional Air Pollutants Environmental Effect vector__________________________ 92 4.2.3.2 Updated and Reformulated Conventional Air Pollutant Environmental Effect vector ___________ 93 4.2.3.2.1 AirData ____________________________________________________________________ 93 4.2.3.2.2 National Emissions Trends and Air Quality________________________________________ 95 4.2.3.2.2.1 NAQET Distribution Method_______________________________________________ 97 4.2.3.2.3 Fugitive Dust ______________________________________________________________ 100 4.2.3.2.3.1 Where Fugitive Dust Comes From__________________________________________ 101 4.2.3.2.3.2 Fugitive Dust Allocation _________________________________________________ 102 4.2.3.2.4 Compiled Updated & Reformulated Conventional Air Pollutant Environmental Effect vector 105

4.2.4 Toxic Release Inventory Environmental Effect vector _______________________________109 4.3 DISCUSSION ___________________________________________________________________115 CHAPTER 5: INSTITUTING AND APPLYING THE HYBRID TOOL FOR CONSTRUCTION 117 5.1 INTRODUCTION _________________________________________________________________117 5.2 INTERFACE ____________________________________________________________________117 5.2.1.1 Hybrid Model Features and Functions _______________________________________________ 118 5.2.1.1.1 Hybrid Model Background____________________________________________________ 118 5.2.1.1.2 Hybrid Model Methods ______________________________________________________ 119

5.3 CASE STUDIES _________________________________________________________________122 5.3.1 Requirements ______________________________________________________________123 5.3.1.1 Bids __________________________________________________________________________ 123

5.3.2 Summary of Case Studies_____________________________________________________125 5.3.2.1 Producer / Purchaser Price Conversion_______________________________________________ 5.3.2.2 Ochoa Residential Construction Case Study __________________________________________ 5.3.2.2.1 Ochoa Case Study Update, Conversion, & Hybridization ____________________________ 5.3.2.2.1.1 Ochoa Case Study Comparative Phases______________________________________ 5.3.2.2.1.2 Case Study Hybridization_________________________________________________ 5.3.2.2.2 Ochoa Residential Case Study Results___________________________________________ 5.3.2.2.2.1 Ochoa Residential Case Study Result Comparison _____________________________ 5.3.2.2.3 Limitations to Comparisons to Past LCA Studies __________________________________ 5.3.2.3 Junnila / Guggemos Commercial Building Case Study __________________________________ 5.3.2.3.1 Junnila / Guggemos Commercial Building Case Study Results________________________ 5.3.2.3.1.1 Commercial Building Case Study Result Comparison __________________________ 5.3.2.4 RAND Commercial Building Interior Outfitting Case Study______________________________ 5.3.2.4.1 RAND Commercial Interior Outfitting Case Study Results __________________________ 5.3.2.5 Carnegie Mellon University Campus Design and Facility Development_____________________ 5.3.2.5.1 Commercial Building Renovation Case Study_____________________________________ 5.3.2.5.1.1 Commercial Renovation Case Study Results__________________________________ 5.3.2.5.2 New House Dormitory Construction Case Study___________________________________

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126 127 127 127 129 134 139 143 144 145 148 152 153 156 157 157 161

5.3.2.5.2.1 New House Dormitory Case Study Results ___________________________________ 5.3.2.5.2.2 New House Dormitory Case Study Result Comparison _________________________ 5.3.2.6 Large Public Construction Projects _________________________________________________ 5.3.2.6.1 Roadway Construction Case Study _____________________________________________ 5.3.2.6.1.1 Asphalt Paving Case Study Results _________________________________________ 5.3.2.6.1.2 Asphalt Paving Case Study Result Comparison _______________________________ 5.3.2.6.2 Bridge Superstructure Repair Case Study ________________________________________ 5.3.2.6.2.1 Bridge Repair Case Study Results __________________________________________ 5.3.2.6.3 Maintenance and Repair of Public Space Case Study _______________________________ 5.3.2.6.3.1 Other Public Repair Case Study Results _____________________________________

162 166 168 168 169 173 176 177 180 182

5.4 COMPARISON OF CASE STUDY RESULTS ______________________________________________185 5.4.1 Case Study Result Discussion _________________________________________________191 5.4.2 Sensitivity Analysis _________________________________________________________192 5.4.3 Uncertainty _______________________________________________________________197 5.4.4 Further Discussion of Analysis ________________________________________________199 CHAPTER 6: CONCLUSIONS AND RECOMMENDATIONS_____________________________201 6.1 CONCLUSIONS _________________________________________________________________201 6.1.1 Hybrid Model Summary______________________________________________________202 6.1.2 Contribution_______________________________________________________________204 6.1.3 Significance _______________________________________________________________205 6.2 RECOMMENDATIONS ____________________________________________________________207 6.2.1 Recommendations for Construction Industry Stakeholders Use of Hybrid Tool ___________207 6.2.2 Policy Recommendations _____________________________________________________210 6.2.3 Construction Industry Data Quality ____________________________________________210 6.3 FUTURE WORK _________________________________________________________________212 BIBLIOGRAPHY __________________________________________________________________217 APPENDIX A: TOWARDS A SUSTAINABLE GREEN BUILDING STANDARD ____________231 APPENDIX B: CONSTRUCTION SECTOR MAP DETAILS ______________________________257 APPENDIX C: APPLICABLE CONSTRUCTION INDUSTRY DATA FROM THE 2002 VEHICLE INVENTORY AND USE SURVEY ____________________________________________________309 APPENDIX D: NAICS-BASED REFORMULATED EIO-LCA CONSTRUCTION SECTOR ENVIRONMENTAL EFFECT VECTORS______________________________________________316 APPENDIX E: ITEMIZED DIRECT SUPPLY CHAIN EXPENDITURES FOR SELECTED CASE STUDIES__________________________________________________________________________323

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LIST OF TABLES TABLE 1: RELEVANT CONSTRUCTION INDUSTRY DATA SOURCES _________________________________8 TABLE 2: 1997 BENCHMARK MODEL EIO-LCA CONSTRUCTION SECTORS _________________________24 TABLE 3: SERVICE SECTORS FROM 1997 EIO-LCA BENCHMARK MODEL __________________________26 TABLE 4: REAL ESTATE AND INSURANCE SECTORS FROM 1997 EIO-LCA BENCHMARK MODEL _________27 TABLE 5: TRADE SECTORS FROM 1997 EIO-LCA BENCHMARK MODEL ___________________________27 TABLE 6: TRANSPORTATION SECTORS FROM 1997 EIO-LCA BENCHMARK MODEL ___________________27 TABLE 7: UTILITY SECTORS FROM 1997 EIO-LCA BENCHMARK MODEL __________________________28 TABLE 8: TOP 10 SECTORS FOR ECONOMIC CONTRIBUTION GIVEN $1 MILLION IN “COMMERCIAL AND INSTITUTIONAL BUILDINGS” I-O SECTOR AND ASSOCIATED GLOBAL WARMING POTENTIAL IMPACT 28 TABLE 9: COMPARISON OF PROCESS AND INPUT-OUTPUT LCA APPROACHES _______________________34 TABLE 10: SUMMARY OF SELECTED RESEARCH APPLICABLE TO CONSTRUCTION LCAS _______________38 TABLE 11: 1997 AND 2002 ESTIMATES OF GASOLINE AND DIESEL USE FOR CONSTRUCTION IN PETAJOULES ______________________________________________________________________________49 TABLE 12: 1997 AND 2002 CONSTRUCTION ENGINE EMISSIONS IN THOUSAND METRIC TONS ___________53 TABLE 13: 1999 – 2013 EMISSION STANDARDS FOR NONROAD DIESEL ENGINES UP TO 37 KW (50 HP) IN GRAMS / KILOWATT-HOUR__________________________________________________________56 TABLE 14: NAICS INDUSTRIES INCLUDED IN I-O SECTOR 230220 IN FINAL CSM ____________________64 TABLE 15: TYPICAL EXAMPLE OF I-O SECTOR AND NAICS INDUSTRY MAPPING ____________________66 TABLE 16: BEA MAPPING FOR ALL CONSTRUCTION SECTORS ___________________________________67 TABLE 17: CURRENT EIO-LCA MAP BETWEEN NAICS AND I-O CONSTRUCTION CODES (% NAICS INDUSTRY ALLOCATED TO I-O CODE)_________________________________________________68 TABLE 18: EXISTING EIO-LCA CONSTRUCTION SECTOR ENVIRONMENTAL EFFECT VECTOR DATA SOURCES ______________________________________________________________________________75 TABLE 19: 1997 ENERGY COMMODITY PRICES AND HEAT RATES USED FOR EXISTING EIO-LCA ENERGY VECTOR ________________________________________________________________________76 TABLE 20: 2002 ENERGY COMMODITY PRICES USED FOR REFORMULATED EIO-LCA ENERGY VECTOR __80 TABLE 21: REFORMULATED ENERGY ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS84 TABLE 22: REFORMULATED GWP ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS __89 TABLE 23: NAQET / NEI CATEGORIES INVOLVING CONSTRUCTION FOR 2002 NOX EMISSIONS (THOUSAND SHORT TONS) ___________________________________________________________________95 TABLE 24: 2002 CONSTRUCTION NAICS INDUSTRIES NOT ALLOCATED ANY PM10 FUGITIVE DUST EMISSIONS PER “SMART” ALLOCATION SCHEME _______________________________________103 TABLE 25: REFORMULATED CONSTRUCTION AIR POLLUTANT ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS _________________________________________________________106 TABLE 26: REFORMULATED TOXIC RELEASE INVENTORY ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS _________________________________________________________113 TABLE 27: REFORMULATED EIO-LCA CONSTRUCTION SECTOR ENVIRONMENTAL EFFECT VECTOR DATA SOURCES ______________________________________________________________________115 TABLE 28: ESTIMATE OF CONCEPTUAL ESTIMATE / BID ACCURACY _____________________________124 TABLE 29: CASE STUDIES MODELED WITH I-O-BASED HYBRID LCA FRAMEWORK__________________125 TABLE 30: OCHOA RESIDENTIAL CASE STUDY REVISIONS DEFINITIONS __________________________128 TABLE 31: OCHOA RESIDENTIAL CASE STUDY IN 1997 $ - ORIGINAL, CONVERTED, AND HYBRIDIZED ___132 TABLE 32: ITEMIZED DIRECT SUPPLY CHAIN EXPENDITURES FOR VIRGINIA DEPARTMENT OF TRANSPORTATION ROADWAY PAVING PROJECT IN WISE COUNTY, VA ______________________169 TABLE 33: ITEMIZED DIRECT SUPPLY CHAIN EXPENDITURES FOR DESIGN / BUILD BRIDGE SUPERSTRUCTURE REPLACEMENT IN ALLEGHENY COUNTY, PA __________________________________________176 TABLE 34: ITEMIZED DIRECT SUPPLY CHAIN EXPENDITURES FOR NORTHSIDE LIGHTING PROJECT IN PITTSBURGH, PA ________________________________________________________________181 TABLE 35: PROPOSED CONSTRUCTION SECTORS FOR 2002 EIO-LCA BENCHMARK MODEL ___________211

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LIST OF FIGURES FIGURE 1: LIFE CYCLE OF CONSTRUCTION PROJECT ____________________________________________2 FIGURE 2: PHASES OF A LIFE CYCLE ASSESSMENT ____________________________________________16 FIGURE 3: PERCENTAGE OF TOTAL ECONOMIC, GWP, AND TOTAL ENERGY RESULTS FOR EIO-LCA “NEW RESIDENTIAL 1-UNIT STRUCTURES, NONFARM” SECTOR BY SECTOR CATEGORY________________30 FIGURE 4: PERCENTAGE OF TOTAL ECONOMIC, GWP, AND TOTAL ENERGY RESULTS FOR EIO-LCA “COMMERCIAL & INSTITUTIONAL BUILDINGS” SECTOR BY SECTOR CATEGORY ________________30 FIGURE 5: PERCENTAGE OF TOTAL ECONOMIC, GWP, AND TOTAL ENERGY RESULTS FOR EIO-LCA “HIGHWAY, STREET, BRIDGE, & TUNNEL CONSTRUCTION” SECTOR BY SECTOR CATEGORY _______31 FIGURE 6: PERCENTAGE OF TOTAL ECONOMIC, GWP, AND TOTAL ENERGY RESULTS FOR EIO-LCA “MAINTENANCE & REPAIR OF HIGHWAYS, STREETS, BRIDGES, & TUNNELS” SECTOR BY SECTOR CATEGORY _____________________________________________________________________31 FIGURE 7: CONSTRUCTION PROJECT LIFE CYCLE AND PROPOSED SYSTEM BOUNDARY ________________37 FIGURE 8: 2002 CONSTRUCTION INDUSTRY AND SUBSECTOR ENERGY USE IN PETAJOULES _____________47 FIGURE 9: 2002 ELECTRICITY GENERATION EMISSION FACTORS IN GRAMS / KILOWATT-HOUR __________57 FIGURE 10: EXISTING CONNECTIONS BETWEEN U.S. DEPARTMENT OF COMMERCE INFORMATION _______63 FIGURE 11: DATA SOURCE AND PROCESS COMPARISON FOR EXISTING AND REFORMULATED ENERGY EFFECT VECTORS _______________________________________________________________________78 FIGURE 12: PERCENT DIFFERENCE BETWEEN “VALUE OF BUSINESS DONE” AND “EMPLOYMENT” ALLOCATION METHODS FOR 2002 NAICS CONSTRUCTION INDUSTRY CODES __________________82 FIGURE 13: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED ENERGY ENVIRONMENTAL EFFECT VECTOR (ELECTRICITY) FOR I-O CONSTRUCTION SECTORS __________________________85 FIGURE 14: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED ENERGY ENVIRONMENTAL VECTOR (LPG) FOR I-O CONSTRUCTION SECTORS _______________________________________86 FIGURE 15: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED ENERGY ENVIRONMENTAL EFFECT VECTOR (NATURAL GAS, MOTOR GASOLINE, AND DISTILLATE FUEL) FOR I-O CONSTRUCTION SECTORS _______________________________________________________________________87 FIGURE 16: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED GWP ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS ______________________________________90 FIGURE 17: COMPARISON OF SECTORAL % OF TOTAL VECTOR RATIOS BETWEEN EXISTING AND REVISED GWP EFFECT VECTORS & REVISED ENERGY EFFECT VECTOR ______________________________91 FIGURE 18: DATA SOURCE AND PROCESS COMPARISON FOR EXISTING AND REFORMULATED CONVENTIONAL AIR POLLUTANT EFFECT VECTORS ___________________________________________________93 FIGURE 19: COMPARISON OF EXISTING AND REFORMULATED 1999 AIRDATA BY I-O SECTOR __________94 FIGURE 20: 2002 NAQET / NEI EMISSIONS FOR TRADITIONAL AND ADDITIONAL (ON-HIGHWAY) CONSTRUCTION INDUSTRY SOURCES _________________________________________________97 FIGURE 21: DISTRIBUTION OF CONVENTIONAL AIR POLLUTANTS USING PERCENT USAGE OF GASOLINE AND DIESEL FUEL BY I-O SECTOR FROM REFORMULATED ENERGY VECTOR _______________________98 FIGURE 22: DISTRIBUTION OF CONVENTIONAL AIR POLLUTANTS USING PERCENT USAGE OF GASOLINE AND DIESEL FUEL BY I-O SECTOR FROM USE TABLE PETROLEUM ESTIMATES ______________________99 FIGURE 23: CONTRIBUTION OF FUGITIVE DUST TO PM10 EMISSIONS BY NAICS CONSTRUCTION INDUSTRY _____________________________________________________________________________104 FIGURE 24: CONTRIBUTION OF FUGITIVE DUST TO PM10 EMISSIONS BY I-O CONSTRUCTION SECTOR ____105 FIGURE 25: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED CAP ENVIRONMENTAL EFFECT VECTOR (CO, NOX, AND VOC) FOR I-O CONSTRUCTION SECTORS __________________________107 FIGURE 26: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED PM10 ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS _____________________________________108 FIGURE 27: TOTAL TRI ON- AND OFF-SITE DISPOSAL OR OTHER RELEASES, 1998 – 2004_____________109 FIGURE 28: COMPARISON OF 2000 AND 2003 TRI EMISSIONS FROM CONSTRUCTION-RELATED SIC CODES _____________________________________________________________________________111 FIGURE 29: PERCENT DIFFERENCE BETWEEN EXISTING AND REFORMULATED TRI ENVIRONMENTAL EFFECT VECTOR FOR I-O CONSTRUCTION SECTORS ____________________________________________114 FIGURE 30: SAMPLE MOCK-UP INTERFACE FOR EIO-LCA HYBRID FEATURE_______________________121 FIGURE 31: TOTAL ECONOMIC SUPPLY CHAIN IMPACTS FROM OCHOA RESIDENTIAL CASE STUDY RUNS _134

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FIGURE 32: REFORMULATED GLOBAL WARMING POTENTIAL RESULTS FROM OCHOA CASE STUDY RUNS 135 FIGURE 33: PERCENTAGE INCREASE IN RESULTS BY ENVIRONMENTAL CATEGORY FOR OCHOA RESIDENTIAL CASE STUDY (HYBRID VS. CONVERTED) ______________________________________________136 FIGURE 34: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR OCHOA RESIDENTIAL CASE STUDY ________________________________________________________________________137 FIGURE 35: NOX AND PM10 HYBRID MODEL RESULTS FOR OCHOA RESIDENTIAL CASE STUDY _________138 FIGURE 36: GWP HYBRID MODEL RESULTS FOR OCHOA RESIDENTIAL CASE STUDY ________________138 FIGURE 37: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR OCHOA RESIDENTIAL CASE STUDY _____________________________________________________________________________139 FIGURE 38: COMPARISON OF OCHOA ENERGY USE PER SQUARE FOOT TO PAST RESIDENTIAL LCAS ____140 FIGURE 39: COMPARISON OF OCHOA GWP PER SQUARE FOOT TO PAST RESIDENTIAL LCAS __________142 FIGURE 40: COMPARISON OF OCHOA AIR EMISSION RESULTS TO PAST RESIDENTIAL LCAS ___________143 FIGURE 41: TOTAL ECONOMIC AND EMPLOYEE RESULTS FOR COMMERCIAL BUILDING CASE STUDY ____146 FIGURE 42: NOX AND PM10 HYBRID MODEL RESULTS FOR COMMERCIAL BUILDING CASE STUDY ______147 FIGURE 43: GWP HYBRID MODEL RESULTS FOR COMMERCIAL BUILDING CASE STUDY ______________147 FIGURE 44: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR COMMERCIAL BUILDING CASE STUDY ________________________________________________________________________148 FIGURE 45: COMPARISON OF HYBRID LCA AND JUNNILA / GUGGEMOS AIR POLLUTANT EMISSION RESULTS FOR U.S. COMMERCIAL BUILDING ___________________________________________________149 FIGURE 46: COMPARISON OF HYBRID LCA AND JUNNILA / GUGGEMOS ENERGY USE AND CO2 EMISSION RESULTS FOR U.S. COMMERCIAL BUILDING ___________________________________________150 FIGURE 47: COMPARISON OF ORIGINAL AND HYBRID JUNNILA / GUGGEMOS COMMERCIAL BUILDING ENERGY USE RESULT TO PAST COMMERCIAL LCAS _____________________________________152 FIGURE 48: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR INTERIOR OUTFITTING CASE STUDY ________________________________________________________________________154 FIGURE 49: NOX AND PM10 HYBRID MODEL RESULTS FOR INTERIOR OUTFITTING CASE STUDY ________155 FIGURE 50: GWP HYBRID MODEL RESULTS FOR INTERIOR OUTFITTING CASE STUDY________________155 FIGURE 51: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR INTERIOR OUTFITTING CASE STUDY _____________________________________________________________________________156 FIGURE 52: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR COMMERCIAL INTERIOR RENOVATION CASE STUDY ________________________________________________________159 FIGURE 53: NOX AND PM10 HYBRID MODEL RESULTS FOR COMMERCIAL INTERIOR RENOVATION CASE STUDY ________________________________________________________________________160 FIGURE 54: GWP HYBRID MODEL RESULTS FOR COMMERCIAL INTERIOR RENOVATION CASE STUDY ___160 FIGURE 55: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR COMMERCIAL INTERIOR RENOVATION CASE STUDY ________________________________________________________161 FIGURE 56: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR DORMITORY CASE STUDY 163 FIGURE 57: NOX AND PM10 HYBRID MODEL RESULTS FOR DORMITORY CASE STUDY ________________164 FIGURE 58: GWP HYBRID MODEL RESULTS FOR DORMITORY CASE STUDY _______________________165 FIGURE 59: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR DORMITORY CASE STUDY _____166 FIGURE 60: COMPARISON OF NEW HOUSE DORMITORY ENERGY USE PER SQUARE FOOT TO PAST MULTIFAMILY LCAS _____________________________________________________________167 FIGURE 61: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR ASPHALT PAVING CASE STUDY ________________________________________________________________________170 FIGURE 62: NOX AND PM10 HYBRID MODEL RESULTS FOR ASPHALT PAVING CASE STUDY ____________171 FIGURE 63: GWP HYBRID MODEL RESULTS FOR ASPHALT PAVING CASE STUDY ___________________172 FIGURE 64: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR ASPHALT PAVING CASE STUDY _173 FIGURE 65: COMPARISON OF ASPHALT PAVING ENERGY USE PER LANE-MILE TO PAST PAVING LCAS___174 FIGURE 66: COMPARISON OF ASPHALT PAVING ENERGY USE PER DOLLAR TO PAST PAVING LCAS _____175 FIGURE 67: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR BRIDGE REPAIR CASE STUDY _____________________________________________________________________________178 FIGURE 68: NOX AND PM10 HYBRID MODEL RESULTS FOR BRIDGE REPAIR CASE STUDY _____________179 FIGURE 69: GWP HYBRID MODEL RESULTS FOR BRIDGE REPAIR CASE STUDY _____________________179 FIGURE 70: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR BRIDGE REPAIR CASE STUDY __180 FIGURE 71: TOTAL ECONOMIC AND EMPLOYEE HYBRID MODEL RESULTS FOR OTHER PUBLIC REPAIR CASE STUDY ________________________________________________________________________183

- xii – Chapter 1

FIGURE 72: NOX AND PM10 HYBRID MODEL RESULTS FOR OTHER PUBLIC REPAIR CASE STUDY _______184 FIGURE 73: GWP HYBRID MODEL RESULTS FOR OTHER PUBLIC REPAIR CASE STUDY _______________184 FIGURE 74: GASOLINE AND DIESEL FUEL HYBRID MODEL RESULTS FOR OTHER PUBLIC REPAIR CASE STUDY _____________________________________________________________________________185 FIGURE 75: COMPARISON OF HYBRID MODEL NOX RESULTS FOR EXISTING EIO-LCA AND REFORMULATED ENVIRONMENTAL EFFECTS ________________________________________________________187 FIGURE 76: COMPARISON OF HYBRID MODEL PM10 RESULTS FOR EXISTING EIO-LCA AND REFORMULATED ENVIRONMENTAL EFFECTS ________________________________________________________188 FIGURE 77: COMPARISON OF HYBRID MODEL GWP RESULTS FOR EXISTING EIO-LCA AND REFORMULATED ENVIRONMENTAL EFFECTS ________________________________________________________188 FIGURE 78: COMPARISON OF HYBRID MODEL GASOLINE USE RESULTS FOR EXISTING EIO-LCA AND REFORMULATED ENVIRONMENTAL EFFECTS___________________________________________189 FIGURE 79: COMPARISON OF HYBRID MODEL DIESEL FUEL RESULTS FOR EXISTING EIO-LCA AND REFORMULATED ENVIRONMENTAL EFFECTS___________________________________________190 FIGURE 80: TOP 10 CONTRIBUTING SECTORS TO HYBRID MODEL NOX EMISSIONS FOR ALL CONSTRUCTION IO SECTORS ____________________________________________________________________193 FIGURE 81: TOP 10 CONTRIBUTING SECTORS TO HYBRID MODEL PM10 EMISSIONS FOR ALL CONSTRUCTION I-O SECTORS ___________________________________________________________________194 FIGURE 82: TOP 10 CONTRIBUTING SECTORS TO HYBRID MODEL GWP EMISSIONS FOR ALL CONSTRUCTION I-O SECTORS ___________________________________________________________________195 FIGURE 83: TOP 10 CONTRIBUTING SECTORS TO HYBRID MODEL TOTAL ENERGY USE FOR ALL CONSTRUCTION I-O SECTORS ______________________________________________________196

- xiii – Chapter 1

ABBREVIATIONS Abbreviation BDGC BEA BEES BLS CAP CEE Census CMU CSM CWM DOC DOE DOT EIE EIO-LCA EPA EPP GAMS GDI GWP HFO I-O IPCC ISO LCA LCI LCIA LEED® LFO LPG NAICS NAQET NEI NIPA NIST NREL TRI URA USGBC VIP VIUS

Description Building, Developing, & General Contracting (NAICS Industries) Bureau of Economic Analysis Building for Environmental & Economic Sustainability (LCA tool) Bureau of Labor Statistics Criteria air pollutant(s) Department of Civil and Environmental Engineering U.S. Census Bureau Carnegie Mellon University Construction Sector Map Construction waste management Department of Commerce Department of Energy Department of Transportation ATHENATM Environmental Impact Estimator (LCA tool) Economic Input-Output Life Cycle Assessment (I-O LCA model) Environmental Protection Agency Department of Engineering and Public Policy General Algebraic Modeling System Green Design Institute Global Warming Potential Heavy fuel oil Input-Output Intergovernmental Panel on Climate Change International Organization for Standardization Life cycle assessment Life cycle inventory Life cycle impact assessment Leadership in Energy and Environmental Design Light fuel oil Liquefied petroleum gas North American Industry Classification System National Air Quality and Emissions Trends Report National Emissions Inventory National Income and Product Accounts National Institute of Standards and Technology National Renewable Energy Laboratory Toxic Release Inventory Urban Redevelopment Authority of Pittsburgh U.S. Green Building Council Value Put in Place Vehicle Inventory and Use Survey - xiv – Chapter 1

CHAPTER 1: INTRODUCTION In its infancy, the base goal of this research was to determine how the amount of resources required and pollutants emitted from construction sites could be reduced. The actual modeling attempt that ensued is much more complex than the original objective, but it expands the original question while supplying answers and an analysis mechanism for stakeholders whose numbers have vastly expanded since the project began in 2003. This proliferation of parties interested in reducing the impacts of construction is a direct result of green building industry growth. Consequently, it is an objective of this research to provide information to policy makers and green builders that supports and initiates future attempts to reduce the air, water, and solid waste pollutants from the infrastructure life cycle by focusing on on-site construction activities and their supply chain. This shift in infrastructure impact focus is supported by the input-output-based hybrid life cycle assessment model for construction processes described herein. Background is provided on the construction industry, life cycle assessment, and environmental data sources, while the methods utilized in creation of the input-outputbased hybrid life cycle assessment model are outlined, utilized, and analyzed. 1.1

Motivation As a prevalent fixture around the world and a economic indicator of the U.S.

economy, the economic impacts of the construction industry are undeniable at 5% of the U.S. GDP (DOC 2005d). Prevalent, yet unregulated in many ways, construction has great potential for reducing its ecological footprint. But, as the building industry has gradually been undergoing a “green revolution” with the growth of the concept of “green building,” few holistic sustainable practices have been applied to the construction industry itself. The majority of past building research has focused on the environmental impacts of material selection, building energy use, and indoor environmental quality (Horvath 2004; Koomey et al. 2001; Lee and Chang 2000; Lippiatt and Norris 1995; Osman and Ries 2003). While these effects are undeniably vast and important, the construction industry itself is also responsible for many environmental impacts, primarily air

-1– Chapter 1

emissions, land use, waste generation, water use and discharges, and energy use and demand (Bilec et al. 2007; Ochoa et al. 2002). However, most LCAs either ignore or negate the construction phase of infrastructure projects. If the entire life cycle of a structure (shown in Figure 1) is ever to be truly quantified, a life cycle assessment (LCA) of the construction phase of a project must be performed to help place construction’s environmental impacts in context with the rest of the building process.

Figure 1: Life Cycle of Construction Project Past building LCAs have used existing underestimations of construction activity instead of addressing the construction process as requiring renovation in terms of environmental effects (Junnila and Horvath 2003; Keoleian et al. 2001; Ochoa et al. 2002). This problem is common to environmental impacts from all types of infrastructure, of which constructed facilities are a subset. Because the environmental impacts of the construction site have never been adequately quantified, the assumption -2– Chapter 1

that the effects of construction are negligible in comparison with the other building phases is supposition based on the status quo. Consequently, many existing decision models ignore the environmental impacts of infrastructure construction because these impacts were assumed to be negligible at the start of the assessment in question. The input-output-based LCA model specifically for construction processes that has been created for this research attempts to remedy this problem. Thus, even if the environmental impacts from infrastructure and construction are small compared to building operation, once adequately quantified, these impacts may be large when analyzed in a different time frame or as a function of all buildings (i.e., a marginal vs. total comparison). Additionally, the model created here attempts to more appropriately serve infrastructure stakeholders interested in creating a more sustainable construction industry than other LCA tools. As a result, the input-output-based LCA model is in the public domain (http://www.eio-lca.net/aurora-hybrid.html), useable with existing construction project information, and easily comparable to other estimation methods. 1.2

Research Objectives Much of the current focus of sustainability and life cycle assessment within the

green building movement focuses on building materials (Gambatese and Rajendran 2005; Kreissig and Binder 2005). Conversely, this research focuses on the efficiency, economic effect, and environmental impact of construction activities, not construction materials. Only through completely analyzing the economic costs and environmental impacts of on-site construction can we move past the simple building analysis that the green building standards like the U.S. Green Building Council’s (USGBC) Leadership in Energy and Environmental Design (LEED®) has started and towards a complex building LCA model that incorporates the site, construction, skeleton, interior, operation, and maintenance aspects of creating a structure. In-depth assessment of the existing and future status of LEED and green building activities is provided in Appendix A. One tool available to assess and manage the environmental impacts of the construction process is life cycle assessment. LCA is a modeling tool that holistically estimates the environmental effects of a product, process, or activity by evaluating its entire life (commonly referred to as cradle-to-grave, cradle-to-cradle, or cradle-to-gate -3– Chapter 1

modeling). LCA is a decision-support tool that presents the economic and environmental impacts of various processes, while inherently providing a sustainable outlook / assessment of the topic being considered by including the global, national, and regional social and environmental impacts. The two primary LCA approaches are process LCA and input-output LCA. These approaches are described in-depth in Chapter 2. Both methods have strengths and weaknesses; this research combines the two methods into a “hybrid” LCA tool. Current process LCA models either ignore or underestimate the environmental impacts of the construction process. This research includes a brief overview of how these existing process-based LCA software packages address the construction process. Because input-output (I-O) LCA models require national-level data collection, they are much more complex; thus, there are only a few operating. The I-O tool of focus for this research is Carnegie Mellon University’s Economic Input-Output Life Cycle Assessment tool (EIO-LCA), which models the U.S. economy (CMU GDI 2007). As described in Section 3.3.2 and Appendix B, the modeling problems with EIO-LCA’s construction sectors are complex and the impetus for creation of a hybrid model. Environmental impacts for the thirteen construction sectors in the existing EIO-LCA 1997 benchmark model are distributed in a uniform manner instead of via more informed techniques. Thus, the existing EIO-LCA modeling scheme is simplified and improperly represents the environmental discharges from the construction industry. More detailed discussion regarding the thirteen EIO-LCA construction sectors, their economic interaction with each other, and the assumptions on which these interactions are based is provided in Sections 2.3.1. The possible measures of dealing with and improving EIO-LCA’s integrated assumptions about the construction sectors are the backbone for the hybrid model, which improves estimates of the environmental impacts of construction processes and their related activities. One of the goals of this project is to adequately quantify the environmental impacts of construction and determine whether or not they are larger than previous estimates, thus requiring they be re-accounted for in other LCAs. Even though the construction industry uses considerable resources and energy that in turn produce significant emissions to the natural environment, the built environment continues to -4– Chapter 1

consume resources and produce emissions once the actual construction phase of the project has been completed (a.k.a. during the operation phase). Additionally, the hybrid LCA model created here improves on existing construction models by addressing concerns like boundary issues, uncertainty, and applicability to construction. The model does all of this by allowing the input of processlevel information into the hybrid framework so that all results have the benefit of projectspecific information in addition to average supply chain information for each of the economic interactions required. The hybrid LCA model for construction processes explained within is accessible via the EIO-LCA website (http://www.eiolca.net/aurora-hybrid.html) as a tool to help inform and guide public and private decision-makers faced with problems related to the construction industry’s environmental effects. In the short-term, these “consumers” include LCA practitioners, academics, and green building professionals interested in minimizing the ecological footprint of their infrastructure projects by focusing on the construction process. Construction estimators could also use the hybrid LCA tool for decisions as simple as determining which mode of transportation should be utilized to and from site to minimize certain environmental emissions. Additionally, the hybrid tool has been utilized to determine which aspects of the construction process require further research and development so that given pollutants or impacts can be minimized. It is the eventual goal of this research to encourage construction companies to use the hybrid LCA tool to target potential areas of improvement on their own. In the long-term, the information this model provides could help the U.S. government and other organizations like the USGBC reevaluate and refine their construction industry legislation and standards. Because current construction industry regulations are broadly focused, the results of this research can support development of regulations that could facilitate movement of the construction industry and construction sites towards a more sustainable status quo. The hybrid LCA tool subsequently described estimates many aspects of the construction industry that are often underestimated, underreported, or ignored; consequently, it has the potential to be utilized by a variety of construction industry stakeholders, including academics, contractors, and public policy makers. Because the -5– Chapter 1

model’s results are presented via the EIO-LCA framework in a manner accessible to all stakeholders, this research should trigger greater interest in the environmental performance of construction and cause construction stakeholders to reassess their view of construction’s environmental footprint. 1.2.1

The Construction Industry The construction industry is a sizeable contributor to the U.S. economy, using

significant quantities of resources and energy, while discharging considerable levels of environmental pollutants. Despite the fact that construction is a large, visible activity, industry-wide issues are often difficult to control because of the industry’s dispersed nature. Instead of having large, stationary emission sources like the manufacturing industry does in factories, construction sites are constantly changing their location, their labor pool, their resource suppliers, and their magnitude. Construction site activities are constantly shifting, with a variety of workers and processes in use at any one time, yet some projects last only a few hours or days, while others stretch on for decades. Research on construction site impacts has been primarily limited to construction waste management (Franklin Associates 1998) and nonroad vehicle emissions (EPA 1991). Legislation has been limited to wetlands preservation, soil erosion control, and, in some jurisdictions, open burning of wastes. The green building movement’s focus (to date) on designing and occupying buildings that achieve higher energy and environmental efficiency is well founded, as over a building’s life cycle, the use phase leads to the highest energy consumption (Keoleian et al. 2001; Ries 2000). However, in terms of toxic emissions and resource use, the material production and construction phases are more important (Ochoa et al. 2002). This varied result provides a renewed purpose for reconsidering the implications of more sustainable construction practices. 1.2.1.1

Impact of the U.S. Construction Industry It is often quoted that the construction industry is 5% of the U.S. GDP (BEA

2005c; DOC 2005d). Per the BEA, the construction industry grew an average of 6% annually between 1997 and 2002 (one of the higher industry growth rates) (Stanley-Allen et al. 2005). Because the construction industry is a major force in the national and global -6– Chapter 1

economy, it is imperative that building industry stakeholders address the issue of construction sustainability. The construction industry had approximately $850 billion and $1.2 trillion worth of expenditures in 1997 and 2002, respectively; the environmental impacts resulting from this level of spending is a topic that few are addressing on an industry-wide level (DOC 2000; DOC 2005a). Increasing interest in LEED®, the green building framework created and facilitated by the USGBC, indicates that building owners and the design and construction industry have begun to recognize the negative environmental impacts of buildings; however, the direct impacts of on-site construction processes are often overlooked and underestimated. The construction industry is responsible for many environmental impacts (Bilec et al. 2007; Ochoa et al. 2002); the need for these specific impacts to be quantified and placed in an interpretable and useable form is pressing, especially when one realizes how prevalent construction is and how much it affects daily life. Recent research indicates that in terms of fuel usage, construction consumes 4% of gasoline and 22% of diesel fuel used in the U.S. annually (Sharrard et al. 2007a). With such a large percentage of U.S. diesel fuel consumption, the construction industry has more resulting impacts from air emissions and other environmental outputs than previous estimates have been willing to assign it. Additionally, the construction industry’s intermixing with other service industries (i.e., accounting, engineering, etc.) indicates that environmental impact estimates based solely on simplified modeling of the construction industry are incorrect. 1.2.1.2

Construction Industry Data Sources There is a variety of construction industry-specific data available for analysis.

Much of this data is economic and related to the Economic Census, which is performed every 5 years (1992, 1997, 2002, etc.); however, there is usually a time lag in the dissemination of Economic Census data: it usually takes another 5 years for this data to be processed and released. EIO-LCA is based on Economic Census data. When compared to the electricity generation industry, for example, there are few stationary emissions sources in the construction industry that are required to report their emissions or wastes directly to the Environmental Protection Agency (EPA). As a result, -7– Chapter 1

the construction industry’s emissions and resource use are usually estimated from survey data. Then, emissions estimates are often aggregated with emission factors; further allocation to the construction sectors is unclear and ambiguous. Consequently, estimates of environmental impact based on current construction data is unclear, if not inaccurate. Emissions from the construction industry are not otherwise tracked, unless companies choose to do so on their own. Even when such data is tracked within a company, it is often difficult for researchers to obtain, as it is project-specific instead of time, spending, or spatially specific. Additionally, companies often view this information as proprietary and are unwilling to share and/or extract it. There is a small pool of data sources available for use in creation of a construction LCA model and the majority of them were utilized for this project; a list is provided in Table 1. Because this model will be an input-output-based hybrid, many of the sources listed in Table 1 are I-O or NAICS-based. Table 1: Relevant Construction Industry Data Sources Source

Type Input-Output Tables (I-O)

Bureau of Economic Analysis

Census Bureau

I-O Use Table National Income and Product Accounts (NIPA) Standard Industrial Classification (SIC) North American Industry Classification System (NAICS) Value Put in Place (VIP) Economic Census Vehicle Inventory and Use Survey (VIUS) AirData Facility SIC Report

Environmental Protection Agency

Categories Covered All economic sectors Electricity and fuel use; GWP All economic sectors Classification system only Classification system only Construction sectors High-level economic sectors Vehicle numbers, use, and fuel Criteria air pollutants

Most Recent Year Available

Used for EIO-LCA

1997

1997

1997

1997

2007

No

1997 2002

As comparison As comparison

2007

No

2002

1997

2002

No

1999

199

National Air Quality and Emissions Trends (NAQET) / National Emissions Inventory (NEI)

Conventional pollutants by high-level sector

2002

1997

Toxic Release Inventory (TRI)

Toxic releases (SIC-based)

2005

2000

-8– Chapter 1

Each of the data sources in Table 1 was investigated as to its viability of use; details are provided in Chapters 3 and 4. Data sets applicable to the construction industry, but not used in the existing EIO-LCA model because of difficulties applying them to the entire economy, have been utilized to complement the I-O-based hybrid LCA model. Additionally, project-specific process-level data used for the case studies in Chapter 5. 1.2.1.2.1

National-Level Air Emissions

In terms of air emissions, the majority of air emission estimates for the construction industry are available via the national-level datasets summarized in Table 1. A few regional datasets have been located, but are not comprehensive enough to be applicable to the national-level estimates being created in this research; they are more applicable to regional EIO-LCA research (Cicas 2005; Mid-Atlantic/Northeast Visibility Union 2006). An alternative analysis was also made to compare local air monitor data with known locations and timeframes of construction activity to determine if increases in criteria air pollutant (CAP) levels paralleled past and present construction activity. Preliminary investigation indicated that there is a correlation between the concentration of air pollutants and activity on large construction sites located within approximately half of a mile of appropriate air monitors (Sharrard et al. 2007b). Future research into this correlation is recommended for other projects and locales. 1.2.1.2.2

Vehicle Inventory and Use Survey

Because there is no existing summary of vehicle use specific to the construction industry, this research included analysis of the 2002 Vehicle Inventory and Use Survey (VIUS). As this information was difficult to extract and does not exist elsewhere in print, a graphical summary of significant construction industry VIUS information is summarized in Appendix C (DOC 2005c). The average reported registered weight of construction vehicles was 960 pounds; when “zero” answers were excluded, this number jumped to 2,000 pounds. Additionally, 93% of “construction” survey respondents said that their vehicles pull no trailer and 7% -9– Chapter 1

of respondents reported that their vehicle pulled a single trailer. The other notable VIUS construction industry information is summarized in Appendix C. 1.2.1.3

Framing Construction in an Environmental Context The construction industry is unique compared to the rest of the U.S. economy,

though the building industry itself has also been recognized as a complex entity elsewhere in the world (Udo de Haes 2001a; Udo de Haes 2001b). Whereas other U.S. industries have distinct products and manufacturers, construction is a very diffuse entity, with multiple types of contractors, all of who have very specific responsibilities in creating a building or piece of infrastructure, but whose progress and specific impacts on the larger project are very difficult to track by means other than economics. Even these seemingly simple dollar expenditures are increasingly complicated, as there are general contractors who are in charge of subcontractors; these subcontractors may have their own subcontractors, who have their own subcontractors, etc. Additionally, the subcontractor team and relationships can differ from project to project, making standardized modeling and data collection even more complex. Obviously, for very large construction projects, tracking who is in charge of what, as well as how many materials, wastes, and environmental impacts each of these subcontractors is responsible for becomes increasingly difficult. Consequently, when large governmental agencies like the Department of Commerce (DOC), Department of Energy (DOE), and EPA attempt to survey construction companies about the economics and environmental impacts of their activities, complex scenarios occur that can either double count or miscount (and misallocate) subcontractor activity (especially with large projects where a contractor is working for the owner on one part of the project, but as a subcontractor on another part of the project). This subcontractor issue is one of the main problems with calculating an adequate estimate of the construction industry’s environmental impacts. It creates questions about data reliability and veracity, while simultaneously limiting the methods that can be utilized to create proper estimates. As a result, few existing LCAs have attempted to tackle the environmental modeling of the construction industry. With a constantly - 10 – Chapter 1

rotating source of labor, ever-changing seasonal economic contribution, and differential spatial distribution, it is certainly not easy to quantify the construction industry’s environmental impacts. Thus, part of the lack of research for the construction phase of an LCA exists because of inconsistent industry data collection. The recent domestic and global emphasis on “green building” has wrought the first major changes the U.S. construction industry has faced in decades. As this trend continues and governmental regulations applying to construction are revised, the baseline on which these proposed reductions are established must be analyzed, verified, and modified. This research hopes to improve the basis of such decisions by creating a tool that creates estimates of the construction industry’s economic and environmental impacts that improve on those currently provided by the U.S. government and private process LCA software. 1.2.1.4

Construction and LEED An in-depth discussion of LEED, the main impetus for broad green building

growth, through 2005 is provided in Appendix A. LEED has undergone several changes since Appendix A was last updated, but the current LEED for New Construction standard (Version 2.2) focuses on only three areas of construction sustainability: fugitive dust emission reductions, construction waste management (CWM), and indoor air quality (USGBC 2005). While these construction impacts are important, this research establishes that there are other areas of concern if the construction industry is to reduce and even minimize its environmental impacts, most specifically on-site construction activities and machinery, as well as support activities from transportation, utility, and service sectors. Transportation is an interesting construction issue because it might be provided by a construction firm (and counted in that sector) or contracted out, maybe in the purchase price of supplies (and counted as part of the supply chain). LEED does address transportation, but only for regional materials, with no differentiation between who demands it; for a green building standard to address transportation at all is definitely unique (Bunz et al. 2006). Given that the environmental impacts of any product or

- 11 – Chapter 1

process can be significantly reduced through focusing on transportation, it is surprising that more standards do not target it as an area for improvement. Two specific LEED credits that attempt to reduce the environmental effects of transporting goods to construction sites are Materials and Resources (MR) credits 5.1 and 5.2. In LEED-NC version 2.1, one point was awarded for MR 5.1 if 20% of building materials and products were manufactured regionally (within 500 miles); another point was awarded for MR 5.2 if 50% of building materials and products were extracted, harvested, recovered, and manufactured within 500 miles (USGBC 2003). What these credits failed to take into account was the mode of transportation and the distance traveled. For example, truck transport may be advantageous up to 300 miles, but for longer distances, train transport may be more economically feasible and/or less environmentally detrimental (Matthews et al. 2001a). Additionally, in certain parts of the country where these distances might include land in Mexico or Canada, the definition of what resources are “local” may require new definition through LCA (Bilec et al. 2007). A better way to account for economic and environmental impacts of transportation might be to use LCA and/or accepted emissions factors to determine how to appropriately modify LEED credits like these (Horst 2003). In an attempt to address these approximations, LEED-NC, Version 2.2, altered MR 5.1 and 5.2, among other credits. The revised MR 5.1 credit awards respective points for 10 and 20% “regional” materials (i.e., those extracted, harvested, processed, and manufactured within 500 miles) by cost (USGBC 2005). This credit change is not significant from LEED-NC 2.1. However, an earlier edition of the LEED-NC, Version 2.2, edit attempted a much larger deviation, addressing shrinking the “regional” distance definition and environmental impacts from different modes of transportation. This internal USGBC revision specified that at least 80% of the mass of at least 10% of building materials or products be extracted, processed, and manufactured either within 300 miles of the project site or within 1,000 miles of the project site (and shipped by rail or water in the latter case); another option was that a minimum of 10% of building materials or products be specified that “reflect a combination of the above extraction, processing, manufacturing and shipping criteria (e.g., 5% within 300 miles and 5% shipped by rail within 1,000 miles)” (USGBC 2004e). The revised MR 5.2 credit - 12 – Chapter 1

required at least 80% of the mass of at least 20% of building materials or products to adhere to the same restrictions as MR 5.1 (USGBC 2004e). These mode and distancespecific LEED credits were not enacted and LEED-NC, Version 2.2 awards points for 10 and 20% “regional” materials by cost, which are those extracted, harvested, processed, and manufactured within 500 miles (USGBC 2005). 1.3

Thesis Outline Chapter 1 of this dissertation has provided an introduction to the motivation,

research objectives, and construction industry background of this research. Chapter 2 includes a literature review of the various types of life cycle assessment (LCA), as well as a discussion of its past applications and pertinence to the construction industry. A synopsis of the optimal hybrid LCA inclusions for construction in provided in Chapter 3, followed by background regarding support sectors, on-site energy, and the construction sector map (CSM) for the 13 EIO-LCA construction sectors and the 28 NAICS construction industries; the detailed methods used to create the CSM are provided as Appendix B. Chapter 4 covers the update and reformulation of the EIO-LCA construction sector environmental effect vectors, and Chapter 5 summarizes how various methods were combined to create the actual I-O-based hybrid LCA model that more accurately and completely assesses the environmental impacts of the construction process than existing tools. Also in Chapter 5, the results from running a variety of construction case studies through the model are summarized and compared to existing LCA estimates of construction industry impact. Conclusions, recommendations, and an outline of suggested future research are provided in Chapter 6. The Appendices are also integral to comprehension of this work. Appendix A is my otherwise unpublished master’s thesis, “Towards a Sustainable Green Building Standard,” which addresses the sustainability of the LEED standards and system; it was last edited in 2005. As mentioned previously, Appendix B is the continuation of the detailed breakdown of the CSM creation initiated in Section 3.3.2; both of these sections were partially written by Melissa Bilec. Appendix C is a graphically summary of construction industry information from the 2002 Vehicle Inventory and Use Survey, and Appendix D provides the NAICS-based construction industry environmental effect - 13 – Chapter 1

vectors developed in conjunction with the I-O-based construction sector environmental effect vectors detailed in Section 4.2. Appendix E includes process-level direct supply chain data for selected case studies; similar information for case studies with shorter supply chains are provided in Section 5.3.2.

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CHAPTER 2: LIFE CYCLE ASSESSMENT 2.1

Background LCA is an increasingly prevalent scientific approach to comprehensive analysis of

the environmental impacts of a given product or process (Vigon et al. 1993). A wellperformed LCA is a systematically inclusive inventory and impact assessment for each life cycle stage of a given product. The phases for which impacts are determined often include resource extraction, material production, manufacturing, assembly, use, and disposal (reuse, recycling, incineration, or landfill). Based on assessment of each phase’s environmental impact, improvements can then be made to selected aspects of a product or process’s development to minimize the ecological footprint over its life cycle. What follows is a limited literature review of LCA. The American National Standards Institute (ANSI) and the International Organization for Standardization (ISO) have delineated the national and international standard for life cycle assessment with the ISO 14040 environmental management series. Per ISO, LCA is a “compilation and evaluation of the inputs, outputs, and the potential environmental impacts of a product system throughout its life cycle” (ANSI / ISO 1997). ISO’s LCA standards state that a LCA incorporates a goal and scope definition, life cycle inventory (LCI), and life cycle impact assessment (LCIA). After each of these steps, interpretation and iteration are also required; thus, each step is redefined repeatedly. ISO’s LCA framework is depicted in Figure 2. Many LCAs actually stop at the inventory step, as impact assessment can complicate interpretation of results if all decision-makers are not from similarly minded institutions or have consistent goals. LCIs typically include dozens of inputs and outputs; the former is usually resources and the latter environmental discharges. LCIA has traditionally included global warming potential, ozone depletion potential, eutrophication potential, land use, ecosystem destruction, and human toxicity potential, among others.

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Figure 2: Phases of a Life Cycle Assessment (ANSI / ISO 1997) Two LCA approaches are most common: one is based on detailed process model descriptions and corresponding emissions and wastes, while the other is based on economic input-output data and publicly available resource consumption and environmental discharge data. Both approaches have advantages and limitations. Thus, while LCA has been recognized worldwide as an important tool for environmental performance measurement and management of products and processes, it has also been criticized for being tedious, expensive, and slow to generate results, especially when trying to include all upstream components, which requires working through the hierarchy of process models in the supply chain while trying to match ever-decreasing product development cycles (Arnold 1993; Curran 1996; Portney 1993-94). Additionally, data is often proprietary, so cannot be shared. Also, due to different assumptions and boundary conditions used in different LCAs, results are sometimes difficult to compare. Additionally, because many modern processes that yield multiple products, there are often issues surrounding how various resource uses and environmental outputs should be allocated (i.e., by weight, dollar, etc.) 2.2

Process Life Cycle Assessment A number of research groups worldwide have developed process LCA approaches

and databases. In the U.S., the Society for Environmental Toxicology and Chemistry - 16 – Chapter 2

(SETAC) and the EPA have spearheaded development efforts (Fava et al. 1991; Keoleian and Menerey 1993; Lawson et al. 2002; Vigon et al. 1993). Some LCA models use mass-balance calculations for process models that identify and quantify inputs and outputs at each life cycle phase (Curran 1996; Fava et al. 1991; Strassman 1988). This process approach often requires detailed data be collected directly from companies, public databases, or published studies. Process LCA was the basis for the creation of the ISO 14040 standards (Technical Committee 207 1998). Additionally, Graedel and Allenby developed “streamlined LCA,” which employs matrices for products and processes (Graedel 1998; Graedel et al. 1995). Life cycle assessment is a holistic tool that considers influences beyond the scope typically utilized by metrics (which quantify the worth or impact of a product or process). However, in process LCA, the boundary around the problem is often drawn tightly for practical reasons, inadvertently excluding potentially important upstream and downstream life cycle components. While detailed, specific data on processes and materials is often necessary and unavoidable for detailed process LCAs, time and money are often decisive factors in determining if an LCA will be conducted at all. In terms of construction, very few process LCAs of just construction activities have been performed and many of those that do exist are based on extremely projectspecific or national-level data. Even SETAC’s own recommendations for LCAs of building and construction recommend that this phase can be omitted in certain types of LCAs and acknowledge that even when included, it is often incomplete due to incomplete data (Kotaji et al. 2003). In creating a workable hybrid LCA framework, it was necessary to briefly assess various process LCA modeling software like BEES, GaBi, SimaPro, and Athena, to determine whether or not their treatment of a project’s construction phase and associated data conforms to data requirements for the proposed hybrid LCA model (Athena Institute 2006a; NIST 2004; PE Consulting Group 2004; Pre 2007). 2.2.1

Existing Pure Process LCA Tools’ Applicability to Construction Because there are a variety of existing process-based LCA tools in the building

marketplace that analyze the life cycle economic and environmental impacts of building - 17 – Chapter 2

materials (BEES, GaBi, SimaPro, and Athena), there is already a small foundation of process-based construction data that could have supported the hybrid model (in theory). However, it should not be overlooked that process-based LCAs scrutinize specific processes for creating and transporting certain products, and their specificity is both their strength and downfall. Existing process-based data is also heavily reliant upon the boundary chosen by creators or users of each respective framework. This boundary can exclude or inadvertently eliminate important input aspects of a product or process and must be considered. In an attempt to move beyond the boundary limitations of process LCA, the ultimate goal behind creating a hybrid LCA framework is to gain a more comprehensive estimate of the impacts of construction processes; current process-based and I-O models have not evolved in this manner. 2.2.1.1

BEES A process LCA model approach used in a large number of construction-related

applications is Building for Environmental and Economic Sustainability (BEES), a software tool developed by the National Institute of Standards and Technology (NIST) to estimate the implications of materials selection in infrastructure planning, mostly for buildings (Lippiatt and Norris 1995). The green building movement has fueled the growth and popularity of BEES, which provides economic and environmental data for 200+ building products (NIST 2004). BEES is based on manufacturer data, which can be unreliable and includes a certain amount of uncertainty. BEES is also material-based and does not include on-site construction processes, so its applicability to the hybrid LCA being created here is negligible. 2.2.1.2

GaBi All data provided in the GaBi software is from Germany and thus inapplicable to

U.S. construction sites (PE Consulting Group 2004). Even so, the software was investigated for its pertinence to construction processes. Under the “Flows, Ecoinvent” category, GaBi offers three “construction processes:” buildings, civil engineering, and

- 18 – Chapter 2

machines; data for all of these data flows was last updated on January 1, 2004. Under the “Buildings” category, the choices include the following: • • •

• • •

CH: building, hall CH: building, hall, steel construction CH: building, hall, wood construction

RER: building, multi-storey RER: electronics for control units RER: facilities, chemical production

Under the “Civil Engineering” category, the choices are as follows: • •

•

RER: blasting RER: excavation, hydraulic digger

•

RER: excavation, skid-steer loader RER: hydraulic digger

Under the “Machines” category, the choices are as follows: • • • • • •

GLO: diesel, burned in building machine RER: building machine RER: conveyor belt, at plant RER: crushing, rock RER: Industrial machine, heavy, unspecified, at plant RER: power saw, with catalytic converter

• • •

RER: power saw, without catalytic converter RER: power sawing, with catalytic converter RER: power sawing, without catalytic converter

There is also a “construction products” category under the “Processes, Production” heading, but only 18 products are listed, whereas many more go into each construction project. As all GaBi LCAs must be created from scratch, assembling all of the processes necessary for a true supply chain assessment of construction site impacts would be timeconsuming and is limited by the small array of construction-specific databases GaBi offers. While it is possible to create your own database and add in project-specific processes and products, GaBi is currently designed more for products than processes, especially if those processes are construction-related. A short literature review did not uncover any published GaBi results for buildings, construction, or infrastructure. However, GaBi is releasing a new land use and social LCA database in Spring 2007 that is expected to expand their offerings.

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2.2.1.3

SimaPro Users of SimaPro have reported that it is easy to use and self-explanatory.

However, similar to GaBi, much of the data provided in SimaPro is international, and thus not applicable to U.S. construction sites (Pre 2007). Even so, the SimaPro software was investigated regarding its applicability to construction sites. No SimaPro databases provide any on-site construction processes (e.g., earthmoving) as building blocks to help create an LCA. However, SimaPro’s databases do offer a whole building mass process that can be used as an LCA building block, but it is unclear whether or not this process includes on-site construction. Either way, the whole building mass process cannot be used to estimate just the construction phase of a project and was thus not useful for comparison to or in creation of an LCA of construction. As for specific SimaPro databases, the most applicable is the ETH-ESU 9 database. Though outdated and based on Swiss data, the ETH-ESU 9 database does claim to include facility construction for its transportation, electricity, and energy life cycles, which includes roadway, pipeline, and power plant construction; however, particulate matter emissions were not included (Frishknecht and Jungbluth 2004). Additionally, none of these construction-specific processes can be extracted for use on their own, which means they could not be utilized in creation of a construction hybrid LCA model. The Franklin database was applicable to U.S. data, but only supplied information on building materials, transport modes, and the manufacture and use of different fuels and engines that could be used to mimic pieces of construction equipment and estimate exhaust emissions (Norris 2004). As is, these processes do not sum to complete on-site construction activities, leading to the conclusion that in terms of a construction LCA, SimaPro may be helpful as a supporting database, but not to model on-site construction on its own unless the user is willing to create their own processes. An additional benefit of SimaPro is that the user could easily convert their LCI results into an LCIA if they could create enough construction-specific processes within SimaPro. However, SimaPro is not capable of assessing uncertainty, which limits its LCA capabilities.

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2.2.1.4

ATHENATM Environmental Impact Estimator The ATHENATM Environmental Impact Estimator (EIE) is by far the most

construction-specific process LCA tool on the market. It allows the user to select building system components to model the life cycle impact of the designed structure. The EIE allows for a creation of a building using the following assemblies: foundation, wall, beam and column, floor / roof, and extra basic materials. Each of these categories requires inputs specific to the assembly, which are then utilized to calculate the life cycle impacts of the structure “created” within the ATHENA software package. The environmental impact results can then be viewed as a table or a graph by either summary effects or absolute value for the building’s life cycle, various assembly groups, or total operating energy. Impact categories include air and water pollution, solid waste, GWP, primary fuel consumption, weighted resource use, embodied energy, and annual operating energy. Available Life cycle stages include manufacturing, construction, operation, and maintenance (embodied and annual operating energy only), and end-of-life. For the sample Athena projects provided with the software, the construction phase was dwarfed by the manufacturing life cycle phases in all environmental impact categories except for solid waste emissions, where construction’s contribution is almost equivalent to manufacturing’s. Otherwise, embodied and annual operating energy only impacts from the construction phase were either equivalent to or on the same order of magnitude as impacts from the operation and maintenance and end-of-life phases. Documentation provided with the ATHENA™ software explains how estimates proceed from the assembly input to final results. However, for construction, the only text supplied states that construction “includes product/component transportation from the point of manufacture to the building site and on-site construction activities” (Athena Institute 2006a). Line item results for all building phases (including construction) do include materials and transportation, but only these two categories. While building material-oriented, the EIE does have a database for on-site construction energy use and air emissions (Athena Institute 2006b). Per ATHENA’s help feature, the EIE’s construction database includes:

- 21 – Chapter 2

energy use and process related emissions for on-site construction, maintenance and replacement and transportation effects for discrete structural and envelope materials and assemblies applicable to a wide cross-section of building, occupancy types and geographical locations. The Institute has also developed building demolition and final product disposition life cycle effects for various materials.” Athena does provide their LCI database reports to interested parties for $450 ($270 for educational institutions) (Athena Institute 2006b). However, there are only three supporting documents on this CD affecting construction and none adequately explains the nuts and bolts of the EIE construction phase estimates (M. Gordon Engineering 1997; Morrison Hershfield Limited 2001; Morrison Hershfield Limited 2002). 2.2.1.5

NREL LCI Database Though not process LCA software, the National Renewable Energy Laboratory

(NREL) Life Cycle Inventory database is a publicly available database being developed by the Athena Institute and NREL (NREL 2006). It currently provides some building material LCA data and transportation data, but offers nothing regarding construction processes. However, the NREL database hopes to be the LCA data depository of the future and could may well be the source of good construction information in the future. 2.2.1.6

Summary of Existing Process LCA Software/Data’s Construction Applicability The various process LCA software packages investigated here offer little of value

to the quest to more accurately model on-site construction processes. A cursory review of these software packages and databases indicates that their treatment of the construction process involves many assumptions; these assumptions were taken into account when creating the hybrid model on which this research is based. 2.3

Input-Output Life Cycle Assessment The only free and open U.S. I-O model is Carnegie Mellon University’s (CMU’s)

Economic Input-Output Life Cycle Assessment model (EIO-LCA). EIO-LCA is a tangible implementation of the widely used input-output LCA theory. Based on public data gathered by the Census Bureau and Bureau of Economic Analysis, EIO-LCA models - 22 – Chapter 2

the entire U.S. economy with a matrix that considers the contributions and distributions of economic purchases by 491 sectors; EIO-LCA currently operates with the 1997 industry benchmark model. Sample I-O sectors include wholesale trade, truck transportation, oil and gas extraction, child day care services, and tortilla manufacturing. Input-output LCA models considering the environmental impacts for other countries’ economies have also been developed in Japan (Hayami 1997; Kondo and Moriguchi 1998), Australia (Lenzen 1998), and the Netherlands (Pesonen et al. 2000). 2.3.1

EIO-LCA Background EIO-LCA uses economic I-O data derived from detailed inter-industry transaction

matrices and publicly available environmental data to estimate comprehensive, sectorlevel environmental impacts (Hendrickson et al. 1998; Horvath 1997; Joshi 1998; Lave et al. 1995; Matthews and Lave 2000). EIO-LCA employs the most recent (1997 benchmark) U.S. Department of Commerce 491 x 491 commodity-by-commodity inputoutput matrix, auxiliary files with energy and resource consumption, and environmental data, mostly from the DOE and EPA (CMU GDI 2006; Lawson et al. 2002). The EIOLCA model includes all inputs and outputs for a given purchase (e.g., product, service, etc.) through inclusion of not only the direct impacts of producing and using a product, but also the indirect supply chain impacts (Hendrickson et al. 2006). Indirect impacts result from inclusion of all upstream supplier levels (i.e., the suppliers of suppliers). For example, steel production requires electricity, electricity requires coal, coal mining requires steel (for machines), etc. Coal for creating electricity and steel for machines are the indirect inputs of making steel. While coal for electricity generation would typically be included in a process LCA, coal and steel for machines might not, as they might be considered to be too far up the supply chain to be included. The economic information in EIO-LCA is complemented with a variety of publicly available environmental data and emission factors such as heavy metal releases, hazardous waste generation and management, greenhouse gas emissions, and energy use. The entire EIO-LCA model is publicly available online and has had roughly one million users since its online inception in 1999 (CMU GDI 2007).

- 23 – Chapter 2

2.3.1.1

EIO-LCA and the Construction Industry Of EIO-LCA’s 491 sectors, the thirteen sectors shown in Table 2 model the

construction industry. Table 2: 1997 Benchmark Model EIO-LCA Construction Sectors (CMU GDI 2007) I-O Sector # 2301 230110 230120 230130 230140 2302 230210 230220 230230 230240 230250 2303 230310 230320 230330 230340

I-O Title New residential construction New residential 1-unit structures, nonfarm New multifamily housing structures, nonfarm New residential additions and alterations, nonfarm New farm housing units and additions and alterations New nonresidential construction Manufacturing and industrial buildings Commercial and institutional buildings Highway, street, bridge, and tunnel construction Water, sewer, and pipeline construction Other new construction Maintenance and repair construction Maintenance and repair of farm and nonfarm residential structures Maintenance and repair of nonresidential buildings Maintenance and repair of highways, streets, bridges, and tunnels Other maintenance and repair construction

Total Industry Output (1997 Million $) 172,439 26,234 57,679 5,429 27,487 190,818 43,401 17,207 90,757 36,384 56,012 12,411 17,833

The complexity caused by using EIO-LCA’s construction sectors is that their organization differs from most other EIO-LCA sectors in that they’re not divided by type of component (e.g., steel, aluminum, plumbing subcontractor, or electrician). Instead, the construction I-O sectors are divided by the type of product (i.e., commercial building, highway, etc.) While this division may seem to parallel other parts of EIO-LCA, it is not how construction actually occurs. In the manufacturing sectors, manufacturers generally produce one type or category of product. In the construction sectors, however, contractors work on a variety of different projects. Consequently, a contractor could - 24 – Chapter 2

theoretically “work” in all thirteen construction sectors in any given year. As a result, determining exactly what each EIO-LCA construction sector depicts is difficult. Additionally, there is considerable uncertainty in EIO-LCA’s environmental effect estimates, as the I-O construction sectors contain environmental impacts from companies of various sizes, primary activities, and specialization areas. Based on data received from the U.S. Census Bureau, the BEA indicated that the data for the construction industry provided in the benchmark I-O tables is much better at an aggregate (entire industry) level than on a sector level (Planting et al. 2006). Even so, to further understand how the construction industry works in EIO-LCA (as required for creation of the hybrid model), the construction industry was analyzed by sector. 2.3.1.1.1

Support Sectors for the Construction Industry

Analyzing how the existing EIO-LCA model depicts the construction industry emphasizes why improved estimates for the environmental impacts of the construction industry are needed. While Table 2 lists only the thirteen EIO-LCA construction sectors with which this research is concerned, analysis of supply chain support / management functions is just as important as on-site construction processes, as the former contributes to the construction industry’s environmental impacts. One of the foci of the NSF project under which this research is funded is construction industry support activities. The term “support activity” is vague, thus clarification of this term is required here so subsequent discussion and the case study result comparison in Chapter 5 is more easily discernible. For the purposes of this research, “support activities” are defined as those support activities depicted as economic sectors in EIO-LCA that are service oriented and are typically not completed on a construction site. Some construction companies may incorporate these support services in their business models, whereas others may not. Support activities most likely enter the supply chain of construction projects during the following stages: • • •

Project Document Preparation and Distribution Project Award/Contract Administration and Planning Project Design o Geotechnical Subcontractors o Mechanical Subcontractors - 25 – Chapter 2

• • •

o Electrical Subcontractors Construction Site Logistics & Operation Environmental Remediation Architectural Features o Interior Design o Landscaping

By this definition, sectors such as those shown in Table 3 through Table 7 could include “support activities.” Table 3 lists the service sectors designated as construction’s direct support / management category; the service sector boundary could have been drawn much more loosely, but subsequent analyses would have been less effective. Additional support sectors of interest are real estate and insurance sectors, trade sectors, transportation sectors, and utility sectors; these sectors are listed in Table 4 through Table 7, respectively. Sectors listed in Table 3 through Table 5 will be included for the purpose of the “support sector” designation used throughout this dissertation; the transportation and utility sectors listed in Table 6 and Table 7 are not incorporated.

Table 3: Service Sectors from 1997 EIO-LCA Benchmark Model (CMU GDI 2007) I-O Sector # ctu100 541100 541200 541300 541400 541511 541512 54151A 541610 5416A0 541700 541800 541920 541940 5410A0 550000 561100 561200 561300

I-O Sector Description Information services Legal services Accounting and bookkeeping services Architectural and engineering services Specialized design services Custom computer programming services Computer systems design services Other computer related services, including facilities management Management consulting services Environmental and other technical consulting services Scientific research and development services Advertising and related services Photographic services Veterinary services All other miscellaneous professional and technical services Management of companies and enterprises Office administrative services Facilities support services Employment services - 26 – Chapter 2

I-O Sector # 561400 561500 561600 561700 561900

I-O Sector Description Business support services Travel arrangement and reservation services Investigation and security services Services to buildings and dwellings Other support services

Table 4: Real Estate and Insurance Sectors from 1997 EIO-LCA Benchmark Model (CMU GDI 2007) I-O Sector # 524100 531000

I-O Sector Description Insurance carriers Real estate

Table 5: Trade Sectors from 1997 EIO-LCA Benchmark Model (CMU GDI 2007) I-O Sector # 420000 4A0000

I-O Sector Description Wholesale trade Retail trade

Table 6: Transportation Sectors from 1997 EIO-LCA Benchmark Model (CMU GDI 2007) I-O Sector # 481000 482000 483000 484000 485000 486000 48A000 491000 492000 532100 532400

I-O Sector Description Air transportation Rail transportation Water transportation Truck transportation Transit and ground passenger transportation Pipeline transportation Scenic and sightseeing transportation and support activities for transportation Postal service Couriers and messengers Automotive equipment rental and leasing Machinery and equipment rental and leasing

- 27 – Chapter 2

Table 7: Utility Sectors from 1997 EIO-LCA Benchmark Model (CMU GDI 2007) I-O Sector # 221100 221200 221300 513100 513200 513300 S002002

I-O Sector Description Power generation and supply Natural gas distribution Water, sewage and other systems Radio and television broadcasting Cable networks and program distribution Telecommunications State and local government electric utilities

Although site activities and heavy machinery are at the top of the list in determining the typical contributors to construction’s environmental impacts, cursory results from EIO-LCA shown in Table 8 illustrate that support activities should not be ignored. Table 8 summarizes the total EIO-LCA supply chain purchases associated with $1 million worth of “Commercial and institutional building” construction activity in the U.S. Support activities defined in Table 3 through Table 7 are shaded in Table 8. Table 8: Top 10 Sectors for Economic Contribution Given $1 Million in “Commercial and Institutional Buildings” I-O Sector and Associated Global Warming Potential Impact (CMU GDI 2007)

I-O Sector

Economic ($ Million)

Total for all sectors Commercial and institutional buildings Architectural and engineering services Wholesale trade Retail trade Management of companies and enterprises Real estate Truck transportation Telecommunications Fabricated structural metal manufacturing Petroleum refineries

2.00 1.00 0.09 0.06 0.05 0.03 0.03 0.02 0.02 0.02 0.02

Global Warming Potential (Metric tons) 599 212 1 4 3 1 1 35 0 1 12

As Table 8 illustrates, different levels of economic activity are the result of a variety of sectors; some support sectors contribute as much, if not more than building - 28 – Chapter 2

materials and systems. However, as indicated in Table 8, support activities contribute a surprisingly high proportion of the energy and environmental effects of construction. When Table 8 is analyzed in terms of global warming potential (GWP) for the same $1 million of new “Commercial and institutional building” production, just the 7 support sectors shown in Table 8 contribute approximately 7% of the total supply chain greenhouse gas emissions. To better understand how and where support and management functions contribute to negative impacts of the construction industry, delineation between on-site and support processes needs to occur for both economic and environmental data to determine which is contributing to what percentages of environmental impacts. Extending the concept that support sectors are important in the construction industry supply chain, Figure 3 through Figure 6 illustrate the percentage of total economic, global warming potential (GWP), and total energy consumption that each category of sectors presented in Table 3 through Table 7 consumes per the existing EIOLCA model; due to space constraints, the figures presented here are only for the “New Residential 1-Unit Structures, Nonfarm,” “Commercial and Institutional Buildings,” “Highway, Street, Bridge, and Tunnel Construction,” and “Maintenance and Repair of Highways, Streets, Bridges, and Tunnels” construction I-O sectors, respectively. Analyzing these figures and those for the other construction sectors not shown here, it can be concluded that the construction sectors contribute generally less than or about 50% of the total economic, GWP, and total energy categories analyzed. Service sectors account for 5 to 10% of the total economic results, and utility sectors account for 10 to 20% of GWP and total energy effects. Exceptions to these generalities include the “Highway, Street, Bridge, and Tunnel Construction” sector and the related “Maintenance and Repair of Highways, Streets, Bridges, and Tunnels” sector, depicted in Figure 5 and Figure 6, respectively. For these two sectors, construction sectors account for 75 to 80% of the GWP and total energy impacts; the utility sectors contribute a lower percentage than for the other construction IO sectors. Additionally, the three maintenance and repair construction sectors include a slightly higher construction sector contribution in the analyzed categories.

- 29 – Chapter 2

Figure 3: Percentage of Total Economic, GWP, and Total Energy Results for EIOLCA “New Residential 1-Unit Structures, Nonfarm” Sector by Sector Category

Figure 4: Percentage of Total Economic, GWP, and Total Energy Results for EIOLCA “Commercial & Institutional Buildings” Sector by Sector Category

- 30 – Chapter 2

Figure 5: Percentage of Total Economic, GWP, and Total Energy Results for EIOLCA “Highway, Street, Bridge, & Tunnel Construction” Sector by Sector Category

Figure 6: Percentage of Total Economic, GWP, and Total Energy Results for EIOLCA “Maintenance & Repair of Highways, Streets, Bridges, & Tunnels” Sector by Sector Category - 31 – Chapter 2

2.3.1.1.2

EIO-LCA Construction Sector Issues

In addition to the large impact of service and support sectors, the existing EIOLCA model has a variety of other features specific to its construction sectors. Of note is the “1.00” number in “Economic” column of the “Commercial and institutional buildings” row of Table 8. In a typical EIO-LCA investigation, when $1 million is “spent” in a sector, EIO-LCA usually calculates a life cycle economic contribution for the sector in question that is greater than $1 million; this value is larger than the initial final demand because it includes both direct and indirect purchases / environmental impacts (i.e., for the automobile manufacturing sector to produce cars, they or their suppliers must also purchase cars for some activities). Thus, in EIO-LCA, construction is unique in that it requires no indirect construction activity for the construction sectors to operate in the economy; this is contrary to the way the other 478 EIO-LCA sectors operate. This type of estimation creates a situation where the specifics of the economic and environmental interactions are unclear and indeterminate. Additionally, while the economic backbone of EIO-LCA models little to no circularity within each construction I-O sector, it also models an extremely sparse interaction between construction sectors. Besides the construction I-O sector being modeled, the only construction sectors that register in the economic supply chain (direct and indirect) of any construction I-O sector are the “Maintenance and repair of farm and nonfarm residential structures” (220310), “Maintenance and repair of nonresidential buildings” (#220320), and “Other maintenance and repair construction” (#220340) sectors. These three construction sectors register in the economic supply chains of all construction I-O sectors; no other construction sectors besides the sector being modeled appear, indicating as the “1.00” discussed above does that the Census Bureau assumes that the construction industry has no circularity or interaction as other industries do. As described in Section 5.2.1.1, the I-O-based hybrid LCA model attempts to remedy this problem by allowing the user to alter the direct supply chain of a chosen sector. This interface allows other construction sectors to be added to the direct supply chain of a project where necessary.

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2.4

Hybrid Life Cycle Assessment A hybrid analysis was first performed by Bullard for energy, but many others

have followed his lead (Bullard and Herendeen 1975). However, the applicability of a hybrid LCA as an assessment lens for the construction industry requires further rationalization. Life cycle assessment allows for a systematic consideration of the previously unorganized or categorized resource inputs and environmental outputs of the construction process. By using LCA, a rational framework and presentation mechanism can be developed to convey these results to an array of end-users. Once armed with results from the hybrid model, decision-makers will be equipped with the appropriate and accurate information they require to assess the environmental impacts of their respective construction projects. Additionally, given the various benefits and utilities of the separate process, I-O, and various hybrid models, investigation regarding which LCA model is best for improving information flows, helping make decisions, uncertainty, validation, and project specifics is required; the prior and subsequent limited literature review attempts to explores these issues with respect to the construction industry. While ISO has defined the term “life cycle assessment” and the basic process one to perform an LCA, interpretation regarding how to implement these standards is broad. Currently, there are two basic LCA approaches: process and input-output. Both methods strive to fulfill the ISO LCA definition, but each method has assets and shortcomings, which are summarized in Table 9.

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Table 9: Comparison of Process and Input-Output LCA Approaches (Partially Adapted from Bilec et al. 2007) Topic

Issue Analysis Limits

Boundary

Imports and Exports Direct and Indirect Impacts Type Age International Comprehensive?

Data

Life Cycle Phases

Specificity

Can do specific products

Cutting-edge Products

If data is available

Units

Mostly physical

Uncertainty Use / Operation End-of-Life

Yes If data gathered If data gathered Can go as far as life cycle impact assessment If public data

Type Results

Investment

Process LCA Subjectively determined based on data availability Can be considered if data is gathered Must be iteratively determined Public, private, and sometimes proprietary Can be extremely recent Must be obtained Can be an issue

Reproducible? Product / Process Comparisons Process Improvements Time Cost

Possible Can be targeted High High

Input-Output LCA Entire U.S. economy (industries, services, etc.) Must be considered as U.S. products Automatically included Public 5+ years old, at best Limited high quality Entire economy All commodities included, though highly aggregated in some sectors No Dollar; difficult to link to physical units Yes Not included Not included Life cycle inventory Yes Impossible if in same sector Determinable on sector level only Low Low

An entirely process-based construction LCA would be extremely complex and time consuming given the diverse and diffuse nature of the industry. However, even though construction is a large, often vague process, an LCA model composed solely of IO techniques should not be utilized for the construction industry because the existing EIO-LCA construction sectors are highly average and aggregated. As there are 491 EIOLCA sectors, some products are well approximated by a sector; construction is not. - 34 – Chapter 2

Nevertheless, EIO-LCA has the distinct advantage of including all direct and indirect economic and environmental supplier effects, which includes information about every major industry in the U.S. economy; EIO-LCA is also based on publicly available data (which provides reproducible and updatable results), and provides comprehensive results for several environmental impact categories (e.g., air releases, global warming potential, and energy use). EIO-LCA is superior in analyzing the environmental effects of an industry or commodity on a national scale. In contrast, process LCA results are less aggregated, but can be extremely detailed (and thus not broadly applicable). There are differences in data coverage as well. Both process and I-O LCA models have inherent data uncertainties. It is difficult to verify whether data provided by companies has been carefully and accurately measured or simply represents engineering estimates, installations, or actual use (design vs. as-built vs. material use). However, by combining process and I-O LCA techniques, the strengths of both can be exploited while their weaknesses are minimized 2.4.1

Why Hybrid Life Cycle Assessment for Construction? As mentioned previously, the organization of EIO-LCA’s construction sectors by

construction “product” instead of input also causes confusion related to EIO-LCA’s aggregations issues. This is semi-consistent with how other economic sectors are set up, but confusing because of the nature of the construction “products,” which are constantly bought and sold by and to various owners that modify the structure to perform functions specific to that owner’s needs. Consequently, uncertainties in construction-specific process LCA and EIO-LCA results are different in nature and magnitude. Over time, the environmental discharges from construction have proved difficult to adequately track, place in context, and regulate. As a result, there are few pure process LCAs of the construction process. To create such a model, an LCA practitioner would have to gather so much location-specific data that the resulting process LCA model would not be applicable on a large scale. As a result, it is much easier to use average data (such as I-O data) as the basis for a hybrid LCA of construction. It is easier to improve average I-O data so it can become the basis of general estimates instead of expanding process LCA construction data for larger scale comparison. - 35 – Chapter 2

Because of wide variability in the construction industry, completing an LCA to assess the construction phase of building projects requires utilization of both process and I-O LCA techniques. The process LCA aspect will complement the more task-specific construction processes, while the I-O approach will be used to set an appropriate boundary and to help develop improved life cycle inventory support systems. Thus, to construct future building and infrastructure projects in a sustainable and environmentally optimal way, and to have relevant environmental information available when decisions are made (i.e., at the conceptual and detailed design stage), the results from both process and I-O LCA approaches are important. Consequently, a hybrid LCA model that utilizes both methods is required. Additionally, a hybrid model is attractive to current LCA practitioners and provides more comprehensive, easy-to-interpret, and systematic information for construction, government, public, and academic stakeholders. 2.4.2

Hybrid Life Cycle Assessment Background Discerning the type of LCA to use for a certain process or product can be a

complex decision. The concept of a hybrid LCA can complicate or simplify the matter (depending on how the problem is viewed). While the main concept of a hybrid LCA is to combine the two main LCA methods (process and input-output) into a single LCA framework, there is not just one type of hybrid LCA framework. As summarized by others, current hybrid LCA designations include tiered, input-output-based, integrated, and augmented process-based hybrid models (Bilec et al. 2007; Suh et al. 2004). With such a wide array of hybrid LCA systems available for use, the decision of which to use can be difficult. However, due to prior experience with and access granted to the EIO-LCA database and construction sectors, developing an input-output-based hybrid LCA tool was more feasible and executable for construction than the other hybrid options. Additionally, the investigation of the inner workings of the EIO-LCA construction sectors (summarized in Section 3.3.2 and Appendix B) provided insight into how an I-O-based hybrid model could be best instituted to modify and improve the existing EIO-LCA model.

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2.4.2.1

Boundary Issues Many levels of inputs (direct and indirect suppliers) are typically included in

process-level LCA approaches. However, for practical reasons, the assessment of inputs and outputs is often discontinued at some level of suppliers due to time or data constraints. Comprehensive assessment of the entire supply chain to include all indirect effects is necessary. In this research, the relevant boundary for assessing the implications of construction activities across a project’s life cycle is viewed fairly broadly to ensure that off-site construction activities are considered. As shown in Figure 7, the boundary of the I-O-based hybrid LCA model subsequently created includes construction planning, management, and support in addition to on-site construction activities. Additionally, the upstream supply chain purchases and their associated energy and environmental effects have been considered. Consequently, the I-O-based hybrid model combines the fine detail of process-level data and EIO-LCA’s economy-wide assessment (Suh et al. 2004). As an I-O-based hybrid, the basic EIO-LCA construction sectors provide a framework for the analysis, but process-based data helps adjust EIO-LCA data so that it properly estimates project-specific environmental impacts.

Figure 7: Construction Project Life Cycle and Proposed System Boundary

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2.4.3

Past Construction-Related LCA Research Existing research considering the life cycle impacts of buildings and construction

has generally utilized either the process or I-O LCA technique and/or assumed that the impacts of the construction phase are small and, therefore, negligible (Keoleian et al. 2001; Ochoa et al. 2002; Pullen 2000a). A summary of the process LCA tools applicable to construction are summarized in Section 2.2.1; of these process tools, ATHENA is the most applicable to construction industry LCAs. Other investigations have indicated that EIO-LCA tends to underestimate the environmental impacts associated with construction (Hendrickson and Horvath 2000); still others assert that existing green building standards do not address the true life cycle of buildings / structures (Bunz et al. 2006). However, several more recent construction LCAs are leading the way towards more accurate assessments of construction’s environmental impacts, mostly for commercial buildings (Bilec et al. 2006; Guggemos and Horvath 2005a; Guggemos and Horvath 2005b; Guggemos and Horvath 2006; Junnila and Horvath 2003). Past research specifically addressing issues related to both the construction industry and LCAs includes the articles summarized in Table 10; these analyses provide the foundation for this research and are referenced throughout this document.

Table 10: Summary of Selected Research Applicable to Construction LCAs Reference

Hendrickson & Horvath

Year

Title

2000

“Resource Use and Environmental Emissions of U.S. Construction Sectors.”

Ochoa et al.

2002

Bilec et al.

2006

“Economic InputOutput Life cycle Assessment of U.S. Residential Buildings” “Hybrid Life Cycle Assessment of Construction Processes”

Contribution Summary Used EIO-LCA to estimate direct and indirect resource consumption and environmental impacts of construction activities. Determined that 4 construction sectors appeared to use and emit fewer resources and environmental impacts than their share of the GDP suggested. Estimated economic and environmental impacts of residential building projects in terms of construction, use, and demolition. Utilized EIO-LCA and R.S. Means. Summarizes types of hybrid LCAs. Offers preliminary results for augmented process LCA precast parking garage case study.

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Reference

Year

Horvath

1997

Guggemos

2003

Guggemos and Horvath

2006

Title “Estimation of Environmental Implications of Construction Materials and Designs Using Life Cycle Assessment Techniques” “Environmental Impacts of On-Site Construction: Focus on Structural Frames.” “Decision-Support Tool for Assessing the Environmental Effects of Constructing Commercial Buildings”

Contribution Summary

Compares of process and input-output LCA techniques for construction.

Augmented process LCA of buildings based on the type of structural frame; considers transportation.

Process-based hybrid analysis for commercial buildings.

Specifically, the Construction Environmental Decision Support Tool (CEDST) is the only published hybrid LCA attempt at modeling construction (Guggemos and Horvath 2003; Guggemos and Horvath 2005b; Guggemos and Horvath 2006). CEDST was only designed to assess the environmental impacts of commercial buildings, so its applicability to the broader construction industry is limited. However, CEDST’s modeling of the construction industry impacts of commercial buildings is thorough, and it is based on project-specific material , transport, and equipment information, referencing the existing EIO-LCA model for material life cycle data. 2.5

Discussion In the LCA community, there are many different types of LCA models being

implemented. The majority of these models are process LCAs, and of these constructionapplicable process LCAs, many focus on building materials while few address or account for the construction aspects of an engineering project (Gambatese and Rajendran 2005; Kreissig and Binder 2005; Ochoa et al. 2002). Many of the respective limitations of process and input-output LCA methods specific to construction are due to the disparate and separate nature of the construction industry. Existing research, literature, and software packages ignore, minimize, and/or underestimate the construction industry’s

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impacts. The data specificity required for a pure process LCA of a construction project basically ensures that one cannot create a generalizable construction LCA model from just process LCA data. However, the aggregate nature of EIO-LCA’s 13 construction sectors ensures that construction information is lumped categories that do not adequately model construction activity either. As a result, an I-O-based construction LCA framework was selected for the construction industry; this model affords a set structure that can be modified where necessary for future improvements. Additionally, due to open access to Carnegie Mellon University’s EIO-LCA database, creating an I-O-based hybrid LCA model was more accessible than many of the other hybrid options. Previous analysis of the EIO-LCA’s construction sectors also provided insight into how an I-O-based hybrid model might be able to improve estimations of the construction industry’s environmental impacts. If one is to understand the entire life cycle of a building, a detailed LCA must be performed for the construction phase of a project. Part of the reason this assessment has not already been completed is lack of and inconsistency of data directly from the construction industry.

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CHAPTER 3: HYBRID LCA MODEL FOR CONSTRUCTION 3.1

Introduction The prevalence of hybrid LCAs is spreading, but there is are only two extant

hybrid models for the construction; one is a U.S. process-based hybrid and the other is an I-O-based hybrid specific to the Australian economy (Guggemos and Horvath 2005a; Treloar et al. 2000). An augmented process-based hybrid is also under development (Bilec 2007; Bilec et al. 2007). The other U.S.-based hybrid construction LCAs are both augmented process-based hybrid models, whereas the tool created here is an inputoutput-based hybrid. The application of different modeling techniques to the construction process will help further determine the strengths and weaknesses of hybrid construction LCA modeling, while improving estimation of the industry’s environmental impacts so that policy can evolve accordingly. In general, estimates provided by I-Obased hybrid LCA model created herein are more precise and realistic than estimates created by simplified process models and the existing EIO-LCA framework. The first step in creation of this I-O-based hybrid LCA model was to assess the characteristics and implications of the construction industry. At the highest level, it is important to use a hybrid LCA tool for the construction industry to educate decisionmakers about how activities and management decisions in the industry lead to unanticipated effects. It is also important to continue to use the model beyond this specific analysis to identify construction processes that should be future priorities, as important considerations will be exposed with continued model use. The policy implications of the hybrid construction LCA tool are key, especially in terms of its availability to and usability for various industry stakeholders. 3.2

Optimal Construction Industry Inclusions in Hybrid Model Because the hybridization method used here is I-O-based and the EIO-LCA tool is

available for full use, consideration, and editing, there are multiple ways to improve the EIO-LCA construction sectors and the current LCA estimating techniques of on-site construction activity. A preliminary list of inclusions into a perfect LCA of a construction project was created early on in this project and is formally presented here - 41 – Chapter 3

simply as a record of the model creation process. In creating an ideal hybrid model for the construction industry, the following would optimally be included: •

Economics o Cost ƒ Profit o Value Added o Contractor vs. Subcontractor

•

On-Site Activities o Earthwork o Foundation o Structure ƒ Building ƒ Road ƒ Other o Landscaping o Redo Because of Redesign or Mistake o Instrumentation o Site Visits ƒ By whom • Designers • Quality Assurance / Quality Control • Owner • Other Stakeholders ƒ Frequency and Duration ƒ Transportation Impacts ƒ Environmental Impacts

•

•

Construction waste o Volume o Mass o Land use impacts ƒ Landfill ƒ Reuse ƒ Recycle Equity o Employment ƒ Numbers ƒ Salaries ƒ Per diem ƒ Local or imported o Community o Culture - 42 – Chapter 3

•

Equipment o Types ƒ Heavy ƒ Small • Generators o Frequency and Duration of Use ƒ Idling Time ƒ Operation Time o Use o Manufacture

•

Transportation o Of materials ƒ To construction site ƒ To subcontractor o Of equipment ƒ To construction site ƒ At construction site ƒ From construction site o Of workers ƒ To and from construction site ƒ At construction site • Personal vehicles • Contractor vehicles o Frequency and Duration of Use o Of construction waste ƒ To recycling facility ƒ To landfill

•

Water o Drinking o Used ƒ Source o Recycled o Treated o Polluted o Stormwater o Sanitary Sewer o Environmental Impacts

•

Energy o Fuels ƒ Types • Gasoline • Diesel • Natural Gas • Propane ƒ Use ƒ Environmental Impacts o Electricity ƒ Source • Grid • On-site Generators ƒ Use • Heating / airconditioning • Computers • Temporary lighting • Elevator tests ƒ Environmental Impacts

•

Support Services o On-site ƒ Trailer • Phone • Internet ƒ Office supplies ƒ Food and beverages ƒ Port-o-potties • Number • Sewage • Environmental Impacts o Off-site ƒ Service Sectors ƒ Quantity ƒ Frequency ƒ Supply chain impacts

Some other important aspects of construction industry activities that need to be considered when modeling any construction project include the following, which are , not always as easily quantified as the preceding list: o Wasted money and materials wasted due to design errors or incorrect installation ƒ What happens to it? ƒ How much is there of it?

3.3

o o o o o o o o

Seasonality Regionality Subcontracting levels Logistics Economies of scale Noise pollution Congestion Vibrations

Research Needs All of the construction components listed above are not included in every LCA of

a construction project, especially one performed with the aggregate construction sectors in EIO-LCA. However, it is important to realize the large boundary required for assessing the environmental impacts of construction. Transportation, on-site energy use, and support functions (utilities, management, and service sectors like accounting and - 43 – Chapter 3

marketing that inherently interconnected with the construction industry) may have the largest environmental impacts in an LCA of construction (Bilec et al. 2007). The importance of support sectors was previously discussed in Section 2.3.1.1.1. Given the limitations and information needs of the process and I-O LCA methods, a good hybrid LCA of construction requires important consideration of the audience and what kinds of information these decision-makers need concerning possible construction industry improvements that would reduce environmental impacts. These needs are dependent upon the planned uses of the hybrid model’s results and the ability of decision makers to process the information with which they are presented; one type of hybrid LCA model might better satisfy more stakeholders than another (Hofstetter and Mettier 2003; Pearce and Fischer 2001). Features for a hybrid LCA model for construction are ultimately limited by data, but can be enhanced if considered in terms of decision-support. Any model that improves upon the status quo for quantifying that construction industry’s economic and environmental impacts provides stakeholders with information that improves on existing tools. However, data that is comparable to results from other LCA models is most useful. Aspects of how the I-O-based hybrid LCA model improves on the status quo of estimating construction environmental impacts in terms of on-site energy/electricity use, demand, and generation are subsequently discussed. Additionally, investigation of current government categorization of and data sources for the construction sectors instigated creation of a map between the NAICS construction industries and I-O construction sectors. This analysis is introduced below and detailed in Appendix B. 3.3.1

On-Site Energy and Electricity Demand, Use, and Generation1 The construction industry creates a litany of environmental impacts, partly due to

its large energy consumption (Hendrickson and Horvath 2000); however the industry’s energy consumption is not well understood because of the decentralized nature of construction and subcontracting activities. Because past regulation of the construction 1

Portions of an older version of this section were presented at ASCE’s 2005 Construction Research Congress (Matthews et al. 2005). A version of Section 3.3.1 has been submitted to the Journal of Construction and Engineering Management for review; upon publication of this dissertation, it has not yet been accepted for publication (Sharrard et al. 2007a).

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industry has loose, there is great potential for construction policy improvement that could benefit the environment while not sacrificing productivity. Some of the major environmental impacts of the construction process are related to stormwater management, demolition debris, and energy consumption; the focus of this section is the latter. Energy on a construction site is usually provided by gasoline, diesel fuel, electricity, and natural gas. Of these four energy sources, diesel fuel and electricity are responsible for the greatest total air emissions. Aggregate data on energy and resource use in the construction sector is available from the 2002 Economic Census of construction (DOC 2005b); for this survey, roughly one-fifth of known construction businesses were selected with fairly robust selection criteria. As with other Census studies, the survey results were use to statistically approximate average industry estimates. The report summarizes data for all construction expenditures in 2002, including energy costs. Expenditures are summarized for the entire industry and divided into three subcategories: construction of buildings, heavy and civil engineering construction; and special trade contractors. The Census data also contains information on construction industry expenditures categorized as follows: employment/labor, subcontracting, materials, and power/fuels. Out of $648 billion in total non-labor expenses in 2002, the construction industry spent $15 billion on energy, of which $11 billion was spent on gasoline and diesel fuel, $1.1 billion on natural gas, and $2.6 billion on electricity (DOC 2005b). Compared to total construction industry expenditures, overall spending on power/fuels represents about 2.5% of total costs. Specifically, power/fuel spending is approximately 4% of heavy construction, 3.7% of special trade contracting, and 1.2% of total building construction costs. Because no physical or thermal consumption units were provided, average 2002 industrial energy costs were established so that aggregate comparisons could be made. While overall U. S. industrial spending on electricity in 2002 was $49 billion, the construction industry only spent a fraction of that ($2.6 billion) on electricity (EIA 2005a). Consequently, construction represents 1% of the U.S.’s total electricity use and 5.3% of all industrial electricity purchases. Given a 2002 average industrial price of electricity of 4.91 cents per kilowatt-hour and assuming an on-site consumption heat rate of 3,412 BTU/kWh (3.6 MJ/kWh), the construction industry bought 52 TWh of - 45 – Chapter 3

electricity in 2002, or 179 trillion BTUs (189,000 TJ) (EIA 2002; EIA 2005a). Note that given the inefficiency in the electricity generation process, the amount of primary energy (coal, natural gas, etc.) needed to produce a kilowatt-hour of electricity is actually much higher—about 10,360 BTU/kWh (10.9 MJ/kWh) for fossil fuel-based power plants (EIA 2002). Consequently, the electricity purchased annually by the construction industry requires 543 trillion BTU (573,000 TJ). Likewise, assuming the 2002 average industrial price of $4.02 per thousand cubic feet of natural gas ($142 per thousand m3), the construction industry used 267 billion cubic feet of natural gas (272 trillion BTU at 1,020 BTU/cf), or 287,000 TJ (EIA 2002; EIA 2005a). Since total industrial natural gas use in 2002 was 7.5 trillion cubic feet (8,100 TJ) and overall U.S. use was 23 trillion cubic feet (24,800 TJ), the construction industry represented 3.6% of total industrial natural gas purchases and 1.2% of U.S. natural gas consumption (EIA 2001). The $11 billion spent on gasoline and diesel fuel in 2002 at a retail cost of $1.03 per gallon ($0.27 /per liter) converts to 10.6 billion gallons (1,500 TJ) of fuel used (EIA 2006). At an average heat rate of 132,000 BTU per gallon (37 MJ/liter), this is 1.4 quadrillion BTU (1.5 PJ) (Davis and Diegel 2005). The “retail cost” of gasoline and diesel fuel is a relative term, as some construction use of petroleum-based fuels is tax exempt; the estimate shown here is an order of magnitude estimate revisited later. Thus, an initial estimate of the total energy used by the construction industry in 2002 is between 1.8 quadrillion and 2.2 quadrillion BTU ((2,000 to 2,400 PJ—assuming on-site consumption and primary electricity heat rates for fossil fuels). These estimates are 1.9% of total U.S. energy consumption (EIA 2005a). Using the same method delineated above, Figure 8 summarizes energy use for the overall construction industry and its subsectors. In all, it is clear that gasoline and diesel fuel represent the majority of energy consumption in the construction industry with 62 to 75% of all use. The share of natural gas for construction is 13 to 15% of energy required, and electricity accounts for 10 and 25% of total energy. These estimates are subsequently refined and discussed.

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Figure 8: 2002 Construction Industry and Subsector Energy Use in Petajoules (DOC 2005b; EIA 2002; EIA 2005a; EIA 2005b) 3.3.1.1

Estimating Construction Energy Use by Category While the energy consumption estimates for the construction industry provided in

Figure 8 do not represent a large share of overall U.S. energy consumption, the environmental impacts of the construction industry’s energy use relative to other sectors were also considered. Energy and fuel consumption by the construction industry is an interesting topic not only due to the large share of gasoline and diesel used by construction vehicles, but also because of the EPA’s 2004 Nonroad Diesel Rule affecting vehicles and fuels (EPA 2004a). Because the construction industry has not been subject to strict EPA regulations in the past (i.e., Tier 1-3 regulations) EPA’s nonroad rule may provide large potential to reduce the environmental impacts of construction. To make these comparisons, an estimate of the construction industry’s share of diesel and gasoline consumption is required. Of the $11 billion the construction industry spent on gasoline and diesel fuel in 2002, it is estimated that $8 billion was spent for on-

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highway vehicles and $2.9 billion was spent for off-highway gasoline and diesel fuel use (DOC 2005b). Unfortunately, these are the most specific estimates available. Off-highway (on-site) diesel fuel is used to power bulldozers, excavators, cranes, generators, and other types of equipment. Generators are used to meet additional electricity demands for lighting, welding, and elevators, reaching areas of construction sites where it is difficult to supply grid electricity or for which excess demand cannot be met by an electricity grid hookup. Sites demanding a significant amount of welding require such flexible electricity and thus often require on-site diesel generators. An initial challenge in disaggregating the construction industry’s diesel and gasoline purchases is the distinction between on- and off-highway usage. Presumably, the Department of Commerce’s (DOC) “off-highway” category corresponds to EPA's “nonroad engine and vehicles” category. However, the DOC gives no guidance regarding the breakdown of gasoline and diesel consumption for on- and off-highway purposes. For this approach, updates to the EPA National Air Quality and Emissions Trends Report (NAQET) were used as a guide (EPA 2004c; EPA 2005). For example, in the EPA’s “on-road” category, the largest share of particulate matter (PM) emissions comes from heavy-duty diesel vehicles, some of which are unquestionably construction vehicles; thus, the construction industry’s contribution to on-road vehicle fuel consumption needed to be estimated. The Energy Information Administration’s (EIA) Transportation Energy Data Book (an aggregate of a variety of sources) provides energy consumption estimates for various vehicle categories. Table 11 summarizes the construction-related off-highway categories for 1997 and 2002 (Davis and Diegel 2005). It should be noted that Table 11 represents revisions made to previous off-highway estimates by a 2004 Oak Ridge National Laboratory study that used EPA’s NONROAD 2002 program and the 1997 Vehicle and Inventory Use Survey (VIUS) (Davis and Truett 2004).

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Table 11: 1997 and 2002 Estimates of Gasoline and Diesel Use for Construction in Petajoules (Davis and Diegel 2003; Davis and Diegel 2005; DOC 2005b)

Light Trucks (On-Highway) Medium/Heavy Trucks (On-Highway) Construction Equipment (OffHighway) TOTAL

Year

Gasoline

Diesel

Total

1997 2002 1997 2002 1997

6,260 6,940 490 600 38

250 270 3,820 4,690 700

6,510 7,210 4,310 5,290 740

2002

36

800

840

1997 2002

6,790 7,570

4,770 5,760

11,550 13,330

Construction Industry Share 6% 17%

Construction Industry Total 400 3,440 740 910 740

100% --

840 1,880 2,190

Note: As previously mentioned, 2002 off-highway consumption values were estimated based on average annual growth rates between 1997 and 2001. Numbers may not sum due to rounding. While more concrete estimates of off-highway construction fuel use are being developed, on-highway fuel use attributable to the construction industry has been largely overlooked. The national-level estimates compiled in Figure 8 may or may not represent on-highway small-medium truck use, but the data based on the DOC’s vehicle inventory and use survey (and provided in Table 11) definitely does (Davis and Diegel 2005; DOC 2005b). Using this perspective, the revised construction fuel use values shown in Table 11 are 54% higher than the data in Figure 8. For 1997 and 2001, construction industry off-highway fuel use is also available in physical units. Given that 2002 data was required for this analysis, the average annual growth of off-road construction gasoline and diesel use between 1997 and 2001 was calculated and applied to derive an estimate for 2002. More general petroleum use or offhighway growth rates were not applicable to these construction values due to relatively large diesel consumption increases in the construction industry in the past ten years. Gasoline consumption has dropped over this same time period. For 1997, gasoline use was estimated at 289 million gallons, with 270 million gallons used in 2002 (1.1 million and 1.0 million liters, respectively) (Davis and Diegel 2005). Likewise, diesel use was estimated at 4.8 billion gallons in 1997 and 5.5 billion

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gallons in 2002 (18 million and 21 million liters, respectively) (Davis and Diegel 2005). Given these values, the implied average cost per gallon of gasoline and diesel used by the construction industry in off-highway situations in 2002 was $0.51 (or $0.13 per liter— calculated from $2.9 billion spent on off-highway fuel and the 5.8 billion gallons of offhighway fuel used) (Davis and Diegel 2005; DOC 2005b). This estimate suggests that the overall construction industry consumption of gas and diesel in 2002 was 21.5 billion gallons (or 81 billion liters—calculated from $11 billion of expenditures at $0.51 per gallon). The $0.51 per gallon average calculated here is well below the average 2002 retail price, but consistent assuming that a large amount of construction fuel purchases are tax exempt or generate a bulk discount. To help allocate the broad categories in Table 11, the Transportation Energy Data Book also summarizes DOC estimates for construction’s share of vehicle activity and fuel use for 2002 highway vehicle use (DOC 2004). Based on DOE survey results, the percentages of gasoline and diesel vehicles utilized for construction are obtainable for both 1997 and 2002. Due to the variance between these two numbers, an average of the 1997 and 2002 percentages were utilized. Consequently, the percentages of total gasoline and diesel vehicles used by the construction industry (and used for the Table 11 analysis) are as follows: 6% of light trucks (those less than 10,000 pounds (4,536 kg)), 19% of medium trucks (10,000 to 26,000 pounds (4,536 to 11,793 kg), and 17% of heavy trucks were used for construction in 2002 (Davis and Diegel 2003; Davis and Diegel 2005). However, the DOE provides detail for only two truck categories (light and medium/heavy), while information from other sources has three divisions (light, medium, and heavy trucks) (Davis and Diegel 2005). As a result, an average of the DOC’s 1997 and 2002 estimates are that 72% of overall truck fuel use comes from light trucks, 5% from medium trucks, and 22% from heavy trucks; these percentages were estimated based on gasoline fuel use tracked by the DOC survey and used to aggregate the medium and heavy truck categories into the medium/heavy truck category in Table 11. Based on these estimates, 20% of the medium/heavy truck energy shown in Table 11 is from medium trucks and 80% is from heavy trucks. Additionally, the aggregated medium/heavy truck category’s share of construction energy shown in Table 11 is 17%. As the total fuel usage in BTUs was the only value available for 1997, the 1997 gasoline - 50 – Chapter 3

and diesel fuel usage estimates were back-calculated based on the 2002 ratio of gasoline and diesel usage to total fuel usage (Davis and Diegel 2003; Davis and Diegel 2005). Thus, per Table 11, the estimate of construction energy used by both on- and offroad construction vehicles in the form of gasoline and diesel fuel was approximately 1.8 quadrillion BTU in 1997 and 2.1 quadrillion BTU in 2002 (1,900 and 2,200 PJ, respectively); these estimates are more than 50% larger than the original estimate provided in Figure 8, which was 1.4 quadrillion BTU (1,400 PJ). This discrepancy is most likely a result of the DOC’s statistical survey of construction companies, which is unable to see through the construction industry’s subcontracting levels to smaller companies (DOC 2005b). In many cases, this inability to adequately quantify subcontractor energy use with a survey is significant for site-related activities. If the 2002 gas and diesel energy value estimates calculated for Table 11 (2,200 PJ) are used in place of the gas and diesel estimates in Figure 8 (1,400 PJ), then the estimated total energy used by construction increases to 2,500 to 2,900 PJ (2.5 to 2.9 quadrillion BTU—for site and primary electricity use, respectively). These revised estimates are almost double the lower range of the earlier estimate of 1,300 PJ (1.2 quadrillion BTU). Given that the estimate of 1.8 to 2.2 quadrillion BTU (1,900 to 2,300 PJ) of construction energy used in 2002 provided in Figure 8 is widely utilized, questions arise concerning the accuracy and use of data obtained from the construction industry. Assuming the same average ratios of gasoline and diesel use to total fuel use for the entire construction industry, a back-calculation yields estimates of 2002 construction industry energy use of about 1,100 trillion BTU of gasoline and 830 trillion BTU of diesel (1,160 and 880 thousand TJ, respectively). Comparing these values to annual volumetric sales of gasoline and diesel in the U.S., this approximation represents 3% of total gasoline and 21% of overall U.S. diesel fuel use (EIA 2005a). 3.3.1.2

Effects of EPA Nonroad Diesel Rules Construction industry energy and fuel consumption is an interesting topic not only

due to the large share of gasoline and diesel vehicles used by the industry, but also because of the EPA’s 2004 Nonroad Diesel Rule affecting vehicles and fuels (EPA 2004b). The majority of conventional U.S. air emissions are a result of burning fossil - 51 – Chapter 3

fuels, which are the primary source of construction energy use. Because the construction industry has not been subject to strict EPA regulations in the past, EPA’s nonroad rules provide large potential to reduce construction’s environmental impacts. EPA’s Nonroad Rule affects diesel fuel and engines used in non-highway situations. Much of EPA’s ongoing regulatory efforts have been for mobile sources, predominantly for on-highway vehicles. As emission standards for these vehicles have been lowered over the last 20 years, there is relatively little room for improvement left and the current focus has switched to non-highway engines, which produced 60% more particulate matter emissions than highway-based engines in the year 2000 (EPA 2004b). The construction industry is not the only industry held to the EPA’s nonroad standards; many agricultural, material handling, industrial, and equipment industries are also affected. Regardless, the construction industry has been and will continue to be substantially affected by new regulations. While the subsequent focus of this paper is onsite portable generators, it should be noted that stationary generators (i.e., emergency backup power sources for buildings) are excluded from the EPA’s regulations. Most recent sulfur emission legislation has been focused on power plant emissions. However, the EPA’s new diesel fuel rules will reduce the sulfur content in diesel fuel by 99% by 2010 (from 3,000 ppm down to 15 ppm) and decrease the limit at which off-highway diesel engines can emit NOx and PM10 by 90% by the year 2015 (EPA 2004b). The EPA regulates these emissions by setting limits on particular engine types (e.g., in g/hp-hr). 3.3.1.3

Construction Nonroad Diesel Engine Emissions Nonroad engine emissions, specifically diesels, are an emerging target of attention

and regulation. Part of this increasing awareness is due to the fact that the EPA documented more PM emissions from nonroad sources than from highway sources for the first time ever in 1995. In the year 2002, the EPA estimated total transportation emissions of particulate matter less than 10 microns in diameter (PM10) from all sources was 515,000 short tons (467,000 tonnes) (EPA 2005). Of this quantity, 60% were from nonroad engines and vehicles (311,000 short tons (282,000 tonnes)). Diesel equipment is 54% of this nonroad total (169,000 short tons; 153,000 tonnes; or 33% of the U.S.

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transportation total) and construction vehicles represent 42% of nonroad diesel equipment emissions (71,000 short tons; 64,000 tonnes; or 14% of the U.S. transportation total). It should be noted that nonroad construction gasoline engines emit only 2,000 short tons (2,000 tonnes) of PM10 per year, a negligible amount when compared to diesel PM10 emissions (EPA 2005). Thus, from a PM10 perspective, construction diesel use causes disproportionately high environmental impacts. Using a similar approach, it can be determined that off-highway diesel construction vehicles contribute 764,000 short tons of NOx emissions (693,000 tonnes, or 7% of the U.S. total nonroad NOx emissions); NOx emissions contribute to ozone and climate change problems (EPA 2005). 3.3.1.4

Emissions from On-Road and Generator Engines Used for Construction Using a method similar to the one used above to allocate and estimate nonroad

construction vehicle energy use, estimations of light, medium, and heavy-duty truck emissions from construction were also created. Table 12 combines EPA emission estimates for PM10, NOx, and volatile organic compounds (VOC) with the results from Table 11 to estimate air emissions from construction on- and off-road vehicles (EPA 2005). As a result, these numbers can be compared to Table 11 to associate air emissions with fuel usage. Note that the EPA’s inventory has only been reallocated, no emissions have been added. Table 12: 1997 and 2002 Construction Engine Emissions in Thousand Metric Tons (Davis and Diegel 2005; EPA 2005) Year Light Trucks (On-Highway) Medium/Heavy Trucks (On-Highway) Construction Equipment (OffHighway) Total

1997 2002 1997 2002 1997 2002 1997 2002

All Sources Construction Industry PM10 NOx VOC Share PM10 NOx VOC 34 1,350 1,900 2 82 120 6% 29 1,290 1,490 2 78 90 170 4,160 580 29 720 100 17% 110 3,430 360 19 5690 62 73 710 140 73 710 140 100% 66 700 120 66 700 120 280 200

6,220 5,420

2,620 2,980

Note: Numbers may not sum due to rounding.

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104 1,450 87 1,320

360 280

In Table 12, “on-highway” construction vehicles are added to the EPA’s current “construction industry” definition (which only includes off-highway vehicles). Consequently, estimated 2002 vehicle emissions from construction increase by 32% for PM10, 96% for NOx and 125% for VOCs. These improved estimates of construction activity energy use and environmental emissions are much higher than existing EPA national-level data. However, the very data sources referenced in this analysis as underestimations of construction energy use and emissions are the exact same sources heavily utilized by others to estimate the environmental impacts of the construction industry. As a result, past environmental assessments or LCAs dependent on this type of underestimated national data (as well as other survey data from the construction industry) may be under-reporting these effects (Gambatese and Rajendran 2005; Guggemos and Horvath 2005a; Hendrickson and Horvath 2000; Ochoa et al. 2002; Ruether et al. 2004). 3.3.1.5

Effects for On-Site Generators In the past, many EPA diesel emission regulations have only been applicable to

on-highway engines and most sulfur emission legislation has been focused on power plant emissions; both tactics ignore emissions from off-road diesel vehicles. As mentioned previously, the EPA’s Nonroad Rule will reduce sulfur content in diesel and diesel engine NOx and PM emissions. To illustrate the prospective effects of the new EPA Nonroad Rule, a case study is analyzed. The two biggest on-site energy sources are diesel fuel and electricity, but on construction sites, diesel fuel is often used to power heavy machinery and to produce onsite electricity via generators. Consequently, electric generators are a relevant case study, especially since there are other ways of generating power, notably the electricity grid. On construction sites, grid electricity is used to power lights, elevators, and trailers, while generators provide power for more immediate and remote electricity needs from welding and other hand tools. Because grid and generator electricity differ in magnitude, it is very likely that there is a difference in how much pollution grid electricity and electricity generated on-site emit per kWh of electricity produced. If a large difference exists, the potential to reduce emissions without sacrificing productivity is present through application of the EPA Nonroad Rule. As these stringent EPA - 54 – Chapter 3

regulations are phased in for nonroad diesel generators and construction equipment over the next several years, it is possible that the form of “cleaner” electricity generation (in terms of air emissions) could shift between the electricity grid and on-site generators. An inventory of portable generators was not available for the United States, so a Canadian generator inventory was used as a proxy (Tushingham 2004). In Canada, there are over 620,000 portable generators that each average 134 hours of operation per year; 92% of these generators are smaller than 19 kW (25 horsepower (hp)). The Canadian dataset does not specify what percentage of generators are used by any industry or group, including construction. Despite the fact that there are obvious climate, recreational, and use differences between the U.S. and Canada that could lead to differences in generator use, the Canadian generator inventory is most likely strongly linked to U.S. ownership. Interestingly, the Canadian inventory also notes that about 90% of fuel used in onsite generators is gasoline, whereas many U.S. generators run on diesel fuel (Tushingham 2004). The fact that many Canadian generators run on gasoline implies that applying the EPA diesel rules to portable diesel generators in the U.S. could cause significant increases in diesel generator price, consequently causing a simple substitution of gasoline for diesel as a generator fuel. As a result, the market for low-power diesel generators could evaporate, taking with it any potential environmental improvements in the category of construction site electricity generation. As a preventative measure, perhaps portable gasoline generators should also be included in such nonroad regulations to eliminate a scenario perpetuated by the EPA’s fuel-based regulations. Per the Canadian generator inventory, most construction diesel generators range from 1 to 300 hp (1 to 225 kW), with most falling between 3 and 25 hp (2 and 19 kW). However, the new EPA rule covers engines above 750 hp (560 kW), which also incorporates large construction vehicle engines. Table 13 summarizes the history of EPA’s Tier 1-4 rules for nonroad diesel engines with capacities up to 75 hp (56 kW); the EPA reports these emission limitations in units of g/hp-hr (EPA 2004b). Although the EPA Nonroad Rule applies to engines up to about 1 MW, only the low end of the range is shown here because it is most relevant to on-site generators. In Table 13, non-methane hydrocarbons (NMHC) are included in the NOx (+NMHC) column. Like NOx, NMHCs

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are significant precursors to ozone formation; due to this common path to ozone, the EPA often regulates NMHC and NOx together. Table 13: 1999 – 2013 Emission Standards for Nonroad Diesel Engines up to 37 kW (50 hp) in Grams / kilowatt-hour (Adapted from EPA 2002; EPA 2004b; Matthews et al. 2005) Engine Rating Tier Year Kilowatts Horsepower