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Transcript of 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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Evaluation of Human Exposure to Indoor Airborne Pollutants:
Transport and Fate of Particulate and Gaseous Pollutants
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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Evaluation of Human Exposure to Indoor Airborne Pollutants:
Transport and Fate of Particulate and Gaseous Pollutants
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