Analysis of multiple building overheating assessment metrics for long-term indoor thermal patterns in 12 Canadian cities

Abstract

Climate change is a major contributor to extreme heat events, which have been a threat to the health of building occupants. It has been found that the rates of mortality and morbidity are much higher for urban dwellers during prolonged periods of elevated outdoor temperature. However, only limited studies have been conducted on the current overheating problems in buildings of different Canadian cities. This study considered multiple existing building overheating metrics, and the trend of evolution of indoor thermal conditions has been analyzed through linear regression. To permit analyzing the long-term variation of indoor conditions within typical buildings located in different cities across Canada, a series of building simulations were performed using weather station data over a historical period ranging from 1986 to 2016. Twelve (12) cities across Canada were selected for analysis that was located in different climate zones. This study determined the current overheating conditions under the 31-year historical climate conditions in two (2) building types: schools and offices

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©[2021] National Research Council of Canada
Analysis of multiple building overheating assessment metrics for
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long-term indoor thermal patterns in 12 Canadian cities
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3
Chang Shu1, Abhishek Gaur 2, Lili Ji1, Abdelaziz Laouadi2, Michael Lacasse 2 and
4
Liangzhu (Leon) Wang1*
5
1Department of Building, Civil and Environmental Engineering, Concordia University, Montreal,
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1455 De Maisonneuve, H3G 1M8, Montreal, Quebec, Canada
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2 Construction Research Centre, National Research Council Canada,1200 Montreal Road, K1A
8
0R6, Ottawa, Ontario, Canada
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10
Abstract
Climate change is a major contributor to extreme heat
events, which have been a threat to the health of building
occupants. It has been found that the rates of mortality and
morbidity are much higher for urban dwellers during
prolonged periods of elevated outdoor temperature.
However, only limited studies have been conducted on the
current overheating problems in buildings of different
Canadian cities. This study considered multiple existing
building overheating metrics, and the trend of evolution
of indoor thermal conditions has been analyzed through
linear regression. To permit analyzing the long-term
variation of indoor conditions within typical buildings
located in different cities across Canada, a series of
building simulations were performed using weather
station data over a historical period ranging from 1986 to
2016. Twelve (12) cities across Canada were selected for
analysis that was located in different climate zones. This
study determined the current overheating conditions
under the 31-year historical climate conditions in two (2)
building types: schools and offices.
Key Innovations
 Evaluate the overheating condition in cold
climate regions in Canada
 Compare the difference of the overheating
pattern in 12 cities.
 Evaluate the variation of overheating in the past
31 years.
Practical Implications
Few studies have been conducted on the overheating
conditions in cold climate regions. In this study, the
current overheating conditions are evaluated in typical
buildings of 12 major cities in Canada. The building
simulations employed 31 years of historical data from
observed weather data to capture summertime
overheating conditions in Canada.
Introduction
Building overheating-related studies have been ever
increasing over the past 10 years, and around 40% of these
studies have been contributions from the UK, which is a
temperate climate (Chen 2019). The occurrence of
overheating events with mortality and morbidity have
been more frequent in recent years (Lamothe et al. 2019).
People from cold or temperate climates, such as that of
Canada, maybe more vulnerable than those residing in
other climates because they may be less acclimatized to
warm temperatures and levels of humidity occurring
during extreme heat events, and as well, they may have
limited access to air conditioning (Armstrong et al. 2010).
To the authors' best knowledge, there are still few
discussions of the current status of overheating in cold
climates, particularly in Canada.
In this paper, existing methods for assessing overheating
in buildings have been collected based on examining
public literature, standards, and codes. After that, these
methods are compared using building simulations
undertaken over 31 years, the results of which permit
discussing the strengths and weaknesses of these methods
for different Canadian cities in this study. A combination
of the assessment methods was selected to provide a
comprehensive description of the heat events as occur in
buildings. The method was then applied to evaluate the
annual changes in 12 Canadian cities of overheating in
two (2) types of buildings, including schools and offices,
subjected to historical climate data obtained from multiple
weather stations of Environmental and Climate Change
Canada (ECCC), and as well, long-term climate loads as
may arise in the future. This study provides an answer to
how changes in outdoor weather conditions may affect
indoor building conditions for the long-term duration of
31 historical years.
Methods
12 Canadian cities
Table 1 ASHRAE climate zone of selected cities.
City name
Short name
ASHARE zone
Calgary
CAL
7
Charlottetown
CHA
6A
Halifax
HAL
6A
Moncton
MNC
6A
Montreal
MON
6A
Ottawa
OTT
6A
Saskatoon
SAS
7
St. johns
STJ
6A
Toronto
TNT
5A
Vancouver
VAN
4C
Winnipeg
WIN
7
Whitehorse
WHH
7
In this study, 12 Canadian cities of different climate zones
were selected to investigate building indoor overheating
conditions. The distribution of the 12 cities is plotted on
the map in Figure 1. The ASHRAE climate zones
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(ANSI/ASHRAE 2013) of the cities are shown in
different colors for each of the four (4) climate zones:
 4C: Mixed–Marine
 5A: Cool–Humid
 6A: Cold–Humid
 7: Very Cold
The northernmost city selected in this study was
Whitehorse, which is in climate zone 7 of very cold
climate. The southernmost city is Toronto, in climate zone
5A. The 12 cities are selected to cover different climate
zones in Canada, which can, therefore, represent the
current overheating conditions in Canada.
Figure 1 Distribution of selected Canadian cities and their climate zones.
Figure 2 Boxplot of a) air temperature; b) relative humidity; c) global horizontal radiation;
d) wind speed in the 12 cities.
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Climate data
The climate data are based on historical observations from
multiple climate gauging stations within the selected cities
from Environment and Climate Change Canada (ECCC).
The long-term time-series climate data over the 31 years
(1986-2016) was processed and generated following the
method given by (Gaur et al. 2019): the climate data from
the weather station with the most data available is first
selected for the construction of the long-term climate
dataset; then for the missing data of small gaps, the time
series is fixed by linear interpolation of the most adjacent
data points; while for the missing data of longer-term (e.g.,
more than 12 hours), the climate data from other weather
stations that are close to the objective weather station in the
same city will be used to be merged into the whole time-
series dataset. The climate data from other the reanalysis
dataset are merged into the long-term dataset of the
objective weather station location. The general climate
conditions for air temperature, relative humidity, global
horizontal radiation, and wind speeds of the 12 cities in the
summer over the 31 years are plotted in Figure 2. The first
two largest cities, Toronto and Montreal, have the highest
mean air temperature during summer months (i.e., May to
September) over this period, and the fourth largest city,
Ottawa, is similar to that of Montreal. Due to the sea breeze
on the west coast in the summer, the third-largest city in
Canada, Vancouver, has a much lower air temperature in
summer. The other four cities in zone 6A, Charlottetown,
Halifax, Moncton, and St. John's, all cities located on the
east coast, may have lower air temperature, higher relative
humidity, and higher wind speed than the other two cities,
Montreal and Ottawa, in the same climate zone. The four
cities (Winnipeg, Saskatoon, Calgary, Whitehorse) in the
very cold climate zone (i.e., climate Zone 7) may have
greater air temperature variations because their locations
differ greatly from south to north. They also have higher
wind speed and lower relative humidity. The four largest
cities, Toronto, Montreal, Vancouver, Ottawa, and the three
cities in the very cold zone, Winnipeg, Saskatoon, and
Calgary, have relatively higher global horizontal radiation.
The variation of climate variables over the 31 years is
further discussed in the results section. The current study
assumes the climate condition at the weather stations
represents the climate in the city, so the urban heat island
effect in the city cannot be fully considered. Our future
work will adopt a high-resolution regional climate model
(RCM) to enable more detailed consideration of the spatial
variation of the climate condition in each city.
Building simulation
Two types of buildings were considered in this study:
school and office buildings (Figure 3). The ASHRAE
standard 90.1 for commercial building reference model
(ASHRAE 2013) has been used in this study to evaluate the
indoor overheating condition in the 12 cities in Canada. The
building configuration of the model was also changed for
the four climate zones in Canada to the design conditions
of the 12 different cities, following that given in the
ASHRAE Handbook of Fundamentals (ASHRAE 2009).
The HVAC systems in these building models were
removed to mimic the building's freerunning conditions.
The total building area in this study is 6871m2 for the
primary school and 511m2 for the small office building.
The thermal zone of the school building has been divided
by the function of the rooms to consider the different
classrooms, office, computer classroom, and cafeteria .etc.
The thermal zone of the office room has been divided based
on the orientation of the room and also a core thermal zone
in the centre region.
Figure 3 Building models for office and school buildings
The details of the building envelop for each of the
reference building models are listed in Table 2. The cold
climate region may require higher R-values given the low
values of temperatures during the winter months and
Solar Heat Gain Coefficient (SHGC). This study
examined how the indoor heat condition may change in
these buildings in different cities during the summertime.
The infiltration rate for the school buildings is 0.37 ACH,
and 0.45 ACH for office buildings. The orientation of the
buildings is configured to have the longer building façade
facing the south. The window-wall ratio of the small
office building is 21.20%, and 35% for the primary school
building. More details regarding the configuration of the
reference building models can be found in (Deru et al.
2011)
In this study, the reference buildings with one floor are
considered, and the results for the multi-storey buildings
will also be evaluated in the future. The room thermal
zones on the south side are considered for the analysis
because it is exposed to more direct solar irradiation,
which, therefore, may have a higher internal temperature.
Table 2 Building envelope of reference building models.
Bldg.
Type
Cli.
Zone
R-value
(m2·K / W)
U-Factor
(W / m2·K)
SHGC
Ex. walls
Roof
Window
Skylight
Window
Skylight
office
4C
1.17
5.18
3.24
N/A
0.39
N/A
5A
1.43
5.18
3.24
N/A
0.39
N/A
6A
1.69
6.52
3.24
N/A
0.39
N/A
7
1.96
6.52
3.24
N/A
0.49
N/A
school
4C
1.42
2.79
3.241
2.674
0.385
0.414
5A
2.10
2.85
3.241
2.674
0.385
0.414
6A
2.10
2.85
3.241
2.674
0.385
0.414
7
2.75
2.79
3.241
2.674
0.487
0.777
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Assessment method
Multiple overheating assessment methods were collected
from existing studies in different countries. The method
to define indoor overheating conditions can be different
for building occupants in different countries and regions.
However, the existing overheating assessment methods
provide the method to describe the overall indoor thermal
pattern in summers.
Most of the overheating criteria are based on the indoor air
temperature or the operative temperature to develop a static
or adaptive temperature threshold to identify overheating
hours. A few of the newer studies proposed the thermal
comfort and heat stress index, for which the heat stress
index considers the human body's physiological thermal
response to heat (Laouadi et al. 2020). This paper uses,
however, only the (operative) temperature-based criteria to
evaluate overheating in buildings located in Canadian
cities. Both criteria with fixed and adaptive temperature
thresholds are used and compared.
For the fixed temperature criteria used in this study, four
(4) temperatures thresholds were considered based on
different existing overheating assessment criteria: 25 °C,
26 °C, 28 °C, 30 °C, and 32 °C. The temperature threshold
of 25 °C is obtained from the Passive House Institute
(PHI) (PHI 2016). The fixed operative temperatures of 26
°C and 28 °C were also widely used for defining multiple
overheating criteria. In CIBSE Guide A, the indoor
temperature should not exceed 26 °C and 28 °C for 1% of
the annual occupied hours for bedrooms and living rooms
in residential buildings (CIBSE 2011), and CIBSE TM52
and TM59 (CIBSE 2013, 2017), the fixed temperature of
28 °C is used for school and office buildings. In
EN16798-2019, the indoor operative temperature of
mechanically ventilated or cooled zones, a fixed operative
temperature of 26°C is used to define overheating(BS EN
16798 2019). As described in Building Bulletin 101, there
is a requirement that the air temperature in classrooms
during occupied hours should not exceed 32°C.
For adaptive comfort criteria, the temperature limit is
usually a function of the outdoor running mean
temperature. The CIBSE (CIBSE 2013) employed the
adaptive thermal comfort levels defined by the European
Standard EN 16798-2019 (BS EN 16798 2019), in which
three (3) categories of comfort level are identified based
on the predicted comfort temperature:
  
  (1)
where, Trm, is the running mean daily average temperature,
estimated by:

  󰇛      
    󰇜 (2)
and where Ted-1 is the daily mean external temperature for
the previous day, Ted-2 is the daily mean external
temperature for the day before, and so on.
Figure 4 Mean temperature over the 5 months May, June, July, August, and September in 12 cities and the trend in
31 years, shade shows the range between the maximum and minimum values.
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The upper limits of the three (3) categories of thermal
comfort are used for the evaluation of overheating in this
study:
  
    (3)
  
    (4)
  
    (5)
The ASHRAE standard 55 has also similarly defined an
adaptive thermal comfort, with the upper operative
temperature limit defined as

  
  (6)
It can be noted that the ASHRAE thermal comfort upper
limit is close to the upper limit definition for Category 1
thermal comfort given in BS EN 16798.
Results
Comparison of indoor and outdoor variations
After the 31-year simulation of the two building types, the
mean indoor operative temperature of the buildings in 12
cities was summarized and is given in Figure 4. The
overall mean indoor operative temperature in schools is
around 2.5°C higher than the mean temperature in office
buildings. This might be due to the higher internal heat
gain in classrooms than that in office rooms and the higher
R-value of school buildings' external walls. Indoor
operative temperatures are highly affected by the local
outdoor weather conditions, especially the local air
temperature. The outdoor air temperature is also
compared with the indoor temperatures in Figure 4. As
might be expected, the mean indoor operative temperature
is higher than the outdoor temperature, and the
temperature range is much smaller than that outdoors.
Figure 5 Variation of mean a) global horizontal radiation and b) wind speed over the 5 months of May, June, July, August,
and September in 12 cities and the trend in 31 years, shade shows the range between the maximum and minimum values.
The lines of linear regression given in Figure 4 show the
mean temperature variation trend over the 31 years. For
the outdoor air temperature, two cities, Vancouver and
Saskatoon, have an unexpected downward trend. There
might be two reasons for this: i) the 31 year period is not
sufficiently long to capture an increasing trend of climate
change in these two cities; ii) the local climate region in
which these two cities are located is not highly affected
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by the warming climate. Toronto has the highest
increasing trend of all the cities studied, followed by
Montreal. Both the outdoor and indoor mean temperature
for Toronto in 2016 is the highest.
The indoor operative temperature within buildings
located in each of the 12 cities shows a similar trend
compared to the corresponding outdoor conditions, but
the mean indoor temperature is closer among different
cities. The increasing and decreasing trend of mean values
may change when it comes to indoor conditions. For
example, even though the outdoor air temperature of
Charlottetown, St Johns, and Winnipeg has an increasing
trend over the 31 years, the indoor operative temperature
of school buildings shows a decreasing trend; this
suggests that the current type of building construction in
these cities may still have the ability to resist a warming
climate. The indoor conditions might also be affected by
other climate variables
Figure 6 Number of hours exceeding the fixed overheating criteria in the 12 cities over the 31 years.
Figure 7 Number of hours exceeding the adaptive overheating criteria in the 12 cities over the 31 years.
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Figure 8 Cooling degree hours (CDH) with different base temperature threshold of the 12 cities over the 31 years
It can also be noted, as shown in Figure 5, that the solar
radiation of the three cities has a decreasing trend.
Therefore, it is expected that the solar heat gain of
buildings located in these cities would accordingly
decrease. For the city of Saskatoon, even though the
outdoor air temperature has a slightly decreasing trend,
the indoor operative temperatures of the school and office
buildings have changed to a growing trend. An increasing
trend of solar radiation and a decrease in wind speed can
be observed for Saskatoon.
The regression analysis shows that even for the cities in
the same ASHRAE climate zone, the climate variation
and indoor thermal conditions can be quite different. The
mean temperature values and the changing trends in
Toronto (5A) are similar to that found for Montreal and
Ottawa (6A), which is at least 1 °C higher than the other
cities in the same climate zone. The three (3) cities of
Charlottetown, Moncton, and Halifax are at the same
level of indoor operative temperature, whereas St Johns,
which is on the island of Newfoundland, is surrounded by
the ocean (Figure 1) and is around 1 ~ 1.5 °C lower than
that found in these 3 cities located on the east coast of
Canada. For climate Zone 7, the climate conditions of the
different cities located in this zone are quite different from
each other. Still, the three cities' indoor operative
temperatures in Winnipeg, Saskatoon, and Calgary are at
the same level, and the indoor operative temperature of
Whitehorse is around 1 ~ 1.5 °C lower than the other 3
cities in the same region.
Overheating conditions in 12 cities
Multiple overheating methods have been applied to the
building simulation results for the overheating evaluation.
Figure 6 shows the overheating hours based on fixed
thermal comfort levels, and Figure 7 shows the
overheating hours based on adaptive thermal comfort
levels, for which the frequency and duration of
overheating occurrences in buildings are considered. For
office buildings, very few hours can be identified as being
higher than 30°C, whereas schools are exposed to more
severe overheating conditions. The variation of
overheating hours having different temperature thresholds
may exhibit different trends for the same city. But 7 of the
12 cities (Toronto, Montreal, Ottawa, Moncton, Halifax,
Calgary, and Whitehorse) show the increasing trend in
overheating of school buildings using different
temperature thresholds, and this occurs for office
buildings in 6 of the cities (Toronto, Montreal, Ottawa,
Moncton, Charlottetown, Halifax).
On the other hand, the overheating results calculated by
the adaptive thermal comfort levels exhibited a different
result. It can be found that the overheating results
calculated from the BS EN Category 1 and ASHRAE
upper limits have almost the same overheating level.
While most cities have a decreasing trend in overheating
hours, and in Figure 7, only the school buildings in
Halifax and both building types in Saskatoon show an
increasing trend over the 31 years variation. The adaptive
overheating criteria adopted in this paper are based on the
assumption that the occupants may adapt to the higher
temperature when the outside temperature is getting
higher. Therefore, the temperature threshold will also be
higher when the outside temperature is higher. This helps
explain why, in most cities, the number of hours higher
than the adapted temperature threshold does not increase,
even though they mean temperatures in these cities are
increasing. The hours with increased temperature may
still have a lower temperature than the changing
temperature threshold unless the increasing trend indoor
temperature is stronger than the increasing trend of the
adaptive temperature threshold.
Figure 8 shows the cooling degree hours (CDH)
calculated with the different base temperature thresholds.
It is defined as the cumulative overheating hours
identified by the operative temperature above the
threshold discomfort temperature weighted by the
magnitude of the operative temperature exceedance. The
CDH value evaluates the duration and frequency of the
calculated overheating hours and the intensity of
overheating above the thermal comfort thresholds. The
result also shows the different variation trends of using
fixed thermal comfort thresholds and adaptive thermal
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comfort thresholds. Most of the upward regression lines
come from the calculations using fixed thresholds,
whereas the adaptive thermal comfort thresholds may lead
to a downward trend over the 31 years from 1986 to 2016,
which is similar to the observed trend of the overheating
hours in Figure 7.
Conclusion
In this study, the building simulations capture the
variation overheating conditions within the school and
office buildings when subjected to long-term historical
weather for buildings in 12 Canadian cities. The trend in
overheating occurrences in buildings is captured by
assessing building simulation results under freerunning
conditions. The variation of the mean indoor operative
temperatures during the summertime months are
compared with the corresponding outdoor weather
conditions, and for the outdoor air temperature, two cities,
Vancouver and Saskatoon, a decreasing trend is observed.
Most of the indoor operative temperature trends over the
31 years studied are consistent with the outdoor air
temperature variations. It was also determined that the
outdoor temperature is the most sensitive factor affecting
the indoor operative temperature within buildings. But
there are also exceptions, for example, like those found in
Charlottetown, St Johns, Winnipeg, and Saskatoon, in
which the effect of solar radiation and wind speed on the
indoor thermal environment is more pronounced than that
of the outdoor temperatures.
Multiple existing overheating assessment methods,
including the fixed temperature threshold and adaptive
thresholds, were also applied and compared. It was found
that the overheating hours, calculated by using fixed
overheating criteria, were different from those calculated
by the adaptive thermal comfort criteria. The use of fixed
criteria captures the increasing trend of indoor
overheating in most of the cities studied. It is also
surprising that the overheating hours calculated using the
adaptive thermal comfort criteria have a decreasing trend
for most cities. Note that adaptive criteria are based on the
assumption that people might be more resistant to a higher
temperature when exposed to the relatively warmer
environment estimated only by the daily running-mean
temperature. This implies that the overheating criteria are
critical parameters in estimating the risk of overheating in
buildings. Thus, it is crucial to explore indoor overheating
using physical bio-heat thermal comfort models to
evaluate the practical impact on building occupants. In
future work, the sensitivity of building models to different
climate variables will be explored. The study will also be
continued by using the bias-corrected future projected
climate data from the regional model CanRCM4 database
downscaled from a large ensemble of its global parent
model, CanESM2, to explain further the effect of climate
change over a much longer time frame. Different
overheating mitigation strategies will also be evaluated
based on the future projected climate data.
Acknowledgment
The research was supported by the Natural Sciences and
Engineering Research Council of Canada (NSERC) the
“Advancing Climate Change Science in Canada
Program” [#ACCPJ 535986-18], the Construction
Research Centre of the National Research Council of
Canada, from the support of Infrastructure Canada and the
Pan Canadian Framework on Clean Growth & Climate
Change.
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