MODELLING THE DISTRIBUTION OF EXHALED CO2 IN AN
ENVIRONMENTAL CHAMBER
Norhayati Mahyuddin 1* and Hazim B Awbi 2
1
Faculty of Built Environment, University of Malaya, 50603 Kuala Lumpur, Malaysia.
School of Construction Management and Engineering, University of Reading, RG6 6AW,
United Kingdom.
2
*
Corresponding author’s email: [email protected]
ABSTRACT
In most buildings, occupants are the main source of indoor Carbon Dioxide (CO2) due to
exhalation. Although CO2 is not considered to pose health risks to occupants, elevated levels
of CO2 may serve as an indicator of insufficient ventilation. This research examines how CO2
is distributed within a room and how this distribution is affected by different ventilation
strategies. Measuring CO2 concentrations at a single location or height may not act as a true
representation of an entire space, unless it is measured in a very small confined space. In
principle, on-site measurements in an enclosed environment give the most realistic
information concerning airflow and air quality, but due to the variability of outdoor
conditions, the estimation using quantitative analysis can be difficult and inaccurate. In this
article, measurements of CO2 concentration have been performed at a number of points in an
environmental test chamber. To complement the experimental results, Computational Fluid
Dynamics (CFD) simulations were carried out and the results enabled detailed analysis and
visualisation of spatial distribution of CO2 concentration and other effects to be predicted.
Keywords: Carbon Dioxide, exhalation, airflow distribution.
1 INTRODUCTION
In-situ measurement in an enclosed environment generally gives realistic information
concerning the air distribution and airflow parameters in the enclosure. However, because
measurements of the distribution of airflow and contaminant concentrations need to be made
at many locations, these can be very expensive and time consuming. In recent years,
computational fluid dynamics (CFD) has been widely used as a method of simulating room
airflow and studying indoor environment issues to gather data that may be difficult to obtain
through measurements and in-situ data collection. Some parameters of high significance (e.g.
CO2 generation rate, the exhalation production mass flow rate, exhalation velocity, etc.) that
are needed as boundary conditions in a CFD model are rather difficult to establish because
researchers’ interpretations of this data vary widely (Gao and Niu 2006; Melikov and
Kaczmarczyk 2007; Shih et al. 2007; Karthikeyan and Samuel 2008; Lin et al. 2011).
Therefore, most researchers have limited their research towards the study of ventilation
effectiveness in indoor environments (Lin et al. 2009; Lu et al. 2010) and the prediction of
airborne disease transmission (Gao and Niu 2006; Rim and Novoselac 2009; Gupta et al.
2010). It is sometimes much more important to ask how the air is distributed into the space
rather than to know the total ventilation flow rate (Awbi, 1998). However, the main
parameters for CO2 measurement strategies, which involve the positioning of CO2 sampling
sensors (i.e. the location and height) and how CO2 is being distributed in the room, have not
been considered methodically. This article tries to deal with some of these issues in a study
involving an environmental test chamber with accurately controlled conditions.
2 METHOD
This study investigates the airflow and CO2 spatial distribution in an enclosed space using
CFD simulations validated by experimental measurements obtained from chamber tests
(Mahyuddin and Awbi 2010). The main focus of this paper is to examine the methods of
simulation that could be used for such a study and establish the most realistic boundary
conditions needed to simulate the production of CO2 through respiration (i.e. exhalation) from
the occupant, and its spatial distributions within a room. The conditions and the modelling of
the spatial distributions of CO2 in the chamber have been modelled using the ANSYS CFX
12.0 code to determine the most physically realistic combination of mass and energy transport
models, fluid properties and boundary conditions. The types of boundary conditions used in
the simulations were wall properties, heat generation, airflow rate at the inlet and the outlet
and CO2 production rate by an occupant (Figure 1).
z = 2.3
inlet
outlet
Fluorescent
lamp
manikin
2.3m
Heat
source
Y=0
Y= 2.8
2.78
m
x=0
Y=2.8
z=0
2.78m
Figure 1 Geometry of experimental chamber.
The behaviour of the exhalation jet would depend on its temperature and momentum, on the
temperature of the room and of other interactions, for example the boundary layer flow
around a person (Bjorn and Nielsen 2002). The respiration process is approximated by a
sinusoidal curve with a frequency of 17 breaths per minute and a volumetric flow rate of 8.4 l
min-1. These values were also used by Gao and Niu (2006) in their research on the human
respiration process and transports of air by breathing, coughing and sneezing. In this research,
the exhalation of CO2 from the person was through the nose. This assumption was based on
the majority (22 out of 23) of volunteers used in the experimental study who breathed through
their noses (Mahyuddin and Awbi 2010).
In this study, a manikin was placed in the chamber that was supplied by air using two types of
a single air inlet, see Fig. 1. The big inlet (Case 1) was 0.4 m wide and 0.065 m high (area =
0.022 m2) and the small inlet was 0.4 m wide x 0.01 m high (area = 0.004 m2). These sizes of
air supply devices were used with the same airflow rate (8 ls-1) to provide different air
velocity outlet from the diffuser. The air supply velocity for each diffuser was:
Low velocity air supply (0.31 ms-1) from the large air inlet (Case 1)
High velocity air supply (2.00 ms-1) from the small air inlet (Case 2)
Visualising results of a person exhaling through the nose using a smoke test and a manikin in
a CFD simulation of an exhalation process are shown in Figure 2. Based on the smoke test
carried out in the chamber (Figure 2a), the jet with exhalation through the nose is directed
downwards from the nostrils with an angle of approximately 45 degree below the horizontal
line which fits well with the observation made by Hyldgaard (1994) and Haselton and
Sperandio (1988). The results in Figure 2b also show that the numerical simulation of the
exhalation jet that is set at a 45 degrees from the horizontal. Therefore, with a nostril diameter
of 12 mm and considering that the flow rate for sedentary activity is around 8.4 l min-1, an
exit velocity of 1.25 m.s-1 is obtained (based on the calculation in Eq.1), with velocity
components in both the z axis (vertical) and x axis (horizontal) directions of 0.885 ms-1. In
reality, due to the body core temperature (normally about 37.2 ºC), the air inhaled is exhaled
at about 34.0 ºC. The velocity vectors for the exhalation region are large in the front side of
the human face from the nose to the lower parts, as shown in Figure 2b. The warm exhalation
jet is observed to entrain more surrounding air from the upper region.
(b)
(a)
Figure 2 Flow field with constant exhalation (measurement) (a) Visualization
(b) Velocity-vector (CFD)
V exit
Q
Q
S
D
2
(Eq. 1)
4
3 RESULTS AND DISCUSSION
Airflow pattern
The supply air jet that enters the room initially forms a layer of fresh air supply along the
ceiling due to the Coanda effect. The results for the simulation of the airflow patterns for
Cases 1 and 2 are shown in Figure 3 and 4 for two different planes. For both Cases, it is
observed that the convective boundary layer around the manikin entrains air from the lower
part of the room, leading it to the breathing zone and into the buoyant plume that forms above
the head. However, there is a marked difference in the airflow patterns between these two
Cases especially near the ceiling (see Figure 3). Unlike the flow pattern in Case 1 (Figure 3a),
the air jet in Figure 3b is observed to be flowing along the ceiling towards the opposite wall
with high velocity, creating a downward airflow pattern along the opposite wall. Case 1
however, downdraft (dumping) occurs towards the seated manikin causing draught in that
region. A clear difference in the airflow pattern can also be seen between the occupied zone
and the upper region in the two Cases (Figures 3and 4). The velocity in the occupied zone for
Case 1 is generally found to be less than 0.15 ms-1. However in the upper zone (i.e. the region
of interaction of the buoyant plume above the head with the ceiling jet), higher velocities in
the range of 0.15 – 0.50 ms-1 are observed.
(a)
(b)
Figure 3 Air flow pattern after one hour of occupancy (a) Case 1 and (b) Case 2 at x = 1.3
(inlet section)
(a)
(b)
Figure 4 Air flow pattern after one hour of occupancy(a) Case 1 and (b) Case 2 at x = 1.6
(body section)
When a cold jet with a low velocity (0.31 ms-1) is supplied over a ceiling, it is possible that it
will separate (a phenomenon called dumping), the jet drops into the occupied zone. As a result
a stagnant region develops from the point of separation to the opposite wall as shown in
Figure 3a. Therefore, not only the flow domain will be significantly distorted by the jet
separation, it would further reduce the availability of fresh air in most locations in the
chamber. Conversely, in the case of the higher jet inlet velocity (Figure 3b) it is observed that
the jet can actually reach the opposite wall and then deflects down into the lower parts of the
room. Therefore, most of the occupied zone will be provided with a sufficient fresh air. In
addition, it can also be seen that no separation region appears in the middle of the ceiling.
Temperature distribution
The temperature profiles obtained across the side of the manikin body at breathing level were
very similar for both cases. The average temperatures were between 26.0 ºC and 27.0 ºC.
Close to the manikin’s upper body parts, the temperature was around 24.0 ºC. However, a
significant difference in air temperature profiles was observed at the lower region of the
chamber and along the ceiling plane for both cases. In Case 1 the temperatures at the lower
region (i.e. in range 20.0 ºC – 21.0 ºC) are significantly higher than in Case 2 (i.e. in the range
18.0 ºC – 20.0 ºC). In general, the effect of high velocity at the inlet air supply seems to lower
the temperatures in the lower region of the chamber.
Thermal plume above the seated manikin
Within the indoor environment, a human body is not only a heat source but also a potential
source of contaminants. With low supply velocities and poor air distribution (Case 1), the
mean temperature in the chamber based on the measured values was ~ 20.8 ºC. Table 2 shows
that the CFD predictions of the thermal plumes above the manikin’s head are in fairly
reasonable agreement with measured data. The differences observed are less than 0.5 K at
both heights (i.e. 0.2 m and 0.4 m above the manikin’s head), whereas the difference between
the measured data and the CFD results for the maximum velocity above the human head are
even smaller.
Table 2 Air velocity and temperature of the plume above the human head in the chamber:
Measurement and the Simulations
Cases
Case 1
Parameters
Temperature (ºC)
Air velocity (ms-1)
Case 2
Temperature (ºC)
Air velocity (ms-1)
Experiment
Simulation
Experiment
Simulation
Experiment
Simulation
Experiment
Simulation
Height from floor level
1.4 m
21.4
21.9
0.19
0.20
22.0
21.8
0.18
0.19
1.6 m
21.3
21.6
0.19
0.20
21.9
21.6
0.17
0.20
In Case 2, with high air supply velocity and well mixed ventilation, the average temperature
in the experimental chamber was ~ 20.3 ºC. Although this temperature was slightly lower than
in Case 1, the measured temperature for the thermal plumes above the human head was
slightly higher. This was due to jet separation (dumping) from the ceiling for Case 1 which
caused downdraught towards the centre of the chamber. However, as for Case 2, the
temperature difference between the CFD results and those measured is minimal (~ 0.3 K).
The predicted velocity values are also observed to be in agreement with measured data but
slightly over estimated (< 0.03 ms-1 at the height of 1.6m).
CO2 concentration distribution
The CO2 results from the experimental tests are used to validate the results from the CFD
predictions for both Cases 1 and 2. In reality, breathing of human beings is intermittent in
behaviour, i.e. people hold their breath briefly between inhalation and exhalation. However, in
this study only constant exhalation process was simulated (Figure 5).
(a)
(b)
Figure 5 Contours of simulated exhaled breath from the nose of the manikin in the chamber
after 1 hour duration (a) Case 1 and (b) Case 2.
In Figure 5, the flow pattern of the exhaled air is visualised across the body plane at y =1.28m
(i.e. at the centre of the nostrils). Although the boundary conditions of the exhalation are
similar in both cases, the distributions of CO2 exhalation for the two cases are quite different.
This is due to the some entrainment of the (dumped) air jet by the exhalation plume.
5 CONCLUSIONS
The parameters needed to simulate the exhalation of CO2 from a human using CFD were
investigated in this paper. Proper simulation of nose and mouth geometry, i.e. flow
exhalation, will be needed for studying the transport of exhaled air in a room. In the two cases
studied, the simulated temperature and spatial distribution of CO2 concentrations agreed with
the experimental data. The predicted temperature distribution is not sensitive to the flow field
because the general airflow pattern in both cases was close to well-mixed conditions with a
uniformly distributed heat sources. The plume for the exhaled air was found in one case to
interact with other flow phenomena in the room, such as the supply air jet, which influenced
the CO2 stratification in the room. Without such interaction the CO2 concentration around the
breathing zone was found to be higher with a tendency for the person to inhale concentrations
similar to those of ambient air around the breathing zone. On the other hand, with good room
air distribution (i.e. air jet attached to the ceiling) better air movement results and the
distribution of CO2 concentration in the room would move towards a fully mixed situation.
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