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Apparent total evaporative resistance values from human trials over a range of heat stress levels

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Title:
Apparent total evaporative resistance values from human trials over a range of heat stress levels
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Book
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English
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Dooris, Matthew David
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University of South Florida
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Subjects / Keywords:
Convective Transport
Evaporative Cooling
Heat Exchange
Protective Clothing
Water Vapor Diffusion
Dissertations, Academic -- Occupational Health Environmental Health Industrial Engineering -- Masters -- USF   ( lcsh )
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bibliography   ( marcgt )
non-fiction   ( marcgt )

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Abstract:
ABSTRACT: Failure to maintain thermal equilibrium can cause uncontrollable increases in body core temperature beyond critical upper limits. In selecting clothing, consideration must be given to the heat transfer properties of clothing that may restrict the cooling capacity of the human body under heat stress conditions, most importantly, apparent total evaporative resistance (Re,T,a). This study calculated and compared Re,T,a for five clothing ensembles under varying heat stress conditions, including three relative humidity (RH) levels and three stages of heat stress to determine if Re,T,a values varied or remained the same with changes in heat stress conditions. A four-way mixed model analysis of variance demonstrated significant differences for estimated Re,T,a values among ensembles, RH levels, heat stress stages, and interactions among ensembles and RH levels and ensembles and heat stress stages (p < 0.0001). No significant interaction among RH levels and heat stress stages was found (p = 0.67). A Tukey's Honestly Significant Difference multiple comparison test was used to identify where significant differences occurred (p < 0.05). The results of the study indicated that Re,T,a values do change with RH levels and stages of heat stress and that the theoretical framework for explaining heat-exchange in hot environments is not yet well-established. Also confirmed was the dominance of the convection pathway over the diffusion pathway in hot environments.
Thesis:
Thesis (M.S.P.H.)--University of South Florida, 2011.
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Includes bibliographical references.
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by Matthew David Dooris.
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Title from PDF of title page.
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Document formatted into pages; contains 76 pages.

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ABSTRACT: Failure to maintain thermal equilibrium can cause uncontrollable increases in body core temperature beyond critical upper limits. In selecting clothing, consideration must be given to the heat transfer properties of clothing that may restrict the cooling capacity of the human body under heat stress conditions, most importantly, apparent total evaporative resistance (Re,T,a). This study calculated and compared Re,T,a for five clothing ensembles under varying heat stress conditions, including three relative humidity (RH) levels and three stages of heat stress to determine if Re,T,a values varied or remained the same with changes in heat stress conditions. A four-way mixed model analysis of variance demonstrated significant differences for estimated Re,T,a values among ensembles, RH levels, heat stress stages, and interactions among ensembles and RH levels and ensembles and heat stress stages (p < 0.0001). No significant interaction among RH levels and heat stress stages was found (p = 0.67). A Tukey's Honestly Significant Difference multiple comparison test was used to identify where significant differences occurred (p < 0.05). The results of the study indicated that Re,T,a values do change with RH levels and stages of heat stress and that the theoretical framework for explaining heat-exchange in hot environments is not yet well-established. Also confirmed was the dominance of the convection pathway over the diffusion pathway in hot environments.
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Apparent Total Evaporative Resistance Values from Human Trials Over a Range of Heat Stress Levels by Matthew D. Dooris A thesis submitted in partial fulfillment of the requirements for the degree of Master of Science in Public Health Department of Environmental and Occupational Health College of Public Health University of South Florida Major Professor: Thomas E. Bernard, Ph.D. Steven Mlynarek, Ph.D. Yehia Y. Hammad, Sc.D. Candi D. Ashley, Ph.D. Date of Approval: March 28, 2011 Keywords: Protective Clothing, Evaporative Cooling, Heat Exchange, Water Vapor Diffusion, Convective Transport Copyright 2011, Matthew D. Dooris

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DEDICATION I dedicate this work to my family. The completion of this manuscri pt would not have been possible without the strength, love, and support of my beautiful wif e, Laura Mae Dooris, my son, Matthew Monroe Dooris, and my parents, Drs. George and Patricia Dooris.

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ACKNOWLEDGEMENTS I am grateful to my major professor, Dr. Thomas Bernard, for his di rection and sage advice, as well as guidance and support provided by other members of my committee, Dr. Steven Mlynarek, Dr. Yehia Hammad, and Dr. Candi Ashle y. I am grateful also to Brian Grace and Roberta Moore for their hard w ork and diligence in helping me to complete the data extraction and verification portion of this thesis. I would also like to acknowledge the United States Coast Guard for fundin g my education and allowing me to remain focused on task for the last two years. Thi s work would not have been possible without funding support from the National Institute of Occupat ional Safety and Health Research Grant (1R01-OH03983) and assistance of the NIOS H-supported Sunshine Education and Research Center at USF (T42-OH008438).

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i TABLE OF CONTENTS LIST OF TABLES ............................................................................................................. iii LIST OF FIGURES .............................................................................................................v LIST OF ABBREVIATIONS ............................................................................................ vi ABSTRACT .................................................................................................................. viii CHAPTER 1: INTRODUCTION ........................................................................................1 Problem Statement ...................................................................................................1 Research Question ...................................................................................................8 Significance of Research..........................................................................................8 Overview of Thesis ..................................................................................................9 CHAPTER 2: LITERATURE REVIEW ...........................................................................10 Estimates of Clothing Heat and Vapor Resistance ................................................10 Clothing Insulation.....................................................................................10 Water Vapor Permeability .........................................................................11 Evaporative Resistance ..............................................................................12 Testing Methods for Estimating Clothing Heat and Vapor Resistance .................13 Heated Plate ...............................................................................................13 Heated Copper Manikin .............................................................................14 Modeling ....................................................................................................15 Human Subjects .........................................................................................16 Progressive Heat Stress Protocol ...........................................................................16 Heat Exchange in Hot Environments .....................................................................17 Microclimates and Microclimate Effects ...................................................18 Heat Exchange Pathways ...........................................................................19 CHAPTER 3: METHODOLOGY .....................................................................................23 Overview ................................................................................................................23 Participants .............................................................................................................23 Clothing..................................................................................................................24 Equipment ..............................................................................................................24 Protocols ................................................................................................................25 Inflection Point and Determination of Critical Conditions ....................................26 Data Extraction ......................................................................................................27

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ii Calculation of Clothing Parameters .......................................................................28 Statistical Analysis .................................................................................................31 CHAPTER 4: RESULTS ...................................................................................................32 Overview ................................................................................................................32 Main Effects ...........................................................................................................32 Interactions .............................................................................................................34 Temperature and Vapor Pressure Gradients ..........................................................37 CHAPTER 5: DISCUSSION .............................................................................................42 Analysis of Results ................................................................................................42 Conclusion .............................................................................................................50 Future Research .....................................................................................................50 Study Limitations ...................................................................................................51 REFERENCES ..................................................................................................................52 APPENDICES ...................................................................................................................57 Appendix A: Aggregate Apparent Total Evaporative Resistance Data .................58 Appendix B: Aggregate Environmental Data ........................................................59 Appendix C: Environmental Data for Main Effects ..............................................60 Appendix D: Environmental Data for Interactions ................................................61 Appendix E: Statistical Differences for Interactions .............................................63 ABOUT THE AUTHOR ................................................................................... END PAGE

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iii LIST OF TABLES TABLE 3.1: Physical Characteristics of Participants (Mean Standa rd Deviation) ........24 TABLE 4.1: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles ....................................................................33 TABLE 4.2: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Three Relative Humidity Levels ..........................................33 TABLE 4.3: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Three Heat Stress Stages ......................................................34 TABLE 4.4: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles at Three Relative Humidity Levels ............34 TABLE 4.5: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages ........................36 TABLE 5.1: Apparent Total Evaporative Resistance Values, Temperature and Pressure Gradients, and Net Heat Gain Plus Dry-Heat Loss Values for Two Ensembles at Three Relative Humidity Levels ...............................44 TABLE 5.2: Apparent Total Evaporative Resistance Values, Temperature and Pressure Gradients, and Net Heat Gain Plus Dry-Heat Loss Values for Two Ensembles at Three Heat Stress Stages ..........................................46 TABLE A1: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 20% Relative Humidity .........................................................................................58 TABLE A2: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 50% Relative Humidity .........................................................................................58 TABLE A3: Least Squares Mean of Apparent Total Evaporative Resistance (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 70% Relative Humidity .........................................................................................58

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iv TABLE A4: Average Temperature Difference ( o C) for Five Ensembles at Three Heat Stress Stages and Three Relative Humidity Levels (Mean Standard Deviation) ......................................................................................59 TABLE A5: Average Vapor Pressure Difference (kPa) for Five Ensemble s at Three Heat Stress Stages and Three Relative Humidity Levels (Mean Standard Deviation) ...................................................................................59 TABLE A6: Temperature and Water Vapor Pressure Levels for Five Ensem bles (Mean Standard Deviation) ........................................................................60 TABLE A7: Temperature and Water Vapor Pressure Levels for Three Relat ive Humidity Levels (Mean Standard Deviation) ............................................60 TABLE A8: Temperature and Water Vapor Pressure Levels for Three Heat S tress Stages (Mean Standard Deviation) ............................................................60 TABLE A9: Temperature and Water Vapor Pressure Levels for Five Ensembl es at Three Relative Humidity Levels (Mean Standard Deviation) ...............61 TABLE A10: Temperature and Water Vapor Pressure Levels for Five Ensembl es at Three Heat Stress Stages (Mean Standard Deviation) .........................62 TABLE A11: Statistically Significant Differences for Five Ensem bles at Three Relative Humidity Levels ............................................................................63 TABLE A12: Statistically Significant Differences for Five Ensem bles at Three Heat Stress Stages .......................................................................................64

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v LIST OF FIGURES FIGURE 3.1: Time Course of Rectal Temperature for One Trial .....................................27 FIGURE 4.1: Least Squares Mean of Apparent Total Evaporative Resistance f or Five Ensembles at Three Relative Humidity Levels ...................................35 FIGURE 4.2: Least Squares Mean of Apparent Total Evaporative Resistance for Five Ensembles at Three Heat Stress Stages ...............................................36 FIGURE 4.3: Average Temperature Differences for Five Ensembles at Three Relative Humidity Levels ............................................................................38 FIGURE 4.4: Average Temperature Differences for Five Ensembles at Three Heat Stress Stages .......................................................................................39 FIGURE 4.5: Average Vapor Pressure Differences for Five Ensembles at Thr ee Relative Humidity Levels ............................................................................40 FIGURE 4.6: Average Vapor Pressure Differences for Five Ensembles at Thr ee Heat Stress Stages .......................................................................................41 FIGURE 5.1 Least Squares Mean of Apparent Total Evaporative Resistances (A), Average Pressure Differences (B), and Net Heat Gain Plus Dry-Heat Loss Values for Two Ensembles at Three Relative Humidity Levels ..........................................................................................45 FIGURE 5.2 Least Squares Mean of Apparent Total Evaporative Resistances (A), Average Pressure Differences (B), and Net Heat Gain Plus Dry-Heat Loss Values for Two Ensembles at Three Heat Stress Stages ...........................................................................................................47

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vi LIST OF ABBREVIATIONS A D – Dubois Surface Area ACGIH – American Conference of Governmental Industrial Hygienists ANOVA – Analysis of Variance ASTM – American Society for Testing and Materials C – Compensable Stage of Heat Stress C res – Respiratory Convective Heat Flow CC – Cotton Coveralls CFI – Correction Factor for Insulation DH – Dry-Heat Loss E res – Respiratory Evaporative Heat Flow f g – Fractional Grade of the Treadmill H – Height H net – Net Heat Gain HSD – Honestly Significantly Different I clo Total Intrinsic Clothing Insulation i m – Moisture Permeability Index i m,a – Apparent Moisture Permeability Index i m,stat – Static Moisture Permeability Index I T – Total Insulation I T,r – Total Resultant Insulation I T,stat – Total Static Insulation ISO – International Organization for Standardization M – Metabolic Rate m b – Body Mass OSHA – Occupational Safety and Health Administration P a – Ambient Water Vapor Pressure P sk – Skin Water Vapor Pressure PHS – Predicted Heat Strain

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vii R2 – 20% Relative Humidity R5 – 50% Relative Humidity R7 – 70% Relative Humidity R e,T – Total Evaporative Resistance R e,T,a – Apparent Total Evaporative Resistance R e,T,stat – Static Total Evaporative Resistance RH – Relative Humidity S – Body Heat Storage Rate SD – Standard Deviation T – Transition or Critical Stage of Heat Stress T db – Ambient Air Temperature T exp – Expired Air Temperature T g – Globe Temperature T pwb – Psychrometric Wet Bulb T re – Body Core (Rectal) Temperature T sk – Skin Temperature TLV – Threshold Limit Value U – Uncompensable Stage of Heat Stress USF – University of South Florida v – Air Speed V O2 – Oxygen Consumption V T – Ventilation Index V W – Walking Speed w – Walking Speed or Speed of Treadmill W – Watts (Effective Mechanical Power) W ext – External Work WC – Work Clothes P – Pressure Gradient (P sk – P a ) T – Temperature Gradient (T db – T sk ) T re – Rate of Change in Body Core (Rectal) Temperature

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viii ABSTRACT Failure to maintain thermal equilibrium can cause uncontrollable in creases in body core temperature beyond critical upper limits. In selecti ng clothing, consideration must be given to the heat transfer properties of clothing that may restrict the cooling capacity of the human body under heat stress conditions, most important ly, apparent total evaporative resistance (R e,T,a ). This study calculated and compared R e,T,a for five clothing ensembles under varying heat stress conditions, including three relat ive humidity (RH) levels and three stages of heat stress to determine if R e,T,a values varied or remained the same with changes in heat stress conditions. A four-way mixe d model analysis of variance demonstrated significant differences for estimated R e,T,a values among ensembles, RH levels, heat stress stages, and interactions amon g ensembles and RH levels and ensembles and heat stress stages (p < 0.0001). No signif icant interaction among RH levels and heat stress stages was found (p = 0.67). A T ukey’s Honestly Significant Difference multiple comparison test was used to ident ify where significant differences occurred (p < 0.05). The results of the study indicated that R e,T,a values do change with RH levels and stages of heat stress and that the t heoretical framework for explaining heat-exchange in hot environments is not yet well-establ ished. Also confirmed was the dominance of the convection pathway over the diffusi on pathway in hot environments.

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1 CHAPTER 1: INTRODUCTION Problem Statement Many workplaces provide different types of clothing ensembles to offer protection to employees from assorted chemical, physical, and biolog ical agents. A serious concern faced by employers when selecting appropriate c lothing is whether it will induce some level of heat stress. Heat stress is a signific ant occupational problem in the U.S. as 5-10 million workers are exposed to heat stress conditions e ach year (Occupational Safety and Health Administration [OSHA], 2010). It is estimated that in 2006 approximately 44 U.S. workers died and 3,100 more lost work hours from hea trelated disorders (Office of Compliance, 2009). Through the implementa tion and enforcement of effective control measures and work practices, ris k associated with heatrelated disorders can be managed. OSHA has not promulgated any specific regul ations to govern the protection of employees from heat stress; however, the agency expects employers to protect workers from heat stress in accordance w ith the General Duty Clause, Section 5(a)(1) of the OSH Act (OSHA, 1999). Originally adopted in 1972, the American Conference of Governmental Industrial Hygienists (ACGI H ) publishes a threshold limit value (TLV ) for heat stress to limit body core temperatures of worke rs to 38 o C. Body core temperatures above 38 o C should be avoided to prevent the onset of heat

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2 strain although brief, intermittent work periods are acceptable wit h sufficient recovery periods (ACGIH, 2010; Bernard, 1999). Heat balance analysis as outlined by Havenith (1999) and further di scussed by Havenith et al. (2008) and Bernard (1999) is a method used to conceptuali ze the processes involved in thermoregulation. When a person is capable of elim inating body heat at a rate greater than the rate it is being generate d the body is said to be in a state of compensable heat stress. Failure to maintain thermal equilibrium results in an uncontrollable rise in body core temperature beyond a critical upper limit, a homeostatic threshold, which has become recognized as uncompensable heat stress (B ernard et al. 2010). When uncompensable heat stress is achieved, the human body cannot eliminate heat at the same rate it is being generated. The critical uppe r limit was originally described by Lind (1963) as the upper limit of the prescriptive zone but has since become known as the critical condition (Bernard et al. 2010, 2009, 2005; Caravell o et al. 2008; Kenney et al. 1993; Frye & Kamon, 1981; Belding & Kamon, 1973). Other physiological indicators of heat stress include increased hear t rates and profuse sweating (Ashley et al. 2008; Barker, Kini, & Bernard, 1999). Job risk factors for inducing heat stress consist of environmental condi tions, work demand, and clothing requirements (Bernard & Ashley, 2009; Barker et al 1999). Environmental conditions include air temperature, ambient air vapor pr essure (humidity), radiant heat, and air movement. Heat stress conditions can be induc ed by elevating the ambient air temperature or the ambient water vapor pressure in hot environments (Kenney et al. 1993). The human body absorbs heat from the environment when air temperatures exceed 40 o C (104 o F) and loses heat when temperatures fall below 32 o C

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3 (90 o F). The consequence of reducing air temperature is decreased wa ter vapor pressure levels supported by air. Air loses its capacity to retain wa ter with decreases in temperature which results in higher evaporative cooling rates (he at loss) at lower air humidity levels. The rate of evaporative heat loss is influenced b y the amount of water vapor pressure present in the air versus the skin. In most environmental conditions, higher concentrations of water vapor on the skin than in the air prom ote effective evaporative cooling. In very rare situations and only in extreme climatic conditions will the moisture concentration gradient become equalized or even reversed, prohibiting evaporative heat loss (DiNardi, 2003; Plog & Quinlan, 2002; Havenith, 1999; O SHA, 1999). Radiant heat is generated from hot surfaces that are not adequat ely shielded, insulated, or where the emissivity of the source has not been suffic iently reduced. The body absorbs radiant heat readily at temperatures exceeding 43 o C (109 o F). Air movement stimulates greater air contact with human skin promoting e vaporative cooling and body core temperature reduction. However, several temperature thresholds must be considered when assessing the effect of air movement on heat stress. At temperatures below 35 o C (95 o F) effective heat loss is possible with increased air movement, while opposing results are observed with temperatures above 40 o C (104 o F). Minimal body heat loss occurs between 35 o C and 40 o C (95 o F and 104 o F). Another relevant factor that must be considered is air speed. The best results are obtained betwee n 0 and 2 m/s while no gain in evaporative cooling is detected at air speeds excee ding 3 m/s (ACGIH, 2010; DiNardi, 2003; Plog & Quinlan, 2002; Bernard, 1999; Havenith, 1999; OSHA, 1999).

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4 Metabolic work demand contributes significantly to body heat gain but can be controlled by automating processes, reducing workloads, and pacing job tasks. High metabolic rates sustained over a period of time can generate body h eat at levels which cannot be dissipated effectively, resulting in physiological stra in. Higher levels of metabolic rates are observed with dynamic work when compared t o static work as muscles are required to flex and extend in response to work demands. Standard metabolic rate tables have been established to assist employer s in estimating work demands imposed on workers for different types of job tasks (Interna tional Organization for Standardization [ISO], 2004b). However, metabolic rates will not be uniform among a group of employees because individual differences in height, weigh t, and oxygen consumption influence metabolic rate levels. Heat loss can occur b y five different pathways including conduction, convection, radiation, evaporation, and respirati on. Evaporation is the primary pathway governing thermal equilibrium i n hot environments. The body eliminates sizeable amounts of heat through the evaporation of sweat on the surface of the skin or, in some cases, clothing layers. Conduction is only important for work performed in water. Convection provides a reliable means for dis sipating heat from warmer skin to cooler ambient air as long as air temperatures remain near or below skin temperatures. Internally generated body heat may also be tra nsferred to nearby cooler objects by means of radiation. Exerting even lower effect on he at exchange is respiration which unloads heat by way of convection and evaporation in the pulmonary sys tem (DiNardi, 2003; Plog & Quinlan, 2002; Bernard, 1999; Havenith, 1999; Holmer et al 1999; OSHA, 1999).

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5 The final job risk factor, clothing, is the focus of the remainder of this thesis. Protective clothing can be extremely useful in protecting workers from a number of occupational hazards including chemicals, cold stress, radioactive c ontamination, burns, among other deleterious exposures. Unfortunately, clothing can also lead to heat stress and heat-related disorders. The beneficial and potentially hazardous c haracteristic of clothing is its ability to act as a barrier. Some of the desi red qualities of clothing barriers, depending on intended use, include the ability to prevent the intrusion of chemicals or other unwanted substances, reflect radiant heat, or provide thermoregula tion in cold environments. However, the same barrier which protects the worker can also cause physiological stress. Clothing serves as an impedance barr ier to the exchange of heat and water vapor between the skin and the environment which can result in lower rates of evaporative cooling. Restriction of heat exchange pathways may not di sturb thermoregulation in cool environments with low-moderate metabolic ra tes or warm environments with low metabolic rates. However, moderate-high me tabolic rates in cold environments or moderate metabolic rates in warm environments could i nduce heat strain. Evident in this discussion is the importance of time as a fourth job risk factor for heat stress. Moderate work rates in a warm environment may not i nduce heat stress over 30 minutes but it may if work continued for 60 minutes keeping all other j ob risk factors constant (ACGIH, 2010; Bernard & Ashley, 2009; Havenith, 1999). Havenith (1999) described the most important factors of clothing rela tive to heat stress to be the construction, configuration, and number of layers w orn by a worker. Loose fitting, light-weight clothing such as a cotton work uniform permi ts ambient air to enter the ensemble and make rapid contact with human skin. In doing so, the air,

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6 depending on temperature and humidity, supports evaporative-heat exchange b y transporting vaporized sweat and heat from the body to the environment New air from the workplace environment takes the place of the exiting air to cont inue the process. The net result is evaporative cooling or loss of body heat. Single lay er vapor-barrier clothing, multi-layered clothing, or clothing which is tight fitting can impe de the ability for ambient air to enter and make contact with human skin. The worker p erspires but limited or no evaporative cooling occurs because air is not adequately circul ated in and out of the clothing. A very good example of vapor-barrier clothing can be observe d among wetland scientists who must wear chest waders to enter very wet are as during the summer months in Florida. The coveralls effectively keep water from entering the coveralls but the ensemble is impermeable to both water and air. For this reason, li mited air is permitted to circulate inside the coveralls, except from the “pumping effect ” produced from body movement, preventing sufficient removal of metabolic heat generated fr om walking and performing other demanding work (Havenith & Nilsson, 2004; Havenith, 1999). Over the past several decades, studies have been performed t o expose the principal factors governing the thermal properties of assorted clothing ensembles regularly used in occupational settings (Bernard et al. 2010; Cara vello et al. 2008; Havenith et al. 2008; Barker et al. 1999; Holmer et al. 1999; Kenney et al. 1993). The most commonly used values to describe the thermal properties of c lothing and what is recommended by the ISO are: total insulation (I T ), water vapor permeability, expressed using a moisture permeability index (i m ), and total evaporative resistance (R e,T ). Each value will be described in detail in Chapter 2 but a brief descript ion of R e,T is warranted considering its importance in characterizing the risk of heat st ress among clothing

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7 ensembles. R e,T values are expressed in m 2 kPaW -1 and static (R e,T,stat ) or resultant (R e,T,a ) values can be calculated (Barker et al. 1999; Kenney et al. 1993). Static values reflect periods of clothing wear absent air or body movement while resultant va lues are adjusted for conditions where workers are in motion and air movement exists. T he term “apparent” is often used to describe resultant values because they are measured in laboratory settings and may not represent accurately the complic ated mechanisms of heat transfer experienced in the workplace (Caravello et al. 2008). As will be seen in Chapter 2, R e,T,a values are largely contingent on the differences in water vapor p ressure between the skin and air. Different clothing barriers will prohibit or li mit the transfer of air and moisture between the skin and the environment, thus artificially alte ring water vapor pressure differences inside the ensemble. The end result is a r eduction in evaporative cooling. R e,T,a estimates the water vapor resistance observed from the skin to the environment under prescribed climatic conditions and work demand. What als o makes R e,T,a so useful and telling of heat stress conditions is the estimat ed resistance takes into consideration all layers of clothing, as well as enclosed and boundary air layers (ISO 2007). The problem examined in this thesis is the relationship between R e,T,a values and variable moisture levels in the environment. Presently unknown is wh ether R e,T,a varies or remains the same with changes in ambient air temperature (T db ) or ambient water vapor pressure (P a ) in hot environments. The purpose for this study is to calculate R e,T,a for five clothing ensembles under varying heat stress conditions and analyze results using a mixed model analysis of variance (ANOVA) in combination with T ukey’s Honestly Significant Difference (HSD) multiple comparison tests to de termine if statistical

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8 differences between R e,T,a values exist. All R e,T,a calculations were conducted using environmental and physiological data over a range of heat stress c onditions at, near, or beyond critical conditions. The data were collected previously by C aravello et al. (2008) and Bernard et al. (2005) using a progressive heat stress protocol Empirically quantifying the relationship between R e,T,a using variables derived from different environmental conditions which promote stress on the thermoregulation proces s will advance heat stress research and help safety professionals in t he field advise employers regarding appropriate clothing for use in work settings. Research Question The following research question is addressed in this thesis: “Will estimates of R e,T,a for five different clothing ensembles remain the same independent of compensable, critical, and uncompensable heat stress levels?” Significance of Research This research is critically important to industry, first res ponders, and the military where heat stress hazards exist in the workplace. The first s tep towards the selection and implementation of controls to mitigate risks associated with expos ure to chemical, physical, or biological agents is a thorough risk assessment. Knowledge of the job risk factors linked to heat stress is necessary for the design and ex ecution of any effective company heat stress control program. Addressing one hazard may uninte ntionally create another, more substantial hazard. For example, procuring protective cl othing without

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9 consideration for its thermal properties may prevent scratches, spl inters, contact dermatitis, or burns but it may result in rapid heat stress for w earers depending on environmental conditions and workload. It is essential for company safe ty program managers to have some level of understanding of the construction and config uration characteristics of protective clothing. Although a great dea l is known relative to the roles of different clothing factors in thermal regulation, much is yet to be learned. This thesis seeks to uncover the relationship(s) between R e,T,a values and different environmental conditions, and expand current knowledge of thermal properties of protecti ve work clothing. Overview of Thesis Chapter 2 of this thesis contains a literature review regarding the estimates of clothing heat and vapor resistance, testing methods for computing esti mates, progressive heat stress protocol, and heat exchange processes in hot environments Following the literature review, Chapter 3 describes the methods used in the col lection, extraction, and analysis of data for this thesis. In Chapter 4, the data are ta bulated and graphically displayed. Chapter 5 presents statistically significant trends and compares thesis results with other published findings. Potential heat exchange pathways occur ring during human trials are evaluated and discussed, and conclusions are reported and sugge stions for future research offered.

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10 CHAPTER 2: LITERATURE REVIEW Estimates of Clothing Heat and Vapor Resistance Protective clothing is becoming more important in the workplace as employers become more aware of regulatory requirements and potential health ha zards present in work settings. Many different types of hazardous jobs exist which require clothing impermeable to water or vapor, or both. In some cases, multiple laye rs of clothing are necessary. Protective clothing meeting these requirements wil l likely increase the thickness or insulation of clothing while simultaneously reducing the e vaporation of sweat from the skin (Kenney et al. 1993). To protect workers, emplo yers must carefully choose the most suitable clothing ensemble given the environmental co nditions of the worksite, work demand, and thermal properties of clothing (Barker et al. 1999). Special consideration must be afforded to heat transfer properties of clot hing such as total insulation (I T ), water vapor permeability expressed using a moisture permeabil ity index (i m ), and total evaporative resistance (R e,T ), all which have been shown to influence the cooling capacity of the human body under heat stress conditions (Car avello et al. 2008; Barker et al. 1999; McLellan & Frim, 1994; Kenney et al. 1993). Clothing Insulation I T is a calculated value representing the ability of an ensemble to allow dry-heat exchange between the skin and the environment. I T incorporating both fabric and

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11 enclosed air pockets, is expressed in m 2o C W -1 and both static (I T,stat ) and resultant (I T,r ) values can be estimated. The American Society for Testing a nd Materials (ASTM) publishes criteria for determining I T,stat values for different clothing ensembles (ASTM, 2002) while the International Organization for Standardization (ISO) lists I T,stat values for a number of commonly used ensembles (ISO, 2007). A method for estimating I T,r recommended by the ISO is discussed later in this section. Clot hing insulation is also commonly expressed as total intrinsic clothing insulation (I clo ) or clo as used in some publications (ISO, 2004a). Higher I T values are characteristic of lower dry-heat exchange levels by convection and radiation (Barker et al. 1999). Research indicates that the presence of air pockets has a greater influence on heat stress than clothing fabric composition and is affected by the introduction of air into the garment from wind and fans or from body movements and changes in posture (Havenith & Nilss on, 2004; Havenith, 1999; Havenith et al. 1990). Nilsson, Anttonen, and Holmer (2000) obser ved that I T may be reduced by as much as 20-30% by walking. The insulative capacity of clothing material also diminishes as it becomes inundated with per spiration (Brode et al. 2008; Caravello et al. 2008; Havenith et al. 2008; Holmer & Nilsson, 1995; Ke nney et al. 1993). It is notable that significant changes in I T result in only minimal adjustments to R e,T estimated values (Barker et al. 1999; Bernard & Matheen, 1999). Water Vapor Permeability The ability of water vapor to travel through clothing fabric bet ween the skin and the environment is estimated by the dimensionless value, i m The moisture permeability index is calculated using the equation, i m = I T / 16.7 R e,T where 16.7 refers to the Lewis

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12 Number expressed as 16.7 o C kPa -1 (ISO, 2007; Woodcock, 1962). Both static (i m,stat ) and apparent (i m,a ) values may be calculated depending on the nature of I T and R e,T estimates used in the equation. Apparent i m values are greater than those estimated statically due to the “pumping effect” described by Havenith & Nilsson (2004) and Havenit h (1999). Using five different types of single-layered cotton woven fabric s and a constant ambient air temperature (T db ) of 23 o C, Hes & Araujo (2010) found that tight fitting, wet layered clothing increase water vapor permeability while loose-fitting dry layered clothing exhibited the lowest values. It can be demonstrated from the equation that lower R e,T values for a given clothing ensemble will lead to higher i m values and rates of evaporative cooling (Anna, 2003). The inverse relationship observed between R e,T and i m reveals the significance of clothing permeability and the movement of water vapor between the skin and the environment to heat exchange in hot environments. Evaporative Resistance Evaporation of sweat on the skin surface is the primary cooling me chanism employed by the body to maintain body core temperature in hot envir onments making R e,T of primary importance (Caravello et al. 2008; Havenith et al. 2008; Holmer, 2006; Holmer, 2006). R e,T values are calculated statically (R e,T,stat ) or dynamically (R e,T,a ) with higher values observed when estimated under static conditions (Carave llo et al. 2008). Clothing with higher porosity and smaller insulative pockets of air w ill generally yield lower R e,T estimates (Bernard et al. 2010; Gonzalez et al. 2006; Holmer, 2006) Havenith, Heus, and Lotens (1990) found that body movement and wind effects ca n reduce R e,T estimates by as much as 88%. Therefore, estimating R e,T under dynamic

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13 conditions not only quantifies the ability for clothing to support evaporati ve cooling but it does so under environmental conditions which most closely mimic real work settings (Caravello et al. 2008). Higher R e,T values imply higher levels of heat stress and vice versa (Barker et al. 1999). Testing Methods for Estimating Clothing Heat and Vapor Resistance Levine, Sawka, and Gonzalez (1998) outlines the four primary testing methods for estimating clothing heat and vapor resistance: (1) heated plat e; (2) heated copper manikin; (3) modeling; and, (4) human subjects. A description of each method follows. Heated Plate The heat transfer properties of single or multi-layered fabric samples can be determined using a temperature-controlled, heated (flat) plate c onfined inside an environmental chamber. Methods for measuring heat and vapor resi stance using the guarded hot plate are prescribed by the ISO (ISO, 1993). The heate d plate method attempts to simulate the heat exchange pathways between the ski n and the environment, and provides a relatively inexpensive and rapid means for testing a large number of fabrics. Unfortunately, the heated plate does not take into account t he effects of human sweat or air and body movements. Another shortfall of the heated pla te method is the heat transfer properties of fabric samples can change when integra ted into a clothing ensemble (Barker et al. 1999; Levine et al. 1998). Nevertheless, a number of textile studies have been performed using the heated plate or a similarl y designed apparatus to characterize the affects of temperature and humidity on differ ent fabrics, membranes, and

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14 laminates (Huang & Chen, 2011; Fukazawa et al. 2003; Gibson, 2000, 1999a; Gibson et al. 1999b; Barnes & Holcombe, 1996). Heated Copper Manikin The thermal properties of protective clothing ensembles can be i dentified using life-sized, thermal copper manikins. Procedures for using thermal manikins are outlined by the ASTM and ISO (ASTM, 2005; ISO, 2004c). Mannequins are computer-cont rolled and positioned inside temperature regulated environmental chambers in o rder to monitor, measure, and control for different environmental and physiological con ditions. Most manikins are covered completely with form-fitting cotton to simula te human skin which can be wetted with distilled water to account for human sweat. M ore advanced manikins can simulate limited body movement and may have 30 or more zones on the surface of the manikins to manipulate and/or record “skin” surface temperature s (Bouskill et al. 2002; Havenith et al. 2008). High costs and logistical issues associa ted with technically advanced manikins results in most data being collected using stationa ry manikins in nonsweating conditions (Bouskill et al. 2002). Using copper manikins per mits the collection of temperature-controlled data for different ensembles, accounting for whole clothing ensembles, clothing configuration, sweat, and, in rare cases, partial body movements. A major limitation of manikins is they do not account, in most cases, f or increases in convective heat exchange produced by body movements and air “pumping” in a nd out of insulative air pockets located between the wearer and outer layer of clothing. Nevertheless, they permit researchers to study the thermal properties of clothing using

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15 extreme temperatures beyond those permitted using human subjects (B arker et al. 1999; Levine et al. 1998). Modeling Although modeling does not, by itself, generate data regarding t hermal stress it is worth mentioning because it is becoming a popular method for predicting physiological responses to different clothing ensembles and combinations of environmenta l and metabolic conditions (Levine et al. 1998). Additionally, researchers are using computer modeling in an attempt to improve scientific understanding of microc limates. Data generated from heated copper manikins or human trials are entere d into different types of computer modeling software and desired outputs are calculated automat ically. Ghaddar, Ghali, and Jones (2003) offer a thorough review of a variety of computer models used in heat stress investigations. Wang et al. (2011) recently evaluate d the predicted heat strain (PHS) model (ISO 7933) using six human subjects, three ensembles ( clothing thermal insulation between 0.63 and 2.01 clo), and two environmental conditions. Rectal and skin temperatures predicted by the PHS model using set climati c conditions were compared to data generated from human trials under the same environme ntal conditions. The PHS Model failed to predict accurately the skin temperat ures for all three ensembles. In spite of this, the model’s prediction of rectal temperatures was within 1 standard deviation (SD) of observed rectal temperatures for two of three e nsembles. The predicted versus observed rectal temperature for the third ensemble (2.01 clo) was 3.75 SD greater than the subject average mean SD. Wang et al. (2011) suggested that revisions to the PHS model were needed to account for protective clothing with high cl othing insulation

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16 estimates. Limitations to the study included a small sample s ize, use of clothing ensembles beyond the validation range of the PHS model (<0.6 clo), an d a potentially inaccurate instrument for measuring metabolic rate (Wang et al. 2011). Human Subjects Human laboratory research provides the best approximation of workplac e conditions because it accounts for all of the parameters captured usi ng manikins, in addition to air and body movements. All human subject research requires approval from institutional review boards and volunteer consent forms. Healthy voluntee rs are selected, medically screened, and acclimatized prior to the initiation of e xperiment trials. Acclimatization and experiment trials are conducted inside a cl imate-controlled chamber under varying environmental conditions. Vital signs, body-core temper ature, among other physiological and environmental data, are closely monitored duri ng the trial to protect human subjects and for the collection of thermoregulatory data. Disadvantages of using human subjects in heat stress trials are costs, time, medi cal screening requirements, ethical considerations, and variability among human subjects (Barker et al. 1999; Levine et al. 1998). Progressive Heat Stress Protocol The progressive heat stress protocol is a method first developed by Belding and Kamon (1973), refined by Kenney et al. (1993), and continued by Caravel lo et al. (2008) to identify the critical condition where the threshold of thermoregul atory balance exists. A thermal load is slowly imposed on a person by means of gra dual increases in air

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17 temperature or water vapor pressure eliciting physiological respons es to maintain homeostasis. Climatic changes are made every five minutes permi tting the body to arrive at a temporary thermal equilibrium at each step. Further increa ses in temperature, moisture, or both, eventually cause the body to reach a maximum limit where heat gain equals heat loss. The moment at which the critical condition is ac hieved is dependent on several factors, including differences among individuals, clothing ense mbles, workload, and environmental conditions. The protocol enables R e,T,a values to be estimated without having to weigh subjects or measure directly the water vapor pre ssure of skin (Kenney et al. 1993). Furthermore, estimated R e,T,a values take into account air and body movements and sweat (Caravello et al. 2008). Heat Exchange in Hot Environments There are several important heat exchange pathways that can b e used to describe heat loss or gain in hot environments. Normal heat exchange processes between the skin and environment can be modified when one or more layers of clothing ar e introduced. Clothing acts as a barrier to heat exchange preventing the introduct ion of cooler air into the ensemble or the escape of water vapor transporting heat to the environment. Potential outcomes are the development of microclimates inside a clothing ens emble and a shift in the manner with which heat exchange is accomplished. A discussion of microclimates and heat exchange pathways encountered in hot environments where clothing e nsembles are worn is presented.

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18 Microclimates and Microclimate Effects Microclimates are produced in small pockets of air between skin and clothing layers and are characterized by extreme temperature and mois ture gradients compared to ambient environmental conditions (Holmer, 2006). The significance of mi croclimates cannot be overemphasized as they impact the physiological responses of people wearing clothing in heat stress conditions. Clothing construction (thermal prope rties) and configuration largely determine the nature and magnitude of microcl imates (Holmer, 2006). For example, a vapor-barrier ensemble with no openings to the en vironment can generate microclimates characterized by 100% relative humidi ty, where the saturation pressure of water in the environment (P a ) exceeds the water vapor pressure at the skin (P sk ). Heat exchange is reversed in P a > P sk warm, humid conditions as the body receives heat from the environment, consequently exacerbating the physiologica l effects of heat stress. The same can be said when microclimates are produced ge nerating extreme hot, dry conditions where the T db is greater than skin temperatures (T sk ) (Bouskill et al. 2002). What is different between the warm, humid and hot, dry conditions are the heat exchange processes involved (Havenith et al. 2008). Also important in the thermoregulation of microclimates is air movement inside the clothing ensemble. Air from the environment can gain access int o the ensemble by (1) permeation through the garment material, (2) unabated convective ai r movement into openings, and (3) forced penetration caused by wind, fans, and body move ments (Bouskill et al. 2002). First described by Birnbaum and Crockford (1978) and further examined by Bouskill et al. (2002) is the Ventilation Index (V T ) which is used to quantify the air exchange properties of clothing. Bouskill et al. (2002) used a m anikin enclosed in

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19 a controlled environmental chamber (T db = 10 o C and P a = 0.73 kPa) under static and dynamic (moving) conditions to demonstrate that increases in V T produced by different walking speeds and air speeds reduced I clo of two ensembles. As anticipated, greater effects were observed in the single layer ensemble versus the triple layer ensemble. A final feature of microclimates relevant to heat exchange is the average air layer thickness between human skin and clothing. Several techniques are used to estima te trapped volume including 3D whole-body scanning, use of a thin airtight suit ove r the garments, and modeling. Daanen, Hatcher, and Havenith (2005) investigated all thr ee techniques on human subjects wearing only bicycle shorts, bicycle shorts with Tshirt, and a coverall. It was determined that the microclimate volume for the coveralls was more than double that of the other two ensembles. Further, the 3D scanning method pr oved to supply the most accurate estimates of microclimate volumes. Heat Exchange Pathways Clothing interferes with heat transfer between the skin to the environment by limiting (1) dry-heat exchange or (2) evaporative-heat exchange. D ry-heat exchange is comprised of conduction, radiation, and convection while evaporative-heat exc hange involves the evaporation of sweat at the skin surface directly into t he environment or into a microclimate when clothing is worn. In hot environments, evaporative -heat exchange serves as the primary mechanism in maintaining thermal equilibr ium. Havenith et al. (2008) emphasizes the “microclimate heat pipe” in hot environments when the skin is we t and clothing is worn. The microclimate heat pipe is an evaporat ion/condensation cycle triggered by the evaporation and subsequent condensation of sweat on the ins ide of the

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20 outer clothing layer. The evaporation process transports heat at the surface of the skin into the microclimate where it is transferred to the clothing l ayer upon condensation. The heat contained in the inner layer of the wet clothing is delivered to the outer layer of clothing where it is removed by dry-heat exchange processes. Th e microclimate evaporation/condensation cycle is influenced by temperature effec ts, evaporative heat loss rate, and the water and vapor permeability of the clothing being worn. Havenith et al. (2008) also describes a process of wet conduction that takes plac e when clothing layers become saturated with sweat. Clothing saturation can oc cur either through the condensation of sweat via the heat pipe or by making direct contact w ith wet skin and soaking up excess perspiration (a process also known as wicking ). Only dry-heat exchange processes are present when the skin is dry. Dry heat loss is enhanced with increasing differences between T sk and T a At lower temperatures and when the skin is wet, both dryand evaporative-heat exchange processe s occur simultaneously, albeit not as similar rates. At higher temper atures where T a equals T sk (generally at 34 o C or greater) dry-heat exchange is largely inhibited leaving evaporativeheat exchange as the only mechanism for cooling the body. The a bsence of dry-heat exchange is significant because it does not permit the removal of he at from clothing as required by a fully functional microclimate heat pipe. As P a approaches P sk evaporativeheat exchange becomes moderated, ceasing altogether when P a = P sk (Havenith et al. 2008; Bouskill et al. 2002; Barker, 1999). Equations (1) and (2) demonstrate the relevance of different heat exchange pathways in the estimation of R e,T,a values using the progressive heat stress protocol (Caravello et al. 2008; Kenney et al. 1993; Belding & Kamon, 1973):

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21 (P sk – P a ) / R e,T,a = H net + (T db – T sk ) / I T,r Equation (1) H net = M – W ext – S + C res – E res Equation (2) According to equation (1), the critical condition represents the max imum heat loss attributed to evaporative cooling balanced by the net heat gain from internal sources and dry-heat exchange. Evaporative cooling is equivalent to the differ ence between P sk and P a divided by the estimated R e,T,a Net heat gain (H net ) is comprised of the sum of metabolic rate (M) and respiratory exchange rate by convection (C res ) less external work (W ext ), storage rate (S), and respiratory exchange rate by evaporation (E res ). Equations for estimating M, W ext S, C res and E res are discussed in Chapter 3. Heat stress trials are normally conducted in non-radiant environments permitting dry-heat excha nge to be estimated using the difference in T db and T sk divided by I T,r (Caravello et al. 2008; Kenney et al. 1993; Belding & Kamon, 1973). Equation (1) is only valid for estimating R e,T,a at the critical conditions of the progressive protocol due to the reliance on heat balance. The method for e stimating R e,T,a is dependent on estimates of I T,r a prerequisite founded on the assumption established by Kenney et al. (1993) that clothing insulation and evaporative resistanc e are constant in warm, humid and hot, dry conditions. Bernard et al. (2010), Caravello et al. (2008), and Barker et al. (1999), collectively known as the University of South F lorida (USF) Group, adopted this approach contending that the influence of clothing insul ation on evaporative resistance is negligible (Bernard et al. 2010). Building on the wor k of the USF Group,

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22 the present research investigates whether R e,T,a will remain the same independent of environmental climatic conditions over a range of heat stress levels.

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23 CHAPTER 3: METHODOLOGY Overview Environmental and physiological data collected by Caravello et a l. (2008) and Bernard et al. (2005) using a progressive heat stress protocol were extracted to estimate empirically the apparent total evaporative resistance (R e,T,a ) of five clothing ensembles at a moderate metabolic rate and three levels of relative humidity (RH). A detailed methodology for data collection, extraction, and analysis is provided. Participants Fourteen adults (nine men and five women) participated in experim ental trials. The average and standard deviation of their physical characteris tics by gender are provided in Table 3.1. The study protocol was approved by the University o f South Florida Institutional Review Board. A written informed consent wa s obtained prior to enrollment in the study. Each participant was examined by a phys ician and approved for participation. The participants were healthy with no chronic diseas e requiring medication. While smoking status was not an exclusionary factor, mos t were nonsmokers. Participants were reminded of the need to maintain good hydration. On the day of the trial, they were asked not to drink caffeinated beverages 3 hours before the appointment and not to participate in vigorous exercise before the t rial. Prior to

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24 beginning the experimental trials to determine critical conditi ons, participants underwent a 5-day acclimatization to dry heat that involved walking on a trea dmill at a metabolic rate of approximately 165 W m -2 in a climatic chamber at 50 o C and 20% RH for 2 hours. Participants wore a base ensemble of shorts, tee-shirt (and/or spo rts bra for women), socks, and shoes. Table 3.1. Physical Characteristics of Participants (Mean Standar d Deviation) Age (Years) Height (cm) Weight (kg) Body Surface Area (m 2 ) Women (n = 5) 32 9 161 7 63.4 17.3 1.66 0.23 Men (n = 9) 29 7 183 5 97.4 18.4 2.18 0.20 Both (n = 14) 30 7 175 12 85.3 24.2 1.99 0.33 Clothing Five different clothing ensembles were evaluated. The ensemble s included work clothes (135 g m -2 cotton shirt and 270 g m -2 cotton pants), cotton coveralls (305 g m -2 ), and three limited-use protective clothing ensembles including a pa rticle-barrier ensemble, Tyvek 1424, water-barrier, vapor-permeable ensemble (NexGen LS 417), and a vaporbarrier ensemble (Tychem QC polyethylene-coated Tyvek ). The limited-use coveralls had a zippered closure in the front and elastic cuffs at the arms and legs. None of the ensembles included a hood. The base ensemble was worn under all clothing ensembles. Equipment The trials were conducted in a controlled climatic chamber. Tem perature and humidity were controlled according to protocol and air speed was 0.5 m s -1 Heart rate

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25 was monitored using a chest strap heart rate monitor. Core temper ature (T re ) was measured with a flexible thermistor inserted 10 cm beyond the anal sphincter muscle. The thermistor was calibrated prior to each trial using a hot water bath. The work demand consisted of walking on a motorized treadmill at a speed and grade set to elicit a target metabolic rate of 165 W m -2 Measurement of oxygen consumption was used to assess metabolic rate. Participants brea thed through a two-way valve connected to flexible tubing that was connected to a collection bag. Expired gases were collected for about 2.5 min. The volume of expired air was mea sured using a dry gas meter. An oxygen analyzer was used to determine oxygen conte nt of air. A metabolic rate was recorded for each trial which was the ave rage of three samples of oxygen consumption taken at approximately 30, 60, and 90 minutes into a tria l and expressed as the rate normalized to body surface area. Protocols Each ensemble was worn by each participant performing exerci se at a moderate rate of exertion. The order of ensembles was randomized. Any trial that had to be repeated was repeated at the end of the schedule. Most participa nts completed one trial per day, but some completed two trials per day with at least 3 hours of recovery between trials. The study design called for three environments: warm humid at 70% RH (R7); hot, dry at 20% RH (R2); and a midrange 50% RH (R5). For the R7 pr otocol, the dry bulb temperature (T db ) was set at 30 o C and RH at 70%. Once the participant reached thermal equilibrium (no change in T re and heart rate for at least 15 minutes), T db was increased 0.7 o C every 5 minutes. In the R2 protocol, T db was set at 40 o C with RH at

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26 20%. When participants reach thermal equilibrium, T db was increased 1 o C every 5 minutes. For the R5 protocol, T db was set at 34 o C with 50% RH. On reaching thermal equilibrium, T db was increased 0.8 o C every 5 minutes. During the trials, participants were allowed to drink water or a commercial fluid replacement be verage (Gatorade ) at will. Core temperature, heart rate, and ambient conditions (dry bulb, psychr ometric wet bulb, and globe temperatures; T db T pwb and T g respectively) were monitored continuously and recorded every 5 minutes. Trials were scheduled to l ast 120 minutes unless one of the following criteria was met: (1) a clear ris e in T re associated with a loss of thermal equilibrium (typically 0.1 o C increase per 5 minutes for 15 minutes); (2) T re reached 39 o C; (3) a sustained heart rate greater than 90% of the age-predi cted maximum heart rate; or (4) participant wished to stop. Inflection Point and Determination of Critical Conditions The inflection point marked the transition from thermal balance t o the loss of thermal balance, where body core temperature continued to rise as shown in Figure 3.1 for one trial. The chamber conditions existing at the time of 5 minutes before the observed increase in core temperature was defined as the crit ical condition. One investigator noted the critical condition and some of the decisions w ere randomly reviewed by a second investigator.

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27 Modified from Caravello et al. (2008) Figure 3.1. Time Course of Rectal Temperature for One Trial Data Extraction The progressive heat stress protocol permitted the collection of data at, near, or beyond the critical condition for each participant. Environmental and phy siological data were extracted at three different stages of heat stress ( compensable, transition, and uncompensable; C, T, and U, respectively). The stages included: (1) 20 minutes before the critical condition (C); (2) at the critical condition (T); and (3) 15 minutes beyond the critical condition (U). Theoretically, 630 rows of data were anti cipated based on 14 participants, five ensembles, three RHs, three stages of heat s tress, and a constant metabolic rate. However, 663 rows of data were extracted as 11 r epeated trials were conducted. Each row incorporated 28 columns of data producing a total of 18,564 cell 36.5 37.0 37.5 38.0 38.5 0306090120T re ( C)Time (min) Critical Condition Compensable Uncompensable

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28 blocks containing data. Data extraction was performed by two investi gators and all data were entered into Microsoft ™ Excel 2007. A third investigator performed a random verification of 25% of the database following data extraction indenti fying 11 errors (0.24%). Error percentage was calculated by multiplying 166 (25% of the rows) by 28 (number of columns in each row) and dividing the product into 11 (number of erro rs). The resultant value was multiplied by 100 yielding 0.24% error. All i dentified errors were corrected prior to computing R e,T,a values. Calculation of Clothing Parameters Environmental and physiological data for each of the 663 combinations wer e used to estimate R e,T,a values. The following is the process to calculate derived values for each trial based on trial conditions for the participant and environment. Referring to Kenney et al. (1993), metabolic rate (M), externa l work (W ext ), storage rate (S), and respiratory exchange rate by convection (C res ) and evaporation (E res ) presented in equation (2) were estimated as follows. M in W m -2 was estimated from oxygen consumption (V O2 ) in liters per minute: M = 350 V O2 / A D Equation (3) The Dubois surface area (A D ) was calculated for each subject as A D = 0.202m b 0.425 H 0.725 where m b was the mass of the body (kg) and H was the height (m). W ext was calculated (W m -2 ) in the following manner:

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29 W ext = 0.163m b V W f g / A D Equation (4) V W was the walking velocity in m min -1 while f g was the fractional grade of the treadmill (%). Values for C res (W m -2 ) and E res (W m -2 ) were calculated using equations provided in ISO 7933 (2004a). The estimation of C res required that expired air temperature (T exp ) be calculated using T db and P a : T exp = 28.56 + (0.115 T db ) + (0.641 P a ) Equation (5) C res = 0.001516 M (T exp – T db ) Equation (6) E res = 0.00127 M (59.34 + 0.53 T db – 11.63 P a ) Equation (7) Kenney et al. (1993) recognized that there may be some heat stora ge represented by a gradual change in T re To account for this, the rate of change in heat storage can be estimated knowing the specific heat of the body (0.97 W h o C -1 kg -1 ), m b and the rate of change of body temperature ( T re t -1 ) as an average over the 20 minute period preceding the inflection point. This approach was taken by Barker et al. (1999) with some changes in sign conventions: S = 0.97m b T re A D -1 t -1 Equation (8)

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30 Total static clothing insulation (I T,stat ) values were determined according to ASTM F 1291, Standard Test Method for Measuring the Thermal Insulation of Clothing using a Heated Manikin using a fixed environment and adjusting the heat input to achieve thermal equilibrium (ASTM, 2002). In the current study, these values were treated as a fixed value for all ensembles. The total dynamic clothing insulation (I T,r ) was estimated according to ISO 9920 (2007) (Equation 32) in two stages. First, the correction factor for insulation (CFI) was calculated according to Havenith and Nilsson (2004) (Equation 4) and I SO 9920 (2007) where v is air speed (0.5 m s -1 ) and w refers to walking speed or speed of the treadmill (m s -1 ) for each wear trial. This adjustment for air and body movement was similar to that proposed by Holmer et al. (1999). The equation to estimate the CFI is as follows: CFI = exp[-0.281(v – 0.15) + 0.044(v – 0.15) 2 – 0.492w + 0.176w 2 ] Equation (9) Second, I T,stat and CFI values were multiplied by 0.9 (reduced by 10%) finaliz ing the estimated I T,r to account for the reduction in insulation due to wetting (Brode et al. 2008): I T,r = CFI I T,stat 0.9 Equation (10) R e,T,a values were calculated by rearranging equation (1). R e,T,a = (P sk – P a ) / [H net + (T db – T sk ) / I T,r ] Equation (11)

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31 Each I T,r value was inserted into equation (11) along with other applicable environmental and physiological data for each combination to estima te the R e,T,a The process was repeated yielding 663 R e,T,a values in all. Statistical Analysis JMP (version 7.1) statistical software (SAS, Cary, North Carolina) was used to analyze data. A mixed model analysis of variance (ANOVA) in combination with Tukey’s Honestly Significant Difference (HSD) multiple compari son tests were used to determine where the main differences occurred. To analyze the relationships among ensembles, RH levels, and heat stress stages, a four-way ANOVA was performed in which those factors were fixed effects and the participants wer e maintained as a random effect. Also evaluated were three interactions between ensem bles-RH levels, ensemblesheat stress stages, and RH levels-heat stress stages. The depe ndent variable for the statistical test was R e,T,a and significance was established at = 0.05.

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32 CHAPTER 4: RESULTS Overview A four-way mixed model analysis of variance (ANOVA) was used to test for three fixed main effects and three second order interactions. T he main effects were ensemble, relative humidity (RH), and stage of heat stress. Pa rticipants were treated as a random effect. The analysis of the data demonstrated significant differences for estimated R e,T,a values among ensembles, RH levels, heat stress stages, and inter actions among ensembles and RH levels and ensembles and heat stress stage s (p < 0.0001). No significant interaction among RH levels and heat stress stag es was found (p = 0.67). A Tukey’s Honestly Significant Difference (HSD) multiple compa rison test was used to identify where significant differences occurred (p < 0.05). Main Effects A Tukey’s HSD multiple comparison test was used to identify diff erences among ensembles. Referring to Table 4.1, there were no significant differences among work clothes, cotton coveralls, and Tyvek 1424. Significant differences (p < 0.05) were detected between NexGen LS 417 and Tychem QC and among these two ensembles and work clothes, cotton coveralls, and Tyvek 1424. The highest R e,T,a values were observed for the vapor-barrier ensemble followed by the water-bar rier, vapor-permeable ensemble, particle-barrier ensemble, cotton coveralls (CC), and work clothes (WC).

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33 Table 4.1. Least Squares Mean of Apparent Total Evaporative Resistanc e (m 2 kPa/W) for Five Ensembles Ensembles Evaporative Resistance Statistical Difference WC 0.014 A CC 0.015 A Tyvek 0.016 A Nexgen 0.019 B Tychem 0.034 C *Similar letters denote no significant differences (p < 0.05) Tukey’s HSD test demonstrated significant differences (p < 0.0 5) for each RH level. Estimated R e,T,a values were highest at 20% RH and lowest at 70% RH as demonstrated by Table 4.2. Table 4.2. Least Squares Mean of Apparent Total Evaporative Resistanc e (m 2 kPa/W) for Three Relative Humidity Levels RH (%) Evaporative Resistance Statistical Difference 20 0.023 A 50 0.018 B 70 0.017 C *Similar letters denote no significant differences (p < 0.05) Every stage of heat stress was determined to be significant ly different (p < 0.05) based on Tukey’s HSD test. The compensable heat stress stage was characterized with the highest estimated R e,T,a values, while the lowest values were observed under uncompensable heat stress conditions as shown in Table 4.3.

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34 Table 4.3. Least Squares Mean of Apparent Total Evaporative Resistanc e (m 2 kPa/W) for Three Heat Stress Stages Heat Stress Stage Evaporative Resistance Statistical Difference Compensable 0.024 A Transition 0.019 B Uncompensable 0.016 C *Similar letters denote no significant differences (p < 0.05) Interactions The estimated R e,T,a values for each clothing ensemble at different RH levels are shown in Table 4.4, and R e,T,a values for every ensemble at 20, 50, and 70% RH are illustrated in Figure 4.1. The results from Tukey’s HSD test revealed that R e,T,a values for the Tychem QC ensemble were statistically different (p < 0.05) from R e,T,a estimates for all other ensembles at different RH levels. The NexGen LS 417 ensemble at 20% RH was statistically different from all other ensembles except Tyvek 1424 at 20% RH. See also Appendix E for other statistical differences for interactions. Table 4.4. Least Squares Mean of Apparent Total Evaporative Resistanc e (m 2 kPa/W) for Five Ensembles at Three Relative Humidity Levels Relative Humidity Levels 20% 50% 70% Ensembles WC 0.016 0.013 0.013 CC 0.017 0.013 0.014 Tyvek 0.019 0.015 0.014 Nexgen 0.022 0.018 0.017 Tychem 0.043 0.033 0.026

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35 Figure 4.1. Least Squares Mean of Apparent Total Evaporative Resist ance for Five Ensembles at Three Relative Humidity Levels What was apparent from Figure 4.1 was the magnitude of difference s in R e,T,a values of the Tychem QC ensemble from those of all other ensembles, particularly at 20% RH. The Tychem QC ensemble appeared to be the most sensitive to changes in RH. There were greater differences among R e,T,a values at 20% RH where higher R e,T,a values existed for all ensembles compared to 70% RH where all ensembles expressed the lowest estimates. R e,T,a values for the WC, CC, and Tyvek 1424 were grouped in the same way at each RH level. Estimated R e,T,a values for the NexGen LS 417 ensemble were elevated slightly above R e,T,a values for WC, CC, and Tyvek 1424 but maintained a similar pattern at each RH level. R e,T,a values for the Tychem QC ensemble did not mirror the pattern of any of the ensembles. 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040 0.045 0.050 205070Apparent Total Evaporative Resistance (m 2 kPa/W)Relative Humidity Level (%) WC CC Tyvek NexGen Tychem

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36 The estimated R e,T,a values for every clothing ensemble at different heat stress stages were compiled in Table 4.5, and the R e,T,a values for each ensemble at compensable, transition, and uncompensable conditions were graphed in Figure 4.2. Table 4.5. Least Squares Mean of Apparent Total Evaporative Resista nce (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages Heat Stress Stages Compensable Transition Uncompensable Ensembles WC 0.017 0.014 0.012 CC 0.018 0.014 0.012 Tyvek 0.019 0.016 0.013 Nexgen 0.024 0.018 0.015 Tychem 0.042 0.033 0.027 C = Compensable, T = Transition, U = Uncompensable Figure 4.2. Least Squares Mean of Apparent Total Evaporative Resist ance for Five Ensembles at Three Heat Stress Stages 0.000 0.005 0.010 0.015 0.020 0.025 0.030 0.035 0.040 0.045 CTUApparent Total Evaporative Resistance (m 2 kPa/W)Stage of Heat Stress WC CC Tyvek NexGen Tychem

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37 R e,T,a values for Tychem QC and NexGen LS 417 decreased more rapidly from compensable to uncompensable stages of heat stress than the other thre e clothing ensembles. Figure 4.2 displayed a similar pattern seen in Figur e 4.1 where the greatest differences among R e,T,a values were observed under compensable heat stress conditions, which was characterized with the highest R e,T,a values for all ensembles. The patterns demonstrated by estimated R e,T,a values for each ensemble indicated that the Tychem QC ensemble was most sensitive to different stages of heat stress, followed b y NexGen LS 417 and Tyvek 1424. WC and CC ensembles maintained a similar pattern along t he stages of heat stress which was reinforced by the fact t hat there were no significant differences between R e,T,a values for each ensemble at the same RH level. Similar estimated R e,T,a values among RH levels and heat stress stages yielded no significant differences (p = 0.05) from Tukey’s HSD test. Temperature and Vapor Pressure Gradients The changes observed in R e,T,a values for RH and heat stress stages might be explained by changes in temperature and water vapor pressure. Ave rage temperature differences were calculated by averaging the differences of skin temperatures (T sk ) from ambient air temperatures (T db ). Average temperature differences (T db – T sk ) can be indicative of the direction and magnitude of dry-heat exchange. Ave rage vapor pressure differences were estimated by averaging the differences of a mbient water vapor pressures (P a ) from skin (P sk ). Average vapor pressure differences (P sk – P a ) provided information regarding the magnitude of evaporative-heat exchange.

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38 The average temperature differences for different clothing ense mbles at three RH levels were graphed in Figure 4.3, and the average temperature diff erences for different clothing ensembles at three stages of heat stress were illustrated i n Figure 4.4. Figure 4.3. Average Temperature Differences for Five Ensembles at Three Relative Humidity Levels As expected, greater temperature differences were observed at 20% RH with lowest differences occurring at 70% RH. For three ensembles t here was a greater dryheat loss at 20% RH (117 W m -2 ) than at 70% RH (12 W m -2 ). The NexGen LS 417 ensemble was not much different. Only the Tychem QC ensemble exhibited negative average temperature differences (T sk > T db ) resulting in dry-heat losses of -22 W m -2 at 20% RH and -35 W m -2 at 70% RH. Additionally, the Tychem QC ensemble did not -6.0 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 14.0 16.0 205070Average Temperature Difference ( o C)Relative Humidity Level (%) WC CC Tyvek NexGen Tychem

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39 follow the pattern observed with other ensembles as less than 2 o C of difference existed between temperature gradients at 20 and 70% RH levels. Figure 4.4. Average Temperature Differences for Five Ensembles at Three Heat Stress Stages Similar average temperature differences for WC and CC ensem bles prohibited the line-plot for the WC ensemble from being detected in Figure 4.4. Agai n, as expected, greater average temperature differences were associated with the uncompensable stage of heat stress among all clothing ensembles. For three ensembles there was a greater dryheat loss under uncompensable conditions (83 W m -2 ) than under compensable conditions (35 W m -2 ). The NexGen LS 417 ensemble was slightly different experiencing a dryheat loss of 61 W m -2 and 10 W m -2 under uncompensable and compensable conditions, respectively. Only the Tychem QC ensemble exhibited negative average temperature -8.0 -6.0 -4.0 -2.0 0.0 2.0 4.0 6.0 8.0 10.0 12.0 CTUAverage Temperature Difference ( o C)Heat Stress Stages WC CC Tyvek NexGen Tychem

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40 differences (T sk > T db ) leading to a dry-heat loss of -6 W m -2 and -54 W m -2 under uncompensable and compensable conditions, respectively. Every ensemble fol lowed a relatively consistent pattern among RH levels. The average pressure differences for different clothing ensembl es at three RH levels were illustrated in Figure 4.5, while the average pressure differences for different clothing ensembles at three heat stress stages were displayed in Figur e 4.6. Figure 4.5. Average Vapor Pressure Differences for Five Ensemble s at Three Relative Humidity Levels Greater average vapor pressure differences were observed at 20% RH with lowest differences occurring at 70% RH. The greatest pressure gradi ents were associated with the Tychem QC ensemble at all RH levels. 0.0 1.0 2.0 3.0 4.0 5.0 6.0 205070Average Vapor Pressure Difference (kPa)Relative Humidity Level (%) WC CC Tyvek NexGen Tychem

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41 C = Compensable, T = Transition, U = Uncompensable Figure 4.6. Average Vapor Pressure Differences for Five Ensemble s at Three Heat Stress Stages Similar vapor pressure differences for WC and CC ensembles prohi bited the visibility of the WC ensemble line-plot in Figure 4.6. All clothing ensembles with the exception of Tychem QC experienced slight decreases in average vapor pressure differences (0.3-0.4 kPa) from compensable to uncompensable heat stress stages. The average vapor pressure of the Tychem QC ensemble remained fairly stable over heat stress stages with a small increase under the transitional heat stres s condition. 0.0 0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 CTUAverage Vapor Pressure Difference (kPa)Heat Stress Stages WC CC Tyvek NexGen Tychem

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42 CHAPTER 5: DISCUSSION Analysis of Results Differences among ensembles were anticipated based on the re sults published by Caravello et al. (2008). Caravello et al. (2008) reviewed the sa me ensembles used in this study but only at 50% relative humidity (RH) and at critical condit ions. The apparent total evaporative resistance (R e,T,a ) values recorded by Caravello et al. (2008) at 50% RH were 0.013 m 2 kPa W -1 for work clothes (WC), 0.013 m 2 kPa W -1 for cotton coveralls (CC), 0.015 m 2 kPa W -1 for Tyvek 1424, 0.018 m 2 kPa W -1 for NexGen LS 417, and 0.032 m 2 kPa W -1 for Tychem QC The R e,T,a values presented in Table 4.1, while including the effects of the three RH levels and stages of he at stress, were virtually the same. The R e,T,a values reported by Bernard et al. (2010), Barker et al. (1999), and Kenney et al. (1993) for WC were 0.014 m 2 kPa W -1 0.013 m 2 kPa W -1 and 0.016 m 2 kPa W -1 respectively, and were comparable to the R e,T,a value of 0.014 m 2 kPa W -1 calculated for WC in this study. The reported R e,T,a value of 0.016 m 2 kPa W -1 for Tyvek 1424 in this study was also close to the R e,T,a value of 0.017 m 2 kPa W -1 documented at 50% RH by Barker et al (1999). The R e,T,a value of 0.019 m 2 kPa W -1 obtained in this study for NexGen LS 417 was inside the range of R e,T,a values 0.014 m 2 kPa W -1 to 0.026 m 2 kPa W -1 reported by Barker et al. (1999) at 50% RH for microporous barriers The three garments used by Barker et al. (1999) were constructed similar ly but had different films

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43 and included integral hoods. Because no hoods were used in this study, differences among R e,T,a values may have been due to the use of hoods. It was, however, more li kely that the different films modified the thermal properties of the e nsembles. The only comparable ensemble to the Tychem QC ensemble in the literature was a two-piece ensemble over military fatigues used by Kenney et al. (1993). He reported a R e,T,a value of 0.038 m 2 kPa W -1 for the ensemble which is higher than 0.034 m 2 kPa W -1 estimated in this study. Statistical differences among RH levels, heat stress stages, and i nteractions among ensembles and RH levels and ensembles and heat stress stages we re not anticipated. In order to gain insight into the differences observed among R e,T,a values for RH levels, heat stress stages, and interactions among ensembles and RH levels and ensembles and heat stress stages, the relationship between temperature and vapor press ure gradients was explored and evaluated. For this work, equation (11) from Chapter 3 used to calculate R e,T,a values was revisited. R e,T,a = (P sk – P a ) / [H net + (T db – T sk ) / I T,r ] Equation (11) As mentioned previously, water vapor pressure gradients were repres ented by the differences between skin vapor pressure and ambient air vapor pressure (P sk – P a ), and differences between ambient air temperature and skin temperatur e (T db – T sk ) denoted temperature gradients. Net heat gain (H net ) and total resultant insulation (I T,r ) remain about the same for each trial and among each ensemble demonstr ating that the only variables in equation (11) which can vary are differences in vapor pres sure and

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44 temperature. Dry-heat loss (DH) is characterized by (T db – T sk ) / I T,r and is influenced significantly by changes in temperature gradients. Decrease s in temperature gradients or increases in vapor pressure gradients led to higher R e,T,a values. In order to explain study results, each component comprising equation (11) was tabulated for two clothing ensembles at different RH intervals ( Table 5.1) and heat stress stages (Table 5.2). WC was one of two ensembles chosen because it represented a baseline ensemble used frequently in industry while the Tychem Q C ensemble was different from all other ensembles under every environmental condition. Table 5.1. Apparent Total Evaporative Resistance Values, Temperat ure and Pressure Gradients, and Net Heat Gain Plus Dry-Heat Loss Values for T wo Ensembles at Three Relative Humidity Levels Ensembles WC Tychem RH Levels 20% 50% 70% 20% 50% 70% R e,T,a (m 2 kPa/W) 0.016 0.013 0.013 0.043 0.033 0.026 P (kPa) 4.2 2.5 2.0 5.0 3.7 2.9 T ( o C) 14.0 5.4 1.5 -2.3 -3.4 -3.7 H net (W m -1 ) 133 142 151 149 151 158 DH (W m -1 ) 132 52 14 -21 -31 -34 H net + DH (W m -1 ) 265 194 165 128 120 124 DH = (T db – T sk ) / I T,r The relationships among R e,T,a values, vapor pressure gradients, and H net plus DH for WC and Tychem QC ensembles at three different RH levels were illustrated in Figure 5.1.

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45 Figure 5.1. Least Squares Mean of Apparent Total Evaporative Resis tances (A), Average Pressure Differences (B), and Net Heat Gain Plus Dry-Hea t Loss (C) for Two Ensembles at Three Relative Humidity Levels 0.000 0.010 0.020 0.030 0.040 0.050 205070Apparent Total Evaporative Resistance (m 2 kPa/W)Relative Humidity Level (%) WC Tychem 0 1 2 3 4 5 6 205070 P (kPa) Relative Humidity Level (%) WC Tychem 0 50 100 150 200 250 300 205070H net + Dry Heat Loss (W/m 2 ) Relative Humidity Level (%) WC Tychem A B C

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46 The changes among data in Table 5.1 progressed in the same dire ction. R e,T,a values and vapor pressure gradients were greatest at 20% RH and low est at 70% RH. For WC, higher temperature gradients were observed at 20% RH with the lowest values recorded at 70% RH. Temperature gradients as well as H net plus DH remained fairly stable for the Tychem QC ensemble across RH levels. Referring to equation (11), higher vapor pressure gradients (numerator) in conjunction with stable H net plus DH values (denominator) yielded higher R e,T,a values for the Tychem QC ensemble. The elevated vapor pressure and temperature gradients for the WC ense mble countered each other, resulting in R e,T,a values that were nearly the same across RH levels. Table 5.2. Apparent Total Evaporative Resistance Values, Temperat ure and Pressure Gradients, and Net Heat Gain Plus Dry-Heat Loss Values for T wo Ensembles at Three Heat Stress Stages Ensembles WC Tychem Heat Stress Stages C T U C T U R e,T,a (m 2 kPa/W) 0.017 0.014 0.012 0.042 0.033 0.027 P (kPa) 3.0 2.8 2.6 3.8 3.9 3.8 T ( o C) 3.7 7.0 9.2 -5.9 -2.9 -0.6 H net (W m -1 ) 143 143 142 153 153 152 DH (W m -1 ) 35 66 87 -54 -27 -6 H net + DH (W m -1 ) 178 209 229 99 126 146 DH = (T db – T sk ) / I T,r ; C = Compensable, T = Transition, U = Uncompensabl e The relationships among R e,T,a values, vapor pressure gradients, and H net plus DH for WC and Tychem QC ensembles at different stages of heat stress were illustr ated in Figure 5.2.

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47 Figure 5.2. Least Squares Mean of Apparent Total Evaporative Resis tances (A), Average Pressure Differences (B), and Net Heat Gain Plus Dry-Hea t Loss (C) for Two Ensembles at Three Heat Stress Stages 0.000 0.010 0.020 0.030 0.040 0.050 CTUApparent Total Evaporative Resistance (m 2 kPa/W)Stage of Heat Stress WC Tychem 0 1 2 3 4 5 CTU P (kPa) Stage of Heat Stress WC Tychem 0 50 100 150 200 250 CTUH net + Dry Heat Loss (W/m 2 ) Stage of Heat Stress WC Tychem A B C

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48 The changes among data in Table 5.1 were also monotonic. R e,T,a values were greatest at the compensable stage of heat stress and lowest under uncompensable conditions. Lower temperature gradients and H net plus DH values were observed under compensable conditions with the highest values seen under uncompensable condit ions. Vapor pressure gradients remained relatively similar for both e nsembles across heat stress stages. Using equation (11), it was evident that stable va por pressure gradients (numerator) combined with lower H net plus DH values (denominator) resulted in higher R e,T,a values for both ensembles. Describing the relationships among variables in equation (11) at di fferent RH levels and stages of heat stress provided a foundation to explain heatexchange pathways which may have been present during heat stress trials. Average temperature differences for WC, CC, Tyvek 1424, and NexGen LS 417 were positive implying that “microclimate heat pipes” were not present, and any sweat accum ulated on the ensembles was the result of the wicking of sweat from the skin prior to evapor ation. A negative average temperature difference of -3.1 2.8 o C (T sk > T db ) for the Tychem QC ensemble may have supported a “microclimate heat pipe” but because the ma gnitude of the temperature gradient was small its presence was unlikely. Thes e findings were consistent with the results published by Havenith et al. (2008) who observed microc limate evaporation/condensation cycles at lower temperatures (below 20 o C) and among ensembles with higher evaporative resistances and temperature gr adients of 20 o C or greater (Havenith et al. 2008). While clothing saturation reduce d the total insulation (I T ) of clothing, thus increasing radiation and convective heat exchange, it only affected estimated R e,T,a values minimally (Caravello et al. 2008; Holmer, 2006; Barker et al.

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49 1999; Bernard & Matheen, 1999; Havenith, 1999). Also important to consider was the fact that tight-fitting clothing saturated with sweat incre ased the water vapor permeability properties of an ensemble. However, evaporative cooling may be r educed when sweat was wicked by clothing because a percentage of the heat which would have been emitted during skin evaporation was left behind or dissipated by other, less ef ficient heatexchange processes (Hes & Aruajo, 2010; Havenith et al. 2008; Cain & Mc Lellan, 1998). In hot climates (T db T sk ), it was possible for the heat energy in the environment to be substituted as a driving force for evaporation further reducing body heat loss (Holmer, 2006; Bouskill et al. 2002). Eliminating the presence of a microclimate evaporation/condensation cycle left only two major pathways for heat-exchange: convection and diffusion ( Havenith et al. 2008). The convection pathway was driven by air movement (ventilati on) through clothing layers and resulted in the transfer of heat and water vapo r (evaporated sweat) from the skin to the environment. The diffusion pathway, incorporating conduct ion and radiation heat transfer, and molecular diffusion of water vapor, co ntinues to be maintained as the traditional theory for heat-exchange in hot environment s (Havenith, 1999). However, results published by Bernard et al. (2010) and Gonzalez et al. (2006), and reinforced by Havenith et al. (2010), found that evaporative cooling was better supported by the air permeability properties of the fabric than by molecular diffusion. Increasing levels of air permeability (porosity) improved the capa bility of clothing ensembles to support the convective transfer of water vapor for ev aporative cooling (Bernard et al. 2010; Gonzalez et al. 2006). Clothing with greater poros ity (WC, CC, Tyvek 1424) can ventilate evaporated water vapor with greater efficie ncy resulting in

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50 lower R e,T,a values. Clothing with lower porosity (NexGen LS 417 followed by Tychem QC ) exhibited lower capacities to ventilate leading to higher R e,T,a values. Clearly, convection was the dominant pathway and had a greater impact on R e,T,a values than the diffusion (Bernard et al. 2010; Havenith et al. 2010; Gonzalez et al. 2006). What remained unclear were the factor(s) which gave rise t o the experimental results observed in this study. Different R e,T,a values were calculated despite the fact that the work demand and convective air movement were about the same at every RH level and stage of heat stress. Theoretically, larger vapor pressur e gradients would have been more supportive of evaporative cooling, promoting convective transport of eva porated water vapor from the skin to the environment and lower R e,T,a values. However, the opposite finding was observed. The results of this study suggested that the heat -exchange processes present in hot environments were not as clear as conceived previously Conclusion The results of the study established that R e,T,a values do change with RH levels and stages of heat stress and that the theoretical framework for explaining heat-exchange in hot environments is not yet well-established. Also confirmed w as the dominance of the convection pathway over the diffusion pathway in hot environments. Future Research Further research to verify the findings of this study is war ranted. Also recommended is a close examination of the current model used to eva luate heat stress to evaluate its reliability under different stages of heat stre ss and environmental conditions.

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51 New models may need to be developed around the convective properties of clot hing ensembles to understand the relationship between temperature and vapor pr essure gradients on R e,T,a values. Study Limitations Study results may have been influenced by random and systematic error. The order of testing ensembles was randomized among study participants to limit confounding but some level of random error may have been introduced. Sys tematic errors related to the precision and accuracy of heat lab instrume nts, as well as data recording, were likely present. Errors, although very small, were detected during random verification of the database following data extraction. Such errors would have impacted R e,T,a values, which are also vulnerable to errors inherent in the quantita tive method used in the study protocol described by Bernard et al. (2010) and Caravell o et al. (2008). Most notably, the assumption regarding skin being fully wet may have been violated for experimental trials conducted at the compensable stage of heat stress. Additionally, R e,T,a values were estimated 20 minutes before and 15 minutes after the critical condition when equation (1) may not be true (Bernard et al. 2010; Caravello et al. 2008 ). The data were collected in a controlled climatic chamber where other factors, w hich may contribute to heat stress, were absent or not measured. Finally, study resul ts can be extended to only the five specific ensembles tested in the experiment.

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52 REFERENCES American Conference of Governmental Industrial Hygienists. (2010). Threshold limit values and biological exposure indices. Cincinnati, Ohio: Author. American Society for Testing and Methods. (2005). Standard method for measuring the evaporative resistance of clothing using a sweating manikin (ASTM F1291-05). West Conshohocken, Pennsylvania: ASTM International. American Society for Testing and Methods. (2002). Annual book of ASTM standards (Volume 11.03). West Conshohocken, Pennsylvania: ASTM International. Anna, D.H. (2003). Chemical protective clothing (2 nd ed.). Fairfax, VA: AIHA Press. Ashley, C.D., Luecke, C.L., Schwartz, S.S., Islam, M.Z., & Bernard, T. E. (2008). Heat strain at the critical WBGT and the effects of gender, clothi ng and metabolic rate. International Journal of Industrial Ergonomics, 38 640-644. Barker, D.W., Kini, S., & Bernard, T.E. (1999). Thermal characteristi cs of clothing ensembles for use in heat stress analysis. American Industrial Hygiene Association Journal, 60 (1), 32-37. Barnes, J., & Holcombe, B. (1996). Moisture sorption and transport in clothing during wear. Textile Research Journal, 66 (12), 777-786. Belding, H.S., & Kamon, E. (1973). Evaporative coefficients for predic tion of safe limits in prolonged exposures to work under hot conditions. Federal Proceedings 32 (5), 1598-1601. Bernard, T.E., Ashley, C., Trentacosta, J., Kapur, V., & Tew, S. (2010). Cr itical heat stress evaluation of clothing ensembles with different levels of porosity. Ergonomics, 53 (8), 1048-1058. Bernard, T.E., & Ashley, C.D. (2009). Short-term heat stress exposure l imits based on wet bulb globe temperature adjusted for clothing and metabolic rate. Journal of Occupational and Environmental Hygiene, 6 (10), 632-638. Bernard, T.E., Luecke, C.L., Schwartz, S.W., Kirkland, K.S., & Ashley, C .D. (2005). WBGT clothing adjustments for four clothing ensembles under three rel ative

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53 humidity levels. Journal of Occupational and Environmental Hygiene, 2 (5), 251256. Bernard, T.E. (1999). Heat stress and protective clothing: An emerging approach from the United States. Annals of Occupational Hygiene, 43 (5), 321-327. Bernard, T.E., & Matheen, F. (1999). Evaporative resistance and sustaina ble work under heat stress conditions for two cloth anticontamination ensembles. International Journal of Industrial Ergonomics, 23 (5-6), 557-564. Birnbaum, R.R., & Crockford, G.W. (1978). Measurement of clothing ventilati on index. Applied Ergonomics, 9 (4), 194-200. Bouskill, L.M., Havenith, G., Kuklane, K., Parsons, K.C., & Withey, W.R. (2002). Relationship between clothing ventilation and thermal insulation. American Industrial Hygiene Association Journal, 63 262-268. Brode, P., Havenith, G., Wang, X. Candas, V., den Hartog, E.A., Griefahn, B., e t al. (2008). Non-evaporative effects of a wet mid layer on heat transfer through protective clothing. European Journal of Applied Physiology, 104 (2), 341-349. Cain, B., & McLellan, T.M. (1998). A model of evaporation from the skin w hile wearing protective clothing. International Journal of Biometeorology, 41 183-193. Caravello, V., McCullough, E.A., Ashley, C.D., & Bernard, T.E. (2008). Apparent evaporative resistance at critical conditions for five clothin g ensembles. European Journal of Applied Physiology 104 (2), 361-367. Daanen, H., Hatcher, K., & Havenith, G. (2005). Determination of clothing microclimate volume. In Y. Tochihara, & T. Ohnaka (Volume 3), Environmental ergonomics – The ergonomics of human comfort, health, and performance in the thermal environment (pp. 361-365). Amsterdam, The Netherlands: Elsevier B.V. DiNardi, S.R. (2003). The occupational environment: Its evaluation, control, and management (2 nd ed.). Fairfax, VA: AIHA Press. Farnworth, B., Lotens, W.A., & Wittgen, P.P.M.M. (1990). Variation of wate r vapor resistance of microporous and hydrophilic films with relative humi dity. Textile Research Journal, 60 50-53. Frye, A.J., & Kamon, E. (1981). Responses to dry heat of men and women with similar aerobic capacities. Journal of Applied Physiology, 50 (1), 65-70. Fukazawa, T., Kawamura, H., Tochihara, Y., & Tamara, T. (2003). Water vapor transport through textiles and condensation in clothes at high altitudes – Combine d

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54 influence of temperature and pressure simulating altitudes. Textile Research Journal, 73 657-663. Ghaddar, N., Ghali, K., & Jones, B. (2003). Integrated human-clothing system model for estimating the effect of walking on clothing insulation. International Journal of Thermal Stress, 42, 605-619. Gibson, P.W. (2000). Effect of temperature on water vapor transport th rough polymer membrane laminates. Polymer Testing, 19 673-691. Gibson, P.W. (1999a). Water vapor transport and gas flow properties of t extiles, polymer membranes, and fabric laminates. Journal of Coated Fabrics, 28 300-327. Gibson, P.W., Rivin, D., Kendrick, C., Schreuder-Gibson, H. (1999b). Humiditydependent air permeability of textile materials. Textile Research Journal, 69 (5), 311-317. Gonzalez, N.W., Bernard, T.E., Carroll, N.L., Bryner, M.A., & Zeigler, J.P (2006). Maximum sustainable work rate for five protective clothing ensembl es with respect to moisture vapor transmission rate and air permeability Journal of Occupational and Environmental Hygiene, 3 (2), 80-86. Havenith, G., Zhang, P., Hatcher, K., & Daanen, H. (2010). Comparison of two trace r gas dilution methods for the determination of clothing ventilation and of vapour resistance. Ergonomic, 53 (4), 548-558. Havenith, G., Richards, M.G., Wang, X., Brode, P., Candas, V., den Hartog, E., et al. (2008). Apparent latent heat of evaporation from clothing: Attenuation and “ heat pipe” effects. Journal of Applied Physiology 104 142-149. Havenith, G., & Nilsson, H. (2004). Correction of clothing insulation for movem ent and wind effects, a meta-analysis. European Journal of Applied Physiology, 92 (6), 636-640. Havenith, G. (1999). Heat balance when wearing protective clothing. The Annals of Occupational Hygiene 43 (5), 289-296. Havenith, G., Heus, R., & Lotens, W.A. (1990). Resultant clothing insulation: A function of body movement, posture, wind, clothing fit and ensemble thickness. Ergonomics 33 (1), 67-84. Hes, L., & Arujo, M. (2010). Simulation of the effect of air gaps betw een the skin and a wet fabric on resulting cooling flow. Textile Research Journal, 80 (14), 14881497. Holmer, I. (2006). Protective clothing in hot environments. Industrial Health, 44 404413.

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55 Holmer, I., Nilsson, H., Havenith, G., & Parsons, K. (1999). Clothing convective heat exchange–Proposal for improved prediction in standards and models. Annals of Occupational Hygiene 43 (5), 329-337. Huang, J., & Chen, Y. (2011). Effect of environmental parameters on wate r vapor transfer of fabrics. The Journal of the Textile Institute, 102 (1), 50-56. International Organization for Standardization 9920. (2007). Ergonomics of the thermal environment: Estimation of the thermal insulation and water vapour resista nce of a clothing ensemble Geneva, Switzerland: International Organization for Standardization. International Organization for Standardization 7933. (2004a). Ergonomics of the thermal environment: Analytical determination and interpretation of heat stress usi ng calculation of the predicted heat strain Geneva, Switzerland: International Organization for Standardization. International Organization for Standardization 8996. (2004b). Ergonomics – Determination of metabolic heat production Geneva, Switzerland: International Organization for Standardization. International Organization for Standardization 15831. (2004c). Clothing – Physiological effects – Measurement of thermal insulation by means of a thermal mani kin Geneva, Switzerland: International Organization for Standardization. International Organization for Standardization 11092. (1993). Textiles – Physiological effects – Measurement of thermal and water-vapour resistance under steady -state conditions (sweating guarded – hotplate test) ISO. Geneva, Switzerland. Kenney, W.L., Mikita, D.J., Havenith, G., Puhl, S.M., & Crosby, P. (1993). Simultaneous derivation of clothing-specific heat exchange coefficients. Medicine & Science in Sports & Exercise 25 (2), 283-289. Levine, L., Sawka, M.N., & Gonzalez, R.R. (1998). Evaluation of clothing sys tems to determine heat strain. American Industrial Hygiene Association Journal, 59 (8), 557-562. Lind, A.R. (1963). A physiological criterion for setting thermal e nvironmental limits for everyday work. Journal of Applied Physiology, 18 51-56. McLellan, T.M., & Frim, J. (1994). Heat strain in the Canadian forces chemical defence clothing: Problems and solutions. Canadian Journal of Applied Physiology 19 (4), 379-399. Nilsson, H.O., Anttonen, H., & Holmer, I. (2000). New algorithms for prediction of wind effects on cold protective clothing NOKOBETEF 6, 1 st ECPC, 17-20, Norra Latin, Stockholm, Sweden. Occupational Safety and Health Administration. (2010). OSHA regional notice (Region VI: Directive Number: 02-00-027). Washington, D.C.: Department of Labor.

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56 Occupational Safety and Health Administration. (1999). OSHA technical manual: Heat stress (Directive Number: TED 01-00-015). Washington, D.C.: Department of Labor. Office of Compliance. (2009). Heat stress: Don’t let the heat get you down Washington, D.C.: Congressional Accountability Office of Compliance. Plog, B.A., & Quinlan, P.J. (2002). Fundamentals of industrial hygiene (5th ed.). Itasca, IL: National Safety Council. Wang F., Kuklane, K., Gao, C., & Holmer, I. (2011). Can the PHS model (IS O 7933) predict reasonable thermophysiological responses while wearing p rotective clothing in hot environments? Physiological Measurement, 32 239-249. Woodcock, A.H. (1962). Moisture transfer in textile systems, part I. Text Research Journal, 32 (8), 628-633.

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57 APPENDICES

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58 APPENDIX A: Aggregate Apparent Total Evaporative Resistance Data Table A1. Least Squares Mean of Apparent Total Evaporative Resista nce (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 20% Relative Humidity Heat Stress Stages Compensable Transition Uncompensable Ensembles WC 0.019 0.016 0.014 CC 0.020 0.017 0.016 Tyvek 0.020 0.018 0.017 Nexgen 0.027 0.021 0.019 Tychem 0.054 0.041 0.034 Table A2. Least Squares Mean of Apparent Total Evaporative Resista nce (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 50% Relative Humidity Heat Stress Stages Compensable Transition Uncompensable Ensembles WC 0.017 0.013 0.011 CC 0.017 0.013 0.010 Tyvek 0.019 0.015 0.013 Nexgen 0.022 0.018 0.014 Tychem 0.040 0.032 0.027 Table A3. Least Squares Mean of Apparent Total Evaporative Resista nce (m 2 kPa/W) for Five Ensembles at Three Heat Stress Stages and 70% Relative Humidity Heat Stress Stages Compensable Transition Uncompensable Ensembles WC 0.017 0.012 0.010 CC 0.017 0.013 0.010 Tyvek 0.017 0.013 0.011 Nexgen 0.022 0.015 0.011 Tychem 0.033 0.025 0.019

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59 APPENDIX B: Aggregate Environmental Data Table A4. Average Temperature Difference ( o C) for Five Ensembles at Three Heat Stress Stages and Three Relative Humidity Levels (Mean Standard Deviation) Clothing Ensembles RH (%) Heat Stress Stages WC CC Tyvek NexGen Tychem 20 C 10.5 2.8 10.0 2.6 9.7 3.0 5.4 3.0 -5.5 2.2 20 T 14.3 2.5 13.7 2.8 13.0 4.0 8.9 2.8 -1.9 2.2 20 U 17.0 2.6 16.4 3.2 15.5 3.8 11.6 3.1 0.5 1.8 50 C 2.6 1.9 3.1 1.8 2.1 2.4 0.4 1.6 -5.8 1.9 50 T 5.9 1.4 6.5 1.7 5.4 1.9 3.5 1.9 -3.5 1.9 50 U 7.8 1.5 8.6 1.6 7.4 2.0 5.7 1.9 -1.0 1.8 70 C -1.1 1.7 -1.4 1.7 -1.2 1.0 -2.5 1.2 -6.3 1.0 70 T 1.7 2.0 1.4 2.3 1.5 1.4 0.6 1.7 -3.4 1.1 70 U 3.7 2.2 3.5 2.3 3.5 1.6 3.0 1.5 -1.3 1.0 T = T db T sk Table A5. Average Vapor Pressure Difference (kPa) for Five Ens embles at Three Heat Stress Stages and Three Relative Humidity Levels (Mean Standard De viation) Clothing Ensembles RH (%) Heat Stress Stages WC CC Tyvek NexGen Tychem 20 C 4.2 0.4 4.2 0.4 4.4 0.5 4.5 0.7 4.8 0.3 20 T 4.2 0.4 4.2 0.4 4.5 0.4 4.4 0.9 5.0 0.3 20 U 4.1 0.7 4.2 0.5 4.5 0.5 4.4 1.1 5.0 0.6 50 C 2.7 0.3 2.6 0.2 3.0 0.3 2.9 0.7 3.6 0.4 50 T 2.4 0.3 2.3 0.4 2.8 0.5 2.8 0.4 3.7 0.2 50 U 2.2 0.5 2.1 0.5 2.6 0.6 2.6 0.4 3.7 0.2 70 C 2.3 0.3 2.2 0.3 2.2 0.3 2.5 0.3 3.1 0.3 70 T 1.9 0.4 2.0 0.3 2.0 0.3 2.2 0.4 2.9 0.3 70 U 1.7 0.4 1.6 0.6 1.8 0.3 1.8 0.4 2.7 0.3 P = P sk P a

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60 APPENDIX C: Environmental Data for Main Effects Table A6. Temperature and Water Vapor Pressure Levels for Five E nsembles (Mean Standard Deviation) Ensembles T db ( o C) T sk ( o C) T ( o C) P (kPa) + WC 43.1 6.5 36.5 1.0 6.7 6.0 2.8 1.0 CC 43.1 6.5 36.3 1.0 6.7 5.9 2.8 1.1 Tyvek 42.7 6.5 36.4 1.0 6.4 5.9 3.1 1.1 Nexgen 40.5 5.2 36.4 1.0 4.1 4.6 3.1 1.2 Tychem 32.9 3.7 36.0 1.2 -3.1 2.8 3.8 0.9 T = T db T sk ; + P = P sk P a Table A7. Temperature and Water Vapor Pressure Levels for Thre e Relative Humidity Levels (Mean Standard Deviation) RH (%) T db ( o C) T sk ( o C) T ( o C) P (kPa) + 20 45.7 7.7 36.6 0.9 9.1 7.2 4.5 0.6 50 39.5 5.1 36.3 1.0 3.2 4.5 2.8 0.6 70 36.2 4.1 36.1 1.2 0.1 3.2 2.2 0.5 T = T db T sk ; + P = P sk P a Table A8. Temperature and Water Vapor Pressure Levels for T hree Heat Stress Stages (Mean Standard Deviation) Heat Stress Stage T db ( o C) T sk ( o C) T ( o C) P (kPa) + Compensable 36.6 6.2 35.4 0.9 1.2 5.7 3.3 1.0 Transition 40.8 6.3 36.4 0.7 4.4 6.0 3.2 1.1 Uncompensable 43.9 6.3 37.2 0.7 6.7 6.2 3.0 1.3 T = T db T sk ; + P = P sk P a

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61 APPENDIX D: Environmental Data for Interactions Table A9. Temperature and Water Vapor Pressure Levels for Fi ve Ensembles at Three Relative Humidity Levels (Mean Standard Deviation). Configuration T db ( o C) T sk ( o C) T ( o C) P (kPa) + A2 50.7 4.3 36.7 0.8 14.0 3.7 4.2 0.5 A5 41.8 3.4 36.4 0.9 5.4 2.7 2.5 0.4 A7 37.8 3.7 36.3 1.1 1.5 2.8 2.0 0.4 B2 49.9 4.2 36.6 0.7 13.4 3.9 4.2 0.4 B5 42.6 3.5 36.5 0.9 6.1 2.8 2.4 0.4 B7 37.1 3.8 36.0 1.2 1.2 2.9 2.0 0.5 C2 49.4 5.0 36.6 0.9 12.7 4.3 4.4 0.5 C5 41.4 3.6 36.4 0.9 5.0 3.0 2.8 0.5 C7 37.3 3.3 36.1 1.1 1.3 2.4 2.0 0.3 D2 45.4 4.4 36.7 0.9 8.6 3.9 4.5 0.9 D5 39.4 3.4 36.2 0.9 3.2 2.8 2.8 0.5 D7 36.7 3.6 36.4 1.1 0.4 2.7 2.2 0.5 E2 33.9 4.0 36.2 1.1 -2.3 3.2 5.0 0.4 E5 32.5 3.7 35.9 1.3 -3.4 2.7 3.7 0.3 E7 32.3 3.4 35.9 1.3 -3.7 2.3 2.9 0.3 A = Work Clothes, B = Cotton Coveralls, C = Tyvek, D = NexGen, E = Tychem 2 = 20% Relative Humidity, 5 = 50% Relative Humidit y, 7 = 70% Relative Humidity T = T db T sk ; + P = P sk P a

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62 Table A10. Temperature and Water Vapor Pressure Levels for Five Ensembles at Three Heat Stress Stages (Mean Standard Deviation) Configuration T db ( o C) T sk ( o C) T ( o C) P (kPa) + AC 39.4 5.7 35.7 0.8 3.7 5.3 3.0 0.9 AT 43.5 5.9 36.5 0.7 7.0 5.6 2.8 1.0 AU 46.5 6.2 37.3 0.7 9.2 5.9 2.6 1.1 BC 39.3 5.6 35.5 0.9 3.8 5.1 3.0 0.9 BT 43.4 5.8 36.4 0.6 7.0 5.5 2.8 1.0 BU 46.5 6.0 37.1 0.7 9.3 5.8 2.6 1.2 CC 39.0 5.6 35.5 0.8 3.5 5.2 3.2 1.0 CT 43.1 5.9 36.5 0.7 6.7 5.6 3.1 1.1 CU 46.1 5.9 37.2 0.6 8.8 5.8 2.9 1.3 DC 36.7 4.2 35.6 0.8 1.2 3.8 3.3 1.0 DT 40.9 4.3 36.5 0.7 4.4 4.0 3.2 1.1 DU 44.0 4.3 37.2 0.8 6.8 4.2 2.9 1.3 EC 29.0 2.1 34.8 1.0 -5.9 1.8 3.8 0.8 ET 33.2 2.1 36.1 0.7 -2.9 1.9 3.9 0.9 EU 36.5 2.1 37.1 0.5 -0.6 1.7 3.8 1.1 A = Work Clothes, B = Cotton Coveralls, C = Tyvek, D = NexGen, E = Tychem C = Compensable, T = Transition, U = Uncompensable T = T db T sk ; + P = P sk P a

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63 APPENDIX E: Statistical Differences for Interactions Table A11. Statistically Significant Differences for Five Ens embles at Three Relative Humidity Levels A2 A5 A7 B2 B5 B7 C2 C5 C7 D2 D5 D7 E2 E5 E7 A2 S S S S A5 S S S S S S A7 S S S S S S S S B2 S S S S S B5 S S S S S S B7 S S S S S S C2 S S S S S S S S C5 S S S S C7 S S S S S S D2 S S S S S S S S S S S S S D5 S S S S S S S S S D7 S S S S S E2 S S S S S S S S S S S S S S E5 S S S S S S S S S S S S S S E7 S S S S S S S S S S S S S S S = Statistically Significant (p < 0.05), = Not S tatistically Significant A = Work Clothes, B = Cotton Coveralls, C = Tyvek, D = NexGen, E = Tychem 2 = 20% Relative Humidity, 5 = 50% Relative Humidit y, 7 = 70% Relative Humidity

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64 Table A12. Statistically Significant Differences for Five E nsembles at Three Heat Stress Stages AC AT AU BC BT BU CC CT CU DC DT DU EC ET EU AC S S S S S S S AT S S S S S S S AU S S S S S S S S S BC S S S S S S S S BT S S S S S S S BU S S S S S S S S CC S S S S S S S S S S CT S S S S S CU S S S S S S S S DC S S S S S S S S S S S S S DT S S S S S S S S DU S S S S S EC S S S S S S S S S S S S S S ET S S S S S S S S S S S S S S EU S S S S S S S S S S S S S S S = Statistically Significant (p < 0.05), = Not S tatistically Significant A = Work Clothes, B = Cotton Coveralls, C = Tyvek, D = NexGen, E = Tychem C = Compensable, T = Transition, U = Uncompensable

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ABOUT THE AUTHOR Lieutenant Matthew Dooris of the United States Coast Guard wa s born in Tampa and raised in Brooksville, Florida, and graduated from Saint Leo Univers ity in 1999 with a Bachelor of Science in Biology. He was an environmental consulta nt and wetland ecologist for the civil engineering firm, Reynolds, Smith & Hi lls, Inc., prior to joining the Coast Guard in January 2001. As a Coast Guard Officer, he has s erved at Officer Candidate School in New London, Connecticut, Naval Flight School, Pensacola, F lorida, Sector New Orleans, New Orleans, Louisiana, and Sector St. Pet ersburg, Tampa, Florida. In December 2008, Lieutenant Dooris completed a Master’s Degree in Security Studies from the Naval Postgraduate School, Center for Homeland Defense and S ecurity. Following graduation from the University of South Florida, Lieutenant Door is will assume responsibilities of Safety, Environmental, and Health Office r, Coast Guard Eleventh District in San Pedro, California.