Eval of Human Exposure to Airborne Pollutants

8/4/2019 Eval of Human Exposure to Airborne Pollutants

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Copyright

by

Donghyun Rim

2009


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The Dissertation Committee for Donghyun Rim Certifies that this is the approved

version of the following dissertation:

Evaluation of Human Exposure to Indoor Airborne Pollutants:

Transport and Fate of Particulate and Gaseous Pollutants

Committee:

Atila Novoselac, Supervisor

Jeffrey Siegel

Richard Corsi

Ben Hodges

Ofodike Ezekoye


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by

Donghyun Rim, M.S.E.; B.S.E.

Dissertation

Presented to the Faculty of the Graduate School of

The University of Texas at Austin

in Partial Fulfillment

of the Requirements

for the Degree of

Doctor of Philosophy

The University of Texas at Austin

May 2009


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Dedication

To my God, my mother, father, and sisters


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Acknowledgements

This Ph.D. work was carried out in the Indoor Air Quality Research Group at theUniversity of Texas at Austin during the years 2006-2008, and was funded by The

University of Texas at Austin, American Society of Heating, Refrigerating and Air-

Conditioning Engineers (ASHRAE), and The National Institute for Occupational Safety

and Health (NIOSH). The research was also partially supported by the National Science

Foundation Integrative Graduate Education and Research Traineeship (IGERT) grant

DCE-0549428, Indoor Environmental Science and Engineering, at The University of

Texas at Austin.

I would like to express my sincere thanks to my principal advisor, Dr. Atila

Novoselac, for his support and guidance. His encouragement and positive attitude made

me motivated to finish my projects. He has been a great advisor and a role model who

actively interacts and shares knowledge with the students and colleagues. I sincerely

thank Dr. Jeffrey Siegel, who co-advised me in 2006 and provided valuable perspective

on scientific research throughout my entire graduate school years. I would like to

acknowledge Dr. Richard Corsi, who involved me in a nationally renowned graduate

program, IGERT. As an affiliate member, I had an opportunity to interact with

internationally prominent scholars and participate in public outreach program. I express

my sincere gratitude to Dr. Glenn Morrison from Missouri University of Science and

Technology. His valuable advice and suggestions were essential for completion of this

research work.

I would like to thank to Michael Warning, Diana Hun, Catherine Mukai, Brent

Stephen, John Vershaw and my colleagues in the Indoor Air Quality Research Group,


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who contributed to this work by reviewing papers and sharing ideas. It has been such a

blessing to work with you.

I would like to acknowledge the counseling and constructive suggestions given by

my dissertation committee members: Dr. Ben Hodges and Dr. Ofodike Ezekoye.

The last thanks to my family my Mother Yeonja Choi, and my Father Beonsu

Rim and my sisters Carol (Yunkyung), Haekyung, and Woohyun for their love and

support over my life.


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Publication No._____________

Donghyun Rim, Ph.D.

The University of Texas at Austin, 2009

Supervisor: Atila Novoselac

Building environmental conditions such as ventilation and contaminant

concentrations are important factors that influence occupant health and comfort. The

objective of the present work is to investigate how personal exposure to gaseous and

particulate pollutants depends on indoor airflow, source characteristics, and occupant

activity in commercial and residential environments.

The study examines airflow and pollutant transport using experimental

measurements in conjunction with computational fluid dynamics (CFD). The results

demonstrate that breathing has a measurable influence on the airflow in an occupant

breathing zone, but it has very small impacts on the occupant thermal plume. The results

also show that breathing can significantly affect inhaled particle concentrations, even

though the influence varies with source position and particle size. Also, localized hand

motions of a sitting manikin do not significantly disrupt the upward thermal plume.

In typical US residences, forced convection driven mixing airflow or buoyancy

driven stratified airflow occurs depending on the HVAC fan operation (fan on or fan off,


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respectively). The measured transition period between mixing flow (fan on) and stratified

flow (fan off) is approximately one minute, implying that most airflow in the residence is

either dominated by mixing or stratification. A high level of exposure to short-term

pollutant sources, such as resuspension of particles from floor surfaces due to human

activity, more likely occurs with stratified flow than with highly mixed airflow. This is

due to the strong influence of the occupant thermal plume that transports the pollutants

into the breathing zone. Furthermore, by transporting air containing ozone across the

reactive occupant surface, the occupant thermal plume has a large effect on exposure to

ozone reaction products. Due to the reaction of ozone with the skin oils and clothing

surfaces, the occupant surface boundary layer becomes depleted of ozone and conversely

enriched with ozone reaction products.

The parameter ventilation effectiveness quantifies the effectiveness of airflow

distribution and can be used for assessment of exposure to gaseous pollutants. Based on

the study results, the usefulness of ventilation effectiveness as an indicator of exposure to

particulate pollutants depends on the particle size. For small particles (~1 m), an

increase of ventilation effectives caused a decrease in occupant exposure, while for large

particles (~7 m), source location and airflow around the pollutant source are significant

factors for the exposure, and the ventilation effectiveness has very little to no effect.


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Table of Contents

List of Tables ........................................................................................................ xii

List of Figures ...................................................................................................... xiii

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

2. LITERATURE REVIEW .................................................................................4

2.1 Indoor airflow ...........................................................................................4

2.2 Source characteristics..............................................................................10

2.3 Measurement and simulation of airflow and pollutant transport............13

3. STUDY OBJECTIVES......................................................................................15

4. STUDY METHODS..........................................................................................17

4.1 Investigation of air quality surrounding an occupant .............................17

4.1.1 Effects of breathing, movement and air mixing on airflow around anoccupant ......................................................................................17

4.1.2 Effect of occupant breathing on exposure to gaseous and particulatepollutants.....................................................................................19

4.1.3 Effect of air mixing around the human body on exposure to gaseousand particulate pollutants ............................................................20

4.2 Transport of reactive gases in the vicinity of a human body ..................21

4.2.1 Study design................................................................................21

4.2.2 Parametric analysis .....................................................................22

4.3 Transport of gaseous and particulate polutants in the room with differentairflow patterns ....................................................................................24

4.3.1 Study design................................................................................24

4.3.2 Experimental measurements .......................................................24

4.3.3 CFD validation: unsteady pollutant flow analysis......................25

4.3.4 Prediction of pollutant distribution using validated numerical model.....................................................................................................26

4.4 Ventilation effectiveness as an indicator of Particle concentration........27

4.4.1 Study design................................................................................27


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4.4.2 Simulation matrix........................................................................28

5. RESULTS AND DISCUSSION........................................................................31

5.1 Airflow and pollutant transport in the occupants vicinity.....................31

5.1.1 Effects of breathing, air mixing, and occupant movement on airflowin the occupants vicinity............................................................31

5.1.2 Effect of breathing on particle transport around an occupant.....33

5.1.3 Air quality in the occupants vicinity depending on air mixing .34

5.2 Transport of reactive gases in the vicinity of an occupant......................36

5.2.1 CFD validation with experimental measurements......................37

5.2.2 Distribution of ozone concentration surrounding an occupant...37

5.2.3 Parametric analysis results..........................................................38

5.3 Transport of aerosol associated with airflow pattern..............................41

5.3.1 CFD validation for airflow and transport of gaseous and particulatepollutant ......................................................................................42

5.3.2 Distribution of pollutants with mixing and stratified airflow flow42

5.4 Air change effectiveness as air quality indicator ....................................45

5.4.1 CFD validation: age-of-air vs. particle distribution....................45

5.4.2 Parametric analysis: the relationship between ventilationeffectiveness and particle concentration .....................................46

6. SUMMARY AND CONCLUSIONS ................................................................49

Appendix A............................................................................................................51

PAPER I Transport of particulate and gaseous pollutants in the vicinity of ahuman body..........................................................................................52

Appendix B ............................................................................................................82

PAPER II The influence of chemical interactions at the human surface onbreathing-zone levels of reactants and products ..................................83

Appendix C ..........................................................................................................113

PAPER III Transient simulation of airflow and pollutant dispersion undermixing and buoyancy driven flow regimes in residential buildings..114


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Appendix D..........................................................................................................144

PAPER IV Ventilation effectiveness as an indicator of occupant exposure toindoor particles...................................................................................145

Appendix E ..........................................................................................................174

I. Simulation of airflow and pollutant transport..........................................175

1. Airflow modeling..................................................................175

2. Simulation of gaseous pollutants ..........................................177

3. Transport of particulate pollutants........................................178

II. Measurement of airflow and pollutant transport....................................184

References............................................................................................................185

Vita .....................................................................................................................196


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List of Tables

Table 1: Mean convective heat transfer coefficients of a human body in still air

(Reference: Gao and Niu, 2005).........................................................9


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List of Figures

Figure 1 Velocity monitoring points to examine the effects of breathing, movement

and ventilation on the thermal plume....................................................19

Figure 2 Positions of pollutant sources (Source Position 1 and Source Position 2) and

air sampling locations (S1, S2, S3, S4, and S5) in the vicinity of the

manikin..................................................................................................20

Figure 3 Simulation geometry for ozone uptake experiments: (a) CASE I has the air

supply opening at floor level in front of the occupant; (b) CASE II has the

air supply at ceiling level behind the occupant. ....................................22

Figure 4 Experimental setup for the mock-up tests, showing the air handling unit, a

manikin, heat sources, and a displacement diffuser. .............................25

Figure 5 Geometry of models used to simulate momentum driven mixing flow (a)

and buoyancy driven flow (b). ..............................................................27

Figure 6 Velocity profiles at characteristic sampling points with changing

parameters: breathing, hand movement and mechanical fan operation 33

Figure 7 Distribution of SF6 gas and 0.77m particles in the vicinity of the manikin

with (a, c) forced-convection mixing flow and (b, d) stratified flow....35

Figure 8. Room airflow distribution simulated with (a) forced-convection ceiling air

supply (mixing flow) and (b) low-momentum floor air supply (stratified

flow) ......................................................................................................36

Figure 9 (a) Occupant thermal plume for air exchange rate 0.5 h-1: mean velocity

magnitude around the body = 0.1 m/s. (b) Contour of ozone concentration

(normalized by chamber inlet concentration) around the body and sampling

region for inhaled concentration (0.5 h-1

)..............................................38


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Figure 10 Average air speed in the skin boundary layer (a), ozone decay rate (b),

ozone ratio (c), and ORPHS ratio (d) as a function of air exchange rate for

the two characteristic airflows: CASE I (floor supply) and CASE II

(ceiling supply). ...................................................................................40

Figure 11 Transient concentrations of SF6 gas and 3.2 m particles at the two

sampling locations with mixing flow and buoyant flow. For both cases, the

source release period was two minutes. The air exchange rate was 2.7hr-1.

Note that the vertical scale for particles is ten times larger in the graphs for

buoyant flow than those for mixing flow.............................................43

Figure 12 Comparison between SF6 peak (with intermittent injection) and steady-

state (with continuous injection) concentrations at the two sampling

locations with mixing flow and buoyant stratified flow. For both cases, the

air exchange rate was 2.7 hr-1. .............................................................45

Figure 13 Ventilation effectiveness vs. Reduction in particle concentration for

breathing plane: (a) 1 m and (b) 7 m...............................................48


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1. INTRODUCTION

Indoor environmental conditions including ventilation, contaminantconcentrations, and human microclimate have been associated with occupant comfort and

exposure to indoor airborne pollutants. Previous studies (Fisk and Rosenfeld 1997;

Mendell et al. 2002; Sundell 2004; Li et al. 2007) reported the association of indoor

environmental conditions with increased risks of occupant health problems such as

building-related hypersensitivity reactions (sick building syndrome), respiratory disease,

allergies, lung cancer, sensory irritation, and transmission of infectious disease.

Several epidemiological studies (Jerrett et al. 2005; Pope et al. 2002; Bell et al.,

2006) demonstrated the relationship between adverse health effects and exposure to

airborne gaseous and particulate pollutants. Pollutant concentrations in indoor

environments such as houses and offices are often much higher than outdoor levels

(Wallace 2000; Ozkaynak et al. 1996), and people spend most of their time in buildings

(Klepeis et al., 2001). Consequently, inhalation exposure to airborne pollutants in built

environment has been the focus of many research studies and the subject of various

control efforts.

Elevated occupant exposure is directly related to the health and productivity of

occupants. Fisk (2000) estimated the economic loss caused by exposure to indoor air

pollutants as $40160 billion, considering healthcare cost and productivity of building

occupants. Especially these days, the need for building energy conservation and carbon

footprint reduction draw attention to sustainable and healthy building design that also can

control the indoor air pollution and reduce the human exposure to indoor air pollutants.

The pollutants encountered in indoor environments are broadly classified as

gaseous pollutants and particulate matter. Examples of gaseous pollutants of public


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concern include: volatile organic compounds (VOCs) such as formaldehyde from

building materials and consumer products, ozone that originates from indoor and outdoor

sources, radon decay products that infiltrated from underlying soil, carbon monoxide due

to incomplete combustion, and nitrogen dioxide from household gas appliances. The

potential health effects of the gaseous pollutants are respiratory function impairment,

asthma, lung cancer, sensitization, eye and airway irritation (Ernst and Zibrak 1998;

Clausen et al. 2001; Bostrm et al. 2002). Examples of particulate pollutants are

combustion-related aerosols from gas burners or from smoking, dust and resuspended

particles from indoor surfaces, particles of outdoor-origin such as ammonium sulfate

particles, and bioaerosols including viruses and bacteria. Particulate matter exposure is

associated with respiratory and cardiovascular disease (Nemmar et al. 2002; Salvi et al.

1999) and aggravated asthma. Also, bioaerosols can cause transmission of airborne

infectious diseases such as tuberculosis and SARS (Li et al. 2007; Qian et al. 2006;

Rengasamy et al. 2004). In addition to human health effects, indoor particles can cause

the failure of sophisticated electronic equipment and degradation of cultural artifacts

(Weschler and Shields 1999).

To reduce indoor air pollution and foster a healthy indoor environment, it is

necessary to understand the airflow pattern and pollutant transport mechanism in

occupied spaces (Faulkner et al. 1999; Fisk et al. 1997). Specially, the pollutant

dispersion in occupied spaces and in the vicinity of an occupant is of great interest for

analyses of personal exposure (Melikov and Kaczmarczyk 2007). The breathing

concentrations of airborne pollutants vary greatly across indoor environments, and the

major factors affecting air quality in an occupant breathing zone are (1) indoor airflow,

(2) source characteristics, and (3) occupant breathing and activity (Zhang and Chen 2006;

Ferro et al. 2004a; Bjrn and Nielsen 2002; Fisk et al. 1997).


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The objective of this dissertation is to explore the influence of indoor airflow,

source characteristics, and occupant breathing on the pollutant concentration in the

occupant breathing zone, and accordingly, the occupant exposure.

To present the test methods and the results, this Ph.D. dissertation consists of two

major parts. The first part presents the literature review, research objectives, and major

findings of the research work in four research papers, which are already published or in

preparation for publication. The second part consists of appendixes, which list the

research papers (Appendix A, B, C, and D) and provide technical details about the

methodology used in this research (Appendix E). The first part of the dissertation

summarizes overall work and reports the most important findings. The papers in

Appendixes A, B, C, and D provide more details of the study methods and results that

address the research questions posed for the present work. Finally, Appendix E provides

details about: 1) applied CFD and particle tracking modeling methods and 2)

experimental measurements and facilities used in this research and indoor air quality

research in literature.


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2. LITERATURE REVIEW

This section presents previous research work on indoor airflow and pollutant

characteristics in relation to pollutant transport and occupant exposure. Furthermore, at

the end of each subsection a short summary or directions for future research are provided.

2.1INDOOR AIRFLOW

Ventilation of an occupied space is primarily governed by infiltration and

mechanical ventilation. Infiltration is uncontrolled airflow through building envelopes

due to indoor-outdoor pressure differences caused by wind or temperature gradients.

With mechanical ventilation, fans control the amount of outdoor air supplied to an

occupied space in order to maintain acceptable air quality and occupant thermal comfort.

In the US, airflow through a mechanical ventilation system is common in most public and

commercial buildings. Building codes and standards recommend that a ventilation system

provides a specific amount of minimum airflow per person, depending on the building

type. For example, ASHRAE Standard 62 recommends a minimum ventilation rate pf 8.5

L/s-person for office spaces (ASHAE, 2006). Compared to infiltration, mechanical

ventilation has the advantage of controlling the ventilation rate for occupant health and

comfort. However, it requires energy for supplying an acceptable quantity and quality of

air to occupied spaces.

The ventilation air dilutes or removes indoor airborne pollutants. Providing

adequate quantities of ventilation air to an occupied space is necessary to promote a

healthy and energy efficient indoor environment. Researchers have studied ventilation

rates and the associated pollutant concentrations in buildings. Weschler and Shields

(2000) examined the effect of ventilation on chemical reactions among gaseous pollutants

and reported a higher potential for reactions to generate irritating byproducts with lower


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ventilation rates. A review paper by Seppanen et al. (1999) found an association of

ventilation rates with occupant bio-effluent (CO2) and reported that low ventilation rates

(below 10 L/s per person) lead to degraded perceived air quality outcomes. Other studies

investigated the air exchange rate (frequency of displacement of the air in the building

with outdoor air) in residential and commercial buildings. Murray and Burmaster (1995)

analyzed the air exchange rate in approximately three thousand U.S. homes during four

seasons and reported a mean air exchange rate of 0.5 hr-1. Wallace et al. (2002) conducted

continuous measurements of air exchange rates in an occupied house for one year and

found a mean air exchange rate of 0.65 hr-1. Persily et al. (1994) measured air exchange

rates in an office/library building and reported mean value of 0.8 hr-1. It is important to

note that with outdoor pollutants such as ozone, higher air exchange rate leads to higher

indoor exposure. Conversely, with pollutants of indoor emission such as VOCs from

furnishings, higher air exchange rate leads to lower indoor exposure. Based on the

previous studies, the air exchange rate is closely related to the occupant exposure to

various pollutants and varies with building type, operation of ventilation, and building

conditions.

Just as important as the amount of air supplied into an occupied space is the

distribution of airflow in the space. The investigations by Novoselac and Srebric (2003)

and Fisk et al. (1997) found that airflow distribution determines transport and removal of

air contaminants in the space. Air distribution within a ventilated room can be classified

into three characteristic forms: unidirectional, perfect mixing, and short-circuiting flows.

Unidirectional flow develops when air moves in mainly one direction, such as plug flow,

in which supply air is the least polluted and exhaust air is the most polluted. Perfect

mixing flow assumes intensive air mixing in a space. In this case, the pollutant

concentration at any location in the room is the same as the concentration at the exhaust.


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In short-circuiting flow, a large proportion of the supply air flow directly moves to the

extract air device without passing through the occupied zone. In this case, the

contaminants generated in the occupied zone are less likely to be flushed out. The short-

circuiting flow is normally not a desirable type of room airflow pattern.

Based on their driving force, air motions in buildings are mainly divided into

buoyancy-driven airflow and momentum-driven airflow. Buoyancy-driven (natural

convection) airflow originates from heat sources such as heaters, windows, computers,

and occupants in buildings. Around indoor heat sources, a warm rising airflow called

thermal plume develop and transport airborne pollutants upward direction. The

buoyancy-driven flow is dominant in residential buildings where only infiltration exists

and spaces with displacement ventilation. With the displacement ventilation principle,

fresh air is supplied at floor level, moved (raised) by heat sources in the space, and

exhausted at the ceiling level, providing thermal stratification in the space. On the other

hand, momentum-driven (forced convection) airflow is typically driven by operation of

mechanical ventilation or pressure difference across an opening caused by wind. With the

momentum-driven airflow, a large momentum flow supplied from a diffuser allows the

fresh air to mix well with room air. In some cases, momentum-driven and buoyancy-

driven flows often exist together causing complex mixed convection airflow in the space.

Air distribution in occupied spaces determines fate and transport of indoor

pollutants. Researchers have examined the effect of air distribution on occupant exposure

the pollutant removal in buildings. Lin et al. (2005) compared mixing and displacement

ventilations by measuring carbon monoxide, VOCs, and mean age-of-air in offices,

industrial workshops and public places. They concluded that the displacement ventilation

provides better indoor air quality. Qian et al. (2006) studied infectious droplet nuclei or

bacteria in a hospital environment with either mixing or displacement ventilation and


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reported increased infection risks in the room with displacement ventilation. These

previous studies provide valuable information on the relationship between airflow

distribution and pollutant concentrations in the breathing zone; however, it is difficult to

generalize influence of airflow on occupant exposure, given that different environments

have distinct airflow and pollutant sources.

To quantitatively characterize indoor airflow distribution patterns in relation to

the pollutant removal process, researchers have developed several indoor air quality

indicators (Novoselac and Srebric 2003; Fisk et al. 1997; Persily et al. 1994). One type of

commonly used indoor air quality indicator is the ventilation effectiveness. Ventilation

effectiveness is calculated based on the spatial distribution of age-of-air (time elapsed

from the moment that the air enters the space and reaches the considered location).

Ventilation effectiveness is defined as the ratio of the age-of-air that would occur with

perfect mixing to the actual age-of-air in a considered zone (ASHRAE Standard 129

2004). The ventilation effectiveness characterizes how well a considered zone is

ventilated compared to the whole space. In a room with perfect mixing, the age-of-air in

the breathing zone is the same as in the whole room, and therefore the ventilation

effectiveness for the breathing zone is 1. In unidirectional flow, the age-of-air in the

breathing zone is smaller than that of in perfect mixing condition, causing the ventilation

effectiveness for the breathing zone to be larger than 1. Conversely, in short-circuiting

flow, the age-of-air in the breathing zone is larger than that of in the perfect mixing

condition, leading to ventilation effectiveness for the breathing zone less than 1.

Previous studies that measured ventilation effectiveness in office buildings with

conventional ventilation system, i.e. air supply and return of air at ceiling level, reported

values between approximately 0.8 and 1.2 (Olesen and Seelen 1992; Persily et al. 1994).

Fisk et al. (1997) indicated that air-change effectiveness is strongly influenced by test


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variable of heating versus cooling. They reported the air-change effectiveness ranging

from 0.69 to 0.91 for heating condition and from 0.99 to 1.15 for cooling condition.

Novoselac and Srebic (2003) and Fisk et al. (1997) showed that the ventilation

effectiveness is a valuable indicator in evaluating occupant exposures to passive

(diffusively dispersing) and spatially distributed sources of pollutants. However, to date,

there have been no reported studies showing any relationship between ventilation

effectiveness and particle concentrations in the space or the breathing zone.

Besides airflow distribution in the space due to the ventilation system, buoyant

airflow generated by warm human body also affects airflow and pollutant concentration

in the vicinity of the occupant. Gao and Niu (2005) and Johnson et al. (1996) indicated

that the warm rising thermal plume from a human body affects pollutant dispersion in the

breathing zone. The buoyant thermal plume becomes especially important in cases where

there is little or no intensive air mixing, such as a room with displacement ventilation or a

residential building when the HVAC system is off (Srensen and Voigt 2003; Xing et al.

2001). In these situations, natural convection (heat transfer by moving fluid) due to the

temperature difference between the body surface and the surrounding air has a major

influence on the airflow around the occupant. The convective airflow (i.e., rising thermal

plume) may entrain contaminants in the lower level of the room and transport them to the

breathing zone. To quantify the strength of natural convection that causes the thermal

plume around the occupants, researchers studied convective heat transfer coefficients of a

human body, as summarized in Table 1 (Gao and Niu 2005). The studied convective

transfer coefficients range from 3.3 to 7.4 Wm-2C-1, depending on occupant posture and

environmental conditions such as air velocity, airflow direction, and turbulence intensity.

With regard to the ratio of the convective to radiative heat transfer, Srensen and Voigt


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(2003) reported that in stagnant air, convective and radiative heat transfer account for

40% and 60% of the total sensible heat flux, respectively.

Human breathing influences the local airflow in the breathing zone and should be

taken into account when studying occupant exposure. For instance, the exhalation from

one person may penetrate into another persons breathing zone, causing transmission of

infectious disease. Melikov and Kaczmarczyk (2007) suggested consideration of the

effect of human respiration on local airflow when studying the amount of re-inhaled air

after exhalation and pollutant transport between occupants. Bjrn and Nielsen (2002),

Hyun and Kleinstreuer (2001), and Murakami et al. (1997) examined the effect of

breathing activity on local airflow and gaseous pollutant concentration around an

occupant, finding that the airflow, temperature, and gaseous concentration in the

breathing zone are sensitive to the breathing activity.

Table 1: Mean convective heat transfer coefficients of a human body in still air(Reference: Gao and Niu, 2005)

Researchers Method PostureAmbient air

speed (m/s)

Convective heattransfer coefficient

(Wm-2C-1)

Murakami et al.(1995) CFD Standing < 0.12 3.9

Srensen and Voigt (2003) CFD Seated Stagnant 3.13

Topp et al. (2002) CFD Seated 0.05 7.4

Voigt (2001) CFD Seated 0.025 6.1

Brohus (1997) Experiment Standing < 0.05 3.86

De Dear et al. (1997) Experiment Standing < 0.1 3.4

De Dear et al. (1997) Experiment Seated < 0.1 3.3

These previous studies provide valuable information on the relationship between

local airflow around a human body and pollutant concentrations in the breathing zone.


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However, most of the previous studies have focused on the transport of non-reactive

gaseous pollutants. To our knowledge, there is a lack of studies that show how reactive

gases and particulate matter in the vicinity of a human body interact with airflow. Also,

more studies are needed to characterize breathing zone concentrations associated with

airflow surrounding a human body.

2.2SOURCE CHARACTERISTICS

One of the first steps toward analyzing human exposure in indoor environments is

to identify airborne pollutant sources in an occupied space. Based on the literature, indoor

pollutant sources can be characterized by three components: properties, location, and

strength (Sundell 2004; Ferro et al. 2004b). The characteristics of gaseous and particulate

pollutants are described as follows.

Gaseous pollutants in indoor spaces, including ozone, VOCs, moisture and radon,

are transported by convection and diffusion. In general, convection transport occurs in

association with indoor airflow while diffusion is relatively slow mass transport at the

molecular level or turbulent fluctuation scale. Beside the physical transport of gas,

chemical reactions among gases or between gases and surfaces often cause chemical

transformation, creating reaction products (Weschler and Shields 1997). In many cases,

most of the reactions inside buildings are directly and indirectly related to the presence of

ozone. Reaction products due to ozone and surface reactions include aldehydes, ketones,

carboxylic acids, and secondary organic aerosols (Weschler and Shields 2000; Morrison

2008). The reaction products themselves are likely to be unhealthy, resulting in toxicants

(e.g. formaldehyde), irritants, and sensitizers (Wolkoff et al. 2000; Rohr et al. 2002;

Wilkins et al. 2001). The most important source for indoor ozone is outdoor ozone

transported into buildings. If there are no indoor sources, ozone concentrations in

moderately ventilated spaces typically range from 20 to 30% of the outdoor concentration


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(Lee et al., 1999). Although indoor levels of ozone are usually lower than outdoor levels,

integrated exposure and inhalation rates tend to be approximately equally divided

between indoor and outdoor environments (Weschler, 2006). Typical indoor sources of

ozone include office equipment such as photocopiers and laser printers (Leovic et al.

1996) and portable ion or ozone generators (Waring et al. 2008).

The major VOC sources in residential indoor and workplace microenvironments

are mainly indoor emission sources including building materials, furniture, consumer and

household related products. Wallace et al. (1987) reported VOC concentrations and

emissions measured in 650 residences in seven US cities for EPAs Total Exposure

Assessment Methodology (TEAM) study. The study reported elevated indoor

concentrations of VOCs including chloroform, carbon tetrachloride, 1,1,1-

trichloroethane, n-decane, n-undecane, p-dichlorobenzene, 1,2-dichloroethane, and

styrene. The mean emission rates of those compounds ranges from 0.17 to 71 g m-2 min-

1. Sax et al. (2004) measured emission rates of VOCs in residences in New York and Los

Angeles and identified six significant indoor VOCs and their total house emission rates:

chloroform (0.11 mg/h), 1,4-dichlorobenzene (19 mg/h), formaldehyde (5 mg/h),

acetaldehyde (2 mg/h), benzaldehyde (0.6 mg/h), and hexaldehyde (2 mg/h).

Particulate pollutants are mainly characterized by their size and the major external

forces acting on them. Particle diameter is a key attribute of particulate pollutant. The

range of indoor particle diameters extends from a few nanometers to larger than 10 m, a

difference of over five orders of magnitude. Due to this large range of particle sizes,

particles are divided into three modes: ultrafine particles, fine particles, and coarse mode

particles. Ultrafine particles (< 100 nm) can penetrate deeply into the lungs and blood

vessels, causing respiratory and cardiovascular disease (Nemmar et al. 2002; Penttinen et

al. 2001). Sources of ultrafine particles are vehicle exhaust that penetrates into the indoor


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environment and particles generated from some indoor sources such as gas stoves or

ozone chemistry. (Harrison et al. 1999; Wallace 2008) Fine particles (0.1 to 2.5 m) are

unlikely to deposit on indoor surfaces, typical residential air filters, or the upper

respiratory region (Hinds 1999, Nazaroff 2004). A typical source of fine particles is

smoking. Coarse mode particles (> 2.5 m) have large settling velocities and easily

resuspend from floor surfaces (Hinds 1999; Ferro et al. 2004b). Resuspended particles

may contain indoor allergens or pollen and can trigger respiratory and allergic symptoms

among occupants (Causer et al. 2004).

The indoor particle sources in literature include particle resuspension from floor,

outdoor particles infiltrated into buildings, combustion products from cooking or

smoking, secondary particle formation from reaction of gaseous pollutants, and the

release of bioaerosol from coughing/sneezing (McBride et al. 1999; Wallace 2006;

Weschler and Shields 2000, Rudnick and Milton 2003). Ferro et al. (2004b) reported that

normal indoor activities can contribute to a significant increase in indoor concentrations

of particles greater than 1m. The study reported the particle emission rates ranging from

0.03 to 0.5 mg/min for PM2.5 (particles smaller than 2.5 m in diameter) and from 0.1 to

1.4 mg/min for PM5 (particles smaller than 5 m in diameter) due to walking or

vacuuming. McBride et al. (1999) investigated a source proximity effect on exposure and

found that pollutant sources close to an occupant cause elevated exposures. Abt et al.

(2000) studied the relative contribution of outdoor and indoor particle sources to indoor

particle concentration. They reported that air exchange rates influence indoor fine and

coarse particle size distribution, with higher air exchange rates shifting the indoor size

distributions closer to that of outdoors. Studies conducted by Weschler and Shields

(1999) measured a significant increase (up to 95 g m-3) in concentrations of submicron

particles due to ozone/terpene reaction. In addition, Zhu et al. (2006) reported that


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approximately 95% of aerosols expelled during breathing, coughing, and sneezing are

less than 1 in diameter. Several other studies (Wallace 2006; He et al. 2004) measured the

particle source strengths from combustion, including cigarette smoking and cooking.

The presented studies show that there is a large variety of indoor pollutants with

different source location, source intensity, and physical properties. For accurate

prediction of occupant exposure it is very important to understand source characteristics,

such as chemical/physical properties of the pollutant, and identify the source location,

and strength.

2.3MEASUREMENT AND SIMULATION OF AIRFLOW AND POLLUTANT TRANSPORT

Studies in literature have examined occupant exposure and pollutant transport in

enclosed spaces employing either one or a combination of the following methods:

experimental measurement, numerical (CFD) simulation, and analytical modeling.

Experimental measurements have an advantage of measuring actual pollutant

concentrations and producing reliable first-hand data. However, experimental

measurement often requires high labor and equipment costs, and it is sometimes difficult

to secure repeated measurements. Compared to experimental measurements, CFD

simulation is less expensive and more informative, giving detailed information on non-

uniform airflow and concentration in a space. With the increase of computing power in

the past decade, CFD has been increasingly applied to predict airflow, heat transfer, and

contaminant transportation in and around buildings (Zhai and Chen 2005). Nevertheless,

due to the uncertainties and errors associated with the CFD boundary conditions and

numerical schemes, sophisticated modeling technique is required for CFD simulation

(Srensen and Nielsen 2003). Analytical solutions provide opportunity to give insight

into the physical mechanism of pollutant transport without the need for measurements.


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However, in most cases, analytical solutions are limited to simple cases and assumptions

are required to obtain the solution.

Due to the advantages and disadvantages of the three research methods,

researchers often use at least two methods to assure the quality of data by comparing the

results. Reliable numerical models should be validated based on experimental mock-up

tests or analytical models. Then the validated simulation models can be used to predict

airflow and pollutant dispersion in indoor environments where repetitive measurements

are very difficult and/or expensive.


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3. STUDY OBJECTIVES

The literature review identifies major parameters that affect occupant exposure to

indoor pollutants. These parameters are air exchange rate, airflow distribution in an

occupied space as well as in the vicinity of an occupant, pollutant properties, and source

position. All these parameters determine the pollutant transport from the source to the

occupant, and analysis of each parameter in relation to the exposure is crucial for the

development of exposure reduction measures. The literature review shows the need for

advancement in analyses of airflow and pollutant transport in an occupied space and

personal breathing zone. Therefore, the objective of the present work is to analyze indoor

pollutant transport mechanisms in environments typical of commercial and residential

buildings and to evaluate personal exposure to gaseous and particulate matter pollutants

for three different variables: indoor airflow patterns, source characteristics, and occupant

activity.

The specific research goal is to provide a unique set of data that answer the

following questions:

1. To what extent do the breathing, movement of an occupant, and room air mixing

affect the airflow and particle transport in the vicinity of the occupant?

2. What is the behavior of reactive gaseous pollutants around an occupant?

3. How does the space airflow pattern affect the distributions of particulate and

gaseous pollutants?

4. Can air-change effectiveness be used as an easily detectable air quality indicator

for occupant exposure to particulate matter?

Each of the questions above is addressed in the four research papers in

Appendixes A, B, C, and D. The four papers are entitled Transport of particulate and


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gaseous pollutants in the vicinity of a human body accepted to Building and

Environment Journal, The influence of chemical interactions at the human surface on

breathing-zone levels of reactants and products accepted to Indoor Air Journal,

Transient simulation of airflow and pollutant dispersion under mixing and buoyancy-

driven flow regimes in residential buildings published in ASHRAE Transactions, and

Ventilation effectiveness as an indicator of occupant exposure to indoor particles

submitted to HVAC&R Research Journal.


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4. STUDY METHODS

For the research methods, a combination of experimental measurements and

computer simulation was used. Experimental measurements were primarily used for the

development of numerical simulation models and validation of simulation methods. The

numerical simulations were used to obtain data that could not be measured due to the

available technology or constraints in resource. Also, validated numerical methods were

used for parametric analyses in the case where a large number of expensive and time

consuming experiments would be necessary. In the investigations where numerical

simulation would not provide sufficient accuracy, such as analysis of breathing or

occupant movement on the air quality surrounding an occupant, priority was given to full

scale experimental study.

For each of the four research questions of this Ph.D. study, detailed methodology

is provided in the paper manuscripts in the Appendixes A, B, C, and D. The following

section points out only the most important information to address the research questions.

4.1INVESTIGATION OF AIR QUALITY SURROUNDING AN OCCUPANT

To study airflow and pollutant concentrations in the vicinity of human body, full

scale experiments with a test chamber and thermal breathing manikin were used. The

effect of human activity on airflow was analyzed, followed by detailed study of the

effects of breathing on particulate and gaseous pollutant flow. Furthermore, the effects of

air mixing in the space and particle source position on pollutant concentration in the

occupants vicinity were investigated.

4.1.1 Effects of breathing, movement and air mixing on airflow around an occupant

The experimental study was conducted to examine the impacts of occupant

breathing, movement, and room air mixing on the airflow in vicinity of an occupant.


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Experiments with a breathing thermal manikin were conducted in a 67 m3 environmental

chamber with the geometry typical for an average sized room. The manikin had a very

similar geometry to a real person and was capable of simulating realistic airflow

associated with inhalation and exhalation. To provide an indoor environment that enables

the study of the manikins thermal plume, air mixing in the space was controlled with the

fresh air supplied by a low momentum diffuser. Detailed descriptions of the manikin and

the experimental set-up in the environmental chamber are provided in Appendix A (page

57).

After stabilizing surface temperatures and the airflow field in the chamber, the

airflow velocity was measured at 16 positions inside and outside of the boundary layer of

the manikins thermal plume (Figure 1). Eight velocity sensors (V1-V8 in Figure 1)

measured the airflow velocity profile above the manikins head. The air speed inside the

thermal plume was the largest in this region, and the eight sensors were able to capture

the large gradients of the velocity profile as well as the turbulent fluctuation of the plume.

Any change in the thermal plume was reflected in a change of the velocity field above the

head, and therefore the average of these eight velocities was used to represent the effect

that human activity and/or ventilation systems have on the airflow surrounding the human

body. Experimental results showed that the standard deviation of the average velocity

was 0.05 m/s, which was approximately four times smaller than the average velocity

above the head. By observing the changes in the averaged velocity in the circular area

above the head, the sensitivity of the thermal plume to (1) breathing, (2) occupant

movement, and (3) mechanical ventilation was analyzed. Detailed conditions for the

experimental set-ups for the study of each parameter are described in Appendix A (pages

59-61).


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Figure 1 Velocity monitoring points to examine the effects of breathing, movement andventilation on the thermal plume

4.1.2 Effect of occupant breathing on exposure to gaseous and particulate pollutants

Given the lack of data on inhaled particle concentrations associated with

breathing, the effect of breathing on inhaled concentrations was measured. To examine

the dynamics of small and large particles in human vicinity, the concentrations of a tracer

gas (SF6) and 0.77 and 3.2 m particles were analyzed for two source locations (Source

Position 1 and Source Position 2 in Figure 2). Source Position 1 was placed 1.6 m in front

of the manikins face upstream of the room airflow to simulate pollutants moving

towards the occupant. The Source Position 2 was located 0.5 m behind the manikin and

0.15 m above the floor to simulate particle resuspension from the floor or off-gassing

from the carpet source.

In the six types of experiments, a steady-state emission of a tracer gas and two-

sized particles was used at the two source locations. Concentrations of the tracer gas and

particles were measured at five sampling locations (S1-S5 in Figure 2) in the manikins

vicinity with a constant gas/particle emission and stable airflow field in the room. In each

type of experiment, the concentrations were monitored for 20 min without any breathing


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activity. Afterwards, the breathing mechanism was activated and the air samples were

monitored for another period of 20 min. For both gas and particles, the experiments were

repeated 3-5 times until consistent concentration patterns were observed.

Figure 2 Positions of pollutant sources (Source Position 1 and Source Position 2) and airsampling locations (S1, S2, S3, S4, and S5) in the vicinity of the manikin.

4.1.3 Effect of air mixing around the human body on exposure to gaseous and

particulate pollutants

To investigate the effect of air mixing around the human body on pollutant

concentration in the occupants vicinity, previously described experiments in Section

4.1.2 were repeated with two different airflow regimes: mixing flow and stratified flow.

The mixing flow and stratified flow were simulated by placing a diffuser at ceiling level

and floor level, respectively. A circular wall opening at ceiling level produced mixed

flow with an air exchange rate of 4.5 hr-1

and the average air speed in the central area

ranged from 0.15 to 0.25 m/s, which is typical of office environments. Alternatively, a

low-momentum air supply diffuser at floor level generated the stratified flow with an air

exchange rate of 3 hr-1 with average air speeds lower than 0.10 m/s. This low velocity


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stratified flow prevented air mixing in the vicinity of the manikin. In both cases, the

tracer gas and 0.77 and 3.2 m particle concentrations were monitored at the sampling

locations (S1-S5 in Figure 2). The time-integrated concentrations were normalized by the

concentration at the reference point above the manikins head (Point S1 in Figure 2). The

goal of the normalization was to quantitatively determine the concentration pattern in the

vicinity of an occupant on a relative basis.

The errors due to measurement and normalization were estimated using the mean

and standard deviation of the observed concentrations in repetitive tests. Details about

data processing and the uncertainty analysis are provided in Appendix A (page 65).

4.2TRANSPORT OF REACTIVE GASES IN THE VICINITY OF A HUMAN BODY

This part of my Ph.D. dissertation considers ozone as an example of a reactive gas

that is common in indoor environments. Both ozone and its reaction products have

adverse effects on human health. The following section provides methods used in

analysis of ozone and reaction product concentrations in the vicinity of an occupant.

4.2.1 Study design

Given the ozone reactivity with occupant surfaces, the study investigated the

breathing concentrations of ozone and reaction products. Validated computational fluid

dynamics (CFD) models were used to calculate ozone mass transport in the boundary

layer of an occupant surface. The accuracy of the CFD simulation models were validated

with experimental results that considered airflow and ozone mass transfer. Simulation

parameters such as thermal boundary conditions, grid resolution, and mass transfer

models were adjusted based on a set of experiments with simplified geometry. Details of

the validation experiments are described in Appendix B (pages 90-91 and 94-97). These


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validated CFD models were applied further in a parametric analyses of different airflow

conditions in the space.

4.2.2 Parametric analysis

The validated CFD models were applied to simulate a more detailed and more

realistic geometry of a standing occupant in a room (Figure 3). The convective portion of

the heat flux from the occupant was set to 30 W over a total occupant surface area of 1.8

m2 which corresponds to a 1.73 m tall, 70 kg person (DuBois and DuBois 1916). The

occupant was centered in a room with dimensions of 3.03.52.5m, and the airflow in

the room was supplied and exhausted in two different ways (CASE I and CASE II in

Figure 3).

(a) CASE I (b) CASE II

Figure 3 Simulation geometry for ozone uptake experiments: (a) CASE I has the airsupply opening at floor level in front of the occupant; (b) CASE II has theair supply at ceiling level behind the occupant.

For each case, the CFD provided data for analysis of airflow distribution, the

temperature field in the space and in the occupant vicinity, and the ozone concentration in

the breathing zone. The breathing zone concentration was calculated as the volume-

averaged concentration over a 0.5 liter air volume below the nose tip (Melikov and


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Kaczmarczyk, 2007). For each case in Figure 3, ozone concentrations in the breathing

zone and bulk flow region were calculated for seven different ventilation rates: 0.5, 1, 2,

3, 5, 8.8, and 17.6 hr-1

. Ventilation rates lower than 5 hr-1

are typical in residential and

commercial buildings (Waring and Siegel 2008), while those higher than 5 hr-1

are

associated with indoor environments such as automobiles (Park et al. 1998), operation

rooms, or rooms with open windows on a windy day.

Based on the resulting breathing zone concentration, bulk air concentration, and

the concentrations at the supply inlet and exhaust, the analysis considers three

parameters:

1) Ozone decay rate, kozone. This parameter describes mass transfer of ozone at

the occupant surface and varies with ventilation rate and surface reactivity.

2) Ozone ratio, rO3. This parameter is defined as the concentration ratio

between the breathing zone and bulk air. The ozone ratio relates the breathing

zone mixing ratio to that of the bulk air in the room. An ozone ratio less than

1 suggests that bulk-air ozone measurements will overestimate inhalation

exposure or intake.

3) O RPHS ratio, rORPHS. The Ozone Reaction Products associated with the

Human Surface (hair, skin and skin-oil coated clothing and accessories) were

designated as ORPHS. The ORPHS ratio is defined as the ratio of the

breathing zone ORPHS to the bulk-air ORPHS mixing ratios. The ORPHS

ratio is calculated based on ozone removal assuming the same molar yield in

the breathing zone and bulk-air. The ratio relates the breathing zone

concentration to that of the bulk air in the room. An ORPHS ratio greater

than 1 indicates that bulk room measurements would underestimate

inhalation exposure to ORPHS.


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The detailed mathematical expressions for the three parameters are described in

Appendix B (pages 93-94). These parameters were analyzed in conjunction with

airflow distribution around the occupant, ventilation rate, and air mixing intensity.

4.3TRANSPORT OF GASEOUS AND PARTICULATE POLUTANTS IN THE ROOM WITHDIFFERENT AIRFLOW PATTERNS

The transport of the pollutant from a source to an occupant depends on the airflow

distribution in the space. The airflow distribution in a typical US residential house is very

complex due to the periodic operation of a heating, ventilating and air-conditioning

(HVAC) system. Depending on the HVAC fan operation, forced convective airflow (fan

on) or buoyancy driven stratified airflow (fan off) occurs in the space. Since people spend

most of the time in residential buildings, this third part of my Ph.D. dissertation

investigates the effects of the periodic operation of residential fan on the transport of

gaseous and particulate pollutants.

4.3.1 Study design

This study is divided into three stages. First, experiments measured temporal and

spatial concentrations of gaseous and particulate pollutants in a typical residential

environment with a short-term point source release. Second, the experimental results

validated the accuracy of models that calculated the spatial and temporal distribution of

particulate and gaseous pollutants. Finally, when a sufficiently accurate CFD model was

established, the model was used to investigate spatial and temporal pollutant

concentrations with the two characteristic airflow regimes: (1) mixing flow (fan on) and

(2) buoyancy driven flow (fan off).

4.3.2 Experimental measurements

The experiments with the buoyancy driven flow were used to develop high quality

mock-up tests, given the challenges in modeling the turbulence with the buoyancy driven


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flow. Figure 4 shows a schematic diagram of the experimental set-up including the

environmental chamber equipped with a thermal manikin, displacement diffuser, and

indoor heat sources. The small amount of cool air was supplied at the floor level by a

displacement diffuser, simulating an indoor environment with infiltration. The supplied

air was raised by heat sources in the space, generating buoyancy-induced airflow. Heated

boxes and floor heating panels simulated indoor heat sources, such as a computer and sun

patches on the floor. Using this experimental set-up and characteristic indoor airflow with

dominant buoyancy forces, validation data were collected. Air velocity, temperature, and

spatial and temporal distributions of tracer gas and particles were measured for validation

test cases. A summary of monitoring devices and sampling procedures for data collection

are described in Appendix C (pages 124-125).

Figure 4 Experimental setup for the mock-up tests, showing the air handling unit, amanikin, heat sources, and a displacement diffuser.

4.3.3 CFD validation: unsteady pollutant flow analysis

The experimental data was used to validate the quality of data produced in the

CFD simulations. All the simulations were carried out using CFD software FLUENT


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(2006). Based on the recommendations provided in previous CFD validation studies

(Chen and Srebric 2002; Srensen and Nielsen 2003), the parameters in the CFD model,

which include the computational grid, turbulence model, boundary conditions, near-wall

treatment, calculation time step and number of particles, were adjusted to establish a

reliable CFD model.

To simulate turbulent eddies associated with buoyancy driven flow, the RNG k-

model was applied as a turbulent model. The application of the RNG k- model was

based on previous studies (Chen 1995; Posner et al. 2003), which reported that the RNG

k- turbulence model best predicts the turbulent indoor airflow among two-equation

turbulence models. The spatial and temporal particle concentrations in the chamber were

modeled using Lagrangian particle modeling, which determines particle trajectory based

on the particle momentum equation (Zhang and Chen 2006). The detailed information on

the Lagrangian particle tracking model, boundary condition, and sensitivity analysis is

available in Appendix C (pages 129-130)and Appendix E (pages 175-183).

4.3.4 Prediction of pollutant distribution using validated numerical model

The validated CFD model calculated transient gaseous and particulate

contaminant transport under two airflow regimes: (1) momentum driven mixing flow (fan

on) and (2) buoyancy driven flow (fan off). Figure 5 shows the geometries of the

numerical models used to simulate the mixing flow and buoyant flow, in a room with an

air exchange rate of 2.7 hr-1. The momentum of the air supply jets (Figure 5a) creates air

mixing typical for a residential space with air-conditioning, whereas the low velocity air

supply from the displacement ventilation diffuser (Figure 5b) represents a naturally

ventilated space in which buoyant airflow is dominant. In both cases, SF6 gas and

particles were steadily injected for two minutes and monitored for an hour at two

characteristic sampling positions S1 and S2, located 25 cm above the manikins head and


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120 cm above the heated box, respectively. The pollutant concentrations monitored at the

two sampling positions illustrate characteristics of occupant exposure and pollutant

transport in the vicinity of the heat source. The CFD results show the dependence of the

pollutant distribution on the flow condition in the room (fan on or off).

a) Room with mixing flow b) Room with buoyant flow

Figure 5 Geometry of models used to simulate momentum driven mixing flow (a) andbuoyancy driven flow (b).

4.4VENTILATION EFFECTIVENESS AS AN INDICATOR OF PARTICLE

CONCENTRATION

Given that the airflow distribution determines transport and removal of air

contaminants, the correlation between the ventilation effectiveness and particle

concentration was examined. The study design and simulation matrix are presented as

follows.

4.4.1 Study design

To examine the relationship between ventilation effectiveness and particle

concentration, an experimentally validated CFD simulation was applied. The validation

experiments were conducted with the full scale environmental chamber featuring a

partitioned office space with heat sources in it. The experimental setup, measurement


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procedure, and sampling apparatus are described in Appendix D (pages 150 151). The

CFD calculations of age-of-air, particle transport, sensitivity analysis are described in

Appendix D (pages 152-154). The validated CFD model was used further to simulate

age-of-air and particle dispersion in a total of 54 cases in which source location, airflow

pattern, and particle size varied.

4.4.2 Simulation matrix

The validated CFD simulation was used to perform parametric analysis. The

variables controlled for the parametric analysis are as follows:

- 3 ventilation strategies: floor air supply, ceiling air supply, all air-heating

- 3 ventilation rates: 1.93 hr-1, 3.85 hr-1, 7.72 hr-1

- 3 source locations: floor source, source in thermal plume, momentum source

- 2 particle sizes: 1 m and 7 m particles

The details of each variable and simulation geometry (4 6 2.7 m 3 room) used

in the parametric analysis are presented in Appendix D (pages 157). Based on the matrix,

a total of 54 cases with 9 airflow patterns (3 ventilation strategies and 3 ventilation rates)

and 6 different particle sources (3 source locations and 2 particle sizes) were simulated.

The particle tracking model simulated dispersion of an instantaneous particle

release and the results show the non-uniform temporal and spatial concentration in the

space. For each of 54 simulated cases, the normalized particle concentration (CN) is

calculated as the ratio between the mean concentration of particles in a considered zone

and the mean concentration in the case of perfect mixing. The mean concentration

represents the average spatial values integrated over the period of 1.5 hours. The

integration time period was selected to ensure that the particle concentration in the space


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decayed to the level close to the background before the release of particles. For perfect

mixing condition, normalized particle concentration CN is equal to 1. Larger CN values

indicate higher occupant exposure than perfect mixing, and lower values lower exposure.

The normalized particle concentration (CN) can have values from 0 to infinity,

whereas ventilation effectiveness (VE) defined by air-change efficiency ranges from 0 to

2. Also, a larger VE value indicates good ventilation performance, while CN has the

opposite trend: a smaller value indicates lower exposure to particles. The discrepancy in

the limit values for CN and VE and the opposite trend in the scale poses difficulties in

directly comparing CN and VE. Therefore, a parameter describing reduction of particles

(RP) in a considered zone was developed as follows:

CNRP

+=

1

1(2)

RP ranges from 0 to 1, and for perfect mixing, the value is equal to 0.5 (CN = 1).

RP values less than 0.5 represent that the considered zone is more polluted than perfect

mixing condition (CN > 1), whereas an RP value larger than 0.5 reflects that the

considered zone is less polluted (CN < 1) than perfect mixing.

VE is the only function of distribution of age-of-air (airflow pattern) in a space,

while RP indicates particle removal in a considered zone compared to perfect mixing.

The comparison of VE and RP enabled the investigation of the relationship between

airflow distribution and particle pollution in two considered spaces: the whole room and

breathing plane for a sitting person. The breathing plane was defined as the fluid box 0.6

m away from the chamber wall with the height ranging from 1.0 to 1.2 m above the floor

(an average height of 1.1 m).


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The detailed simulation boundary conditions and the corresponding air speed in

the whole room and breathing zone are illustrated in Appendix D (page 165). Also, more

information on the VE is presented in pages 7-8 in the Literature Review, Section 2.


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5. RESULTS AND DISCUSSION

The results of the present work are organized in sections according to the four

major research questions. The following four sections discuss the airflow and pollutant

concentrations in the vicinity of a human body, evaluate the breathing concentrations of

ozone and reaction products, analyze pollutant distribution in the occupied space as a

function of the airflow pattern, and investigate the correlation between ventilation

effectiveness and particle concentration.

5.1AIRFLOW AND POLLUTANT TRANSPORT IN THE OCCUPANTS VICINITY

The first research question focused on effects of breathing, room air mixing, and

occupants movement on airflow and particle transport in the vicinity of the occupant.

The question is addressed in the following three subsections: 1) effects of breathing, air

mixing, and occupant movement on airflow in the occupants vicinity; 2) effect of

breathing on particle transport around an occupant; and 3) air quality in the vicinity of an

occupant depending on room air mixing.

5.1.1 Effects of breathing, air mixing, and occupant movement on airflow in theoccupants vicinity

Figure 6a shows the effect of breathingon velocity profiles observed above the

head (average of velocities at position V1-V8 in Figure 1) and the breathing zone (V9 in

Figure 1). Figure 6a indicates that the breathing jets directly affect the airflow in the

breathing zone, whereas the change in the mean velocity above the head due to the

breathing is negligible. Periodic oscillation in the velocity above the head (profile of

velocity in Figure 6a) indicates that the thermal plume generates an airflow field with

turbulent eddies above the head. The average velocity above the head is approximately

0.21 m/s and this value is similar to the maximum air speed (0.23m/s) above the head


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reported in a previous review (Gao and Niu 2005). Results in Figure 6 show that there is

very little change in the average velocity above the head with breathing activation. This

result suggests that the breathing jet of a sedentary person does not significantly affect the

buoyant thermal plume.

Figure 6b presents the effect of air mixing. The results in Figure 6b show the

velocity profiles with the two fan operation modes: fan on and fan off. When the fan is

off, the velocity above the head (average of V1-V8 in Figure 6b) and velocity in the

stagnation zone (V15 in Figure 6b) are 0.20 m/s and 0.05 m/s, respectively. This four-

fold difference in velocity is due to the buoyancy driven airflow from the occupant being

dominate when the fan is off. When the ventilation fan is on, however, the difference

between airflow velocities above the head and at the location out of the thermal plume

(V5) decreases, suggesting that intensive air mixing occurs in the space with the fan

operation, both in the thermal plume and surrounding air. Figure 6b indicates that the

transition time between the two fan operation modes is approximately 60 sec. This

transition time is relatively short compared to the typical length of fan-on and fan-off

periods. This result implies that, depending on the fan operation, the airflow in a

residential building is primarily mixing flow or buoyant driven flow, with a short

transition time between the two. Even though the results is not shown here (detailed

results are provided in Appendix A, page 69 Figure 4b), the effects of an occupants arm

and hand movements on occupant thermal plume are small. The occupants localized

motions such as typing or filing seem to have smaller influences on the airflow

surrounding an occupant compared to a moving person. Bjrn and Nielsen (2002)

indicated that a moving person walking by a seated person creates strong air movements

due to the wake behind the walking person. Their results show that the wake is strong

enough to disrupt the thermal plume surrounding the seated person.


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(a)Velocity profiles at two sampling points (25 cm above the head and 5cm in front ofthe mouth) with and without breathing

(b) Velocity profiles at two sampling points (25 cm above the head and room corner)with two fan operation modes: fan ON and fan OFF

Figure 6 Velocity profiles at characteristic sampling points with changing parameters:breathing, hand movement and mechanical fan operation

5.1.2 Effect of breathing on particle transport around an occupant

The effects of breathing of the thermal manikin on inhaled concentrations of 0.77

and 3.2 m particles in the breathing zone are provided in Appendix A (page 71). The

results show that particle concentrations in the breathing zone either decrease or increase

with breathing activation depending on the particle size and source position. The changes

in particle concentrations after the breathing activation are approximately 30% for 3.2 m

particles and 15% for 0.77 m particles. Consequently, the effect of breathing is likely


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more important for evaluating exposure to larger particles. One study that analyzed

gaseous pollutants and breathing (Melikov and Kaczmarczyk, 2007) also reports that

breathing affects the inhaled gas concentrations. However, the study shows that the

inhaled concentration of gaseous pollutants can be measured with accuracy of 5%

without taking into account the breathing of thermal manikin. This is in the case where

the sampling location is less than 0.01 m from the occupants upper lip. This dissertation

research and the study conducted by Melikov and Kaczmarczyk (2007) suggest that

human breathing has a larger effect on particles than on gases and that the effect

increases with the size of the particles.

One limitation of the results is that the experiments only consider adiabatic

breathing. Detailed information on effects of humidity and temperature of exhaled air on

the airflow and pollutant transport around the body are described in the paper by Melikov

and Kaczmarczyk (2007)

5.1.3 Air quality in the occupants vicinity depending on air mixing

The air quality in the manikins vicinity depending on air mixing is illustrated in

Figure 7. The results show the concentration of particulate and gaseous pollutants in the

vicinity of the seated thermal manikin with the pollution sources in the manikins vicinity

at floor level (Source Position 2 in Figure 2), for both mixing and stratified flow in the

space. The results indicate that with mixing airflow in the space, the concentrations of

tracer gas (SF6 in Figure 7a), and particles (0.77 m particles in Figure 7c) at all the

sampling points in the manikins vicinity are similar to the ambient concentrations,

regardless of the source location and particle size (Results for other particle sizes are

shown in Appendix A, pages 74 and 80). This uniform concentration field of particulate

and gaseous pollutants can be explained by the intensive air mixing shown in Figure 8a.

The highly mixed flow produces relatively uniform concentrations in the occupant


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vicinity and the space. In this case, the effect of the thermal plume on pollutant transport

mechanism is very small compared to the effect of the air mixing in the space.

Figure 7 Distribution of SF6 gas and 0.77m particles in the vicinity of the manikin with(a, c) forced-convection mixing flow and (b, d) stratified flow

With the stratified flow, which is the case when the ventilation is off, non-uniform

concentration patterns are observed due to the occupant thermal plume (Figures 7b, 7d).

The airflow distribution associated with the occupant thermal plume in the room with the

stratified flow is shown in Figure 8b. It seems that the thermal plume drives the pollutants

to the upper region all around the body, causing the highest concentration above the head.

With the particle source at floor level and in near proximity to an occupant, inhaled

particle concentrations (concentration at mouth) are up to three times higher than the

ambient concentrations (Figure 7d). This finding implies that the occupant thermal plume

may play a significant role in transporting pollutants from the floor level to the breathing

zone. The non-uniform concentration observed with stratified flow also suggests caution

in estimating inhalation exposure using a well-mixed mass balance model for this flow

regime.


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Figure 8. Room airflow distribution simulated with (a) forced-convection ceiling airsupply (mixing flow) and (b) low-momentum floor air supply (stratifiedflow)

The difference between inhaled concentrations and ambient concentrations is

larger for particles than gases (Figure 7b, 7d). The highest inhalation exposure compared

to the ambient level was observed for coarse particles (3.2 m, results are presented in

Appendix A 80). These coarse particles are the most likely to be resuspended by human

activity, such as walking and vacuuming (Ferro et al. 2004a). Therefore, it seems

reasonable to conclude that thermal plume is one of major contributors to inhalation

exposure to resuspended particles in a space with stratified flow.

5.2TRANSPORT OF REACTIVE GASES IN THE VICINITY OF AN OCCUPANT

Given the importance of the environment surrounding a human body in occupant

exposure, the second research question relates to ozone reaction with reactive occupant

surface. The study results are presented in the following subsections: 1) CFD validation

with experimental measurements, 2) distribution of ozone concentration surrounding an


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occupant, and 3) the parametric analysis results for occupant exposure to ozone and

reaction products.

5.2.1 CFD validation with experimental measurements

Before the CFD models were used for analysis of ozone concentration in the

vicinity of a human body, the CFD models were validated. The emphasis of validation

efforts was on the accurate calculation of mass transfer through the surface boundary

layer. The CFD validation results indicate that the cell size distribution (1mm, 3mm, and

10mm) adjacent to the reactive surface moderately affects the air velocity and mass

transfer rate. The percent difference in the measured and calculated mass transfer

coefficient ranges from 15 to 38%, with the better results for cases with finer grid

resolution in the boundary layer. Possible reasons for these differences in the measured

and simulated mass transfer coefficient are inaccuracy of experimental measurements,

imperfect CFD turbulence model, and inaccuracy of the model boundary conditions such

as heat flux or air exchange rate (detailed validation results are provided in Appendix B,

page 100). Considering the variation in sizes and geometry of occupants, the mass

transfer coefficient between different occupants can be much larger than the difference

between the measured and experimental results. Therefore, the validation results suggest

that the accuracy of the CFD model is sufficient to give insight into ozone mass transfer

in the vicinity of an occupant and in the space.

5.2.2 Distribution of ozone concentration surrounding an occupant

The validated CFD model simulated the concentration gradient surrounding an

occupant with a realistic geometry, as shown in Figure 9. The scale represents the

concentration at that location normalized by the chamber inlet concentration. Figure 9

suggests that the thermal plume draws air up and across the reactive occupant surface,


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and the boundary layer consequently becomes depleted of ozone (~20% of the inlet

value) and conversely enriched with reaction products. The breathing zone, as defined as

a 0.5 liter air volume below the nose tip, encompasses a region with ozone levels that are

approximately one-third to one-half the level in the bulk air region (1 m from the body).

This simulation result should be analyzed with caution because the effect of respiration

on flow was not taken into account. However, the uncertainty due to the breathing (up to

30% at a distance of 0.15 m from the mouth based on Melikov and Kaczmarczyk, 2007)

is in the range of the accuracy of CFD simulation, and the results can be used as a proxy

for the general pattern of ozone distribution around an occupant.

Figure 9 (a) Occupant thermal plume for air exchange rate 0.5 h-1

: mean velocitymagnitude around the body = 0.1 m/s. (b) Contour of ozone concentration(normalized by chamber inlet concentration) around the body and samplingregion for inhaled concentration (0.5 h-1).

5.2.3 Parametric analysis results

Knowing that the occupant is surrounded by a sheath, or personal cloud, of ozone-

depleted, reaction product enriched air, scaling analysis results were analyzed with

different ventilation conditions. Figure 10 shows the average air speed in the occupant

surface boundary layer, the ozone decay rate (kozone), the breathing zone ozone ratio (rO3),


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and the breathing zone reaction product ratio (rORPHS) as a function of air exchange rate

() for ceiling and floor inlet simulations.

Figure 10a indicates that for air exchange rate of < 5 hr-1, the air speed in the

skin boundary layer changes little with increase in . his result suggests that when

< 5 hr-1, the thermal plume dominates the airflow close to the occupant. For > 5 hr-1,

the air speed around the occupant increases significantly as increases for CASE I (floor

supply in Figure 3), but changes little for CASE II (ceiling supply in Figure 3). In CASE

I, the jet of air from the floor supply across the occupants feet intensifies the velocity

around the occupant surface. Conversely, in CASE II, the jet from the ceiling supply

circulates along the chamber surfaces including the ceiling and walls before approaching

the occupant. The circulated jet does not affect the airflow around the occupant as much

as the direct floor supply jet. The detailed description of airflow with each air supply

pattern at the highest is described in Appendix B (page 104).

Figure 10b shows that the difference in ozone decay rate between the floor and

ceiling supply is slight for < 5 h-1, but the difference widens above this air exchange

rate limit. Comparison of Figures 10a and 10b suggests that an increase in the air speed in

the surface boundary layer leads to an increase the in the mass transfer rate, enhancing

ozone deposition onto the occupants surface.


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Figure 10 Average air speed in the skin boundary layer (a), ozone decay rate (b), ozone

ratio (c), and ORPHS ratio (d) as a function of air exchange rate for the twocharacteristic airflows: CASE I (floor supply) and CASE II (ceiling suppl

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Eval of Human Exposure to Airborne Pollutants