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Decision Model to Optimize Indoor Air Quality in Commercial Buildings in Florida


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DECISION MODEL TO OPTIMI ZE INDOOR AIR QUALITY IN COMMERCIAL BUILDINGS IN FLORIDA By BILGE GOKHAN CELIK A DISSERTATION PRESENTED TO THE GRADUATE SCHOOL OF THE UNIVERSITY OF FLOR IDA IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY UNIVERSITY OF FLORIDA 2006

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Copyright 2006 By Bilge Gokhan Celik

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This dissertation is dedicated to my dear pa rents, Kemal and Nukhet Celik. This endeavor would not have been possible without their unwavering patience, support, and love.

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ACKNOWLEDGMENTS I would like to acknowledge Dr. Charles J. Kibert for his support throughout the past four years and for giving me the opportuni ty to work in a very interesting area. I have learned substantially from his uncompromising emphasis on quality and meaningful research, and he has truly been a ment or in the fullest sense of the word. I would like to thank Dr. Ke vin Grosskopf for sharing his intelligent ideas and for giving me the opportunity to work for the MC project, which helped me both financially and academically. I am very thankful to Dr. Svetlana Olbina for her support, patience and most importantly for always having the time to listen. I would lik e to thank Dr. Abdol Chini and Dr. Paul Oppenheim for their in sightful feedback in assuring a quality outcome. I also want to thank to Dr. Hal dun Aytug for sharing his expertise, and for sparing time to teach for hours whenever I needed. I would like to acknowledge Fidan Boylu who has always been there to encourag e me either in person or on the phone for whatever the circumstances might be. Words ar e inadequate to express my thanks to the Erenguc Family who have made me feel home since the beginning of my journey at University of Florida. I would like to ac knowledge Gokce, Deniz, and Goksu Celik for sparing their time and money on endless phone conversations. Finally I would like to thank a very special person, D. Arzu Erenguc. It is a fact that none of this would be possible without her help. She has enlighten ed me with her patience, wisdom, and personality. Her support helped me minimi ze the burden on my family and myself. iv

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TABLE OF CONTENTS page ACKNOWLEDGMENTS .................................................................................................iv LIST OF TABLES ............................................................................................................vii LIST OF FIGURES .........................................................................................................viii ABSTRACT .........................................................................................................................x CHAPTER 1 INTRODUCTION........................................................................................................1 Introduction ...................................................................................................................1 Statement of the Problem ..............................................................................................3 Purpose of the Study .....................................................................................................4 Research Questions .......................................................................................................4 Significance of the Study ..............................................................................................5 Assumptions and Limitations .......................................................................................6 Organization of the Study .............................................................................................8 2 REVIEW OF THE LITERATURE..............................................................................9 Introduction ...................................................................................................................9 Sustainability and the Built Environment ...................................................................10 Humans and Their Environment .................................................................................12 Humans and Technology .....................................................................................13 Humans and Buildings ........................................................................................15 Indoor Air Quality (IAQ) in Commercial Buildings ..................................................21 Standards, Regulations and Guidelines ...............................................................23 Sources of Indoor Air Pollutants .........................................................................29 IAQ Control Techniques .....................................................................................32 IAQ and Health ...........................................................................................................39 IAQ and True Costs....................................................................................................40 Optimization of IAQ ...................................................................................................47 Review of Literature Summary..................................................................................51 v

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3 METHODOLOGY.....................................................................................................53 Introduction.................................................................................................................53 Research Questions.....................................................................................................53 Research Design.........................................................................................................54 Research Methodology...............................................................................................60 Population...................................................................................................................61 Summary of Methodology..........................................................................................61 4 DEFINING PARAMETERS AND THE OPTIMIZATION MODEL.......................63 Introduction.................................................................................................................63 Estimating the Costs of Improved Ventilation...........................................................65 Estimating Installed Costs for Increased Ventilation..........................................66 Estimating Operating and Maintenan ce Costs for Increased Ventilation...........70 Estimating the Costs for Air Cleaning........................................................................73 Estimating Installed Costs for Air Cleaners........................................................75 Estimating Operating and Mainte nance Costs for Air Cleaners.........................76 Estimation of Income Function from Incr eased Productivity due to Increased IAQ.78 Defining the Optimization Model...............................................................................82 Decision Variables...............................................................................................83 Objective Function..............................................................................................86 Decision Constraints............................................................................................88 User-Defined Independent Variables as Input Data............................................90 Summary of Chapter...................................................................................................92 5 RESULTS AND DISCUSSION.................................................................................93 Introduction.................................................................................................................93 Solution to the Model.................................................................................................93 Case 1..................................................................................................................95 Case 2..................................................................................................................98 Sensitivity Analysis..................................................................................................100 Summary of Chapter.................................................................................................105 6 CONCLUSION.........................................................................................................107 APPENDIX A WORKSHEETS.......................................................................................................110 B MS EXCEL SOLVER..............................................................................................121 LIST OF REFERENCES.................................................................................................124 BIOGRAPHICAL SKETCH...........................................................................................130 vi

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LIST OF TABLES Table page 2-1 Historical progress of bu ilding issues and concepts.................................................21 2-2 Comparison of regulations and guidelines for acceptable contaminant levels........31 2-3 Collection device characteristics..............................................................................38 2-4 Complaints on floors with out side air provided per person.....................................40 2-5 Potential economic costs and benefi ts of increasing ventilation rate.......................46 4-1 Incremental increases in cooling and heating capacities..........................................68 4-2 Incremental annual cooling a nd heating energy requirements.................................71 4-3 Approximate installed costs of various in-duct particulate air cleaners...................76 4-4 Approximate replacement costs of media cartridges...............................................78 4-5 Ventilation rate (cfm per pe rson) vs. performance index.........................................78 vii

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LIST OF FIGURES Figure page 2-1 Historical design for the Eski mo igloo, Baffin Island, Canada................................17 2-2 Mud masonry Indian House.....................................................................................18 2-3 Larkin Administration Building, Buffa lo, NY, 1906 by F. L. Wright.....................18 2-4 Hong Kong and Shanghai Banking Headquarters, Hong Kong...............................19 2-5 Commerzbank Headquarters, Frankfurt, Germany..................................................20 2-6 Logic diagram for selecti ng an IAQ control approach.............................................33 2-7 Typical HVAC system components.........................................................................35 2-8 Overall performance of simulated office work as a function of sensory pollution..45 2-9 Building design decisions require performance prediction and evaluation.............48 2-10 PMV and thermal sensation.....................................................................................48 2-11 Example pay-off characteristic.................................................................................50 3-1 Research design........................................................................................................54 3-2 Example illustration for the proposed LP model.....................................................59 3-3 Summary of methodology in comparison to Simons decision modeling process..62 4-1 The performance index and its co rrelation with the supplied OA amount..............79 4-2 PPI and its correlation with the amount of OA........................................................80 4-3 An example for piecewise linear overestimate and underestimate..........................81 4-4 One-piece linearization of the PPI vs. OA function.................................................81 4-5 Possible air cleaner locations...................................................................................85 5-1 MS EXCEL Spreadsheet developed....................................................................94 viii

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5-2 Case 1MS Excel screen for solution..................................................................96 5-3 Case 1Answer sheet generated by MS Excel Solver ..........................................97 5-4 Case 2MS Excel screen for solution..................................................................99 5-5 Case 2-Answer sheet gene rated by MS Excel Solver ........................................100 5-6 Case 1MS Excel Solver sensitivity report........................................................102 5-7 Case 2-MS Excel Solver sensitivity report........................................................103 B-1 MS. Excel screen that shows the configuration of the variables............................121 B-2 MS Excel and Solver screen showing the integration of objective function.........122 B-3 MS Excel screen and the options menu of the Solver module...............................123 ix

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Abstract of Dissertation Pres ented to the Graduate School of the University of Florida in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy DECISION MODEL TO OPTIMIZE INDOO R AIR QUALITY IN COMMERCIAL BUILDINGS IN FLORIDA By Bilge Gokhan Celik August 2006 Chair: Dr. Charles J. Kibert Major Department: Design, Construction, and Planning Sustainable design and construction practi ces have been developing rapidly. Many building experts apply sustainable building strategies to their practices. One of the crucial aspects of designing a sustaina ble building is creating a heal thy and comfortable indoor air quality (IAQ). Specific levels of indoor air pollutants may affect the health and comfort of the occupants of a building. The pr oblem starts with the lack of a decision system for choosing a specific IAQ manageme nt option. The building industry is not thoroughly aware of the consequences of different IAQ management methods and decisions, and it lacks the resources to iden tify the best solutions to IAQ problems. These consequences may result in added soft costs such as lost productivity, as well as added hard costs such as the conditioning of the incoming outdoor air. This research combines these two types of costs into a true cost and introduces a modeling methodology of linear mathematical program ming for optimizing IAQ in commercial buildings. These analyses also explore the conflicts between IAQ and energy efficiency. x

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This research explores alternative IAQ cont rol options in terms of improved ventilation and air cleaning and presents an objective func tion and a set of decision variables, as well as the technical, financial, and legal constrai nts. The significance of the research derives from introducing the idea of applying operations research to construction management and providing the conceptual background fo r formulating the optimization of IAQ in commercial buildings. Defining a decision model for commercial buildings will help decision makers such as desi gners, contractors, or buildi ng owners and managers in making more sophisticated decisions rega rding indoor air cont rol technologies and strategies. xi

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CHAPTER 1 INTRODUCTION Introduction The Massachusetts Environmentally Pr eferable Products Program (MAEPP) defines sustainability as th e process of conducting busine ss in a resource conservative and efficient manner so that operations do not compromise the ability of future generations to meet their own needs (MAEPP 2006). Sustainability concerns have been emerging in many different areas. The building industry is one of these areas that have been integrating the concepts of sustainability into industr y practices. Sustainable design and construction of buildings deals with many different issues in bu ildings. One of these is Indoor Environmental Quality (IEQ). The IE Q concept includes factors such as noise, indoor air quality (IAQ), lighting, and acoustics. All of these f actors affect the quality of a buildings interior space. C onsequently different levels of IEQ affect the comfort and health of occupants differently. On the ot her hand, IAQ focuses specifically on the control of indoor air pollutants. Most people are more aware that not only outdoor air pollution but also indoor air pollution can be damaging to their health. A public opinion survey of 1,000 full-time workers reported that 95 percent of those inte rviewed ranked the quality of air at work as very or somewhat important, and only 3 percent believed it was not important (Chelsea 2000). The United States (US) Environmental Pr otection Agency (EPA) studies of human exposure to air pollutants indica te that indoor air levels of many pollutants may be 2 to 5 times, and occasionally more than 100 times, higher than outdoor levels (USEPA 1993). 1

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2 These levels of indoor air pollu tants are of particul ar concern because it is estimated that most people spend as much as 90% of their time indoors. In contrary to outdoor air, indoor air can be recycled constantly causing the air to trap and build up contaminants. Common contaminants include smoke, dust, mold and spores, pollen, and odors. The indoor air pollutants can be caused by seve ral different reasons such as various equipments, heating ventilation and air c onditioning (HVAC) systems, human activities, and building materials. Controlling these sy stems and many other s ources of air pollution involves measures to be taken at many stages of a buildings lifecycle. Design, construction, and occupancy phases are all cruc ial stages that can include activities and decisions to affect IAQ. One of the interesting contradictions of sustainable constr uction practices is between IAQ and energy efficiency measures. Energy efficiency has become one of the most important issues for many industries since the oil crisis took place in 1970s. This trend has become stronger with the deve lopment of green building strategies, environmentalism, and other movements that promote tighter building envelopes to maximize the energy savings. However this tr end unintentionally decr eased the indoor air quality of the buildings. Tighter building envelopes decrease the amount of outdoor air (OA) supplied into the building, thus creati ng buildings that are mostly dependant on mechanical systems. In several cases this approach created the Sick Building Syndrome (SBS), which describes situations in which buildi ng occupants experience acut e health and/or comfort effects that appear to be linked to time spent in a particular building, but where no specific illness or cause can be identifi ed; complaints may be localized in a particular room or zone, or may be spread throughout th e building. (BIOTECH 2005, p. 6)

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3 The effects of poor indoor air quality are not limited to health problems. Buildings with higher indoor air contam inant levels can possibly cause loss of productivity, legal liabilities, and remediation co sts. The problems associated with poor indoor air quality are examined and explained in more detail in Chapter 2. Statement of the Problem The building itself generates many indoor air pollutants mainly due to poor choices of building materials or furniture, and poor maintenance of HVAC systems. The main objective for improving air quality is to determin e the required levels of ventilation, air filtering, and contaminant source management. The problem that the building industry is facing is that there are no decision suppor t tools other than th e local and national standards that can guid e the decision makers with their choice of indoor air management options in a more precise and cost-effective manner. A common experience is that building regulations do not in themselves guarantee a good indoor climate in specific ca ses. Mendell et al. (2002) ex plain that cu rrent building codes are also based primarily on practical ex perience within the building sector and not on health-related criteria. The major IAQ problems derive from frequent design, construction, and operation defects. These de fects usually create indoor environmental problems deriving from indoor air contaminants such as mold, fungi, various bacteria, and viruses. The environmental technology that is used in a building can either be a contributor or a solution to the IAQ of a building. Mendell et al. (2002) argue that science is not the limiting factor but rather economic and institutional barriers are the pr imary barriers. Decisions affecting IAQ are often made on lowest hard costs and this ap proach usually discourages spending more on

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4 improving IAQ. The cost of poor IAQ commonly falls on occupants rather than on building decision makers who may ignore the soft costs of IAQ measures. Soft costs in the building industry are ar chitectural, engineeri ng, and legal fees as distinguished from land and construction cost s (Corporate Real Estate Solutions [CRES] 2005). Soft costs generally represent any costs that are not related to the actual land and construction costs. Consequently the soft co sts associated with IAQ may include but not be limited to costs associated with productivity, health, insura nce fees, litigation, etc. One of the most important issues in regard to improving IAQ of a building thus reducing the soft costs may be found in the relationship between occupant comfort and productivity. Worker salaries constitute the major cost of operating a commercial building, generally estimated at over 90% of the total operating cost, so that even a small increase in employee productivity can considerably decrease a company's operating costs ( American Institute of Architects San Francisco Chapter [AIASF] 2001). Purpose of the Study The purpose of this research is to de velop a decision model for optimizing the control of indoor air pollutan ts in commercial buildings in Florida. The goal of the research is to help decision makers determ ine the optimal indoor air management options to maximize the benefits of a better indoor air quality. Research Questions The major research question to be investig ated in this research is given below: Can an optimization model be developed to select effectively the optimal IAQ measures in commercial buildings in Florida to meet or exceed the standards required by code? This study also explores the an swers to the following question:

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5 What are the decision criteria for buildi ng owners and managers when choosing a specific indoor air management option? Significance of the Study Decision-making processes for IAQ issues in the building industry have been determined by the local and national regula tions that may not always guarantee the optimum decision. Building owners and mana gers or their representatives are not completely aware of the consequences of different indoor air quality management methods and decisions, and they may lack the means to identify the best solutions to IAQ problems. The significance of this study derives from the determination of the optimum IAQ options for commercial buildings in Florida. However the outcome model of this study and its methodology would also be used as a basis of similar buildingrelated decisions such as differe nt locations, different types of buildings, or even different management problems. From a wider perspective, th is research contributes to current sustainable building research in terms of quantifying the benef its of better IAQ in buildings, which would eventually help promote sustainable buildings. The research also aims to contribute to the clarification of arguments re garding the conflicts between IAQ and energy efficiency issues from a quantitative poi nt of view. In conclusion, defining a decision model for commercial buildings will help decision makers such as designers, contractors, or building owners and managers in making more sophisticated decisi ons regarding indoor air control technologies and st rategies. The model developed in this research may potentially help commercial building owners and managers build long-term savings by increasing the productivity of the workers and decreasing the losses due to worker health and performance problems.

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6 Assumptions and Limitations Indoor air problems in buildings can appear in many different types of buildings. However these problems are more common in co mmercial and institutional buildings due to their dense population. This study onl y focuses on IAQ management in new commercial buildings, where significant savi ngs can be generated by increased worker productivity and performance. There are several types of IAQ manageme nt options in commercial buildings. These options may include different technologie s with various initial and lifecycle costs. In order to limit the number of options, th is study concentrates on the following two categories: Improved Ventilation Air Cleaning There are various situation and considerat ions under which one or more options may be included, or excluded, as a candidate for IAQ control in a particular building. Although in some cases one of these approaches might be the only logical candidate, this research limits the research to buildings that would have the two above options as IAQ control techniques. More detailed descriptions of these and some other options are given in Chapter 2. In order to control the different fixed cost s, the study limits the an alysis to research on marginal costs. Marginal cost may be de fined as the change in cost per exposure where exposure would be (concen tration) x (number of occu pants) x (time) (Henschel 1999). This research only focuses on buildings that are not located in regions or zones where the outside air is a source of contamination such as industrial sites. It is also assumed that the number of occupants inside a building will not exceed the limits that are

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7 mentioned in ASHRAE Standard 62.1-2001 (Ame rican Society of Heating, Refrigerating, and Air-Conditioning Engineers [ASHRAE] 2001). The assumptions adapted while configur ing the optimization model are given below. Many of these assumptions aim to clarify the optimization model and set clear boundaries on the potential appl ications of the model. The cost data regarding the proposed energy cost calculati ons are based on equipment that runs on electricity. Simple modifications that ar e also mentioned in this study would provide calcu lation methods for other sources of energy as well. The cleaners considered are only the part iculate air cleaners with an average removal efficiency of 65% or greater as measured in ASHRAE standard 52.1-1992 (Henschel 1999). The model assumes that the total outdoor air (OA) ventilation will not go over 140 cfm assuming that above this value there would be additional fixed costs due to equipment replacement and/or upgrade. As default the overall Energy Efficiency Ratio (EER) for the cooling system is assumed to be 10 Btu/h/W. Overall efficiency of the heating system is assumed to be 1.0 Btu/h per Btu/h. (Users may use 0.7 for systems that work with gas) The assumption is that in Florida, on aver age over the cooling and heating seasons, all of the heat added to the air stream by the fan must be removed by the cooling system (Henschel 1999). The assumption is that the productivity cu rves for air cleaning and the amount of OA ventilation are independent from each other. However studies such as Wargocki et al. (2000) state that th e amount of pollution and the amount of ventilation are in fact corr elated when calculating the performance index. Yet there is not enough data to actually quantify this dependency. In the case of generation of these new data the model would become nonlinear. The assumption for the proposed cost cal culation methods is that the heating capacity range of the HVAC system is between 11 and 40 kW. The assumption is that the systems used in buildings have economizers where the required OA increase can be achieved w ithout enlarging the OA intake duct and without increasing the dimensi ons of the central exhaust ducting compared to initial design (Henschel 1999).

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8 The assumption is that if a dedicated-OA un it is to be installed in a new building, it will be designed to condition a ll of the OA entering the building. Organization of the Study The major outline of the research is expl ained in more detail in the following chapters. Chapter 1 introduces the problems regarding IAQ in commercial buildings, as well as lists the research questions, purpos e, limitations, and assumptions. Chapter 2 reviews the current literature that is releva nt to IAQ issues in sustainable buildings. Different techniques to contro l IAQ in commercial buildings, and the consequences of change in indoor air quality ar e also investigated in Chapter 2. There are many studies that demonstrate the importance of IAQ in commercial buildings and its effects on the occupants of a building. Chapter 2 covers some of these important studies in terms of their approach and results. Chapter 3, which includes the design of th e research as well as the tools and methods used in the study, briefly explores the methodology of the research. Chapter 3 also introduces the research questions and the research population. Chapter 4 covers the details of the methodologies for calculating the required parameters and introduces the developed IAQ decision model. The solution to the model and the sensitivity analyses along with the discussions of the solutions ar e presented in Chapter 5. Finally Chapter 6 presents an overall conclusion and the po ssible recommendations for future work.

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CHAPTER 2 REVIEW OF THE LITERATURE Introduction This chapter explores the existing literature relevant to sustainable buildings and specifically IAQ issues in commercial buildings. Buildings have significant impacts on the environment and their occupants duri ng construction, throughout their operation, and during end-of-life (decommissioning). The US Green Building Council (USGBC) defines green or sustainable building as a term that refers to design and construction practices that significantly reduce or elimin ate the negative impact of buildings on the environment and its occupant s through all life cycle pha ses of the building (USGBC 2003). This concept can be applied to de sign, construction, and operation of new buildings or renovations of existing buildings. The building industry is ever more focused on making its buildings more sustainable, which includes using healthie r, less contaminating, and more resourceefficient practices. Indoor environmental quali ty (IEQ) deals with the quality of the air and environment inside buildings, based on many different conditions that can affect the health, comfort, and performance of o ccupants. These conditions may include contaminant concentration, temperature, rela tive humidity, light, sound, and other factors (USEPA 2005a). It is important to note that a good IEQ is a vital element of sustainable buildings. Building owners, managers, occupant s, architects and bu ilders can all benefit from the increased IEQ in terms of minimizing the negative health e ffects, legal liability, and possible remediation cases. 9

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10 IAQ is a crucial segment of IEQ and has major impacts on the overall IEQ of a building. Improving IAQ involves to desi gn, construct, commission, operate, and maintain buildings in ways that decrease contaminant sources and remove contaminants while ensuring that fresh outdoor air is persistently supplied. Sustainability and the Built Environment The problem of sustainability should first be explored in order to provide a strong basis for the concept of sustainable buildings. The subject of a sustai nable future is taking place at the center of gravity of the tria ngle of environment, sociology, and economy. Environmental problems, the magnitude a nd frequency of which are continuously increasing, keep their place at th e agenda of many countries ra ther than being just a local concern. In order to find an answer to all of these worries, many different ideologies and hypothesis are being discussed in todays wo rld. One of these different proposals to determine the relation between nature, human, and the built environment is sustainability or sustainable development. Many definitions of sustainable developmen t have been offered, some general and some more precise. The following definitions are some examples. Development, which meets the needs of the present without compromising the ability of future generation to meet their own needs. (World Commission on Environment and Development [WCED] 1987, p. 43) Using natural renewable resources in a ma nner that does not eliminate or degrade them or otherwise diminish their renewabl e usefulness for future generations while maintaining effectively constant or nondeclin ing stocks of natural resources such as soil, groundwater, and biomass. (Wor ld Resource Institute [WRI] 1992, p. 2) The net benefits of economic development, subject to maintaining the services and quality of natural resources. (Goodland & Ledec 1987, p. 36)

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11 To generalize and simplify various defin itions, the definition of sustainability can be summarized as a system that delivers se rvices without exhausti ng resources over time. It uses all resources effici ently in an environmental, social and economic sense. In past years, sustainability has beco me a catchword capable of capturing the attention not only of environmental scientists and activists but also of some mainstream economists, social scientists, and policymakers. The reason for that is the sustainability of the human activity in the biggest sense de pends on technological, economic, political, and cultural factors, as well as on environmenta l ones (Holdren et al. 1995). According to this context, economists explain different ideas about sustainability. According to Lehner et al. (1999), a sustainable economy is one that is capable of continuously securing and reproducing the basis of its operation. This economy incl udes both the natural system from which the economy extracts all the re sources that it needs, and a variety of economic and social factors. These factors may include knowledge and skills, technology, social standards, and political st andards and regulations, which determine the capacity of an economy to generate wea lth and living standa rds in society. At this point instead of explaining all th e definitions of vari ous disciplines about sustainability a more convenient approach may be to refer to the ideas of McHarg (Kibert et al. 2002). He states that geologists, meteorologists, hydr ologists, and soil scientists were informed in physical science but not in real life; on the ot her hand, ecology and the biological sciences were only aw are of physical processes. He determined this problem as the lack of integration within the environmental sciences. Now one has to answer the question: How are all these discussions related to the built environment? That is the question various disciplines try to answer and come finally

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12 to the word of Sustainable Construction. Su stainable construction can be defined as the creation and maintenance of a healthy built environment using ecologically sound principles (Kibert et al. 2002) Many different concepts are involved in creating the healthy built environment. Energy, water, wa ste, materials, and IEQ are some of the concepts to focus on when creating and main taining a healthy built environment. Since this study concentrates on the IEQ issues in buildings the following sections will be exploring the relations between sust ainability and IEQ in more detail. Humans and Their Environment Human beings have always had a mental and physical rela tionship with their environment. Human beings themselves can be called a microenvironment and the environment around them a macro envir onment (Fitch & Bobenhausen 1999). The problem has always been to understand and balance the relations between these two environments. There were times throughout history that had extreme environmental conditions. There are currently regions in the world where sustaining a direct relationship with the natural environment is almost impossi ble. In fact there ar e only few regions in the world where people can survive w ithout developing an interface between themselves and nature (Fitch & Bobenhausen 1999). Fitch and Bobenhausen (1999) in their The American Building rename the te rm interface as the third environment. So what are the interfaces that people need in order to interact with the environment around them? The simplest answer to this question would be clothing. However, wearing clothes has not always sa tisfied people, so they also have created spaces such as buildings to live in. Controlli ng the environment of these spa ces rather than controlling the natural environment, has always been much easier. These comfort conditions for humans depend on the essential requiremen ts of their microenvironment. Several

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13 conditions that are listed below determine the metabolic level of relationship between humans and their environm ent (Fitch & Bobenhausen 1999). Thermal Aqueous Sonic Spatio-gravitational forces Atmospheric Luminous World of objects Adjusting these conditions according to th e specific individual needs forms the basics of the configuration of IEQ. This is one of the means used to create the essential conditions in the third environment and many issues have affected the use of this tool. These issues and their solutions that concerned humans have been constantly changing throughout the history. The discus sion on controlling the third environment is related to some other issues such as the use of science, technology and its integration in buildings. These issues are discussed in the following sections. Humans and Technology According to Heidegger (1976) the purpose held by human beings has always been to conquer the physical world in order to establish and extend the power and domain of the human race itself over the universe. However, human freedom and victory over nature has depended on the degree of knowle dge about the laws of nature. The pure knowledge of humans can be called science whereas the application of science is known as technology. Often the terms, tec hnology and science, are confused. Science deals with the natural world. Technology is the ap plication of natural laws, which govern the universe. This is not to say science and technology are unrelated. Science deals with "understanding" while technology deal s with "doing"(Heidegger 1976).

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14 Technology is a human activity. It is an act ivity in which human beings form and change natural reality for prac tical reasons with the help of means and methods. In his A Question Concerning Technology, Heidegger ( 1976) states that the manufacture and utilization of equipment, tools, and mach ines, the manufactured and used things themselves, and the needs and ends that they serve, all belong to what technology is. Modern science and technol ogy have been intentionally and methodically applied to every side of human existence. Heidegge r (1976) states that modern technology is something incomparably different than all ear lier technologies because it is based on modern physics as an exact scie nce. He concludes that modern science represents nature as a calculable coherence of forces. Nature at any case seems to have the most crucial significance when dealing with technology. Mc Cleary (1983) in his A n Interpretation of Technology clearly defines the relations between technology, human, and nature. He explains a persons fundamental activity as one of productive interc hange with nature. This productive interchange that we may call technology is defined as the communication between societies and their natural environmen ts in the production of the built environment. According to McCleary (1983), construction of a new nature, which is interposed between societies and original nature, is calle d supernature. Supernature is definitely a product of technology. A higher level of supernatural existence is super-supernature, which is the concern of hi gh technology. McCleary (1983) divides technology, which is an interconnection between the original nature and human, into three levels: High technology Middle technology Low technology

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15 McCleary (1983) explains the product of super-supernature as the concern of high technology. Low technology on the other ha nd is explained as a concern of those who wish to return to that earlier relation th at existed between societies and their natural environments preferably in a technologically underdevel oped region. McCleary (1983) claims that current practice of our prof essions is in the bondage of middle level technology to the exclusion of both high and low technologies. Heid egger (1976) states that more questioning of technology means th at the mystery of it reveals itself. Yet because of the more questioning of the tec hnologys essence, the more mysterious the essence of art becomes. Heidegger (1976) s hows the contradictions of human nature by stating that the feeling of danger helps hum an being become more questioning. Finally, Heidegger (1976) wants to emphasize whether the kind of reveali ng of Being that shows itself in the fine arts can rescue ma n from danger of enframing, which he defines as the essence of technology. So man has to rethink the meaning of modern science and technology. Humans and Buildings The relation of humans with buildings is related to the essence of architecture and building construction. It is esse ntial at this point to reme mber the purpose of buildings. Fitch and Bobenhausen (1999) define the ultimate task of architecture as activity in favor of human beings. They state th at the purpose of architecture is to maximize our capacities by permitting us to focus our limited energies upon those tasks and activities that are the essence of the human experience. To be able to understand the relation between the buildings and the occupying people we should also remember the essential n eeds of humans so that we will be able to understand the expected fundamental require ments about the buildings and the third

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16 environment they create. Th e relation of the human with the environment can be reviewed at two different levels, which are perceptual and metabolic (Fitch & Bobenhausen 1999). The conditions that determ ine the metabolic level of relation are already given in the Human and Their Envi ronment section. The perceptual level on the other hand, comes into play only after the metabolic level requirements are met (Fitch & Bobenhausen 1999). IEQ deals with controlling and adjusting th e third environment in a metabolic level. According to Fitch and Bobenhausen (1999) ther e are four stages of optimizing metabolic fit between building and its environment: Mechanical systems Enclosing membranes Buildings exterior surfaces Site Banham (1969) in his Architecture of th e Well-Tempered Environment discusses the environmental management in three different modes: Conservative mode Selective mode Regenerative mode Thick walls of a house in a hot climate hol d the radiation heat as a thermal mass during the day, and then, after sunset, the radi ation of the heat into the house helps to control the sudden chill of evening. This whole technique can be termed as Conservative mode of environmental mana gement. The Selective mode, on the other hand, employs structure not just to retain desi rable environmental cond itions but also to admit desirable conditions from outsi de (Banham 1969). However traditional construction has always had to mix these tw o modes, even without recognizing their

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17 existence, just as it has always had to in corporate the Regenerative mode of applied power without fully acknowledging its presence (Banham 1969). The Eskimo igloo displayed in Figure 2-1 is a good example for the conservative mode of environmental management. The shap e and material used to build the igloo signifies high-level environmental recogni tion and responsibility. The rounded shape provides maximum resistance and minimum exposed surface to cold winds while enclosing the most volume with the least ma terial. With no mechanical systems and no source of heat other than a sma ll stove, interior air temperatur es can be hold at a tolerable range. Figure 2-1. Historical design for the Eskimo igloo, Baffin Island, Canada. (Wikipedia 2006a). Another pre-industrial age example for the conservative mode of environmental management is the mud masonry Indian Hous e (Fig.2-2). The high heat capacity of mud masonry, well suited to the great environmental fl uctuations of the dese rt, is cleverly used in primitive housing. Although the air may be dry, when it becomes very hot ventilation may not be desirable. Native Americans bui ld freestanding brush-covered arbors for

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18 daytime shade, using houses for storage and cold weather sleeping while they used the rooftops for summer sleeping (Fitch & Bobenhausen 1999). Figure 2-2. Mud masonry Indian House (Fitch & Bobenhausen 1999). The Larkin Administration Building by Fra nk Lloyd Wright is th e first entirely airconditioned building on record (Banham 1969) It was built in 1904 and demolished in 1950 and was one of the early masterpieces of pioneer, modern architecture (Banham 1969). The Larkin Building is one of the good examples, which employ both selective and regenerative modes of environmental mana gement. The mechanical and architectural aspect of the whole environmental con cept is illustrated in Figure 2-3. A B Figure 2-3. Larkin Administration Building, Buffa lo, NY, 1906 by F. L. Wright A)Exterior photo, B)Isomet ric drawing (Banham 1969). In the late 80s, while the application of computer technology into buildings was the main theme of the building practice, Norman Foster Associates designed an innovative

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19 building in Hong Kong that is dominated by se veral environmental management ideas. In 1986, Hong Kong and Shanghai Banking Corpor ation Headquarters was built in Hong Kong by Norman Associates (Fig. 2-4). Flexible layout and systems such as raised floor system provide space for the distribution of serv ices and also help to cope with the issue of flexible functional design. Computer technol ogy is used in the building in order to control the sun scoops that are used to tr ack the sun location, together with mirrors positioned outside and on top of the building atri um to diffuse sunlight to different floors through the atrium and down to the plaza floor (Dobney 1997). The concept of energy efficiency in the Hong Kong Bank resulted in the sunshades on the external facades to avoid direct sun light into the building and to reduce the heat gain (Dobney 1997). A B Figure 2-4. Hong Kong and Shanghai Banking Headquarters, Hong Kong. A) Exterior photo, B) Floor plan (Dobney 1997). In 1997, Norman Associates built anothe r innovative design for Commerzbank in Frankfurt, Germany (Fig. 2-5). Commerzbank Headquarters is termed as the worlds first ecological tower (Fischer & Gr neis 1997). Commerzb ank Headquarters ventilation is provided by mechanical ventila tion and air extraction th at is used only on days with extreme conditions, and the outer offices are naturally vent ilated directly from

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20 the outside. The offices on the atrium side r eceive air from outside indirectly through ventilation flaps designed on the high glass walls of the garden facades. Just like the Hong Kong Bank, Commerzbank also integrat ed complex computer technology that controls the quantity of air pumped in, cut of supply to unoccupied spaces, sun shading, the opening angle of windows, and the release or lock of controls and regulators. Cooling on hot days is provided by a water-filled coo ling system and the cold water needed for cooling is produced by environmentally frie ndly refrigerating machines (Fischer & Grneis 1997). High heat insulation quality on the facades and glazing also has a positive influence on the energy efficiency of the building. Fluorescent tubes with daylightdependent regulation light the offices, a nd movement detectors automatically switch continuous lighting in the corridors and offices (Fischer & Grneis 1997). A B Figure 2-5. Commerzbank Hea dquarters, Frankfurt, Germany. A) Exterior photo, B) Natural ventilation diagram (Fischer & Grneis 1997). Similar to what Banham (1969) proposed earlier, Baker and Steemers (2000) categorized the modes of environmental management in contemporary buildings. They state that there are two modes of environmental management. The Selective mode

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21 includes designs that work with a combina tion of form and fabric operating in a calculated relationship with mechanical systems such as Hong Kong Bank or Commerzbank Headquarters. On the other hand, exclusive mode of environmental management separates the exte rior and interior environmen ts and employs mechanical services as the main controller s of the interior environment. The environmental management concep ts, techniques and their influence on building design, construction, and themes ha ve always been changing since humans created their third environment. Table 2-1 su mmarizes all these diffe rent approaches in the context of major issues a nd the building concepts in the world of buildings since the 1960s. Table 2-1.Historical progress of building issues and concepts. Decade Issues Building concept 1960s Sense of coolness, heating, ventilation, insulation, shading Mechanical systems 1970s Energy crisis Energy-efficient buildings 1980s Application of computer and high technology in buildings Intelligent and smart buildings 1990s Sick building syndrome Healthy, green buildings Twenty-first century Globalization towards sustainable development Sustainable buildings Indoor Air Quality (IAQ) in Commercial Buildings Commercial buildings can include office buildings, retail establishments, light manufacturing and assembly, re staurants, bars, etc. Commercial buildings, just like other types of buildings use HVAC systems in or der to provide a well-conditioned interior

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22 environment for the occupants. Unlike resident ial buildings, these buildings have a higher density of population and equipment. Consequently, managing a good IAQ in commercial building may be more challe nging than residential buildings. The major IAQ problems in commercial bu ildings include air borne particles, moisture, insufficient ventila tion, and odors and gases from ma terials, etc. It is more likely in commercial buildings that more moisture will be present due to the lack of fresh air and the inconsistency in humidity and te mperature control. Therefore commercial buildings have higher risks associated with mold and bacteria problems. Many office spaces have a number of toxic gas generating equipments such as computers, fax machines, copiers, and printers. This can si gnificantly impact th e quality of air in commercial buildings and the employees would be exposed to a variety and high concentration of contaminants for at least 8 hours per day in these buildings. Levels of carbon dioxide inside commercial buildings may also be higher due to lack of fresh outdoor air ventilation. This can possibly cause headaches and other health related problems among the workers. These effects and their details will be discussed in the IAQ and Health section of this study. Air quality in a space is determined by the quantity of air intake and also by other factors such as air conditioni ng, room function, etc. Intake air in general is provided by outdoor air (OA) and in some cases by re-circulating the existing air. However, recirculated air should be cont rolled in a manner, which would minimize energy use but also protect occupant health thus maintain acceptable levels for worker performance and productivity. The IAQ systems should be de signed by fresh OA intake strategies whenever it is possible. The reason fresh air intake should be used is that in many cases

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23 increasing OA should ensure a sufficient amount of dilution to reduce the concentration of pollutants. Natural ventilation is one of the possible ways to bring more OA into the building as long as the energy consumption of the building is still kept at an acceptable range. The amount of indoor air pollutants is co rrelated with different conditions that create the building such as the site, buildi ng materials, constructi on techniques, building type and use, occupant density, HVAC system and etc. The following four elements are involved in the development of IAQ problems (USEPA 2005b): Source: source of contamination or discom fort indoors, outdoors, or within the mechanical systems of the building. HVAC: the HVAC system that is not able to control existing air contaminants, not able to control conditions that help build up contaminants. Pathways: one or more pollutant pathways that connect the source of contamination to the occupants of the building and a dr iving force to move pollutants along the pathway(s). Occupants: building occupants who are present in the building. It is important to understand the role that each of the above factors may play in order to identify, prevent, and resolve IAQ problems. Standards, Regulations and Guidelines Currently, the Federal government in the USA does not regulate IAQ in nonindustrial settings. However, many state a nd local governments regulate ventilation system capacity through their building codes. Building code s have been developed in different states in order to promote healt hy and safe construction practices. There also professional associations, international health associations, industr y organizations, state governments, and private programs that develop recommendations or guidelines for appropriate building and equipment design and installation. These recommendations may

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24 play a mandatory role when state or local regul ations integrate them in to their code and regulation policies (USEPA 2005c). There is ge nerally a time delay between the change in new standards by professional organizations such as ASHRAE and the integration of those new standards as code requirements (USEPA 2005c). Below are some of the major tools, sta ndards, and regulations towards regulating IAQ in commercial buildings. Occupational Safety and Health Administration (OSHA). The agency proposed guidelines in 1994 towards regulating I AQ in non-industrial buildings. However on December 17, 2001 OSHA withdrew its IAQ pr oposal and terminated the rulemaking proceedings (OSHA 1994). The proposed I AQ regulations would have help (OSHA 1994): Ban smoking in the workplace or required employers to provide separately ventilated smoking areas. Develop IAQ compliance plans in non-industr ial work sites to protect workers from certain indoor air contaminants, inad equate ventilation, and sick building syndrome. Have periodic inspectio ns and air testing. Maintain written records including do cumentation of reported IAQ problems. Control for specific contaminants such as restricting the use of chemicals and pesticides. Have a good maintenance program. Conduct employee-training programs about IAQ. OSHA stated that integrating these regulat ions would have required an initial cost of $1.4 billion along with an annual cost of $8.1 billion to employers. These costs would have occurred due to increased and proper ma intenance of building IAQ systems as well as the increased operating costs. OSHA also estimated an annual $15 billion savings for

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25 employers due to increased employee produc tivity and reduced absenteeism (OSHA 1994). Although these proposed regulations cannot yet be enforced, they at least provide guidelines for those companies, which are willing to start a high-quality IAQ management program. The General Duty Clause of the Occupa tional Safety and Health Act requires employers to provide a safe and healthy work ing environment regard less of the proposed IAQ guidelines being in effect. It is also important to know that all workers are covered under federal OSHA. These regulations are enforced also at the state level in the 23 states including Florida. American Society of Heating, Refrigerating, and Air-Conditioning Engineers (ASHRAE). ASHRAE has noncompulsory ventilati on standards for commercial and industrial buildings. Howeve r ASHRAE standards become mandatory when local governments adopt the standards into their lo cal building codes. ASHRAE first published its Ventilation for Acceptable Indoor Air Quality 62.1 in 1973. ASHRAE Standard 62.11989 defined acceptable IAQ as the air in wh ich there are no known contaminants at harmful concentrations as determined by authorities and with which a substantial majority of the people exposed do not expre ss dissatisfaction (ASHRAE 1989). However, this statement could not gua rantee that no unpleasant hea lth effects would occur. ASHRAE Standard 62.1-2001 aimed to minimize the probability of adverse heath effects among building occupants. It became applicable to all occupied spaces except where other standards exist. ASHRAE Standard 62.1-2001, depending on the building function, recommended that 15 to 20 cubic feet per mi nute (cfm) of outdoor air should be supplied for each building occupant (ASHRAE 2001). Recently the 2001 standard has been

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26 replaced by ASHRAE 62.1-2004, wh ich specifies outdoor air requirement for an office as 5 cfm per person plus 0.06 cfm/ft 2 (ASHRAE 2004). In this la test version of ASHRAE Standard 62.1, requirements for the office may still remain the same in cases where the occupant density varies, or is indefinite at the time of the system design. However this recent ASHRAE revision as the first major revision to the ventil ation rates since 1989 appears to result in slightly lower outdoor air requirements for the office spaces (17 cfm/person). The reason for this reducti on in ventilation rates should be further researched to explore whether the motive towa rds this change derived from the effort towards reducing equipment capacities as well as the energy usage over the life of each mechanical system. New construction design and building operation plans should ensure that at least the minimum OA amounts recommended by ASHRAE Standard 62.1 are being followed to minimize IAQ concerns and associated discomfort and illness. Authorities may also consider writing these specifications into th e construction and buildi ng operation codes. Environmental Protection Agency (EPA). The EPA does not have any constitutional role in the enforcement of I AQ, other than issues regarding asbestos and radon. However, there has been a legislation pr oposal presented in C ongress that requires the EPA to create a voluntary program to certify indoor air contractors, but this legislation has never passed (Conlin & Carey 2000) The EPA has established a set of specifications for use in its own facilities to regulate the emissions from office furnitu re, equipment and other products. The specifications include regulations such as workstations cannot add more than 0.5 mg/m

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27 of total volatile organic compounds (VOC), 0.05 ppm of formalde hyde, and 0.1 ppm total aldehydes within one week of receiving and unpacking the furniture. Other guidelines. The American Conference of Governmental Industrial Hygienists (ACGIH) has created a manual called "Guidelines for the Assessment of Bioaerosols in the Indoor Environment". The manual provides the most important basic data on IAQ however it does not go into much detail. ACGIH also presents exposure limits for chemicals in the workplace, in a document called "Threshold Limit Values". This document is widely used in assessi ng whether excessive chemical exposure has occurred (ACGIH 1989). National Institute fo r Occupational Safety and Health (NIOSH) and National Ambient Air Quality Standard s (NAAQS) also published standards to regulate specific IAQ levels. The Air-Conditioning and Refrigeration Institute (ARI), which is an industry trade group for air-conditioning system manufactur ers, has created guidelines for design, installation, and maintenance of A/C systems. These guidelines provide some of the basic information one should know on these issues. Building codes. Building codes vary from place to place. These codes generally regulate IAQ by specifying the amount of OA th at is to be supplied by the ventilation system for commercial buildings. Additiona lly, these codes are often very specific on construction means and methods, which may af fect IAQ of a building such as carbon monoxide problems, moisture entry into the bu ilding, and re-entry of exhaust fumes. As a general rule, building codes are only enfo rceable during the cons truction and renovation processes. Code requirements may change over time as code organizations adapt to new technologies and information. However the buildings are usually not obligated to make

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28 modifications in their structure or the way th ey operate in order to conform to the new codes. It also a well known fact that many bu ildings do not operate in standards parallel with current building codes, or even with the codes they had to meet at the time of their construction (USEPA 2005c). State laws and regulations. In the absence of any action at the national level, several states took steps on th eir own to improve IAQ in bu ildings. At least 37 out of 53 states and territories have designated an I AQ contact person due to the increase in the number of complaints about SBS, also cal led building-related symptoms (Slap 1995). 45 states have laws prohibiting smoking in public buildings. Also 19 states limit or restrict smoking in private workplaces acknowledging th at tobacco smoke is a major indoor air pollutant (OSHA 1994). The Florida Building Co de (FBC) regulates IAQ in commercial buildings in Florida. FBC is based on th e 2003 editions of the International Building Code (IBC), International M echanical Code (IMC), and In ternational Plumbing Code (IPC). FBC mandates that: Ventilation units shall distribute tempered heated or cooled air to all spaces and shall supply outside air in the quantity of either the su m of all exhausts or 20 cfm per person whichever is greater. The quantity of all exhaust air must matc h the intake volume of all outside air. Supply, exhaust, and return fans shall run continuously wh ile the building is occupied. Areas in which smoking is permitted shall be well vented by at least 35 cfm per person to the outside in order to mi nimize smoke diffusion throughout the unit. The International Mechanical Code that is the base of ventilation regulations in FBC has the following statements re garding ventilation in section 403.3: No less than 15 cfm of outside air per occ upant is required for waiting room areas, based on the estimated maximum occupant load of 60 per 1,000 square feet.

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29 No less than 20 cfm of outside air per o ccupant is required for office areas, based on the estimated maximum occupant load of 7 per 1000 square feet. Although ASHRAE 62.1-2004 has change d the requirements for minimum ventilation rates in office spaces, the rates in IMC and FBC still remain to be parallel to ASHRAE 62.1-2001. However IMC is giving strong considerat ion for a change in the code towards synchronization with th e new ASHRAE 62.1-2004 standards. Sources of Indoor Air Pollutants Indoor air contaminants can start buildi ng up within the building itself. Although this study assumes that OA is not a source of contamination, pollutants can be brought from outdoors as well. If the pollution sour ces are not controlled, IAQ problems can begin, even if the HVAC system is accurate ly configured and well maintained. The USEPA categorizes the sources of indoor air pollutants as given below. The examples given for each category are not intended to be a complete list (USEPA 1991). Sources Outside Building o Contaminated outdoor air Pollen, dust, fungal spores Industrial pollutants General vehicle exhaust o Emissions from nearby sources Exhaust from vehicles Loading docks Odors from dumpsters Re-entrained (drawn back into the building) o Soil gas Radon Leakage from underground fuel tanks Pesticides Equipment o HVAC system Dust or dirt in ductw ork or other components Microbiological growth in drip pans, Humidifiers, ductwork, coils Improper use of biocides, seal ants, and/or cleaning compounds Improper venting of combustion Refrigerant leakage

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30 o Non-HVAC equipment Emissions from office equipment (VOCs, ozone) Supplies (solvents, toners, ammonia) Emissions from shops, labs, cleaning processes Elevator motors and other mechanical systems Human Activities o Personal activities Smoking Cooking Body odor Cosmetic odors o Housekeeping activities Cleaning materials and procedures Emissions from stored supplies or trash Use of deodorizers and fragrances Airborne dust or dirt (e.g., circ ulated by sweeping and vacuuming) o Maintenance activities Microorganisms in mist from improperly maintained cooling towers Airborne dust or dirt Pesticides from pest control activities Emissions from stored supplies Building Components and Furnishings o Locations that produce or collect dust or fibers Textured surfaces such as carpe ting, curtains, and other textiles Open shelving Old or deteriorated furnishings Materials containing damaged asbestos o Unsanitary conditions and water damage Microbiological growth on soiled or water-damaged furnishings Microbiological growth in areas of surface condensation Standing water from clogged or poorly designed drains Dry traps that allow th e passage of sewer gas o Chemicals released from building components or furnishings Volatile organic compounds or inorganic compounds Other Sources o Accidental events Spills of water or other liquids Microbiological growth due to flooding or to leaks Fire damage (soot, PCBs from electrical equipment, odors) o Special use areas and mixed use buildings Laboratories Print shops, art rooms Exercise rooms Beauty salons Food preparation areas

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31 o Redecorating/remodeling/repair activities Emissions from new furnishings Dust and fibers from demolition Odors and volatile organic and inorganic compounds. Depending on building location and characte ristics, several different types of contaminants can pollute the indoor air from the processing of or ganic and inorganic elements. Daniels (1998) cate gorizes these pollutants as: Gases and vapors (CO, CO2, SO2, O3, radon, formaldehyde, carbon-hydrogen) Odors Aerosols (inorganic or organic particul ates such as heavy metals and pollen) Viruses Bacteria and bacterial spores Fungi and fungal spores ASHRAE 62.1-2004 provides a ta ble that compares the acce ptable levels of indoor air contaminants by different agencies (Table 2-2). Table 2-2. Comparison of regulations and guide lines for acceptable contaminant levels Enforceable & regulatory levels Non-enforced guidelines NAAQS/EPA OSHA NIOSH ACGIH Carbon dioxide 5,000 ppm 5,000 ppm 30,000 ppm [15m] 5,000 ppm 30,000 ppm [15m] Carbon monoxide 9 ppm 35 ppm [1 h] 50 ppm 35 ppm 200 ppm [Ceiling] 25 ppm Formaldehyde 0.75 ppm 2 ppm [15 m] 0.016 ppm 0.1 ppm [15 min] 0.3 ppm [Ceiling] Lead 1.5 g/m [3 months] 0.05 mg/m 0.1 mg/m [10 h] 0.05 mg/m Nitrogen dioxide 0.05 ppm [1 yr] 5 ppm [Ceiling] 1 ppm [15 m] 3 ppm 5 ppm [15 m] Ozone 0.12 ppm [1 h] 0.08 ppm 0.01 ppm 0.1 ppm [ceiling] 0.02 ppm Particles <2.5 m MMAD 15 g/m [1 yr] 65 g/m [24 h] 5 mg/m 3 mg/m Particles <10 m MMAD 50 g/m [1 yr] 150 g/m [24 h] 10 mg/m Sulfur dioxide 0.03 ppm [1 h] 0.14 ppm [24 h] 5 ppm 2 ppm 5 ppm [15 m] 2 ppm 5 ppm [15 m] Total particles 15 mg/m (ASHRAE 2004).

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32 Many of the indoor pollutants can be avoided by increased OA ventilation as long as the outdoor air is not po lluted. However the building materials inside the building can be the source of contamination as well. Daniels (1998) lists the sources of the worst contaminants as follows: Insulating paints Adhesives of all kinds Floor coverings Suspended ceilings Jointing compounds Insulating materials Pre-fabricated materials Wood preservatives Raised floors IAQ Control Techniques Efforts towards improving IAQ may include different strategies depending on the nature of the problem. Henschel (1999) a pproaches the control techniques in three categories for reducing the concentra tions of indoor air pollutants: Improved ventilation: Increas es in the quantity of outdoor air (OA) supplied to a building, and/or improvement in the di stribution and mixing of the supply air throughout the various zones in the building. Air cleaning: Devices mounted in the central HVAC ducting, or self-contained devices mounted in the occupied zones, to remove contaminants from the air. Source management: Removal of all or part of the source, replacement of the source by a lower-emitting alternative, treatment of the source to reduce emissions, relocation of the source or relocation of the occupants. In some situations it may be difficult for the decision-makers to choose which one(s) of these options to use. When there is a localized source of contaminant Henschel (1999) suggests using a logic diagram presen ted in Figure 2-6 that may help select a specific IAQ control option. He nschel (1999) helps users by asking yes or no questions regarding the source of contamination and directs the users towards one of the options.

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33 Figure 2-6. Logic diagram for selecting an I AQ control approach (Localized problem resulting from sources inside the building) (Adapted from Henschel 1999).

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34 According to a 1987 NIOSH survey, 52 out of 100 buildings with IAQ problems suffered from mainly inadequate ventilati on (Seitz 1989). Accord ing to the same study, 16% of the buildings suffered from indoor contaminants where 10% suffered from outdoor contaminants (Seitz 1989). These numbers clearly indicate that many IAQ problems derive from within the building and its indoor air management systems. Manufacturers have been working on genera ting more advanced products for a better ventilation technology. One example is a ve ntilator manufactured by Honeywell called Perfect Window This ventilator is a heat recovery ventilator, which is structured as a pair of insulated ducts run to an outside wall. This ventilat or recovers the moisture and heat from the outgoing air in winter times, and removes it from in-coming air in the summer 1 Another important issue in controlling the IAQ in a commercial building is to be able to monitor IAQ constantly (Bas 1993). For this reason, manufacturers like Honeywell and some other companies have introduced more efficient and easy to use handheld CO2 monitoring devices. Monitoring CO2 levels is vital since studies show that at levels beyond 1,000 ppm occupants can experience health problems and general discomfort, making it more difficult for them to think and work (Bas 1993). The health effects of IAQ problems are discussed in more detail in the IAQ and Health section. Ventilation: All buildings require a certain amount of OA. The outdoor air may need to be conditioned (heated or cooled) before it is distributed into the occupied space depending on the specific climate. Bringing OA into the building allows the indoor air to be exhausted or to escape by passive re lief, which aids to remove indoor air contaminants. The types HVAC systems range from independent units that serve 1 More information available online at http://www.honeywell.com/sites/acs/

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35 individual spaces to large central systems serving multiple zones in a building (USEPA 1991). The components of a t ypical HVAC system are gi ven in Figure 2-7, which illustrates the general rela tionship between many components of an HVAC system. However it is important to note that many variations can be possible. Figure 2-7. Typical HVAC system components (USEPA 1991). The EPA categorizes different HVAC systems as follows (USEPA 1991): Single zone systems Multiple zone systems According to the EPA, a single air-handli ng unit can serve more than one building area if the areas served have similar HVAC requirements. This would also be possible if the control system can compensate for differences in HVAC needs among the served spaces. Areas regulated by a common control are referred to as zones (USEPA 1991).

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36 Multiple zone systems can provide each zone with air at different temperatures by heating or cooling the air stream in each zone. Alternative design strategies involve delivering air at a constant temperature wh ile varying the volume of airflow, or modulating room temperature with a supplem entary system (USEPA 1991). Constant volume systems, on the other hand, generally deliver constant amounts of air to each space. These systems often operate with a fixed minimum percentage of OA or with an air economizer feature (USEPA 1991). Rather than by changing the air temper ature variable air volume (VAV) systems maintain thermal comfort by changing the amoun t of heated or cooled air delivered to each space. However, many VAV systems al so have requirements depending on the characteristics of the weather, such as rese tting the temperature of the delivery air on a seasonal basis. Underventilation often happens if the system is not arranged to introduce at least a minimum quantity of OA as the VAV sy stem throttles back from full airflow, or if the supply air temperature is set too lo w for the loads in the zone (USEPA 1991). Overcooling or overheating can also occur in a zone if the system is not adjusted to according to the cooling or heating load (USEPA 1991). Most commercial buildings use VAV systems for ventilation (Public Interest Energy Program [PIER] 2005). However the main reasons VAV systems are used in commercial buildings derive from the financial constraints. In 1970s before the energy crisis, a different system was used in order to bring constant air vo lume into the building spaces however the air was at variable temp eratures. This system brought substantial quantities of OA to the building. However wh ile energy efficiency has become a more important concept, this system became less popular due to its expensive operating

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37 (energy) costs. The VAV system on the other ha nd brings in only the amount of air that is necessary and re-circulates a buildings already conditioned air at various quantities. Although a VAV system saves energy, re-circulati ng air thus increasing the amount of air contaminants is the price that it pays for t hose savings. This is one of the good examples of the contradiction between IAQ and energy e fficiency. The true costs of IAQ issues are discussed in more detail in th e IAQ and True Costs section. Air cleaning: Air cleaning is one of the IAQ control techniques. The air filter is a product that has been around for many years and still is one of the most crucial parts of a buildings IAQ management system. There ar e currently many different types of air filters in the market that provide different protections and methods for different types of contaminants. Many buildings use poor performance of 89% filters, which are used to protect the HVAC system but not the occupant s of the buildings. According to ASHRAE (1999), the performance of these filters on filt ering dust and similar contaminants is only 7 to 12% effective. Burgess et al. (2004) categorize the filters into three categories: Fibrous and Granular (Media) Filters: Remove large particles before a second stage collector of greater efficiency and filters the dusts that cannot be easily collected by other collectors. High Efficiency Particle Air (HEPA) Filte rs: These filters are used extremely high particle collection is required such as in hospital operating ro oms. This type of cleaners are not cleanable and have low dus t capacity which limits their use to gas streams with low dust loading. Fabric Filters: These are the most comm on type of filters in the industrial environments. They must be eventually cleaned. Another method for cleaning air is electrosta tic precipitators. This type of cleaner collects particles by electromagnetic action. Th ese cleaners have the advantage of less maintenance but can pose a different threat due to ozone production (Stein & Reynolds 1992).

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38 The most challenging part of the air-cleaning problem is the selection of the type of filter or the cleaning device to be used. Different contaminants may require different types of air-cleaning devices. Thus the selection of the de vice demands the knowledge of the type of contaminants to be removed. Burgess et al. (2004) summarizes the basic information about the colle ction device in Table 2-3. Table 2-3. Collection de vice characteristics. Collection Device Type Types of Contaminants Initial Cost Operating Cost Durability Filters Industrial HEPA All dry powder Pre-cleaned air Moderate Moderate Moderate High Good Fair to Poor Electrostatic Precipitators Single Stage Two Stage Flyash, H2SO4 Welding Fume High Moderate Low Low Fair Good Wet Scrubbers Venturi Scrubber Wetted Cyclone Chemical Fumes Crushing, grinding Low Moderate High Moderate Good Good (Burgess et al. 2004). Contaminant source management: One of the control t echniques when dealing with air contaminants is to manage the contaminant source. This may involve several approaches (USEPA 1993): Source removal: This strategy involves identifying a source of contamination and relocating it therefore it will not affect the IAQ. Examples include not keeping garbage in spaces with HVAC equipmen t, and replacing moldy materials. Source substitution: This strategy involves identifying a material likely to impact the IAQ of the building and selecting a similar but less toxic substitute. For example choosing latex paint in stead of oil based paint. Source encapsulation: Encapsulation invol ves creating a barrier around the source and isolating it from other areas of the build ing so that there is no recirculation of air from the contaminated area into occupi ed spaces. This may include isolating a division of the building with polyethylene sheeting as well as isolating the space from the general ventilation system by blocking return air grilles.

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39 IAQ and Health Following the energy efficiency tren d in 1970s, many concerns about the occupants health in buildings started to arise due to low i ndoor air quality of commercial buildings in 1980s. Government agencies, university groups, and private consulting firms started to receive an increas ing number of requests to inve stigate health complaints specifically in office spaces. This led to a whole new syndrome, which is called Sick Building Syndrome (SBS). SBS is defined as a group of symptoms that are twoto threefold more common in those who work in la rge, energy-efficient buildings, associated with an increased frequency of headaches, lethargy, and dry skin. Clin ical manifestations include hypersensitivity pneumonitis (alveolitis extrinsic allergic), allergic rhinitis (rhinitis, allergic, perennial), asthma, infec tions, skin eruptions, and mucous membrane irritation syndromes (Segen 1992). A 1984 World Health Organization Committee report suggested that up to 30 percent of new and remodeled buildings worldwide may be the subject of excessive complain ts related to poor indoor air quality (IAQ) (American Lung Association [ALA] 2000). Although the most common site of injury by airborne pollutants is the lung, acute effects may also include non-respiratory signs and symptoms, which may depend on the toxicological charac teristics of the contaminant substances (ALA et al. 1994). Although many studies prove that indoor air contaminants can have various health affects on the occupants, there is still an on-going argument on the validity of several studies such as the health affects of mold. Along with many studies indicating a relationship between the several symptoms of occupants and allergic pollutants such as mold, there are also some studies claiming th at this has not been scientifically proven. However it is already acknowledged by the scientific community that there are many

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40 other indoor air pollutants that can cause low to severe health problems. According to Gamble et al. (1986), buildings where alle rgies are suspected present a difficult diagnostic challenge. Gamble et al (1986) believe that only a few people may be affected, and an allergic diagnosis may be overlooke d when building occupants have complaints about insufficient outdoor air supply, thermal discomfort, or cigarette smoke. Allergic symptoms can be relatively mild and nonsp ecific, and may have disappeared by the time a worker visits a physicians office. Some of the findings of Gamble et al. (1986) in a study where they evaluated a 9-story office building and compared the results to the outside air provided per person are given in Table 2-4. According to Table 2-4, the SBS symptoms as well as the thermal discomfort reaches to the highe st rates, on the 2 nd and 3 rd floors where no outside air (OA) was provided for 175 workers. Table 2-4. Complaints on floors w ith outside air provided per person. n=Number of occupants Floors 8-9 n=56 Floors B-1 N=42 Floors 6-7 n=155 Floors 4-5 n=131 Floors 2-3 n=175 Chronic Bronchitis Symptoms 12% 5% 6% 6% 7% 3 or more SBS symptoms 26% 26% 15% 20% 36% Sinus Symptoms 40% 36% 25% 31% 46% Thermal Discomfort 76% 84% 73% 67% 89% OA (cfm/person) 126 72 28 14 0 (Gamble et al. 1986) IAQ and True Costs Indoor air quality has financial consequences as well as its health affects. The cost of an IAQ management option is associated with two different types of costs. These costs can be categorized as hard and soft costs.

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41 Hard costs in the building industry is a term for the amount that includes total land and construction costs (Environmental La w Institute [ELI] 2005) In addition hard costs associated with indoor ai r quality would be the life cycle costs (LCC) of managing the indoor air quality in a building. LCC of a specific system should include the owning and the operating costs. Owning costs of a system include (Rizzi 1980): Initial cost of the system Capital recovery Interest and return on the investment Property taxes Insurance Operating costs of a system include the following costs: Fuel and energy Maintenance allowances Labor for operation Water costs Water treatment cost Rizzi (1980) explains how LCC analysis should be conducted for any heating, cooling, and/or ventilating systems. Rizzi (1980) states that when studying owning and operating costs of a system, the period coveri ng the lifetime of the system should be 20 years. Rizzi (1980) also pr ovides a methodology to calculate the owning and operating costs of an HVAC system. Soft costs in the building industry are known as architectural, engineering, and legal fees as differentiated from land or cons truction costs. However soft costs in general represent any costs that are not related to the actual land and construction costs. Consequently soft costs of a specific IAQ management opti on include costs associated with productivity, health, insura nce fees, litigation, etc. Unfortunately many investors or

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42 building owners usually do not see major in centives in considering the soft costs associated with poor or good IAQ. One of the most important soft costs of IAQ is productivity. Productivity and its financial consequences become a more im portant issue in commercial buildings. Worker salaries constitute the major cost of operati ng a commercial building, generally estimated at over 90% of the total oper ating cost, so that even a small increase in employee productivity can substantially increase a company's financial return (AIASF 2001). According to the study conducted by the US Department of Energy (USDOE) and Lawrence Berkeley National Labs in 1997, the costs of lower productivity for the US economy ranged from $12 to $125 billion per year (Damiano 2005). Another survey conducted by Reel Grobma n & Associates (2005) among interior design and facility planning decision-makers indicates that the re spondents feel that overcrowding, followed by IEQ complaints have the greatest negative impact on employee productivity (Damiano 2001). According to the report, 40% of the respondents said that overcrowding had the greatest nega tive effect, while 31% cited noise. Poor indoor air quality (19%) and poor lighting (10%) were among other factors cited by those surveyed. 74% of the respondents said they felt that workplace envi ronmental conditions were critical to employee productivity, while the rest said those conditions had some impact (Reel Grobman & Associates 2005). Very often, building owners or managers propose cost-saving measures without considering the added costs due to lowered performance and productivity. An example of this occurred when the Building Owners a nd Managers Association (BOMA) presented to members about its success in beating b ack two provisions in ASHRAE Standard 62.1.

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43 The article was published in BOMA's memb er newsletter SkyLines (Bas 1993). The two provisions that were discussed by BOMA would have required renovation areas to be secluded from the rest of the building by us ing negative pressure and mandated a 48-hour period for purging contaminants from t hose areas following construction (Bas 1993). BOMA stated that these requirements were ha rd to implement and also would have cost building owners about $0.10 per ft for the first provision and $0.01 per ft for the second. According to the BOMA analysis, rejecti ng those provisions w ould save a building owner approximately $11,000 for a 100,000-ft building 2 However, BOMA's analysis did not take the loss of productivity (soft cost ) into consideration. This soft cost would increase if pollutants from construction activit ies were drawn into th e occupied space of the building. This has been a factor in numerous IEQ cases and was the principal cause of the problems 10 years ago at the headquart ers of the EPA (Bas 1993). This type of situation may also result in people being injured and thus may result in multiple lawsuits. But according to Bas (1993) just a small pos itive effect on productivity in a typical 100,000 ft commercial building c ould save more than sign ificant amounts of money. If we consider a building with an occupant density of 5 persons per 1,000 ft this would result in a total of 500 peopl e in the building. If an aver age annual salary of $30,000 were assumed for each person in that building, this would be a total biweekly salary of $576,923. If construction activ ities cause IEQ degradation th us the productivity decreases by 0.5%, this would be result in a loss of $2,884 every two weeks that the situation existed. 2 More information can be found online at http://www.boma.org/

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44 Wargocki et al. (2000) conducted a study in order to evaluate the correlation between IAQ and productivity in an office space. In order to define the performance index Wargocki et al. (2000) defined four major tasks for the subjects of the study. The subjects throughout different exposur es of IAQ, were asked to perform simulated office work consistin g of four different tasks: text typi ng, addition, proofread ing and creative thinking. Wargocki et al. (2000) calculated and nor malized the average number of characters typed per minute, average number of correctly completed arithmetical calculations (units) per hour, and average number of lines that were correctly proof-read per minute. Performance was measured in three independent studies with differe nt subjects and could have been influenced by group differences in the subjects experience intellectual skills, and level of practice. The nor malization factors were the ratios between the mean of performance at all air quality le vels in all three studies to th e means of performance at all air quality levels in each individual study. To estimate the overall performance of simulated office work, the Wargocki (2000) calculated a performance index by dividing norma lized performance at a specific level of air quality by the mean of normalized performa nce of a specific task at all air quality levels. The findings of Wargockis study clearly display the importance of IAQ in office buildings. Figure 2-8 shows an overall summar y of the results of the study and displays how productivity index increases when the ve ntilation rate increas es and the pollution load decreases.

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45 Figure 2-8.Overall performance of simulate d office work as a function of sensory pollution load and ventilation rate (outdoor air) (Wargocki 2000). One of the other soft costs associated with IAQ is the economic loss created by health problems. In OSHA's effort to estab lish ventilation rules for nonindustrial workers, they used the following justifications, in part 3 : The Agency estimates that the excess risk of developing the type of non-migraine headache, which may need medical attention or restrict activity, which has been associated with poor indoor air qua lity, is 57 per 1,000 exposed employees. In addition the excess risk of developing upper respiratory symptoms, which are severe enough to require medi cal attention or restrict act ivity, is estimated to be 85 per 1,000 exposed employees. These numbers are extrapolated from actual field studies and therefore show the magnitude of the problem at present (OSHA 1994, p. 63). This amounts to an estimated average excess risk of lost work-time or diminished productivity for approximately 6% of workfor ce, on any given day, in any facility that exhibits poor indoor air quality (Damiano 2001). Additionally, approximately 9% are estimated to be at excess risk and would proba bly incur lost time due to upper respiratory sickness (Damiano 2001). In the same La wrence Berkley/USDOE study mentioned 3 On December 17, 2001 OSHA with drew its indoor air quality proposa l and terminated the rulemaking proceedings, see Federal Register 66:64946.

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46 earlier, it is estimated that the direct cost to the U.S. economy due to increased allergies, asthma and SBS symptoms were $7 to $23 billion per year (Damiano 2005) Damiano (2001) claims that a large portion of these co sts are estimated to be in the form of workmen's compensation claims, health care in surance premiums and direct health care costs mostly borne by the claimants' employers. Milton et al. (2000) conducted one of the studies that focus on how employers need to strike a balance between the energy costs of providing higher ve ntilation rates and the health benefits from higher ventilation rates. The researchers of this study analyzed the sick leave records of 3720 hourly workers fo r the calendar year of 1994. They used a statistical technique called Poisson regression to analyze the relati onship of sick leave with ventilation rate category. The results generated by this study, when the ventilation rate is increased by 25-cfm per person, are given in Table 2-5. The results indicate that by increasing the ventilation rate by 25-cfm up to 50-cfm/person employers can save up to $400 per employee assuming $40 hourly compensation rate. Table 2-5. Potential economic costs and benef its of increasing vent ilation rate by 25 cfm per Person. Criteria Annual savings per employee Energy Costs 25 cfm/ workers x $3.22/cfm/year $80 Sick Leave Costs Sick Leave avoided (1.50 days per workers) -$480 Total Savings -$400 (Kumar & Fisk 2002) IAQ related litigation cases are increasing along with the awareness of the effects of poor IAQ in buildings. One of the buildings that exhib ited the classic symptoms of SBS was the DuPage County Courthouse in Wheaton, IL (Bas 1993). Bas (1993) reports that one day in 1992, 25 employees were rushed to the hospital, suffering from shortness

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47 of breath, headaches, and nausea. The f our-story, $50 million building was closed temporarily, affecting some 700 employees. Th e main problem with the courthouse as it is with many other buildings with SBS, wa s inadequate ventilation. The county in this case sought $3 million in damages for the desi gn, engineering, and construction of the building (Bas 1993). Another sick building wa s the Polk County C ourthouse in Central Florida. The building was opened in the summer of 1987 at a cost of $37 million. Due to IAQ problems, the building was shut down, and the remediation of the building realized at a cost of $26 million (Bas 1993). Public attention and the litigation cases about IAQ issues have been continuously increasing. The major reason for this incr ease is due to the growing belief among employees that the employers owe them a sa fe and healthy working environment. Many of the employees believe there is a higher possibility of winning this type of litigation cases when there is a third responsible pa rty involved. This may include anybody that is involved in the design, construc tion or operation of the build ing. This list may include HVAC engineers, contractors, subcontracto rs, property managers, building owners, and designers as the major targets in IAQ related liability cases. Optimization of IAQ The continuous demand for sustainable and higher performance buildings has resulted in the development of more sophisticated and efficient technologies. The main goal of this development is to create bette r buildings that would satisfy many different performance criteria. Papamichael (1998) describes the decision-making process in relation to performance predic tion and evaluation for design options in high performance buildings in Figure 2-9. According to Fi gure 2-9 building design is the iterative generation of alternative course s of actions in the form of technological combinations and

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48 the prediction and evaluation of their performance. According to Papamichael (1998), building performance is considered and communicated through the use of performance indices, or parameters, based on the values of which designers judge appropriateness. Some of these might include measures su ch as aesthetics, ec onomics, and comfort. Figure 2-9. Building design decisions require performance prediction and evaluation with respect to multiple performance c onsiderations (Papamichael 1998). Atthajariyakul and Leepha kpreeda (2004) conducted a st udy that presents another example of parameter generation to measur e Indoor Environmental Quality. They use well-known parameter indices to quantify the degree of thermal comfort and air quality for human and energy usage in an HVAC system These parameter indices are directly or indirectly defined in terms of time-depende nt variables of the indoor-air condition in building. An example of parameter generation by the use of Predicted Mean Vote (PMV) and its indication as a thermal sensat ion index is given in Figure 2-10. Figure 2-10. PMV and thermal sensation (Atthajariyakul & Leephakpreeda 2004).

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49 There are several studies that concentrated on optimizing IEQ. Some of these studies have concentrated on multi-criteria optimization by taking many concepts of IEQ into consideration. The most studied items in the optimization studies are building shape, thermal comfort, IAQ, and aesthetics. Al-Homoud (1997) used the direct search optimization technique in order to optimize the building envelope. His study consisted 14 variables and used an external simulation program to perform the optimization. Nielsen (2002) developed an optimization system by using Matlab to find the optimum combination of the geometry and mix of building components to maximize building performance. Caldas and Norford (2002) used a genetic algorithm (GA) 4 as response generator in optimal sizing of windows for optimal heating, cooling and lighting performance. Additional exampl es of building envelope optim ization for thermal comfort and energy savings can be reached at Marks (1997). Bouchlaghem (2000) also presents examples for optimization studies developed for environmental technology in buildings. Wright (2002) presents an example for HVAC system optimization by using GA to examine the trade-offs between HVAC system costs and thermal discomfort. Gustafsson (2000) also studied optimization of HVA C systems, by mixed integer linear programming. Linear programming (LP) has been used to solve optimization problems in industries as diverse as banking, education, forestry, and construction scheduling and planning. LP has been used as a tool to determine the optimal allocation of limited resources in linear and deterministic problems. In a survey of Fortune 500 firms, 85% of those responded said that they had used linear programming (Winston 1993). Kumar et 4 A genetic algorithm is a search technique used in computer science to find approximate solutions to optimization and search problems. Gene tic algorithms are a particular cla ss of evolutionary algorithms that use techniques inspired by evolutionary biology (Wikipedia 2006b).

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50 al. (2003) have also studied various successf ul applications of the use of linear programming in construction projects. One of the most challenging issues in IAQ modeling derives from energy efficiency constraints. One of the reasons for this is because the HVAC systems are subject to time varying boundary conditions, and that the system operation must be optimized at each boundary condition. Wright et al. (2002) in their work on optimizing HVAC system design, optimized the model fo r 9 boundary conditions that represent a period during the early morning, midday, and af ternoon, in each of three seasons: winter, fall/spring, and summer. Wright et al. (2002) in their study seeks to minimize the annual energy use of the system. However they ta ke the annual energy use as a weighted average of the system capacity at each of the 9 operating conditions, the weights being applied in accordance with th e relative proportion of the pr evailing climatic conditions. Wright et al. (2002) configure the decision variables in a wa y to investigate the pay-off between the HVAC system energy cost and the occupant thermal comf ort. Wright et al. (2002) also gives interesting examples for di fferent pay-off situations such as the one between capital cost of a system and the operating cost of a system. Figure 2-11 is an illustration of the function between these different costs. Figure 2-11. Example pay-off char acteristic (Wright et al.2002).

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51 Wright et al. (2002) group the decision variables under two categories: system operation and size of the HVAC system. Wright et al. (2002) specify three optimization criteria: The operating cost of the HVAC system for the design days The maximum thermal discomfort during occupancy on each design day The infeasibility objective The constraints in the study can be summarized as follows: Restriction on design of the coils Performance of the supply fan Requirements to ensure that the system has sufficient capacity Air velocity to limit noise Water velocity limit to prevent excessive pipe erosion Fan speed Volume flow rate through the fan HVAC capacity to meet required supply air temperature and flow rate Although there are some successful examples of optimization for different aspects of indoor air quality, none of these studies look at the problem from the building owner and manager point of view. Thus these studies generally ignore the soft costs associated with the various values of decision variab les. Many of the previous studies are constructed for optimization of system co mponent design thus they rely on mostly technical engineering variables and constraints. This res earch approaches the problem as a prescreening of the sustainable manageme nt problem and simplifies the engineering calculations since the goal is not to find the optimum com ponent design but to find the optimum comparison of alternative values in relation to their performance change and associated cost per change in air quality. Review of Literature Summary The body of knowledge for IAQ has been expanding tremendously since the1980s. Many studies have been conducted. However th ere are still gaps in our knowledge of

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52 IAQ in buildings. European Commission (1996) listed a comprehensive list of recommendations for the resear chers and the industry in or der to improve indoor quality and energy efficiency of buildings. Some of the areas that require further research could be listed as follows: Contaminants and sources: Identify contam inants and occurring occupant exposure, safe and acceptable emissions, safe and acceptable levels of contaminants in buildings, contaminant sources, and contaminant source management. Building assessment: Assess the built environment from energy, indoor air quality, and climate aspects. Building systems: Identify cost-effective low energy systems for providing high quality IEQ levels. Performance measurement: Identify simple, and effective methods that include both energy efficiency and IAQ measures, for predicting the performa nce of buildings. Operation and maintenance of buildings: Identify the effectiveness of means and methods of assessing and controlling existing buildings, including measurement techniques to quantify the levels of IAQ. Changes to building design and operation: Identify the problems with IAQ caused by the force to reduce energy consump tion, and identify strong optimization solutions. Experimental data: Generate data that can be used for st atistical correlation analyses for factors affecting IAQ, as well as data quantif ying productivity in relation to air cleaning and ventilation rates.

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CHAPTER 3 METHODOLOGY Introduction The objective of this research is to de velop a decision model for optimizing the control of indoor air pollutants in commercial buildings in Fl orida. This chapter briefly describes the nature of the research and the specific methods and concepts that satisfy the research goals. After exploring the research questions, in the research design section, the scope of the research and its main steps are discussed. The research methodology section briefly discusses the use of linear programm ing as a tool to solve the optimization problem. This chapter also clarifies the target populations that are th e subject of research or who may benefit from the decision model. The details of the steps taken in the methodology of this research a nd the detailed configuration of the research model and parameters are given in Chapter 4. Research Questions The major research question to be investigat ed in this disserta tion is given below: Can an optimization model be developed to select the optimal IAQ measures in commercial buildings in Florida to meet or exceed the standards required by code? This study also explores the an swers to the following question: What are the decision criteria for buildi ng owners and managers when choosing a specific indoor air management option? 53

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54 Research Design The summary of the scope of the research and the outline of the dissertation is given in Figure 3-1. Figure 3-1. Research design.

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55 The steps that are illustrated in Figure 3-1 are explained below in more detail. Step 1. Identify the indoor-air-pollutant-rel ated IAQ hurdles of the building industry. One of the hurdles that the building industr y is facing is to manage the quality of indoor air. This problem occurs due to fina ncial constraints and the trade-off between better indoor air quality and energy efficiency of a buildi ng. Some of the consequences of a better IAQ are healthy, clean, and sustainable air and air systems. The IAQ related cautions should be considered from the de sign of the project through the construction, and the postconstruction (operation) phases of the building. Industr y is facing several problems on each of these phases. This dissertation conducts a broad literature search in order to examine these hurdles under two categories: Identify the indoor air pollutant threat s for the buildings and its occupants. Identify the problems regarding the curre nt indoor air qual ity technologies in commercial buildings. This research first identifies the abov e problems of the building industry by using qualitative research through broad literatu re review (See Chapter 2). Many studies present the problems regarding the current I AQ technologies in the buildings. There are also studies that show the fi nancial consequences of poor IAQ in buildings. This study defines these problems in terms of their soft and hard financial consequences. One of the alternative methodologies for this step of the research could be conducting a regional survey among the subjects of the rese arch in Florida. Building Owners and Managers Associati on (BOMA) would be an adequate source of subjects. This would help clarify the specific IAQ rela ted technical and qualita tive problems of the industry.

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56 Step 2. Evaluate the types of IAQ options to control indoor air quality and the factors that affect IAQ in commercial buildings. Types of IAQ control techniques and the factors that affect the IAQ in commercial buildings have already been desc ribed in Chapter 2. This step of the research ensures that the model to be created includes a solution th at takes all the factor s affecting IAQ into account. The comparison of the available techno logies with the optimal solutions in the model enables the researcher to make suggest ions towards systems that may not exist but would be a better option than any existing syst ems. The types of indoor air quality control techniques will include: Improved ventilation Air cleaning This study evaluates the above options in terms of their tech nology, physical effects on IAQ, and the operational factors such as the policies and regulations. This study includes the national ASHRAE Standard 62.12001 for acceptable indoor ventilation as a lower constraint assuming that the Florida Bu ilding Code mandates a ll buildings to meet or exceed values mentioned in these standards. Step 3. Evaluate the true costs of ind oor air quality control techniques by combining LCC analysis, and soft and hard costs. Combining the lifecycle costs, other hard co sts, and soft costs generates the true costs of indoor air quality c ontrol. From an engineering perspective, LCC are all costs from project inception to disposal of e quipment. The LCC analysis includes the ownership and operating costs and uses comm on value engineering procedures such as described in Isola (1997). However the users of the model will be able to choose the values such as discount and inflation rates.

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57 The required cost parameters and the met hodology to help users carry out the cost analysis is provided by an EPA study A Pr eliminary Methodology for Evaluating CostEffectiveness of Alternative Indoor Air Qu ality Approaches by Henschel (1999), and by the actual supplier quotes for the system components. The analysis includes determination of two diff erent types of costs: Soft-costs Hard costs There are three areas of soft costs that e ngineers and their clients need to consider in the design for acceptable IAQ in any bu ilding project: the impact on productivity of the occupants, positive or negative; effects on health of the occupants, positive or negative; and the risk of litigat ion and/or legal liability that may result from any negative impacts. The most compelling category out of three areas is the one associated with worker productivity. In order to calculate the soft costs, this research uses the results of a study by Wargocki et al. (2000). Wargocki et al. (2000) use the amount of outdoor air as the only independent variable in a controlled office environment, in order to determine the function between IAQ and productivity. This function provides a performance index associated with different IAQ conditions. The performance index is used in this research to calculate the savings that may potentially be generated by increasing the amount of work output over the working hours. Soft costs associated with health and litigation, are kept out of the model due to their stochastic nature. Step 4. Combine the true costs, and the cont rol options, to define and generate a decision model. Chapter 4 defines the details of the optim ization model. However the procedures for building the decision model follows the following five-step procedure:

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58 Formulate the problem. Defining the problem includes specifying the objectives and the parts of the system that must be studied before the problem can be solved. In this research the objective is to minimize the true costs of an IAQ control option by increasing the amount of OA, and the air cleaned, inside a given commercial building. Observe the system. In this phase the research is oriented towards the collection of data that would affect the problem determined in the previous section. The data to be collected include: how much an increase in productivity saves th e owner in costs; how much an increase in the supplied air amount would increase producti vity; how much hard costs are associated with a unit increase in the amount of air or the treatment of the air; how much energy cost occurs by an increase in the unit of outdoor air supply or recirculation air; etc. Formulate a mathematical model of the problem. In this phase a mathematical model of the problem will be developed (Figure 3-2). The model developed in this research includes: o Decision Variables o Objective Function o Constraints Figure 3-2 illustrates a preliminary i llustration of a possible linear modeling example with only two decision variables. It is shown in Figure 3-2, how the value of the objective function of a model might change wh ile changing the values for the decision variables (X1 and X2). According to Figure 3-2, the optimum result of the model would fall on to one of the extreme points around the fe asible region that is defined by different constraints.

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59 Figure 3-2. Example illustration for the proposed LP model. Verify and use the model for prediction. At this step the goal is to determine if th e model developed in the third step is an accurate representation of the real world. In or der to manage this, the model is compared to the current situation in a test commercia l building in Florida. This process also includes the information from sensitivity analysis. Select a suitable alternative. The available alternative IAQ control op tions are compared to each other on the basis of the developed model in order to c hoose the optimum system(s). A possibility is that the best alternative may not exist. Ho wever the model helps to choose the feasible alternatives even if a best alternative doe s not exist. Step 5. Present the results and conclusions. In this step, the model that is generated in Step 4 will be presented along with the possible results for different cases. This st ep will also include the recommendations for optimum alternatives as well as the future work for further developing the model. The

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60 results will include the sensitiv ity analysis in order to determine the range of validity of the optimization and the managerial implications. Research Methodology This research uses a quantitative methodol ogy that combines LCC analysis with the soft cost analysis in order to optimize th e true costs of indoor air quality control technologies and strategies in buildings. Howe ver, this research also uses qualitative literature review techniques to explore the criteria when the decision makers of the building industry are choosing sp ecific IAQ control options. This research utilizes the methodology of operations research, which is a quantitative methodology that offers considerable assistance to the building owners and managers in their quest for optimal solutions. With the help of mathematical programming this research provides the owners or managers increased ability to analyze their IAQ problems and generate solutions in a structured manner. Linear programming (LP) is used as a prelimin ary option for this research. There are basically two assumptions implicit in an LP model. One is that any relationship of two or more variables mu st satisfy the characteristics of a linear relationship. Second, the model uses dete rministic assumptions meaning that the variances in the values are not significant enough to warrant a nondeterministic approach. In summary, an LP model may be considered as a potential tool in determining the optimal allocation of limited resources if and only if the situation under consideration adequately satisfies the linear and deterministic assumptions. In a real world situation some of the constraints a nd variables in a decision process may have nonlinear relationships such as the re lationship between productivity and IAQ. This research

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61 simplifies these relationships into a lin ear level by using piece-wise linear approximations 5 In order to solve the model there are many software available. Excel Solver is one of those alternatives and is used to solve the model created in this research. Population There are two target groups that can use the results of this research. One of these is the building owners and managers. The reason this research is oriented towards the building owners and managers, is that owners and managers are the investors in a buildings IAQ system. For this reason an important factor is to uti lize their perspective to develop the decision model. The second group includes almost everyone that is involved in the creation of a building. This incl udes architects, engine ers, and contractors. This group is the one that will benefit most fr om the results of this research. Since many times owners leave the decisions to their repr esentatives, this study will be useful for experts that hold the deci sion power on investing in the IAQ of a building. Summary of Methodology The summary of the proposed methodology is illustrated in Figure 3-3 parallel and compared to Simons decision-making pr ocess (Simon 1960). The proposed methodology involves similarities to Sim ons decision-modeling process. In this research, well-known intelligence, design, choice, and implementation phases introduced by Simon (1960) are transformed into research, speculation, d ecision, and implementation phases. In the research phase, the options for different indoor air quality levels will be evaluated. This phase also covers the res earch on hurdles of the industry regarding IAQ and the 5 Chapter 4 provides a broad descriptio n of piece-wise linear approximation.

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62 generation of the major parameters of the model. In the speculation phase, the optimization model will be configured in te rms of objective function, decision variables, and constraints. The decision phase mainly covers the solution to the model, and the implementation phase is the output of speci fic recommendations by using the results. Figure 3-3. Summary of met hodology in comparison to Simons decision modeling process. (Simon 1960)

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CHAPTER 4 DEFINING PARAMETERS AND THE OPTIMIZATION MODEL Introduction The purpose of this chapter is to presen t the details of the methodology that was briefly introduced in Chapter 3. This purpose includes broad definitions of the methodologies used to generate the parameters and to generate the optimization model. In optimization problems, researchers gene rally use already defined parameters for generating the objective function. Parameter gene ration in this research is an important part of finding a solution to the genera ted model. Although many optimization studies leave this phase to the user, this research is generating the parameters in order to provide default values to the users. The parameters that are being used in the model are generated by Life Cycle Cost (LCC) analysis in the following areas: LCC for increased outdoor air (OA) to achieve desired reduction in contaminant concentration using increased ventila tion by a central or dedicated unit. LCC for the increased amount of air cl eaned, by calculating the air cleaner efficiency required to achieve desired reduction in contaminant concentration. In order to calculate the parameters a bove, this research adapts a preliminary methodology that is developed by the EP A (Henschel 1999). EPAs study provides a number of worksheets to help calculate the LCC of improve d ventilation, and air cleaning techniques (Appendix A). Parall el to the objectives of this research, EPAs worksheets are generated as a part of a pre-screening tool designed for decision makers with limited engineering knowledge. These worksheets are sl ightly modified in order to support the parameter development required by the model. For example, this research reinforces 63

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64 EPAs preliminary methodology with more upto-date quotes on equipment prices from several vendors as well as RS Means and government inflation rates. Although the EPA developed a number of these worksheets to cal culate costs of diffe rent IAQ management options, this research refers to only a total of six worksheets. However some EPA worksheets that are not referred to in this rese arch are converted into and used as simple equations. Definitions and the brief descriptions of the six worksheets adapted from EPA are given below: Worksheet 1: This worksheet is designed to help estimate the installed costs for increased OA by using a central unit. It calculates the increased heating and cooling capacities required to cond ition the increased OA and suggests costs per unit increases in capacities. Worksheet 2: This worksheet uses the same methodology as Worksheet 1 except uses different unit cost suggestions to es timate the installed costs for increased OA by a dedicated OA unit. Worksheet 3: This worksheet helps calcul ate the annual operati ng costs that occur due to increased OA ventilation. Worksheet 3 takes energy efficiency ratings of the HVAC equipment as well as the cooling a nd heating energy requirements in order to calculate an annual cost. Worksheet 4: This worksheet helps to estimate the annual maintenance costs for increased OA by calculating additional labo r and hours required for maintenance of specific equipment. Worksheet 5: This worksheet combines the annual maintenance, operating, and annualized installed costs to estimate th e total annualized costs for increased OA. Worksheet 6: Worksheet helps estimating the annual operating costs for central indoor air cleaners by calculating the energy consumptions and suggesting approximate unit costs. In this methodology, the rough estimates are se t as a screening tool to assist the model in making eliminations among the poten tial decision variable s. The better cost estimates can be developed for the control options if the requir ed HVAC expertise is available in-house or as a consulting servic e. The objective of developing these cost

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65 parameters is to facilitate a quick, inexpensive evaluation by users who may not have the required engineering knowledge for an extensive cost analysis. The costs that are used in the computation are the total annual cost s. This includes the annual operation and maintenance costs, and a nnualized installed costs. Estimating the Costs of Improved Ventilation The first step in assessing the costs associated with increasing the OA ventilation rate is to estimate the OA increase that will be required. Equation 4-1, based on EPAs worksheets, presents the step-wise proce dure for estimating the needed increase, assuming that dilution is the sole mech anism, which reduces the contaminant concentration. b bad C )( (4-1) Where, C = Incremental increase in outdoor airflow ra te required to achiev e the desired reduction in concentration (cfm). a = Current average concentration of the cont aminant of concern in the building (ppmv). b = Average concentration to which a should be reduced (ppmv). d = Current flow of OA in to the building (cfm). It is assumed in Equation 4-1 that the c oncentration of the contaminant of concern is zero in the OA, and that th e indoor air is well mixed so th at pollutant concentrations assumed at one point represent c oncentrations at all points inside a build ing. In this case pollutant concern is assumed to be a hom ogenate problem throughout the whole section of the building. The OA being provided by the air handler is correspondingly being increased to treat that whole section of the bu ilding in a consistent way. In this case, as a

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66 first approximation, one might use Equation 41 to estimate the additional clean air that would have to be provided to effectively reduce the concentrati on in the building. Note that Equation 4-1 disregards the a dded supply air increasing the mixing of the local contaminant throughout the area served by the air handler. Also the supply air, which is largely recirculated air, will thus increasingly differ from the assumption that there is zero concentration of a given contaminant in the ve ntilating air. The user would have to consider treating th e building by moderately increas ing OA flows to the entire portion of the problematic area if a localized source were to be addressed by an increase in direct supply air. In this study, the model requires the cost per one cfm unit increase in OA ventilation as an input. Consequently the va lue of C in Equation 4-1 can be taken as 1 (one) cfm to further develop the LCC analys is. Thus the user can calculate the cost associated with increasing the OA amount by one cfm unit and use the result as a default value in the optimization model. The details of these calculations can be seen in the upcoming sections. The LCC calculations of th e improved ventilation will be explored under three main categories. These are: Installed Costs Operation (Energy) Costs Maintenance Costs Estimating Installed Costs for Increased Ventilation According to EPA, the existing HVAC equipment needs to be modified or adjusted when an increase in the OA is required (Hen schel 1999). Consequently an installed cost would occur for making these modifications. An important factor in this study is the concentration on only new construction cases. The installed costs in new construction

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67 cases are in fact the incremental increase in the installed costs of the mechanical system resulting from the adjustments that are made in the specifications to increase the OA rate. Enlarged central units Worksheet 1 in Appendix A presents a procedure for estimating the installed costs as sociated with an increasing capacity of the central HVAC units to handle increased OA in the new c onstruction case. Worksheet 1 helps calculate the installed costs due to increased heati ng and cooling capacities required to condition the increase in OA. This worksheet is ad apted from EPAs preliminary methodology for evaluating cost-effectiveness of alternative indoor air qu ality approaches (Henschel 1999). The worksheet presented in EPAs me thodology includes an option of entering up to 3 (three) HVAC units. However in this disse rtation calculations are modified for only one HVAC unit. In this case, it is assume d that a system capable of handling and conditioning the increased OA flow is now to be installed instead of the system that had originally been designed for the bu ilding that has not been built yet. Worksheet 1 is based on the following circumstances (Henschel 1999): Cooling and Heating Capacity: The orig inally designed cooling and heating capacities are increased for the HVAC unit to handle the increased OA flow to itself. The air handler, cooling coils, conde nser, compressor, heating elements, and controls of each unit are re-designed as required before construction. Since this preliminary worksheet assumes direct-expan sion cooling units having electric heat, the calculations would be less accurate for systems that have chillers and furnaces. OA Intake Fan (if present): In cases where one or more OA intake fans are required in the new building, the worksheet assumes th at intake fans of greater capacity are installed in lieu of the lower capacity, originally designed fans. In the model described in this research, this item has not been included in th e cost calculations for testing purposes. In systems without economizers the worksh eet assumes that intake and exhaust ducting of larger dimensions are installed instead of the original intake and exhaust ducting.

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68 In systems with no economizers but that ha ve one or more central exhaust fans, worksheet assumes that exhaust fans of greater capacity are installed instead of the original ones. In order to use the calculations in Work sheet 1, the required in creases in heating and cooling capacities are taken from ASHRAE (1997) by using 1% design values for the cooling dry-bulb/mean wet-bulb temperatures. These values for Miami are 4.6tons/1000cfm for the required increase in cooling capacity and 6-kW/1000cfm for the required increase in heating capacity. The users can modify these values depending on the location of the project. Table 4-1 lists these values for several cities in the US. Table 4-1. Incremental increases in cooling and heating capacities required by increases in OA ventilation rates. City Required Increase in Cooling Capacity (tons per 1000 cfm OA) Required Increase in Heating Capacity (kW per 1000 cfm OA) Albuquerque, NM ~0 16 Atlanta, GA 3.3 15 Boston, MA 2.7 18 Chicago, IL 3.3 22 Cincinnati, OH 3.9 18 Cleveland, OH 2.7 20 Dallas-Fort Worth, TX 3.9 14 Denver, CO ~0 21 Houston, TX 4.6 12 Los Angeles, CA 0.5 8 Miami, FL 4.6 12 Minneapolis, MN 2.7 26 New York, NY 3.3 17 Omaha, NE 3.9 23 Pittsburgh, PA 2.1 20 Raleigh, NC 3.9 16 St. Louis, MO 3.9 20 San Francisco, CA ~0 10 Seattle, WA 0.5 13 Washington, D.C. 3.9 16 (Henschel, 1999).

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69 These values in Table 4-1 are computed by EPA using 99% heating dry-bulb temperatures for the various cities, as defined by ASHRAE standards. The heating capacity presented in the table is the increm ental power required to increase 1,000 cfm of outdoor air from the 99% value of outdoor te mperature to an indoor temperature of 70 F and 50% relative humidity. New dedicated OA units. Worksheet 2 in Appendix A presents a procedure developed by EPA for estimating the instal led costs associated with the use of a dedicated-OA unit in the new construction case Calculations in Worksheet 2 assume that since a dedicated-OA unit is to be installe d in a new building, it will be designed to condition all of the OA entering the building, rath er than just the incremental increases in OA. The EPA presents Worksheet 2, based on the following circumstances (Henschel 1999): Cooling and Heating Capacity: One or more rooftop direct-expansion systems with electric heat, dedicated to treating the incoming OA, are added to the original design. These added units have the capacity required to condition all of the OA that is now to be supplied to the building. Th e cooling and heating capacities of all of the originally designed HVAC units in the building are reduced, since the original units will no longer be required to co ndition OA, providing a cost savings that partially offsets the cost of the dedica ted-OA units. The linear model that is developed in this research, gives the user the option of entering a value for fixed installed costs, which allows the model, produce more sophisticated decisions if desired. OA Intake Fan (If present): The air handler s associated with the dedicated-OA units become the intake fans for the entire OA flow into the building. In systems that included OA intake fans in the original design, these intake fans can now be eliminated, which results in cost savings. OA Intake Ducting: In systems with econom izers, it is assumed that the increased total volume of OA being supplied by the dedicated-OA units is delivered into the originally designed OA intake ducting with no modifications to the original design.

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70 In systems without economizers the worksh eet assumes that intake ducting and exhaust ducting of larger dimensions is installed instead of the original ducting. For systems that have central exhaust fans but do not have economizers, Worksheet 2 assumes that exhaust fans of greater capacity are installed instead of the originally designed fans. Estimating Operating and Maintenance Costs for Increased Ventilation Estimating the annual operating and maintena nce costs is an important step in LCC analysis. In order to complete this estima te, in addition to the installed costs this dissertation suggests using th e worksheets in Appendix A, provided by EPA (Henschel 1999). Annual operating costs. EPA suggests that the annual operating cost associated with an increase in ventilation rate can be the incremental energy cost resulting from: Cooling and heating the incr eased flow of outdoor air Operating the enlarged or new intake or exhaust fans (if applicable) Worksheet 3 in Appendix A presents the method to calculate the annual operating costs for increased ventilation. However it is important to note that this methodology should only be used when thorough modeling of the building energy consumption and costs is not possible. The system size and characteristics depends on the climate of different regions as well as the number of days and hours the OA is supplied and conditioned (Westphalen & Koszalinski 1999). EPA states th at a calculation of heating energy consumption that is based only on the total heating degree-days in a specific geographical location may be misleading; the mechanical system may not be supplying OA to the building during the middle of the night, which is the coldest period of a day. This would definitely impact the heating degree-day figure, which would alter the calculations based on only the geographical location (Henschel 1999).

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71 Accordingly, the EPAs methodology to calcu late the operating costs has utilized the DOE-2 building energy computer model to compute the required energy output from the mechanical system per incremental cfm of OA in a variety of climates with alternative mechanical systems. EPAs met hod assumes that OA is being supplied for 13 hours per day and 5 days per week. Since this research is concentrating on commercial buildings this assumption is also valid for the types of buildings for which the model is being generated. The results in the form of the average Btu of cooling energy output and Btu of heating energy output per incrementa l cfm for the different cities are given in Table 4-2. The values in Table 4-2 are genera ted for a small office building for which the input was available from Henschel (1999). Th e figure for each geogra phical location is an average for alternative variable-volume and constant-volume systems, and for OA flow rates at a range of 5 to 60 cfm/person at an occupancy density of 7 persons per 1000 The values in Table 4-2 are calculated with the assumption that the OA is supplied to the building 13 hours/day (6 am to 7 pm) on weekdays only (excluding holidays) 2ft Table 4-2. Incremental annual cooling and h eating energy requirements per unit increase in OA ventilation rate by geographical location. City Incremental Additional Annual Cooling Energy Required per Incremental Increase in OA Intake Rate (Btu/yr per incremental cfm) Incremental Additional Annual Heating Energy Required per Incremental Increase in OA Intake Rate (Btu/yr per incremental cfm) Chicago, IL 13,000 41,000 Miami, FL 67,000 200 Minneapolis, MN 13,000 63,000 Northern Virginia 20,000 25,000 Raleigh, NC 26,000 16,000 Seattle, WA 3,000 28,000 (Henschel, 1999).

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72 In Worksheet 3, the annual incremental co st of energy is computed by using the required energy output from the mechanical system and also by taking the system efficiency and the unit cost of fuel or electricity into account. In the same sheet users also have the option to calculate the ener gy cost for new or enlarged fans. Annual maintenance costs: Worksheet 4 originally developed by EPA in Appendix A provides a preliminary methodol ogy to calculate the annual maintenance costs for increased ventilation. The EPAs preliminary methodology assumes that increases in ventilation cause an increase in maintenance costs only when a new intake or exhaust fan is added or when a new dedicated OA HVAC unit is added. The EPA worksheets assume no increase in maintenance to result from enlargements of existing equipment. Although the worksheet is presente d in the Appendix A for some users that may require it, in this research upper bound c onstraints are avoiding one of the two cases that were explained above. Thus the input data used in this research to test the model, assumes that there would be no significant cha nge in the maintenance costs of the system. As for users that want to add the maintenan ce cost input to their model, the worksheet suggests figures of 5 hr/yr for each fan, and 20 hr/yr for each dedicated OA unit. The labor rate including or excludi ng the overhead can be obtained from the latest version of Recommended Standard (RS) Means. Estimating total annualized costs for increased ventilation: Worksheet 5 in Appendix A is designed to combine the annua lized installed costs with annual operating and maintenance costs associated with th e increased ventilation. However the model developed in this research uses two different figures for the i nput cost data. It is possible to combine the installed costs and the a nnual costs into one si ngle annual cost and

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73 eliminate the fixed cost figure. It is also possible to keep the annual O&M costs separate from the installed costs. Worksheet 5 should be used if the user decides to combine all the costs into one annual cost. In this case th e annualized amount for th e installed costs is determined using the Capital Recovery Factor (CRF). The user can select the number of years over which the installed cost is to be am ortized, and the interest rate that is to be charged. The number of years will generally be the estimated lifetime of the system equipments. The value for the interest rate is the rate that is being paid on money borrowed to install the equipment, or the inte rest rate that could have been obtained on the money if it was invested rather than be ing used for the installation (Kirk & Isola 1995). Where n is the number of years, a nd i is the interest rate CRF could be calculated by using the Equation 42 given below (Kirk & Isola 1995): ]1)1/[(])1([ n niiiCRF (4-2) The CRF is the fraction of the initial cost th at must be amortized each year if after n years, the initial cost is to be recovered with an i per cent annual interest rate being charged on the unpaid balance. Consequently th e total annualized co st computed in the Worksheet 5 is the sum of: The CRF multiplied by the increm ental total installed cost The incremental annual operating cost The incremental annual maintenance cost Estimating the Costs for Air Cleaning Sometimes it may be appropriate to consider the use of air clean ers to remove the contaminant(s) of concern. For practical r easons, air cleaners are usually considered when ventilation and source management are not the feasible opti ons (Henschel 1999). The model developed allows use all of th ese techniques together when feasible.

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74 Methodology to calculate the costs of air cl eaning includes two classes of indoor air particulate cleaners: media air cleaners a nd electronic air cleaners. Media air cleaners include: Pleated filter panels Bag filters Variations of the above types (e.g., pocket filters) Electronic air cleaners are electrostatic precipitators. The EPA methodology used only considers particulate air cleaners with an average removal efficiency of 65% or greater as measured in ASHRAE sta ndard 52.1-1992 (ASHRAE 1992). The methodology also assumes that lower efficiency filters are already present on the HVAC system, to protect the fan and coils. Users of the model also have the option to modify the cost data by including high-efficiency particulate ai r (HEPA) filters, which offer 99.97% removal efficiency. These types of filters are generally used in hospital operation rooms. The cost data generated by EPAs methodolog y does not include HEPA filters. The air cleaners considered for gaseous c ontaminants involve th e use of beds of dry, granular material acti ng by physical adsorption, chemi cal absorption, or catalysis (Henschel 1999). Such air cleaners can be c onsidered for the cont rol of a variety of gaseous contaminants (ASHRAE 1995), however EPAs cost calc ulations are more focused on the VOCs. The worksheets that are adapted from EPAs preliminary study address the incremental costs of a larger fan motor and of removing the heat ge nerated by the larger motor. However the worksheets do not intend to calculate any costs associated with modifying the mechanical room or the HVAC equipment to house the air cleaner, since these costs will be very building specific. Additionally, the installed costs for the air

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75 cleaners computed in EPAs worksheets assume that there are no part icular complications in the installation, which would significan tly increase installa tion labor hours and materials. Estimating Installed Costs for Air Cleaners The following items generate the costs associ ated with installati on of a central air cleaner: Obtaining and installing the air cleaner itself A larger motor for the central air handling fan, to compensate for the pressure drop across the cleaner (for media fi lters and gaseous air cleaners) Cooling capacity that may potentially in crease to remove the additional heat produced by the larger fan In order to calculate the installed costs for the air cleaners, Equation 4-3 can be used as extracted from the worksheets de veloped by Henschel (1999). According to the equation, installed costs are a simple function of total flow through the air cleaner and a vendor quote for 1000 cfm of OA. VQE (4-3) Where, E = Installed costs Q = Total flow through the air cleaner V = Vendor quote ($/1000 cfm) OR Refer to Table 4-3. In Equation 4-3 it is important that the user s first select an ap propriate air cleaner based upon the performance requirements. With this selection the user may then either obtain an estimate from a vendor for this t ype of air cleaner, or may use a simplified option given by Table 4-3. The table presents rough installed costs per 1,000 cfm air for different types of air cleaners.

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76 Table 4-3. Approximate installed costs of va rious in-duct particulate air cleaners Type of Air Cleaner Total Unit Installed Cost ($/1000 cfm) Pleated panel cartridge filter, ASHRAE 65 142 Pleated panel cartridge filter, ASHRAE 85 142 Pleated panel cartridge filter, ASHRAE 95 148 Electronic Air Cleaner 496 Adapted from Henschel (1996), updated by inflation rates from http://inflationdata.com The installed costs given in Table 4-3 incl ude the cost of taking the air through the filter and of the increase in fan motor horsepower, but exclude any costs for increased cooling or heating capacity. Estimating Operating and Maintenance Costs for Air Cleaners Annual operating costs: The methodology by Henschel (1999) includes the following items when calculati ng the annual operating costs: The increase in power consumption by the fan motor Power consumption by the corona wires and plates (electronic air cleaner) Added power consumption by the cooling system Worksheet 6 in Appendix A presents a me thod for estimating the energy costs. The worksheet that is modified from Henschel (1999) estimates incremental additional fan horsepower requirements by multiplying the to tal airflow through th e air cleaner times the average pressure drop across it, accounti ng for fan/motor efficiency, and applying the appropriate conversion factors. Annual ener gy later is calculated by multiplying this power requirement times the number of hours pe r year that the fan will be operating. The annual operating cost for the larger fan motor is determined from this energy consumption and based on the unit cost of electricity. The default values are available for pre ssure drop, fan efficiency, hours of fan operation, and unit energy costs. If the user does not have these values available the following values can be used:

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77 Pressure drop: 1 in. WG Electric Input Ratio (EIR) fo r the cooling system: 0.34 kW/kW Hours of fan operation: 3,276 hr /yr (for 13 hr/day, 5 day/wk) Worksheet 6 in this research calculates the operating costs of media air cleaners for particulate matter. However preliminary met hodologies for calculati ng cost of electronic air cleaners for particulate matter and the cost of air cleaners for gaseous contaminants are available through EPA. Annual maintenance costs: Maintenance costs for air cleaning include the materials and labor costs associated with periodic replacement of the filter media for media particulate air cleaners. Henschel (1999) developed a worksheet that is converted to Equation 4-4 in order to calculate a rough estimate for the maintenance of media particulate air cleaners. He nschel (1999), in his study, includes more information regarding different types of cleaners if required. Table 4-4 includes the price information to be used in Equation 4-4. If the user has more project sp ecific data, then these data could be easily replaced with more accurate ones in the model. N Fi 1000 ($/yr) (4-4) Where, Annual cost of replacing the particulate media filters Approximate unit cost for replacing filters per MCFM (Table 4-4) iF Amount of air through clean er i (i=1,2,3) (cfm) Number of times per year that the filter media will be replaced.

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78 Table 4-4. Approximate replacement costs of media cartridges for particulate media air cleaners Type of Air Cleaner Unit Cost of Replacement Cartridges ($/MCFM) Plated panel cartri dges, ASHRAE 65 45 Plated panel cartri dges, ASHRAE 85 45 Plated panel cartri dges, ASHRAE 95 50 Adapted from Henschel (1996), updated by inflation rates from http://inflationdata.com It is assumed that only minimal labor is re quired to install the re placement of cartridges. Estimation of Income Function from In creased Productivity due to Increased IAQ The effects of indoor air quality on produc tivity were discussed in Chapter 2. Wargocki (2000) conducted one of the important studies that this research has used in order to build the cost data for productivity. Wargocki (2000 ) conducted three studies that involved 90 subjects. Using similar procedures and blind exposures, the studies showed that increasing air quality (by decreasing the pollution load or by increasing the ventilation rate, with otherwise constant indoor climate conditions) could improve the performance of simulated office work (tex t typing, addition, and proof-reading). The results imply that doubling the outdoor air supply rate at c onstant pollution load, or a two-fold decrease of pollution load at cons tant ventilation rate, can increase overall performance by 1.9%. Inspired from Wargockis results, imaginary data in Table 4-5 was generated to calculate the increased inco me as a result of increased productivity. Table 4-5. Ventilation rate (cfm per person) vs. performance index 17 0.99000 44 1.021972 71 1.028903 98 1.032958 125 1.035835 20 1.000000 47 1.023025 74 1.029444 101 1.033322 128 1.036109 23 1.006931 50 1.023978 77 1.029957 104 1.033672 131 1.036375 26 1.010986 53 1.024849 80 1.030445 107 1.034011 134 1.036635 29 1.013862 56 1.025649 83 1.030910 110 1.034339 137 1.036888 32 1.016094 59 1.026390 86 1.031354 113 1.034657 140 1.037135 35 1.017917 62 1.027080 89 1.031780 116 1.034965 143 1.037376 38 1.019459 65 1.027725 92 1.032188 119 1.035263 41 1.020794 68 1.028332 95 1.032580 122 1.035553

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79 The data listed in Table 4-5 is generate d by using log (e) function and is partially integrated in the MS Excel sheet where th e model uses a piece-wise linearization in order to control the estimated profit genera ted by the total amount of outdoor air. One of the reasons for choosing this method is due to the limitations of the linear programming on a nonlinear problem. If the nonlinear productivity function is linearized by using only one line, the model produces results for either the lower bound or upper bound that is defined with the constraints. Once the profit due to increas ed productivity becomes more than the cost, the model pushes the results to wards bringing as much air as possible. On the other hand, if the profit from increased prod uctivity comes out to be less than the cost of bringing OA, then the model goes down to th e lower constraint and tries to bring as little air as possible. The values for the performance index were given in Table 4-5. The graphic that shows the plot of those valu es is given in Figure 4-1. Performance Index vs OA0.995 1 1.005 1.01 1.015 1.02 1.025 1.03 1.035 1.04 0102030405060708090100110120130140150160 OA Amount (cfm/person)Performance Index Figure 4-1. The performance index and its correlation with the supplied OA amount. Although performance index is the value th at is defined in Wargockis (2000) study, this dissertation subtracts 1 (one) from these values so when they are multiplied with the total salary of the occupants of th e building, only the prof it can be calculated. A

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80 more detailed description of this calcula tion will be explained in the User Defined Independent Variables as Input Data subsection. The final numbers in the productivity curve after subtracting 1 from the performance index are illustrated in Figure 4-2. This new value in this research will be referred to as Performance Profit Index (PPI). Since this research is assuming linearity in the functions used in the model, the productivity function is linearized by s lightly underestimating the PPI values. Many studies that choose to linearize a nonlinear function chooses one of the two options: Piece-wise linearization by overestimating Piece-wise lineariza tion by underestimating PPI vs OA0 0.005 0.01 0.015 0.02 0.025 0.03 0.035 0.04 020406080100120140160 Amount of OA (cfm/person)PPI Figure 4-2. PPI and its correlati on with the amount of OA. Piece-wise linearization is used in many studies by choosing either to overestimate or underestimate. Examples of piece-wise li nearization of an e xponential function are given in Figure 4-3. The model developed in this research howe ver would only be sound if at least a number of segments are create d. Otherwise the model as the total amount of OA brought into the building would still create solutions at the extreme OA values. If the PPI versus OA function was to be linearized at point in only two lines this would only limit the OA solutions to either 20, or 140. However linearizi ng this function to at

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81 least n number of lines would require the user to include additional constraints. In order to simplify the configuration of the model, the PPI versus OA function is linearized with 11 lines at points, 20, 26, 32, 38, 44, 50, 56, 62, 68, 74, 80, and 86 (cfm). These functions and their integrations in the optimization m odel will be discussed in the Defining the Optimization Model section. The piece-wise linearization of the PPI vs. OA function is given in Figure 4-4. A B Figure 4-3. An example for piecewise linea r overestimate and underestimate of an exponential function. A) Overestimating, B) Underestimating (Irion et al. 2004) Figure 4-4. Piece-wise lineariza tion of the PPI vs. OA function. In order to calculate the equation of the lines presented in Figure 4-4, the values obtained from Figure 4-4 or Table 4-5 can be inserted in Equation 4-5. The value of the

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82 slope (m) can be calculated by finding the tangent of the : angle for each linear segment by using Equation 4-6. cmxy (4-5) Where, m The slope of the line c The constant. Tan = m OAMin -OAMax PPIMin -PPIMax (4-6) This research disregards the correlation between the amount of air cleaned with the productivity levels and PPI. If any scientific data are developed in the future, a new linear function can be calculated by using similar methods shown for OA vs. PPI calculations. Defining the Optimization Model The optimization study includes three major parts as listed below: Improved ventilation by central unit Improved ventilation by a dedicated unit Air cleaning These areas are all combined in an objectiv e function in order to set the values for the decision variables that are subject to the constraints. An important factor to note is that using the preliminary methodology developed by EPA th at is introduced earlier can help estimate the rough values for the input un it costs. However it is also important to evaluate the model not in term s of the actual numbers that will be constantly changing due to inflation rates and other economic and technological developments, but of the relationships among the IAQ control options. The model is developed as a preliminary model that is basically simplified in many terms to clarify the application of linear programming methodologies in construc tion management. Although more complex

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83 optimization methodologies are widely used in the engineering side of this area, construction managers and the building owners and managers are still not aware of the possibilities that optimizati on studies can offer in making preliminary decisions. Decision Variables Decision variables are the de pendent variables in LP th at are subject to changing while optimizing the objective function. There are a total of eleven decision variables in this research. The units of all the variable s except the binary ones and the productivity variable are cubic feet per minute per person and all the cost values in the model are annual. Decision variables of the model in this research are listed below: 1X = Amount of OA supplied by a central unit (cfm/person) 2X = Amount of OA supplied by a dedicated unit (cfm/person) W = Profit generated by incr eased productivity ($) 1F = Amount of air through cleaner 1 (cfm/person) 2F = Amount of air through cleaner 2 (cfm/person) 3F = Amount of air through cleaner 3 (cfm/person) 1Y = if central unit is used, if not 2Y = if dedicated unit is used, if not 1B = if cleaner 1 is used, if not 2B = if cleaner 2 is used, if not 3B = if cleaner 3 is used, if not

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84 The details explanations of the above decision variables are given below: a) ( ) 1X Amount of OA supplied by a central unit This variable represents the amount of outdoor air that is being supplied to the building by a central HVAC unit in cfm/ person units. ASHRAE 62.1-2001 standards mandate the total amount of OA supplied in commercial buildings as 20 cfm per person. However the model investigates in more dept h to explore if bringing more OA would still be economically feasible. b) ( ) 2X Amount of OA supplied by a dedicated unit The difference of the OA by the dedicated unit from the central unit appears only when dealing with fixed installed costs. Th e operating and maintenance costs associated with this variable are supposed to be exactly the same as the OA by the central unit. Thus the model will choose to bring OA into the bu ilding by either a dedicated or central unit depending on their fixed installed costs. c) ( ) iF Amount of air through cleaner i (for i=1,2,3) This is the amount of air that passes through the air cleaners that are located possibly in three different locations. These lo cations are illustrate d in Figure 4-5. The relations among these different locations will be discussed under the constraints section. According to Figure 4-5, if a cleaner is located on location1 then it will only clean the outdoor air supplied to the system If it is located in Location 2 then it will only clean the recirculating air. If it is located on Lo cation 3 then it will be able to filter both recirculating air and the outdoor air.

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85 Figure 4-5. Possible ai r cleaner locations. d) ( ) 1Y Binary variable fo r central air unit This variable is the binary variable for th e central unit. It gives the model the option of either using this unit or not. If the model finds it opt imum to use the central air unit, the value of this decision va riable appears in the solution as and O if not used. e) ( ) 2Y Binary variable for dedicated unit This variable is the binary variable for the dedicated unit. It gives the model the option of either using this un it or not. If the model finds it optimum to use the dedicated air unit the value of this decision variable a ppears in the solution as and O if not used.

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86 f) ( ) iB Binary variable for air cleaners (for i=1,2,3) This variable is the binary vari able for each of the air cleaners. represents the binary for location 1, is the binary variab le for location 2, and is the binary variable for air cleaner in location 3 (See Figure 43). Depending on these variables being or the user can decide which one(s) should be used or not. 1B 2B 3B Objective Function The objective function of the model is give n in Equation 4-7. The objective of the model in managerial terms is to minimize the true costs of indoor air quality management options. In more detail, it is to minimize th e overall cost of providing outdoor air and cleaning air in a commercial building while ma ximizing the benefits of increased worker productivity. Equation 4-7 represents the summ ation of three major costs. These are the cost of OA by a central unit, OA by a dedicate d unit, and cleaning air in three possible locations. The cost of bringing OA by a centr al unit includes the variable cost (VC), revenue generated by increased productiv ity (R), and the fixed costs (FC). WEBDFYCXj jj i iii )() (A zMin 3 1 2 1 i (4-7) Where, VC FC FC VC R z = The total annual cost of the IAQ control ($) 1A = Marginal cost of air by central unit ($ x person/cfm) 2A = Marginal cost of air by dedicated unit ($ x person/cfm) 1C = Fixed cost for central unit ($) 2C = Fixed cost for dedicated unit ($)

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87 D = Cost for cleaning air ($ x person/cfm) E = Fixed cost for air cleaners ($) 1P = Money saved by increased productivity by central unit (See Eq. 4-7) ($) 2P = Money saved by increased productivity by dedicated unit (See Eq. 4-7) ($) 3P = Money saved by increased productivity by air cleaners (See Eq. 4-7) ($) 1X = Amount of OA supplied by a central unit (cfm/person) 2X = Amount of OA supplied by a dedicated unit (cfm/person) 1F = Amount of air through cleaner 1 (cfm/person) 2F = Amount of air through cleaner 2 (cfm/person) 3F = Amount of air through cleaner 3 (cfm/person) 1Y = if central unit is used, if not 2Y = if dedicated unit is used, if not 1B = if cleaner 1 is used, if not. 2B = if cleaner 2 is used, if not. 3B = if cleaner 3 is used, if not. W = Profit generated by increased pr oductivity by using PPI function. ($) Although the data stating the de pendency among the variables are not clearly set with the current literature and studies, there is a strong belief that in fact there should be a relationship (Wargocki 2000). If data become available then this dependency can be reflected in th e model by including a function of and in the calculation of W. This may create a more accu rate and actual representation of the IAQ j 21F and ,X,X iX jF

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88 measures and productivity. However the ne w objective function in that case would become a nonlinear function, which would requi re a more complex solution to the model. Thus solving the model with MS. Excel Solver would not be possible anymore. On the other hand there are other softwa re and tools available for this type of optimization such as Lingo Once the data and verification ar e available one should consider using these software to complete the solution of the model. Decision Constraints Decision constraints of the model are a set of constraints that the model is limited with while changing the value of the d ecision variables to optimize the objective function. The decision constraints that the objective function (S ee Equation 4-7) is subject to, are given below: 1. cfm XX 14021 2. cfmXX 2021 3. 121 YY 4. 1321 BBB 5. 01401 1 YX 6. 01402 2 YX 7. 0140 i iBF 8. 0321 FFF 9. 0) (32121 FFFXX 10. 1831.02 X 1 1831.02 X 2 + W <= .41 11. 851.38 X 1 851.38 X 2 + W <= .65 12. 560.79 X 1 560.79 X 2 + W <= .81

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89 13. 418.36 X 1 418.36 X 2 + W <= 3542.52 14. 334.45 X 1 334.45 X 2 + W <= 7256.39 15. 278.42 X 1 278.42 X 2 + W <= 10057.78 16. 238.50 X 1 238.50 X 2 + W <= 12293.41 17. 208.61 X 1 208.61 X 2 + W <= 14146.98 18. 185.38 X 1 185.38 X 2 + W <= 15726.56 19. 166.81 X 1 166.81 X 2 + W <= 17100.76 20. 151.62 X 1 151.62 X 2 + W <= 18315.65 21. All variables 0 Constraint 1. This constraint mandates that the amount of OA taken into the building does not go over 140 cfm of OA sin ce this would requir e a replacement or upgrade of the equipment. Constraint 2. This constraint mandates that the total amount of OA supplied by both units should be at leas t 20 cfm per person, which is the requirement of ASHRAE Standard 62.1-1999 for commercial buildings. Constraint 3. This binary constraint requires the model to select at least one of the HVAC units (dedicated or central). Constraint 4. This binary constraint requires the model that at least one of the air cleaners at one of the possible locations shall be selected. If the user decides that only one of the cleaners should be selected then the should be replaced with =. Constraint 5. This constraint is similar to the Big M method. It makes sure that if the model decides not to use the central unit, will be zero (0), thus the model will automatically give the value of zero (0) so it will not be included in the objective function cost calculations. 1Y 1X

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90 Constraint 6. This constraint is similar to the Big M method. It makes sure that if the model decides not to use the dedicated unit, will be zero (0), thus the model will automatically give the value of so it will not be included in the objective function cost calculations. 2Y 2X Constraint 7 This constraint is very similar to Constraint 5 and 6. It assures that if any of the cleaners are not used, then the vari able associated with that cleaner becomes zero (0) to make sure the costs associated with that specific cleaner are not calculated in the objective function. Constraint 8. This constraint makes sure that the air, which flows through three different locations, creates a closed network. This is assured by equalizing everything going into the zone being equal to ever ything coming out. Thus the OA plus the recirculated air equals the air supplied into the zone. Constraint 9. This constraint assures that the amount of air cleaned is not greater than the amount of air supplied into the zone. Constraint 10-20: These constraints are used to linearize the PPI function introduced earlier. However the coefficients of these constraints vary depending on the chosen total salary. The cons traints shown are configured for an average salary of $1,000,000. The coefficient should be adjusted when there is a change in the total salary by using the segments and asso ciated values in Table 4-5. Constraint 11. This constraint is known as the nonnegativity constr aint and assures that none of the variables defined pr eviously result in a negative value. User-Defined Independent Variables as Input Data There are two very important independent variables in the optimization model:

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91 Number of employees inside the building Average salary of the employees These variables are necessary in order to solve the model and find an optimum decision. All the cost for OA air and cost for cleaning air calculati ons are in terms of cfm per person. Thus if there is only one pe rson in a zone, and if the model decides to bring 20 cfm per person, that means the system should supply 20 cubic feet of air every minute. However in the same exact setting, if there are 2 people in the zone then the HVAC system should supply 2 x 20 cfm/person, which would be 40 cubic feet of OA every minute. If the cost of supplying 20 cf m/person OA is X amount of dollars then supplying OA to the entire building woul d cost: $(X x Number of occupants). Another important information to know is the average salary of the employees inside the building. The basic r eason for that derives from the productivity issues. Since the model is trying to optimize the cost, which includes the savings from the increased productivity, the average salary makes a diffe rence in terms of how much the increased performance is actually saving the employer. For instance if the average salary of the employees in a building is $30K then incr easing their performance index to 1.02 would actually save: 600$)102.1(000,30$ per employee. The actual savings is calculated by multiply ing the above savings per person by the number of employees. The above calculations are embedded in the MS Excel spreadsheet while configuring the input para meters for the model. The two independent variables in this study are left blank to be completed by th e user to create a buildingspecific model. However, the user also would have the option to change some of the variables that are used in the cost calculations If not, the default va lues are used in the

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92 model developed in this research. Below are so me of the values that the user may have control over for more accurate results: Energy efficiency ratings for HVAC equipment (1 Btu/h per Btu/h) Cooling capacity of the HVAC (4.6 tons/1000cfm) Heating capacity of the HVAC (12 kW/1000cfm) The unit costs for electricity (or gas) ($0.09/kWh) Unit costs for heating and/or cooling capacity Location of the building Electric Input Ratio (EIR) of the equipment (10 Btu/h/W) Appendix B presents the sample MS. Excel Solver screens in which the model is integrated. Configuration of the cells for vari ables, constraints, and the objective function are shown in Figure B-1 and the Solver modul e is shown in Figure B-2 and Figure B-3. Summary Defining parameters is a crucial part of an optimization problem. Chapter 4 as a part of the methodology explores some methods to generate these parameters. By using the equations and the worksheets introduced in this Chapter, one would be able to generate preliminary data for the unit annual costs of bringing OA air into the building and cleaning the indoor air. This chapter provides worksheets and equations for calculating LCC of IAQ systems. The deci sion model is defined by determining the decision variables, constraints, and the objec tive function. The set of constraints can be expanded by adding specific constraints that limit the amount of ventilation due to issues in air velocity, sound insulation, etc. An im portant point is that the assumptions and limitations section in Chapter 1 has very im portant information to keep the generated model valid. Chapter 5 discusses the solutions to the model that is defined in this chapter and determines if there is a feasible region defined by the model or not..

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CHAPTER 5 RESULTS AND DISCUSSION Introduction In order to test the model and show that the model can find solutions in the feasible region a user initially needs to plug in the data that the model requires. An LP can generate several different results. The major possibilities other than finding one optimal solution, are listed below: Alternative or multiple optimal solutions Infeasible LPs Unbounded LPs This section of the dissertation is moving towards the solution of the model to observe if any of the above cases apply. If not, then the optimum solutions generated by the model are presented by solving the mode l with sound imaginary input data. This chapter also explores the sensitivity analys is by answering what if questions about the generated solutions. Solution to the Model Before hitting the solve bu tton on the Solver menu, it is important to make sure that the model is transformed on the spread sheet correctly. Figure 5-1 presents how decision variables, objective function, constraint s, and the input data are transformed into the MS Excel spreadsheet. Cells A6 to A16 contain the names of each decision variable that was described in Chapter 4. Th e results for decision variables are expected to appear in cells F6 to F16. These cells are locked so the user has no control over changing the values in these cells. Since no co st or demographic data are plugged in yet, 93

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94 Figure 5-1 shows for these values (deci sion variables). The objective function is programmed in cell C21. The formula embedded in the objective functi on cell is an exact transformation of Equation 4-7. Figure 5-1. MS EXCEL Spreadsheet deve loped to correspond to the generated optimization model. The names of the models constraints that were described in Chapter 4, are located in cells B27 to B48. Constraint number 11, whic h is the non-negativity constraint, will be implemented in the Solver menu window. The cost data to be input by the user are given in cells K6 through K11. These includ e the unit costs of bringing one cfm of OA

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95 into the building by a dedicated or central unit an d cleaning one cfm of air. These costs can be calculated by following the instructions in Chapter 4 and the worksheets given in Appendix A. Cells K19 and K20 are for the user to input the number of occ upants in the building and the average salary of the employees. Then MS Excel calculates the total salary costs for the owner in Cell K21 by simply multiplying the average salary by the number of occupants (K19 x K20). In order to test if the model is worki ng this research solves the model for two different sets of input data The only difference between th e two imaginary cases derives from the change in the cost data used as input. The change in number of employees and the average salary and their effects on th e solution will be discussed in sensitivity analysis. Although the cost data according to the worksheets should not be changing for different buildings in the same region, the difference may be a result of the variation in the energy efficiency of the buildings or the default values such as the energy efficiency of the equipment used in the buildings. Case 1 The building used in the first case is assumed to be located in Miami and is a middle-sized commercial building. Co st data that is used in th is case are rough estimates. These costs may significantly vary due to ch anges in system design and the operating and maintenance unit costs. In the first case study, the following demographic data are used to solve the model. Number of occupants: 50 Average salary of the occupants: $20,000

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96 The cost data are set as follows: Cost of OA by central unit: $3.40 cfm/person Cost of OA by dedicated unit: $3.20 cfm/person Cost of cleaning air: $3.40 cfm/person Fixed cost for central unit: $35,000 Fixed cost for dedicated unit: $40,000 Fixed cost for air cleaner: $8,000 When these values are used as input in the model, the results generated by MS Excel Solver are shown in Figure 5-2. Figure 5-2. Case 1MS Excel screen for solution.

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97 According to Figure 5-2, the optimum so lution to the above case would require bringing 44 cfm/person OA by using the central unit. Also the solution suggests using an air cleaner in location 3 and cleaning 44 cfm of air/person. The number (zero) corresponding the binary variab les indicate that in this hy pothetical situation, it is not optimal to use a dedicated unit, cleaner lo cation 1, and cleaner location 2. The objective function is displayed to be $35,988.00. This means that the cost of the system (when the productivity increase is taken into consider ation) would be appr oximately $36K annually. The answer sheet that shows the binding and not binding constraints as well as the final values of the objective function and th e variables is given in Figure 5-3. Figure 5-3. Case 1Answer sheet ge nerated by MS Excel Solver

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98 Case 2 The second case assumes that the same building in Case 1 has lower energy efficiency or less efficient equipment thus may have higher amounts of marginal annual costs. Thus the cost data in the second case is slightly higher then data used in Case 1. The demographic input data for this case remain the same as the data used in Case 1. Number of occupants: 50 Average salary of the occupants: $20,000 The cost data are adjusted as listed below: Cost of OA by central unit: $4.90 cfm/person Cost of OA by dedicated unit: $4.70 cfm/person Cost of cleaning air: $4.80 cfm/person Fixed cost for central unit: $32,500 Fixed cost for dedicated unit: $37,500 Fixed cost for air cleaner: $7,500 The solution of the second case is given in Figure 5-4. The results show that the objective function (the total annual cost of the system), increases to $38,971.00 due to high unit costs in spite of the decrease in th e fixed costs. One of the results worthy of note is that the total amount of OA reco mmended in Case 2 is only 38-cfm/person. The solution shows that due to increased unit prices for bringing OA into the building, the savings expected by the increase in productivity is not high enough to encourage a further increase in the ventilation rate. Accordi ng to Figure 5-5, bringing 38-cfm/person OA by using the central unit and cleaning 38-cfm/person air by cleaner in location 3, provides the optimum cost. The reason the model chooses to use the central unit rather than the dedicated unit in both cases is because of the fixed costs associated with them. Although the unit cost of air brought by the dedicated unit seems to be cheaper, it is not economical enough to compensate the $5,000.00 difference in the fixed costs of these systems.

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99 Figure 5-4. Case 2MS Excel screen for solution. The binding and not binding constraints are listed in Figure 5-5. The results for the decision variables would stay the same as long as the binding state of the constraints stay the same. Once the change in the input values cause a change in the binding status of a constraint, the optimum solution for the model shifts to another extreme point and thus may change the values of the decision variables. This res earch discusses the what if questions regarding both cases in the sensitivity analysis section.

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100 Figure 5-5. Case 2-Answer sheet ge nerated by MS Excel Solver Sensitivity Analysis Sensitivity analysis is a procedure to dete rmine the sensitivity of the outcomes of an alternative to changes in its parameters. If a slight change in a parameter results in relatively large changes in the results, the resu lts are considered to be sensitive to that parameter. This may mean that the parameter ha s to be determined ve ry precisely or that it has to be reconfigures for a lower sensit ivity. One of the challenges in creating the sensitivity analysis report by using MS Excel Solver is th at the reports generated for problems that involve integer constraints are not meaningful. In order to get the

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101 sensitivity report from the solver, after solv ing the problem, the results for the binary variables can be plugged in directly. It is also important to take the binary variables from the list of decision variables in the solver module. Binary constraints also should be removed from the constraints section in the solver window. Afte r executing the above steps the model will not be considered to be an integer programming, thus a sensitivity report can be generated by MS Excel Solver The sensitivity report for Case 1 is given in Figure 5-6. According to the Allowable Increase/Decrease column s, provided the coefficient of in the objective function lies between 170+78.86=248.86 a nd 170-5.55=164.45, the values of the variables in the optimal LP solution will remain unchanged. Similarly, if the coefficient of goes above 160+10=170 then the model will not be valid anymore and will need to be solved again with the new coefficient values. However it is important to note that the actual optimal solution value will change as the objective func tion coefficient of X 1X 2X 1 or X 2 are changing. If the coefficient of W (prof it from increased productivity) lies between +0.19=.81 and .02=.02 the values for the de cision variables would remain the same. If the right hand side value of the total maximum OA constraint, which forces the total amount of OA below 140-cfm/person, stays above 140=44, the value of the decision variables will remain unchanged. Simila rly, if the right hand side value of the ASHRAE constraint stays below 20+24=44, the results of the solution would remain unchanged.

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102 Figure 5-6. Case 1MS Excel So lver sensitivity report The sensitivity report for Case 2 is given in Figure 5-7. According to the report, the Allowable Increase/Decrease columns indi cate that, provided the coefficient of X 1 in the objective function lies between 245+75.79=320.79 and 245=235, the values of the variables in the optimal LP solution will remain unchanged. Also, if the coefficient of X 2 stays below 235+10=245, the values for the decision variables would not change. However it is important to note that for the ranges mentioned above, the actual optimal solution value would change as the objective function coefficient of X 1 or X 2 is changing. Similarly, if the coefficient of the deci sion variable, W lies between +0.14=.86 and

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103 .16=.16 the solution to the model will st ill remain valid while the objective function value changing. If the right hand side value of the ASHR AE constraint, which forces the total amount of OA above 20-cfm/person, stays below 20+18=38, the value of the decision variables will remain unchanged. Also, if the right hand side value of the maximum total OA constraint stays above 140-102=38, the results of the case would remain the same. Figure 5-7. Case 2-MS Excel Solver sensitivity report The sensitivity reports given in Fi gure 5.6 and 5.7 provide a number of informational data about the range of validity of the model. Howeve r it does not include

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104 clear data regarding the effect of the demographic data. In order to see the impacts of these user-defined values on the results, the model is solved for a number of times to explore some thresholds values. As a result, it is observed that in Case 1, changing the number of occupants does not change the optimal values of variables. However it changes the total cost of the system. One of the threshold values of the number of occupants is 306. If the number of occupants is more than 306, th e total cost starts taking negative values as long as the fixed costs remain the same. This means that, for Case 1, when the number of occupants goes above 306, the owner can compensate the cost of the system in the first year and can start making a profit. To generalize, in Case 1 the number of occupants has an indirect correlation with the total a nnual cost of the system. In Case 1, if the average salary of th e occupants in the building does not stay between $16,235.00 and $20,331.00, the values for th e decision variables do not stay optimal anymore. This means the model with a new total salary beyond this range needs to be solved again in order to find the ne w objective value and more importantly the new values for decision variables. This is main ly due to the shift of the optimum extreme point to a different extreme point, which happe ns when at least one of the constraints changes its state of being bi nding or not binding. In general if the total salary of the occupants increases, the objective function (the total cost of the system) decreases due to the increase in total savings by increased productivity. It is observed that in Case 2 changing, the number of occupants does not change the optimal values of variables. However it ch anges the total cost of the system. The threshold value of the number of occupants for Case 2 is above 1000 people. This means

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105 that in this case it is almost impossibl e for the owner to start making profit due to limitations avoiding to exceed the number of occupants allowed in a commercial building. However in Case 2, the number of o ccupants has an indirect correlation with the total annual cost of the system (objective function). In Case 2, if the average salary of th e occupants in the building stays between $17,298.00 and $23,158.00, the values for the decision variables remain the same. This means that the model with a value outside of th is range needs to be solved again in order to find the new objective value and the new va lues of the decision variables. This is mainly due to the shift of the optimum extr eme point to a different extreme point, which happens when at least one of the constraint s changes its state of being binding or not binding. In general if th e total salary of the occupants increases, th e objective function (the total cost of the system) decreases due to the increase in total savings by increased productivity. In general for both cases, if the to tal salary of the occ upants increases, the objective function (the total cost of the system) decreases. Summary of Chapter The solution to the optimi zation problem is generated by the use of MS. Excel Solver In order to generate the solution, two imaginary cases are developed. The parameters associated with each case are pl ugged in the spreadsheet and the model is solved. The results showed that the ASHR AE minimum requirement of 20-cfm/person OA might not always be the optimum decision in all cases when the productivity costs are taken into consideration. The solution to Case 1 indicates that 44 cfm/person would provide the most optimum solution for that spec ific case. Also the results of the Case 2 showed that using less efficient equipment w ould increase the total cost of IAQ control system while decreasing the amount of OA broug ht into the building. The results in this

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106 chapter also included the sensitivity repor ts and generated the correlations among the number of occupants, total cost of the system, and the total salary of the occupants in a building.

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CHAPTER 6 CONCLUSION Planning, design, and construction work should be based not on tight but on generous estimates as regards the time re quired for each phase. An extensive reserve capacity should be designed and built into th e building and its system s. Indoor air quality is a crucial part of the efforts towards mo re sustainable systems in construction and building technologies. The benefits of a better IAQ are widely known although the quantity of potential savings has not been very clear to a ma jority of the audience. This problem causes the building ow ners and managers, architec ts, or the contractors to choose systems and options that increase ener gy efficiency and decrease the hard costs which eventually decrease IAQ in their buildings. This study develops an optimization model that takes the operation and maintenance costs of a better IAQ into account combines them with potential soft cost savings and quantifies the true cost of a system under different circumstances. This study demonstrates that an optimization study by us ing linear programming can be used to prescreen the optimal IAQ measures in commercia l buildings in Florida. As a result, this study shows that meeting the minimum code recommendations may not always create the most optimum cost saving results. It is also clear that there is an indirect relationship between the total salary and the total cost of an IAQ system when th e initial cost of the system is held constant. The same indirect relationship is also observed between the number of the occupants and the total cost of the system in commercial buildings when the fixed costs are held constant. 107

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108 The model uses mixed integer linear programming to generate the optimization study. One of the advantages of linear program ming is the simplicity and the speed of the solution generation. However, it has been disc ussed earlier that there are several matters in this area that have nonlinear correlations. This study mo stly deals with the nonlinear functions by piece-wise linear ization with underestimating. Fu ture studies may consider configuring a nonlinear optimization problem th at concentrates more on the correlations among productivity, air cleaning, an d ventilation. However this would also require more studies developing realistic data for the effects of air cleaning and ventilation on productivity. Future research should also concentrate on the correlation between ventilation and air cleaning, which when proved would transform a linear objective function to a non-linear function. Users with diffe rent specific cases can also consider reevaluating the constraints list provided in this study. The constraints regarding air velocity, noise, and many more can be easily integrated in the model to represent more accurate scenarios. Future studies may also concentrate on including other soft costs introduced in this study but excluded from the model due to their stochastic nature such as litigation and health related costs. Thus stochastic modeling studies may be conducted towards an improved financial representation of the be nefits of a better IAQ in commercial buildings. Integrating marginal cost calcula tion methodologies into spreadsheet would be a very useful contribution towards improvi ng the proposed optimization model. Also integration of the developed optimization models for IAQ into the green building assessment tools such as LEED would strengthen the foundation of building assessment methods.

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109 The significance of the presented methodol ogy derives from the determination of the optimum IAQ measures for commercial bui ldings. Another signif icant contribution of this research is introducing the idea of applying operations research methodologies in the sustainable construction area. The methodology studied in this research can be used as a basis for similar building-related decisions such as buildings with different sizes, occupation, location, climate, business structur e or different management problems. This study is unique in terms of utilizing the mixe d integer linear programming in sustainable construction-related managerial decisions. Studies adapting the proposed optimization model would contribute to the current sust ainable building research by quantifying the benefits of better IAQ. This model also cont ributes to the clarifi cation of arguments on the conflicts among IAQ and energy efficiency issues, which would eventually help promote sustainable buildings.

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APPENDIX A WORKSHEETS This section includes 6 worksh eets that are adapted from an EPA study introduced earlier (Henschel 1999). The worksheets are slightly modified and si mplified for more specific use. Worksheet 1. Estimating the installed costs for increased OA (Central units) 6 1. Enter incremental increase in OA intake _____________ cfm 2. Enter the required cooling a nd heating capacity required for the HVAC unit in the building, to treat the increased OA (Refer to Table 4.1) 2a. Cooling capacity 2b. Heating capacity ______tons/1000 cfm ______ kW/1000cfm 3. Compute the incremental additional cooling capacity required for the HVAC unit to treat the increased OA (Line 1 x Line 2a 1000) ________tons 4. Enter the incremental cost per ton of increased cooling capacity corresponding to the capacity of HVAC unit. ($1250 if cooling capacity range between 0-20 tons) ($1120 if cooling capacity range is > 20 tons) $________/ton 6 For systems with economizers where the required OA increase can be achieved without enlarging the OA intake duct and without increasing the dimensions of the central exhaust ducting compared to initial design. 110

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111 5. Compute the estimated incremental increase in the installed costs to provide increased cooli ng capacity. (Line 3 x Line 4) $ _________ 6. Compute the incremental additional heating capacity for the HVAC unit in the building, to treat the increased OA. (Line 1 x Line 2b 1000) _________kW 7. Enter the incremental cost per ton of increased heating capacity corresponding to the capacity of the HVAC unit. ($95 if heating capacity range is between 0-10 kW) ($75 if heating capacity range is between 11-20 kW) ($50 if heating capacity range is between 21-40 kW) ($30 if heating capacity range is between 41-100 kW) ($18 if heating capacity ra nge is > 100 kW) $_______/kW 8. Compute the estimated incremental increase in the installed cost of the HVAC unit to provi de increased heating capacity. (Line 6 x Line 7) $ __________ 9. Enter the total incremental increase in installed cost resulting from the specification of an HVAC system having a greater cooling and heating cap acity. (Line 5 + Line 8) $ __________

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112 Worksheet 2. Estimating the installed costs for increased OA (dedicated OA unit) 7 1. Enter the total OA intake rate that is required for the building. _________ cfm 2. Enter the required cooling capacity per 1000 cfm OA for the climate of the city building is locate d. (Refer to Table 4.1) _____ tons/1,000 cfm 3. Compute the total cooling capacity required to treat the increase in OA flow into the build ing. (Line 1 x Line 2 1000) __________ tons 4. Enter the total cost per ton of increased cooling capacity corresponding to the capacity of HVAC unit. ($1500 if cooling capacity range between 0-5 tons) ($1250 if cooling capacity range is > 6 tons) $ __________ 5. Compute the estimated total installed costs of HVAC unit (excluding heating). (Line 3 x Line 4) $ __________ 6. Enter the required heating capacity per 1000 cfm OA for the climate of the users city. (Refer to Table 4-1) ______ kW/1000 cfm 7. Compute the total heating capacity required to treat the increased OA flow into the buildi ng. (Line 1 x Line 6 1000) __________ kW 8. Enter the total installed cost per kW of installing the required heating capacity in to the dedicated-OA unit. ($125 if heating capacity range is between 0-10 kW) ($80 if heating capacity range is between 11-20 kW) 7 It is assumed that a single rooftop direct expansion HVAC unit is installed, dedicated to treating the total OA flow being supplied to the building.

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113 ($50 if heating capacity range is between 21-40 kW) ($30 if heating capacity range is between 41-100 kW) ($18 if heating capacity range is > 100 kW) $_________/kW 9. Compute the total installed cost of incorporating the required heating capacity into th e dedicated OA unit. (Line 7 x Line 8) $__________ 10. Compute the total cost of the new dedicated-OA unit treating the total OA flow entering the building. (Line 5 + Line 10) $__________

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114 Worksheet 3. Estimation of Annual Operating Costs for Increased OA 1. Enter the incremental increase in OA intake rate that is required for the entire building, beyond the originally designed rate (use 1 cfm for a unit cost). _________ cfm 2. Enter the overall Energy Efficiency Ratio (EER) for the cooling system in the building. (As default, assume EER=10 Btu/h/W) (If the compressor/condenser of the cooling system is driven by a source other than an electric motor, system efficiency should be expressed in the appropriate units of Btu/hr cooling output per un it energy input. ______Btu/h/W 3. Enter the overall efficiency of the heating system in the building. (As default, assume an efficien cy of 1.0 for electricity and 0.7 for gas or oil.) _____Btu/h per Btu/h 4. Enter the unit costs of the appli cable utilities used as energy sources in the building: 4a. Cost of electricity, if applicable (Default: $0.09/kWh) 4b. Cost of natural gas, if a pplicable (Default: $0.7/therm) 4c. Cost of fuel oil, if applicable (Default: $2.2/gal) ________$/kWh ________$/therm _________$/gal 5. Enter the average number of hours per day, and the days per week, that OA is being supplied to the building. 5a. Hours per day 5b. Days per week ________hours/day ______days per week

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115 6. Enter the value for the annual cooling energy that is required by the air stream, per incrementa l cfm of OA (Refer to Table 4-2) _______Btu/yr/cfm 7. Table 4-2 is based on operation at 13 hours/day and 5 days/week. If the users system operates on a significantly different cycle, correc t the figure on Line 6. (Line 6) x (Line 5a ) x (Line 5b 5) ________Btu/yr/cfm 8. Calculate the total energy i nput required to the cooling system, considering system efficiency: (Line 1) x (Line 7) (Line 2) 1000 W/kW [Note: The form of this equa tion assumes that the cooling system is driven by a compressor having an electric motor, that Line 8 thus has the units of kW h/yr. If this is not the case, modify the units of Line 2 (and thus of Line 9) accordingly] ________kWh/yr 9. Calculate the annual energy cost associated with cooling the incremental additional OA: (L ine 8) x (Line 4a) $_______/yr 10. Enter the value for the annua l heating energy that is required by the air stream, per incremental cfm of OA (Refer to Table 4-2 ) ________Btu/yr//cfm 11. Correct the annual heating ener gy on Line 10 if the users system operates on a significantly different cycle from 13 hr/day, 5 days/week: (Line 10) x (Line 5a 13) x (Line 5b 5) ________Btu/yr/cfm

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116 12. Calculate the total energy i nput required to the heating system, considering system efficiency: (Line 1) x (Line 11) (Line 3) _________Btu/yr 13. Compute the amount of input en ergy to the system that is required to provide the Bt us indicated on Line 12: 13a. Line 12 x (1 kWh/3413 Btu) (electric heat) 13b. Line 12 x (1 therm/100,000 Btu) (gas heat) 13c. Line 12 x (1 gal/140,000 Btu) (fuel oil heat) _________kWh/yr ________therms/yr ________gal/yr 14. Calculate the annual energy co st associated with heating the incremental additional OA (Line 13a x Line 4a for electric; Line 13b x Line 4b for gas; Line 13c x Line 4c for oil) $__________/yr 15. Calculate the total annual en ergy cost associated with cooling and heating the incremental additional OA (Line 9 + Line 14) $__________/yr

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117 Worksheet 4. Estimation of annual maintenance costs for increased OA 1. Enter the number of new OA inta ke fans, if applicable. ________fans 2. Enter the number of new central exhaust fans, if applicable ________ fans 3. Enter the total number of ne w fans, if applicable _________fans 4. Enter the estimated additional maintenance labor hours per year per new fan. (Default: 5 hours/year/fan) _______hr/yr/fan 5. Enter the estimated hourly labor rates for fan maintenance personnel. $________/hr 6. Compute the annual mainte nance cost increase for additional fans (Line 3 x Line 4 x Line 5) $_______ /yr 7. Enter the number of new dedicated-OA units, if applicable _______ units 8. Enter the estimated additional maintenance labor hours per year per new dedicated-OA unit. (D efault 20 hours/yr//unit) ________hr/yr/unit 9. Enter the estimated hourly labor rates for HVAC maintenance personnel. $ ________/hr 10. Compute the annual maintenan ce cost increase for the new dedicated-OA units. (Line 7 x Line 8 x Line 9) $________/yr 11. Compute the total incremen tal annual maintenance cost associated with the increase in OA ventilation rate (Line 6 + Line 10, as applicable) $_________/yr

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118 Worksheet 5. Estimation of total annualized costs for increased OA 1. Enter the total installed cost of the equipment required for the increase in ventilation rate. Obtain this value from: Worksheet 1, Line 9 or Worksheet 2, Line 10 $__________ 2. Enter the total incr emental annual operating cost associated with the increase in ventilation rate (Worksheet 3, Line 15) $__________/yr 3. Enter the total incrementa l annual maintenance cost associated with the increase in ventilation rate (Worksheet 4, Line 11) $__________/yr 4. Enter the equipment lifetime, n, that will be assumed for these calculations (comm only 10 or 20 years) __________yr 5. Enter the annual interest rate, i, that will be assumed for these calculations. __________% 6. Using the values n and i, calcu late the appropriate value for CRF by using Formula 4.2 in Chapter 4. ___________ 7. Compute the average annual capital charge (Line 1 x Line 6) $_________/yr 8.Compute the annual operati ng and maintenance (O&M) costs associated with the increas e in ventilation rate (Line 2 +Line 3) $________/yr 9. Compute the total annualized cost associated with the increase in OA ventilation rate (Line 7 + Line 8) $ ________/yr

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119 Worksheet 6. Estimation of annual operating cost s for central indoor air cleaners 1. Enter the total flow through the air cleaner _________ cfm 2. Enter the number of hours pe r year that the central air handler (and the indoor air clean er) will be opera ting. (Default: 3,276 hr/yr, for 13 hr/day, 5 da ys/week, excluding holidays) ________ hr/yr 3. Enter the unit cost of electricity (Default: $0.09/kWh) $________/kWh 4. Enter the Electric Input Ratio (EIR) for the cooling system on which the air cleaner is to be installed. (Default: 0.34 kW/kW) ________kW/kW 5. Enter the overall energy efficien cy of the central air handler. (Default: 0.50 for fans<1000 cfm or 0.65 for fans>1000 cfm) ________hp out/hp in 6. Enter the average pressure drop across the filter over its lifetime (ranging from unloaded at the outset, to completely loaded with collected particulat e prior to replacement of the media) (Default: 1 in. WG) _______ in. WG 7. Compute the required incremental additional power input to the fan/motor, required to en able the flow on Line 1 to overcome the added pressure drop identified in Line 6. (Line 1) x (Line 6) x [(5.19 lb /ft)/(in.WG)] x [(1 hp)/(33,000 ft-lb/min)] (Line 5) _______ hp in 8.Compute the incremental a nnual energy consumption resulting from the added fan power: ________kWh/yr

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120 (Line 7) x (0.746 kW/hp) x (Line 2) 9. Compute the incremental annual energy cost associated with the increased fan power required to handle the filter pressure drop: (Line 8) x (Line 3) $ ________/yr 10. Compute the incremental addi tional energy input required to the cooling system, to remove the additional heat created by this increase in fan power. ________kWh/yr 11. Compute the incremental a nnual energy cost associated with the increased cooling ener gy consumption necessitated by the increase in fan power. (Line 10 x Line 3) $_________/yr 12. Compute the total increm ental annual operating cost associated with the addition of a media filter for indoor particulate control (Lin e 9 + Line 11) $_________/yr

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APPENDIX B MS EXCEL SOLVER Figure B-1. MS Excel screen that shows the c onfiguration of the vari ables, constraints, and the objective function on a spreadsheet. 121

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122 Figure B-2. MS Excel and Solver screen showing the integration of objective function and the constraints in to the Solver module.

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123 Figure B-3. MS Excel screen and the options menu of the Solver module.

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LIST OF REFERENCES AIASF (American Institute of Archit ects San Francisco Chapter) (August 2001). Building a Case for Building Performance Retrieved May 15, 2005, from http://techstrategy.com/lineonline/aug01/page4aug01.html ALA (American Lung Association) (February 2000). Air Quality in Large Buildings. American Lung Association. Retrieved March 5, 2005, from http://www.lungusa.org/site /pp.asp?c=dvLUK9O0E&b=35987 ALA (American Lung Association), EPA (E nvironmental Protection Agency), CPSC (Consumer Product Safety Commission), and AMA (American Medical Association) (1994). Indoor Air Pollution: An Introduction for Health Professionals. US Government Printing Office: Washington. Al-Homoud, M. (1997). Optimum Thermal Design of Air-Conditioned Residential Buildings. Building and Environment, Vol. 32, No. 3, pp. 203-210. ACGIH (American Conference of Govern mental Industrial Hygienists) (1989). Guidelines for the assessment of bioaerosols in the indoor environment American Governmental Industrial Hygienists: Cincinnati. ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (1989). Ventilation for Acceptable Indoor Air Quality, Standard 62-1989. American Society of Heating, Refrigerat ion, and Air Conditioning Engineers, Inc: Atlanta, GA. ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (1992). Gravimetric and Dust-Spot Procedures for Testing Air-Cleaning Devices Used in General Ventilation fo r Removing Particulate Matter Standard 52.1-1992. American Society of Heating, Refrigerat ing, and Air-Conditioning Engineers, Inc: Atlanta, GA ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (1997). ASHRAE Handbook: Fundamentals, Chapter 26 (Climatic Design Information) American Society of Heating, Refrigerating, and Air-Conditioning Engineers, Inc: Atlanta, GA. ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (1999). Ventilation for Acceptable Indoor Air Quality, Standard 62-1999. American Society of Heating, Refriger ation, and Air Conditioning Engineers: Atlanta, GA. 124

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125 ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (2001). Ventilation for Acceptable Indoor Air Quality, Standard 62-2001. American Society of Heating, Refriger ation, and Air Conditioning Engineers: Atlanta, GA. ASHRAE (American Society of Heating, Re frigerating, and Air-C onditioning Engineers) (2004). Ventilation for Acceptable Indoor Air Quality, Standard 62-2004. American Society of Heating, Refriger ation, and Air Conditioning Engineers: Atlanta, GA. Atthajariyakul, S. & Leephakpreeda, T. (2004). Real-time determination of optimal indoor-air condition for ther mal comfort, air quality and efficient energy usage. Energy and Buildings, Vol. 36, pp. 720-733. Baker, N. & Steemers, K. (2000) Energy and Environment in Architecture: A Technical Design Guide E & FN Spon: London. Banham, R. (1969) The Architecture of the Well-Tempered Environment The University of Chicago Press: Chicago. Bas, E. (1993) Indoor Air Quality in the Building Environment Business News Publishing Company: Troy, MI. BIOTECH (July 2005) Glossary Retrieved March 8, 2005, from http://www.biotecinc.com/Glossary.htm Bouchlaghem, N. (2000). Optimising the design of building envelopes for thermal performance. Automation in Construction, Vol. 10, No. 1, pp. 101-112. Burgess, W. A., Ellenbecker, M. J., and Treitman, R. D. (2004). Ventilation for Control of the Work Environment. Wiley Interscience: Hoboken, NJ. Caldas, L.G. & Norford, L.K. (2002). A de sign optimization tool based on a genetic algorithm. Automation in Construction, Vol. 11, No. 2, pp 173-184. Conlin, M. & Carey, J. (June 5, 2000). Is Your Office Killing You Business Week, Issue 3684, pp. 114-128. Chelsea Group, Ltd. (July 31, 2000). People are willing to spend money to improve indoor air quality. Press release: Itasca, IL. CRES (Corporate Real Estate Solutions) (July 2005). Glossary of Corporate Real Estate Solutions Retrieved March 4, 2005, from http://www.crescorp.com/glossary/default.htm Damiano, L. (2001) The Real Costs of P oor Indoor Air Quality Retrieved April 10, 2006, from http://www.automatedbuildings.com/n ews/jan01/articles/ ebtrn/ebtrn.htm

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126 Damiano, L. (2005) The Real Costs of P oor Indoor Air Quality EBTRON Inc. Retrieved February 18, 2005, from http://www.ebtron.com/indoor_air_quality/f eature_articles/real_costs_of_poor_ind oor_air_quality_01.htm Daniels, K. (1998). Low-Tech, Light-Tech, High-TechBuilding in the Information Age. Birkhauser Publishers: Berlin. Dobney, S. (1997), The Master Architect Series II: Norman Foster Selected and Current Works of Foster and Partners Everbest Printing: Hong Kong. ELI (Environmental Law Institute) (2005). Brownfields Glossary Retrieved January 18, 2006, from http://www.brownfieldscente r.org/big/glossary.shtml European Commission (1996). Indoor Air Quality and the Us e of Energy in Buildings, Report No: 17, Retrieved March 6, 2005, from http://www.inive.org/medias/ECA/ECA_Report17.pdf Fischer, V. & Grneis, H. (1997). Sir Norman Foster and Partners Commerzbank, Frankfurt am main Axel Menges: Stuttgart/London. Fitch, J. M. & Bobenhausen, W. (1999). American Building Environmental Forces That Shape It Oxford University Press: New York Gamble, J. M., Richards, P. T., Peters on, M., and Castellan, R.M. (1986). Building Related Respiratory Symptoms: Problems in Identification. Proceedings of the ASHRAE Conference IAQ, pp. 16-30. Atlanta, GA. Goodland, R., & Ledec, G. (1987). Neoclassical economics and principles of sustainable development. Ecological Modeling, Vol. 38, pp. 19-46. Gustafsson, S. 2000. Optimisation and simulation of building energy systems. Applied Thermal Engineering, Vol. 20, pp 1731-1741. Heidegger, M. (1976). Basic writings from Being and Time to the Task of Thinking Harper & Row: New York. Henschel, D. B. (1999). A Preliminary Methodology for Ev aluating Cost-Effectiveness of Alternative Indoor Ai r Quality Approaches US Environmental Protection Agency, EPA/600/R-99/053, Washington, DC. Holdren, J. P., Daily, G. C., and Ehrlich, P. R. (1995). The Meaning of Sustainability: Biogeophysical Aspects. The World Bank: Washingt on, D.C. Retrieved April 8, 2004, from http://dieoff.org/page113.htm Irion, J., Al-Khayyal, F., and Lu, J.C. (2004). A Piecewise Linearization Framework for Retail Shelf Space Management Models Retrieved May 6, 2006, from http://www.optimization-onlin e.org/DB_FILE/2004/10/967.pdf

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127 Isola, A. (1997). Value Engineering: Practical Applications for Design, Construction, Maintenance & Operations RS Means Company: Kingston, MA. Kibert, C. J., Sendzimir, J., and Guy, G. B. (2002). Construction Ecology: As the Basis for Green Buildings. Spon Press: London. Kirk, S. J. & DellIs ola, A. J. (1995). Life Cycle Costing for Design Professionals. McGraw Hill Inc: New York. Kumar, S., Fisk, W. J. (2002). IEQ and the Impact on Employee Sick Leave. ASHRAE Journal Vol. 44, No. 7, pp. 97-98. Kumar, V., S., Hanna, A. S., and Nataraja n, P. (2003). Application of Fuzzy Linear Programming in Construction Projects. International Journal of IT in Architecture, Engineering, and Construction, Vol. 1, Issue. 4, pp. 265-274. Lehner, F., Bierter, W., and Charles, T. (1999). Resource Productivity, Competitiveness, and Employment in the Advanced Economies. Retrieved August 12, 2005, from http://www.factor10-institute.org/pdf/charles.pdf MAEPP (Massachusetts Environmentall y Preferable Products Program) (2006) Massachusetts EPP Glossary of Terms Retrieved May 16, 2006, from http://www.mass.gov/epp/info/define.htm Marks, W. (1997). Multicriteria Optimisati on of Shape of Energy-Saving Buildings. Building and Environment, Vol. 32, No. 4, pp 331-339. McCleary, P. (1983). An Interpretation of Technology. Journal of Architectural Education, Vol. 37, No. 2, pp. 2-4. Mendell, M., Fisk, W., Kreiss, K., Levin, H., Alexander, D., Cain, W., Girman, J., Hines, C., Jensen, P., Milton, D., Rexroat, L ., and Wallingford, K (2002). Improving the Health of Workers in Indoor Environments: Priority Research Needs for a National Occupational Research Agenda. American Journal of Public Health, Vol. 92, No. 9, pp. 1430-1440. Milton, D. K., Glencross, M., Walters, M. D. (2002). IEQ and the Impact on Employee Sick Leave. ASHRAE Journal, Vol. 44, No.7, pp.97-98. Nielsen, T.R. (2002). Optimisation of Buildings with Respect to Energy and Indoor Environment PhD dissertation, Technical Univ ersity of Denmark: Denmark. OSHA (Occupational Safety and H ealth Administration) (1994). Proposed Indoor Air Quality Regulations Federal Register #: 59:15968-16039, CFR Title: 29. Papamichael, K. (1998). Application of Information T echnologies in Building Design Decisions Ernest Orlando Lawrence Berkeley Na tional Laboratories, University of California: Berkeley, CA.

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128 PIER (Public Interest Energy Program) (2005). Large VAVs, Low Loads, and High Performance California Energy Commission: CA. Retrieved May 8, 2006, from http://www.esource.com/public /pdf/cec/CEC-TB-19_VAVs.pdf Reel Grobman & Associates (2005). Newsletter Archive Retrieved June 2, 2005, from http://www.reelgrobman.com/html/news.html Rizzi, E. (1980). Design and Estimating for Heati ng, Ventilating, and Air Conditioning Litton Educational Publishing: New York. Segen, J. C. (1992). Dictionary of Modern Medicine. Parthenon Publishing: New Jersey. Seitz, T.A. (1989). NIOSH Indoor Ai r Quality Investigations 1971-1988. Proceedings of. Indoor Air Quality International Symposium, pp. 163-171. American Industrial Hygiene Association. Akron: Ohio. Simon, H. A. (1960). The New Science of Management Decision Harper and Brothers: New York. Slap A. J.(1995). The legal aspe cts of indoor air and health. Occupational Medicine: State of the Art Reviews, Vol. 10, No. 1, pp. 205-215. Stein B. & Reynolds J. S. (1992). Mechanical and Electrical Equipment for Buildings John Wiley & Sons: New York. USEPA (United States Environmen tal Protection Agency) (1991). Building Air Quality: A Guide for Building Owners and Facility Managers Retrieved March 3, 2005, from http://www.epa.gov/iaq/la rgebldgs/baqtoc.html USEPA (United States Environmen tal Protection Agency) (1993). Targeting Indoor Air Pollution: EPAs Approach and Progress. EPA Office of Air and Radiation. Retrieved March 3, 2005, from http://www.epa.gov/iaq/pubs/targetng.html USEPA (United States Environmen tal Protection Agency) (2005a). EPA Green Indoor Environments Program Retrieved March 3,2005, from http://www.epa.gov/iaq/greenbuilding USEPA (United States Environmen tal Protection Agency) (2005b). IAQ Tools for Schools Kit IAQ Coordinators Guide. Retrieved February 25, 2005, from http://www.epa.gov/iaq/schools/tfs/guide5.html USEPA (United States Environmen tal Protection Agency) (2005c). Indoor Air Quality for Schools. Retrieved June 16, 2006, from http://www.epa.gov/iaq/schools/tfs/ pdf_files/reference_guide.pdf USGBC (United States Green Building Council) (2003). An Introducing to the U.S. Green Building Council and the LEED Building Rating System Retrieved April 8, 2005, from http://www.usgbc.org/Docs/About/usgbc_intro.ppt

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129 Wargocki, P., Wyon, D., P. and Fanger, P., O. (2000). Productivity is affected by the Air Quality in Offices. Healthy Buildings, Vol. 1, pp. 635-640. WCED (World Commission on Environment and Development) (1987). Our Common Future. Oxford University Press: New York. Westphalen, D. and Koszalinski, S. (1999). Energy Consumption Characteristics of Commercial Building HVAC Systems, Volume 2. US Department of Commerce: Springfield, VA. Wikipedia (2006a). Igloo Retrieved June 26, 2006, from http://en.wikipedia.org/wiki/Igloo Wikipedia (2006b). Genetic Algorithm Retrieved June 3, 2006, from http://en.wikipedia.org/wiki/Genetic_algorithm Winston, L., W. (1993). Operations Research: Applications and Algorithm Duxbury Press: Belmont, CA. WRI (World Resources Institute) (1992). Dimensions of Sustainable Development World Resources 1992-93: A Guide to the Global Environment Oxford University Press: New York. Wright, J.A., Loosemore, H.A. and Farmani, R. (2002). Optimization of building thermal design and control by multi-criterion genetic algorithm. Energy and Buildings, Vol. 34, No. 20, pp. 959-972. Wright, J. & Zhang, Y. (2005). An Ageing Operator and Its Use in the Highly Constrained Topological Optimiza tion of HVAC System Design. Proceedings of GECCO, pp. 2075-2082.Washington: DC.

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BIOGRAPHICAL SKETCH Bilge Gokhan Celik was born in Monter ey, California, on April 1978. He has graduated from Anadolu University in Tu rkey in 2000 with a bachelors degree in architecture. He has completed his Master of Science degree in the Natural and Applied Sciences Institute of Anadolu University in 2002 with a major in architecture and a minor in building construction. Since 2000, Bilge Gokhan Celik has worked on many architectural as well as construction, preservation and interior design projects in Turkey, a nd in the USA. Bilge Gokhan Celik has also worked as a graduate research/teaching assistant in both Anadolu University and the University of Florida. Bilge Gokhan Celik has been studying for his Doctor of Philosophy degree in the School of Building Construction at the College of Design, Construction, and Planning since 2002. 130


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Permanent Link: http://ufdc.ufl.edu/UFE0015584/00001

Material Information

Title: Decision Model to Optimize Indoor Air Quality in Commercial Buildings in Florida
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0015584:00001

Permanent Link: http://ufdc.ufl.edu/UFE0015584/00001

Material Information

Title: Decision Model to Optimize Indoor Air Quality in Commercial Buildings in Florida
Physical Description: Mixed Material
Copyright Date: 2008

Record Information

Source Institution: University of Florida
Holding Location: University of Florida
Rights Management: All rights reserved by the source institution and holding location.
System ID: UFE0015584:00001


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DECISION MODEL TO OPTIMIZE INDOOR AIR QUALITY
IN COMMERCIAL BUILDINGS IN FLORIDA
















By

BILGE GOKHAN CELIK


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


2006




























Copyright 2006

By

Bilge Gokhan Celik


































This dissertation is dedicated to my dear parents, Kemal and Nukhet Celik. This endeavor
would not have been possible without their unwavering patience, support, and love.
















ACKNOWLEDGMENTS

I would like to acknowledge Dr. Charles J. Kibert for his support throughout the

past four years and for giving me the opportunity to work in a very interesting area. I

have learned substantially from his uncompromising emphasis on quality and meaningful

research, and he has truly been a mentor in the fullest sense of the word.

I would like to thank Dr. Kevin Grosskopf for sharing his intelligent ideas and for

giving me the opportunity to work for the MC3 prOj ect, which helped me both financially

and academically. I am very thankful to Dr. Svetlana Olbina for her support, patience and

most importantly for always having the time to listen. I would like to thank Dr. Abdol

Chini and Dr. Paul Oppenheim for their insightful feedback in assuring a quality

outcome. I also want to thank to Dr. Haldun Aytug for sharing his expertise, and for

sparing time to teach for hours whenever I needed. I would like to acknowledge Fidan

Boylu who has always been there to encourage me either in person or on the phone for

whatever the circumstances might be. Words are inadequate to express my thanks to the

Erenguc Family who have made me feel home since the beginning of my j ourney at

University of Florida. I would like to acknowledge Gokce, Deniz, and Goksu Celik for

sparing their time and money on endless phone conversations. Finally I would like to

thank a very special person, D. Arzu Erenguc. It is a fact that none of this would be

possible without her help. She has enlightened me with her patience, wisdom, and

personality. Her support helped me minimize the burden on my family and myself.




















TABLE OF CONTENTS


page

ACKNOWLEDGMENT S ............ ...... .__ .............. iv....


LI ST OF T ABLE S ........._._ ...... .__ .............. vii...


LI ST OF FIGURE S ........._._ ...... .__ .............. viii..


AB S TRAC T ..... ._ ................. ............_........x


CHAPTER


1 INTRODUCTION ................. ...............1.......... ......


Introducti on ................. ...............1.................
Statement of the Problem. ................ ............... ........ ......... ........ ...3

Purpose of the Study ................. ...............4.......... .....
Research Questions ................. ...............4.................
Significance of the Study ................. ...............5................
Assumptions and Limitations .............. ...............6.....
Or ganization of the Study ................. ...............8.......... .....

2 REVIEW OF THE LITERATURE .............. ...............9.....


Introducti on ............... ... ......... .... .......... .............
Sustainability and the Built Environment ................. ...............10........... ...
Humans and Their Environment ................. ...............12................
Humans and Technology ................. ......... ...............13......
Humans and Buildings .............. .... ........... ............1
Indoor Air Quality (IAQ) in Commercial Buildings ................ ................ ...._.21
Standards, Regulations and Guidelines .............. ...............23....
Sources of Indoor Air Pollutants ................ .......................... ..........29

IAQ Control Techniques .............. ...............32....
IAQ and Health ................. ...............39........... ....
IAQ and True Costs ................. ...............40................
Optimization of IAQ ................. ...............47........... ....
Review of Literature Summary .............. ...............51....












3 METHODOLOGY .............. ...............53....


Introducti on ................. ...............53.................
Research Questions............... ...............5
Research Design .............. ...............54....
Research Methodology .............. ...............60....
Population ................... ...............61.......... ......
Summary of Methodology ................. ...............61................


4 DEFINING PARAMETERS AND THE OPTIMIZATION MODEL ................... ....63


Introducti on ............... ... .......... ... ........... .............6
Estimating the Costs of Improved Ventilation ................. ................ ............65
Estimating Installed Costs for Increased Ventilation ............... ........ ...............6
Estimating Operating and Maintenance Costs for Increased Ventilation ...........70
Estimating the Costs for Air Cleaning ...._ ......_____ .......___ ...........7
Estimating Installed Costs for Air Cleaners .............. .... ...............75..
Estimating Operating and Maintenance Costs for Air Cleaners .........................76
Estimation of Income Function from Increased Productivity due to Increased IAQ .78
Defining the Optimization Model ...._ ......_____ .......___ ............8
Decision Variables............... ...............8

Obj ective Function ............ _...... ._ ...............86...
Decision Constraints............... ..................8
User-Defined Independent Variables as Input Data.............___ ........._ ......90
Summary of Chapter ............. ...... ._ ...............92....


5 RE SULT S AND DI SCU SSION ............... ...............9


Introducti on ............. ...... ._ ...............93....
Solution to the M odel .............. ...............93....
C ase 1 .............. ...............95....
C ase 2 .............. ...............98....
Sensitivity Analysis .............. ...............100....
Summary of Chapter ............. ...... ._ ...............105...

6 CONCLUSION................ ..............10


APPENDIX


A WORKSHEETS ............ _...... ._ ...............110...


B MS EXCEL SOLVER ............. ...... ._ ...............121...


LIST OF REFERENCES ............_ ..... ..__ ...............124..


BIOGRAPHICAL SKETCH ............_...... ._ ...............130...


















LIST OF TABLES


Table pg

2-1 Historical progress of building issues and concepts ................. .......................21

2-2 Comparison of regulations and guidelines for acceptable contaminant levels ........3 1

2-3 Collection device characteristics. .............. ...............38....

2-4 Complaints on floors with outside air provided per person. ............. ...................40

2-5 Potential economic costs and benefits of increasing ventilation rate.............._.._.. ...46

4-1 Incremental increases in cooling and heating capacities..........._.._.._ ........_.._.. ...68

4-2 Incremental annual cooling and heating energy requirements ................ ...............71

4-3 Approximate installed costs of various in-duct particulate air cleaners. ................. .76

4-4 Approximate replacement costs of media cartridges. .........._.._. ........_.._.........78

4-5 Ventilation rate (cfm per person) vs. performance index ............... ... .........__ ...78


















LIST OF FIGURES


Figure pg

2-1 Historical design for the Eskimo igloo, Baffin Island, Canada. .............. ..... .........._17

2-2 Mud masonry Indian House. ............. ...............18.....

2-3 Larkin Administration Building, Buffalo, NY, 1906 by F. L. Wright. ................... .18

2-4 Hong Kong and Shanghai Banking Headquarters, Hong Kong. .............. ..... ..........19

2-5 Commerzbank Headquarters, Frankfurt, Germany. ................... ...............2

2-6 Logic diagram for selecting an IAQ control approach.............___ ........._ ......33

2-7 Typical HVAC system components. .............. ...............35....

2-8 Overall performance of simulated office work as a function of sensory pollution..45

2-9 Building design decisions require performance prediction and evaluation. ............48

2-10 PMV and thermal sensation. ............. ...............48.....

2-11 Example pay-off characteristic ................. ...............50........... ...

3-1 Research design ................. ...............54........... ....

3-2 Example illustration for the proposed LP model. ............. .....................5

3-3 Summary of methodology in comparison to Simon' s decision modeling process. .62

4-1 The performance index and its correlation with the supplied OA amount. .............79

4-2 PPI and its correlation with the amount of OA. ............. ...............80.....

4-3 An example for piecewise linear overestimate and underestimate. .........................81

4-4 One-piece linearization of the PPI vs. OA function ................. .......................81

4-5 Possible air cleaner locations. ............. ...............85.....

5-1 MS EXCEL 9 Spreadsheet developed. ............. ...............94.....











5-2 Case 1-MS Excel 9 screen for solution. ............. ...............96.....

5-3 Case 1-Answer sheet generated by MS Excel Solver 9~................... ...............9

5-4 Case 2-MS Excel 9 screen for solution. ............. ...............99.....

5-5 Case 2-Answer sheet generated by MS Excel Solver 9. ................... ...............10

5-6 Case 1-MS Excel Solver 9 sensitivity report............... ...............102

5-7 Case 2-MS Excel Solver 9 sensitivity report .............. ...............103....

B-1 MS. Excel screen that shows the configuration of the variables.............._.._..........121

B-2 MS Excel and Solver screen showing the integration of obj ective function. ........122

B-3 MS Excel screen and the options menu of the Solver module. .............. .............123
















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

DECISION MODEL TO OPTIMIZE INDOOR AIR QUALITY IN COMMERCIAL
BUILDINGS IN FLORIDA

By

Bilge Gokhan Celik

August 2006

Chair: Dr. Charles J. Kibert
Major Department: Design, Construction, and Planning

Sustainable design and construction practices have been developing rapidly. Many

building experts apply sustainable building strategies to their practices. One of the crucial

aspects of designing a sustainable building is creating a healthy and comfortable indoor

air quality (IAQ). Specific levels of indoor air pollutants may affect the health and

comfort of the occupants of a building. The problem starts with the lack of a decision

system for choosing a specific IAQ management option. The building industry is not

thoroughly aware of the consequences of different IAQ management methods and

decisions, and it lacks the resources to identify the "best" solutions to IAQ problems.

These consequences may result in added soft costs such as lost productivity, as well as

added hard costs such as the conditioning of the incoming outdoor air. This research

combines these two types of costs into a true cost and introduces a modeling

methodology of linear mathematical programming for optimizing IAQ in commercial

buildings. These analyses also explore the conflicts between IAQ and energy efficiency.









This research explores alternative IAQ control options in terms of improved ventilation

and air cleaning and presents an objective function and a set of decision variables, as well

as the technical, financial, and legal constraints. The significance of the research derives

from introducing the idea of applying operations research to construction management

and providing the conceptual background for formulating the optimization of IAQ in

commercial buildings. Defining a decision model for commercial buildings will help

decision makers such as designers, contractors, or building owners and managers in

making more sophisticated decisions regarding indoor air control technologies and

strategies.















CHAPTER 1
INTTRODUCTION

Introduction

The Massachusetts Environmentally Preferable Products Program (MAEPP)

defines sustainability as the process of conducting business in a resource conservative

and efficient manner so that operations do not compromise the ability of future

generations to meet their own needs (MAEPP 2006). Sustainability concerns have been

emerging in many different areas. The building industry is one of these areas that have

been integrating the concepts of sustainability into industry practices. Sustainable design

and construction of buildings deals with many different issues in buildings. One of these

is Indoor Environmental Quality (IEQ). The IEQ concept includes factors such as noise,

indoor air quality (IAQ), lighting, and acoustics. All of these factors affect the quality of

a building' s interior space. Consequently different levels of IEQ affect the comfort and

health of occupants differently. On the other hand, IAQ focuses specifically on the

control of indoor air pollutants.

Most people are more aware that not only outdoor air pollution but also indoor air

pollution can be damaging to their health. A public opinion survey of 1,000 full-time

workers reported that 95 percent of those interviewed ranked the quality of air at work as

very or somewhat important, and only 3 percent believed it was not important (Chelsea

2000). The United States (US) Environmental Protection Agency (EPA) studies of human

exposure to air pollutants indicate that indoor air levels of many pollutants may be 2 to 5

times, and occasionally more than 100 times, higher than outdoor levels (USEPA 1993).









These levels of indoor air pollutants are of particular concern because it is estimated that

most people spend as much as 90% of their time indoors. In contrary to outdoor air,

indoor air can be recycled constantly causing the air to trap and build up contaminants.

Common contaminants include smoke, dust, mold and spores, pollen, and odors. The

indoor air pollutants can be caused by several different reasons such as various

equipment, heating ventilation and air conditioning (HVAC) systems, human activities,

and building materials. Controlling these systems and many other sources of air pollution

involves measures to be taken at many stages of a building's lifecycle. Design,

construction, and occupancy phases are all crucial stages that can include activities and

decisions to affect IAQ.

One of the interesting contradictions of sustainable construction practices is

between IAQ and energy efficiency measures. Energy efficiency has become one of the

most important issues for many industries since the oil crisis took place in 1970s. This

trend has become stronger with the development of "green" building strategies,

environmentalism, and other movements that promote tighter building envelopes to

maximize the energy savings. However this trend unintentionally decreased the indoor air

quality of the buildings. Tighter building envelopes decrease the amount of outdoor air

(OA) supplied into the building, thus creating buildings that are mostly dependant on

mechanical systems. In several cases this approach created the Sick Building Syndrome

(SB S), which describes

situations in which building occupants experience acute health and/or comfort
effects that appear to be linked to time spent in a particular building, but where no
specific illness or cause can be identified; complaints may be localized in a
particular room or zone, or may be spread throughout the building. (BIOTECH
2005, p. 6)









The effects of poor indoor air quality are not limited to health problems. Buildings

with higher indoor air contaminant levels can possibly cause loss of productivity, legal

liabilities, and remediation costs. The problems associated with poor indoor air quality

are examined and explained in more detail in Chapter 2.

Statement of the Problem

The building itself generates many indoor air pollutants mainly due to poor choices

of building materials or furniture, and poor maintenance of HVAC systems. The main

obj ective for improving air quality is to determine the required levels of ventilation, air

filtering, and contaminant source management. The problem that the building industry is

facing is that there are no decision support tools other than the local and national

standards that can guide the decision makers with their choice of indoor air management

options in a more precise and cost-effective manner.

A common experience is that building regulations do not in themselves guarantee a

good indoor climate in specific cases. Mendell et al. (2002) explain that current building

codes are also based primarily on practical experience within the building sector and not

on health-related criteria. The maj or IAQ problems derive from frequent design,

construction, and operation defects. These defects usually create indoor environmental

problems deriving from indoor air contaminants such as mold, fungi, various bacteria,

and viruses. The environmental technology that is used in a building can either be a

contributor or a solution to the IAQ of a building.

Mendell et al. (2002) argue that science is not the limiting factor but rather

economic and institutional barriers are the primary barriers. Decisions affecting IAQ are

often made on lowest hard costs and this approach usually discourages spending more on









improving IAQ. The cost of poor IAQ commonly falls on occupants rather than on

building decision makers who may ignore the soft costs of IAQ measures.

Soft costs in the building industry are architectural, engineering, and legal fees as

distinguished from land and construction costs (Corporate Real Estate Solutions [CRES]

2005). Soft costs generally represent any costs that are not related to the actual land and

construction costs. Consequently the soft costs associated with IAQ may include but not

be limited to costs associated with productivity, health, insurance fees, litigation, etc. One

of the most important issues in regard to improving IAQ of a building thus reducing the

soft costs may be found in the relationship between occupant comfort and productivity.

Worker salaries constitute the maj or cost of operating a commercial building, generally

estimated at over 90% of the total operating cost, so that even a small increase in

employee productivity can considerably decrease a company's operating costs (American

Institute of Architects San Francisco Chapter [AIASF] 2001).

Purpose of the Study

The purpose of this research is to develop a decision model for optimizing the

control of indoor air pollutants in commercial buildings in Florida. The goal of the

research is to help decision makers determine the optimal indoor air management options

to maximize the benefits of a better indoor air quality.

Research Questions

The maj or research question to be investigated in this research is given below:

*Can an optimization model be developed to select effectively the optimal IAQ
measures in commercial buildings in Florida to meet or exceed the standards
required by code?

This study also explores the answers to the following question:










*What are the decision criteria for building owners and managers when choosing a
specific indoor air management option?

Significance of the Study

Decision-making processes for IAQ issues in the building industry have been

determined by the local and national regulations that may not always guarantee the

optimum decision. Building owners and managers or their representatives are not

completely aware of the consequences of different indoor air quality management

methods and decisions, and they may lack the means to identify the "best" solutions to

IAQ problems. The significance of this study derives from the determination of the

optimum IAQ options for commercial buildings in Florida. However the outcome model

of this study and its methodology would also be used as a basis of similar building-

related decisions such as different locations, different types of buildings, or even different

management problems.

From a wider perspective, this research contributes to current sustainable building

research in terms of quantifying the benefits of better IAQ in buildings, which would

eventually help promote sustainable buildings. The research also aims to contribute to the

clarification of arguments regarding the conflicts between IAQ and energy efficiency

issues from a quantitative point of view. In conclusion, defining a decision model for

commercial buildings will help decision makers such as designers, contractors, or

building owners and managers in making more sophisticated decisions regarding indoor

air control technologies and strategies. The model developed in this research may

potentially help commercial building owners and managers build long-term savings by

increasing the productivity of the workers and decreasing the losses due to worker health

and performance problems.










Assumptions and Limitations

Indoor air problems in buildings can appear in many different types of buildings.

However these problems are more common in commercial and institutional buildings due

to their dense population. This study only focuses on IAQ management in new

commercial buildings, where significant savings can be generated by increased worker

productivity and performance.

There are several types of IAQ management options in commercial buildings.

These options may include different technologies with various initial and lifecycle costs.

In order to limit the number of options, this study concentrates on the following two

categories:

* Improved Ventilation
* Air Cleaning

There are various situation and considerations under which one or more options

may be included, or excluded, as a candidate for IAQ control in a particular building.

Although in some cases one of these approaches might be the only logical candidate, this

research limits the research to buildings that would have the two above options as IAQ

control techniques. More detailed descriptions of these and some other options are given

in Chapter 2.

In order to control the different Eixed costs, the study limits the analysis to research

on marginal costs. Marginal cost may be defined as the "change in cost per exposure"

where exposure would be (concentration) x (number of occupants) x (time) (Henschel

1999). This research only focuses on buildings that are not located in regions or zones

where the outside air is a source of contamination such as industrial sites. It is also

assumed that the number of occupants inside a building will not exceed the limits that are









mentioned in ASHRAE Standard 62.1-2001 (American Society of Heating, Refrigerating,

and Air-Conditioning Engineers [ASHRAE] 2001).

The assumptions adapted while configuring the optimization model are given

below. Many of these assumptions aim to clarify the optimization model and set clear

boundaries on the potential applications of the model.

* The cost data regarding the proposed energy cost calculations are based on
equipment that runs on electricity. Simple modifications that are also mentioned in
this study would provide calculation methods for other sources of energy as well.

* The cleaners considered are only the particulate air cleaners with an average
removal efficiency of 65% or greater as measured in ASHRAE standard 52. 1-1992
(Henschel 1999).

* The model assumes that the total outdoor air (OA) ventilation will not go over 140
ofm assuming that above this value there would be additional fixed costs due to
equipment replacement and/or upgrade.

* As default the overall Energy Efficiency Ratio (EER) for the cooling system is
assumed to be 10 Btu/h/W.

* Overall efficiency of the heating system is assumed to be 1.0 Btu/h per Btu/h.
(Users may use 0.7 for systems that work with gas)

* The assumption is that in Florida, on average over the cooling and heating seasons,
all of the heat added to the air stream by the fan must be removed by the cooling
system (Henschel 1999).

* The assumption is that the productivity curves for air cleaning and the amount of
OA ventilation are independent from each other. However studies such as
Wargocki et al. (2000) state that the amount of pollution and the amount of
ventilation are in fact correlated when calculating the performance index. Yet there
is not enough data to actually quantify this dependency. In the case of generation of
these new data the model would become nonlinear.

* The assumption for the proposed cost calculation methods is that the heating
capacity range of the HVAC system is between 11 and 40 kW.

* The assumption is that the systems used in buildings have economizers where the
required OA increase can be achieved without enlarging the OA intake duct and
without increasing the dimensions of the central exhaust ducting compared to initial
design (Henschel 1999).









*The assumption is that if a dedicated-OA unit is to be installed in a new building, it
will be designed to condition all of the OA entering the building.

Organization of the Study

The maj or outline of the research is explained in more detail in the following

chapters. Chapter 1 introduces the problems regarding IAQ in commercial buildings, as

well as lists the research questions, purpose, limitations, and assumptions. Chapter 2

reviews the current literature that is relevant to IAQ issues in sustainable buildings.

Different techniques to control IAQ in commercial buildings, and the consequences of

change in indoor air quality are also investigated in Chapter 2. There are many studies

that demonstrate the importance of IAQ in commercial buildings and its effects on the

occupants of a building. Chapter 2 covers some of these important studies in terms of

their approach and results.

Chapter 3, which includes the design of the research as well as the tools and

methods used in the study, briefly explores the methodology of the research. Chapter 3

also introduces the research questions and the research population. Chapter 4 covers the

details of the methodologies for calculating the required parameters and introduces the

developed IAQ decision model. The solution to the model and the sensitivity analyses

along with the discussions of the solutions are presented in Chapter 5. Finally Chapter 6

presents an overall conclusion and the possible recommendations for future work.















CHAPTER 2
REVIEW OF THE LITERATURE

Introduction

This chapter explores the existing literature relevant to sustainable buildings and

specifically IAQ issues in commercial buildings. Buildings have significant impacts on

the environment and their occupants during construction, throughout their operation, and

during end-of-life (decommissioning). The US Green Building Council (USGBC) defines

"green" or "sustainable" building as a term that refers to design and construction

practices that significantly reduce or eliminate the negative impact of buildings on the

environment and its occupants through all life cycle phases of the building (USGBC

2003). This concept can be applied to design, construction, and operation of new

buildings or renovations of existing buildings.

The building industry is ever more focused on making its buildings more

sustainable, which includes using healthier, less contaminating, and more resource-

efficient practices. Indoor environmental quality (IEQ) deals with the quality of the air

and environment inside buildings, based on many different conditions that can affect the

health, comfort, and performance of occupants. These conditions may include

contaminant concentration, temperature, relative humidity, light, sound, and other factors

(USEPA 2005a). It is important to note that a good IEQ is a vital element of sustainable

buildings. Building owners, managers, occupants, architects and builders can all benefit

from the increased IEQ in terms of minimizing the negative health effects, legal liability,

and possible remediation cases.










IAQ is a crucial segment of IEQ and has maj or impacts on the overall IEQ of a

building. Improving IAQ involves to design, construct, commission, operate, and

maintain buildings in ways that decrease contaminant sources and remove contaminants

while ensuring that fresh outdoor air is persistently supplied.

Sustainability and the Built Environment

The problem of sustainability should first be explored in order to provide a strong

basis for the concept of sustainable buildings. The subj ect of a sustainable future is taking

place at the center of gravity of the triangle of environment, sociology, and economy.

Environmental problems, the magnitude and frequency of which are continuously

increasing, keep their place at the agenda of many countries rather than being just a local

concern. In order to Eind an answer to all of these worries, many different ideologies and

hypothesis are being discussed in today's world. One of these different proposals to

determine the relation between nature, human, and the built environment is sustainability

or sustainable development.

Many definitions of sustainable development have been offered, some general and

some more precise. The following definitions are some examples.

Development, which meets the needs of the present without compromising the
ability of future generation to meet their own needs. (World Commission on
Environment and Development [WCED] 1987, p. 43)

Using natural renewable resources in a manner that does not eliminate or degrade
them or otherwise diminish their renewable usefulness for future generations while
maintaining effectively constant or nondeclining stocks of natural resources such as
soil, groundwater, and biomass. (World Resource Institute [WRI] 1992, p. 2)

The net benefits of economic development, subj ect to maintaining the services and
quality of natural resources. (Goodland & Ledec 1987, p. 36)










To generalize and simplify various definitions, the definition of sustainability can

be summarized as a system that delivers services without exhausting resources over time.

It uses all resources efficiently in an environmental, social and economic sense.

In past years, sustainability has become a catchword capable of capturing the

attention not only of environmental scientists and activists but also of some mainstream

economists, social scientists, and policymakers. The reason for that is the sustainability of

the human activity in the biggest sense depends on technological, economic, political,

and cultural factors, as well as on environmental ones (Holdren et al. 1995). According to

this context, economists explain different ideas about sustainability. According to Lehner

et al. (1999), a sustainable economy is one that is capable of continuously securing and

reproducing the basis of its operation. This economy includes both the natural system

from which the economy extracts all the resources that it needs, and a variety of

economic and social factors. These factors may include knowledge and skills,

technology, social standards, and political standards and regulations, which determine the

capacity of an economy to generate wealth and living standards in society.

At this point instead of explaining all the definitions of various disciplines about

sustainability a more convenient approach may be to refer to the ideas of McHarg (Kibert

et al. 2002). He states that geologists, meteorologists, hydrologists, and soil scientists

were informed in physical science but not in real life; on the other hand, ecology and the

biological sciences were only aware of physical processes. He determined this problem as

the lack of integration within the environmental sciences.

Now one has to answer the question: How are all these discussions related to the

built environment? That is the question various disciplines try to answer and come finally









to the word of"Sustainable Construction". Sustainable construction can be defined as the

creation and maintenance of a healthy built environment using ecologically sound

principles (Kibert et al. 2002). Many different concepts are involved in creating the

healthy built environment. Energy, water, waste, materials, and IEQ are some of the

concepts to focus on when creating and maintaining a healthy built environment. Since

this study concentrates on the IEQ issues in buildings the following sections will be

exploring the relations between sustainability and IEQ in more detail.

Humans and Their Environment

Human beings have always had a mental and physical relationship with their

environment. Human beings themselves can be called a microenvironment and the

environment around them a macro environment (Fitch & Bobenhausen 1999). The

problem has always been to understand and balance the relations between these two

environments. There were times throughout history that had extreme environmental

conditions. There are currently regions in the world where sustaining a direct relationship

with the natural environment is almost impossible. In fact there are only few regions in

the world where people can survive without developing an "interface" between

themselves and nature (Fitch & Bobenhausen 1999). Fitch and Bobenhausen (1999) in

their "The American Building" rename the term "interface" as the third environment.

So what are the interfaces that people need in order to interact with the environment

around them? The simplest answer to this question would be "clothing". However,

wearing clothes has not always satisfied people, so they also have created spaces such as

buildings to live in. Controlling the environment of these spaces rather than controlling

the natural environment, has always been much easier. These comfort conditions for

humans depend on the essential requirements of their microenvironment. Several










conditions that are listed below determine the metabolic level of relationship between

humans and their environment (Fitch & Bobenhausen 1999).

* Thermal
* Aqueous
* Sonic
* Spatio-gravitational forces
* Atmospheric
* Luminous
* World of objects

Adjusting these conditions according to the specific individual needs forms the

basics of the configuration of IEQ. This is one of the means used to create the essential

conditions in the third environment and many issues have affected the use of this tool.

These issues and their solutions that concerned humans have been constantly changing

throughout the history. The discussion on controlling the third environment is related to

some other issues such as the use of science, technology and its integration in buildings.

These issues are discussed in the following sections.

Humans and Technology

According to Heidegger (1976) the purpose held by human beings has always been

to conquer the physical world in order to establish and extend the power and domain of

the human race itself over the universe. However, human freedom and victory over

nature has depended on the degree of knowledge about the laws of nature. The pure

knowledge of humans can be called "science" whereas the application of science is

known as "technology". Often the terms, technology and science, are confused. Science

deals with the natural world. Technology is the application of natural laws, which govern

the universe. This is not to say science and technology are unrelated. Science deals with

"understanding" while technology deals with "doing"(Heidegger 1976).









Technology is a human activity. It is an activity in which human beings form and

change natural reality for practical reasons with the help of means and methods. In his "A

Question Concerning Technology", Heidegger (1976) states that the manufacture and

utilization of equipment, tools, and machines, the manufactured and used things

themselves, and the needs and ends that they serve, all belong to what technology is.

Modem science and technology have been intentionally and methodically applied

to every side of human existence. Heidegger (1976) states that modern technology is

something incomparably different than all earlier technologies because it is based on

modern physics as an exact science. He concludes that modem science represents nature

as a calculable coherence of forces. Nature at any case seems to have the most crucial

significance when dealing with technology. McCleary (1983) in his "An Interpretation of

Technology" clearly defines the relations between technology, human, and nature. He

explains a person' s fundamental activity as one of productive interchange with nature.

This productive interchange that we may call "technology" is defined as the

communication between societies and their natural environments in the production of the

built environment.

According to McCleary (1983), construction of a new nature, which is interposed

between societies and original nature, is called "supernature". Supemature is definitely a

product of technology. A higher level of supernatural existence is super-supernature",

which is the concern of high technology. McCleary (1983) divides technology, which is

an interconnection between the original nature and human, into three levels:

* High technology
* Middle technology
* Low technology









McCleary (1983) explains the product of "super-supernature"' as the concern of

high technology. Low technology on the other hand is explained as a concern of those

who wish to return to that earlier relation that existed between societies and their natural

environments preferably in a technologically underdeveloped region. McCleary (1983)

claims that current practice of our professions is in the bondage of middle level

technology to the exclusion of both high and low technologies. Heidegger (1976) states

that more questioning of technology means that the mystery of it reveals itself. Yet

because of the more questioning of the technology's essence, the more mysterious the

essence of art becomes. Heidegger (1976) shows the contradictions of human nature by

stating that the feeling of danger helps human being become more questioning. Finally,

Heidegger (1976) wants to emphasize whether the kind of revealing of 'Being' that

shows itself in the fine arts can rescue man from danger of enframing, which he defines

as the essence of technology. So man has to rethink the meaning of modern science and

technology.

Humans and Buildings

The relation of humans with buildings is related to the essence of architecture and

building construction. It is essential at this point to remember the purpose of buildings.

Fitch and Bobenhausen (1999) define the ultimate task of architecture as activity in favor

of human beings. They state that the purpose of architecture is to maximize our capacities

by permitting us to focus our limited energies upon those tasks and activities that are the

essence of the human experience.

To be able to understand the relation between the buildings and the occupying

people we should also remember the essential needs of humans so that we will be able to

understand the expected fundamental requirements about the buildings and the third










environment they create. The relation of the human with the environment can be

reviewed at two different levels, which are perceptual and metabolic (Fitch &

Bobenhausen 1999). The conditions that determine the metabolic level of relation are

already given in the "Human and Their Environment" section. The perceptual level on

the other hand, comes into play only after the metabolic level requirements are met (Fitch

& Bobenhausen 1999).

IEQ deals with controlling and adjusting the third environment in a metabolic level.

According to Fitch and Bobenhausen (1999) there are four stages of optimizing metabolic

fit between building and its environment:

* Mechanical systems
* Enclosing membranes
* Building's exterior surfaces
* Site

Banham (1969) in his "Architecture of the Well-Tempered Environment" discusses

the environmental management in three different modes:

* Conservative mode
* Selective mode
* Regenerative mode

Thick walls of a house in a hot climate hold the radiation heat as a thermal mass

during the day, and then, after sunset, the radiation of the heat into the house helps to

control the sudden chill of evening. This whole technique can be termed as

"Conservative" mode of environmental management. The "Selective" mode, on the other

hand, employs structure not just to retain desirable environmental conditions but also to

admit desirable conditions from outside (Banham 1969). However traditional

construction has always had to mix these two modes, even without recognizing their










existence, just as it has always had to incorporate the "Regenerative" mode of applied

power without fully acknowledging its presence (Banham 1969).

The Eskimo igloo displayed in Figure 2-1 is a good example for the conservative

mode of environmental management. The shape and material used to build the igloo

signifies high-level environmental recognition and responsibility. The rounded shape

provides maximum resistance and minimum exposed surface to cold winds while

enclosing the most volume with the least material. With no mechanical systems and no

source of heat other than a small stove, interior air temperatures can be hold at a tolerable

range.



















Figure 2-1. Historical design for the Eskimo igloo, Baffin Island, Canada. (Wikipedia
2006a).

Another pre-industrial age example for the conservative mode of environmental

management is the mud masonry Indian House (Fig.2-2). The high heat capacity of mud

masonry, well suited to the great environmental fluctuations of the desert, is cleverly used

in primitive housing. Although the air may be dry, when it becomes very hot ventilation

may not be desirable. Native Americans build freestanding brush-covered arbors for









daytime shade, using houses for storage and cold weather sleeping while they used the

rooftops for summer sleeping (Fitch & Bobenhausen 1999).















Figure 2-2. Mud masonry Indian House (Fitch & Bobenhausen 1999).

The Larkin Administration Building by Frank Lloyd Wright is the first entirely air-

conditioned building on record (Banham 1969). It was built in 1904 and demolished in

1950 and was one of the early masterpieces of pioneer, modern architecture (Banham

1969). The Larkin Building is one of the good examples, which employ both selective

and regenerative modes of environmental management. The mechanical and architectural

aspect of the whole environmental concept is illustrated in Figure 2-3.











A BI.

Figure 2-3. Larkin Administration Building, Buffalo, NY, 1906 by F. L. Wright
A)Exterior photo, B)Isometric drawing (Banham 1969).

In the late 80s, while the application of computer technology into buildings was the

main theme of the building practice, Norman Foster Associates designed an innovative










building in Hong Kong that is dominated by several environmental management ideas. In

1986, Hong Kong and Shanghai Banking Corporation Headquarters was built in Hong

Kong by Norman Associates (Fig. 2-4). Flexible layout and systems such as raised floor

system provide space for the distribution of services and also help to cope with the issue

of flexible functional design. Computer technology is used in the building in order to

control the sun scoops that are used to track the sun location, together with mirrors

positioned outside and on top of the building atrium to diffuse sunlight to different floors

through the atrium and down to the plaza floor (Dobney 1997). The concept of energy

efficiency in the Hong Kong Bank resulted in the sunshades on the external facades to

avoid direct sun light into the building and to reduce the heat gain (Dobney 1997).









.. A BDCrI
Figure~~~~~ 2-4 HogKogad hnha anigHedurters HogKn.A)Etro


photo ,,. B)Forpa(ony19)





Frankfurt, Germany (Fig. 2-5). Commerbanki Headquarters, isn termed as te "worl'




first ecological tower" (Fischer & Grtineis 1997). Commerzbank Headquarters'

ventilation is provided by mechanical ventilation and air extraction that is used only on

days with extreme conditions, and the outer offices are naturally ventilated directly from









the outside. The offices on the atrium side receive air from outside indirectly through

ventilation flaps designed on the high glass walls of the garden facades. Just like the

Hong Kong Bank, Commerzbank also integrated complex computer technology that

controls the quantity of air pumped in, cut of supply to unoccupied spaces, sun shading,

the opening angle of windows, and the release or lock of controls and regulators. Cooling

on hot days is provided by a water-filled cooling system and the cold water needed for

cooling is produced by environmentally friendly refrigerating machines (Fischer &

Griineis 1997). High heat insulation quality on the facades and glazing also has a positive

influence on the energy efficiency of the building. Fluorescent tubes with daylight-

dependent regulation light the offices, and movement detectors automatically switch

continuous lighting in the corridors and offices (Fischer & Griineis 1997).
















A B

Figure 2-5. Commerzbank Headquarters, Frankfurt, Germany. A) Exterior photo, B)
Natural ventilation diagram (Fischer & Griineis 1997).

Similar to what Banham (1969) proposed earlier, Baker and Steemers (2000)

categorized the modes of environmental management in contemporary buildings. They

state that there are two modes of environmental management. The Selective mode









includes designs that work with a combination of form and fabric operating in a

calculated relationship with mechanical systems such as Hong Kong Bank or

Commerzbank Headquarters. On the other hand, exclusive mode of environmental

management separates the exterior and interior environments and employs mechanical

services as the main controllers of the interior environment.

The environmental management concepts, techniques and their influence on

building design, construction, and themes have always been changing since humans

created their third environment. Table 2-1 summarizes all these different approaches in

the context of maj or issues and the building concepts in the world of buildings since the

1960s.

Table 2-1.Histor cal progress of building, issues anc concepts.

Decade Issues Building concept

Sense of coolness, heating,.
1960s. Mechamical systems
ventilation, insulation, shading

1970s Energy crisis Energy-efficient buildings

Application of computer and
1980s .Intelligent and smart buildings
high technology in buildings

1990s Sick building syndrome Healthy, green buildings

Twenty-first Globalization towards
Sustainable buildings
century sustainable development


Indoor Air Quality (IAQ) in Commercial Buildings

Commercial buildings can include office buildings, retail establishments, light

manufacturing and assembly, restaurants, bars, etc. Commercial buildings, just like other

types of buildings use HVAC systems in order to provide a well-conditioned interior









environment for the occupants. Unlike residential buildings, these buildings have a higher

density of population and equipment. Consequently, managing a good IAQ in

commercial building may be more challenging than residential buildings.

The maj or IAQ problems in commercial buildings include airborne particles,

moisture, insufficient ventilation, and odors and gases from materials, etc. It is more

likely in commercial buildings that more moisture will be present due to the lack of fresh

air and the inconsistency in humidity and temperature control. Therefore commercial

buildings have higher risks associated with mold and bacteria problems. Many office

spaces have a number of toxic gas generating equipment such as computers, fax

machines, copiers, and printers. This can significantly impact the quality of air in

commercial buildings and the employees would be exposed to a variety and high

concentration of contaminants for at least 8 hours per day in these buildings. Levels of

carbon dioxide inside commercial buildings may also be higher due to lack of fresh

outdoor air ventilation. This can possibly cause headaches and other health related

problems among the workers. These effects and their details will be discussed in the IAQ

and Health section of this study.

Air quality in a space is determined by the quantity of air intake and also by other

factors such as air conditioning, room function, etc. Intake air in general is provided by

outdoor air (OA) and in some cases by re-circulating the existing air. However, re-

circulated air should be controlled in a manner, which would minimize energy use but

also protect occupant health thus maintain acceptable levels for worker performance and

productivity. The IAQ systems should be designed by fresh OA intake strategies

whenever it is possible. The reason fresh air intake should be used is that in many cases









increasing OA should ensure a sufficient amount of dilution to reduce the concentration

of pollutants. Natural ventilation is one of the possible ways to bring more OA into the

building as long as the energy consumption of the building is still kept at an acceptable

range.

The amount of indoor air pollutants is correlated with different conditions that

create the building such as the site, building materials, construction techniques, building

type and use, occupant density, HVAC system, and etc. The following four elements are

involved in the development of IAQ problems (USEPA 2005b):

* Source: source of contamination or discomfort indoors, outdoors, or within the
mechanical systems of the building.

* HVAC: the HVAC system that is not able to control existing air contaminants, not
able to control conditions that help build up contaminants.

* Pathways: one or more pollutant pathways that connect the source of contamination
to the occupants of the building and a driving force to move pollutants along the
pathway(s).

* Occupants: building occupants who are present in the building.

It is important to understand the role that each of the above factors may play in

order to identify, prevent, and resolve IAQ problems.

Standards, Regulations and Guidelines

Currently, the Federal government in the USA does not regulate IAQ in

nonindustrial settings. However, many state and local governments regulate ventilation

system capacity through their building codes. Building codes have been developed in

different states in order to promote healthy and safe construction practices. There also

professional associations, international health associations, industry organizations, state

governments, and private programs that develop recommendations or guidelines for

appropriate building and equipment design and installation. These recommendations may










play a mandatory role when state or local regulations integrate them in to their code and

regulation policies (USEPA 2005c). There is generally a time delay between the change

in new standards by professional organizations such as ASHRAE and the integration of

those new standards as code requirements (USEPA 2005c).

Below are some of the maj or tools, standards, and regulations towards regulating

IAQ in commercial buildings.

Occupational Safety and Health Administration (OSHA). The agency proposed

guidelines in 1994 towards regulating IAQ in non-industrial buildings. However on

December 17, 2001 OSHA withdrew its IAQ proposal and terminated the rulemaking

proceedings (OSHA 1994). The proposed IAQ regulations would have help (OSHA

1994):

* Ban smoking in the workplace or required employers to provide separately
ventilated smoking areas.

* Develop IAQ compliance plans in non-industrial work sites to protect workers from
certain indoor air contaminants, inadequate ventilation, and sick building
syndrome.

* Have periodic inspections and air testing.

* Maintain written records including documentation of reported IAQ problems.

* Control for specific contaminants such as restricting the use of chemicals and
pesticides.

* Have a good maintenance program.

* Conduct employee-training programs about IAQ.

OSHA stated that integrating these regulations would have required an initial cost

of $1.4 billion along with an annual cost of $8. 1 billion to employers. These costs would

have occurred due to increased and proper maintenance of building IAQ systems as well

as the increased operating costs. OSHA also estimated an annual $15 billion savings for









employers due to increased employee productivity and reduced absenteeism (OSHA

1994). Although these proposed regulations cannot yet be enforced, they at least provide

guidelines for those companies, which are willing to start a high-quality IAQ

management program.

The General Duty Clause of the Occupational Safety and Health Act requires

employers to provide a safe and healthy working environment regardless of the proposed

IAQ guidelines being in effect. It is also important to know that all workers are covered

under federal OSHA. These regulations are enforced also at the state level in the 23 states

including Florida.

American Society of Heating, Refrigerating, and Air-Conditioning Engineers

(ASHRAE). ASHRAE has noncompulsory ventilation standards for commercial and

industrial buildings. However ASHRAE standards become mandatory when local

governments adopt the standards into their local building codes. ASHRAE first published

its Ventilation for Acceptable Indoor Air Quality 62. 1 in 1973. ASHRAE Standard 62. 1-

1989 defined acceptable IAQ as the air in which there are no known contaminants at

harmful concentrations as determined by authorities and with which a substantial

maj ority of the people exposed do not express dissatisfaction (ASHRAE 1989). However,

this statement could not guarantee that no unpleasant health effects would occur.

ASHRAE Standard 62. 1-2001 aimed to minimize the probability of adverse heath effects

among building occupants. It became applicable to all occupied spaces except where

other standards exist. ASHRAE Standard 62. 1-2001, depending on the building function,

recommended that 15 to 20 cubic feet per minute (cfm) of outdoor air should be supplied

for each building occupant (ASHRAE 2001). Recently the 2001 standard has been









replaced by ASHRAE 62. 1-2004, which specifies outdoor air requirement for an office as

5 ofm per person plus 0.06 ofm/ft2 (ASHRAE 2004). In this latest version of ASHRAE

Standard 62.1, requirements for the office may still remain the same in cases where the

occupant density varies, or is indefinite at the time of the system design. However this

recent ASHRAE revision as the first maj or revision to the ventilation rates since 1989

appears to result in slightly lower outdoor air requirements for the office spaces (17

ofm/person). The reason for this reduction in ventilation rates should be further

researched to explore whether the motive towards this change derived from the effort

towards reducing equipment capacities as well as the energy usage over the life of each

mechanical system.

New construction design and building operation plans should ensure that at least

the minimum OA amounts recommended by ASHRAE Standard 62.1 are being followed

to minimize IAQ concerns and associated discomfort and illness. Authorities may also

consider writing these specifications into the construction and building operation codes.

Environmental Protection Agency (EPA). The EPA does not have any

constitutional role in the enforcement of IAQ, other than issues regarding asbestos and

radon. However, there has been a legislation proposal presented in Congress that requires

the EPA to create a voluntary program to certify indoor air contractors, but this

legislation has never passed (Conlin & Carey 2000)

The EPA has established a set of specifications for use in its own facilities to

regulate the emissions from office furniture, equipment and other products. The

specifications include regulations such as workstations cannot add more than 0.5 mg/m3









of total volatile organic compounds (VOC), 0.05 ppm of formaldehyde, and 0. 1 ppm total

aldehydes within one week of receiving and unpacking the furniture.

Other guidelines. The American Conference of Governmental Industrial

Hygienists (ACGIH) has created a manual called "Guidelines for the Assessment of

Bioaerosols in the Indoor Environment". The manual provides the most important basic

data on IAQ however it does not go into much detail. ACGIH also presents exposure

limits for chemicals in the workplace, in a document called "Threshold Limit Values".

This document is widely used in assessing whether excessive chemical exposure has

occurred (ACGIH 1989). National Institute for Occupational Safety and Health (NIOSH)

and National Ambient Air Quality Standards (NAAQS) also published standards to

regulate specific IAQ levels.

The Air-Conditioning and Refrigeration Institute (ARI), which is an industry trade

group for air-conditioning system manufacturers, has created guidelines for design,

installation, and maintenance of A/C systems. These guidelines provide some of the basic

information one should know on these issues.

Building codes. Building codes vary from place to place. These codes generally

regulate IAQ by specifying the amount of OA that is to be supplied by the ventilation

system for commercial buildings. Additionally, these codes are often very specific on

construction means and methods, which may affect IAQ of a building such as carbon

monoxide problems, moisture entry into the building, and re-entry of exhaust fumes. As a

general rule, building codes are only enforceable during the construction and renovation

processes. Code requirements may change over time as code organizations adapt to new

technologies and information. However the buildings are usually not obligated to make









modifications in their structure or the way they operate in order to conform to the new

codes. It also a well known fact that many buildings do not operate in standards parallel

with current building codes, or even with the codes they had to meet at the time of their

construction (USEPA 2005c).

State laws and regulations. In the absence of any action at the national level,

several states took steps on their own to improve IAQ in buildings. At least 37 out of 53

states and territories have designated an IAQ contact person due to the increase in the

number of complaints about SBS, also called building-related symptoms (Slap 1995). 45

states have laws prohibiting smoking in public buildings. Also 19 states limit or restrict

smoking in private workplaces acknowledging that tobacco smoke is a maj or indoor air

pollutant (OSHA 1994). The Florida Building Code (FBC) regulates IAQ in commercial

buildings in Florida. FBC is based on the 2003 editions of the International Building

Code (IBC), International Mechanical Code (IMC), and International Plumbing Code

(IPC). FBC mandates that:

* Ventilation units shall distribute tempered heated or cooled air to all spaces and
shall supply outside air in the quantity of either the sum of all exhausts or 20 ofm
per person whichever is greater.

* The quantity of all exhaust air must match the intake volume of all outside air.
Supply, exhaust, and return fans shall run continuously while the building is
occupied.

* Areas in which smoking is permitted shall be well vented by at least 35 ofm per
person to the outside in order to minimize smoke diffusion throughout the unit.

The International Mechanical Code that is the base of ventilation regulations in

FBC has the following statements regarding ventilation in section 403.3:

* No less than 15 ofm of outside air per occupant is required for waiting room areas,
based on the estimated maximum occupant load of 60 per 1,000 square feet.










* No less than 20 ofm of outside air per occupant is required for office areas, based
on the estimated maximum occupant load of 7 per 1000 square feet.

Although ASHRAE 62. 1-2004 has changed the requirements for minimum

ventilation rates in office spaces, the rates in IMC and FBC still remain to be parallel to

ASHRAE 62. 1-2001. However IMC is giving strong consideration for a change in the

code towards synchronization with the new ASHRAE 62. 1-2004 standards.

Sources of Indoor Air Pollutants

Indoor air contaminants can start building up within the building itself. Although

this study assumes that OA is not a source of contamination, pollutants can be brought

from outdoors as well. If the pollution sources are not controlled, IAQ problems can

begin, even if the HVAC system is accurately configured and well maintained. The

USEPA categorizes the sources of indoor air pollutants as given below. The examples

given for each category are not intended to be a complete list (USEPA 1991).

* Sources Outside Building
0 Contaminated outdoor air
Pollen, dust, fungal spores
Industrial pollutants
*General vehicle exhaust
o Emissions from nearby sources
Exhaust from vehicles
Loading docks
Odors from dumpsters
Re-entrained (drawn back into the building)
o Soil gas
Radon
Leakage from underground fuel tanks
Pesticides
* Equipment
o HVAC system
Dust or dirt in ductwork or other components
Microbiological growth in drip pans,
Humidifiers, ductwork, coils
Improper use of biocides, sealants, and/or cleaning compounds
Improper venting of combustion
Refrigerant leakage










o Non-HVAC equipment
Emissions from office equipment (VOCs, ozone)
Supplies (solvents, toners, ammonia)
Emissions from shops, labs, cleaning processes
*Elevator motors and other mechanical systems
* Human Activities
o Personal activities
Smoking
Cooking
Body odor
*Cosmetic odors
o Housekeeping activities
*Cleaning materials and procedures
Emissions from stored supplies or trash
Use of deodorizers and fragrances
Airborne dust or dirt (e.g., circulated by sweeping and vacuuming)
o Maintenance activities
Microorganisms in mist from improperly maintained cooling
towers
Airborne dust or dirt
Pesticides from pest control activities
Emissions from stored supplies
* Building Components and Furnishings
o Locations that produce or collect dust or fibers
Textured surfaces such as carpeting, curtains, and other textiles
Open shelving
Old or deteriorated furnishings
*Materials containing damaged asbestos
o Unsanitary conditions and water damage
Microbiological growth on soiled or water-damaged furnishings
Microbiological growth in areas of surface condensation
Standing water from clogged or poorly designed drains
*Dry traps that allow the passage of sewer gas
o Chemicals released from building components or furnishings
Volatile organic compounds or inorganic compounds
* Other Sources
o Accidental events
Spills of water or other liquids
Microbiological growth due to flooding or to leaks
*Fire damage (soot, PCBs from electrical equipment, odors)
o Special use areas and mixed use buildings
Laboratories
Print shops, art rooms
Exercise rooms
Beauty salons
Food preparation areas









o Redecorating/remodeling/repair activities
Emissions from new furnishings
Dust and fibers from demolition
Odors and volatile organic and inorganic compounds.

Depending on building location and characteristics, several different types of

contaminants can pollute the indoor air from the processing of organic and inorganic

elements. Daniels (1998) categorizes these pollutants as:

*Gases and vapors (CO, CO2, SO2, OS, radon, formaldehyde, carbon-hydrogen)
*Odors
*Aerosols (inorganic or organic particulates such as heavy metals and pollen)
*Viruses
*Bacteria and bacterial spores
*Fungi and fungal spores

ASHRAE 62. 1-2004 provides a table that compares the acceptable levels of indoor

air contaminants by different agencies (Table 2-2).

Table 2-2. Comparison of regulations and guidelines for acceptable contaminant levels
Enforceable & regulatory levels Non-enforced guidelines
NAAQ S/EPA OSHA NIO SH ACGIH
5,000 ppm 5,000 ppm
Carbon dioxide 5,000 ppm
30,000 ppm [15m] 130,000 ppm [15m]
Carbon 9 ppm 35 ppm
50 ppm 25 ppm
monoxide 35 ppm [1 h] 200 pm [Ceiling]
0.75 ppm 0.016 ppm
Formaldehyde 0.3 ppm [Ceiling]
2 pm [15 m] 0.1 pm [15 min]
Lead 1.5 pLg/m3 0.05 mg/m3 0.1 mg/m3 [10 h] 0.05 mg/m3
[3 months]
Nitrogen 3 ppm
0.05 ppm [1 yr] 5 ppm [Ceiling] 1 ppm [15 m]
dioxide 5 ppm [15 m]
0.12 ppm [1 h]
Ozone 0.01 ppm 0.1 ppm [ceiling] 0.02 ppm
0.08 pm
Particles 15 Cpg/m3 lr
5 mg/m3 3 mg/m3
<2.5Cpm MMAD 65 Cpg/m3 [24 h]
Particles <10Cpm 50 Cpg/m3 10 /m3
MMAD 150 yg/m3 [24 h] 1 mg/m
Sufu d .xd 0.03 ppm [1 h] pp 2 ppm 2 ppm
0.14 ppm [24 h] 5 ppm [15 m] 5 ppm [15 m]
Total particles 15 mg/m3
(ASHRAE 2004).










Many of the indoor pollutants can be avoided by increased OA ventilation as long

as the outdoor air is not polluted. However the building materials inside the building can

be the source of contamination as well. Daniels (1998) lists the sources of the worst

contaminants as follows:

* Insulating paints
* Adhesives of all kinds
* Floor coverings
* Suspended ceilings
* Jointing compounds
* Insulating materials
* Pre-fabricated materials
* Wood preservatives
* Raised floors

IAQ Control Techniques

Efforts towards improving IAQ may include different strategies depending on the

nature of the problem. Henschel (1999) approaches the control techniques in three

categories for reducing the concentrations of indoor air pollutants:

* Improved ventilation: Increases in the quantity of outdoor air (OA) supplied to a
building, and/or improvement in the distribution and mixing of the supply air
throughout the various zones in the building.

* Air cleaning: Devices mounted in the central HVAC ducting, or self-contained
devices mounted in the occupied zones, to remove contaminants from the air.

* Source management: Removal of all or part of the source, replacement of the
source by a lower-emitting alternative, treatment of the source to reduce emissions,
relocation of the source or relocation of the occupants.

In some situations it may be difficult for the decision-makers to choose which

one(s) of these options to use. When there is a localized source of contaminant Henschel

(1999) suggests using a logic diagram presented in Figure 2-6 that may help select a

specific IAQ control option. Henschel (1999) helps users by asking yes or no questions

regarding the source of contamination and directs the users towards one of the options.




















START


Y

Is


building?


This s~ndy
assumes outside air
Is niot the source


As Cleanmu



Source Massnaemen


there an
impyortan source
inside the bulilding
that can be:
removed

NO



th~at area
receiving supply
air flow condsisnt
wvith HVAC
desigl"


YES Considbersource
malscnaemen


HVAC: lmoe yggS
Appear possible 10
supply suflicient
additional air to



INO


Is YES
localized
exhaus1 an
option


Des
di~ffser/relum
YEEC intak~e onfiguration
provide adequate
air mixing in that
area"


There must be an
\-S imporlant sorurcet
in that aren that
cannot be rem~oved


estimate. COStS





cleampg





Inads. csnm ite
cosl


Will

inre-dcsiir YES
heclp address she
problem


NO Madify HVAC aperation
to provided design supply
flowr. Consider further >
HVAC modls if further
reduction needed


Figure 2-6. Logic diagram for selecting an IAQ control approach (Localized problem resulting from sources inside the building)

(Adapted from Henschel 1999).


> mpoed Vetlin









According to a 1987 NIOSH survey, 52 out of 100 buildings with IAQ problems

suffered from mainly inadequate ventilation (Seitz 1989). According to the same study,

16% of the buildings suffered from indoor contaminants where 10% suffered from

outdoor contaminants (Seitz 1989). These numbers clearly indicate that many IAQ

problems derive from within the building and its indoor air management systems.

Manufacturers have been working on generating more advanced products for a better

ventilation technology. One example is a ventilator manufactured by Honeywell called

Perfect Window 9. This ventilator is a heat recovery ventilator, which is structured as a

pair of insulated ducts run to an outside wall. This ventilator recovers the moisture and

heat from the outgoing air in winter times, and removes it from in-coming air in the

summer Another important issue in controlling the IAQ in a commercial building is to

be able to monitor IAQ constantly (Bas 1993). For this reason, manufacturers like

Honeywell and some other companies have introduced more efficient and easy to use

handheld CO2 monitoring devices. Monitoring CO2 lCVOIS is vital since studies show that

at levels beyond 1,000 ppm occupants can experience health problems and general

discomfort, making it more difficult for them to think and work (Bas 1993). The health

effects of IAQ problems are discussed in more detail in the "IAQ and Health" section.

Ventilation: All buildings require a certain amount of OA. The outdoor air may

need to be conditioned (heated or cooled) before it is distributed into the occupied space

depending on the specific climate. Bringing OA into the building allows the indoor air to

be exhausted or to escape by passive relief, which aids to remove indoor air

contaminants. The types HVAC systems range from independent units that serve


SMore information available online at http://www.honeywell.com/sites/acs/.









individual spaces to large central systems serving multiple zones in a building (USEPA

1991). The components of a typical HVAC system are given in Figure 2-7, which

illustrates the general relationship between many components of an HVAC system.

However it is important to note that many variations can be possible.


Figure 2-7. Typical HVAC system components (USEPA 1991).

The EPA categorizes different HVAC systems as follows (USEPA 1991):

* Single zone systems
* Multiple zone systems

According to the EPA, a single air-handling unit can serve more than one building

area if the areas served have similar HVAC requirements. This would also be possible if

the control system can compensate for differences in HVAC needs among the served

spaces. Areas regulated by a common control are referred to as zones (USEPA 1991).









Multiple zone systems can provide each zone with air at different temperatures by

heating or cooling the air stream in each zone. Alternative design strategies involve

delivering air at a constant temperature while varying the volume of airflow, or

modulating room temperature with a supplementary system (USEPA 1991). Constant

volume systems, on the other hand, generally deliver constant amounts of air to each

space. These systems often operate with a fixed minimum percentage of OA or with an

"air economizer" feature (USEPA 1991).

Rather than by changing the air temperature variable air volume (VAV) systems

maintain thermal comfort by changing the amount of heated or cooled air delivered to

each space. However, many VAV systems also have requirements depending on the

characteristics of the weather, such as resetting the temperature of the delivery air on a

seasonal basis. Underventilation often happens if the system is not arranged to introduce

at least a minimum quantity of OA as the VAV system throttles back from full airflow, or

if the supply air temperature is set too low for the loads in the zone (USEPA 1991).

Overcooling or overheating can also occur in a zone if the system is not adjusted to

according to the cooling or heating load (USEPA 1991).

Most commercial buildings use VAV systems for ventilation (Public Interest

Energy Program [PIER] 2005). However the main reasons VAV systems are used in

commercial buildings derive from the financial constraints. In 1970s before the energy

crisis, a different system was used in order to bring constant air volume into the building

spaces however the air was at variable temperatures. This system brought substantial

quantities of OA to the building. However while energy efficiency has become a more

important concept, this system became less popular due to its expensive operating










(energy) costs. The VAV system on the other hand brings in only the amount of air that is

necessary and re-circulates a building' s already conditioned air at various quantities.

Although a VAV system saves energy, re-circulating air thus increasing the amount of air

contaminants is the price that it pays for those savings. This is one of the good examples

of the contradiction between IAQ and energy efficiency. The true costs of IAQ issues are

discussed in more detail in the "IAQ and True Costs" section.

Air cleaning: Air cleaning is one of the IAQ control techniques. The air filter is a

product that has been around for many years and still is one of the most crucial parts of a

building's IAQ management system. There are currently many different types of air

filters in the market that provide different protections and methods for different types of

contaminants. Many buildings use poor performance of 89% fi1ters, which are used to

protect the HVAC system but not the occupants of the buildings. According to ASHRAE

(1999), the performance of these fi1ters on filtering dust and similar contaminants is only

7 to 12% effective. Burgess et al. (2004) categorize the fi1ters into three categories:

* Fibrous and Granular (Media) Filters: Remove large particles before a second stage
collector of greater efficiency and fi1ters the dusts that cannot be easily collected by
other collectors.

* High Efficiency Particle Air (HEPA) Filters: These filters are used extremely high
particle collection is required such as in hospital operating rooms. This type of
cleaners are not cleanable and have low dust capacity which limits their use to gas
streams with low dust loading.

* Fabric Filters: These are the most common type of filters in the industrial
environments. They must be eventually cleaned.

Another method for cleaning air is electrostatic precipitators. This type of cleaner

collects particles by electromagnetic action. These cleaners have the advantage of less

maintenance but can pose a different threat due to ozone production (Stein & Reynolds

1992).









The most challenging part of the air-cleaning problem is the selection of the type of

filter or the cleaning device to be used. Different contaminants may require different

types of air-cleaning devices. Thus the selection of the device demands the knowledge of

the type of contaminants to be removed. Burgess et al. (2004) summarizes the basic

information about the collection device in Table 2-3.

Table 2-3. Collection device characteristics.
Collection Types of Initial Operating
Device Typ Contaminants Cost Cost Drblt
Filters
Industrial All dry powder Moderate Moderate Good
HEPA Pre-cleaned air Moderate High Fair to Poor
Electrostatic
Precipitators
Single Stage Flyash, H2SO4 High Low Fair
Two Stage Welding Fume Moderate Low Good
Wet Scrubbers
Venturi Scrubber Chemical Fumes Low High Good
Wetted Cyclone Crushing, grinding Moderate Moderate Good
(Burgess et al. 2004).

Contaminant source management: One of the control techniques when dealing

with air contaminants is to manage the contaminant source. This may involve several

approaches (USEPA 1993):

* Source removal: This strategy involves identifying a source of contamination and
relocating it therefore it will not affect the IAQ. Examples include not keeping
garbage in spaces with HVAC equipment, and replacing moldy materials.

* Source substitution: This strategy involves identifying a material likely to impact
the IAQ of the building and selecting a similar but less toxic substitute. For
example choosing latex paint instead of oil based paint.

* Source encapsulation: Encapsulation involves creating a barrier around the source
and isolating it from other areas of the building so that there is no recirculation of
air from the contaminated area into occupied spaces. This may include isolating a
division of the building with polyethylene sheeting as well as isolating the space
from the general ventilation system by blocking return air grilles.









IAQ and Health

Following the energy efficiency trend in 1970s, many concerns about the

occupants' health in buildings started to arise due to low indoor air quality of commercial

buildings in 1980s. Government agencies, university groups, and private consulting firms

started to receive an increasing number of requests to investigate health complaints

specifically in office spaces. This led to a whole new syndrome, which is called Sick

Building Syndrome (SBS). SBS is defined as a group of symptoms that are two- to three-

fold more common in those who work in large, energy-efficient buildings, associated

with an increased frequency of headaches, lethargy, and dry skin. Clinical manifestations

include hypersensitivity pneumonitis (alveolitis, extrinsic allergic), allergic rhinitis

rhinitiss, allergic, perennial), asthma, infections, skin eruptions, and mucous membrane

irritation syndromes (Segen 1992). A 1984 World Health Organization Committee report

suggested that up to 30 percent of new and remodeled buildings worldwide may be the

subj ect of excessive complaints related to poor indoor air quality (IAQ) (American Lung

Association [ALA] 2000). Although the most common site of injury by airborne

pollutants is the lung, acute effects may also include non-respiratory signs and symptoms,

which may depend on the toxicological characteristics of the contaminant substances

(ALA et al. 1994).

Although many studies prove that indoor air contaminants can have various health

affects on the occupants, there is still an on-going argument on the validity of several

studies such as the health affects of mold. Along with many studies indicating a

relationship between the several symptoms of occupants and allergic pollutants such as

mold, there are also some studies claiming that this has not been scientifically proven.

However it is already acknowledged by the scientific community that there are many










other indoor air pollutants that can cause low to severe health problems. According to

Gamble et al. (1986), buildings where allergies are suspected present a difficult

diagnostic challenge. Gamble et al (1986) believe that only a few people may be affected,

and an allergic diagnosis may be overlooked when building occupants have complaints

about insufficient outdoor air supply, thermal discomfort, or cigarette smoke. Allergic

symptoms can be relatively mild and nonspecific, and may have disappeared by the time

a worker visits a physician' s office. Some of the findings of Gamble et al. (1986) in a

study where they evaluated a 9-story office building and compared the results to the

outside air provided per person are given in Table 2-4. According to Table 2-4, the SBS

symptoms as well as the thermal discomfort reaches to the highest rates, on the 2nd and

3rd flOOrs where no outside air (OA) was provided for 175 workers.

Table 2-4. Complaints on floors with outside air provided per person.
n=Number of Floors 8-9 Floors B-1 Floors 6-7 Floors 4-5 Floors 2-3
occupants n=56 N=42 n=155 n=131 n=175
Chronic
Bronchiti s 12% 5% 6% 6% 7%
Symtoms
3 or more SBS
26% 26% 15% 20% 36%
smtoms

Sinus Symptoms 40% 36% 25% 31% 46%

Thermal
76% 84% 73% 67% 89%
Di comfort

OA (cfm/person) 126 72 28 14 0
(Gamble et al. 1986)

IAQ and True Costs

Indoor air quality has financial consequences as well as its health affects. The cost

of an IAQ management option is associated with two different types of costs. These costs

can be categorized as hard and soft costs.










"Hard costs" in the building industry is a term for the amount that includes total

land and construction costs (Environmental Law Institute [ELI] 2005). In addition hard

costs associated with indoor air quality would be the life cycle costs (LCC) of managing

the indoor air quality in a building. LCC of a specific system should include the owning

and the operating costs. Owning costs of a system include (Rizzi 1980):

* Initial cost of the system
* Capital recovery
* Interest and return on the investment
* Property taxes
* Insurance

Operating costs of a system include the following costs:

* Fuel and energy
* Maintenance allowances
* Labor for operation
* Water costs
* Water treatment cost

Rizzi (1980) explains how LCC analysis should be conducted for any heating,

cooling, and/or ventilating systems. Rizzi (1980) states that when studying owning and

operating costs of a system, the period covering the lifetime of the system should be 20

years. Rizzi (1980) also provides a methodology to calculate the owning and operating

costs of an HVAC system.

Soft costs in the building industry are known as architectural, engineering, and

legal fees as differentiated from land or construction costs. However soft costs in general

represent any costs that are not related to the actual land and construction costs.

Consequently soft costs of a specific IAQ management option include costs associated

with productivity, health, insurance fees, litigation, etc. Unfortunately many investors or









building owners usually do not see maj or incentives in considering the soft costs

associated with poor or good IAQ.

One of the most important soft costs of IAQ is productivity. Productivity and its

financial consequences become a more important issue in commercial buildings. Worker

salaries constitute the maj or cost of operating a commercial building, generally estimated

at over 90% of the total operating cost, so that even a small increase in employee

productivity can substantially increase a company's financial return (AIASF 2001).

According to the study conducted by the US Department of Energy (USDOE) and

Lawrence Berkeley National Labs in 1997, the costs of lower productivity for the US

economy ranged from $12 to $125 billion per year (Damiano 2005).

Another survey conducted by Reel Grobman & Associates (2005) among interior

design and facility planning decision-makers indicates that the respondents feel that

overcrowding, followed by IEQ complaints have the greatest negative impact on

employee productivity (Damiano 2001). According to the report, 40% of the respondents

said that overcrowding had the greatest negative effect, while 31% cited noise. Poor

indoor air quality (19%) and poor lighting (10%) were among other factors cited by those

surveyed. 74% of the respondents said they felt that workplace environmental conditions

were critical to employee productivity, while the rest said those conditions had some

impact (Reel Grobman & Associates 2005).

Very often, building owners or managers propose cost-saving measures without

considering the added costs due to lowered performance and productivity. An example of

this occurred when the Building Owners and Managers Association (BOMA) presented

to members about its success in beating back two provisions in ASHRAE Standard 62.1.









The article was published in BOMA's member newsletter "SkyLines" (Bas 1993). The

two provisions that were discussed by BOMA would have required renovation areas to be

secluded from the rest of the building by using negative pressure and mandated a 48-hour

period for purging contaminants from those areas following construction (Bas 1993).

BOMA stated that these requirements were hard to implement and also would have cost

building owners about $0.10 per ft2 for the first provision and $0.01 per ft2 for the second.

According to the BOMA analysis, rej ecting those provisions would save a building

owner approximately $11,000 for a 100,000-ft2 buildings. However, BOMA's analysis

did not take the loss of productivity (soft cost) into consideration. This soft cost would

increase if pollutants from construction activities were drawn into the occupied space of

the building. This has been a factor in numerous IEQ cases and was the principal cause of

the problems 10 years ago at the headquarters of the EPA (Bas 1993). This type of

situation may also result in people being injured and thus may result in multiple lawsuits.

But according to Bas (1993) just a small positive effect on productivity in a typical

100,000 ft2 COmmercial building could save more than significant amounts of money. If

we consider a building with an occupant density of 5 persons per 1,000 ft2 this would

result in a total of 500 people in the building. If an average annual salary of $30,000 were

assumed for each person in that building, this would be a total biweekly salary of

$576,923. If construction activities cause IEQ degradation thus the productivity decreases

by 0.5%, this would be result in a loss of $2,884 every two weeks that the situation

existed.


2 More information can be found online at httpl u\ \\ l\boma.org/.










Wargocki et al. (2000) conducted a study in order to evaluate the correlation

between IAQ and productivity in an office space. In order to define the performance

index Wargocki et al. (2000) defined four maj or tasks for the subj ects of the study. The

subj ects throughout different exposures of IAQ, were asked to perform simulated office

work consisting of four different tasks: text typing, addition, proofreading and creative

thinking.

Wargocki et al. (2000) calculated and normalized the average number of characters

typed per minute, average number of correctly completed arithmetical calculations (units)

per hour, and average number of lines that were correctly proof-read per minute.

Performance was measured in three independent studies with different subj ects and could

have been influenced by group differences in the subj ects' experience, intellectual skills,

and level of practice. The normalization factors were the ratios between the mean of

performance at all air quality levels in all three studies to the means of performance at all

air quality levels in each individual study.

To estimate the overall performance of simulated office work, the Wargocki (2000)

calculated a performance index by dividing normalized performance at a specific level of

air quality by the mean of normalized performance of a specific task at all air quality

levels.

The findings of Wargocki's study clearly display the importance oflIAQ in office

buildings. Figure 2-8 shows an overall summary of the results of the study and displays

how productivity index increases when the ventilation rate increases and the pollution

load decreases.















o 1.061.7 us/mmoowr
~ l~osC~e~, /12' 0 'ir stmWoor
[ ~ c~\ic~c;'~,",P~~,~/lllr2.3 L/ls~rmoor
.. 1.02


0.98


0.94 *
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1
Sensory pollution load (olf/m2Roor)
Figure 2-8.Overall performance of simulated office work as a function of sensory
pollution load and ventilation rate (outdoor air) (Wargocki 2000).

One of the other soft costs associated with IAQ is the economic loss created by

health problems. In OSHA's effort to establish ventilation rules for nonindustrial workers,

they used the following justifications, in part3

The Agency estimates that the excess risk of developing the type of non-migraine
headache, which may need medical attention or restrict activity, which has been
associated with poor indoor air quality, is 57 per 1,000 exposed employees. In
addition the excess risk of developing upper respiratory symptoms, which are
severe enough to require medical attention or restrict activity, is estimated to be 85
per 1,000 exposed employees. These numbers are extrapolated from actual field
studies and therefore show the magnitude of the problem at present (OSHA 1994,
p. 63).

This amounts to an estimated average excess risk of lost work-time or diminished

productivity for approximately 6% of workforce, on any given day, in any facility that

exhibits poor indoor air quality (Damiano 2001). Additionally, approximately 9% are

estimated to be at excess risk and would probably incur lost time due to upper respiratory

sickness (Damiano 2001). In the same Lawrence Berkley/USDOE study mentioned


3 On December 17, 2001 OSHA withdrew its indoor air quality proposal and terminated the rulemaking
proceedings, see Federal Register 66:64946.









earlier, it is estimated that the direct cost to the U.S. economy due to increased allergies,

asthma and SBS symptoms were $7 to $23 billion per year (Damiano 2005). Damiano

(2001) claims that a large portion of these costs are estimated to be in the form of

workmen's compensation claims, health care insurance premiums and direct health care

costs mostly borne by the claimants' employers.

Milton et al. (2000) conducted one of the studies that focus on how employers need

to strike a balance between the energy costs of providing higher ventilation rates and the

health benefits from higher ventilation rates. The researchers of this study analyzed the

sick leave records of 3720 hourly workers for the calendar year of 1994. They used a

statistical technique called Poisson regression to analyze the relationship of sick leave

with ventilation rate category. The results generated by this study, when the ventilation

rate is increased by 25-cfm per person, are given in Table 2-5. The results indicate that by

increasing the ventilation rate by 25-cfm up to 50-cfm/person employers can save up to

$400 per employee assuming $40 hourly compensation rate.

Table 2-5. Potential economic costs and benefits of increasing ventilation rate by 25 ofm
per Person.
Criteria Annual savings per employee
Energy Costs$8
25 ofm/ workers x $3.22/cfm/year
Sick Leave Costs
Sick Leave avoided (1.50 days per -$480
workers)
Total Savings -$400
(Kumar & Fisk 2002)

IAQ related litigation cases are increasing along with the awareness of the effects

of poor IAQ in buildings. One of the buildings that exhibited the classic symptoms of

SBS was the DuPage County Courthouse in Wheaton, IL (Bas 1993). Bas (1993) reports

that one day in 1992, 25 employees were rushed to the hospital, suffering from shortness









of breath, headaches, and nausea. The four-story, $50 million building was closed

temporarily, affecting some 700 employees. The main problem with the courthouse as it

is with many other buildings with SBS, was inadequate ventilation. The county in this

case sought $3 million in damages for the design, engineering, and construction of the

building (Bas 1993). Another sick building was the Polk County Courthouse in Central

Florida. The building was opened in the summer of 1987 at a cost of $37 million. Due to

IAQ problems, the building was shut down, and the remediation of the building realized

at a cost of $26 million (Bas 1993).

Public attention and the litigation cases about IAQ issues have been continuously

increasing. The maj or reason for this increase is due to the growing belief among

employees that the employers owe them a safe and healthy working environment. Many

of the employees believe there is a higher possibility of winning this type of litigation

cases when there is a third responsible party involved. This may include anybody that is

involved in the design, construction or operation of the building. This list may include

HVAC engineers, contractors, subcontractors, property managers, building owners, and

designers as the maj or targets in IAQ related liability cases.

Optimization of IAQ

The continuous demand for sustainable and higher performance buildings has

resulted in the development of more sophisticated and efficient technologies. The main

goal of this development is to create "better" buildings that would satisfy many different

performance criteria. Papamichael (1998) describes the decision-making process in

relation to performance prediction and evaluation for design options in high performance

buildings in Figure 2-9. According to Figure 2-9 building design is the iterative

generation of alternative courses of actions in the form of technological combinations and











the prediction and evaluation of their performance. According to Papamichael (1998),

building performance is considered and communicated through the use of performance

indices, or parameters, based on the values of which designers judge appropriateness.

Some of these might include measures such as aesthetics, economics, and comfort.


Design Options


Performance Prediction Comfort
Aesthetiss
Economics
Energy
Performance Evlaluation



Decision Making

Figure 2-9. Building design decisions require performance prediction and evaluation with
respect to multiple performance considerations (Papamichael 1998).

Atthaj ariyakul and Leephakpreeda (2004) conducted a study that presents another


example of parameter generation to measure Indoor Environmental Quality. They use

well-known parameter indices to quantify the degree of thermal comfort and air quality

for human and energy usage in an HVAC system. These parameter indices are directly or

indirectly defined in terms of time-dependent variables of the indoor-air condition in

building. An example of parameter generation by the use of Predicted Mean Vote (PMV)

and its indication as a thermal sensation index is given in Figure 2-10.


Air temperatum 3Ho
Air Relative humidtly -2 Wr
Airvelcit pg PM C 1 Silightly warm
Meaan Radianrt tmperatum -0Neta
(0.325e aorss +0.32) C .1 Slightly cool
Activity level
Ckloting insulation -2Co
-3 Cold


Six thermal variables Thermal sensation indicator


Figure 2-10. PMV and thermal sensation (Atthaj ariyakul & Leephakpreeda 2004).









There are several studies that concentrated on optimizing IEQ. Some of these

studies have concentrated on multi-criteria optimization by taking many concepts of IEQ

into consideration. The most studied items in the optimization studies are building shape,

thermal comfort, IAQ, and aesthetics. Al-Homoud (1997) used the direct search

optimization technique in order to optimize the building envelope. His study consisted 14

variables and used an external simulation program to perform the optimization. Nielsen

(2002) developed an optimization system by using Matlab to find the optimum

combination of the geometry and mix of building components to maximize building

performance. Caldas and Norford (2002) used a genetic algorithm (GA)4 as response

generator in optimal sizing of windows for optimal heating, cooling and lighting

performance. Additional examples of building envelope optimization for thermal comfort

and energy savings can be reached at Marks (1997). Bouchlaghem (2000) also presents

examples for optimization studies developed for environmental technology in buildings.

Wright (2002) presents an example for HVAC system optimization by using GA to

examine the trade-offs between HVAC system costs and thermal discomfort. Gustafsson

(2000) also studied optimization of HVAC systems, by mixed integer linear

programming. Linear programming (LP) has been used to solve optimization problems in

industries as diverse as banking, education, forestry, and construction scheduling and

planning. LP has been used as a tool to determine the optimal allocation of limited

resources in linear and deterministic problems. In a survey of Fortune 500 firms, 85% of

those responded said that they had used linear programming (Winston 1993). Kumar et



4 A genetic algorithm is a search technique used in computer science to find approximate solutions to
optimization and search problems. Genetic algorithms are a particular class of evolutionary algorithms that
use techniques inspired by evolutionary biology (Wikipedia 2006b).










al. (2003) have also studied various successful applications of the use of linear

programming in construction proj ects.

One of the most challenging issues in IAQ modeling derives from energy

efficiency constraints. One of the reasons for this is because the HVAC systems are

subject to time varying boundary conditions, and that the system operation must be

optimized at each boundary condition. Wright et al. (2002) in their work on optimizing

HVAC system design, optimized the model for 9 boundary conditions that represent a

period during the early morning, midday, and afternoon, in each of three seasons: winter,

fall/spring, and summer. Wright et al. (2002) in their study seeks to minimize the annual

energy use of the system. However they take the "annual energy use" as a weighted

average of the system capacity at each of the 9 operating conditions, the weights being

applied in accordance with the relative proportion of the prevailing climatic conditions.

Wright et al. (2002) configure the decision variables in a way to investigate the pay-off

between the HVAC system energy cost and the occupant thermal comfort. Wright et al.

(2002) also gives interesting examples for different pay-off situations such as the one

between capital cost of a system and the operating cost of a system. Figure 2-11 is an

illustration of the function between these different costs.



2:1, Capital :
Operating Cost

U ~+50%,
.5 Capital





Capital Cost
Figure 2-11i. Example pay-off characteristic (Wright et al.2002).










Wright et al. (2002) group the decision variables under two categories: system

operation and size of the HVAC system. Wright et al. (2002) specify three optimization

criteria:

* The operating cost of the HVAC system for the design days
* The maximum thermal discomfort during occupancy on each design day
* The infeasibility obj ective

The constraints in the study can be summarized as follows:

* Restriction on design of the coils
* Performance of the supply fan
* Requirements to ensure that the system has sufficient capacity
* Air velocity to limit noise
* Water velocity limit to prevent excessive pipe erosion
* Fan speed
* Volume flow rate through the fan
* HVAC capacity to meet required supply air temperature and flow rate

Although there are some successful examples of optimization for different aspects

of indoor air quality, none of these studies look at the problem from the building owner

and manager point of view. Thus these studies generally ignore the soft costs associated

with the various values of decision variables. Many of the previous studies are

constructed for optimization of system component design thus they rely on mostly

technical engineering variables and constraints. This research approaches the problem as

a prescreening of the sustainable management problem and simplifies the engineering

calculations since the goal is not to find the optimum component design but to find the

optimum comparison of alternative values in relation to their performance change and

associated cost per change in air quality.

Review of Literature Summary

The body of knowledge for IAQ has been expanding tremendously since thel980s.

Many studies have been conducted. However there are still gaps in our knowledge of










IAQ in buildings. European Commission (1996) listed a comprehensive list of

recommendations for the researchers and the industry in order to improve indoor quality

and energy efficiency of buildings. Some of the areas that require further research could

be listed as follows:

* Contaminants and sources: Identify contaminants and occurring occupant exposure,
safe and acceptable emissions, safe and acceptable levels of contaminants in
buildings, contaminant sources, and contaminant source management.

* Building assessment: Assess the built environment from energy, indoor air quality,
and climate aspects.

* Building systems: Identify cost-effective low energy systems for providing high
quality IEQ levels.

* Performance measurement: Identify simple, and effective methods that include both
energy efficiency and IAQ measures, for predicting the performance of buildings.

* Operation and maintenance of buildings: Identify the effectiveness of means and
methods of assessing and controlling existing buildings, including measurement
techniques to quantify the levels of IAQ.

* Changes to building design and operation: Identify the problems with IAQ caused
by the force to reduce energy consumption, and identify strong optimization
solutions.

* Experimental data: Generate data that can be used for statistical correlation
analyses for factors affecting IAQ, as well as data quantifying productivity in
relation to air cleaning and ventilation rates.















CHAPTER 3
METHODOLOGY

Introduction

The obj ective of this research is to develop a decision model for optimizing the

control of indoor air pollutants in commercial buildings in Florida. This chapter briefly

describes the nature of the research and the specific methods and concepts that satisfy the

research goals. After exploring the research questions, in the research design section, the

scope of the research and its main steps are discussed. The research methodology section

briefly discusses the use of linear programming as a tool to solve the optimization

problem. This chapter also clarifies the target populations that are the subj ect of research

or who may benefit from the decision model. The details of the steps taken in the

methodology of this research and the detailed configuration of the research model and

parameters are given in Chapter 4.

Research Questions

The maj or research question to be investigated in this dissertation is given below:

* Can an optimization model be developed to select the optimal IAQ measures in
commercial buildings in Florida to meet or exceed the standards required by code?

This study also explores the answers to the following question:

* What are the decision criteria for building owners and managers when choosing a
specific indoor air management option?





54


Research Design

The summary of the scope of the research and the outline of the dissertation is

given in Figure 3-1.

SUSTAINABLE CONSTRUCTION


RESIDMENTAL COMEIL INSIUTOA INDTIA

LIT.ATE ENERGY SIEQ A AT EYLN MATERIALS
REV.
ASETSORMALDEHYD$ PESTICIDES BIOLOGICAL POLLUTANTS NO2 R ADO~ LEAD ~OBACCCd CO


i"---~


TEP 3 4


T NUTY UVY


DECISIN SUPPORT MODEL (DSM)


VICE SYSTEM ANALYSIS


IQ IAQ ASSESSMENT > STEP 2



CONTROL OPTIONS


_ -


STEP FINAL DS MODEL


Figure 3-1. Research design.


COMFORT HEALTH


STEP1


TRUE COS









The steps that are illustrated in Figure 3-1 are explained below in more detail.

Step 1. Identify the indoor-air-pollutant-related IAQ hurdles of the building

industry.

One of the hurdles that the building industry is facing is to manage the quality of

indoor air. This problem occurs due to financial constraints and the trade-off between

better indoor air quality and energy efficiency of a building. Some of the consequences of

a better IAQ are healthy, clean, and sustainable air and air systems. The IAQ related

cautions should be considered from the design of the proj ect through the construction,

and the postconstruction (operation) phases of the building. Industry is facing several

problems on each of these phases. This dissertation conducts a broad literature search in

order to examine these hurdles under two categories:

* Identify the indoor air pollutant threats for the buildings and its occupants.

* Identify the problems regarding the current indoor air quality technologies in
commercial buildings.

This research first identifies the above problems of the building industry by using

qualitative research through broad literature review (See Chapter 2). Many studies

present the problems regarding the current IAQ technologies in the buildings. There are

also studies that show the financial consequences of poor IAQ in buildings. This study

defines these problems in terms of their soft and hard financial consequences.

One of the alternative methodologies for this step of the research could be

conducting a regional survey among the subj ects of the research in Florida. Building

Owners and Managers Association (BOMA) would be an adequate source of subj ects.

This would help clarify the specific IAQ related technical and qualitative problems of the

industry.










Step 2. Evaluate the types of IAQ options to control indoor air quality and the

factors that affect IAQ in commercial buildings.

Types of IAQ control techniques and the factors that affect the IAQ in commercial

buildings have already been described in Chapter 2. This step of the research ensures that

the model to be created includes a solution that takes all the factors affecting IAQ into

account. The comparison of the available technologies with the optimal solutions in the

model enables the researcher to make suggestions towards systems that may not exist but

would be a better option than any existing systems. The types of indoor air quality control

techniques will include:

* Improved ventilation
* Air cleaning

This study evaluates the above options in terms of their technology, physical effects

on IAQ, and the operational factors such as the policies and regulations. This study

includes the national ASHRAE Standard 62. 1-2001 for acceptable indoor ventilation as a

lower constraint assuming that the Florida Building Code mandates all buildings to meet

or exceed values mentioned in these standards.

Step 3. Evaluate the true costs of indoor air quality control techniques by

combining LCC analysis, and soft and hard costs.

Combining the lifecycle costs, other hard costs, and soft costs generates the true

costs of indoor air quality control. From an engineering perspective, LCC are all costs

from proj ect inception to disposal of equipment. The LCC analysis includes the

ownership and operating costs and uses common value engineering procedures such as

described in Isola (1997). However the users of the model will be able to choose the

values such as discount and inflation rates.










The required cost parameters and the methodology to help users carry out the cost

analysis is provided by an EPA study "A Preliminary Methodology for Evaluating Cost-

Effectiveness of Alternative Indoor Air Quality Approaches" by Henschel (1999), and by

the actual supplier quotes for the system components. The analysis includes

determination of two different types of costs:

* Soft-costs
* Hard costs

There are three areas of soft costs that engineers and their clients need to consider

in the design for acceptable IAQ in any building proj ect: the impact on productivity of

the occupants, positive or negative; effects on health of the occupants, positive or

negative; and the risk of litigation and/or legal liability that may result from any negative

impacts. The most compelling category out of three areas is the one associated with

worker productivity. In order to calculate the soft costs, this research uses the results of a

study by Wargocki et al. (2000). Wargocki et al. (2000) use the amount of outdoor air as

the only independent variable in a controlled office environment, in order to determine

the function between IAQ and productivity. This function provides a performance index

associated with different IAQ conditions. The performance index is used in this research

to calculate the savings that may potentially be generated by increasing the amount of

work output over the working hours. Soft costs associated with health and litigation, are

kept out of the model due to their stochastic nature.

Step 4. Combine the true costs, and the control options, to define and generate a

decision model.

Chapter 4 defines the details of the optimization model. However the procedures

for building the decision model follows the following five-step procedure:










* Formulate the problem.

Defining the problem includes specifying the obj ectives and the parts of the system

that must be studied before the problem can be solved. In this research the obj ective is to

minimize the true costs of an IAQ control option by increasing the amount of OA, and

the air cleaned, inside a given commercial building.

* Observe the system.

In this phase the research is oriented towards the collection of data that would

affect the problem determined in the previous section. The data to be collected include:

how much an increase in productivity saves the owner in costs; how much an increase in

the supplied air amount would increase productivity; how much hard costs are associated

with a unit increase in the amount of air or the treatment of the air; how much energy cost

occurs by an increase in the unit of outdoor air supply or recirculation air; etc.

* Formulate a mathematical model of the problem.

In this phase a mathematical model of the problem will be developed (Figure 3-2).

The model developed in this research includes:

0 Decision Variables
o Obj ective Function
0 Constraints

Figure 3-2 illustrates a preliminary illustration of a possible linear modeling

example with only two decision variables. It is shown in Figure 3-2, how the value of the

obj ective function of a model might change while changing the values for the decision

variables (X1 and X2). According to Figure 3-2, the optimum result of the model would

fall on to one of the extreme points around the feasible region that is defined by different

constraints.




















Figue 3-. Exmpl illstraionfor he popoed~ LP model
Verifyand use he mode foT)rprdcin
At his step c th ol st dtr inei h oe eeoe ntetidse sa



incuds te nfomtio from~ sensiivitanaysis











that te best Eamltraie mlutayo not xs.Hwvr the rps L model hlst hoetefail


StVepf 5.d Prsen the roesltso aned cnluions.

In this step, the model sthadt risgnerae in Step 4wll bee oprsned along hr withp the

possible rersulsfrdfeentai oh ceases.ld Tis stdep willo ianclue thi te reommendaios fompr





otimum ilbl alternatives asQ wellro asn th ft re workre for further deeopn the mdl h









results will include the sensitivity analysis in order to determine the range of validity of

the optimization and the managerial implications.

Research Methodology

This research uses a quantitative methodology that combines LCC analysis with the

soft cost analysis in order to optimize the true costs of indoor air quality control

technologies and strategies in buildings. However, this research also uses qualitative

literature review techniques to explore the criteria when the decision makers of the

building industry are choosing specific IAQ control options.

This research utilizes the methodology of operations research, which is a

quantitative methodology that offers considerable assistance to the building owners and

managers in their quest for optimal solutions. With the help of mathematical

programming this research provides the owners or managers increased ability to analyze

their IAQ problems and generate solutions in a structured manner. Linear programming

(LP) is used as a preliminary option for this research.

There are basically two assumptions implicit in an LP model. One is that any

relationship of two or more variables must satisfy the characteristics of a linear

relationship. Second, the model uses deterministic assumptions meaning that the

variances in the values are not significant enough to warrant a nondeterministic approach.

In summary, an LP model may be considered as a potential tool in determining the

optimal allocation of limited resources if and only if the situation under consideration

adequately satisfies the linear and deterministic assumptions. In a real world situation

some of the constraints and variables in a decision process may have nonlinear

relationships such as the relationship between productivity and IAQ. This research










simplifies these relationships into a linear level by using piece-wise linear

approximations'

In order to solve the model there are many software available. Excel Solver 9 is

one of those alternatives and is used to solve the model created in this research.

Population

There are two target groups that can use the results of this research. One of these is

the building owners and managers. The reason this research is oriented towards the

building owners and managers, is that owners and managers are the investors in a

building's IAQ system. For this reason an important factor is to utilize their perspective

to develop the decision model. The second group includes almost everyone that is

involved in the creation of a building. This includes architects, engineers, and contractors.

This group is the one that will benefit most from the results of this research. Since many

times owners leave the decisions to their representatives, this study will be useful for

experts that hold the decision power on investing in the IAQ of a building.

Summary of Methodology

The summary of the proposed methodology is illustrated in Figure 3-3 parallel and

compared to Simon's decision-making process (Simon 1960). The proposed methodology

involves similarities to Simon's decision-modeling process. In this research, well-known

intelligence, design, choice, and implementation phases introduced by Simon (1960) are

transformed into research, speculation, decision, and implementation phases. In the

research phase, the options for different indoor air quality levels will be evaluated. This

phase also covers the research on hurdles of the industry regarding IAQ and the


SChapter 4 provides a broad description of piece-wise linear approximation.












generation of the maj or parameters of the model. In the speculation phase, the


optimization model will be configured in terms of obj ective function, decision variables,


and constraints. The decision phase mainly covers the solution to the model, and the


implementation phase is the output of specific recommendations by using the results.


S;imon's decision-moldeling
process
INTELLIGENCE
Scanning Procedures
Data Collection
Problem Identification
Problem Statemnent



DESIGN PHASE
Formulate a M~odel
Set Criteria for Choice
Search for Alternatives
Predict and Measure Outcomes


IAQ Ruesurchl Process

RESEARCH PHASE
Identify Options
True Cost Analysis
Problem Identification
Problem Statement



SPECULATION PHASE
Formulate a ModelI


CHOICE PHASE DECISION PHASE
Solution to the Model Comparison of Alternatives
Sensitivity Analysis Solution to the Model
Selection of Alternatives U V Selection of the Optimum
Plan for Implementation Plan for Implementation



IMPLEMENTATION PHASE 1U IMPLEMENTATION PHASE
Implementation of Soluho~n Output Speolfic G;uidelines


Figure 3-3. Summary of methodology in comparison to Simon' s decision modeling
process. (Simon 1960)















CHAPTER 4
DEFINING PARAMETERS AND THE OPTIMIZATION MODEL

Introduction

The purpose of this chapter is to present the details of the methodology that was

briefly introduced in Chapter 3. This purpose includes broad definitions of the

methodologies used to generate the parameters and to generate the optimization model.

In optimization problems, researchers generally use already defined parameters for

generating the obj ective function. Parameter generation in this research is an important

part of finding a solution to the generated model. Although many optimization studies

leave this phase to the user, this research is generating the parameters in order to provide

default values to the users. The parameters that are being used in the model are generated

by Life Cycle Cost (LCC) analysis in the following areas:

* LCC for increased outdoor air (OA) to achieve desired reduction in contaminant
concentration using increased ventilation by a central or dedicated unit.

* LCC for the increased amount of air cleaned, by calculating the air cleaner
efficiency required to achieve desired reduction in contaminant concentration.

In order to calculate the parameters above, this research adapts a preliminary

methodology that is developed by the EPA (Henschel 1999). EPA's study provides a

number of worksheets to help calculate the LCC of improved ventilation, and air cleaning

techniques (Appendix A). Parallel to the obj ectives of this research, EPA' s worksheets

are generated as a part of a pre-screening tool designed for decision makers with limited

engineering knowledge. These worksheets are slightly modified in order to support the

parameter development required by the model. For example, this research reinforces










EPA's preliminary methodology with more up-to-date quotes on equipment prices from

several vendors as well as RS Means and government inflation rates. Although the EPA

developed a number of these worksheets to calculate costs of different IAQ management

options, this research refers to only a total of six worksheets. However some EPA

worksheets that are not referred to in this research are converted into and used as simple

equations. Definitions and the brief descriptions of the six worksheets adapted from EPA

are given below:

* Worksheet 1: This worksheet is designed to help estimate the installed costs for
increased OA by using a central unit. It calculates the increased heating and cooling
capacities required to condition the increased OA and suggests costs per unit
increases in capacities.

* Worksheet 2: This worksheet uses the same methodology as Worksheet 1 except
uses different unit cost suggestions to estimate the installed costs for increased OA
by a dedicated OA unit.

* Worksheet 3: This worksheet helps calculate the annual operating costs that occur
due to increased OA ventilation. Worksheet 3 takes energy efficiency ratings of the
HVAC equipment as well as the cooling and heating energy requirements in order
to calculate an annual cost.

* Worksheet 4: This worksheet helps to estimate the annual maintenance costs for
increased OA by calculating additional labor and hours required for maintenance of
specific equipment.

* Worksheet 5: This worksheet combines the annual maintenance, operating, and
annualized installed costs to estimate the total annualized costs for increased OA.

* Worksheet 6: Worksheet helps estimating the annual operating costs for central
indoor air cleaners by calculating the energy consumption and suggesting
approximate umit costs.

In this methodology, the rough estimates are set as a screening tool to assist the

model in making eliminations among the potential decision variables. The better cost

estimates can be developed for the control options if the required HVAC expertise is

available in-house or as a consulting service. The obj ective of developing these cost










parameters is to facilitate a quick, inexpensive evaluation by users who may not have the

required engineering knowledge for an extensive cost analysis. The costs that are used in

the computation are the total annual costs. This includes the annual operation and

maintenance costs, and annualized installed costs.

Estimating the Costs of Improved Ventilation

The first step in assessing the costs associated with increasing the OA ventilation

rate is to estimate the OA increase that will be required. Equation 4-1, based on EPA' s

worksheets, presents the step-wise procedure for estimating the needed increase,

assuming that dilution is the sole mechanism, which reduces the contaminant

concentration.

d x (a b)
C =(4-1)

Where,

C = Incremental increase in outdoor airflow rate required to achieve the desired reduction

in concentration (cfm).

a = Current average concentration of the contaminant of concern in the building (ppmy).

b = Average concentration to which "a" should be reduced (ppmy).

d = Current flow of OA into the building (cfm).

It is assumed in Equation 4-1 that the concentration of the contaminant of concern

is zero in the OA, and that the indoor air is well mixed so that pollutant concentrations

assumed at one point represent concentrations at all points inside a building. In this case

pollutant concern is assumed to be a homogenate problem throughout the whole section

of the building. The OA being provided by the air handler is correspondingly being

increased to treat that whole section of the building in a consistent way. In this case, as a









first approximation, one might use Equation 4-1 to estimate the additional clean air that

would have to be provided to effectively reduce the concentration in the building.

Note that Equation 4-1 disregards the added supply air increasing the mixing of the

local contaminant throughout the area served by the air handler. Also the supply air,

which is largely recirculated air, will thus increasingly differ from the assumption that

there is zero concentration of a given contaminant in the ventilating air. The user would

have to consider treating the building by moderately increasing OA flows to the entire

portion of the problematic area if a localized source were to be addressed by an increase

in direct supply air.

In this study, the model requires the cost per one efm unit increase in OA

ventilation as an input. Consequently the value of C in Equation 4-1 can be taken as 1

(one) ofm to further develop the LCC analysis. Thus the user can calculate the cost

associated with increasing the OA amount by one efm unit and use the result as a default

value in the optimization model. The details of these calculations can be seen in the

upcoming sections. The LCC calculations of the improved ventilation will be explored

under three main categories. These are:

* Installed Costs
* Operation (Energy) Costs
* Maintenance Costs

Estimating Installed Costs for Increased Ventilation

According to EPA, the existing HVAC equipment needs to be modified or adjusted

when an increase in the OA is required (Henschel 1999). Consequently an installed cost

would occur for making these modifications. An important factor in this study is the

concentration on only new construction cases. The installed costs in new construction









cases are in fact the incremental increase in the installed costs of the mechanical system

resulting from the adjustments that are made in the specifications to increase the OA rate.

Enlarged central units. Worksheet 1 in Appendix A presents a procedure for

estimating the installed costs associated with an increasing capacity of the central HVAC

units to handle increased OA in the new construction case. Worksheet 1 helps calculate

the installed costs due to increased heating and cooling capacities required to condition

the increase in OA. This worksheet is adapted from EPA' s preliminary methodology for

evaluating cost-effectiveness of alternative indoor air quality approaches (Henschel

1999). The worksheet presented in EPA' s methodology includes an option of entering up

to 3 (three) HVAC units. However in this dissertation calculations are modified for only

one HVAC unit. In this case, it is assumed that a system capable of handling and

conditioning the increased OA flow is now to be installed instead of the system that had

originally been designed for the building that has not been built yet.

Worksheet 1 is based on the following circumstances (Henschel 1999):

* Cooling and Heating Capacity: The originally designed cooling and heating
capacities are increased for the HVAC unit to handle the increased OA flow to
itself. The air handler, cooling coils, condenser, compressor, heating elements, and
controls of each unit are re-designed as required before construction. Since this
preliminary worksheet assumes direct-expansion cooling units having electric heat,
the calculations would be less accurate for systems that have chillers and furnaces.

* OA Intake Fan (if present): In cases where one or more OA intake fans are required
in the new building, the worksheet assumes that intake fans of greater capacity are
installed in lieu of the lower capacity, originally designed fans. In the model
described in this research, this item has not been included in the cost calculations
for testing purposes.

* In systems without economizers the worksheet assumes that intake and exhaust
ducting of larger dimensions are installed instead of the original intake and exhaust
ducting.










*In systems with no economizers but that have one or more central exhaust fans,
worksheet assumes that exhaust fans of greater capacity are installed instead of the
original ones.

In order to use the calculations in Worksheet 1, the required increases in heating

and cooling capacities are taken from ASHRAE (1997) by using 1% design values for the

cooling dry-bulb/mean wet-bulb temperatures. These values for Miami are 4.6-

tons/1000cfm for the required increase in cooling capacity and 6-kW/1000cfm for the

required increase in heating capacity. The users can modify these values depending on

the location of the proj ect. Table 4-1 lists these values for several cities in the US.

Table 4-1. Incremental increases in cooling and heating capacities required by increases
in OA ventilation ra es.
Required Increase in Required Increase in
City Cooling Capacity Heating Capacity
(tons pr1000 cfm OA) (kW pr1000 cfm OA)
Albuquerque, NM ~0 16
Atlanta, GA 3.3 15
Boston, MA 2.7 18
Chicao, IL 3.3 22
Cincinnati, OH 3.9 18
Cleveland, OH 2.7 20
Dallas-Fort Worth, TX 3.9 14
Denver, CO ~0 21
Houston, TX 4.6 12
Los Angeles, CA 0.5 8
Miami, FL 4.6 12
Minneapolis, MN 2.7 26
New York, NY 3.3 17
Omaha, NE 3.9 23
Pittsburh PA 2.1 20
Raleigh, NC 3.9 16
St. Louis, MO 3.9 20
San Francisco, CA ~0 10
Seattle, WA 0.5 13
Washingtn D.C. 3.9 16
(Henschel, 1999).









These values in Table 4-1 are computed by EPA using 99% heating dry-bulb

temperatures for the various cities, as defined by ASHRAE standards. The heating

capacity presented in the table is the incremental power required to increase 1,000 ofm of

outdoor air from the 99% value of outdoor temperature to an indoor temperature of 70 oF

and 50% relative humidity.

New dedicated OA units. Worksheet 2 in Appendix A presents a procedure

developed by EPA for estimating the installed costs associated with the use of a

dedicated-OA unit in the new construction case. Calculations in Worksheet 2 assume that

since a dedicated-OA unit is to be installed in a new building, it will be designed to

condition all of the OA entering the building, rather than just the incremental increases in

OA.

The EPA presents Worksheet 2, based on the following circumstances (Henschel

1999):

* Cooling and Heating Capacity: One or more rooftop direct-expansion systems with
electric heat, dedicated to treating the incoming OA, are added to the original
design. These added units have the capacity required to condition all of the OA that
is now to be supplied to the building. The cooling and heating capacities of all of
the originally designed HVAC units in the building are reduced, since the original
units will no longer be required to condition OA, providing a cost savings that
partially offsets the cost of the dedicated-OA units. The linear model that is
developed in this research, gives the user the option of entering a value for fixed
installed costs, which allows the model, produce more sophisticated decisions if
desired.

* OA Intake Fan (If present): The air handlers associated with the dedicated-OA units
become the intake fans for the entire OA flow into the building. In systems that
included OA intake fans in the original design, these intake fans can now be
eliminated, which results in cost savings.

* OA Intake Ducting: In systems with economizers, it is assumed that the increased
total volume of OA being supplied by the dedicated-OA units is delivered into the
originally designed OA intake ducting with no modifications to the original design.









* In systems without economizers the worksheet assumes that intake ducting and
exhaust ducting of larger dimensions is installed instead of the original ducting.

* For systems that have central exhaust fans but do not have economizers, Worksheet
2 assumes that exhaust fans of greater capacity are installed instead of the
originally designed fans.

Estimating Operating and Maintenance Costs for Increased Ventilation

Estimating the annual operating and maintenance costs is an important step in LCC

analysis. In order to complete this estimate, in addition to the installed costs this

dissertation suggests using the worksheets in Appendix A, provided by EPA (Henschel

1999).

Annual operating costs. EPA suggests that the annual operating cost associated

with an increase in ventilation rate can be the incremental energy cost resulting from:

* Cooling and heating the increased flow of outdoor air
* Operating the enlarged or new intake or exhaust fans (if applicable)

Worksheet 3 in Appendix A presents the method to calculate the annual operating

costs for increased ventilation. However it is important to note that this methodology

should only be used when thorough modeling of the building energy consumption and

costs is not possible.

The system size and characteristics depends on the climate of different regions as

well as the number of days and hours the OA is supplied and conditioned (Westphalen &

Koszalinski 1999). EPA states that a calculation of heating energy consumption that is

based only on the total heating degree-days in a specific geographical location may be

misleading; the mechanical system may not be supplying OA to the building during the

middle of the night, which is the coldest period of a day. This would definitely impact the

heating degree-day figure, which would alter the calculations based on only the

geographical location (Henschel 1999).









Accordingly, the EPA' s methodology to calculate the operating costs has utilized

the DOE-2 building energy computer model to compute the required energy output from

the mechanical system per incremental efm of OA in a variety of climates with

alternative mechanical systems. EPA's method assumes that OA is being supplied for 13

hours per day and 5 days per week. Since this research is concentrating on commercial

buildings this assumption is also valid for the types of buildings for which the model is

being generated. The results in the form of the average Btu of cooling energy output and

Btu of heating energy output per incremental efm for the different cities are given in

Table 4-2. The values in Table 4-2 are generated for a small office building for which the

input was available from Henschel (1999). The figure for each geographical location is an

average for alternative variable-volume and constant-volume systems, and for OA flow

rates at a range of 5 to 60 ofm/person at an occupancy density of 7 persons per 1000 ft

The values in Table 4-2 are calculated with the assumption that the OA is supplied to the

building 13 hours/day (6 am to 7 pm) on weekdays only (excluding holidays)

Table 4-2. Incremental annual cooling and heating energy requirements per unit increase
in OA ventilation rate by geographical location.
Incremental Additional Incremental Additional
Annual Cooling Energy Annual Heating Energy
City Required per Incremental Required per Incremental
Increase in OA Intake Rate Increase in OA Intake Rate
(Btu/yr per incremental efm) (Btu/yr per incremental efm)
Chicag,IL 13,000 41,000
Miami, FL 67,000 200
Minneaois, MN 13,000 63,000
Northern Virginia 20,000 25,000
Raleigh, NC 26,000 16,000
Seattle, WA 3,000 28,000
(Henschel, 1999).









In Worksheet 3, the annual incremental cost of energy is computed by using the

required energy output from the mechanical system and also by taking the system

efficiency and the unit cost of fuel or electricity into account. In the same sheet users also

have the option to calculate the energy cost for new or enlarged fans.

Annual maintenance costs: Worksheet 4 originally developed by EPA in

Appendix A provides a preliminary methodology to calculate the annual maintenance

costs for increased ventilation. The EPA's preliminary methodology assumes that

increases in ventilation cause an increase in maintenance costs only when a new intake or

exhaust fan is added or when a new dedicated OA HVAC unit is added. The EPA

worksheets assume no increase in maintenance to result from enlargements of existing

equipment. Although the worksheet is presented in the Appendix A for some users that

may require it, in this research upper bound constraints are avoiding one of the two cases

that were explained above. Thus the input data used in this research to test the model,

assumes that there would be no significant change in the maintenance costs of the system.

As for users that want to add the maintenance cost input to their model, the worksheet

suggests figures of 5 hr/yr for each fan, and 20 hr/yr for each dedicated OA unit. The

labor rate including or excluding the overhead can be obtained from the latest version of

Recommended Standard (RS) Means.

Estimating total annualized costs for increased ventilation: Worksheet 5 in

Appendix A is designed to combine the annualized installed costs with annual operating

and maintenance costs associated with the increased ventilation. However the model

developed in this research uses two different Eigures for the input cost data. It is possible

to combine the installed costs and the annual costs into one single annual cost and










eliminate the fixed cost figure. It is also possible to keep the annual O&M costs separate

from the installed costs. Worksheet 5 should be used if the user decides to combine all

the costs into one annual cost. In this case the annualized amount for the installed costs is

determined using the Capital Recovery Factor (CRF). The user can select the number of

years over which the installed cost is to be amortized, and the interest rate that is to be

charged. The number of years will generally be the estimated lifetime of the system

equipment. The value for the interest rate is the rate that is being paid on money

borrowed to install the equipment, or the interest rate that could have been obtained on

the money if it was invested rather than being used for the installation (Kirk & Isola

1995). Where "n" is the number of years, and "i" is the interest rate CRF could be

calculated by using the Equation 4-2 given below (Kirk & Isola 1995):

CRF = [i( + i)"] /[(1+ i)" 1] (4-2)

The CRF is the fraction of the initial cost that must be amortized each year if after n

years, the initial cost is to be recovered with an "i" percent annual interest rate being

charged on the unpaid balance. Consequently the total annualized cost computed in the

Worksheet 5 is the sum of:

* The CRF multiplied by the incremental total installed cost
* The incremental annual operating cost
* The incremental annual maintenance cost

Estimating the Costs for Air Cleaning

Sometimes it may be appropriate to consider the use of air cleaners to remove the

contaminants) of concern. For practical reasons, air cleaners are usually considered

when ventilation and source management are not the feasible options (Henschel 1999).

The model developed allows use all of these techniques together when feasible.









Methodology to calculate the costs of air cleaning includes two classes of indoor air

particulate cleaners: "media" air cleaners and electronic air cleaners. Media air cleaners

include :

* Pleated fi1ter panels
* Bag fi1ters
* Variations of the above types (e.g., pocket filters)

Electronic air cleaners are electrostatic precipitators. The EPA methodology used

only considers particulate air cleaners with an average removal efficiency of 65% or

greater as measured in ASHRAE standard 52. 1-1992 (ASHRAE 1992). The methodology

also assumes that lower efficiency filters are already present on the HVAC system, to

protect the fan and coils. Users of the model also have the option to modify the cost data

by including high-efficiency particulate air (HEPA) filters, which offer 99.97% removal

efficiency. These types of filters are generally used in hospital operation rooms. The cost

data generated by EPA' s methodology does not include HEPA filters.

The air cleaners considered for gaseous contaminants involve the use of beds of

dry, granular material acting by physical adsorption, chemical absorption, or catalysis

(Henschel 1999). Such air cleaners can be considered for the control of a variety of

gaseous contaminants (ASHRAE 1995), however EPA' s cost calculations are more

focused on the VOCs.

The worksheets that are adapted from EPA's preliminary study address the

incremental costs of a larger fan motor and of removing the heat generated by the larger

motor. However the worksheets do not intend to calculate any costs associated with

modifying the mechanical room or the HVAC equipment to house the air cleaner, since

these costs will be very building specific. Additionally, the installed costs for the air










cleaners computed in EPA' s worksheets assume that there are no particular complications

in the installation, which would significantly increase installation labor hours and

materials.

Estimating Installed Costs for Air Cleaners

The following items generate the costs associated with installation of a central air

cleaner:

* Obtaining and installing the air cleaner itself

* A larger motor for the central air handling fan, to compensate for the pressure drop
across the cleaner (for media filters and gaseous air cleaners)

* Cooling capacity that may potentially increase to remove the additional heat
produced by the larger fan

In order to calculate the installed costs for the air cleaners, Equation 4-3 can be

used as extracted from the worksheets developed by Henschel (1999). According to the

equation, installed costs are a simple function of total flow through the air cleaner and a

vendor quote for 1000 ofm of OA.

E = QxV (4-3)

Where,

E = Installed costs

Q = Total flow through the air cleaner

V = Vendor quote ($/1000 ofm) OR Refer to Table 4-3.

In Equation 4-3 it is important that the users first select an appropriate air cleaner

based upon the performance requirements. With this selection the user may then either

obtain an estimate from a vendor for this type of air cleaner, or may use a simplified

option given by Table 4-3. The table presents rough installed costs per 1,000 ofm air for

different types of air cleaners.

















a Adapted from Henschel (1996), updated by inflation rates from http://inflationdata. com.

The installed costs given in Table 4-3 include the cost of taking the air through the

filter and of the increase in fan motor horsepower, but exclude any costs for increased

cooling or heating capacity.

Estimating Operating and Maintenance Costs for Air Cleaners

Annual operating costs: The methodology by Henschel (1999) includes the

following items when calculating the annual operating costs:

* The increase in power consumption by the fan motor
* Power consumption by the corona wires and plates (electronic air cleaner)
* Added power consumption by the cooling system

Worksheet 6 in Appendix A presents a method for estimating the energy costs. The

worksheet that is modified from Henschel (1999) estimates incremental additional fan

horsepower requirements by multiplying the total airflow through the air cleaner times

the average pressure drop across it, accounting for fan/motor efficiency, and applying the

appropriate conversion factors. Annual energy later is calculated by multiplying this

power requirement times the number of hours per year that the fan will be operating. The

annual operating cost for the larger fan motor is determined from this energy

consumption and based on the unit cost of electricity.

The default values are available for pressure drop, fan efficiency, hours of fan

operation, and unit energy costs. If the user does not have these values available the

following values can be used:


Total Unit Installed Cost a
Type of Air Cleaner
($/1000 ofm)
Pleated panel cartridge filter, ASHRAE 65 142
Pleated panel cartridge filter, ASHRAE 85 142
Pleated panel cartridge filter, ASHRAE 95 148
Electronic Air Cleaner 496


Table 4-3 Approximate i s










* Pressure drop: 1 in. WG
* Electric Input Ratio (EIR) for the cooling system: 0.34 kW/kW
* Hours of fan operation: 3,276 hr/yr (for 13 hr/day, 5 day/wk)

Worksheet 6 in this research calculates the operating costs of media air cleaners for

particulate matter. However preliminary methodologies for calculating cost of "electronic

air cleaners for particulate matter" and the cost of "air cleaners for gaseous contaminants"

are available through EPA.

Annual maintenance costs: Maintenance costs for air cleaning include the

materials and labor costs associated with periodic replacement of the fi1ter media for

media particulate air cleaners. Henschel (1999) developed a worksheet that is converted

to Equation 4-4 in order to calculate a rough estimate for the maintenance of media

particulate air cleaners. Henschel (1999), in his study, includes more information

regarding different types of cleaners if required. Table 4-4 includes the price information

to be used in Equation 4-4. If the user has more proj ect specific data, then these data

could be easily replaced with more accurate ones in the model.


T = ($/yr) (4-4)
1000 x N



Where,

T = Annual cost of replacing the particulate media filters

u, = Approximate unit cost for replacing filters per MCFM (Table 4-4)

F,= Amount of air through cleaner i (i=1,2,3) (cfm)

N = Number of times per year that the fi1ter media will be replaced.









Table 4-4. Approximate replacement costs of media cartridges for particulate media air
cleaners
Unit Cost of Replacement Cartridgesa
Type of Air Cleaner
($/MCM
Plated pael cartridges, ASHRAE 65 45
Plated pael cartridges, ASHRAE 85 45
Plated pael cartridges, ASHRAE 95 50
a Adapted from Henschel (1996), updated by inflation rates from http://inflationdata. com.
It is assumed that only minimal labor is required to install the replacement of cartridges.

Estimation of Income Function from Increased Productivity due to Increased IAQ

The effects of indoor air quality on productivity were discussed in Chapter 2.

Wargocki (2000) conducted one of the important studies that this research has used in

order to build the cost data for productivity. Wargocki (2000) conducted three studies that

involved 90 subj ects. Using similar procedures and blind exposures, the studies showed

that increasing air quality (by decreasing the pollution load or by increasing the

ventilation rate, with otherwise constant indoor climate conditions) could improve the

performance of simulated office work (text typing, addition, and proof-reading). The

results imply that doubling the outdoor air supply rate at constant pollution load, or a

two-fold decrease of pollution load at constant ventilation rate, can increase overall

performance by 1.9%. Inspired from Wargocki's results, imaginary data in Table 4-5 was

generated to calculate the increased income as a result of increased productivity.

Table 4-5. Ventilation rate (cfm pe eson) vs. pefrmance index
17 0.99000 44 1.021972 71 1.028903 98 1.032958 125 1.035835
20 1.000000 47 1.023025 74 1.029444 101 1.033322 128 1.036109
23 1.006931 50 1.023978 77 1.029957 104 1.033672 131 1.036375
26 1.010986 53 1.024849 80 1.030445 107 1.034011 134 1.036635
29 1.013862 56 1.025649 83 1.030910 110 1.034339 137 1.036888
32 1.016094 59 1.026390 86 1.031354 113 1.034657 140 1.037135
35 1.017917 62 1.027080 89 1.031780 116 1.034965 143 1.037376
38 1.019459 65 1.027725 92 1.032188 119 1.035263
41 1.020794 68 1.028332 95 1.032580 122 1.035553










The data listed in Table 4-5 is generated by using log (e) function and is partially

integrated in the MS Excel 9 sheet where the model uses a piece-wise linearization in

order to control the estimated profit generated by the total amount of outdoor air. One of

the reasons for choosing this method is due to the limitations of the linear programming

on a nonlinear problem. If the nonlinear productivity function is linearized by using only

one line, the model produces results for either the lower bound or upper bound that is

defined with the constraints. Once the profit due to increased productivity becomes more

than the cost, the model pushes the results towards bringing as much air as possible. On

the other hand, if the profit from increased productivity comes out to be less than the cost

of bringing OA, then the model goes down to the lower constraint and tries to bring as

little air as possible.

The values for the performance index were given in Table 4-5. The graphic that

shows the plot of those values is given in Figure 4-1.


Performance Index vs OA

1.01
x 1.035-
1.03-
1.025-
1.02-
1 .015
1.01-
1 .005

0.005
0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160
OA Amount (cfmlperson)

Figure 4-1. The performance index and its correlation with the supplied OA amount.

Although performance index is the value that is defined in Wargocki's (2000)

study, this dissertation subtracts 1 (one) from these values so when they are multiplied

with the total salary of the occupants of the building, only the profit can be calculated. A










more detailed description of this calculation will be explained in the "User Defined

Independent Variables as Input Data" subsection. The final numbers in the productivity

curve after subtracting 1 from the performance index are illustrated in Figure 4-2. This

new value in this research will be referred to as "Performance Profit Index" (PPI).

Since this research is assuming linearity in the functions used in the model, the

productivity function is linearized by slightly underestimating the PPI values. Many

studies that choose to linearize a nonlinear function chooses one of the two options:

* Piece-wise linearization by overestimating
* Piece-wise linearization by underestimating


PPI vs OA

0.01


0.025





0 20 40 60 80 100 120 140 160
Am ount of OA (cfmlpe rson)

Figure 4-2. PPI and its correlation with the amount of OA.

Piece-wise linearization is used in many studies by choosing either to overestimate

or underestimate. Examples of piece-wise linearization of an exponential function are

given in Figure 4-3. The model developed in this research however would only be sound

if at least a number of segments are created. Otherwise the model as the total amount of

OA brought into the building would still create solutions at the extreme OA values. If the

PPI versus OA function was to be linearized at point r in only two lines this would only

limit the OA solutions to either 20, r or 140. However linearizing this function to at










least "n" number of lines would require the user to include additional constraints. In order

to simplify the configuration of the model, the PPI versus OA function is linearized with

11 lines at points, 20, 26, 32, 38, 44, 50, 56, 62, 68, 74, 80, and 86 (cfm). These functions

and their integration in the optimization model will be discussed in the "Defining the

Optimization Model" section. The piece-wise linearization of the PPI vs. OA function is

given in Figure 4-4.











A, E D A ^ o B
Figure 4-3. An example for piecewise linear overestimate and underestimate of an
exponential function. A) Overestimating, B) Underestimating (Irion et al.
2004)


0.04
0 035 g


L 0.02
0 015
0.01
0 005

0 20 40 60 80 100 120 140 160
Am ount of OA (cfmlpe rs on)

Figure 4-4. Piece-wise linearization of the PPI vs. OA function.

In order to calculate the equation of the lines presented in Figure 4-4, the values

obtained from Figure 4-4 or Table 4-5 can be inserted in Equation 4-5. The value of the


PPI vs OA









slope (m) can be calculated by finding the tangent of the B : angle for each linear segment

by using Equation 4-6.

y = mx + c (4-5)

Where,

m = The slope of the line

c = The constant.

S(Maxe PPI Min PPI)
Tan(0)= = m. (4-6)
(Max OA Min OA)

This research disregards the correlation between the amount of air cleaned with the

productivity levels and PPI. If any scientific data are developed in the future, a new linear

function can be calculated by using similar methods shown for OA vs. PPI calculations.

Defining the Optimization Model

The optimization study includes three maj or parts as listed below:

* Improved ventilation by central unit
* Improved ventilation by a dedicated unit
* Air cleaning

These areas are all combined in an obj ective function in order to set the values for

the decision variables that are subj ect to the constraints. An important factor to note is

that using the preliminary methodology developed by EPA that is introduced earlier can

help estimate the rough values for the input unit costs. However it is also important to

evaluate the model not in terms of the actual numbers that will be constantly changing

due to inflation rates and other economic and technological developments, but of the

relationships among the IAQ control options. The model is developed as a preliminary

model that is basically simplified in many terms to clarify the application of linear

programming methodologies in construction management. Although more complex










optimization methodologies are widely used in the engineering side of this area,

construction managers and the building owners and managers are still not aware of the

possibilities that optimization studies can offer in making preliminary decisions.

Decision Variables

Decision variables are the dependent variables in LP that are subj ect to changing

while optimizing the obj ective function. There are a total of eleven decision variables in

this research. The units of all the variables except the binary ones and the productivity

variable are cubic feet per minute per person and all the cost values in the model are

annual. Decision variables of the model in this research are listed below:

X, = Amount of OA supplied by a central unit (cfm/person)

X2= Amount of OA supplied by a dedicated unit (cfm/person)

W= Profit generated by increased productivity ($)

F,= Amount of air through cleaner 1 (cfm/person)

F2= Amount of air through cleaner 2 (cfm/person)

F3= Amount of air through cleaner 3 (cfm/person)

Y,= "1" if central unit is used, "O" if not

Y2 "1" if dedicated unit is used, "O" if not

B, = "1" if cleaner 1 is used, "O" if not

B2 -- "1" if cleaner 2 is used, "O" if not

B3 -- "1" if cleaner 3 is used, "O" if not









The details explanations of the above decision variables are given below:

a) (X, ) Amount of OA supplied by a central unit

This variable represents the amount of outdoor air that is being supplied to the

building by a central HVAC unit in efm/person units. ASHRAE 62. 1-2001 standards

mandate the total amount of OA supplied in commercial buildings as 20 ofm per person.

However the model investigates in more depth to explore if bringing more OA would still

be economically feasible.

b) (X, ) Amount of OA supplied by a dedicated unit

The difference of the OA by the dedicated unit from the central unit appears only

when dealing with fixed installed costs. The operating and maintenance costs associated

with this variable are supposed to be exactly the same as the OA by the central unit. Thus

the model will choose to bring OA into the building by either a dedicated or central unit

depending on their fixed installed costs.

c) (Fi ) Amount of air through cleaner "i" (for i=1.2,3)

This is the amount of air that passes through the air cleaners that are located

possibly in three different locations. These locations are illustrated in Figure 4-5. The

relations among these different locations will be discussed under the constraints section.

According to Figure 4-5, if a cleaner is located on location then it will only clean the

outdoor air supplied to the system. If it is located in Location 2 then it will only clean the

recirculating air. If it is located on Location 3 then it will be able to filter both

recirculating air and the outdoor air.







































Figure 4-5. Possible air cleaner locations.

d) ( Y,) Binary variable for central air unit

This variable is the binary variable for the central unit. It gives the model the option

of either using this unit or not. If the model finds it optimum to use the central air unit,

the value of this decision variable appears in the solution as "1" and "O" if not used.

e) (Y2) Binary variable for dedicated unit

This variable is the binary variable for the dedicated unit. It gives the model the

option of either using this unit or not. If the model finds it optimum to use the dedicated

air unit the value of this decision variable appears in the solution as "1" and "O" if not

used.


Exhaunst Air










f) (B ) Binary variable for air cleaners (for i=1,2,3)

This variable is the binary variable for each of the air cleaners. B, represents the

binary for location 1, B, is the binary variable for location 2, and B, is the binary variable

for air cleaner in location 3 (See Figure 4-3). Depending on these variables being "1" or

"O" the user can decide which one(s) should be used or not.

Objective Function

The obj ective function of the model is given in Equation 4-7. The obj ective of the

model in managerial terms is to minimize the true costs of indoor air quality management

options. In more detail, it is to minimize the overall cost of providing outdoor air and

cleaning air in a commercial building while maximizing the benefits of increased worker

productivity. Equation 4-7 represents the summation of three maj or costs. These are the

cost of OA by a central unit, OA by a dedicated unit, and cleaning air in three possible

locations. The cost of bringing OA by a central unit includes the variable cost (VC),

revenue generated by increased productivity (R), and the fixed costs (FC).


Minz= ~(AiX, +C,Y,)+ (FD)+BE)- (4-7)
I=1 J=1


VC, FC, VC, FC, R
Where,

z = The total annual cost of the IAQ control ($)

A, = Marginal cost of air by central unit ($ x person/cfm)

A, = Marginal cost of air by dedicated unit ($ x person/cfm)

C, = Fixed cost for central unit ($)

C, = Fixed cost for dedicated unit ($)









D = Cost for cleaning air ($ x person/cfm)

E = Fixed cost for air cleaners ($)

4= Money saved by incre~ased productivity by central unit (See~ Eq. 4T-7) ($)

P,= Money saved by increased productivity by dedicated unit (See Eq. 4-7) ($)

P,= Money saved by increased productivity by air cleaners (See Eq. 4-7) ($)

X, = Amount of OA supplied by a central unit (cfm/person)

X, = Amount of OA supplied by a dedicated unit (cfm/person)

F,= Amount of air through cleaner 1 (cfm/person)

F,= Amount of air through cleaner 2 (cfm/person)

F,= Amount of air through cleaner 3 (cfm/person)

Y,= "1" if central unit is used, "O" if not

Y,= "1" if dedicated unit is used, "O" if not

B, = "1" if cleaner 1 is used, "O" if not.

B, = "1" if cleaner 2 is used, "O" if not.

B, = "1" if cleaner 3 is used, "O" if not.

W = Profit generated by increased productivity by using PPI function. ($)

Although the data stating the dependency among the variables X X,, and F, are

not clearly set with the current literature and studies, there is a strong belief that in fact

there should be a relationship (Wargocki 2000). If data become available then this

dependency can be reflected in the model by including a function of X, and F, in the

calculation of W. This may create a more accurate and actual representation of the IAQ










measures and productivity. However the new obj ective function in that case would

become a nonlinear function, which would require a more complex solution to the model.

Thus solving the model with MS. Excel Solver 9 would not be possible anymore. On the

other hand there are other software and tools available for this type of optimization such

as Lingo 9. Once the data and verification are available one should consider using these

software to complete the solution of the model.


Decision Constraints

Decision constraints of the model are a set of constraints that the model is limited

with while changing the value of the decision variables to optimize the obj ective

function. The decision constraints that the objective function (See Equation 4-7) is

subj ect to, are given below:

1. X, +X2 <140clinn

2. X, + X 2 >20 c/i~n

3. Y, + Y 2

4. B, + B2 + B3

5. X, -140Y, <0

6. X2 -140Y2 <0

7. ( -140B, <0

8. F, + F2 F3 < 0

9. X, + X2 (F, + F2 + F3) < 0

10. 1 83 1.02 X1 1 83 1.02 X2 + W <= -3 6620.41

11. 851.38 X1 851.38 X2 + W <= -11149.65

12. 560.79 X1 560.79 X2 + W <= -1850.81










13. 418.36 XI 418.36 X2 + W <= 3542.52

14. 334.45 X1 334.45 X2 + W <= 7256.39

15. 278.42 X1 278.42 X2 + W <= 10057.78

16. 23 8.50 X1 23 8.50 X2 + W <= 12293.41

17. 208.61 X1 208.61 X2 + W <= 14146.98

18. 185.38 Xi 185.38 X2 + W <= 15726.56

19. 166.81 XI 166.81 X2 + W <= 17100.76

20. 151.62 Xi 151.62 X2 + W <= 18315.65

21. All variables 2 0

Constraint 1. This constraint mandates that the amount of OA taken into the

building does not go over 140 ofm of OA since this would require a replacement or

upgrade of the equipment.

Constraint 2. This constraint mandates that the total amount of OA supplied by

both units should be at least 20 ofm per person, which is the requirement of ASHRAE

Standard 62. 1-1999 for commercial buildings.

Constraint 3. This binary constraint requires the model to select at least one of the

HVAC units (dedicated or central).

Constraint 4. This binary constraint requires the model that at least one of the air

cleaners at one of the possible locations shall be selected. If the user decides that only one

of the cleaners should be selected then the > should be replaced with "="

Constraint 5. This constraint is similar to the Big M method. It makes sure that if

the model decides not to use the central unit, Y, will be zero (0), thus the model will

automatically give X, the value of zero (0) so it will not be included in the obj ective

function cost calculations.