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Temperature Reduction Effects of Rooftop Garden Arrangements: A Case Study of Seoul National University

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Increasing urbanization has highlighted the need for more green spaces in built-up areas, with considerable attention of vertical installations such as green walls and rooftop gardens. This study hypothesizes that the rooftop-garden-induced temperature reduction effects vary depending on the type of arrangements. Therefore, the objective of this study is to find the most efficient arrangement of the roof gardens for temperature reduction. This paper presents the results of a quantitative analysis of the temperature reduction effect of rooftop gardens installed on structures and sites on the campus of Seoul National University. An ENVI-Met simulation is utilized to analyze the effects of roads, buildings, green areas, and vacant land on temperature and humidity. The effects of the following five rooftop garden configurations were compared: extreme, linear (longitudinal), linear (transverse), checkerboard, and unrealized rooftop gardens. The extreme and linear (longitudinal) gardens achieved the maximum temperature reduction, −0.3 °C, while the lowest maximum reduction of −0.2 °C was achieved by the checkerboard pattern. Over larger areas, the greatest impact has been recorded in the mornings rather than in the afternoons. The results of this study will be useful for those planning and installing rooftop gardens at the district and city levels.
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sustainability
Article
Temperature Reduction Eects of Rooftop Garden
Arrangements: A Case Study of Seoul
National University
Jaekyoung Kim 1, Sang Yeob Lee 1and Junsuk Kang 1,2,3,4,*
1Department of Landscape Architecture and Rural Systems Engineering, Seoul National University,
Seoul 08826, Korea; kimnam124@snu.ac.kr (J.K.); lsyapl98@snu.ac.kr (S.Y.L.)
2Research Institute of Agriculture and Life Sciences, Seoul National University, Seoul 08826, Korea
3Interdisciplinary Program in Landscape Architecture, Seoul National University, Seoul 08826, Korea
4Interdisciplinary Program in Urban Design, Seoul National University, Seoul 08826, Korea
*Correspondence: junkang@snu.ac.kr; Tel.: +82-2-880-2227
Received: 9 June 2020; Accepted: 23 July 2020; Published: 27 July 2020


Abstract:
Increasing urbanization has highlighted the need for more green spaces in built-up areas,
with considerable attention of vertical installations such as green walls and rooftop gardens. This
study hypothesizes that the rooftop-garden-induced temperature reduction eects vary depending
on the type of arrangements. Therefore, the objective of this study is to find the most ecient
arrangement of the roof gardens for temperature reduction. This paper presents the results of a
quantitative analysis of the temperature reduction eect of rooftop gardens installed on structures and
sites on the campus of Seoul National University. An ENVI-Met simulation is utilized to analyze the
eects of roads, buildings, green areas, and vacant land on temperature and humidity. The eects of
the following five rooftop garden configurations were compared: extreme, linear (longitudinal), linear
(transverse), checkerboard, and unrealized rooftop gardens. The extreme and linear (longitudinal)
gardens achieved the maximum temperature reduction,
0.3
C, while the lowest maximum reduction
of
0.2
C was achieved by the checkerboard pattern. Over larger areas, the greatest impact has been
recorded in the mornings rather than in the afternoons. The results of this study will be useful for
those planning and installing rooftop gardens at the district and city levels.
Keywords: ENVI-met; heatwave; rooftop gardens; temperature; humidity; vertical green areas
1. Introduction
1.1. Background
The rapid growth in industrial and urban development has led to ongoing indiscriminate
urbanization in countries around the world, creating serious environmental problems, the destruction
of forests, and extreme air pollution [
1
3
]. Above all, global warming is becoming critical. Between
1880 and 2018, the temperature of the Earth’s surface increased by around 0.9
C [
1
]. The resulting
rise in global sea levels and the destruction of ecosystems that are unable to withstand these rising
temperatures will have a major impact on everyday life for billions of people [2,3]. By the end of this
century, the average temperature on Earth could rise by anything between 1.1
C to 6.4
C according to
an intergovernmental panel on climate change and the global average sea-level rise is forecast to be
somewhere between 0.4 m and 0.77 m, with every 0.1 m rise in global sea level directly aecting up to
10 million people [24]. Our growing awareness of this impending crisis is driving many researchers
to seek new ways to tackle global warming, including developing alternative energy sources to reduce
greenhouse gas emissions and new approaches that reduce energy consumption levels [
3
5
]. This
Sustainability 2020,12, 6032; doi:10.3390/su12156032 www.mdpi.com/journal/sustainability
Sustainability 2020,12, 6032 2 of 17
is particularly important in densely populated built-up areas such as cities, where environmental
problems are most obvious [
3
,
4
]. Mitigating the heat island eect caused by artificial heat emissions
in urban areas could, thus, make a significant contribution; integrating garden areas such as parks
and street water features into urban environments could not only improve the standard of living of
inhabitants but also substantially reduce the impact of the city on global warming [
4
]. However, in the
case of the Seoul Metropolitan Government area, only about 34.9% of the surface area is currently
devoted to gardens and parks [
5
,
6
]. In other words, it is necessary to create a new type of green space
that can replace buildings and roads [7].
1.2. Purpose of This Study
One approach that is gaining widespread support is the aorestation of vertical space, with
gardens and vegetation no longer being limited to ground level installations [
4
]. By way of illustration,
options for integrating garden space into buildings and other man-made structures could be green
walls and roof gardens [
8
]. Unfortunately, green walls tend to be very sensitive to local environmental
conditions, limiting the kinds of plants that can be used and only certain types of structures are suitable
for wall aorestation [9]. Rooftop gardens are thus far more common than green walls, as they suer
from fewer restrictions [
10
]. So far, many studies have dealt with rooftop gardens. However, the
impact of rooftop gardens on the entire city or a wide area was not clearly understood, mainly by
analyzing only small-scale temperature reduction eects in one space [
4
,
7
11
]. The study began with
the hypothesis that the eect of temperature reduction, in a wide range of areas, changes with the
arrangements of rooftop gardens. Therefore, the purpose of this study is to learn how much the
temperature reduction eect is depending on the arrangement of rooftop gardens in a large area. This
study conducted a quantitative analysis of the temperature reduction eects of rooftop gardens on both
the structures hosting them and the surrounding area. ENVI-Met, a climate simulation software [
11
],
was adopted to derive optimal plans that maximize the temperature reduction eects achieved by each
type of rooftop gardens.
2. Literature Review
In a recent study [
11
], a green area policy proposal was made for future improvement of Taiwan’s
heat environment by using the ENVI-met program. It suggests that if the green area is increased to
more than 60%, the thermal environment can be improved. When the ratio of increasing green area was
fixed at 60%, there was a temperature reduction eect of at least
0.44
C, up to
2.0
C, depending on
the installation rate of the permeable pavement. The last prior research identifies the eect of urban
form and specific building functions on the thermal environment [
12
]. This study suggests that the
optimal size, height, and layout of buildings were presented in dierent ways. Therefore, a single index
is insucient to measure the direct relationship between the urban form and the thermal environment.
Roof gardens, which can be installed on existing residential, commercial, and industrial
buildings [
13
], provide the following three main types of benefits: (1) environmentally, (2) socially, and
(3) economically [
13
36
]. Their environmental eects go beyond simply reducing surface temperatures:
the plants absorb carbon dioxide and hence help to mitigate the urban heat island eect. Besides, they
often support the creation of garden spaces to help maintain a more diverse and resilient biological
ecosystem [
14
,
15
]. It has been documented that a 10-cm-deep soil layer can absorb 20–30 L of rainwater
in each m
2
, reducing the pressure on urban storm drains and helping to prevent flooding during
extreme rainfall events [
16
]. Social eects include a more attractive urban environment that enhances
inhabitants’ quality life and psychological stability [
17
]; on the roof of a building with a garden installed,
a 20 cm layer of soil has been shown to reduce ambient noise levels by as much as 46dB [
18
]. The
subsequent reduction in the amount of energy required to meet the building’s needs provides a further
economic incentive to encourage greater rooftop aorestation [
19
]. Although these three classes of
advantages are closely related to each other [
4
,
20
], this study focuses on the environmental eects,
quantitatively analyzing the temperature-reduction eects of roof gardens.
Sustainability 2020,12, 6032 3 of 17
Most of the research into the environmental impacts of roof gardens have focused on
temperature reduction. For example, a year-long study tracking the environmental impacts
(temperature/humidity/light) achieved by nine dierent types of flowers at building in Gyeonggi-do,
Korea, reported that before the roof garden was installed, the highest figures are as follows; at the
average atmospheric in July, at 34.4
C, the average relative humidity was September, at 59.3%, and
the illumination levels were in August, at 990,150 lux. All the flowers planted in the rooftop plots
successfully reduced the temperature, with the greatest temperature reduction being achieved by
the Blackberry Lily, Belamcanda chinensis, which was around 7.7
C lower than that recorded on the
comparison concrete plot [
21
]. Another study found that a temperature reduction of 5
C could be
achieved by the evaporation of soil moisture from bare soil, with no plant material presece [
22
]. In a
more recent study, bare soil plots were found to heat up and cool down relatively rapidly compared to
plots containing plants, probably because the plants had a higher heat conductivity than the soil [
7
].
This caused the temperature across the rooftop to vary by up to 2
C. The humidity varied from about
2.6 to 3.1%, indicating that a rooftop garden can indeed absorb solar energy that would otherwise pass
into the building below and thus reduce the load on the building’s air conditioning system.
Users’ psychological changes were compared and analyzed with the Profile of Mood States (POMS)
and Semantic Dierential Method (SDM) as they visited six dierent types of rooftop gardens [
23
,
24
]. In
another study, bamboo forests, ponds, and city areas were randomly arranged in an arboretum. Study
participants were asked to quietly appreciate the scenery in their assigned area for 10 min and then
walk through either the natural environments or the urban area for 15 min [
25
]. Their physiological
characteristics were measured before and after completing the task, revealing a statistically significant
improvement in those walking through the natural areas compared to those assigned to the urban
environment [25,26].
Several studies have analyzed the energy and economic savings achieved with the aid of dierent
types of rooftop garden systems, with most utilizing the Life Cycle Cost for the analysis. Overall, a
deep layer of sandy loam delivered the highest savings rate of heat energy, with reinforced insulation
material a close second. An energy-saving rate of around 10% per unit area was achieved for soil
depths of over 300 mm [2730].
The software, which is used in this study, is a three-dimensional climate analysis program that
quantifies the eects of environmental factors such as vegetation, buildings, and solar radiation [
31
33
].
Fur the more, the program can model the impact of gardens, fields, and building materials as well as
taking into account the airflow between and around buildings, evaporation, and the heat exchange
systems of surfaces [
34
,
35
]. ENVI-met has been used to analyze the urban thermal environment of the
city of Songdo [
36
] and the campus of Konkuk University [
37
]. Both of these studies involved only a
simple analysis.
3. Site Selection and Specifications
Two dierent sites were chosen for this study, both on the campus of Seoul National University in
Gwanak-gu, Seoul. In addition to their proximity to the weather station on Mt. Gwanak, where the
weather data was collected, their distinctly dierent characteristics provide a good test of the model.
The reason for selecting the aforementioned sites is that two sites are easily accessible, and a lot of
geographical information is provided from the Seoul Metropolitan Government and Seoul National
University. The first site, Seoul National University Engineering college is a public facility, so all the
rooftop entrances are open. Therefore, it is easy to measure the environmental data such as temperature
and humidity of the site and to analyze the target site. In the case of Seoul National University Station,
it is easy to obtain building information, sea level, height, land use, and soil conditions of site by using
the three-dimensional spatial information system provided by the Seoul Metropolitan Government.
The first study site is an area around the Engineering College of Seoul National University located
in the south of Gwanak-gu in Seoul (Figure 1). The campus is located in a mountainous area, with Mt.
Cheongnyongsan to the north, Mt. Dolsan to the west, and Mt. Gwanak to the east. The lowest site at
Sustainability 2020,12, 6032 4 of 17
Seoul National University is 58.0 m above sea level, and the highest is 189.3 m. Within the first analysis
site, the lowest altitude of the sea level is 114 m and the highest altitude is 140 m.
Figure 1. The first study site (Seoul National University, Seoul, Korea).
The slope of the highest and lowest points was 7.9%, and the total area of this site is 200,000 m
2
(400
×
500 m). The site consists of university buildings, roads, and mountains, and 51% of the site was
used as buildings. The number of buildings is 24 in total, and the buildings are partially connected
through a passageway. The height of the tallest building is 28.8 m while that of the lowest one is 11.2 m.
Accordingly, the average height of the buildings is 19.2 m. All buildings used for research or lecture
purposes were of reinforced concrete type. The roads have occupied 19% of the site area, while the rest
of the region specified to the green areas, gardens, and parking lots [38].
The second study site is an intersection at a Seoul National University Station in Gwanak-gu,
Seoul Metropolitan Government (Figure 2). The Seoul National University station is located in
Bongcheon-dong, the center of Gwanak-gu. The site area is 250,000 m
2
(500 m
×
500 m) and consists
of 450 commercial buildings and 311 residential buildings. The second site consists of a total of 761
buildings. The lowest altitude in the site was 32.0 m, and the highest one was 38.7. The overall slope
was less than 2% and 72% of areas were buildings, 21 of roads, and the rest of the area accounted
for parks and parking lots. The tallest building has 73.9 m in height, while the shortest one acquired
height of 6.5 m, and the average height of buildings is 28.2 m [
38
]. For this study, the analysis was
conducted for the 24 h when Gwanak-gu experienced its highest temperature of the year, midnight to
midnight, on 5 August 2019.
Figure 2. The second study site—a major intersection at an outstation of Seoul National University.
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4. Methods of Design and Simulation
Once appropriate study sites had been selected, the local temperature, humidity, and wind speed
data provided by the Korea Meteorological Administration were collected, and the target locations
were modeled. Information on building heights from the National Geographic Information Institute’s
spatial information portal was converted to a format compatible with ENVI-met using Rhino 6 and the
Grasshopper and Dragonfly plug-ins [
39
]. The second step has been related to utilizing the information
collected to conduct the simulation analysis. Finally, the new model was applied to develop an optimal
design for rooftop gardens in the study areas.
4.1. Site Design and Data Analysis
A polyline file provided by the National Geographic Information Institute was utilized for this
research. Figure 3shows the terrain and buildings depicted using the realistic modeling program
Rhino 6. Two plug-in modules, Grasshopper and Dragonfly, were then used to convert the Rhino 6
data into a format suitable for ENVI-Met.
Figure 3.
Model data for the Rhino 6 analysis and Grasshopper code. (
a
) Numerical map and modeling
top view; (b) modeling perspective view.
The modeling data were transferred to ENVI-Met Space using Grasshopper codes. ENVI-Met
inputs include buildings, topography, soil, vegetation, and receptors. The materials of the building
were set up as reinforced concrete, and asphalt was set for land pavement. GIS topography files were
also used for modeling. The lattice spacing was 5 m along all three axes; the vertical analysis extended
to a height of 300 m. The corresponding modeling data for Site 1, the Seoul National University
Campus are depicted in Figure 4, and modeling data for site 2, the Seoul National University Outstation
is illustrated in Figure 5.
Sustainability 2020,12, 6032 6 of 17
Figure 4.
Model data for Site 1. (
a
) Building data; (
b
) soil data (roads and land); (
c
) 3D modelling data.
Figure 5.
Model data for Site 2. (
a
) Building and vegetation data; (
b
) soil data (roads and land); (
c
) 3D
modelling data.
Sustainability 2020,12, 6032 7 of 17
4.2. Model Simulation
The two sites’ temperature-reduction analysis utilized two ENVI-Met components—ENVIGuide
and Leonardo—to convert the site models created by Rhino and Grasshopper into appropriate
ENVI-Met formats. Information on the various environmental factors, times of the day, time intervals,
and location characteristics were entered and the simulation performed with ENVIGuide. The resulting
files presented in the output data were then sent to Leonardo to analyze the weather conditions
throughout the day. All research results, including existing modeling analyses, were analyzed based
on the ongoing simulations [39].
Existing modeling analyses were used as controls for all other analyses; apart from the presence
or absence of a rooftop garden, the timing, time intervals, and environment variables remained the
same for all the simulations. The simulation was run for the 6 h from 09:00 to 15:00 on 5 August 2019,
with data extracted at hourly intervals. In the case of environmental analysis, the basic Beginner Level
was selected and simulated for general data. The temperature range was set between 22
C and 34
C
to reflect the temperature of a hot day. Besides, the wind speed and direction were set at an average
of 1 m/s and toward the east with the direction angle between 80 and 100 degrees, respectively. To
evaluate the potential eectiveness of the various types of rooftop gardens, simulations of the existing
situation and the temperatures with gardens installed on all the available rooftops were performed.
This type of comparison is supported by ENVI-Met’s Leonardo program.
Five rooftop garden configurations were analyzed for this study (Table 1). The impact of changes
in various environmental factors on the host structure itself and the surrounding area for each
configuration was modeled using ENVI-Met and an optimal plan derived [
40
]. The five types were:
an extreme rooftop garden, linear (longitudinal) and linear (transverse) gardens, a checkerboard
pattern, and an unrealized (bare rooftop) garden. In Korea, where there is a predominant wind
direction, the results obtained would be expected to dier when the roof-top aorestation is aligned in
dierent directions.
Table 1. The five rooftop garden configurations tested.
Extreme Rooftop
Garden
Linear
(Longitudinal)
Linear
(Transverse) Check Patterned Unrealized
Rooftop Garden
5. Results and Discussion
5.1. Existing Model Analysis
5.1.1. Simulated Data
The results analyzed by employing the Leonardo program were derived in the form of a series of
2D maps with the maps generated at 5 m vertical intervals as shown in Figure 6.
The altitude at which the best observation of the temperature distribution could be achieved
was 122.5 m. Figure 6shows the data for 12:00 from the existing modeling data. The minimum and
maximum temperatures are 27.5
C and 27.9
C, respectively. The distribution of temperature varies
with respect to the location of the building as the wind direction has been fixed in one direction only.
By shielding the building from the hot winds of the heatwave period, one can assume that the west
Sustainability 2020,12, 6032 8 of 17
part of the building has a low temperature. Winds shielded by buildings in the longitudinal direction
will then have winds in the northeast and southeast, respectively.
Figure 6.
Simulated data at 12:00 in the Target Site. (
a
) Seoul National University (temperature on
5 August); (b) National University Station (temperature on 5 August).
From Figure 6b illustrating the simulation data at 15:00, it was found that the minimum and
maximum temperatures were 28.1
C and 33.2
C, respectively. Considering the location of the building,
it can be inferred that the northeastern part of the site subjected to a low temperature due to shielding
the building from extreme heat.
5.1.2. Analysis Results by Time Zone
The results of the site1 model analysis by time zone are shown in Figure 7.
Figure 7.
Time zone simulation data before modeling the rooftop garden (Site 1). (10, 11, 12 (
above
),
13, 14, 15 (below).)
Sustainability 2020,12, 6032 9 of 17
From Figure 7, it can be cathed out that the temperature gradually increased from 10:00 to 15:00,
and the distribution of temperature, excluding buildings, varied in the shape from time to time. The
distribution of the y-axis at 12:00 between 130 m and 270 m and the x-axis at 13:00 tend to have a
temperature distribution that varies with wind direction. Meanwhile, the temperature distribution of
point at 12:00 is 0.5
C higher than the surrounding area. This is the result of a concentration of air
shielded by buildings all over the place.
The analysis results for the models of site 2, by time zone, are shown in Figure 8.
Figure 8.
Time zone simulation data before modelling rooftop garden (site 2) (4, 8, 12 (
above
), 16, 20,
24 (below)).
From the results, it was revealed that changes in temperature by time zone were mostly aected
by the location of the sun. Temperatures, before sunrise, acquired almost a concrete amount about
25–26
C until 08:00, while a sharp increase in temperature was observed after sunrise. Also, for
temperature distribution within each time zone, the temperature dierence between the region in the
northeast and the southwest was assumed relatively small due to the eects of altitude and wind
direction. On the other hand, the comparison of the analysis data between 4 h and 24 h indicates that
the temperature decrease is less than the temperature increase, which is assumed to be the result of the
slow-decreasing properties of asphalt. This is because the range of temperature changes on roads set
as asphalt, through the time, was smaller. The daily maximum temperature was 33.2
C at 15:00, and
the maximum temperature dierence was about 5.3 C at 14:00.
5.2. Results of the Analysis on the Eciency of Rooftop Aorestation by Time Zone
To analyze the eects of temperature reduction of the rooftop garden through the time, the
simulations of the existing model and the model carried out at the rooftop garden of all buildings were
compared. The simulation results revealed the reduced temperature and areas by time zone (Figure 9).
The comparison was made except for areas which reduced the temperature by 0.03
C. When the
roof garden was created, the most eective times were 10:00 and 11:00. Referring to Figure 9, from
12:00 to 15:00 the reduction temperature and the shape of the area were similar.
The maximum temperature reduction and the frequency of reduction over time are shown in
Figure 10. The maximum temperature reduction at 10 a.m. was
0.3
C and that of 11:00 was
0.2
C,
Sustainability 2020,12, 6032 10 of 17
which significantly reduced compared to other times. The frequency was also 42.1% at 10:00 and 38.0%
at 11:00, which can be said to have been aected by the temperature reduction.
Figure 9.
Analysis of temperature reduction eect of roof garden by time zone at Seoul National
University (10, 11, 12 (above), 13 14 15 (below)).
Figure 10.
Maximum temperature reduction and frequency of reduction of rooftop garden by time
zone at Seoul National University.
In the case of roof garden by time zone, the dierence between the simulation of the existing
model and the simulation of the greening at all rooftops was analyzed and the reduced temperature
and area were compared by time zone (Figure 11). In the case of having the gardens installed at all
the rooftops, most areas experienced a temperature reduction of about 1
C. It was observed that the
temperature reduction diered over time. For instance, at 00:00–09:00, only the temperature in the
Sustainability 2020,12, 6032 11 of 17
rooftop garden area was reduced. However, at 11:00–17:00, the temperature reduced near the areas
where the roadside trees were planted. It might have resulted from the increased transpiration of
plants with strong sunlight and lower humidity. It was seen that the temperature reduction was low
on 5 August due to high humidity from 00:00–09:00. It was also observed that after 18:00, areas with
reduced temperatures were near the rooftop, before which temperatures were reduced only on roads,
not near buildings.
Figure 11.
Analysis of roof garden-induced temperature reduction by time zone at Seoul National
University Station (6, 12 (above), 18, 24 (below)).
The variation of the maximum temperature reduction with respect to the time zone is shown in
Figure 12. At all times, the maximum temperature reduction was 6
C or higher, of which the maximum
temperature reduction occurred at 15 o’clock and 12.9
C. This is assumed to be the area in which the
elevation dierence occurred in ENVI-Met Space or the area in which the horizontal number exists.
Figure 12.
Maximum temperature reduction and variation of reduction of rooftop garden by time zone
at Seoul National University Station.
Sustainability 2020,12, 6032 12 of 17
5.3. Results of the Analysis on the Eciency of Rooftop Aorestation by Type
Modeling of Target Sites by Aorestation
Modeling was made in dierent ways depending on the type of roof-top garden of each type. The
area covered by the rooftop garden is shown in green (Tables 2and 3).
Table 2. Target location model by type of rooftop garden at Seoul National University.
Extreme Rooftop
Garden
Linear
(Longitudinal)
Linear
(Transverse) Check Patterned Non-Rooftop
Garden
Table 3.
Target location model considering type of rooftop garden at Seoul National University Station.
Extreme Rooftop
Garden
Linear
(Longitudinal)
Linear
(Transverse) Check Patterned Non-Rooftop
Garden
Figure 13 shows the results of the temperature-reduction analysis by the rooftop type. Depending
on the location and degree of rooftop green, the extent to which temperature distribution is aected was
subtly dierent (extreme rooftop garden type). In the case of a fully aorestation type, both the west
side of the building site decreased in temperature. On the other hand, in the case of linear (longitudinal)
less space than the full-green type was aected by temperature reduction, and the lower-temperature
range was greatly distributed to the west. Meanwhile, the linear (transverse) type was significantly
lower in temperature than the other three types and the aected area was also transverse-shaped for
both cases. The check pattern type was generally an area aected by the west side of the building site,
but unlike fully aorestation, linear (longitudinal), an area with very little temperature reduction was
located between the building and the building.
The simulation data for each arrangement were compared with data when the rooftop garden
was not installed. In particular, when comparing point
1
to point
2
shown in Figure 13, the dierence
in temperature reduction eect can be clearly seen for each type of rooftop garden. This is attributed
to the location of the building, and the results shown in Figure 13 are due to the unique shape of the
building, where several layers of the building are connected at dierent heights. In extreme rooftop
garden type, the northern part of the building was aected by the temperature reduced. In the linear
(longitudinal) direction, the center of 39 dong building was aected by the temperature reduced. In the
check pattern type, the only northeastern part of the building was aected by the temperature reduced,
and in the linear (transverse direction), no area was aected by the temperature decrease.
Sustainability 2020,12, 6032 13 of 17
Figure 13.
Temperature-reduction analysis by rooftop type—extreme green rooftop, linear (longitudinal),
(above)/linear (transverse) check pattern type, (below).
For the analyzed time zone, data from the 15:00 time zone, which had the greatest eect on
reducing the temperature of the rooftop garden, was utilized among the time zones of the previous
study results. Two of the four types of temperature reduction, extreme rooftop green and linear
(longitudinal), were found to be about 0.1
C higher than other types on average. In the case of
complete gardening and linearity (longitudinal), the extent to which temperature distribution was
aected was subtly dierent depending on the location and degree of the roof garden. In the case of a
complete green area, the temperature of buildings located on the edge of the target site had further
reduction. On the other hand, linearity (longitudinal direction) had a greater eect on the building’s
surroundings compared to the full-roof garden type, and the temperature in the center of the target
area showed more decrease (Figure 14).
Sustainability 2020,12, 6032 14 of 17
Figure 14.
Plotted data corresponding to 15:00 linear (longitudinal) temperature reduction eect result
(left)/linear (longitudinal) extreme rooftop temperature reduction dierence (right).
The maximum temperature reduced for each type is shown in Table 4.
Table 4. Maximum temperature reduction eect by type and time zone (unit: C).
Time Type A Type B Type C Type D
Seoul National
University
10:00 0.32 0.32 0.28 0.22
11:00 0.27 0.27 0.23 0.19
12:00 0.27 0.26 0.21 0.18
13:00 0.24 0.23 0.18 0.17
14:00 0.18 0.17 0.15 0.14
15:00 0.22 0.21 0.20 0.17
Seoul National
University
Station
10:00 0.67 0.63 0.43 0.41
11:00 0.76 0.74 0.51 0.46
12:00 0.77 0.75 0.61 0.57
13:00 0.68 0.66 0.58 0.51
14:00 0.70 0.67 0.53 0.56
15:00 0.89 0.88 0.66 0.68
Type A means extreme rooftop, Type B refers to longitudinal linear rooftop, Type C means transverse rooftop
greening, and Type D means check patterned rooftop.
From Table 4, it can be realized that the maximum temperature reduction of the full-aorestation
type and linear (longitudinal) was
0.3
C, while the type with the minimum amount was
0.2
C in a
check-patterned format. On the other hand, for the linear (transverse) type, the area of temperature
reduction was lower than the other three types, but the maximum temperature reduction was
0.3
C,
which had more decrease than the check pattern type owing to the parallel building sites on the x-axis
0–150 m and the y-axis 320–450 m.
6. Concluding Remarks
This study analyzed the weather conditions on the engineering area of Seoul National University’s
campus via an ENVI-Met analysis simulation to simulate the temperature reduction achieved by
five dierent rooftop garden configurations. The temperature in the target area is, not surprisingly,
aected by environmental factors such as wind direction and wind speed. The results of the simulation
conducted during the three hours either side of noon (09:00–15:00) on the hottest day of the year
(5 August 2019) showed that the overall temperature at the target site increased as time went on and
the temperature on the western side of the buildings, which was sheltered from the prevailing wind,
was lower than that on the eastern side.
Sustainability 2020,12, 6032 15 of 17
The examination of the temperature reduction eect achieved by rooftop gardens showed that the
gardens successfully reduced the temperature across a wider area in the morning than in the afternoon.
In the morning, about 39% and more of the total area experienced a reduction in temperature compared
to the afternoon, and the temperature decreased by more than 0.3% C. This is likely the result of
less photosynthesis in the morning than in the afternoon, but further work is needed to understand
the underlying mechanism and it is also necessary to explore the eects of dierent types of roofing
material at night when dew is deposited. This research examined only a short six-hour period in
summer; the temperature reduction eects of rooftop gardening deserve a much longer-period study
tracking the eects over multiple days or a year-long analysis over all four seasons.
Based on the analysis of the temperature reduction eect by type of rooftop garden, extreme rooftop
garden planting was the most eective type in terms of the area, delivering the greatest reduction of
temperature. The two linear configurations, transverse and longitudinal plantings, exhibited major
dierences. Despite the rooftops of the buildings in the target area were mostly rectangular and
having many dierent types of rooftops commonly encountered in urban neighborhoods, further
research is needed in a more diverse urban area. The target sites covered in this study had significant
temperature reduction eects of the Linear (Longitudinal) type. This is dierent from other studies.
Other studies expressed that more than 60 percent of green space will have a temperature reduction
eect [
6
]. However, the results revealed in this study can produce a large temperature reduction eect
if the arrangement is concerned, even if approximately 50% of the rooftop green space is secured.
This study has made two major contributions to research into developing more ecient plans for
wide-area-unit rooftop gardens. First, there are economic eects due to the quantitative identification
of temperature-reduction eects across a wider area that will reduce the energy cost incurred by
air-conditioning buildings during heatwaves; further research could examine the associated impact
on resource circulation, including water resources. Second, the environmental eects suggest rooftop
gardens may contribute to eorts to address the urban heat island phenomenon, providing a theoretical
basis for the assessment of the potential utility of increasing the vertical garden area around the site.
This study can make policy suggestions related to the installation of rooftop gardens. It can
have the greatest eect if a rooftop garden is installed in all buildings. However, if the construction
costs are insucient, an arrangement of rooftop gardens should be set in consideration of the wind
direction. In other words, it is deemed necessary to install a linear (longitudinal) rooftop garden that is
perpendicular to the direction of the wind.
However, the study was based on the simulation without collecting historical climate data for
both target sites. Therefore, future study will require at least one to two years of detailed temperature
information to ensure the justification for the selection of the target site.
Author Contributions:
J.K. (Junsuk Kang) designed and coordinated the study. J.K. (Jaekyoung Kim) and S.Y.L.
performed the analytical and conceptual study under the supervision of J.K. (Junsuk Kang). J.K. (Junsuk Kang)
reviewed the results of this study, and all authors have written and revised the text of this paper. All authors have
read and agreed to the published version of the manuscript.
Funding:
This work is supported by Smart City R&D project of the Korea Agency for Infrastructure Technology
Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (20NSPS-B154565-03)
and the 10th Creative Research Program of the College of Agricultural and science at Seoul National University.
Conflicts of Interest: The authors declare no conflict of interest.
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2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access
article distributed under the terms and conditions of the Creative Commons Attribution
(CC BY) license (http://creativecommons.org/licenses/by/4.0/).
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