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Decision Analysis Methodology to Evaluate Integrated Solid Waste Management Alternatives for a Remote Alaskan Air Station

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Air Force Institute of Technology AFIT Scholar Theses and Dissertations Student Graduate Works 3-2001 Decision Analysis Methodology to Evaluate Integrated Solid Waste Management Alternatives for a Remote Alaskan Air Station Mark J. Shoviak Follow this and additional works at: https://scholar.afit.edu/etd Part of the Environmental Engineering Commons Recommended Citation Shoviak, Mark J., "Decision Analysis Methodology to Evaluate Integrated Solid Waste Management Alternatives for a Remote Alaskan Air Station" (2001). Theses and Dissertations. 4696. https://scholar.afit.edu/etd/4696 This Thesis is brought to you for free and open access by the Student Graduate Works at AFIT Scholar. It has been accepted for inclusion in Theses and Dissertations by an authorized administrator of AFIT Scholar. For more information, please contact [email protected]. DECISION ANALYSIS METHODOLOGY TO EVALUATE INTEGRATED SOLID WASTE MANAGMENT ALTERNATIVES FOR A REMOTE ALASKAN AIR STATION THESIS Mark J. Shoviak, Captain, USAF AFIT/GEE/ENV/01M-20 DEPARTMENT OF THE AIR FORCE AIR UNIVERSITY AIR FORCE INSTITUTE OF TECHNOLOGY Wright-Patterson Air Force Base, Ohio APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED. The views expressed in this thesis are those of the author and do not reflect the official policy or position of the United States Air Force, Department of Defense, or the U. S. Government. AFIT/GEE/ENV/01M-20 DECISION ANALYSIS METHODOLOGY TO EVALUATE INTEGRATED SOLID WASTE MANAGEMENT ALTERNATIVES FOR A REMOTE ALASKAN AIR STATION THESIS Presented to the Faculty Department of Systems and Engineering Management Graduate School of Engineering and Management Air Force Institute of Technology Air University Air Education and Training Command In Partial Fulfillment of the Requirements for the Degree of Master of Science in Engineering and Environmental Management Mark J. Shoviak, B.S. Captain, USAF March 2001 APPROVED FOR PUBLIC RELEASE; DISTRIBUTION UNLIMITED AFIT/GEE/ENV/OlM-20 DECISION ANALYSIS METHODOLOGY TO EVALUATE INTEGRATED SOLID WASTE MANAGEMENT ALTERNATIVES FOR A REMOTE ALASKAN AIR STATION Mark J. Shoviak, B.S. Captain, USAF Approved: Alfred/E. Thai, Jr., Lt Col, USAF, Ph.D. date Advisor William K. Stockman, Lt Col, USAF, Ph.D. date Reader 2fe Fez *\ Stephen P. Chambal, Capt, USAF, Ph.D. date Reader Acknowledgments There are many people I would like to thank for their support and guidance during this challenging and fulfilling thesis effort. This research would not have been possible without the assistance of many people. My sponsor, Captain Mark McCloud, Chief of Environmental Compliance, 611th Civil Engineer Squadron, suggested the thesis topic. Captain McCloud provided much insight and information needed to complete the work. Lieutenant Colonel Al Thal, my thesis advisor, took me under his wing and tailored some of my course electives to give me a better background in solid waste issues. He endured many meetings, discussions, and draft thesis chapters that helped me to improve my research and to complete the project. Capt Stephen Chambal, one of my readers, introduced me to the field of decision analysis, taught me about decision analysis tools and techniques, and provided guidance on the methodology used in this thesis. I would also like to thank Lieutenant Colonel William Stockman, another one of my readers, who made himself available whenever I needed assistance. Additionally, many members of the 611th Civil Engineer Squadron gave me technical information and insight without which, I could not have completed this project. I would especially like to thank my wife for her patience and understanding throughout this program, especially after our daughter was born. I could not have accomplished this without her support. Captain Mark J. Shoviak IV Table of Contents Page Acknowledgments iv List of Figures x List of Tables xii List of Acronyms xiii Abstract xiv Chapter 1. Introduction 1 1.1 Background 5 1.2 Research Problem 5 1.3 Research Objective 5 1.4 Research Question 6 1.5 Research Approach 6 Chapter 2. Literature Review 7 2.1 Fundamentals of MS W 7 2.1.1 Definition of MS W 7 2.1.2 MSW Components 8 2.1.3 Integrated Solid Waste Management 9 2.1.4 Characteristics of MSW 10 2.1.4.1 Physical Properties 11 2.1.4.2 Chemical Properties 13 2.1.4.3 Biological Properties 15 2.1.5 Characterizing the MSW Stream 15 2.2 Eareckson Air Station 17 2.2.1 Military Mission 17 2.2.2 Location 17 2.2.3 Physical Settings 18 2.2.4 Current MSW Management System 19 2.2.4.1 Administration 19 2.2.4.2 Generation 19 2.2.4.3 Storage 19 2.2.4.2 Collection : 19 2.2.4.3 Landfilling 20 2.3 MSW Regulatory and Policy Environment 20 2.3.1 MSW Disposal Regulations 21 2.3.1.1 Federal Disposal Requirements 21 2.3.1.2 State Disposal Requirements 22 2.3.2 Air Emissions Regulations Related to MSW Management 24 Page 2.3.2.1 Federal Air Emissions Requirements 24 2.3.2.2 State Air Emissions Requirements 24 2.3.3 MSW Pollution Prevention Regulations and Policies 26 2.3.3.1 Federal MSW Pollution Prevention Regulations 26 2.3.3.2 MSW Pollution Prevention Related Executive Orders 27 2.3.3.3 Air Force Pollution Prevention Policy 28 2.4 MSW Management Alternatives 29 2.4.1 Recycling Alternatives 30 2.4.1.1 Materials 31 2.4.1.2 Collection and Separation 31 2.4.1.3 Transportation 32 2.4.2 Composting Alternatives 32 2.4.2.1 Vermiculture 33 2.4.2.2 Windrow 33 2.4.2.3 Aerated Static Pile 33 2.4.2.4 In-Vessel 34 2.4.3 Incineration Alternatives 34 2.4.3.1 Starved Air/Modular Systems 35 2.4.3.2 Mass-Fired Systems 36 2.4.3.3 RDF-Fired Systems 36 2.4.4 Landfilling Alternatives 37 2.4.4.1 Class IMSWLF 37 2.4.4.2 Class II MSWLF 38 2.4.4.3 Class III MSWLF 38 2.5 Decision Analysis 39 2.5.1 Introduction to Decision Analysis 39 2.5.2 General Applications to MSW 41 2.5.3 Specific Applications to MSW 42 2.5.4 Value-Focused Thinking 44 2.5.4.1 VFT Versus Alternative-Focused Thinking 44 2.5.4.2 Advantages of Value-Focused Thinking 44 2.6 Decision Support Model Framework 47 2.6.1 Step 1 - Identify the Problem 47 2.6.2 Step 2 - Develop Objectives Hierarchy 47 2.6.2.1 Generating Objectives 48 2.6.2.2 Structuring Objectives 49 2.6.2.3 Desirable Properties of an Objectives Hierarchy 50 2.6.3 Step 3 -Develop Evaluation Measures 51 2.6.4 Step 4 - Create Value Functions 52 2.6.5 Step 5 - Objectives Hierarchy Weights 56 2.6.6 Step 6 - Alternative Generation 58 2.6.7 Step 7 - Alternative Scoring 59 2.6.8 Step 8 - Deterministic Analysis 59 2.6.9 Step 9 - Sensitivity Analysis 61 VI Page 2.6.10 Step 10 - Recommendations Presentation 61 Chapter 3. Methodology 62 3.1 Step 1 - Identify the Problem 64 3.2 Step 2 - Develop Objectives Hierarchy 65 3.2.1 20-Year Compliant MSW System 66 3.2.1.1 Resources 66 3.2.1.2 Waste Diversion 68 3.2.1.3 Implementation Time 68 3.2.1.4 Compliance Burden 69 3.3 Step 3 - Develop Evaluation Measures 70 3.3.1 Evaluation Measure for Facility Size 72 3.3.2 Evaluation Measure for Start-Up Cost 72 3.3.3 Evaluation Measure for Recurring O&M Cost 72 3.3.4 Evaluation Measure for Facility Location 72 3.3.5 Evaluation Measure for Waste Diversion 73 3.3.6 Evaluation Measure for Implementation Time 73 3.3.7 Evaluation Measure for CEV Overhead 73 3.3.8 Evaluation Measure for Liability to Air Force 73 3.3.9 Evaluation Measure for Impact to Environment 74 3.4 Step 4 - Value Functions 75 3.4.1 Value Function for Facility Footprint 75 3.4.2 Value Function for Start-Up Cost 77 3.4.3 Value Function for Recurring O&M Cost 78 3.4.4 Value Function for Facility Location 79 3.4.5 Value Function for Waste Diversion 80 3.4.6 Value Function for Implementation Time 81 3.4.7 Value Function for CEV Overhead 82 3.4.8 Value Function for Liability to Air Force 83 3.4.9 Value Function for Impact to Environment 84 3.5 Step 5 -Objectives Hierarchy Weights 85 3.5.1 Local Weight for Resources Sub-Objectives 86 3.5.2 Local Weight for Compliance Burden Sub-Objectives 87 3.5.3 Local Weight for 2-Year Compliant MSW System Sub-Objectives 87 3.5.4 Global Weights for Last-Tier Objectives 88 3.6 Step 6 - Alternative Generation 88 3.6.1 Landfill Assumptions and Constraints 89 3.6.2 Incineration Assumptions and Constraints 89 3.6.3 Recycling Assumptions and Constraints 90 3.6.4 Composting Assumptions and Constraints 91 3.6.5 Political Assumptions and Constraints 91 3.6.6 Summary of Eareckson AS MSW Alternatives 92 vn Page Chapter 4. Data Collection & Analysis of Results 93 4.1 Alternative Analysis 93 4.2 Eareckson AS Waste Stream Characterization 94 4.3 Step 7 - Alternative Scoring 97 4.3.1 Data for Facility Size 97 4.3.2 Date for Start-Up Cost 99 4.3.3 Data for Recurring O&M Cost 100 4.3.4 Data for Facility Location 101 4.3.5 Data for Waste Diversion 102 4.3.6 Data for Implementation Time 104 4.3.7 Data for CEV Overhead 105 4.3.8 Data for Liability to Air Force 106 4.3.9 Data for Impact to Environment 107 4.4 Step 8 - Deterministic Analysis 108 4.4.1 Overall Value and Ranking of Alternatives 108 4.4.2 Insight Into Top Model Alternatives 110 4.5 Step 9 - Sensitivity Analysis 112 4.5.1 Global Weight Sensitivity 113 4.5.1.1 Facility Size Global Weight Sensitivity 114 4.5.1.2 Start-Up Cost Global Weight Sensitivity 115 4.5.1.3 Recurring O&M Cost Global Weight Sensitivity 116 4.5.1.4 Facility Location Weight Global Sensitivity 118 4.5.1.5 Waste Diversion Weight Global Sensitivity 120 4.5.1.6 Implementation Time Global Weight Sensitivity 121 4.5.1.7 CEV Overhead Weight Global Sensitivity 122 4.5.1.8 Liability to Air Force Weight Global Sensitivity 123 4.5.1.9 Impact to Environment Weight Global Sensitivity 124 4.5.1.10 Global Weight Sensitivity Summary 125 4.5.2 Local Weight Sensitivity (Third-Tier) 126 4.5.3 Local Weight Sensitivity (Second-Tier) 128 4.5.3.1 Resources Local Weight Sensitivity 129 4.5.3.2 Waste Diversion Local Weight Sensitivity 130 4.5.3.3 Implementation Time Local Weight Sensitivity 130 4.5.3.4 Compliance Burden Local Weight Sensitivity 130 4.5.3.5 Local Weight Sensitivity Summary 131 4.5.4 Sensitivity of Key Model Parameters 132 4.5.4.1 Landfill Depth Sensitivity 132 4.5.4.2 Recovery Rate Sensitivity 134 4.5.4.3 Waste Characterization Data Sensitivity 136 Chapter 5.
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