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Performance of a CO2-based demand controlled dual core
energy recovery ventilation system for northern housing
experiencing varying occupancy
Boualem Ouazia1
*
, Chantal Arsenault1, Sador Brhane1, Daniel Lefebvre1, Gang Nong1, Sandra Mancini1, and Patrique
Tardif1
1Construction Research Centre, National Research Council Canada, Ottawa, Ontario Canada
Abstract. Indoor air quality and health are major areas of concern in northern and remote communities
where homes experience varying occupancy, often overcrowding and are influenced by ventilation.
Heat/energy recovery ventilators installed in the north are selected to provide required minimum ventilation
rate set by ventilation standards (ASHRAE 62.2, etc.). Northern overcrowded homes become under-
ventilated, leading to deteriorated IAQ, mold and health-related problems. This paper present results from a
side-by-side testing of a CO2-based demand-controlled ERV versus a constant air flows ERV, using twin
houses with simulated occupancies. The control strategy was based on the difference in CO2-concentration
between exhaust/return air from the house and outdoor air. The implemented strategy based on a CO2 sensor
network connected with an ERV continuously exhausting stale air from kitchen and bathrooms was simple
and efficient in adjusting ventilation rate based on occupancy rate. The CO2-based demand-controlled ERV
provided a much better control of indoor CO2 concentrations in the main floor and master bedroom, and
with lower CO2 concentrations in bedrooms during night time, compared to the reference house with
concentrations exceeding 2000 ppm. However, the CO2-based demand-controlled ERV had higher power
consumption than conventional ERV with constant air flows.
1 Introduction
In order to provide a healthy indoor environment
for building occupants, most jurisdictions prescribe
residential ventilation rates based on the size of the
space and the number of anticipated occupants. These
ventilation rates are intended “to provide indoor air
quality that is acceptable to human occupants and that
minimizes adverse health effects” [1, 2]. As interest in
energy conservation grows, balanced supply and
exhaust systems are becoming increasingly popular in
cold climates because they allow for waste heat to be
recaptured from exhaust air. Balanced residential
ventilation systems such as heat/energy recovery
ventilation systems also allow for pre-filtration of
supply air and prevent depressurization, which can have
negative effects on indoor air quality [3]. ASHRAE
ventilation standard [1] and the National Building Code
[4] set the required (constant) ventilation rate, calculated
on the basis of fixed liveable floor area and fixed
number of bedrooms or people. HRV/ERV units are
selected to meet the required ventilation and their
selection is based on the calculated minimum ventilation
rate. Canada’s northern and remote communities face an
acute overcrowding housing crisis which threatens their
*
Corresponding author: boualem.ouazia@nrc-cnrc.gc.ca
health and safety. In Nunavik alone, over half of the
Inuit families live in overcrowded housing, and in too
many communities, up to 15 people, including young
children, live in small three bedroom units.
Overcrowding continues to have serious public health
repercussions throughout Inuit territories. High levels of
respiratory infections among Inuit children, such as
chronic lung disease developing after lower respiratory
tract infections, are also linked to crowding and poorly
ventilated homes [5]. For northern housing experiencing
varying occupancy (often overcrowding) and indoor
conditions (high indoor activities), to ensure good
indoor air and environment quality, finding optimal
mechanical ventilation solution is the concern in
northern residential well-insulated dwellings.
HRVs/ERVs installed in northern communities offer
constant airflows and constant ventilation rate that is
often not adequate for varying and high occupancy
situations common in northern and remote communities,
leading to deteriorated indoor air quality (IAQ). To
better address IAQ under varying occupancy and indoor
environment conditions seen in northern and remote
communities, ventilation needs to become smarter. The
key of the smart heat/energy recovery ventilation
concept is to use controls to ventilate more at times
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© The Authors, published by EDP Sciences. This is an open access article distributed under the terms of the Creative
Commons Attribution License 4.0
(http ://creativecommons.org/licenses/by/4.0/). s
when it provides either an energy or IAQ advantage (or
both) and less when it provides a disadvantage. The
fundamental goal of this concept is to adjust ventilation
provision of outdoor air) according to indoor needs and
provide required ventilation to maintain a comfortable
and healthy indoor environment [6]. In this study, a
simple strategy for residential demand-controlled
heat/energy recovery ventilation has been investigated
through the assessment of the performance of a CO2-
based residential dual core ERV system to better control
the indoor CO2 concentrations when a house is
experiencing varying occupancy or overcrowding. The
control is based on the measured difference in CO2-
concentration between the return air from indoor to the
ERV and the outdoor air. The main objective of this
paper is to evaluate the effect of CO2-based demand-
controlled ventilation applied to an energy recovery
ventilation system on: zonal indoor CO2 concentrations
and control, and the power consumption of the demand-
controlled ERV.
Method
The Canadian Centre for Housing Technology’s
(CCHT) twin houses were used for the comparative
side-by-side testing between a CO2-based demand-
controlled dual core ERV (installed in the Test House)
and a conventional single core ERV with constant air
flows (installed in the Reference House). The presence
of people is based on the difference in CO2
concentration between the ERV’s exhaust air and
outdoor air intake. The CO2-based DCV strategy was
implemented to the dual core ERV installed in the Test
House. CCHT Houses are unoccupied, automated CO2
dosing systems were designed and deployed in both
houses to simulate variable occupancies through
automated zonal controlled CO2 dosing strategy. The
concentration level of indoor carbon dioxide is a good
indicator of the occupancy rate while protecting the
personal privacy of dwelling residents. CO2 sensors are
easy and relatively cheap to install compared to other
techniques for occupant detection.
1.1 Control strategy
The implemented control strategy was based on
the CO2 concentration difference between outdoor and
ERV’s exhaust air from indoor, and the difference in
CO2 concentration was used to determine occupancy.
Assuming return air from indoor CO2 concentration
equal to the outdoor concentration when the space is
unoccupied (time 0), and with development of a
difference in CO2 concentration in situations when one
person enters the bedroom at up to 4 flow rates. This
ventilation strategy switches the air flows between up to
4 flow rates controlled by the speed of the fans - supply
air flow controlled by the speed of the supply fan and
the exhaust air flow controlled by the speed of the
exhaust fan of the ERV. The low air flow is used for an
unoccupied house and it is adjusted (demand-controlled)
for increased occupancy rates. This control strategy was
based only on measurements in the ERV unit that
control the speed of the supply and exhaust fans, to make
the system less expensive. A threshold for CO2
concentration between 100 and 200 ppm is suitable to
ensure that the system switches to the high ventilation
rate shortly after people enter the bedroom [6]. The
proposed CO2 sensor network or system consists of CO2
sensors and a central computer. Measurement results at
the intake and the return to the ERV are transmitted to
the central control computer via wired communication.
The CO2 sensors have a wide measuring range of 0-5000
ppm. Their output is an analog voltage, which linearly
varies with sensed CO2 level. As a result, the output
voltage of this CO2 sensor precisely indicates ambient
CO2 level. The output voltage of a CO2 sensor should
respond to timing-varying space occupancy (varying
indoor CO2 concentration).
1.2 Side-by-side testing
The side-by-side testing methodology using the
CCHT twin houses enabled a whole house evaluation of
the impact of the CO2-based demand-controlled dual
core ERV system. The side-by-side testing involved first
benchmarking the houses for a set of operating
conditions and simulated occupancy, using existing high
efficiency single core ERVs originally installed in each
house, followed by installing the dual core ERV unit in
the Test House basement and making no other
modifications to the house, then programing the dual
core unit to match the single core ERV supply and
exhaust airflows in the Reference House, and finally
monitoring the performance of the two houses side-by-
side for four weeks during winter. The side–by-side
testing – dual core ERV versus single core ERV – was
done with continuous mixing, 100% central fan
operation at low speed when there is no call for heating.
ERVs are partially dedicated systems with a direct
connection of the supply air stream to the air handler air
return, and stale air drawn from kitchen and bathrooms,
as shown in Figure 1.
Fig. 1. ERV in conjunction with forced air system.
ERVs were instrumented with temperature and
humidity sensors, and two air flow meters to monitor the
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supply and exhaust airstreams. The dual core ERV has
a dedicated DAS and laptop, with a program that
controls the change in the relative fan speed to adjust the
supply and exhaust air flows. Indoor conditions in terms
of temperature, relative humidity and CO2 concentration
were measured in both houses and in zones with
simulated occupancy; main floor (MF), master bedroom
(MBR), bedroom 2 (BR2) and bedroom 4 (BR4), using
Hobos data loggers.
1.3 Testing procedure
Measurements have been performed over three
periods with respectively simulated occupancy of two
adults + two children, four adults + four children and six
adults + four children. The ventilation rate required by
the North American ventilation standard (ASHRAE
2017) is 0.3 cfm (0.15 L/s) per m2 required by the
building plus 7.5 cfm (3.5 L/s) per person (number of
bedroom + 1) required by people. Testing have been
done for normal operation of the single core ERV in the
Reference House with a constant air flows of 85 cfm (40
L/s) and the dual core ERV in the Test House set at its
minimum air flows of 75 cfm (35 L/s) and demand-
controlled to up 150 cfm (71 L/s) based on the difference
in CO2 concentration between return air from indoor to
the ERV and outdoor, as shown in Table 1.
Table 1. Fan’s relative speed for control strategy.
Speed
SA Fan
(%)
RA Fan
(%)
CO2
threshold
(ppm)
Flow
(L/s)
[cfm]
1
47
40
< 150
35 [75]
2
58
48
> 150
47 [100]
3
70
57
> 300
59 [125]
4
79
63
> 450
71 [150]
Simulated occupancies were achieved in
designated zones shown in Figure 2; main floor [M]
(open area with kitchen, dining/living areas and
bathroom), master bedroom [1] on the second floor
(with automated door and a master bathroom with door
open), bedroom 2 [2] and bedroom 4 [4] on the second
floor with automated doors. Both houses had bedroom 3
[3] on the second floor with door open and no simulated
occupancy, and a bathroom with open door.
Fig. 2. Designated zones for simulated occupancy.
The twin houses were unoccupied and required
simulation occupancy achieved by automated CO2
dosing systems. Two automated CO2 dosing systems
were designed and used to simulate identical zonal
occupancies in both houses. The dosing systems were
designed with a 4-channel stand-alone microprocessor-
based configurable digital indicator and power supply
capable of interfacing directly to analog mass flow
controllers (MFCs). The instrument configuration and
control was done via the RS-232C interface. The MFC
is an all-metal mass flow meter designed to measure the
flow of CO2 with accuracies of 1% of full scale and 1%
of reading, respectively, and automated CO2 dosing
systems were controlled via dedicated laptop.
A varying 24 hours of zonal simulated
occupancies were performed in both houses from 0:00
to 24:00 as presented in Table 2. Adult bedroom with
one male and one female sleeping in the bedroom is
simulated by a CO2 dosing flow of 0.216 L/min, child’s
bedroom with one male and one female sleeping in the
bedroom is simulated by a CO2 dosing flow of 0.150
L/min and a residence (common areas such as dining
room, living room, etc.) with two adults (one male and
one female) and two children (one male and one female)
is simulated by a CO2 dosing flow of 0.240 L/min [7].
Table 2. Fan’s relative speed for control strategy.
Zone
1
2
3
Start Time
(Duration)
Overnight
MBR
2 adults
2 adults
2 adults
+
2 children
0 :00
(6 hrs 45 min)
BR2
0
2 adults
2 adults
0 :00
(6 hrs 45 min)
BR4
2 children
4 children
2 adults
+
2 children
0 :00
(6 hrs 45 min)
Morning/Breakfast
MF
2 adults
+
2 children
4 adults
+
4 children
6 adults
+
4 children
7 :00 (1 hr)
Noon/Lunch
MF
2 adults
+
2 children
4 adults
+
4 children
6 adults
+
4 children
12:00 (1 hr)
Evening
MF
2 adults
+
2 children
4 adults
+
4 children
6 adults
+
4 children
17:30
(3 hrs 30 min)
MF
2 adults
4 adults
6 adults
21:00 (2 hrs)
MBR
2 adults
4 adults
2 children
21:00 (2 hrs)
MBR
2 adults
+
2 children
23:00 (1 hr)
BR2
0
2 adults
2 adults
23:00 (1 hr)
BR4
2 adults
4 adults
2 children
21:00 (2 hrs)
BR4
2 adults
+
2 children
23:00 (1 hr)
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2 Results and discussion
The difference in CO2-concentrations between the
exhaust air and the outdoor air was used to determine
occupancy with the assumption that for a difference in
CO2-concentrations below 150 ppm between the
exhaust air from indoor and outdoor air, the house is
empty (no presence of people). Results are presented as
the difference in CO2-concentration between the
extracted air and outdoor air and the relative supply and
exhaust fans speeds. Figure 3 shows the typical 24-hours
demand-controlled ventilation in the test house for
Period 3 with occupancy of 6 adults and 4 children.
Results are presented as the difference in CO2-
concentration between extracted air and outdoor air and
the relative supply and exhaust ERV fans speeds. The
plots show clearly that the high ventilation rate is active
when one of the threshold values are exceeded.
Fig. 3. Difference in CO2 concentration and relative fan’s
speeds for period 3.
The difference in CO2-concentration between
extracted air and outdoor air exceeded the three
thresholds of 150 ppm, 300 ppm and 450 ppm during
period 3, and the CO2-based demand-controlled dual
core ERV fans switched between speed 1 and speed 4.
Table 3 shows the fraction of time during measured
periods 1, 2 and 3 the fans were on speed 1, speed 2,
speed 3 and speed 4.
Table 3. Fraction of time fans were on each speed.
Period
Speed 1
Speed 2
Speed 3
Speed 4
1
40%
60%
0%
0%
2
10%
39%
50%
1%
3
2%
29%
50%
19%
During Period 1, the CO2-based DC dual core
ERV was running 40% of the time on speed 1 and 60%
of the time on speed 2. In this case, the ventilation in the
Test House was running with the low ventilation rate of
35 L/s [75 cfm] 40% of the time. With increased
occupancy during Period 2, the supply and exhaust fans
had to switch to higher speeds. The CO2-based DC dual
core ERV was running 10% of the time on speed 1, 39%
of the time on speed 2, 50% of the time on speed 3 and
1% of the time on speed 4. With the highest occupancy
rate of 6 adults and 4 children, the DC dual core ERV
was running only 2% of the time on low speed 1, 29%
of the time on speed 2, 50% of the time on speed 3 and
on the highest speed 4 19% of the time.
Measurements of CO2 concentrations were
undertaken in four zones with simulated occupancy;
main floor (MF), bedroom 2 (BR2), bedroom 4 (BR4)
and master bedroom (MBR). Figure 4 shows a daily
measured CO2 concentration in zones with simulated
occupancies in the Test House equipped with a CO2-
based demand-controlled ERV during period 3. Figure
5 shows a daily measured CO2 concentration in zones
with simulated occupancies in the Reference House
equipped with a conventional constant air flows ERV,
during period 3. The plots of the variation in zonal CO2
concentrations were characterized by four indoor
events; [1] bedtime with bedroom’s door closed, [2]
breakfast time on the main floor, [3] lunch time on the
main floor and [4] family time including dinner time on
the main floor.
Fig. 4. Daily time variations of zonal CO2 concentrations
in Test House during Period 3.
Fig. 5. Daily time variations of zonal CO2 concentrations
in Reference House during Period 3.
The highest CO2 concentrations were measured in
bedrooms during bedtime, with bedroom’s door closed,
exceeding 1200 ppm. This is a result of high people load
in the bedroom with occupancy two adults + two
children sleeping in master bedroom, two adults
sleeping in bedroom 2 and two adults + two children
sleeping in bedroom 4. Bedroom 4 with occupancy of
two adults + two children sleeping during Period 3 had
the highest CO2 concentrations during night time
reaching 1800 ppm in the Test House with demand-
controlled ERV and much higher concentration
concentrations up to 2800 ppm in the Reference House
with constant air flow ERV. Master bedroom with same
occupancy as bedroom 4 of 2 adults and 2 children
sleeping in the room had much lower CO2
concentrations, due to the continuous extraction of air
from the master bathroom by the ERV and with master
bathroom door open to the master bedroom. Stale air
extracted from bedroom 4 was not directly extracted to
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outdoor, but recirculated in the house through the
furnace were it was conditioned and filtered. CO2
concentrations in master bedroom did not exceed 1200
ppm in the Test House during bedtime and reached 1500
ppm in the Reference House. Bedroom 2 with two adults
sleeping in the room were below 1300 ppm in the Test
House during night time and below 1450 ppm in the
Reference House. The main floor area had higher CO2
concentrations exceeding 1000 ppm in the morning
when the whole family was having breakfast, at lunch
time and in the evening between 6 and 11 PM. During
daytime the house is unoccupied and the CO2
concentration drops to values close to the outdoor
concentration.
Figure 6 and Figure 7 show respectively the
fraction of time the measured CO2 concentration in
master bedroom and bedroom 4 exceeded the threshold
of 1000 ppm during Period 1 with occupancy of two
adults sleeping in the master bedroom and two children
sleeping in bedroom 4, a total house occupancy of 2
adults + 2 children. Both houses had CO2 concentrations
in master bedroom 100% of the time below 1000 ppm,
due to the continuous exhaust from master bathroom
with door open to master bedroom by the ERV.
However, measured CO2 concentrations in bedroom 4
with stale air recirculated in the house through the
Furnace for conditioning and filtration and not
exhausted directly to outdoor has exceeded 1000 ppm
20% of the time. All zones had CO2 concentrations
bellow 1200 ppm during Period 1 with a total occupancy
of 2 adults + 2 children, two adults sleeping in master
bedroom and two children sleeping in bedroom 4.
Fig. 6. Fraction of time CO2 concentrations in MBR during
Period 1.
Fig. 7. Fraction of time CO2 concentrations in BR4 during
Period 1.
Figure 8 and Figure 9 show respectively the
fraction of time the measured CO2 concentration in
master bedroom and bedroom 4 exceeded the threshold
of 1000 ppm during Period 2 with occupancy of two
adults sleeping in the master bedroom and four children
sleeping in bedroom 4, and total house occupancy of 4
adults + 4 children (two adults sleeping in bedroom 2).
With higher occupancy during period 2, Figure 8 shows
that measured CO2 concentration in the master bedroom
exceeded 1000 ppm, with 89% of the time below 1000
ppm in the Test House with CO2-based DC ERV and
70% of the time in the Reference House with constant
air flows ERV, and master bedroom measured
concentrations were below 1200 ppm in both houses.
However, Bedroom 4 had much higher CO2
concentrations than master bedroom as shown in Figure
9, with concentrations 34% of time higher than 1000
ppm in the Test House compared to 39% of the time in
the Reference house. Concentrations exceeded 1800
ppm 3% of the time in the Test House compared to 12%
in the Reference House.
Fig. 8. Fraction of time CO2 concentrations in MBR during
Period 2.
Fig. 9. Fraction of time CO2 concentrations in BR4 during
Period 2.
Figure 10 and Figure 11 show respectively the
fraction of time the measured CO2 concentration in
master bedroom and bedroom 4 exceeded the threshold
of 1000 ppm during Period 3 with occupancy of two
adults and two children sleeping in the master bedroom
and bedroom 4, and total house occupancy of 6 adults +
4 children (two adults sleeping in bedroom 2). With the
highest occupancy during Period 3, Figure 10 shows that
master bedroom had CO2 concentrations 40% of the
time higher than 1000 ppm in the Test House and 52%
of the time in the Reference House. Master bedroom had
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much higher concentrations during Period 3, exceeding
1400 ppm 1% of the time in the Test House compared to
25% in the Reference House. Figure 11 shows that
bedroom 4 with higher occupancy of two adults + 2
children sleeping in the room and without direct exhaust
of stale to outdoor by the ERV, had again much higher
concentrations than during Period 2 and master bedroom
during Period 3. Measured concentrations exceeded
1000 ppm were 45% of time higher than 1000 ppm in
the Test House with DC ERV compared to 66% in the
Reference House with constant air flows ERV, 30% of
the time higher than 1400 ppm in the Test House
compared to 37 % in the Reference House, and 3% of
the time higher than 2000 ppm in the Test House
compared to 28% in the Reference House.
Fig. 10. Fraction of time CO2 concentrations in MBR
during Period 3.
Fig. 11. Fraction of time CO2 concentrations in BR4
during Period 3.
The main floor with continuous exhaust of stale
from kitchen and one bathroom had CO2 concentrations
100% of the time below 1000 ppm during Period 1 in
both houses with two adults + 2 children. During Period
2 with occupancy of 4 adults + 4 children, measured CO2
concentrations were 3% of the time higher than 1000
ppm in the Test House compared to 11% in the
Reference House and without exceeding 1200 ppm.
During Period 3 with occupancy of 6 adults + 4 children,
measured CO2 concentrations were 20% of the time
higher than 1000 ppm in the Test House compared to
60% in the Reference House and were below 1200 ppm.
Overall results from the first phase of this research
showed that a simple CO2-based energy recovery
ventilation system was more effective in controlling
indoor CO2 concentrations in zones with continuous and
direct exhaust of stale air to outdoor such as main floor
and master bedroom than zones (bedrooms with closed
door during bedtime) relying on dilution, return of stale
air from bedroom through the furnace and recirculated
in the house. A house with a simple demand-controlled
strategy implemented to an ERV with continuous
exhaust from kitchen and bathrooms improved
significantly the control of indoor CO2 concentrations in
a house experiencing high occupancies and specifically
in bedrooms with closed doors during bedtime.
Table 4 shows the ERV’s power consumption. As
the CO2 concentration in the test house increases, made
the CO2-based DC ERV operate at higher fan’s speeds.
As expected, this caused operation time at high speeds
and higher energy consumption of the ERV in the test
house, increased by 53% between period 1 and period 2
(high occupancy), and by 82% between period 1 and
period 3.
Table 4. Fraction of time fans were on each speed.
Period
Test House
(kWh)
Reference House
(kWh)
Difference
(%)
1
0.877
0.904
-2.9%
2
1.343 (+53%)
0.904
+48.6%
3
1.599 (+82%)
0.895
+78.7%
3 Conclusion
Results revealed that a simple control strategy
based on sensing CO2 concentrations in the outdoor air
and a return air from indoor to the ERV can be effective
in controlling the CO2 concentration in the entire house.
A house with a CO2-based demand-controlled ERV had
a much better control of indoor CO2 concentrations
during high occupancy and bedtime in rooms. A CO2-
based demand-controlled energy recovery ventilation
was more effective for zones with direct and continuous
extraction of stale air to outdoor (such as main floor and
master bedroom), but less effective for bedrooms with
doors closed during sleeping time of the residents.
Bedrooms experienced levels of CO2 concentrations
exceeding 1600 ppm during bedtime. As expected,
demand-controlled ventilation strategy had a negative
impact on the CO2-based dual core ERV power
consumption that increased by up to 82%.
Acknowledgments
The research was funded by Natural Resources
Canada through the Panel on Energy Research and
Development (PERD) and National Research Council
Canada through Action on Air Pollution Horizontal
Initiative (AAPHI).
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