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An Integrated Decision-Making Model for Selecting HVAC Systems Using Multiple Performance Criteria

Permanent Link: http://ufdc.ufl.edu/UFE0042005/00001

Material Information

Title: An Integrated Decision-Making Model for Selecting HVAC Systems Using Multiple Performance Criteria
Physical Description: 1 online resource (192 p.)
Language: english
Creator: Jia, Xun
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: ahp, decision, economical, energy, environmental, hvac, leed, performance
Mechanical and Aerospace Engineering -- Dissertations, Academic -- UF
Genre: Mechanical Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: There is currently no comprehensive model which considers multiple performance criteria in choosing HVAC systems. This dissertation aims at developing an integrated decision-making model for selecting HVAC systems based on various performance criteria, including technical performance, environmental performance, economic performance and LEED performance. An analytical hierarchy process (AHP) method is used as the basis of the decision-making model to generate the optimal HVAC system. The preference weightings of performance criteria are assigned to the hierarchy structure based on the preference of the decision-makers. The weightings of the performance criteria are further integrated with the performance indicators of alternatives to calculate an overall score for each HVAC alternative of interest. With the decision-making model, the alternatives are ranked by the overall scores and the alternative with the highest score indicates the optimal HVAC system based on its comprehensive performance and preferences of the decision makers. A case study is conducted to further test the validity of the methodology. Sensitivity analysis and consistency checks are conducted to track the sensibility and accuracy of the model. This dissertation also provides thoughts on the development of software for the decision-making model for the purpose of facilitating the programming process and reducing the complexity of the model inputs and outputs.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Xun Jia.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Ingley, Herbert A.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-02-28

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042005:00001

Permanent Link: http://ufdc.ufl.edu/UFE0042005/00001

Material Information

Title: An Integrated Decision-Making Model for Selecting HVAC Systems Using Multiple Performance Criteria
Physical Description: 1 online resource (192 p.)
Language: english
Creator: Jia, Xun
Publisher: University of Florida
Place of Publication: Gainesville, Fla.
Publication Date: 2010

Subjects

Subjects / Keywords: ahp, decision, economical, energy, environmental, hvac, leed, performance
Mechanical and Aerospace Engineering -- Dissertations, Academic -- UF
Genre: Mechanical Engineering thesis, Ph.D.
bibliography   ( marcgt )
theses   ( marcgt )
government publication (state, provincial, terriorial, dependent)   ( marcgt )
born-digital   ( sobekcm )
Electronic Thesis or Dissertation

Notes

Abstract: There is currently no comprehensive model which considers multiple performance criteria in choosing HVAC systems. This dissertation aims at developing an integrated decision-making model for selecting HVAC systems based on various performance criteria, including technical performance, environmental performance, economic performance and LEED performance. An analytical hierarchy process (AHP) method is used as the basis of the decision-making model to generate the optimal HVAC system. The preference weightings of performance criteria are assigned to the hierarchy structure based on the preference of the decision-makers. The weightings of the performance criteria are further integrated with the performance indicators of alternatives to calculate an overall score for each HVAC alternative of interest. With the decision-making model, the alternatives are ranked by the overall scores and the alternative with the highest score indicates the optimal HVAC system based on its comprehensive performance and preferences of the decision makers. A case study is conducted to further test the validity of the methodology. Sensitivity analysis and consistency checks are conducted to track the sensibility and accuracy of the model. This dissertation also provides thoughts on the development of software for the decision-making model for the purpose of facilitating the programming process and reducing the complexity of the model inputs and outputs.
General Note: In the series University of Florida Digital Collections.
General Note: Includes vita.
Bibliography: Includes bibliographical references.
Source of Description: Description based on online resource; title from PDF title page.
Source of Description: This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
Statement of Responsibility: by Xun Jia.
Thesis: Thesis (Ph.D.)--University of Florida, 2010.
Local: Adviser: Ingley, Herbert A.
Electronic Access: RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2011-02-28

Record Information

Source Institution: UFRGP
Rights Management: Applicable rights reserved.
Classification: lcc - LD1780 2010
System ID: UFE0042005:00001


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1 AN INTEGRATED DECISIONMAKING MODEL FOR SELECTING HVAC SYSTEMS USING MULTIPLE PERFORMANCE CRITERIA By XUN JIA A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLORIDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2010

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2 2010 Xun Jia

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3 To my parents, Yun Jia and Min Xu

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4 ACKNOWLEDGMENTS First of all, I would like to express my appreciation to my advisor Dr. H. A. Ingley T his dissertation would not have been possible without his insights encouragement guidance and support from the preliminary to the concluding level of my dissertation. I am also appre ciated for his continuing advice and support on my future career planning so that I could have more opportunities of professional experience s in industry. It greatly benefit s on the completion of my dissertation as well as my future professional career I am g rateful to my committee members for their effort s and insights on my dissertation Thanks to the support of my family and friends. Special thanks to Qiang for his company and unselfish love, which encouraged me through tough times during my PhD pursu it.

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5 TABLE OF CONTENTS page ACKNOWLEDGMENTS ...................................................................................................... 4 LIST OF TABLES ................................................................................................................ 8 LIST OF FIGURES ............................................................................................................ 10 ABSTRACT ........................................................................................................................ 12 CHAPTER 1 INTRODUCTION ........................................................................................................ 14 Introduction ................................................................................................................. 14 Purpose and Goal ....................................................................................................... 16 Scope of This Dissertation ......................................................................................... 17 Methodology Overview ............................................................................................... 17 2 BACKGROUND AND LITERATURE REVIEW .......................................................... 20 Introduction ................................................................................................................. 20 HVAC Systems ........................................................................................................... 20 Assessment Methods for HVAC Performance .......................................................... 22 Technical Performance ........................................................................................ 22 Effectiveness ................................................................................................. 23 Reliability ....................................................................................................... 24 Maintainability ................................................................................................ 24 Spatial requirements ..................................................................................... 25 Technical performances of typical HVAC systems ...................................... 25 Environmental Performance ................................................................................ 29 Brief history of LCA ....................................................................................... 30 Definition of LCA ............................................................................................ 30 Phases of an L CA ......................................................................................... 31 Recent r esearch of a pplying LCA to HVAC systems ................................... 40 Economic Performance........................................................................................ 45 Green Buildi ng Rating System: LEED ................................................................. 48 3 PERFORMANCE ASSESSMENT MODELS ............................................................. 52 Technical Model .......................................................................................................... 52 Effectiveness ........................................................................................................ 52 Maintainability ....................................................................................................... 52 Reliability .............................................................................................................. 53 Spatial Requirement ............................................................................................ 53 Environmental Model: Life Cycle Assessment .......................................................... 54

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6 Goal and Scope ................................................................................................... 54 Inventory Analysis ................................................................................................ 54 Impact Assessment .............................................................................................. 54 Interpretation ........................................................................................................ 56 Economic Model: Life Cycle Cost .............................................................................. 56 Simple Payback Method ...................................................................................... 57 Present Value Method ......................................................................................... 57 LEED Green Building Rating System ........................................................................ 60 Optimize Energy Performance ............................................................................ 60 Enhanced Refrigerant Management ................................................................... 60 4 AHP DECISION MAKING MODEL DEVELOPMENT ............................................... 62 The Structure of AHP Model ...................................................................................... 62 Goal Layer ................................................................................................................... 65 Criteria Layer .............................................................................................................. 65 Pairwise comparison ............................................................................................ 65 The importance judgment matrix ......................................................................... 67 Consistency check ............................................................................................... 68 Sub-criteria Layer ....................................................................................................... 68 Alternative Layer ......................................................................................................... 69 5 CASE STUDY ............................................................................................................. 73 Background ................................................................................................................. 73 Building and Location Description ....................................................................... 73 Alternative Systems Description .......................................................................... 73 Performance Results .................................................................................................. 75 LEED Performance .............................................................................................. 75 Energy simulation results .............................................................................. 75 EAc4 Enhanced refrigerant management .................................................... 80 Economic Performance........................................................................................ 82 Capital components ....................................................................................... 82 Utility cost ...................................................................................................... 82 Life cycle cost ................................................................................................ 84 Environmental Performance ................................................................................ 86 Technical Performance ........................................................................................ 88 AHP Module Application ............................................................................................. 90 Established Hierarchy Structur e .......................................................................... 90 Goal Layer ............................................................................................................ 91 Criteria Layer ........................................................................................................ 92 Pairwise comparison ..................................................................................... 92 Calculating weightings of performance criteria ............................................ 93 Consistency check ........................................................................................ 94 Sub-criteria Layer ................................................................................................. 94 Technical crit eria ........................................................................................... 94 Economic criteria ........................................................................................... 95

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7 Environmental criteria.................................................................................... 95 LEED criteria .................................................................................................. 96 Summary of weightings for criteria and sub-criteria ..................................... 96 Alternativ e Layer .................................................................................................. 97 Economic performance criteria ..................................................................... 97 Environmental performance .......................................................................... 98 LEED p erformance ........................................................................................ 99 Technical performance criteria.................................................................... 100 Results ...................................................................................................................... 101 Sensitivity Analysis ................................................................................................... 102 Fuel Mix o f Electricity ......................................................................................... 102 Weighting Effect ................................................................................................. 107 6 THOUGHTS ON SOFTWARE DEVELOPMENT .................................................... 111 Sizing Module ........................................................................................................... 112 Equipment and Syst em Module ............................................................................... 113 Energy Simulation Module ....................................................................................... 115 Performance Module ................................................................................................ 117 Decision Making Module .......................................................................................... 118 7 CONCLUSION AND RECOMMENDATIONS .......................................................... 121 Conclusions .............................................................................................................. 121 Recommendations for Future Work ......................................................................... 122 APPENDIX A ENERGY SIMULATION RESULTS ......................................................................... 124 B PERFORMANCE RATING DETAILS ...................................................................... 161 C ENERGY COST BUDGET ....................................................................................... 163 D ECONOMIC COST ................................................................................................... 165 E BLCC INPUTS AND SUMMARY ............................................................................. 173 F DECISION MAKING MODEL PROGRAM ............................................................... 177 LIST OF REFERENCES ................................................................................................. 188 BIOGRAPHICAL SKETCH .............................................................................................. 192

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8 LIST OF TABLES Table page 2 -1 Global warming contribution of green house gases .............................................. 35 2 -2 Global warming potential and ozone depletion potential of refrigerant ................ 35 2 -3 Comparison of impact assessment methods in SimaPro ..................................... 39 2 -4 LEED 2009 energy performance score card ......................................................... 50 3 -1 Characterization and grouping into damage category in Impact 2002+ ............... 55 3 -2 Characterization damage factors of various reference substances ..................... 55 3 -3 Normalization factors for the four damage categories for Western Europe ......... 56 3 -4 Life cycle cost calculation ...................................................................................... 60 4 -1 Importance scale for pairwise comparison ............................................................ 66 4 -2 Importance judgment matrix in criteria layer ......................................................... 67 4 -3 Random consistency index .................................................................................... 68 4 -4 Weightings of damage categories in Impact 2002+ .............................................. 69 4 -5 Conversions of performance values into PIs for LEED performance ................... 70 4 -6 Conversions of performance values into PIs for technical performance .............. 70 5 -1 Weather and building information .......................................................................... 74 5 -2 The energy mixes of electricity generation in Georgia .......................................... 74 5 -3 Rate structure and water charge ........................................................................... 75 5 -4 Performance parameters for alternative and baseline systems ........................... 76 5 -5 Performance energy cost rating for baseline case: ASHRAE 90.1 2004 ............ 78 5 -6 Energy cost savings and earned points in EAc1, LEED -NC ................................ 79 5 -7 Refrigerant contributions fo r alternatives ............................................................... 81 5 -8 Summary of LEED performance of alternatives .................................................... 81 5 -9 Summary of initial and maintenance cost of alternatives ..................................... 82

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9 5 -10 Life cycle cost of alternative 1 ................................................................................ 85 5 -11 Life cycle cost of alternative 2 ................................................................................ 85 5 -12 Life cycle cost of alternative 3 ................................................................................ 86 5 -13 Energy mix for electricity in Atlanta, GA ................................................................ 86 5 -14 Technical performance of alternatives .................................................................. 89 5 -15 Comparison matrix for criteria layer ....................................................................... 93 5 -16 Comparison matrix in technical requirement criteria ............................................. 94 5 -17 Weighting sets in impact 2002+ ............................................................................. 95 5 -18 Weightings for criteria and sub-criteria .................................................................. 97 5 -19 Performance indicators in life cycle cost ( =2.30E -7, 3 =1.40E 8) ..................... 98 5 -20 Performance indicators for human health ( =0.025, 3 =3.762E 3) ..................... 98 5 -21 Performance indicators for ecosystem quality ( =1.45, 3 =0.213) ...................... 98 5 -22 Performance indicators for climate change ( =0.035, 3 =4.98E 3) .................... 98 5 -23 Performance indicators for resources ( =0.022, 3 =3.237E -3) ........................... 99 5 -24 Performance indicators for optimized energy performance .................................. 99 5 -25 Performance indicators for enha nced refrigerant management ........................... 99 5 -26 Performance indicators for full load effectiveness .............................................. 100 5 -27 Performance indicators for part load effectiveness ............................................. 100 5 -28 Performance indicators for reliability ................................................................... 100 5 -29 Performance indicators for maintainability .......................................................... 100 5 -30 Performance indicators for spatial requirement .................................................. 101 5 -31 Integrated score for three alternatives ................................................................. 101 5 -32 Fuel mix for electricity in five regions of the United States ................................. 103 5 -30 Integrated score with Washington energy m ix scenario ..................................... 107 6 -1 Summarization of software used or needed for the decisionmaking modules and their alternatives ............................................................................................ 112

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10 LIST OF FIGURES Figure page 1 -1 The decisionmaking model structure for choosing the optimal HVAC system ... 18 2 -1 Life cycle processes ............................................................................................... 31 2 -2 Relationship of interpretation steps with other phases of LCA ............................. 32 2 -3 Elements of th e LCIA phase .................................................................................. 34 3 -1 Present value method ............................................................................................ 57 4 -1 The structure of analytic hierarchy process .......................................................... 63 4 -2 Hierarchy structure for choosing the optimal HVAC system ................................. 64 4 -3 Pairwise comparison of performance criteria ........................................................ 66 4 -4 Correlation between PI and standard normal distribution ..................................... 71 5 -1 Monthly HVAC energy consumption of alternatives ............................................. 77 5 -2 Annual energy consumption for alternatives and baseline ................................... 78 5 -3 Energy cost savings of alternatives compared with baseline 90.1 ....................... 79 5 -4 Annual water cost of alternatives ........................................................................... 83 5 -5 Monthly utility cost of alternatives .......................................................................... 83 5 -6 Annual Operating Cost of alternatives ................................................................... 84 5 -7 Characterization of environmental performance in fourteen midpoint categor ies ............................................................................................................... 87 5 -8 Weighting of environmental performance in four impact categories .................... 88 5 -9 Single score of environmental performance for three alternatives ....................... 88 5 -10 The decisionmaking hierarchy structure .............................................................. 91 5 -11 Pairwise comparison of performance criteria ........................................................ 92 5 -12 Midpoint impact of fuel mix for 1kWh electricity in five states of the United States .................................................................................................................... 104

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11 5 -13 Damage assessment of electricity mix for 1kWh electricity in five states of the United States. ....................................................................................................... 105 5 -14 Single score for the environmental impact of electricity mix for 1kWh electricity in five states of the United States ........................................................ 106 5 -15 Damage impacts for alternatives with energy mix in Washington ...................... 106 5 -16 Overall scores for alternatives with energy mix in Washington .......................... 107 5 -17 Sensitivity analysis for the weighting of technical requirement .......................... 108 5 -18 Sensitivity analysis for the weighting of economical performance ..................... 109 5 -19 Sensitivity ana lysis for the weighting of environmental performance ................. 109 5 -20 Sensitivity analysis for the weighting of LEED performance .............................. 110 6 -1 Structure of the sizing module ............................................................................. 114 6 -2 Equipment and system module ........................................................................... 115 6 -3 Structure of energy simulation model .................................................................. 116 6 -4 Structure of performance model .......................................................................... 118 6 -5 Structure of decision making model .................................................................... 119 6 -6 Overall diagram of the entire decisionmaking model structure ......................... 120

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12 Abstract of Dissertation Presented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy AN INTEGRATED DECISIONMAKING MODEL FOR SELECTING HVAC SYSTEMS USING MULTIPLE PERFORMANCE CRITERIA By Xun Jia August 2010 Chair: H. A. Ingley Major: Mechanic al Engineering There is currently no comprehensive model which considers multiple perfo rmance criteria in choosing HVAC systems. This dissertation aims at developing an integrated decision making model for selecting HVAC systems based on various performance criteria, including technical performance, environmental performance, economic performance and LEED performance. An analytical hierarchy process (AHP ) method is used as the basis of the decision-making model to generate the optimal HVAC system. The preference weightings of performance criteria are assigned to the hierarchy structure based on the preference of the decision -makers. The weightings of the performance criteria are further integrated with the performance indicators of alternatives to calculate an overall score for each HVAC alternative of interest With the decision making model, the alternatives are ranked by the overall scores and t he alternative with the highest score indicates the optimal HVAC system based on its comprehensive performance and preference s of the decision makers. A case study is conducted t o further test t he validity of the methodology. Sensitivity analysis and consi stency checks are conducted to track the sensibility and accuracy of the model. This dissertation also provides thoughts on the development of

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13 software for the decisionmaking model for the purpose of facilitating the programming process and reducing the c omplexity of the model inputs and outputs.

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14 CHAPTER 1 INTRODUCTION Introduction The b uilding industry has a great impact on the environment and society It is responsible for 40% of the energy use in the United States, 40% of green house gas emissions worldwide, 50% of natural resource consumption including 25% of the wood harvest worldwide and 1/6 of fresh water consumption according to the United Nations Environment Programme (UNEP). The demand for buildings and building renovation continues to increase worldwide. In 2002, there were more than 76 million residential buildings and more than 5 million commercial buildings in the United States and another 38 million are expected to be bui lt by 2010, according to U.S. Department of Energy. Of particular interest to the author of this dissertation, in China, more than 50% of the urban residential and commercial building stock will have been constructed during the previous 15 years by 2015 e stimated by the World Bank (UNEP, Sustainable building and construction: Facts and figures, April -September 2003) The energy consumption for buildings catches more attention than ever before because of its huge energy demand and its negative contribution to the environment. I n developed countr ies o ne third of the energy end -use is consumed by heating, cooling, lighting, appliances and general services in non-industrial applications (i.e. residential, commercial and public) bui ldings according to the International Energy Agency (IEA, 2009) In the United States, buildings account for 65% of electricity consumption. The negative environmental impact of buildings keeps rising with the increase demand in building and infrastructure as the population increases. With the severe environmental degradation and natural resource depletion occurring today more and more emphasis is being paid

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15 to the use of environmental fri endly products and processes. Since bu ildings ha ve a great impact on the environment during their useful life time, it is urgent and vital to consider sustainability and least -impact principles during the design phase of the building system Identifying and quantifying the environmental impact of HVAC products and systems is essential to the environmental performance of the building industry. Although there have been numerous environmental evaluations on building materials, very little research has been conduct ed on heating, ventilating and air conditioning system s This is probably because of the complexity of their components and various arrangements. One of the focuses of t his dissertation is to apply life -cycle assessment methodology in selecting HVAC products and systems Economic benefit is another important consideration for selecting a HVAC system. The initial investment, life -span energy consumption, the maintenance and replacement cost s are critical factors for evaluating the economical performance of a certain system or equipmen t. Some of the systems may not save energy during their us eful life, but the economic benefits may be significant. For many of the owners and developers, the Cost and Benefit is an essential consideration for choosing the system. So this dissertation als o includes the economic performance for evaluating a HVAC system s combined with the other performances LEED (Leadership in Energy and Environmental Design) has gained popularity in recent years. Developed by USGBC (U.S. Green Building Council), it is a green building certification system recognized internationally. It provides strategies aimed at lessening the impact of the buildings on resources including saving energy, improving water efficiency, reducing CO2 emissions, and improving indoor and outdoor environmental

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16 quality of buildings. More and more developers and building owners would like to get their buildings certified and show their c ommitment for sustainable and green environment. Choosi ng green HVAC systems is important to have a building cert ified with energy efficiency contribut ing the most credits in the rating system. Including LEED thinking into the HVAC system selections has almost became a necessity for new built HVAC design. Other technical requirements may also be considered when choosing a system or equipment for a building These requirements include full load effectiveness, part load effectiveness, reliability, maintainability and the spatial requirement It is more explicit to combine various performance criteria into a certai n value to give a comprehensive result for decision making. For this purpose, the A nalytical Hierarchy Process (AHP) method is introduced to assist the decision makers to find a solution that best suit s their needs. It puts weighting on the performance cri teria based on the preference of the decision makers and combine s them with the performances of the alternatives to get the optimal HVAC system. Purpose and Goal Since t here is currently no integrated model w hich considers comprehensive performances in ch oosing the optimal HVAC systems t his dissertation aims at developing an integr ated decision-making model for select ing HVAC systems based on the pre ferences of decision makers as well as the performances of alternatives. The selection is based on multiple performance criteria including the technical performance, environmental performance, economic performance and LEED performance. These factors are combined into a single score and ranked for the easy interpretation and use by decision makers.

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17 Scope of T his D issertation The decisionmaking methodology can be applied to the selection of all kinds of HVAC systems, especially for large commercial building applications since the HVAC system scenario strategies are vital in the design phase and will have larger impact on the future operation. All of t he HVAC systems in the scope of the decision making model are assumed to meet the cooling and heating load of the building of interest and satisfy indoor thermal comfort requirements. Methodology Overview Performance assessment models are crated to evaluate the integrated performance of the HVAC system and equipment. The performance models include technical model, environmental model, economic model, and LEED model. The Analytical hierarchy process (AHP) method is used as the basis of the decisionmaking model to generate the optimal HVAC system The outline and structure for choosing a HVAC system is shown in Figure 11. A hierarchy structure is set up and the preference weightings are assigned to performance models b ased on the preference of the decision makers. The preference weightings of the performance criteria are further integrated with the p erformance indicators to calculate an overall score for each alternative. The alternative with the highest score indicate s the best choice based on its comprehensive performance and the preference of the decision makers. During these processes, consistency checks and sensitivity analysis are perform ed to track the accuracy of the analysis. A case study is conducted to further explain and test the validity of th e model. The decision making model is also programmed with MAT HCAD to facilitate the calculation.

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18 Figure 11. The decision making model structure for choosing the optimal HVAC system The dissertation also provides t houghts on software development for the decisionmaking model to facilitate the decisionmaking process and reduce the complexity of the model inputs and outputs. Figure 12 shows the 5 modules (sizing module, equipment and system m odule, energy simulation m odule, performance module and decisionmaking module) embedded in the overall model and the internal logical connection between modules

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19 Fig 1 2 Overall di a gram of the decision making model structure for software development

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20 CHAPTER 2 BACKGROUND AND LITERATURE REVIEW Introduction This chapter discusses typical HVAC systems applied in commercial buildings Because of the large variety of HVAC systems, the reference sources of HVAC systems are listed for the further information on HVAC systems. This chapter also discusses different performance assessment methods for evaluating the technical, environmental and economic performances of HVAC systems. The t echnical performance includes effective ness, reliability, maintainability and spatial requirement. Life cycle assessment (LCA) is used for evaluating the environmental performance of HVAC systems. Life cycle cost analysis (LCC) is the method for evaluating the economic performance of HVAC systems. In including Analytical Hierarchy Process (AHP) is introduced as the basis for the decision making model for selecting HVAC systems based on multiple performance criteria HVAC Systems A typical HVAC system for commercial building s contains a cooling plant, a heating plant and air de livery system. For example, for chilled water and heating hot water system chilled water or hot water is pumped from the chiller/boiler plant to the air handling unit(s) ( AHU). At the air handling unit fresh air is introduced for ventilation purposes and often mixed with return air from the conditioned space, the mixed air is then heated and/or cooled and distributed to the conditioned space. The cooling water from the chil lers condenser is carried to the cooling tower to reject heat to the atmosphere. The building autom ation system (BAS) controls and manages the mechanical system

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21 ASHRAE (American Society of Refrigeration and Air -conditioning Engineers) is an international organization that establishes standards for the uniform testing and rating of heating, ventilation, air conditioning, and refrigeration equipment. Series of ASHRAE handbooks are the basis references for HVAC information and one of the handbooks is edited and published each year : ASHRAE Fundamentals (ASHRAE, ASHRAE Handbook Fundamentals, 2005) discusses fundamental thermodynamics and heat transfer theory, load and energy calculation, duct and pipe design of HVAC systems; ASHR AE HVAC Systems and Equipment (ASHRAE, 2008) discusses all kinds of heating, cooling and air handl i ng systems and equipment, and their components; ASHRAE HVAC Applications (ASHRAE, 2007) discusses HVAC systems in various applications including general application, comfort application, industrial application and energy -related application, as well as building operation and management; ASHRAE Refrigeration (A SHRAE, 2006) discusses refrigeration equipment and their application. There are commonly accepted standards and guidelines for the use of architects and engineers. ASHRAE Standard 34 (ASHRAE, 2004) is the designation and Safety classification of refrigerants. ASHRAE Standard 55 (ASHRAE, 2004) is the thermal comfort standard for satisfactory indoor thermal environmental for human occupancy. ASHRAE Standard 62.1 (ASHRAE, 2007) is the ventilation standard for acceptable indoor air quality including the requirement and calculation of minimum ventilation rate. ASHRAE 90.1 (ASHRAE, 2007) is the energy standard for buildings e xcept low -rise residential buildings. ASHRAE 135 (ASHRAE, 2004) is the data communication protocol for building automation and control networks.

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22 For the purpose of LEED (Leadership in Energy and Environmental Design), ASH RAE 90.1 is the main reference standard to provide minimum energy efficiency design and build the baseline model for the energy simulation. It offers the minimum insulation factors for the building envelops in different climate zones, the minimum energy ef ficiency for heating and cooling equipment for different types of buildings, indoor and outdoor lighting allowances, etc. The Appendix G performance rating method in ASHRAE 90.1 is basis of LEED optimized energy performance for rating the energy efficiency of building designs that exceed the requirement of the standard. ASHRAE 62.1 is the reference guideline to meet the minimum ventilation requirement of the building for satisfactory indoor environmental quality in LEED ASHRAE also provides green guide for the design, construction and operation of sustainable buildings to help designer with energy -saving and environmental -friendly strategies in designing mechanical systems. Assessment Methods for HVAC Performance Technical Performance The design of heating, ventilating and air -conditioning system should consider meeting various requirements to provide comfortable, functional, and environmental friendly indoor environment. These requirements include not only the energy effectiveness of the equipment, but also how reliable and maintainable it is. ASHRAE Handbook -Systems and Equipment lists several criteria when selecting an HVAC system considering thermal requirements as well as the economical requirement. The selection of sub -criteria for technical performanc e is based on ASHRAE System and Equipment Handbook.

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23 Effectiveness Coefficient of Performance (COP) and kW/ton COP is used to describe the efficie ncy of chillers under full load. Another similar performance concept uses the electrical demand of the machine referenced to its capacity, i.e., kW/ton. Integrated Part Load Value (IPLV) IPLV is applied to represent both the full and part -load performance of a chiller. The typical system load profile is defined by ARI. T he efficiency of air conditioners is measur ed under a variety of conditions with 25%, 50 %, 75% and 100% of capacity at different temperatures. IPLV is only applied for non residential central air conditioner. Seasonal Energy Efficiency Ratio (SEER) The efficiency of air conditioners and heat pumps less than 5 tons is often rated by the Seasonal Energy Efficiency Ratio (SEER). SEER is the ratio of cooling output (in Btu) during a typical cooling-season to the total electric energy input (in watt -hours) during the same period. The higher SEER rating, the better efficiency of the cooling unit is. In September 2006 DOE began enforcing a 13 SEER standard for all residential central air conditioners ENERGY STAR -labeled central air conditioners have a minimum rating of SEER 12. Energy Efficiency Ratio (EER) Similar to SEER, EER represents the efficiency of air conditioners and heat pumps greater than 5 tons. The efficiency is determined at a single rated condition specified by an appropriate equipment standard. It i s defined as the ratio of the coolin g capacity (in Btu/h) to the total input rate of electric power applied (in Watts ). The units of EER are Btu/Wh. Heating Seasonal Performance Factor (HSPF) The Heating Seasonal Performance Factor (HSPF) is used to measure the energy efficiency of a heat pump during the heating season. It represents the total heating output of a heat pump

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24 (including supplementary electric heat) during the normal heating season (in Btu) as compared to the total electricity consumed (in watt hours) during the same period. All heat pumps should be rated at a minimum of 7.6 HSPF for energy efficient heat pumps Annual Fuel Utilization Efficiency (AFUE) The Annual Fuel Utilization Efficiency (AFUE) measures the amount of fuel converted to heat for combustion equipment (furnaces, boilers). ENERGY STAR label ed furnaces must meet a minimum AFUE of 90. Reliability Reliability defines the ability of a system or component to perform its required functions under stated conditions without failure. It is very important for a HVAC system to be reliable. A centralized s ystem is reliable since it has longer estimated equipment service life. A decentralized system is generally reliable although with a shorter estimated equipment service life. Maintainability Maintainability is the ease, speed and cost for any maintenance activity to be carried out on an equipment or system Both of the time needed and the convenience for maintenance are importance to HVAC system since it costs time and m oney as well as the satisfactory of tenants A centralized system is typically located at an equipment room located in a basement, penthouse, and service area away from the occupancy space. Access to the occupancy space is not required thus eliminating the disruption to the tenants. A decentralized system may or may not need equipment rooms. The maintenance cost for a decentralized system is relatively low since it is conveniently located and equipment with associated components is standardized. Maintenance may be difficult during bad weather when the equipment is located outdoors.

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25 Spatial requirements The total mechanical and electrical space requirements range between 4 to 9% of the gross building area with most buildings falling within the 6 to 9% range according to ASHRAE. The heating and cooling system and associated distribution system often occupy a significant amount of space, so horizontal and vertical space requirements of the HVAC should be considered. A decentralized system may or may not require equipment rooms since the equipment may be located on the roof or ground adjacent to the building because of the space restriction. It also may not require duct and pipe shafts throughout the building. An equi pment room is required by a centralized system which is normally located outside of the conditioned space: in a basement, service area adjacent to or remote from the building. Secondary equipment and system may be required for air or water distribution. T echnical performances of t ypical HVAC systems Typical HVAC system applications in building s are discussed in the following section in term of technical performance in energy and efficiency, reliability, maintainability and spatial requirement. Packaged DX rooftop VAV system System description A rooftop VAV system uses a packaged rooftop VAV air conditioner to delivery conditioned air to VAV terminals which are located at the ceiling plen um above zones. An outdoor air ventilation duct is associated with the system to provide fresh air to the building. Since it is a VAV (Variable Air Volume) system, the quantity of supply air varies based on the cooling load of the building. The supply air flow is regulated by the thermostat in each zone. The rooftop VAV sys tem can only provide cooling and the heating required in the perimeter zone is generally provided by

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26 the fan powered boxes with electric heat strip. The rooftop VAV system is also equipped with an air -cooled condenser. Energy and e fficiency With the use o f the VAV (Variable Air Volume) supply fan and multiple compressors, the rooftop VAV system can perform with great efficiency at the part load operation and save energy. The supply fan can be regulated with the variation of internal load. During the time with low internal load, e.g. after working hours or weekends, the supply air required is minimal thus saving fan motor energy Reliability/ m aintenance The rooftop VAV system is reliable related to repair and replacement since all the parts including com pressor evaporator, condenser, supply and return fan are equipped in one single unit. The single unit configuration also results in fast easy and efficient maintenance since all the components are located on the roof and there is no need to interrupt the tenant for the availability of the space and time. However, if repair or replacement is required, the system must be totally shut down and all the tenants will be affected. Spatial r equirement Since the rooftop VAV system is packaged and located on the roof, there is no need for the extra mechanical room inside of the building. The large duct size for delivery supply air and the associated return air duct may require more space on the ceiling than other systems. Self contained VAV system System description For a self -contained VAV system, or commonly called SWUD (Self -contained Water -cooled Unitary), all the components (including compressor, evaporator and condenser) are housed in a packaged unit. The packaged DX units are located indoors, typically in a s mall mechanical room on each floor of the

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27 building. The compressor is installed in t he system to provide cooling. The cooling water from the condenser is piped to a cooling tower to reject heat to atmosphere. For multi story office buildings or replacement the self -contained VAV unit is installed on each floor. Energy and e fficiency Since a water -cooled condenser is used for a self contained VAV system, the efficiency is around 40% higher than the packaged rooftop units wh ere an air -cooled condenser is used. A waterside economizer is also typically used to pre-cool air before it reaches the evaporator if the cooling water outside is cool enough. With the use of the VAV (Variable Air Volume) supply fan, fan power will be decreased with low internal load, e.g. after working hours or weekends. Reliability/ m aintenance Since the complete SWUD system is distributed on separate floors, equipment on other floors will not be affected if one unit fails. Because the condenser piping is centralized into the coolin g tower on the roof, the access to the roof is minimized. Since the cooling tower is used, chemical treatment must be provided to the cooling tower and the associated water loop to prevent corrosion. Failure in the cooling tower could result in total syst em failure. Spatial r equirement The self -contained VAV system requires the space necessary for small mechanical rooms on each floor. The c ooling tower is located on the roof. Water source heat pump system System description In water source heat pump syst ems, all the heat pumps reject heat to a common water loop along with the cooling tower and hot water boiler. A dedicat e d outdoor system is used to condition all the ventilation air.

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28 Energy and e fficiency Since the heat is rejected to or absorbed from th e same water loop, heating and cooling load can be offset during the mild climate seasons when there is heating required in the perimeter zone while cooling requirement in the core zone. The energy efficiency of water source heat pumps is typically 30% hi gher than the packaged rooftop systems. Reliability/ m aintenance Each heat pump has its own condenser and evaporator. If one heat pump fails, other heat pumps will not be affected. Similar to self contained water -cooled unit, additional chemical treatment is required for the cooling tower and the water loop. The maintenance for the boiler and other associated pumps are minimal. Failure of the cooling tower can cause total system failure. Spatial r equirement The water source heat pump system can be loca ted in a mechanical room, on a roof or above the ceiling. A boiler room is required for the heating during the winter Chilled water VAV system System description For chilled water VAV system, chilled water and hot water are produced at the central location and pumped to the VAV air handlers. Each of the air handler unit deliveries a mixture of outdoor air and re -circulated air to VAV terminals throughout the buildi ng. A cooling tower is connected to the cooling water loop of the chilled water plant. Energy and e fficiency The efficiency of the chiller plant is generally very good With a water -cooled condenser, the system can run very efficiently. The minimum COP o f the air cooled chiller is 2.80 and that of the water cooled centrifugal chiller is 4.90 defined by ASHRAE 90.1 2004.

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29 Reliability/ m aintenance With the existence of the chillers and cooling tower, the maintenance cost is added. Spatial r equirement Space is required for equipment room for the chilled water and hot water plant. A cooling tower is located on the roof. Three HVAC systems talked about here are chosen for t he case study conducted in the later chapter. They are self -contained VAV system, water source heat pump system, and chilled water VAV system since they are the most typical and popular systems used in the modern commercial buildings. Environmental Performance There are many tools developed for evaluating environmental impact including life cycle assessment (LCA), environmental impact assessment (EIA), ecological footprint (EF), emergy analysis, and risk assessment. Life cycle assessment is the most complete and detailed form of life cycle stud ies Life cycle assessment (LCA ) studies analyze the environmental aspects and potential impacts throughout a product's life cycle (e.g., cradle to grave or cradle-to -cradle ) from raw material acquisition through production, use and disposal LCA looks at a whole picture of the product system thus avoidi ng shifting environmental responsibility from one place to another. It has the obvious advantage of revealing potentially significant but hidden environmental impacts. It can provide decisionmakers with the information needed for selecting the process or product which has the least environmental impact It can be widely used in process analysis, material selection, product comparison and evaluation, measuring performance, marketing, policy making and other decision making process. This dissertation uses Life Cycle Assessment (LCA) for evaluating environmental performance of HVAC systems (UNEP, 2003) Since LCA is a relatively new and

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30 compli cate methodology, this dissertation will provide the reader with additional background information B rief history of LCA Life cycle assessment has its beginning in the 1960s. Harold Smith published his calculation of accumulative energy for the production of chemical intermediates and products at the World Energy Conference in 1963. An internal study conducted by The Coca-Cola Company laid the foundation for the life cycle inventory analysis in the United State in 1969. To determine the least impact to the natural resources and the lowest release to the environment of different beverage containers, the study quantified the raw materials and energy consumption during the manufacturing processes for each container In the 1970s, the methodology was refined by the U.S. Environmental Protection Agency and named the Resource and Environmental Profile Analysis (REPA) (Svoboda, 1995) In 1991, LCA standards for the International Standards Organization (ISO) 14000 series (1997 through 2002) were developed (American International Standard, 1998) (American International Standard, 2000) (American International Standard, 2000) Definition of LCA According to ISO 14040 (American International Standard, 1997) life cycle assessment is defined as a compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product system throughout its life cycle. It is a technique for assessing t he environmental aspects and potential impacts by compiling an inventory of relevant inputs and outputs of a product system; evaluating the potential environmental impacts associated with those inputs and outputs; i nterpreting the results of the inventory analysis and impact assessment phases in relation to the objectives of

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31 the study. Figure 2 1 shows the elements and processes within LCA analysis based on (American International Standard, 1997) During the whole life cycle process from raw material acquisition until the end of the products life, the potential environmental impacts of raw materials use, energy consumed and emissions & wastes are considered throughout the process (SAIC, 2006). Fig ure 21 Life cycle processes Phases of an LCA Life cycle assessment methodology consists of four phases: definition of goal and scope, life cycle inventory analysis (LCI) life cycle impact assessment (LCIA) and life cycle interpretation. These phases interact with each other. Figure 2 2 shows the relationship between these phases based on (American International Standard, 1997) Goal and scope definition gives guidance through the entire analysis; i nventory analysis compiles and quantifies all the inputs and outputs through a products life ; impact assessment evaluat es the significance of the potential environmental impacts of the inputs and outputs from inventory analysis; interpretation analysis identify the

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32 significant issues based on the results LCI and LCIA and draw conclusions and recommendations. Goal and Scope Definition. This phase identifies the purpose and the goals for conducting this LCA study, the system/product/process to be studied, assumptions, types of impact and impact assessment method, allocation procedures, data quality requir ement, and its limitations. And it also chooses a functional unit and the system boundaries for the product. Figure 22 Relationship of interpretation steps with other phases of LCA Inventory Analysis (LCI) Life cycle inventory analysis is the second phase of LCA. Inventory analysis compiles and quantifies all the inputs and outputs for a product system through its life time. Life cycle inventory (LCI) components of a product system can be derived to unit processes, elementary flows, product flows across the boundary, and intermediate product flows within the system. Some of the outputs are taken as a part of the inputs; some of the outputs are used as a component of the inputs; some

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33 ancillary inputs (e.g. catalyst) are used within the system boundary. All of these processes obey the mass and energy conservation law. Depending on which database is used for the inventory inputs and outputs, the results of the environmental impact may vary based on the data source. SimaPro is one of the most popu lar and comprehensive LCA tools. SimaPro contains several library data bases for use. Some of the libraries deal with European data (e.g. Ecoinvent); some deal with data from the United States ( e.g. Franklin US LCI 98), however, the US data base is limited. It is impossible to obtain all the necessary data from only a single data base. Thus the data source needed for this analysis is based on the available manufacture data, the Franklin US 98, as well as other European data base s available for use. Impact Assessment (LCIA) Life Cycle I mpact assessment (LCIA ) evaluates the magnitude and significance of the potential environmental impacts of a product system LCIA contains 6 steps (as shown in Figure2 -3 ): Selection of impact categories, Classification, Char acterization, Normalization, Grouping and Weighting. The first three steps are mandatory steps and the last three steps are optional steps according to (American International Standard, 2000) Select ion of the impact categories There are several impact categories commonly being used: global warming, ozone depletion, acidification, eutrophication, photochemical smog, terrestrial toxicity, aquatic toxicity, human health, resource depletion, land use, and water use. These im pact categories differ and change with different impact methods used. Impact categories are chosen based on the LCI results and the project interest.

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34 Figure 2 3 Elements of the LCIA phase Global w arming When solar radiation from the sun passes through the atmosphere, some of the solar radiation is absorbed by the surface of the earth and infrared radiation is emitted from the earths surface. But greenhouse gases in the atmosphere acting as a thickening blanket, absorb and trapp this radiation and re-direct some portion back to the surface, warm ing up the planet ; this is known as the greenhouse effect. Table 2 -1 shows the main greenhouse gases and global warming contribution of these gases (David T. Allen, 2002) W ater vapor, which is the major green house gas, is not included in the table because it is not mainly created by human activities. Emission rate, concentration, residence time and absorptivity rate are four factors for determining the contribution to glob al warming. The increase in carbon dioxide has the largest contribution to global warming (50%) due to fossil fuel combustion and deforestation. For building heating and cooling systems, huge amounts of electricity provided by the burning of fossil fuels a re consumed, which cause high CO2 emissions From the table, it is shown that, except for CO2, chlorofluorocarbon CFC 11 and CFC 12 also contribute greatly to the global warming (1721%). Although CHC -11 and CHC 12 have low emission rates and concentrations, their long residence time and absorptivity capacity can lead to significant global warming. The type and amount of refrigerant use and the maintenance of air -conditioning equipment is significant in their contribution of global warming. Ozone depletion potential The ozone layer in the stratosphere acts as a filter absorbing harmful short wave ultraviolet light while allowing longer wavelengths to pass through. The depletion of the ozone layer allows more harmful short wave

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35 radiation to reach t he Earths surface, causing changes to ecosystems. There may also be adverse effects on agricultural productivity. More harmful radiation can also cause higher skin cancer rates, eye cataracts and suppression of the immune system. CFC 11 is the reference substance for ozone depletion. For a v apor compression chiller, the use of its refrigerant has a key environmental impact on the global warming potential (ODP) and ozone depletion potential (ODP). Table 2 2 lists the contribution of commonly -used refriger ant to these two impacts (Calm, 2002) Table 2 1 G lobal warming contribution of green house gases Gas Estimated Emission Rate (M tons/yr ) Approximate Current Concentration (ppm) Estimated Residence Time ( yrs ) Absorptivity capacity (CO2=1) Estimated Contribution to Global Warming ( % ) CO2 6,000 355 50 200 1 50 Methane (CH4) 300-400 1.7 10 58 1219 Nitrous Oxide (N 2 O) 4 -6 0.31 140-190 206 4 -6 Chlorofluoro -carbons (CFC -11 & CFC 12) 1 0.00040.001 65110 4860 1721 Tropospheric Ozone (O3) not emitted directly 0.022 hrs -days 2000 8 Table 2 2 Global warming potential and ozone depletion potential of refrigerant Refrigerant Ozone Depletion Potential Global Warming Potential R 134a 0 1300 R 123 0.012 120 R 22 0.05 1700 R401a 0.027 970 R404a 0 3260 R407c 0 1525 R408a 0.016 3020 R409a 0.039 1290 R410a 0 1725 R502 0.18 5600 R717 (Ammonia) 0 0 Acidification potential. Acidifying compounds can be dissolved in water or fixed on solid particles. They reach ecosystems through dissolution in rain or wet

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36 deposition and affect trees, soil, buildings, animals, and humans. The main two compounds of acidification are sulfur and nitrogen compounds. The general human source for acidification is fossil fuel and biomass combustion. Other compounds released such as hydrogen chloride and ammonia also contribute to acidification. The reference substance for acidification is the hydroge n ion. Other acidification compounds are converted to hydrogen ions in grams of hydrogen ions per functional unit with the same potential acidifying effect. Eutrophication p otential Eutrophication is the addition of mineral nutrients to the soil or water. Large quantities of mineral nutrients, such as nitrogen and phosphorous, can result in undesirable shifts in the number of species in ecosystems and a reduction in ecological diversity. Algae growth is increased in winter which can lead to lack of oxygen and therefore death of species like fish. Nitrogen is the reference substance. Other substances for eutrophication are converted to nitrogen in grams of nitrogen per functional unit with the same potential nitrifying effect. Fossil fuel d epletion This impact addresses only the depletion aspect of fossil fuel extraction, not the fact that the extraction itself may generate impacts. Extraction impacts, such as methane emissions from coal mining, are addressed in other impacts, such as global warming. The characterization factor of the fossil fuel depletion is in surplus mega joules (MJ) per functional unit of product. Habitat a lternation The land use by humans has potential impact on the habitat alternation which leads to the damage of Threatened and Endangered Species. For the life cycle of the buildings, the use and disposal/landfill stages c ontribute most on this impact. Criteria a ir p ollutants Criteria air pollutants are solid and liquid particles commonly found in the air. The coarse particle s trigger and aggravate respiratory conditions such as asthma. The fine particles can lead to more serious respiratory symptoms and disease. Disability adjusted life years, or DALYs, have been developed to measure health losses from outdoor air pollution. Human h ealth Many potential human health problems are caused by exposure to industrial and natural substances. Some substances have a wide range of different effects, and different individuals have widely varying toler ances to different substances. Smo g formation p otential At certain climatic conditions, air emissions from industry and transportation can be trapped at ground level, where they react with sunlight to produce photochemical smog. One of the component s of smog is ozone, which is produced t hrough the interactions of volatile organic compounds (VOC) and oxides of nitrogen (NOX). Smog leads to harmful impacts on human health and vegetation. Nitrogen oxide is the reference substance used in smog formation potential.

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37 Ecological toxicity The ec ological toxicity impact measures the potential of a chemical released into the environment to harm terrestrial and aquatic ecosystems. The pollutant concentrations from industrial sources as well as the potential of these pollutants to harm ecosystems ar e measured. The reference substance is 2, 4dichlorophenoxy acetic acid (2, 4 -D). Classification At this step, results from life cycle inventory (LCI) analysis are assigned to the specific impact categories. For example, CFC -11emission is classified into the ozone depletion impact and CO2 is classified into the global warming impact. For LCI inputs and outputs which contribute to more than two categories, a representative portion of the LCI results are distributed to the impact categories they contrib ute. Characterization There are several chemicals from LCI results in each specific category. In order to put different kinds and quantities of chemicals on an equal scale to determine the impact of each one, the concept of category indicator is introduced. It allows inventory inputs and outputs to be calculated into the same characterization equivalents, so c omparison and calculation can be made. All the inventory data in the impact category are converted into a single numerical category indicator result with a science based conversion factor, called characterization factor. It is important to choose the appropriate characterization factor for the impact category. For example, all the green gas emissions are converted into the equivalent CO2 emission amount which is the category indicator of global warming potential. Thus the total contribution of this product on global warming can be calculated. Normalization After characterizing each impact category, the categories are measured in one commensurate unit, e.g. global warming is expressed in carbon

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38 dioxide equivalents and ozone depletion in CFC 11 equivalents. The purpose of the normalization is to get each indicator result on the same scale and prepare for additional procedures, such as grouping, weighting or life cycle interpretation. The normalized data can only be compared within a category. This procedure normalizes the category indicator by dividing it by a selected reference value. The reference value can be set as the total emissions or resource use for a given area, which may be global, regional, or local; or the total emissions or resource use for a gi ven area on a per capita basis. Grouping. Grouping assigns impact categories into sets of specific areas of concern as defined in the goal and scope definition. Sorting and/or ranking may be involved in the grouping stage. There are two ways for grouping LCIA data: Sort the indicators by characteristics, such as emissions, resources or locations; sort the indicators by ranking them in a given hierarchy, e.g. high, medium and low priority. Ranking is based on value choices. Weighting. Although the weighting procedure is widely used in LCA, it is the most disputed and challenged on choosing the weight factor for each impact category, because it is based on value-choices rather than based on natural science. But because it simplifies the LCA final results and r eflects the stakeholders choice value, it is also a popular step to be taken. The weighting step assigns weights to the impact categories based on their perceived importance or relevance. Different individuals or organizations may have different preferences which result in different weighting factors and results.

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39 Table 2 3 indicates a comparison between various impact assessment methods included in SimaPro (Mark Goedkoop, 2008) Impact 2002+ is the method used for assessing the environmental performance of HVAC alternative since it comes out with only four damage categories and a weighting scheme which can facilitate the result and represent the preference of decision-makers. Table 2 3 Comparison of impact assessment method s in SimaPr o Name Data source Impact/damag e categories Characterizatio n Normalizatio n Normalizatio n Impact 2002+ Swiss 14 midpoint categories into 4 damage categories Characterizatio n factors are adapted from existing characterizing methods, i.e. Eco -indicator 99, CML 2001, impact 2002, etc. Yes Yes, self determined weighting factor or a default weighting factor of one TRACI 2 U.S. EPA 9 impact categories Impact categories are characterized at the midpoint level No No BEES 4.0 U.S., building materials 6 impact categories SETAC method No No CML 2001 Europea n 9 impact categories Baseline indicators Yes Yes Eco indicato r 99 Swiss 3 damage categories Resource analysis, land use analysis, fate analysis and exposure effect analysis Yes Yes Interpretation. Interpretation is the last phase of life cycle assessment. Life cycle interpretation step contains three key elements, as described in ISO 4042: identify the significant issues based on the results of the LCI and LCIA; evaluate the completeness,

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40 sensitivity, and consistency of the data; draw conclusions, recommend ations and reporting Completeness check. The completeness check ensures all relevant information and data needed for interpretation are available and complete. A checklist should be formed to indicate each main area of the results and verify that data are consistent with the system boundaries and reflect the stated goal and scope of the LCA study. Sensitivity check The sensitivity check assesses the reliability of the final results and conclusions by determining whether the significant issues are affected by the uncertainty in the data, allocation methods or calculation of category indicator results, etc. Sensitivity checks can be performed by conducting data quality analysis for the significant issues. Data quality analysis distinguish es the significan ce, difference and sensitivity of the indicator results It compri ses three evaluation techniques Gravity analysis. Gravity analysis identifies data which has the greatest contribution to the indicator results. These items may then be investigated with increased priority. Uncertainty a nalysis Uncertainty analysis describes the statistically variability in order to determine if indicator results from the same impact category are significantly different from each other. Consistency c heck. Consistency check determines whether the assumptions, me thods and data are consistent with the goal and scope. A checklist should be developed to indicate the inconsistency of the study. Some inconsistency may be acceptable depending on the goal and scope of the LCA Recent r esearch of a pplying LCA to HVAC systems There are several papers of apply life cycle assessment into HVAC related systems (Prek, 2004) (Avat Osman, 2007) Shah, Debella and Ries conducted a life cycle assessment on three types of heating and cooling systems (warm air furnace with air conditioning, hot water boiler with air conditioning and an air air heat pump) over a 35year study period in four regions (Minnesota, Oregon, Pennsylvania and Texas ) (Shah V.P., 2008) The LCA software SimaPro 7 was used to analyze the systems in

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41 this study. In SimaPro, the Franklin USA 98 and ETH -ESU 96 databases are introduced for life cycle inventory (LCI). The Impact 2002+ method is applied to the life cycle impact a ssessment. It links the results of the inventory to four damage categories: human health, climate change, ecosystem quality and resources, via 14 impact categories. The scores calculated in the damage categories are further normalized based on the overal l impacts to one person in 1 year in Western Europe and thus make these damage categories comparable to each other. Results are divided into two categories : the impacts due to the system infrastructure and the impacts for the energy use during the operation time. The boiler and air conditioning system ha d the highest impact on all four damage categories due to the large use of metals, which includes the use of copper pipes and steel radiators for the boiler system and steel duct for the AC system. The h eat pump has the least impact on the environment because it is a single appliance us ed for both heating and cooling. For analyzing life cycle impacts of operational energy use, four energy midpoint categories in Impact 2002+ are picked, including respiratory inorganics (SOx and NOx from natural gas for the furnace and boiler systems or coal generated electricity for the heat pump), aquatic ecotoxicity (oil emis sions during natural gas manufacturing and dispersion of metallic ions during the manufacturing of equipment ), global warming (fossil fuels extraction and combustion), and non -renewable energy (fossil fuels extraction and combustion). Thus boiler and furn ace systems have higher impacts. In this study, it also shows that the energy mix and the climate of different states play a significant role in determining the environmental performance of these three systems Oregon has the least environmental impact bec ause its large percentage of hydropower and other renewable sources for

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42 electricity production (67%) and the least annual heating and cooling load. The heat pump has the highest impacts in the regions where fossil fuel provides the large percentage of the energy mix for electricity. In these states, the furnace and air conditioning is the best system to use. However, the heat pump shows least environmental impact in Oregon, where a large share of electricity is generated from hydropower and other renewabl e sources. So the fuel energy mix for electricity and the region s climate are two important factors which play significant impact on the environment. Mikko and Carey compared the LCA performance of two different ventilation units with air -to air energy exchangers and electrical resistance heating in a cold climate in Finlan d (Mikko Nyman, 2005) Both of the systems provide the same outdoor ventilation airflow at 50 l/s, but are different in sizes, energy effectiveness for the energy exchanger and frost control strategies, etc The function al unit included in the study was only to provide outdoor air, not to condition the air. Unit 1 had two plate energy exchangers in series with an effectiveness of 69%, and unit 2 had onl y one exchanger and an effectiveness of 58%. Unit 1 consumed 3W/l/s electricity while unit 2 consumed 2W/l/s. The article did not consider much on the allocation methods in the production phases because the differences in allocation methods had a marginal effect on the study since the environmental impacts associated with the use of the ventilation units are at least an order of magnitude greater than those associated with production. Analysis show ed that non-renewable energy represented the main portion of energy for production. The steel and aluminum in the system required the most energy since steel

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43 contributes 61% 66% of the material and 26% 27% of energy use and aluminum requires 9% -13% of the material and 20% 27% of the energy use. Since an air conditioning function is not considered but only the ventilation function is considered in this study, energy consumption by the fan was the only source for consumption. Results show ed that the annual energy consumed in the operation period is four times hig her than the energy consumed during the production phase. The emissions during the 50 year operation period are 100-200 times greater than the results from production and transportation. Energy savings by the energy exchanger is five times as much as the energy consumed by the fan. Although there are two plate exchangers in series and higher electricity consumption of the fan for unit 1, the analysis shows greater reduction in emissions due to higher heat energy recovery effectiveness. Thus the energy reco very effectiveness has a larger impact on the environmental performance of the unit compared with the material amount for the unit. Katarina evaluated the environmental performance of two air -conditioning system s for a office building in Sweden using a weighting method for LCA study which leads to a single score of the selected phase (production, use, and disposal) (K. H. 2004) The two AC systems include System A: an all air air handling unit (AHU) with a cooling coil and a vapor compression chiller; System B: an all air desiccant cooling air handling unit. The functional unit of this study is an air handling unit which generates a constant air volume (CAV) at 4.8 m3/s 24 h/day for 15 years. The filter is changed once every y ear, and the annual leakage of the refrigerant is 2% of the refrigerant charge. EPS Design System 4.0 was applied for the inventory data base for the systems. The paper did not state which impact assessment method was used; however, the

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44 weighting method used in this paper is the EPS 2000 default method, which was developed in Sweden. Results show that System B with the desiccant cooling AHU had a greater environmental impact than System A with the chilled water AHU through the entire life of the system b ecause of the large amount quantity of copper in the system (highest ELU/kg). The consumption of other materials and sources in the production phase was negligible compared with copper and steel. The usage phase of the life cycle of both units still played a significant critical part of the overall impact compared with the production and disposal phase of the systems. The reason why system B has the greater impact is because of its higher pressure loss caused by extra components (desiccant rotor, evaporati ve coolers, and regeneration heating coil); higher energy consumption during the use phase due to its higher SFP (specific fan power, kW/ (m3/s)). The end phase of both systems has positive effects on the environment since 90% of the metals were recycled. The impact of the filter materials (mostly sheet steel and rock wool) was negligible. Katarina also evaluated the environmental performance of a borehole based, ground loop heat pump system for cooling compared with a traditional air -conditioning coolin g system with a chiller (K. H. 2008) The functional unit is the air conditioning system which conditions and distributes a variable air flow volume (VAV) of a maximum 5m3/s. Results show that the bolehole heat pump had bet ter environmental performance in three of four impact categories: global warming, acidification, and eutrophication. This is mainly due to the fewer materials used in its production and less operating energy

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45 use for the bore-hole heat pump system. In the category of photochemical ozone creation potential (POCP), the bole-hole heat pump system performed 4 times worse than the traditional air -conditioning system. This is primarily because the use of the polyethylene for the bole hole pipes. However, the ov erall environmental impact of the bore -hole based system is 10% better than the tradition system. Since the electricity use in the building is pretty low (6.28 kW/m2) due to the VAV system control and low supply temperature (15C), the production phase contributed to the most (70%) to the overall impact. The impact related to energy use is around 20% less for bore-hole based system than for the traditional air -conditioning system. Since 95% of metals are recycled, the environmental impact of the end of lif e phase was positive. For further discussion about the influence of weighting methods on the results, different weighting methods are compared in this study for evaluating the same inventory data. LCI data were weighted with five methods: EPS, Ecoscarc ity -Ch, Ecoscarcity S, Effect category and the Tellus method. Results are normalized with respect to the environmental impact of the traditional system, which is equal to 1. The results shows that bore-hole based system has 30% lower environmental impact Although the weighting methods are based on different value principles the results are very similar. Economic Performance Besides environmental impact of building products, economic benefits are also important factors for consumers and manufactures in mak ing a decision. A poll conducted by the American Institute of Architects in 2006 showed that 90 % of U.S. consumers would be willing to pay more to reduce their homes environmental impact, but they would pay only $4000 to $5000, or about 2 %, more (Barbara C. Lippiatt,

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46 2008) Even the most environmentally conscious building product manufacturer or designer will ultimately weigh environmental benefits against economic costs. The most popular method for analyzing the econom ic performance is life cycle cost analysis. Life cycle cost is an economic evaluation of the total cost of purchasing, operating, maintaining, and disposing/recycling of a system during a period of time. Whether a HVAC system is cost effective through its useful life time depends on equipment price and installation cost (first cost), operating cost and maintenance cost. Life Cycle Cost (LCC) analysis utilizes initial cost, operating cost, maintenance cost, replacement cost, disposal cost, salvage, other p eriodic costs and take into account the time value of money (C.Lippiatt, 2007) Initial Cost The initial cost of HVAC systems includes the cost for cooling equipment, heating equipment, cooling and heating distribution equipmen t, air handling and distribution equipment, controls, design, construction, energy and fuel services, mechanical room, electrical service cost, fuel service cost and associated overhead costs. Operating Costs The electricity and other fuel energy usage costs are the main costs during the operation period. Most of the electricity and fuel energy cost are from HVAC equipment. The energy consumption is calculated by conducting an annual energy use calculation of t he HVAC system. The electrical energy cost is a combination of several costs: energy consumption charges, fuel adjustment charges, demand charges, special allowances or other adjustments. In order to reduce peak time electricity usage, some utilities may provide

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47 different rates (onpeak and off -peak) for electricity consumption according to the time of use and season. Fuel adjustment cost may be charged by electricity companies due to the variations in fuel prices. Although the fuel adjustment charge varie s, there will be an average annual or seasonal estimate calculated by the utility. Special allowances may be applicable for customers who can receive power at higher voltages or those who can use renewable energy for electricity production. Demand charge i s based on the customers peak kW demand usage. The demand charge is considered important when load shifting or shedding devices are considered. Natural gas cost is calculated either by volume or by energy content (therm). The cost per therm/volume is a combination of the utility rate for gas consumption and the PGA (purchased gas adjustment), plus taxes and other adjustments. Maintenance and Repair Costs Maintenance and repair cost include the cost for materials and labors. The maintenance cost may be required on a 6month basis or a yearly basis. The repair cost varies with the situation. Study Period The study period may greatly affect the results of LCC analysis. The length of the study period depends on the specific goal of the analysis. In general, the study period can be defined as the length of the ownership. Interest and Discount Rate The discount factors used in this dissertation are based on FEMP (Federal Energy Management Program). All of the updated discount factors for calculation can be found

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48 in the supplemental of LCC handbook 135 developed by DOE (Building and Fire Research Laboratory, Office of applied Economics, 2009) Other Periodic Costs Periodic costs include insurance, property taxes, income taxes, refurbishment, or disposal fee (refrigerant recycling cost) and decommissioning expenses. Building Life Cycle -Cost (BLCC) Software Developed by National Institute of Standard and Technology (NIST), Building Life Cycle Cost (BLCC) software is a tool to evalua te the economic performance of building systems. It contains the latest energy escalating rate updated every year. This dissertation will use BLCC 5.3 to facilitate the economic analysis (Federal Energy Management Program, 2009) Green Building Rating System: LEED LEED (Leadership in Energy & Environmental Design) is a foremost and internationally recognized green building rating system developed by USGBC (U.S. Green Building Council) LEED promotes design, construction and op eration practices that economically and sustainably lessen the negative impact s of building on their occupants and on the environment USGBC is a non-profit organization founded in 1993. It is a collect ion of architects, public policy makers, and designers who provide third-party verification that a building was designed and built in order to save energy and materials, reduce water use and CO2 emissions and improve indoor environmental quality. The growth of USGBC membership is very fast It now ha s 78 local affiliates, more than 20,000 member companies and m ore than 10,000 LEED Accredited Professionals (U.S. Green Building Council) in 41 countries Architects, engineers, realtors, designers, construction managers, lend ers, and government officials all

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49 consider LEED as a tool to make building sustainability. Its now becoming a more important and popular criterion for b uilding industry to consider. USGBC has four levels of LEED: Certified, Silver, Gold and Platinum. The level of LEED you can reach depends on the total points achieved for each category of LEED. LEED has rating systems for both commercial and residential buildings including: New Construction, Existing Buildings, Homes, Schools, Healthcare, Retail, Commerci al Interior, and Core& Shell. But most of the buildings fall under the umbrella of LEED -NC (New Construction). The latest version of LEED called LEED v3 was launched on April 27, 2009. This study will use the criteria in LEED -NC v3 as the criteria for eval uating the performance of HVAC systems (U.S. Green Building Council, 2009) LEED -NC v3 has 7 categories: Sustainable Sites, Water Efficiency, Energy & Atmosphere, Material & Resources, Indoor Environmental Quality, Innovation in Design and Regional Priority. It has 100 base points in total. There also have 6 possible points in Innovation in Design and 4 points in Regional Priority. The categories that relate the most to the HVAC systems is the Energy and Atmosphere category Energy and Atmosphere (EA) Energy and Atmosphere yield the most possible points among these categories (35 /100 points). EA Prerequisite 2: Minimum Energy Performance One of the EA prerequisites is to perform a whole building energy simulation. It requi res demonstrating a 10% improvement in the proposed building performance rating for new buildings and 5% improvement for major renovations to existing buildings compared with the baseline. T he baseline building performance rating is calculated according to the building

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50 performance rating method in Appendix G of ASHRAE/ESNA Standard 90.1-2007 using a computer simulation model for the whole building project. EA Prerequisite 3: Fundamental Refrigerant Management It is a mandatory prerequisite by LEED that there should be no CFC refrigerants used in new construction or a phaseout plan for renovation of existing buildings with CFC refrigerants. EA Credit 1: Optimize Energy Performance A percentage improvement is demonstrated in the proposed building performance rating compared with the baseline building performance rating calculated according to Appendix G of ASHRAE/IESNA standard 90.1-2007 using a computer simulation model for the whole building project. The energy cost savings percentage threshold i s shown in Table 2 4 (U.S. Green Building Council, 2009) Table 2 4 LEED 2009 energy performance score card New Buildings Existing Building Renovations Points 12% 8% 1 14% 10% 2 1 6 % 12% 3 20% 16% 5 24% 20% 7 28% 24% 9 32% 28% 11 36% 32% 13 40% 36% 15 44% 40% 17 48% 44% 19 EA Credit 4: Enhanced Refrigerant Management Refrigerant in chillers may have environmental issues on ozone depletion potential (ODP) and global warming potential (GWP). EA credit 4 can be earned by any of the two options: O ption1 do not

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51 use ANY refrigerants or Option 2 use refrigerants and HVAC that minimizes or eliminates emission of compounds that cause ozone depletion & global warming.

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52 CHAPTER 3 PERFORMANCE ASSESSMENT MODELS Technical Model Effectiveness kW/ton Rating. One of the most common efficiency factors to evaluate the effectiveness of the co oling equipment (mostly chillers) is kW/ton. It is expressed as the power input to compressor motor divided by tons of cooling produced. The lower kW/ton indicates the higher efficiency of the equipment. Coefficient of Performance (COP) = ( ) ( ) (3 1) Integrated Part Load Value (I PLV) It measures the efficiency of equipment (in kW/ton) under full load and part load conditions -that is, when the unit is operating at 25%, 50%, 75% and 100% of capacity and at different temperatures Energy Efficiency Ratio (EER) = ( ) ( ) (3 2) = 3 412 (3 -3) Heating Seasonal Performance Factor (HSPF): = ( ) ( ) (3 -4) Maintainability Maintainability is the ease, accuracy, safety, and economy of maintenance. Since the cost of maintenance is considered in th e economic performance section, maintainability only refers to the ease in which maintenance actions can be performed.

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53 According to 1999 ASHRAE Application Handbook: HVAC Applications (ASHRAE, 1999) the value of maintainability is calculated as following: = 1 ( / ) (3 -5) B: the time that the system is being repaired in regular occupancy Y: the time that the system is operated in one year Reliability Reliability is the probability that a system will perform its function without failure for a specific period of time when used under specific conditions. For multiple integrated systems, the combined reliability can be calculated as following: If the system s are arranged in series, the combined reliability is = (3 -6) If the systems are arranged in parallel, the combined reliability is = 1 ( 1 ) ( 1 ) ( 1 ) (3 7) Spatial Requirement For a central system, the equipment room is normally needed which is located outside of the conditioned area. The additional cost should be considered to install secondary equipment for the air/water distribution. The performance of the spatial requirement of equipment depends on the real area it takes. The s maller area of the equipment room is the better the spatial requirement will be

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54 Environmental Model: Life Cycle Assessment Goal and Scope Generally speaking, the functional unit of analysis is the HVAC system which can satisfy the cooling or heating load of the buil ding and sustain comfort indoor environment. I nventory Analysis There are several data base embedded in SimaPro. Most of the dat a base is European, only a few are based on data from the United States (e.g. Franklin USA 98). The order from choosing these data input is: USA data has the priority compared with the European data and newer data has the priority compared with the older data. Impact Assessment The i mpact 2002+ is the life cycle impact assessment method for this study. It links the life cycle inventory results via 14 midpoint categories to four damage categories. All midpoint scores are expressed in units of a reference substance and related to four damage categories human health, ecosystem quality, climate change and resources. Normalization was performed at damage level rather than midpoint level (Oele, 2006) C haracterization Table 3 -1 lists the number of LCI results covered, damage categories, and reference substances used in the Impact 2002+ (O.Jolliet, 2003) Damage Categories. Damage characterization factors of any substance can be obtained by multiplying the midpoint characterization potentials with the damage ch aracterization factors of the reference substances shown in Table 3-2. Normalization In order to facilitate interpretation, the normalization of the damage categories was performed. The normalization factor was determined by the ratio of the impact per unit of emission divided by the total impact of all substances of

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55 the specific category for which characterization factors exist, per person per year. Table 3 -3 shows the normalization factors for the four damage categories for western Europe (Jolliet et al ). Table 3 1 Characterization and grouping into damage category in Impact 2002+ Midpoint categories Damage category Midpoint reference substance Carcinogens Human health kg eq chloroethylene into air Non carcinogens Human health kg eq chloroethylene into air Respiratory inorganics Human health kg eq PM2.5 into air Ozone layer Human health kg eq CFC 11into air Radiation Human health Bq eq carbon 14 into air Respiratory organics Human health, Ecosystem quality kg eq ethylene into air Aquatic ecotoxicity Ecosystem quality PDF m 2 yr/ kg triethylene glycol Terrestrial ecotoxicity Ecosystem quality PDF m 2 yr/ kg triethylene glycol Terrestrial acidification/nutr. Ecosystem quality PDF m 2 yr/ kg SO 2 Land occupation Ecosystem quality m 2 eq organic arable land year Global Warming Climate change kg eq CO 2 into air Mineral extraction Resources MJ additional energy or kg eq iron (in core) Non renewable energy Resources MJ total primary non renewable or kg eq crude oil Table 3 2. Characterization damage factors of various reference substances Midpoint categories Damage factors Units Carcinogens 1.45E 6 DALY/kg chloroethylene Non carcinogens 1.45E 6 DALY/kg chloroethylene Respiratory inorganics 7.00E 4 DALY/kg PM2.5 Ozone layer 1 .05E 3 DALY/kg CFC 11 Radiation 2.10E 10 DALY/Bq carbon 14 Respiratory organics 2.13E 6 DALY/kg ethylene Aquatic ecotoxicity 8.86E 5 PDF m 2 yr/ kg triethylene glycol Terrestrial ecotoxicity 8.86E 5 PDF m 2 yr/ kg triethylene glycol Terrestrial acidification/nutr. 1.04 PDF m 2 yr/ kg SO2 Land occupation 1.09 PDF m 2 yr/ m 2 organic arable land year Global Warming 1 kg CO 2 /kg CO 2 Mineral extraction 5.10E 02 MJ/kg iron Non renewable energy 45.6 MJ/kg crude oil

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56 Table 3 3 Normalization factors for the four damage categories for Western Europe Damage categories Normalization factors Units Human health 0.0077 Daily/person/yr Ecosystem quality 4650 PDF m 2 yr/person/yr Climate change 9950 kg CO 2 /person/yr Resources 152000 MJ/person/yr Interpretation Sensitivity a nalysis Sensitivity analysis estimates the effects on the outcome of a study of a chosen method and data. Sensitivity analysis is typically conducted in the goal and scope or data collection phase. Uncertainty a nalysis Some data required in the life cycle inventor y analysis were unavailable and they are assumed based on engineering judgment Uncertainty analysis is introduced to make sure and quantify the accumulative impact of the uncertainty and data variability. Economic Model: Life Cycle Cost T here are generally two categories of economic analysis methods: present value method and payback method. Payback method measures the time required to get initial investment recovered. Simple payback method is the most popular method in this category. The most comprehensive present value method is the life cycle cost analysis (LCCA). T here are also some suppl ementary measures using the present value method including Net Savings (NS), the Savings -to -Investment Ratio (SIR), Adjusted Internal Rate of Return (AIRR). The SIR and AIRR are usually applied for ranking independent projects when faced with a budget issu e, and they are not suitable to identify the most cost effective alternative. And N et S avings method is based on the same theory with LCCA. After considering the scope and application of this study, only LCCA

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57 performance with be considered to evaluate the economic performance of HVAC systems. Simple Payback Method Simple payback method measures the time required to recover initial investment costs. It is a simple technique which does not consider the time value of m oney, inflation, and interest. = ( $ ) ( $ ) (3 -8) Present Value Method Present value method takes into consideration the time value of money, which returns all future cost s into today s dollar. The methodology is based on FEMP LCC handbook 135. Fig ure 3 1 Present value method = ( ) (3 9) LCC = ( ) (3 10) Where, PV = present value, Ct = future value, t=tim e of period, d=discount rate or interest rate, n= length of study period

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58 Discount factors. The method and discount factor used in this dissertation were based on FEMP (Federal Energy Management Program). All of th e updated discount factors for calculation can be found in the supplemental of LCC handbook 135 developed by D epartment of Energy Single Present Value Factor (SPV) Used in Replacement/Repair cost or Salvage Single Present Value factor (SPV) is used for single one time costs. This factor can be used for estimating the present worth of replacement/repair cost or salvage assuming that the future cost for replacement is constant. = ( ) (3 11) = ( ) (3 -12) Where, Ft = Future Value Uniform Present Value Factor (UPV) Used in Maintenance Cost Uniform Present Value Factor (UPV) is used for uniform annual recurring amount. In this dissert ation, present value of maintenance cost is assumed to be constant and is calculated based on uniform annual payment. = ( ) (3 -13) =( ) ( ) (3 -14) Where, A0 = Annual cost of maintenance, Modified Uniform Present Value Factor (UPV *) Used in Energy Cost Modified Uniform Present Value Factor (UPV*) is used for annually recurring nonuniform escalating amount. It is used in calculating the present value of annually recurring energy cost over years based on DOE projections = ( ) (3 15)

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59 = 1 (3 16) Where, A0 = A nnual cost of energy, e=escalation rate, n= length of study period, d=discount rate The DOE escalation rates vary according to year, region, fuel type (electricity, natural gas, Liquefied petroleum gas (LPG), distillate and residual fuel oils, and coal) an d rate type (residential, commercial and industrial). Energy Escalation Rate Calculator (EERC) is used for calculating an average annual escalation rate for fuel price based on annually updated EIA energy price forecasts (U.S. Depar tment of Commerce, 2009) If inflation is considered in calculating the PV (current dollars), the price of the equipment is based on a nominal discount rate and the price of energy is based on a nominal escalation rate; if inflation is not considered in the study (constant dollars), they are all based on a real discount and esca lation rate. Both of the approaches will yield the same present value results. For simplicity, constant dollars (excludes inflation) is considered in this study. The relationship between a real interest rate, d, and a nominal discount rate, D, is expressed as follows, = 1 (3 17) Where, I is the inflation rate. The discount and inflation rates for 2009 by DOE are: Real rate (excluding price inflation): 3.0% Nominal rate (including price inflation): 4.2%

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60 Table 3 4 Life cycle cost calculation Initial Investment Energy Maintenance Repair Replacement Salvage Year of Occurrence 0 Annually Annually At certain year End of service life End of service life Discount Factor 1 UPV*(n,d,e) UPV(n,d) SPV(n,d) SPV(n,d) SPV(n,d) Present Value PVi= initial cost PVe= A0 UPV*(n,d,e) PVm= A 0 UPV(n,d,e) PVr= Fr SPV(n,d) PVrt= Frt SPV(n,d) PVs= Fs SPV(n,d) Life Cycle Cost LCC = PVi + PVe + PVm + PVr + PVrt PVs LEED Green Building Rating System In order to earn points in Energy and Atmosphere in LEED, two prerequisites associated with HVAC systems which define the minimum energy performance and fundamental refrigerant management are required After meeting the prerequisites, more points may be earned through the following credits: Optimize Energy Performance Refer to Table 2 7 for LEED 2009 NC energy performance score card. Enhanced Refrigerant Manag e ment There are 2 points available for obtaining this credit. 2 options can be chose (U.S. Green Building Council, 2009) : OPTION 1: do not use ANY refrigerants OPTION 2: use refrigerants and HVAC that minimizes or eliminates emission of compounds that cause ozone depletion & global warming For Option 2, the refrigerants should meet the following calculation, + 10 100 (3 18) Where, = [ ( + ) ] / (3 19)

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61 = [ ( + ) ] / (3 20) L CODP = Lifecycle Ozone Depletion Potential (lbCFC11/TonYear) LCGWP = Lifecycle Direct Global Warming Potential (lbCO 2 /TonYear) ODPr = Ozone Depletion Potential of Refrigerant (0 to 0.2 lbCFC11/lbr) GWPr = Global Warming Potential of Refrigerant (0 to 12, 000 lbCO 2 /lbr) Lr = Refrigerant Leakage Rate (0.5% to 2.0%; default of 2% unless otherwise demonstrated) Mr = End of life Refrigerant Loss (2% to 10%; default of 10% unless other wised demonstrated) Rc = Refrigerant Charge (0.5 to 5 lb of refrigerant per t on of cooling capacity) Life = Equipment Life (10 years; default based on equipment type, unless otherwise demonstrated)

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62 CHAPTER 4 AHP DECISION MAKING MODEL DEVELOPMENT AHP (Analytic Hierarchy Process) is a structured and logical technique for dealing with complicated decision making problems, which helps decision makers find a solution that best suits their needs and preferences. It was developed by Thomas L. Saaty in 1 977 and has been refined and widely used in many areas of the society including business, government, defense, industry, education, etc. It is a comprehensive methodology to build a logical framework for quantifying and evaluating alternative solutions bas ed on various criteria (Satty, 1982) This dissertation utilizes AHP structure for selecting the optimal HVAC system based on the performance of alternatives as well as the preferences of the decision makers. The Structure of AHP Model The AHP model contains several layers: a goal layer, criteria layers, and an alternative layer. The criteria layer can be can be further developed into sub-criteria, sub-sub -criteria and so on, in as many levels as needed. Each box in the model i s called a node. The boxes descending from any node are called its children. The node from which child nods descend is called their parent. The first step is to form the AHP hierarchy structure including the decision goal, the criteria for evaluating the alternatives, the alternatives chosen to be evaluated. Then the importance of each criterion is established by making a series of judgments b ased on pairwise comparisons among criteria. If there is a sub-criteria layer, the importance of each sub-criterion is also determined by the pairwise comparison. The final weighting of the sub-criterion is the product of the weighting of the sub-criterion among the sub criteria under the same criterion and the weighting of the criteria. The third step is to

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63 evaluate each alternative with respect to each sub-criterion and then multipl y that evaluation by the importance of the sub-criterion. This product is summed over all the sub-criteria for the specific alternative to generate the overall score of the alternative. The alternative with the highest overall score is the best choice based on the performance of alternatives as well as the preference of the deci sion makers on the importance of the criteria. Equation 4 -1 shows it mathematically, Figure 41. The structure of analytic hierarchy process = (4 1) Where, OSi is the overall scor e of the i th alternative, PIij is the performance indicator of the i th alternative under j th sub -criteria wj is the weighting or the importance of the j th sub-criterion Figure 42 shows the hierarchy structure established for choosing the optimal HVAC s ystem. The goal layer is to choose a HVAC system which is the purpose for establishing the decisionmaking model. The criteria layer contains the four

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64 performance factors for evaluating the HVAC systems: technical requirement, economic performance, enviro nmental performance and LEED performance. These criteria are further expended into their own sub -criteria in the sub-criteria layer. Figure 42. Hierarchy structure for choosing the optimal HVAC system The technical requirement criterion contains four sub-criteria: full load effectiveness, part load effectiveness, reliability, maintainability and spatial requirement; the economic performance criterion contains only 1 sub-criterion, which is life cycle co sting; the environmental performance contains four sub -criteria: human health, ecosystem, climate change and resources; the LEED performance criterion contains 2 sub-criteria: optimized energy performance and enhanced refrigerant management. The alternati ve layer contains several HVAC alternatives consi d ered for comparison.

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65 Goal Layer The goal for this analysis is to find a HVAC system which has the optimal combined performance and also best suits the preference of decision makers. Criteria Layer The crit eria layer contains the four performance factors for evaluating the HVAC systems: technical requirement, economic performance, environmental performance and LEED performance. Pairwise comparisons are conducted between each two criteria in order to get the weighting of each criterion. Pairwise c omparison Each two criteria are compared in pair. The pairwise comparison is based on the preference of the decision maker on the criteria. In order to quantize the importance of one criterion over another, the import ance intensity is introduced as shown in Table 41. A 9 point importance scale is used to indicate the importance comparison between criteria in terms of equally importance, moderately favored, strongly favored, very strongly favored, and extremely favored. If two criteria are equally important, the importance for both of the criteria is set to be 1. If criterion A is extremely favored over criterion B, the importance of criterion A is 7 compared with criterion B and the importance of criterion B is 1/7 compared with criterion A. The number of the pairwise comparison is based on the number of criteria to be compared, = ( ) (4 -2) Where, N is the number of pairwise comparison; and n is the number of criteria to be compared.

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66 Table 4 1 Importance scale for pairwise comparison Importance Scale Details 1 Two criteria are equally important to the preference 3 One criteria is moderately favored over the other 5 One criteria is strongly favored over the other 7 One criteria is very strongly favored over the other 9 One criteria is extremely favored over the other 2,4,6,8 Intermediate values between two adjacent importance judgment Figure 43 is an example of the subjective importance judgment for comparing the criteria in pair based on the decision makers preference. Figure 43 Pairwise comparison of performance criteria

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67 The i mportance j udgment m atrix With the pairwise compari son for each two of the criteria, weightings of the criteria are calculated by the importance judgment matrix. The size of the matrix is 4 since there are four criteria in the criteria layer. Table 42 shows the importance judgment matrix in criteria layer The element Wij represents the importance comparison between the vertical criteria i and the horizontal criteria j. If Wij equals to 5, that means the vertical criteria i is very strongly important over the horizontal criteria j. If Wij equals to 1/5, that means the horizontal criteria j is very strongly important over the vertical criteria i. The element s along the diagonal equal to 1 (equally important) since the criterion is compared to itself. Notice that the matrix is reciprocal. The values in the lower triangular matrix are filled by using the reciprocal values of the upper triangular matrix. Table 4 2 Importance judgment matrix in criteria layer Criteria Technical C1 Economic C2 Environmental C3 LEED C4 Technical C1 1 Economic C2 1 Environmental C3 1 LEED C4 1 The weighting for the performance criteria i is calculated from equation 43 and 4 -4. The sum of the weightings in each layer equals to 1. The sum of the weightings for the sub-criteria under the same criteria is equal to the weighting for the criteria. = ( 1 ) = ( ) / (4 -3) The weighting of criteria is = = ( ) / ( ) / ( 4 -4)

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68 Consistency c heck Consistency ch eck is important to check cardinal transitivity of preferences of decision makers. In order to check the consistency of the subjective judgment and make sure the comparison is transitive, the consistency ratio (CR) is used. The consistency ratio is the ratio of the consistency index (CI) over the random consistency index (RI), shown in equation 4 -5. The consistency index CI is calculated by equation 4 -6. max is the maximum Eigen value of the matrix, n is the size of the matrix. Random Consistency Inde x (RI) is randomly generated from of a sample size 500 matrices. It is decided by the size of the matrix, which is shown in Table 4 3. The judgment matrix is considered consistent if CR subjective judgment is needed to be revised. = ( 0 1 ) (4 5) = (4 6) Table 4 3 Random consistency index n 1 2 3 4 5 RI 0 0 0.58 0.9 1.12 Subcriteria Layer Similar to the weighting calculation for the criteria layer, the weighting for the sub criteria under Technical requirement is also based on the pairwise importance matrix generated by the decision makers. Since life cycle costing is th e only criteria in the Environmental performance criterion, the weighting is set to 1. For the weightings of sub-criteria under environmental performance criteria, a recommended weighting structure for the damage categories is used based on Impact 2002+ in SimaPro Table

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69 4 -4 shows the recommended weightings for the four impact categories. For LEED criteria, the weightings between Optimized Energy Performance and Enhanced Refrigerant Management are calculated based on the points available in each credit. N o te that the total weighting factors for sub-criteria in the sub -criteria layer should be multiplied by the weighting of the criteria under which the sub-criteria locate. The sum of the total weightings for all sub-criteria is 1. Table 4 4. Weightings of damage categories in Impact 2002+ Environmental factors Human health Climate change Resources Ecosystem quality Weighting 30.1% 35.2% 32.6% 2.1% Alternative Layer To avoid the addition of performance values in different units, the performance Indicator (PI) is introduced to evaluate the performance of alternatives. The performance indicator (PI) is a unitless number, in a range from1 to 9, indicating how good the p erformance of an alternative is among general candidates in the same performance category. The higher performance indicator means a better performance. For LEED criteria the maximum and minimum performance value s are known and listed in Table 4 -5. PI corr elate d to the maximum value is equal to 9 and PI correlated to th e minimum value is equal to 1. All t he other values between the maximum and min imum values can be interpolated into a certain PI by using equation 412. PVmax means the maximum performance value. PImin means the minimum performance indicator. Similar to the situ ation for LEED criteria, the conversion of performance values corresponded with the performance indicators for sub-criteria under technical criteria is

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70 also listed in Table 4-6. The max imum performance value is 4 which is corresponded to PI=9. The minimum performance value is 1 and it is corresponded to PI=1. The values in between is calculated based on equation 412. Table 4 5 C onversions of performance values into PIs for LEED perfor mance Sub-criteria PVmax PImax PVm in PIm in Optimized energy performance 19 9 0 1 Enhanced refrigeration management 1 9 0 1 Table 4 6 Conversions of performance values into PIs for technical performance Technical performance poor fair good excellent Performance values 1 2 3 4 Performance indicators 1 3.67 6.33 9 For environmental and economical criteria, the maximum value and minimum value are unknown. The major categories of HVAC systems in these two criteria are distribut ed in certain range. The probability of HVAC system s with extremely good or extremely bad economical performance and environmental performance are very small. This kind of data distr ibution follows the pattern of normal distribution. Since there is no enough resources and time to collect a data base big enough it is assumed that the economical performance and environmental performance results fall into the normal distribution. The confidence interval is used to define the boundary values of the general perf ormance. expectation an d it is shown in equation 4 deviation and it is calculated by equation 48. For normal distribution, 68.2% of the set

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71 9 5.4% of the data set falls into the interval with two standard deviations from the Th e confidence interval with 99.73% data covered is used to set the performance boundary limit and it can be calculated by equation 49 = (4 -7 ) The arithmetic mean of the performance values of alternatives in interest xiThe performance value for an alternative under a sub-criterion n The number of the alternatives in interest = ( ) (4 8 ) Where, standard deviation = 3 (4 9 ) Where, CI Confidence interval Figure 4 4 shows the correlation between the PI values and standard normal =1. The f irst row in the table is the z value of th e standard normal distribution. The s econd row is the PI corresponding to the z value. The third row is the probability between two PI values. Standard normal 3 2.25 1.50 0.75 0 0.75 1.5 2.25 3 PI 1 2 3 4 5 6 7 8 9 54.7% 86.6% 97.6% 99.7% Figure 4 4 Correlation between PI and standard normal distribution

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72 Because of the small sample size it is hard to calculate the expectation and deviation size of population. Thus the mean value of the observations and standard deviation of sample is used as the estimate value of and So is the mean value of the performance values of alternatives in interest und er a specific sub -criterion. The upper limit of the confidence interval correspond s to indicator 9 which indicates the best performance and the lower limit of the confidence interval is corresponded to 1 which defines the worst performance And the boundary conversion to PI can be found in equation 4-10 and 4-11 Other values between the maximum and minimum CI values can be interpolated into a certain PI by using equation 4-12. For software development in the future, with a comprehensive larger datab ase, a fully developed system would have the ability to calculate the PI values of candidate systems. = + 3 = 9 (4 -1 0 ) = 3 = 1 (4 -1 1 ) = = 9 ( 9 1 )( ) ( ) (4 -1 2 )

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73 CHAPTER 5 CASE STUDY Background B uilding and Location Description The building is a 6 story office building located in Atlanta, Georgia The gross area of the building is 145,583 square feet. Table 51 shows the weather data in Atlanta and building information as the basis for building energy simulation The purpose is to choose the optimum cooling system which has the best integrated perfo rmance in technical, economic, environmental and LEED aspect, as well as the preference of the owners or decisionmakers. The heating systems are identical in all alternative cases. There are 3 Proposed Cases or alternative systems/plants chosen for the ca se study. The baseline case is used as basis to calculate the energy cost savings of alternatives for LEED Energy and Atmosphere Credit. The Baseline Case is designed to meet the requirement of ASHRAE 90.12004. The Proposed Cases improve the building enve lope and have CO2 sensors in each room The building information and schedules for all three alternatives are identical. Table 5 2 shows the energy mix of electricity in Georgia for calculating the environmental contribution of the electricity consumption for both Baseline Case and the Proposed Cases. Table 5 3 shows the rate structure for electricity consumption, electricity demand and water charge. Alternative Systems Description There are 3 alternatives chosen for the building in the case study. Alternative 1 is a self -contained parallel fan powered VAV (PFP) system with dedicated outdoor air system located on each floor. Alternative 2 is a water source heat pump with series fan-

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74 powered VAV system with dedicated outdoor air system. Alternative 3 is an ai r -cooled chiller with constant volume fan coil units system. The system in the Baseline Case is a water -cooled chiller VAV system designed based on ASHRAE 90.12004 Appendix G. Table 5 4 shows the performance parameter for each alternatives and baseline c ase. Table 5 1 Weather and building information Weather Data Summer design dry bulb (F) 96 Summer design wet bulb (F) 73 Winter design dry bulb (F) 22 Building Information Floor Area (Gross Area =145,583 sf) 1st Floor (sf) 23883 2nd-6th Floor (sf/floor) 24162 Elevator machine room (sf) 900 Baseline ASHRAE 90.1 2 004 Case Proposed Cases Building Envelope Wall U value (Btu/hr -sq ft F) 0.124 0.065 Roof U value (Btu/hr -sq ft F) 0.063 0.0425 Slab U value (Btu/hr -sq ft F) 0.052 0.213 Window U value (Btu/hr -sq ft F) 0.57 0.27 Window shading coefficient 0.291 0.29 Internal load (people, equipment, lighting) Identical Thermostat (dry bulb, relative humidity, driftpoint, CO2 sensors) Same except CO2 sensors. No CO2 sensors in the Baseline case Airflow (supply, ventilation, infiltration, exhaust, VAV minimum) Identical ventilation rate is designed based on ASHRAE 62.1 2004/2007 Table 5 2 The energy mixes of electricity generation in Georgia Coal Nuclear Natural gas Oil Hydro Non Hydro renewables and others Percentage 62.5% 23.1% 9.3% 0.6% 1.9% 2.6%

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75 Table 5 3 Rate structure and water charge Electricity Demand Charge For the first 30kW of billing demand per month No Charge For all over 30kW of billing demand per month $3.19 per kW Energy Charge For the first 125 kWh per kW billing demand per month For the first 3000 kWh per month 9.78 cents per kWh For the next 87000 kWh per month 5.43 cents per kWh For all over 90000 kWh per month 4.14 cents per kWh For the next 275 kWh per kW billing demand per month For the first 6000 kWh per month 5.55 cents per kWh For the next 134000 kWh per month 5.44 cents per kWh For all over 140000 kWh per month 5.07 cents per kWh For all over 400 kWh per kW billing demand per month For all kWh per month 4.84 cents per kWh Water Charge $6.61765 per 1000 gallons Performance Results LEED Performance Energy s imulation r esults To evaluate the performance of alternatives in Energy and Atmosphere Credit of LEED, the energy cost savings for each alternative based on the Baseline Case is calculated using Trace 700 (TRANE, 2005) The whole energy simulation report is available in Appendix of the dissertation. Figure 51 shows monthl y HVAC energy consumption of alternatives. To notice that Alternative 2 is set to be the Baseline Case in Trace and Alternative 3 and Alternative 4 are water -source VAV and air -cooled chiller fan coil unit accordingly. The HVAC energy consumption of the Ba seline Case dominates during the heating season since the large amount of heating energy consumption. This is mainly because of the high U value of the building envelope. The

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76 self -contained parallel fan powered VAV system has the lowest energy consumption during the cooling season. Table 5 4 Performance parameters for alternative and baseline systems System and plant type Plant energy rate (kW/ton) System fan full load energy rate (kW/cfm) Primary Secondary Alternative 1 Self -contained unit + parallel fan powered VAV + dedicated OA 0. 77 0.000668 0.00032 Alternative 2 Water source heat pump + series fan powered VAV + dedicated OA 0.86 0.000668 0.000332 Alternative 3 Air -cooled chiller + constant volume fan coil units 1.00 0.000668 0.000332 Baseline ASHRAE 90.1 2004 Water -cooled chiller + VAV with reheat 0.7 2 0.001025 0.00035 Figure 52 shows the energy consumption summary for the Proposed Cases and the Baseline Case. The Baseline Case has the highest electricity consumption due to its high primary heating and auxiliary (supply fans and pumps) energy consumption. Alternative 1 has the lowest energy consumption. Alternative 3 has the highest energy consumption among all three alternatives mostly because of its highest supply fans and pump s energy consumption due to the use of constant volume fan coil unit. To calculate the energy cost of the ASHRAE 90.12004 baseline case, LEED and table G3.1 No.5(a) of ASHRAE Standard 90.12004 require the baseline building performance generated by averaging the simulating results of the building with its actual

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77 orientation and again after rotating the entire building 90, 180, 270 degrees. Table 55 shows the energy cost performance ratings for the Baseline Case by rotating the building into four directions. The average energy cost for the Baseline ASHRAE90.12004 is $183,445. Figure 51. Monthly HVAC energy consumption of alternatives Figure 53 shows the energy cost savings of alternatives compared to the Baseline Case ASHRAE 90.1. Table 5 6 shows the points earned in EAc1Enhanced Energy Performance of LEED -NC for each alternative based on the energy cost savings. Alternative 1 achiev es 16.1% of energy cost savings compared to the Baseline Case, which corresponds to 3 points earned in EAc1. Alternative 2 achieves 13.6% of energy

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78 Figure 52. Annual energy consumption for alternatives and baseline Table 5 5 Performance energy cost rating for baseline case : ASHRAE 90.1 -2004 0 500000 1000000 1500000 2000000 2500000 3000000 Baseline Alternative 1 Alternative 2 Alternative 3 Electricity Consumption (kW ) Primary heating Primary cooling Auxiliary Lighting Receptacle Total Space Heating Space Cooling Total Building Cost ($ /yr ) Energy (10^6 Btu/yr) Peak (kBtuh) Energy (10^6 Btu/yr) Peak (kBtuh) 0 Rotation 1,372.3 1,522 1,221.2 852 178,190 90 Rotation 1345.61 1497.7 1246.65 695.07 184,993 180 Rotation 1,372.2 1,520 1,257.4 685 185,581 270 Rotation 1346.36 1496.28 1246.64 695.48 185,017 Average 1,359.1 1,509 1,243.0 732 183,445

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79 Figure 53. Energy cost savings of alternatives compared with baseline 90.1 Table 5 6 Energy cost savings and earned points in EAc1, LEED -NC Baseline Case (Water -cooled chiller VAV System) Alternative 1 (Self -contained PFP VAV system) Alternative 2 (Water source HP VAV system) Alternative 3 (Air-cooled chiller fan coil unit system) Total building consumption (10^6 Btu/yr) ) 9320 7677 7931.4 8456.4 Total building cost per year ($/year) 183, 462 153, 993 158, 601 168, 333 Percentage of savings compared to the Baseline Case 16.1% 13.6 % 8.2 % Points achievable in EAc1 LEED NC 3 1 0 130 140 150 160 170 180 190 Baseline ASHRAE 90.1 Alt. 1 (Self contained PFP VAV system) Alt. 2 (Water source HP VAV system) Alt. 3 (Air cooled chiller fan coil unit system) $183,462/yr $153,993/yr, 13.6% savings $158,601/yr, 13.6% savings $168,333/yr, 8.2% savings Thousands dollars Total building cost ($/yr)

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80 cost saving and earns 1 point in EAc1. Alternative 3 achieves 8.2% of energy cost saving but since it has not exceed the minimum of energy cost savings (12%) required by LEED, no points is earned to Alternative 3. EAc4 Enhanced r efrigerant m anagement Table 5 7 shows the global warming potential and ozone depletion potential of refrigerants for three alternatives. In order to earn this refrigerant credit in LEED, the GWP and ODP contributions of alternatives should meet the following threshold required by LEED, LCGWP + LCODP 10 100 Where = [ ( + ) ] / = [ ( + ) ] / LCODP = Lifecycle Ozone Depletion Potential (lbCFC11/TonYear) LCGWP = Lifecycle Direct Global Warming Potential (lbCO2/TonYear) ODPr = Ozone Depletion Potential of Refrigerant (lbCFC11/lbr) GWPr = Global Warming Potential of Refrigerant (lbCO2/lbr) Lr = Refrigerant Leakage Rate=2% Mr = End of life Refrigerant Loss =10% Rc = Refrigerant Charge (lbs/ ton of cooling capacit y) Life = Equipment Life Alternative 1 and 2 meet the requirement and can earn 1 point in LEED. Since Alternative 3 excess the maximum threshold required by LEED, no point is earned. Table 5 8 summarizes the LEED performance for three alternatives. Altern ative 1 Self -contained unit + parallel fan powered VAV + dedicated OA can earn 4 points in

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81 total since its good energy cost savings by using more efficient pumps and fans. Alternative 2 Water source heat pump + series fan powered VAV + dedicated OA can ear n 2 points. There is no point earned in Alternative 3 Air -cooled chiller + VAV with reheat since it does not meet the minimum requirements in EAc4. Table 5 7 Refrigerant contributions for altern atives Alternative 1 Self -contained unit + parallel fan po wered VAV + dedicated OA Alternative 2 Water source heat pump + series fan powered VAV + dedicated OA Alternative 3 Air -cooled chiller + Fan coil units Inputs Refrigerant R 22 R 22 R 134a GWPr (lbCO 2 /lbr) 1780 1780 1320 ODPr (lbCFC11/lbr) 0.04 0.04 0 Rc (lb/ton) 0.5 0.5 2.66 Life (yrs) 20 20 20 Lr (%) 2% 2% 2% Mr (%) 10% 10% 10% Calculations Tr Total Leakage (LrLife + Mr) 40% 40% 50% LCGWP (GWPrTr Rc)/Life 22.79 22.79 102.3 LCODP1E5 (GWPrTr Rc)/Life 51.20 51.20 0 Refrigerant Atmospheric Impact=LCGWP + LCODP1E5 73.99 73.99 102.3 Points achievable in EAc4, LEED NC 1 1 0 Table 5 8 Summary of LEED performance of alternatives Alternative 1 Self -contained unit + parallel fan powered VAV + dedicated OA Alternative 2 Water source heat pump + series fan powered VAV + dedicated OA Alternative 3 Air -cooled chiller + Fan coil units Total points earned in LEED 4 2 0

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82 Economic Performance Capital c omponent s The initial costs and yearly maintenance costs of the systems are based on the catalog of Trane Company. The initial costs are $8.75/sf for Alternative 1 self -contained VAV system, $8.15/sf for Alternative 2 water source heat pump system, and $9/sf for air -cooled chiller system. The yearly maintenance cost s are $72.81/ton for Alternative 1, $81.72/ton for Alternative 2, and $70.15/ton for Alternative 3. Table 5-9 summarizes the initial and maintenance cost of alternatives. Table 5 9 Summary of initial and maintenance cost of alternatives Alt # First Cost ($/ton) First Cost ($/sf) Total First Cost ($) Maint. Cost($/ton) Maint. Cost($/ft) Total Maint. Cost ($) Total Alt. Cost ($) Alt 1 4,688.32 8.75 1,273,939 72.81 0.14 19,784 1,293,723 Alt 2 4,366.84 8.15 1,186,583 81.72 0.15 22,205 1,208,788 Alt 3 4,822.27 9.00 1,310,337 70.15 0.13 19,062 1,329,399 Utility cost Water cost Figure 5 -4 shows an nual water cost of three alternatives. The annual water cost is $6,399 for Alternative 1 self -contained VAV system since the condenser is cooled by water from the cooling tower. The annual water cost for Alternative 2 water cooled heat pump is $13,276 for the large amount use of water in the cooling tower And that for Alternative 3 air -cooled chiller fan coil system is $43 since it uses outdoor air to cool the condenser. Electricity cost Figure 5 5 and Figure 56 shows the monthly utility cost and annual operating costs of the three alternatives along with the baseline ASHRAE 90.1 Appendix G chilled water VAV system (indicated as Alternative 2 in Figure 56).

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83 Alternative 1 self -contained VAV system has the lowest yearly total operating cost ($180,177) including utility cost and maintenance cost. Alternative 2 has the highest yearly operating cost (indicated as Alternative 3 in Figure 5 6, $194,083) among three alternatives. That for Alter native 3 (indicated as Alternative 4 in Figure 56) is $187,438. The annual savings of Alternative 1 compared with Alternative 2 (indicated as Alternative 3 in Figure 5 6) is $13,906. Figure 54 Annual water cost of alternatives Figure 55 Monthl y utility cost of alternatives 0 2 4 6 8 10 12 14 Jan Feb Mar Apr May June July Aug Sept Oct Nov Dec TotalThousands dollars Alt.1 Alt.2 Annual water cost Alt.1: $6,399 Alt.2: $13,276 Alt.3: $43

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84 Figure 56 Annual Operating Cost of alternatives Life cycle cost Life cycle cost performance for each alternative is calculated by BLCC 5.3 developed by National Institute of Standard Technology (NIST). Energy escalating rate is embedded in the program and updated annually. Since BLCC 5.3 does not consider complicated rate structure but one index Price/kWh, the total annual electricity consumption (dollars) is used while set the annual kWh consumption as1. Since the wate r rate is not considered as summer and winter rates separately, the total water consumption is assigned to either summer or winter. The discount rate is set to 3%. Inflation for maintenance expense is 2%. The study periods for all the alternatives are 20 y ears. Table 5 10, 11, 12 show the results calculated from BLCC 5.3 The life cycle cost for Alternative 1 self -contained VAV system is $4, 251 937 which is the lowest among the three. The life cycle cost for A lternative 2 is $4,386,235. Alternative 3 has the

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85 highest life cycle cost which is $4,415,848. To note that the initial cost for Alternative 2 is not the lowest one, but since the operational energy consumption for the system is lower than the other two alternatives, it c ompensates the loss for initial cost and also contributes to the lowest life cycle cost among the three alternatives. Table 5 10 Life cycle cost of alternative 1 Present Value Annual Value Initial Cost $1,273,939 $85,637 Energy Consumption costs $2,525,062 $ 169,741 Energy Demand Costs $ 0 $ 0 Energy Utility Rebates $ 0 $ 0 Water Usage Costs $ 95,208 $ 6,400 Water Disposal Costs $ 0 $ 0 Annually Recurring OM &R costs $ 357,728 $ 24,047 Non Annually Recurring OM&R costs $ 0 $ 0 Replacement costs $ 0 $ 0 Less Remaining Value $ 0 $ 0 Total Life Cycle $ 4,251,937 $ 285,825 Table 5 11 Life cycle cost of alternative 2 Present Value Annual Value Initial Cost $1, 186,583 $ 79,765 Energy Consumption costs $ 2,600,621 $ 174,820 Energy Demand Costs $ 0 $ 0 Energy Utility Rebates $ 0 $ 0 Water Usage Costs $ 197.528 $ 13,278 Water Disposal Costs $ 0 $ 0 Annually Recurring OM&R costs $ 401,504 $ 26,990 Non Annually Recurring OM&R costs $ 0 $ 0 Replacement costs $ 0 $ 0 Less Remaining Value $ 0 $ 0 Total Life Cycle $ 4,386,235 $ 294,853

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86 Table 5 12 Life cycle cost of alternative 3 Present Value Annual Value Initial Cost $1, 310,337 $ 88,084 Energy Consumption costs $ 2,760,119 $ 185,547 Energy Demand Costs $ 0 $ 0 Energy Utility Rebates $ 0 $ 0 Water Usage Costs $ 640 $ 43 Water Disposal Costs $ 0 $ 0 Annually Recurring OM&R costs $ 344,673 $ 23,170 Non Annually Recurring OM&R costs $ 0 $ 0 Replacement costs $ 0 $ 0 Less Remaining Value $ 0 $ 0 Total Life Cycle $ 4,415,848 $ 296,844 Environmental Performance SimaPro 7 is the software used for evaluating the life cycle environmental performance of the three alternative HVAC systems. Impact 2002+ is the impact assessment method used in the case study. The environmental performance is mainly based on the particular ener gy mix in the region. Table 5-1 3 shows the energy mix for electricity in Atlanta, GA. The coal is the main source for electricity production in Atlanta. Because of the limited and shaded information from the manufacture on the composition of raw materials of the equipment, also with the proof of low environmental contribution of equipment production phase over the whole life cycle based on the literature, the contribution of manufacture production and disposal phase of the HVAC systems is neglected. Table 5 1 3 Energy mix for electricity in Atlanta, GA Coal (%) Nuclear (%) Natural Gas (%) Oil (%) Hydro and Nonhydro renewable and others* (%) 62.5% 23.1% 9.3% 0.6% 4.7%

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87 Figure 57 shows the environmental performance of the three alternatives. Alternative 2 water source heat pump dominates in all impact categories. Alternative 1 self -contained VAV has the lowest impact among all the impact cat egories. Figure 5 8 shows the environmental performance of alternatives in four impact categories. The weightings of impact categories are also indicated in the figure by comparing the pts among impact categories for a specific alternative. Similarly, alternative 1 self -contained VAV system has the best environmental performance among all the impact categories. Figure 59 shows the single score for each alternative. The contribution of ecosystem quality of the overall environmental performance is negligible. Alternative 1 has the best environmental performance in total and Alternative 2 has the worst environmental performance among the three. Figure 57 Characterization of environmental performance in fourteen midpoint categories

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88 Figure 58 Weighting of environmental performance in four impact categories Figure 59 Single score of environmental performance for three alternatives Technical Performance Technical performance is indicated by the full load efficiency, part load efficiency, reliability, maintainability and spatial re quirement. Table 5-1 4 lists the technica l performance for three alternatives in the scale of poor, fair, good, and excellent

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89 Table 5 1 4 Technical performance of alt ernatives Alternative 1 Self -contained unit + parallel fan powered VAV + dedicated OA Alternative 2 Water source heat pump + series fan powered VAV + dedicated OA Alternative 3 Air -cooled chiller + fan coil unit Full load effectiveness good good good Part load effectiveness excellent good poor Reliability excellent excellent fair Maintainability fair poor good Spatial Requirement fair fair good The application of Variable Air Volume (VAV) system in Alternative 1 and Alternative 2 greatly reduce s the fan power usage during the part load condition. Constant volume fan coil unit is used in Alternative 3, so the power consumption for the fans is significant. Since Alternative 1 self -contained water -cooled unit complete is equipped on separate floors, equipment on other floors will not be affected if one unit fails. Similar to self -contained water -cooled uni t, for Alternative 2 water source heat pump system, e ach heat pump has its own condenser and evaporator. If one heat pump fails, other heat pumps will not be affected. A dditional chemical treatment for the cooling towers is required for the c ooling tower to prevent corrosion and the water loop in Alternative 1 and 2, thus the maintenance effort in these alternatives is increased. Since Alternative 3 air -cooled chilled water fan coil unit system doe s not include a cooling tower, the maintenance effort is reduced. Alternative 1 self -contained VAV system requires the space for small mechanical rooms on each floor. Cooling tower is located on the roof. Alternative 2 water source heat pump system can be located in a mechanical room, on a roof or above the ceiling. Space is required for the air -cooled

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90 chiller for A lternative 3; however, it does not require the space for the cooling tower system. AHP Module Application Established Hierarchy Structure Figure 5 1 0 shows the established hierarchy structure for choosing the optimal HVAC system. There are three alternatives in the alternative layer: Alternative 1 s elf contained unit + parallel fan powered VAV + dedicated OA Alternative 2 water source heat pump + series fan powered VAV + dedicated OA, and Alternative 3 air -cooled chiller + fan coil unit system. The criteria layer contains four criteria: Technical Requirement C1, Economic Performance C2, Environmental Performance C3 and LEED Performance C4. The wei ghtings for the four criteria are calculated by the pairwise importance matrix based on the preference of the owners or decisionmakers. Each criterion has its own subcriteria. Similar to the weighting calculation for the criteria layer, the weighting fo r the sub criteria under Technical requirement is also based on the pairwise importance matrix originally from the decision-makers. Since life cycle costing is the only criteria in the Environmental performance criterion, the weighting is set to 1. For th e weightings of sub-criteria under Environmental Performance, a recommended weighting structure for Impact 2002+ in SimaPro is used. The weightings between Optimized Energy Performance and Enhanced Refrigerant Management are calculated based on the points available in each credit.

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91 Figure 51 0 The decisionmaking hierarchy structure Goal Layer The goal for this analysis is to find a HVAC system which has the optimal combined performance and also best suits the preference of decision makers for a 6story office building located in Atlanta, GA In this case study, the decision makers would like to choose an environmental -friendly HVAC system. And since the project is trying to earn LEED credits, sound performance in LEED Energy and Atmosphere category is also preferable. The economic performance is also an important factor to consider, but not as important as the other two factors mentioned above. The technical requirement is the least important factor to consider.

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92 Criteria Layer Pairwise c omparison The way for setting the importance intensity when comparing two performance criteria is based on the preference of the decision maker. Table 4-1 in Chapter 4 defines the intensity of importance when comparing two criteria. A 9-point importance scale is chosen for this case. Figure 5 1 1 indicates the subjective judgment based on the decision makers preference when comparing each two of the criteria in pai r wise. Figure 51 1 Pairwise comparison of performance criteria Table 5 1 5 shows a 4 by 4 reciprocal comparison matrix in the criteria layer based on pairwise comparison discussed above. Numbers on the diagonal are all 1. The values in the lower triangular matrix are filled by using the reciprocal values of the upper triangular matrix.

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93 Table 5 1 5 Comparison matrix for criteria layer Technical Economic Environmental LEED Energy Technical 1 3 1 5 3 1 1 5 3 1 1 Economic Environmental LEED Energy Calculating weighting s of performance criteria The weighting of each performance criteria in the criteria layer s then calculated as following, 1 = 11 12 13 14 = ( 1 ) = 0 3398 2 = 21 22 23 24 = ( 3 1 ) = 0 5886 3 = 31 32 33 34 = ( 5 3 1 1 ) = 1 968 4 = 41 42 43 44 = ( 5 3 1 1 ) = 1 968 The weighting of criteria is, 1 = 1 100 % = 6 98 % 2 = 2 100 % = 12 1 % 3 = 3 100 % = 40 46 % 4 = 4 100 % = 40 46 %

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94 Consistency c heck The maximum Eigen value of the matrix max is 3.9145 and the consistency index is = (N=4), which is 0.0285. The r andom consistency index (RI) is 0.9 for a 4 by 4 matrix. Then the consistency ratio (CR) is calculated, = = 0 0285 0 9 = 0 0317 Since CR< 0.1, the matrix is considered consistent. Subcriteria Layer T echnical criteria Pairwise c omparison There are five factors representing the technical performance of a HVAC system The comparison between these factors is similar with what is done for the performance criteria in the criteria layer as discussed above A 5 by 5 pairwise comparison matrix is established according to the preference of the decision maker. The pairwise comparison matrix can be expressed in Table 51 6 Table 5 1 6 Comparison matrix in technical requirement criteria Full load effectiveness Part load effectiveness Reliability Maintainability Spatial requirement Full load effectiveness 1 1 5 5 7 1 1 5 5 7 1 1 3 1 1 3 1 Part load effectiveness Reliability Maintainability Spatial requirement Weighting c alculation Similar for the weighting calculation for the performance criteria, the weighting of technical factors is calculated,

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95 = 1 100 % = 38 89 % = 2 100 % = 38 89 % = 3 100 % = 9 06 % = 4 100 % = 9 06 % = 5 100 % = 4 1 % Consistency c heck. T he maximum Eigen value max for this matrix is 5.0736, and the consistency index is = (N=5), which is 0.0184. The random consistency index (RI) is 1.12 for a 5 by 5 matrix. Then the consistency ratio (CR) is calculated, = = 0 0285 0 9 = 0 0317 Since CR< 0.1, the matrix is considered consistent. Economic criteria Weighting. Li fe cycle costing is the only sub -criteria indicating the economic performance of a HVAC system So the weighting factor for life cycle cost is 1. Environmental criteria Weighting. Life cycle assessment is used to evaluate environmental performance of HVAC systems The impact method used in LCA analysis is Impact 2002+. It contains four damage categories: human health, climate change, resources, and Table 5 1 7 Weighting sets in impac t 2002+ Environmental factors Human health Climate change Resources Ecosystem quality Weighting 30.1% 35.2% 32.6% 2.1%

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96 ecosystem quality. In this case study, recommended weightings for these categories by the I mpact 2002+ method in SimaPro program i s used and listed in Table 5-1 7 LEED criteria Weighting. The relative importance or weightings between EAc1 Optimized Energy Performance and EAc4 Enhanced Refrigerant Management depend on the points available in each credit. T here are 19 points available for Optimiz ed E nergy P erformance credit under LEED 2009-NC. And 2 points are obtainable if the refrigerant used in the cooling plant satisfies the requirement in Enhanced Refrigerant Management credit. T hus the weighting between these two factors can be evaluated in specific. = 19 19 + 2 100 % = 90 48 % = 2 19 + 2 100 % = 9 52 % Summary of weightings for criteria and subcriteria Table 5 15 shows the weighting factors calculated in criteria layer and sub-critieria layer. T he summation of the weighting factor s in the crite ria layer is 1. Similarly, the sum for the sub -criteria under the same criteria is also 1. So the total weighting factor s for sub-cri teria in the sub -criteria layer should be multiplied by the weighting of the criteria under which the sub-criteria locate The sum of the total weightings for all sub-criteria is 1. Table 5 -1 5 shows complete weighting results for criteria and subcriteria LEED and environmental criteria have the highest weighting among the criteria which are 40.46%. Technical criterion has the lowest weighting (6.98%) based on the preference of the decision mak ers.

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97 Table 5 1 8 Weightings for criteria and sub-criteria Cri teria level Sub-criteria level Total weighting Technical 6.98% Full load effectiveness 38.89% 2.71% Part load effectiveness 38.89% 2.71% Reliability 9.06% 0.63% Maintainability 9.06% 0.63% Spatial requirement 4.1% 0.29% Environmental 40.46% Ecosystem quality 2.1% 0.85% Human health 30.1% 12.18% Climate change 35.2% 14.24% Resources 32.6% 13.19% Economical 12.1% Life cycle cost 1 00% 12.11% LEED 40.46% Optimized energy performance 90.48% 36.61% Enhanced refrigerant management 9.52% 3.85% Alternative Layer Table 5 18 to Table 5-29 list the performance indicators f or three alternatives under the performance sub -criteria. Economic p erformance criteria For economic performance, the performance indicators (PI) are calculated based on equation 412. The maximum and minimum PI values are calculated by the performance values and the mean of performance values for all alternatives based on equation 4-7, 4 8, 4 9 mentioned in Chapter 4. The calculated mean value and the standard deviation for performance values are also listed in the table. To note that since the best economic performance is corresponded to the lowest life cycle cost, the reciprocals of the lif e cycle cost of three alternatives are made before calculating the mean value of alternatives and its standard deviation. Similar situation is also applicable for environmental performance criteria. The lower point means the better environmental performanc e under that environmental performance category.

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98 Table 5 1 9 Performance i ndicators in l ife cycle cost (= 2.30 E-7 3 = 1.40 E-8 ) Alternatives Life Cycle Cost ($) Preference Indicator (PI) Self contained unit + parallel fan powered VAV + dedicated OA 4 251 937 5.427 Water source heat pump + series fan powered VAV + dedicated OA 4 386 235 4. 105 Air cooled chiller + fan coil unit s 4 415 848 2.658 Environmental p erformance The way for calculating the performance indicators for environmental performance is the same as that for economical performance. Table 5 20 Performance indicators for human health (= 0.025, 3 = 3.762E -3 ) Alternatives Result in Human Health (pt) Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 84 6. 372 Water source heat pump + series fan powered VAV + dedicated OA 73 3.709 Air cooled chiller + fan coil units 78 4.919 Table 5 21 Performance indicators for ecosystem quality ( = 1.45, 3 = 0.213 ) Alternatives Result in Ecosystem Quality (pt) Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 5 4.23 Water source heat pump + series fan powered VAV + dedicated OA 5 4.23 Air -cooled chiller + fan coil units 7.5 6.54 Table 5 22 Performance indicators for climate change (= 0.035, 3 = 4.98E -3 ) Alternatives Result in Climate Change (pt) Preference Indicator (PI) Self contained unit + parallel fan powered VAV + dedicated OA 72 6.17 Water source heat pump + series fan powered VAV + dedicated OA 61.5 5.282 Air cooled chiller + fan coil units 41 3.548

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99 Table 5 2 3 Performance indicators for resources ( = 0.022, 3 = 3.237E -3 ) Alternatives Result in Resources (pt) Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 78 6.223 Water source heat pump + series fan powered VAV + dedicated OA 66 5.199 Air cooled chiller + fan coil units 47 3.578 LEED p erformance For LEED and technical performance, the maximum and minimum performance values in each sub-criterion are defined in Chapter 4. Equation 4 -12 is used for converting the performance values into the performance indicators for LEED and technical performance cr iteria. Table 5 2 4 Performance indicators for optimized energy performance Alternatives Points achievable in Optimized Energy Performance Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 4 3.4 Water source heat pump + series fan powered VAV + dedicated OA 2 1.8 Air -cooled chiller + fan coil units 0 1 Table 5 2 5 Performance indicators for enhanced refrigerant management Alternatives Points achievable in Enhanced Refrigerant Management Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 1 9 Water source heat pump + series fan powered VAV + dedicated OA 1 9 Air -cooled chiller + fan coil units 0 1

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100 Technical p erformance criteria Table 5 2 6 Performance indicators for full load effectiveness Alternatives Full load effectiveness Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 3 6.333 Water source heat pump + series fan powered VAV + dedicated OA 3 6.333 Air -cooled chiller + fan coil units 3 6.333 Table 5 2 7 Performance indicators for part load effectiveness Alternatives Part load effectiveness Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 4 9 Water source heat pump + series fan powered VAV + dedicated OA 3 6.333 Air -cooled chiller + fan coil units 1 1 Table 5 2 8 Performance indicators for reliability Alternatives Reliability Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 4 9 Water source heat pump + series fan powered VAV + dedicated OA 4 9 Air -cooled chiller + fan coil units 2 3.667 Table 5 2 9 Performance indicators for maintainability Alternatives Maintainability Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 2 3.667 Water source heat pump + series fan powered VAV + dedicated OA 1 1 Air -cooled chiller + fan coil units 3 6.333

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101 Results The integrated score for an alternative is the sum of the product of the weighting for the sub -criteri on and the performance indicator under this sub-criterion. There are 12 sub-criteria. The alternative with the highest integrated score is the optimal system based both on the system performance and the pref erence of the decision makers. = Table 5 30 Performance indicators for spatial requirement Alternatives Spatial Requiremen t Preference Indicator (PI) Self -contained unit + parallel fan powered VAV + dedicated OA 2 3.667 Water source heat pump + series fan powered VAV + dedicated OA 2 3.667 Air -cooled chiller + fan coil units 3 6.333 Where, is the weighting of the sub-criterion is the performance indicator under that sub -criteria for an alternative The integrated scores for three alternatives interested are shown in Table 5-2 8 Alternative 1 Self -contained unit + parallel fan powered VAV + dedicated OA has the highest score with 5. 034 thus it is the best choice among all the alternatives. Table 5 31 Integrated score for three alternatives Alternatives Integrated Score Self -contained unit + parallel fan powered VAV + dedicated OA 5.034 Water source heat pump + series fan powered VAV + dedicated OA 3.943 Air -cooled chiller + fan coil units 3.213

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102 Sensitivity Analysis Fuel M ix of Electricity The emissions from burning fossil fuel for electricity and natural gas for the HVAC system during its operation are the main sources for environmental concerns. The major emissions include CO2, SO2, NOx, CO, and particles. These emissions contribute to var ious environmental issues: global warming, ozone depletion, acidification, eutrophication, land use, human toxicity, fossil fuel depletion, etc. The energy mix for electricity in different states varies and the differences may results in different interpretation for the environmental performance of alternatives. The cleanness of the sources for electricity plays an important role in evaluating the environmental performance of the system. The energy mix of electricity typically constitutes of coal, natural g as, nuclear, oil and hydropower. The more fossil fuel (coal, oil and natural gas) involved in the production of the electricity, the worse environmental problems it may cause. The burning of coal at the power plant may cause problems in global warming, ecotoxicity, resources depletion, land use and respiratory/carcinogen problems for human health. The burning of natural gas for electricity mainly causes human health problems, climate change and resources depletion. The use of nuclear for electricity contrib utes most environmental effects in ionizing radiation, ozone layer depletion and resources depletion. And burning of oil mostly contributes to the ozone depletion. There is no significant environmental problem by utilizing hydropower for electricity production. Because of the various fuel mixes for electricity in different states, the environmental contribution for the same system with the identical electricity consumption may very differently.

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103 SimaPro7 is the software to model the life cycle impacts of th e system. Franklin USA 98 database which reflects the average data in the USA is used for energy inputs and outputs. The Impact 2002+ is the life cycle impact assessment method. Table 5 32 shows the fuel mix for electricity in five regions in the United S tates from Energy Information Administration (EIA) (Energy Information Administration, 2007) (Edision Electric Institute, 2010) 97.7 % of the electricity is produced from coal in West Virginia. South Carolina has 51.1% of electricity produced from nuclear. The electricity production in Washington is most clean, which 78.1% is produced from hydropower and other non-hydro renewable. Table 5 32 Fuel mix for electricity in five regions of the United States Coal (%) Nuclear (%) Natural Gas (%) Oil (%) Hydro and Nonhydro renewable and others* (%) Washington 6 8.6 7.3 0 78.1 West Virginia 97.7 0 0.4 0.2 1.7 South Carolina 39.8 51.1 6.1 0.3 2.8 Wisconsin 64.9 19.9 9.1 1.4 4.8 Florida 29.1 14 43 10.2 3.6 "Non Hydro Renewables and Other" includes generation from solar, wind, geothermal, biomass (agricultural waste, municipal solid waste, landfill gas recovery, wood, pitch), hydrogen, batteries, chemicals, non wood waste, purchased steam, sulfur, and miscellaneous technologies. Figure 51 2 and 51 3 shows the midpoint environmental impact and the damage assessment for producing 1kWh electricity in five states of the United States. Electricity in Florida causes the highest impact in human health because of the high composition of natural gas (43%) in electricity production. Because of the large percentage use of coal, electricity production for West Virginia keeps high in all the impact categories. Environmental performances in the four damage categories are further normalize and weighted to a single s core in Figure 514. The lower score indicates better environmental performance. Electricity production in Washington has the lowest

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104 environmental impact among the five regions as a result of the high level use of hydropower. Figure 51 2 Midpoint impact of fuel mix for 1kWh electricity in five states of the United States To evaluate the sensitivity of the model on the energy mix in a different region, another set of calculation is conducted assuming the 6-story office building by using the energy mix of electricity in Washington State since it has the maximum percentage use of hydro power and other renewable sources. Because only energy mix effect is considered in the sensitivity analysis, changes in weather and utility cost for a different region is excluded. To evaluate the sensitivity of energy mix to the decision making model, energy mix scenario in Washington is chosen since it has the lowest composition in coal and oil and highest composition in hydropower for electricity production. If the r esult shows the model is not sensitive on the Washington energy mix scenario, it has little chance to be sensitive on the energy mix scenario for the states in the United States. Figure 515

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105 shows the four damage impacts of three alternatives with the ener gy mix in Washington State. And Figure 516 shows the overall score of environmental impacts among three alternatives. Alternative 3 Chilled Water VAV System has the highest environmental impact in the four categories compared with alternative 2 which has the highest impact with Atlanta energy mix scenario. Alternative 1 still has the lowest environmental impact among all three alternatives. Fig ure 5 1 3 Damage assessment of electricity mix for 1kWh electricity in five states of the United States. Tab le 5 30 shows the overall score with Washington energy mix scenario. Although the order of environmental performances changes between Alternative 2 and Alternative 3, the ranking order for the overall performance for three alternatives does not change comp ared with the Atlanta energy mix scenario in the case study. The result indicates that energy mixes in different regions are not sensitive for the case study even with the most possible mix difference between the two states.

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106 Fig ure 5 1 4 Single score for the environmental impact of electricity mix for 1kWh electricity in five states of the United States Figure 51 5 Damage impacts for alternatives with energy mix in Washington

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107 Figure 51 6 Overall score s for alternatives with energy mix in Washington Table 5 30. Integrated score with Washington energy mix scenario Alternatives Integrated Score Original Score Self -contained unit + parallel fan powered VAV + dedicated OA 5. 375 5.034 Water source heat pump + series fan powered VAV + dedicated OA 4.228 3.943 Air -cooled chiller + fan coil units 2.587 3.213 Weighting Effect The preference s of the decision makers have impact on the results since the preference weightings which are decided by the pairwise matrix developed by the preference of the decision -makers are part of overall performance score calculations In order to identify the weighting effect in the criteria layer, assume the weighting for one of the four criteria equal to x. And the total weightings of the othe r three are all equal to 1x The ratio among the other three criteria is kept the same. The relationships between the weighting of each criterion and the overall score of each criterion are shown form Figure 5-1 7 to Figure 5-2 0 OS m eans the overall score for an alternative.

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108 Fig ure 5 17 shows that overall score s for all three alternatives are increased with the weighting of the technical requirement, and the ranking order for overall scores does not change with the increased weighting of technical requirement. And the overall score also increases with the increase of the weighting of the technical requirement for all three alternatives. The slopes of three alternatives are almost the same. Fig ure 5 18 shows that the ranking order for o verall score s does not change with the increased weighting of economical performance. And the overall score also increases with the increase of the weighting of the technical requirement for all three alternatives. Fig ure 5 17 Sensitivity analysis for the weighting of technical requirement

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109 Fig ure 5 18 Sensitivity analysis for the weighting of economical performance Fig ure 5 19 Sensitivity analysis for the weighting of environmental performance

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110 Fig ure 5 20 Sensitivity analysis for the weighting of LEED performance The overall scores of all three alternatives are increased with the increase of the weighting of the environmental performance as shown in Figure 519 T he ranking order of the overall scores does not change with the increase of the weighting of the environmental performance. The magnitude of the slope is decided by the difference in value between the environmental performance and the other three performance criteria. The larger difference is, the steeper slope of the weightings will be. The overall scores of all three alternatives are decreased with the weighting of LEED performance as shown in Figure 520 And the ranking order of overall scores does not change with the increase of the weighting of LEED performance.

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111 CHAPTER 6 THOUGHTS ON SOFTWARE DEVELOPMENT The integrated decision -making model provides a comprehensive and systemic way to evaluate HVAC systems. It combines the performance data of alternatives and quantized preferences of the decision maker to find the optimal HVAC system. However, t he calculation of the performance indicators and the AHP decisionmaking model is complicated and heavy. In addition, in the real world, there might have more than 3 alternatives exist to choose from. Sometimes the decision makers even dont have a detailed preference on the system other than some general ideas about the system or performance preferred To facilitate the decision -making process and reduce the complexit y of model inputs to make it easier to use, 5 modules are created for software development: s izing m odule, e quipment and s ystem m odule, e nergy s imulation m odule, p erformance m odule and d ecision making m odule. The inputs of modules include the information o f the building, general preferences on performance criteria and HVAC systems from the decision makers, and design data from the consultant engineers. The calculation of these modules can also be integrated with some of popular building calculation software in industry for example, the load calculation software, Auto CAD, energy simulation software, and economic life cycle cost software. Table 61 summarizes software used in the case study and their alternatives O ther possible software or database needed for building up the entire decisionmaking module in the future is also listed. Software which can meet the requirement of analysis is not limited to what are listed in the Table. T he structure s and inputs/outputs of five module blocks are also disc uss in details in the following sections.

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112 Table 6 1. Summarization of software used or needed for the decision -making modules and their alternatives Modules Software used in the dissertation Alternatives Other p ossible software for modules Sizing module Trace Load 700 CHVAC 6, HAP 4.40.0.61, eQUEST3.63 Energy Plus 5.0.0 DOE 2.2 Energy Pro 4.4 Auto CAD, Revit Equipment and system module N/A N/A Performance data base is needed to be developed Energy simulation module Trace 700 DOE 2 .2 eQ UEST 3.63, Energy Plus 5.0.0 Energy 10 HAP 4.40.0.61, None Performance module SimaPro 7 BLCC 5 GaBi 4.3 None Decision making module Self -coded Expert Choice 11.5 None Sizing Module The sizing module is the first module in the model and the basis for generating the appropriate HVAC system alternatives. It calculates the size of air system s and heating and cooling equipment which can serve the building heating and cooling demand appropriately. In order to size the air system and the heating and cooling equipment, load calculation is conducted firstly. Figure 6 1 shows the structure of the sizing module. The inputs for load calculation include the building information (location, type, weather data, zone definition and construction data of the building) and design requirement for comfortable indoor environment (internal load, air flow requirement, thermostat, and schedules). Design cooling load and design heating load can be calculated from the load calculation and they are combined with the air system type, dedicated outdoor air system (if applicable), general fan size to get the air volume required for supply air,

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113 outdoor air, return air and exhaust air. The equipment is sized based on the air volume required for the air system and the input for equipment type and g eneral pump sizes. Equipment and System Module Equipment and system module selects the top three system and equipment candidates as the alternatives for further performance evaluation. This step greatly minimizes the calculation load and improves the effi ciency of the software. Figure 6 2 shows the structure of the equipment and system module. A large general database about information of heating and cooling equipment and air systems for major manufacture brands in the industry are embedded in the module. The general database contains sizes, spatial requirement, running conditions of various air systems and equipment from major HVAC manufacture brands. With the inputs of air system and equipment sizes, brand preference and the spatial requirement of the building, some initial candidates are selected to enter the performance database which contains more detailed information about the performance data for the systems and equipment. These performance data include the technical performance (full load effect iveness, part load effectiveness, maintainability, reliability, and spatial requirement), economic cost (initial cost, maintenance cost, replacement cost), environmental data (material, transportation), refrigerant management and brands. After the internal initial comparison based on the performance data, Top three candidates are selected with the best performances in technical, environmental, economical aspects. The three alternatives are further evaluated in the following energy simulation module, perfor mance module and decisionmaking module to conclude the optimal HVAC system for the building. And technical performance data of three

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114 alternatives from the performance database can be used for the evaluation under technical requirement criteria of the deci sionmaking model. Fig ure 6 1 Structure of the sizing module Notice that since the systems and cooling and heating equipment data in the general and performance database are from major HVAC manufactures, the annual or regular update of the system and equipment database is recommended.

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115 Fig ure 6 2 Equipment and system module Energy Simulation Module Energy simulation module is the key for evaluating the environmental performance, economic performance and LEED performance in the criteria and subcriteria layer of AHP decisionmaking model. Figure 63 shows the structure of energy simulation module. The annual energy consumption of the system and equipment which meet the requirement of ASHRAE 90.1 Appendix G baseline case are also simulated. It will be compared with annual energy consumption of the other three alternatives in

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116 order to find energy cost savings of alternatives for the achievable points in LEED EAc1 Optimized Energy Performance The inputs of the energy simulation module include the system and equipment information (energy rate of pumps, fans, and equipment) of the three alternatives and ASHRAE 90.1 Appendix G Baseline Case The outputs for the energy and consumption module are the annual energy consumption and energy demand of the ASHRAE Baseline Case and three alternatives. Fig ure 6 3 Structure of energy simulation model

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117 Performance Module Figure 64 shows the structure of the performance module. As discussed above, the annual energy consumption and demand from the energy simulation module serve several performance criteria in the performance module. The utility rate structure for electricity consumption, electricity demand, water charge and other charges from the utility companies at the building loc ation are imported into the module for calculating the annual energy cost for alternatives and ASHRAE Baseline Case. The results combine with the economic performance data (initial cost, maintenance cost and replacement cost) from the performance database and the annual energy cost of alternatives to get the life cycle cost of alternatives. The annual energy costs of alternatives are compared with the ASHRAE Baseline Case to get energy cost savings for the achievable points in LEED EAc1 Optimized Energy Pe rformance point structure. Annual energy consumption data are also imported into Inventory Database with the electricity fuel mix of the region where the building is located and the performance database (materials, refrigerant, and transportation from the origin) to calculate the emissions of alternatives during life cycle period. The emissions are further evaluated by the impact assessment method chosen to get final results in Human Health, Global Warming, Energy Resources, and Ecosystem Quality of Life C ycle Assessment categories. Technical Performance of alternatives and the points achievable in LEED EAcr4 Advanced Refrigerant Management credit are available from the performance database in the system and equipment module.

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118 Fig ure 6 4 Structure of performance model Decision Making Module There are five steps include in the decisionmaking module. The goal layer defines the goal and scope of the module. Figure 6-5 shows the structure of the performance module. Pairwise comparisons in criteria or sub-criteria are made based on the preference feedback from the decision makers and the according pairwise importance matrix for each criterion is formed. With the satisfactory results from consistency check, the weightings for criteria and sub-criteria are calculated and applied to the criteria layer and sub-criteria layer as inputs for the alternative layer. Performance results from the performance module (including LCA results in impact categories, points achievable in LEED EAc1 and EAc4, life cycle cost, and technical performance) are the inputs for calculating the performance indicators in the

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119 alternative layer. Then the performance indicators are combined with the weighting for each performance sub-criteria to finally calculate the integrated performance r anking of alternatives. The alternative with the highest integrated score is ranked top which indicates that HVAC system is the optimal system based on the performance results and the preference of the decision makers. Figure 66 shows the whole picture of the entire model structures and the connections between modules. Fig ure 6 5 Structure of decision -making model

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120 Fig ure 6 6 Overall diagram of the entire decision making model structure

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121 CHAPTER 7 CONCLUSIONS AND RECO MMENDATIONS Conclusions The goal for this dissertation is to develop an integrated decision making model for selecting HVAC system based on multiple performance criteria including the technical performance, economic performance, environmental performance, LEED perfor mance as well as the preference s of decision makers. There is no research conducted before which systematically integrates the overall objective performance of HVAC systems with peoples subjective preference together when make a selection This dissertati on offers the decision makers a comprehensive view of the performance of HVAC systems and also a way to put their preferences and realistic condition into the decision-making process. In addition, the environmental performance of HVAC systems is used to b e overlooked through the industrial practice and there is very little research on that. This dissertation is inspired by the rising concern of environmental protection and t he introduction of life cycle assessment thinking into the performance evaluation h elps decision makers to make a decision which is responsible to the environment. The introduction of the Performance Indicator (PI) provides an innovative way to measure the performance of alternatives among general candidates with a unitless number which avoids the addition of performance values in different units from the original AHP model. The case study conducted in Chapter 5 for a 6 -story office building located in Atlanta, GA indicates the self -contained variable air volume system is the optimal

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122 sys tem among all the three alternatives based on its multiple performances as well as the preference of the decisionmakers on performance criteria. The energy mix in different states does not have significant effect on the final ranking order of overall per formance in this case study. However, the regional effects including weather condition, utility cost should still be considered. With the certain performance values of all alternatives, t he preference weightings put on performance criteria are important to the final results. With different weightings assigned to the performance criteria, the ranking for alternatives may vary. The overall score of an alternative may increase or decrease with the weighting increase of a performance criterion, depending on the performance values under that performance criterion compared with the values of other criteria. When the ranking order of alternatives for a specific performance criterion is not consistent with the ranking orde r of the overall performance, the ranking order of overall performance may be changed with the increased weighting of that specific criterion. Recommendations for Future Work This dissertation does not address the interaction between the performance crit eria. Some of the performance criteria use the same performance value as part of their inputs and it may contribute to the double counting on the final performance results. One suggestion is to put all the performance criteria, which partially sharing the same performance value under the same umbrella of a parent node in the AHP decision making structure and let them share the total weighting of that parent they are subject to.

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123 Another suggestion for selecting the appropriate system alternatives is to coop erate with the manufactures, ASHARE or the related and available resources to build a powerful and comprehensive performance database for HVAC systems for the easy access to the performance data especially on the material composition of equipment. As long as the performance database is big enough, appropriate candidates can be generated as the alternatives for the decision making process. For calculating the Performance Indicators (PI) by using normal distribution, a fully developed decision making system w ould also have the ability to calculate the PI values of candidate systems with a comprehensive larger database. To facilitate the decision -making process and reduce the complexity of model inputs to make it easier to use, 5 modules are created for software development in Chapter 6 Thoughts for Software Development. The modules include sizing module, equipment and system module, energy simulation module, performance module and decision making module. The inputs of modules include the information of t he building, general preferences on performance criteria and HVAC systems from the decision makers, and design data from the consultant engineers Software developers can use the se five modules to develop comprehensive HVAC system selection software for pu blic use. And the program for the AHP HVAC decisionmaking model has been also coded and attached in the appendix for the ease of programming and use

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124 APPENDIX A ENERGY SIMULATION RESULTS

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161 APPENDIX B PERFORMANCE RATING D ETAILS

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163 APPENDIX C ENERGY COST BUDGET

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165 APPENDIX D ECONOMIC COST

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177 APPENDIX F DECISION MAKING MODEL PROGRAM

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188 L IST OF REFERENCES [1] American International Standard. (1997). ANSI/ISO 14040 Environmental management Life cycle assessment Principles and framework. American international Standard. [2] American International Standard. (1998). ANSI/ISO 14041 Environmental management Life cycle assessment Goal and scope definition and inventory analysis. American International Standard. [3] American International Standard. (2000). ANSI/ISO 14042 Environmental management Life cycle assessment Life cycle impact assessment. American International Standard. [4] American International Standard. (2000). ANSI/ISO 14043 Environmental management Life cycle assessment Life cycle interpretation. American International Standard. [5] ASHRAE. (2004). ANSI/ASHRAE Standard 135 BACnet A Data Communication Protocol for Building Automation and Control Networks. American Society of Heating, Refrigerating and Air -conditioning Engineers. [6] ASHRAE. (2004). ANSI/ASHRAE Standard 34 Designation and Safety Classification of Refrigerants. American Society of Heating, Refrigerating, and Air -conditioning Society. [7] ASHRAE. (2004). ANSI/ASHR AE Standard 55 Thermal Environmental Conditions for Human Occupancy. American Society of Heating, Refrigerating and Air -conditioning Engineers. [8] ASHRAE. (2007). ANSI/ASHRAE/IESNA Standard 62.1 Ventilation for Acceptable Indoor Air Quality. American Soc iety of Heating, Refrigerating and Air -conditioning Engineers. [9] ASHRAE. (2007). ANSI/ASHRAE/IESNA Standard 90.1 Energy Standard for Buildings Except Low -Rise Residential Buildings. American Society of Heating, Refrigerating and Air -conditioning Enginee rs. [10] ASHRAE. (2005). ASHRAE Handbook Fundamentals. American Society of Heating, Refrigerating and Air -conditioning Engineers. [11] ASHRAE. (2007). ASHRAE Handbook HVAC Applications. American Society of Heating, Refrigerating and Air -conditioning. [12] ASHRAE. (2008). ASHRAE Handbook HVAC System and Equipment. American Society of Heating, Refrigerating and Air -conditioning Engineers.

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189 [13] ASHRAE. (2006). ASHRAE Handbook Refrigeration. American Society of Heating, Refrigerating and Air -conditioning Engineers. [14] ASHRAE. (1999). HVAC Applications. American Society of Heating, Ventilating and Air -conditioning Engineers. [15] Avat Osman, R. (2007). Life cycle assessment of electrical and thermal energy systems for commercial buildings. International Journal of LCA 12(5), 308316. [16] Barbara C. Lippiatt, J. F. (2008). An introduction of building life -cycle costing. Building and Fire Research Laboratory, National Instite of Standards and Technology. [17] Building and Fire Research Laboratory, Office of applied Economics. (2009). Life -Cycle Costing Manual for the Federal Energy Management Program, NIST Handbook 135. [18] C.Lippiatt, B. (2007). Building for Environmental and Economic Sustainability Technical Manual and User Guide. Bui lding and Fire Research Laboratory, National Instite of Standards and Technology. [19] Calm, J. (2002). Emissions and environmental impacts from air -conditioning and refrigeration systems. International Journal of Refrigeration 25, 293305. [20] David T. Allen, D. R. (2002). An introduction to environmental issues. Green engineer: Environmental conscious design of chemical process. Prentice -Hall PTR. [21] Edision Electric Institute. (2010, 07). Keep our fuel mix diverse Retrieved from http://www.geten ergyactive.org/fuel/state.htm [22] Energy Information Administration. (2007). State electricity profiles 2006DOE/EIA 0348. U.S. Department of Energy [23] Federal Energy Management Program. (2009). Building Life Cycle Costing 5. Department of Energy. [ 24] IEA. (2009). World Energy Outlook. International Energy Agency. [25] K., H. (2008). Environmental evaluation of an air -conditioning system supplied by cooling energy from a bore-hole based heat pump system. Building and Environment 43(1), 5161. [2 6 ] K., H. (2004). Environmental impact assessment using a weighting method for alternative air -conditioning systems. Building and Environment 39(10), 11331140.

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190 [2 7 ] Mark Goedkoop, M. O. (2008). SimaPro Database Manual mMthods Library. Pre Consultants, t he Netherlands. [2 8 ] Mikko Nyman, C. J. (2005). Life cycle assessment of residential ventilation units in a cold climate. Building and Environment V40, 15 27. [2 9 ] O.Jolliet, M. R. (2003). Impact 2002+: A new life cyce impact assessment methodology. International Journal of LCA 8(6), 324-330. [ 30 ] Oele, M. G. (2006). SimaPro 7 tutorial. Pre Consultants. [3 1 ] Prek, M. (2004). Environmental impact and life cycle assessment of heating and air conditioning systems, a simplied case study. Energy and Bu ildings 36(10), 10211027. [3 2 ] SAIC. (2006). Life cycle assessment: Principles and practice No. EPA/600/R 06/060. National Risk Management Research Laboratory, U.S. Environmental Protection Agency. [3 3 ] Satty, T. L. (1982). Decison making for leaders: the analytical hierarchy process for decisions in a complex world. Lifetime Learning Publications. [3 4 ] Shah V.P., D. D. (2008). Life cycle assessment of residential heating and cooling systems in four regions in the United States. Energy and Buildings 40(4), 503513. [3 5 ] Svoboda, S. (1995). Note on life cycle analysis. National Pollution Prevention Center for Higher Education. [3 6 ] TRANE. (2005). User's Manual, TRACE700 Building Energy and Economic Analysis Version 6.0. TRANE. [3 7 ] U.S. Department of Commerce. (2009). Energy price indices and discount factors for life -cycle cost analysis. NISTIR 85 327324. [3 8 ] U.S. Green Building Council. (n.d.). An introduction to LEED Retrieved 01 03, 2010, from U.S. Green Building Council: http://www.usgbc.or g/ [3 9 ] U.S. Green Building Council. (2009). LEED 2009 for New Construction and Major Renovations. U.S. Green Building Council. [ 40 ] UNEP. (2003). Envaluation of Environmental Impacts in Life Cycle Assessment. United Nations Environmental Programme, Devi vison of Technology, Industry and Economics.

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191 [4 1 ] UNEP. (April -September 2003). Sustainable building and construction: Facts and figures. Industry and Environment: Sustainable Building and Construction Vol.26 (No. 2-3).

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192 BIOGRAPHICAL SKETCH Xun was born and grew up in Dalian, a coastal city in northeast of China. She received her bachelor of engineering degree from Dalian University of Technology, China, in June 2005 and began her PH.D program in Department of Mechanical Engineering at University of Florida after she got her masters degree in the same department in December 2007. She is also pursuing a minor in b uilding c onstruction at the University of Florida for Sustainable Green Building Design Xun has two internship experiences in mechanical consulting, energy modeling as well as energy saving development in HVAC design companies. Xun is a LEED Accredited Professional and EIT engineer.