use types on canopy layer air temperature

Building and Environment 125 (2017) 451e463

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Building and Environment journal homepage: www.elsevier.com/locate/buildenv

Effect of different land cover/use types on canopy layer air temperature in an urban area with a dry climate Paria Shojaei a, b, Mahdi Gheysari a, *, Baden Myers b, Saeid Eslamian a, Elham Shafieiyoun a, Hadi Esmaeili c a b c

Department of Water Engineering, College of Agriculture, Isfahan University of Technology, Isfahan, 84156-83111 Iran School of Natural and Built Environments, University of South Australia, SA, Australia Department of Water Engineering, Chamran University of Ahvaz, Ahvaz, Iran

a r t i c l e i n f o

a b s t r a c t

Article history: Received 1 May 2017 Received in revised form 5 August 2017 Accepted 6 September 2017 Available online 8 September 2017

Knowledge of the influence of land cover on air temperature in arid cities is scarce, yet essential for urban planners to select landscape design and management strategies which can improve livability and provide efficient landscape irrigation. The objectives of this study were to consider the effects of urban land use on air temperature changes in an arid city based on data collected in Isfahan, Iran at a local scale. This study reports a statistical analysis of temperature variation with respect to land use throughout the day and night. It is also the first study to report the effects of land cover on the time that daily minimum and maximum temperature occurs. The land use characteristics considered included green space, streets, buildings, population density and bare land. Air temperature was measured for 42-months at the canopy level of five intra urban sites and one reference site in a lightly developed suburban location. The temperature of all intra-urban sites was higher than the suburban reference site for a majority of observations during daytime throughout the year. The effect of land use on air temperature overnight was greater than daytime. The highest temperature difference occurred overnight in summer, with differences up to 12 C when comparing an irrigated, vegetated site and the suburban site on an hourly basis. On average, the daily maximum temperature in urban areas occurred sooner than in the suburb in all seasons. The highest mean time difference was 78 min between the commercialeresidential and suburban stations in summer. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Urban microclimate Urban land use/cover Urban cool island Intra-urban air temperature Diurnal temperature range

1. Introduction Urbanization causes distinct changes in a local environment when compared to the formerly natural environment, the result of which produces an urban microclimate [1]. The creation of, urban land cover/use affects net solar radiation, latent and sensible heat fluxes and heat storage, and consequently causes changes in the surface energy balance in cities. Urban geometry such as the layout of the street network, orientation and distribution of buildings [2e5], urban density and building height [6,7] all influence the air temperature pattern in urban environments. For example, Erell and Williamson [5] indicated that the reduced sky view factor caused by urban geometry restricts long wave radiation losses to the sky, while multiple

* Corresponding author. E-mail address: [email protected] (M. Gheysari). http://dx.doi.org/10.1016/j.buildenv.2017.09.010 0360-1323/© 2017 Elsevier Ltd. All rights reserved.

reflections of radiation from building surfaces and the street result in a higher overall absorption of solar radiation in the urban street canyon. Changing vegetated permeable surfaces to non-permeable materials such as brick, concrete and asphalt results in lower latent heat flux and increased sensible heat flux, and hence leads to an increase in the air temperature in urban environments [8]. Anthropogenic heating [9,10] and air pollution [4], together with the parameters noted above create unique microclimates in different points of a city. Recognition of air temperature differences has important uses in many fields such as plant phenology [11e14], urban planning [15,16], human biometeorology and thermal comfort [2,17e19], energy consumption [16,20], air quality [21] and aerobiology [22]. It should be noted that the effects of surface cover type on air temperature patterns during the year in an arid region have subsequent impacts on the management of irrigation under deficient

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P. Shojaei et al. / Building and Environment 125 (2017) 451e463

conditions of water, but these have been less evaluated. In addition, no research has been carried out that has “simultaneously” investigated the effects of land cover/use on minimum, average and maximum air temperature on an hourly, daily and monthly basis over several years in an arid region. Isfahan is an ancient settlement and a major commercial hub. With a population of 1.7 million (Statistical Center of Iran; 2016) it is currently the third largest city in Iran. It has a cold, arid climate €ppen Climate Classification System). On average, there is a green (Ko area of 26 m2 per capita in Isfahan (Isfahan Municipality; 2016). The influence of green spaces on air temperature has not been evaluated in Isfahan. Creation, conservation and management of urban green spaces in an arid region is very important for the Municipality of Isfahan and requires significant financial investment and water resources. Therefore, it is necessary to identify the influences of green space on temperature and consequently on atmospheric evaporation demand. The objective of this study was to consider the effect of green spaces, streets, buildings, population density and bare land on the change in the urban air temperature in Isfahan on a microscale level. This study can help urban planners to create and manage a more liveable environment. This paper focuses on the analysis of differences in canopy layer air temperature due to the type of urban land cover/use over 24 h of the day in all seasons based on a 42-month dataset. This paper is the first to report the effects of land cover/use on the time that the daily minimum and maximum temperature occurs. 2. Data and method 2.1. Study area This study was conducted in Isfahan city (Latitude: 32 360 to 32 430 N, Longitude: 51360 to 51430 ) located in the center of Iran, in the plain of the Zayandehrod River, at the foothills of the Zagros mountain range (Fig. 1). The minimum and maximum height of the city are 1550 m and 1760 m, with an average elevation of approximately 1590 m above sea level. The area is located in a dry region. € ppen Climate Classification System, it has a cold According to the Ko desert climate (i.e. BWk) [23] with an average annual temperature of 17 C. The annual precipitation is 122 mm. In the summer months (approximately July to September), the average temperature is 28 C with no rainfall. In the winter months (approximately January to March), the mean temperature is approximately 5 C. In the data collected for this study (October 2010 to April 2014), monthly average temperature and relative humidity (RH) ranged from 3 C to 30 C and 12%e58%, respectively. The Zayandehrod River, which passes through Isfahan city, was dry for almost 90% of the monitoring period. 2.2. Meteorological stations and data measurement Using land use maps, field visits and through consultation with experts at the Municipality of Isfahan, five sites in the city of Isfahan were selected, each with different surface cover characteristics. A weather station was installed at each site in October 2010, each consisting of an identical temperature data logger inside a weather shelter (Fig. 1). The weather stations were installed 1.8 m above ground level. This height was selected based on the height range of existing urban microclimate investigations which have been in the range of 1.5e2 m [20,24e28]. Air temperature and relative humidity was recorded using a datalogger (Model 8808, AZ Co.). The temperature range was 20 to 70 C, with a resolution of 0.1 C and with an accuracy of ± 0.6 C over the range 0e50 C, and ± 1.2 C outside this range. Temperature and relative humidity was logged throughout the monitoring period of 42 months (October

2010eApril 2014) at 5 min intervals. The humidity range was 0%e 100%, with a resolution of 0.1% and with an accuracy of ± 3% over the humidity range 10e90% and temperature of 25 C, and ± 5% outside this range. A 42 month period was adopted because this was the longest time over which monoitoring stations could be placed due to logistical constraints of open space managment at the Municipality of Isfahan. One additional datalogger, deemed the reference station, was installed in an outer suburban area located at the Research Centre for Atmospheric Chemistry, Ozone and Air Pollution in Isfahan province (http://www.esfahanmet.ir/), part of the Iranian Meteorological Organization (http://www.weather.ir/) (Fig. 1). All datalogger devices were calibrated and compared approximately every six months under identical controlled conditions. The nature of land cover at each site was categorised into the seven categories listed in Table 1 based on analysis of aerial photos. The portion of each surface cover was calculated as a percentage within a circle with a 150 m radius from each weather station. This radius was allocated as a fetch (i.e. the distance upwind to the edge where the transition to a distinctly different surface type occurs) [29]. In this study it was assumed that the surface was spatially homogeneous within the circle and/or that over time the variation of wind direction will create spatial averaging [30]. Table 1 shows the surface cover characteristics within the circle around each station. The five stations in the city consisted of a city park (STN1), a residential-agricultural area (STN2), a sparsely forested park (STN3), a residential area (STN4) and a commercialeresidential area (STN5). The station located in the suburban area (STNref) was used as a reference station to identify temperature differences between the intra-urban and lightly urbanized suburban areas (Table 1, Figs. 1 and 2). Stewart and Oke (2012) described the use of Local Climate Zones (LCZs) as a climate-based classification of urban and rural sites for canopy layer temperature studies [31]. They defined each zone by structural and land cover properties that influence air temperature [32]. Table 1 shows estimates of the LCZs for each station in this study. STN1 (LCZ: 6A or open low rise with dense trees; and LCZ: 2B or compact mid-rise with scattered trees) was located in an 8.2 ha garden area in the centre of the city. It contained over 100 plant species. Just 50 m north of STN1, the green cover changed to an impervious street surface with a high volume of vehicular traffic and a high building surface coverage. The tallest building in a 150 m radius of STN1 was approximately 18 m high (six-storey). STN2 (LCZ: 6 or open low-rise) was located in a built up public space next to a street. The majority of adjacent buildings were two-storey or approximately 6 m high. Some agricultural lands (irrigated grain) were located 150 m south of STN2. STN3 (LCZ: B or scattered trees) was located in a 75 ha sparse forest park in the north east of the city. That park had about 20 tree species, mostly conifers, which are resistant to drought. Approximately 20% of park area was impervious, which represented the lowest impervious area among all stations. STN4 (LCZ: 3B or compact lowrise with scattered trees) was located in built up public space next to a street. Adjacent buildings were typically two to three-storey (6e9 m). STN5 (LCZ: 3 or compact low-rise) was located in a hospital area with a high volume of vehicle traffic. The 150 m radius was predominantly two to three -storey buildings. The reference station, STNref (LCZ: F or bare soil), was located in a lightly developed suburban area about 9 km southwest of the city border within the compound of the Research Centre for Atmospheric Chemistry, Ozone and Air Pollution in Isfahan province. 2.3. Data analysis method To determine the relative influence of land use/cover on air temperature patterns within the urban environment at different


453

Fig. 1. Aerial photograph of Isfahan city showing the study area and location of six air temperature stations (data loggers). The STNref used as a reference station.

Table 1 The position and land use characteristics around each weather station within a circle with 150 m radius from each station calculated from aerial photographs. Station land use/land cover category

Altitude (m.a.s.l.)

Grassa (%)

Building (%)

Water (%)

Agricultural landa (%)

Tree canopya (%)

Bare land (%)

Street and pavement (%)

LCZs

STN1

park

1570

42.6

10.7

4.2

e

21.2

e

21.3

STN2 STN3 STN4 STN5 STNref

Residential-agriculturalSparse forest park Residential Commercial -residential wasteland

1582 1562 1570 1584 1550

2.1 e 1.4 e e

38.7 8.4 54.2 62.9 4.2

e e 0.3 e e

8.8 e e e 10.9

22.5 71.1 14.3 12.2 1.6

e 9.2 7.8 e 63.5

27.9 11.3 22 24.9 19.8

6A, 2B 6 B 3B 3 F

LCZs: Local climate zones, STN: Station. a The vegetation cover was measured in summer on three consecutive years, and the mean value is reported.

454


Fig. 2. Aerial view of monitoring sites in a circle 150 m.

time scales, the trend of temperature change was investigated on a seasonal, monthly and hourly basis. Hourly temperature (Th) was calculated by forward averaging the 5-minute data for each hour. The hourly temperature differences between the intra-urban sites and the reference site (DTh(i-ref)) were investigated using equation (1) in two time scales: day (sunrise to sunset) and night (sunset to sunrise).

DThðirefÞ ¼ ThðiÞ ThðrefÞ

(1)

where: i represents the station number of intra-urban stations (1e5), ref is the suburban station. Daily mean temperature (Tavg.d) was obtained by averaging the daily minimum temperature (Tmin.d) and daily maximum temperature (Tmax.d) (Equation (2)).

Tavg:d

T þ Tmin:d ¼ max:d 2

(2)

Tavg:m ¼

j¼1

Tavg:d

n

j

(3)

j¼1

Tavg:s ¼

Tavg:d

j

k

(4)

Pn

j¼1 ðTmin:d Þj

Tmin:m ¼

n

(5)

Pk

j¼1 ðTmin:d Tmin:d Þj

Tmin:s ¼

n

(6)

Pn Tmax:m ¼

j¼1 ðTmax:d Þj

n

(7)

Pk Tmax:s ¼

where d represents the daily scale. The effects of land use/cover on minimum, average and maximum temperature on a monthly and seasonal basis were investigated using equations (3)e(8).

Pn

Pk

j¼1 ðTmax:d Þj

n

(8)

where: n is the number of days per month, k is the number of days per season, j represents the day, d, m and s represent the daily, monthly and seasonal time scale, respectively. Diurnal temperature range (DTR), i.e. the difference between daily minimum and maximum temperature, was calculated for each month using equation (9).

DTR ¼ Tmax:d Tmin:d

(9)

The time of occurrence of daily minimum and maximum temperature (referred to as TEmin and TEmax, respectively) was


identified for each day of measurement period. To investigate the possible effects of land use/cover on TEmax and TEmin, the differences of the TEmax and TEmin values between the reference site and intra-urban sites (DTEmax(ref-i) and DTEmin(ref-i), respectively) were calculated using equations (10) and (11).

DTEmaxðrefiÞ ¼ TEmaxðrefÞ TEmaxðiÞ

(10)

DTEminðrefiÞ ¼ TEminðrefÞ TEminðiÞ

(11)

The Independent Sample T-test was used to examine if air temperature in the intra-urban and reference areas were significantly different. This test was performed for Tmin.d, Tavg.d and Tmax.d of the reference and intra-urban stations for each month. Calculations were performed using SPSS (IBM Corp. released 2010, Version 19). The null-hypothesis tested was “no significant difference between the temperature of the reference station and the intra-urban station”. A significance level of 5% was chosen. 3. Results 3.1. Evaluation of air temperature on an hourly basis An evaluation of hourly temperature differences between the intra-urban sites and the suburban reference site (DTh(i-ref)) showed that the difference in minimum temperature was greater than the difference in maximum temperature (Fig. 3). Throughout the day and night, DTh(i-ref) in the summer was higher than other seasons. The maximum DTh(i-ref) was 12 C, observed at the park site (STN1) overnight in summer. The maximum DTh(i-ref) for other seasons throughout the study period was 10.2 C in spring, 8 C in autumn and 7.6 C in winter, all of which occurred at the sparse forest park (STN3). For all four seasons during the night-time hours, the minimum and maximum air temperature occurred at the sparse forest park (STN3) and the commercialeresidential site (STN5), respectively. Overall, during the night-time, the greener sites (STN1, 2 and 3) were cooler than the reference site (STNref) and the commercial-residential site (STN5) was warmer than the reference site for all four seasons (Fig. 3). In a majority of observations during daytime hours with the exception of two to 3 h after sunrise and before sunset, the intraurban sites were warmer than the reference site. The maximum DTh(i-ref) during the daytime was 9 C, which was observed at the park site (STN1) in summer. Throughout the daytime, variations of DTh(i-ref) at different stations in autumn and winter were lower than during spring and summer (Fig. 3). During the daytime in warm seasons, the mean DTh(i-ref) in the sparse forest park (STN3) (about 2.5 C) was greater than the other sites (Fig. 3). 3.2. Monthly and seasonal evaluation of Tmin, Tavg, and Tmax The highest difference in the monthly minimum air temperature (Tmin.m), monthly average air temperature (Tavg.m), and monthly maximum air temperature (Tmax.m) at the intra-urban stations and the reference station were approximately 8, 4, and 2 C, respectively (Fig. 4). The difference in Tmin.m recorded at the different sites was larger than that of Tmax.m for all months during the observed period. The difference in Tmax.m, Tavg.m and Tmin.m at the various stations was higher in warm months compared to cool months (Fig. 4). In all months during the period of record, the maximum value of Tmin.m was observed at the commercialeresidential site (STN5) and the minimum value of Tmin.m was observed at the sparse forest park (STN3). During warm months, the minimum value of Tavg.m

455

occurred at STN1 and STN3; during the cool months, the minimum value was at STN3. The maximum value of Tavg.m occurred at STN5 in all months (Fig. 4). As shown in Fig. 4, the highest standard deviation (SD) for Tmax.m, Tavg.m and Tmin.m occurred in March and the lowest SD occurred over the three summer months. Diurnal changes of urban temperature are therefore lower in warm months in Isfahan. This result is in accordance with results of Holder et al. [33]. The SD may be affected by atmospheric phenomena like precipitation and wind speed. In the summer, Isfahan city has a sunny sky, low wind speed and no precipitation (average 1.2 m s1 in summer based on 30 years of wind records by the Iran Meteorological Organization). These characteristics may explain the limited variation in urban temperature as evidenced by the reduction of the SD of air temperature during summer. Table 2 shows seasonal minimum air temperature (Tmin.s), seasonal average air temperature (Tavg.s) and seasonal maximum air temperature (Tmax.s) during the 42-month measurement period. The highest seasonal average air temperature difference among stations occurred in summer and autumn (Table 2). The maximum difference in Tmin.s, Tavg.s and Tmax.s among the various stations were approximately 7, 4 and 2 C, respectively based on the data in Table 2. 3.3. Diurnal temperature range (DTR) Fig. 5 illustrates the diurnal temperature range (DTR) on a monthly average basis. DTR was highest in the warm months and lowest in cool months. The difference in DTR among various stations was also higher in warm months compared to cool months. The highest DTR difference was 9.1 C in September between the sparse forest park (STN3) and the commercial-residential site (STN5, see Fig. 5). In all months, the minimum and maximum DTR occurred at the commercial-residential site (STN5) and sparse forest park (STN3), respectively. STN1 and STN3, both with a larger proportion of green cover (Table 1) had a higher DTR than other stations for all months. The reference station had the second lowest DTR in warm months, and STN5 had the lowest. In cool months the DTR at the reference station was ranked third, followed by STN4 and STN5 which are the most urbanized sites (Fig. 5). 3.4. Statistical analysis There were significant differences (P < 0.05) in Tmin.d between stations with green cover (STN1, 2, and 3) and the reference station and also between the commercial-residential station (STN5) and reference station in warm months. In cool months, Tmin.d in the sparse forest park (STN3) and the residential, commercial sites (STN4, STN5) was significantly different from that in the reference site (Table 3). Tavg.d at STN3 and STN5 were significantly different from that at the reference site in all months. Tavg.d at the park site (STN1) was significantly different from that at the reference site in warm months only. The results of statistical analysis showed that Tmax.d in the sparse forest park (STN3) was significantly different from that of the suburb site in warm months. There were no significant differences in Tmax.d between intra-urban stations and the reference station in cool months (Table 3). Overall, Tmax.m was higher at intra-urban stations than at the reference station for the majority of the year. The Tmin.m at the reference site was almost always lower than that at the commercial and residential stations (STN4 and 5) and higher than that at the stations with more green space (STN1, 2, and 3). The Tavg.m showed

456


Fig. 3. Box plot of air temperature difference between intra-urban stations and the suburban reference station on an hourly average basis (DTh(i-ref)) over the 42 months from October 2010 to April 2014. The positive value of DTh(i-ref) indicates that the intra-urban sites were warmer than the suburb site; a negative value indicates the opposite.


457

Fig. 4. Daily average, minimum and maximum air temperature on a monthly basis over the 42 month monitoring period.

the same trend as Tmin.m. 3.5. The effects of urban land use/cover on the timing of maximum and minimum temperature The timing of daily maximum temperature (TEmax) and daily minimum temperature (TEmin) for all days during the 42-month measuring period was identified for all stations. The difference between the TEmax at intra-urban stations and TEmax at the reference station (DTEmax(ref-i)) is presented on a seasonal basis in Fig. 6a. The average DTEmax(ref-i) (larger markers) throughout all seasons was positive, indicating that, on average, TEmax at the reference station occurred after TEmax at the intra-urban stations. This matter reveals the effect of land cover/use on TEmax. The highest mean value of DTEmax(ref-i) was 56, 78, 34 and 16 min in spring, summer, autumn and winter, respectively (Fig. 6a). The difference between TEmin at intra-urban stations and the

reference station is presented on a seasonal basis in Fig. 6b. Overall, there was little difference in TEmin between the intra-urban stations and reference station. The maximum value of DTEmin(ref-i) occurred at the commercialeresidential site (STN5), where it was 25 min in summer (Fig. 6b). 4. Discussion 4.1. The effect of land use/cover on minimum and maximum temperature The results of this study have shown that there was little difference in the maximum temperature of the monitored sites throughout the year - the highest difference of Tmax.d was 4 C, but the difference in minimum temperature among the sites was more considerable - the highest difference of Tmin.d was 10 C (Figs. 3 and 4). In other words, the effect of land use/cover on air temperature

458


Table 2 Seasonal minimum air temperature (Tmin.s), seasonal average air temperature (Tavg.s), and seasonal maximum air temperature (Tmax.s) during the 42-month measurement period. (SD: standard deviation). STN

Tmin±SD( C)

Tavg±SD( C)

Tmax±SD( C)

Spring

1 2 3 4 5 ref

10.1 ± 0.46 11.7 ± 0.47 9 ± 0.46 13.5 ± 0.67 15 ± 0.55 13.2 ± 0.66

18.6 ± 0.54 19.9 ± 0.39 18.5 ± 0.53 20.5 ± 0.67 21 ± 0.81 19.9 ± 0.80

27.1 28.1 28.1 27.6 27.2 26.7

Summer

1 2 3 4 5 ref

15.5 ± 0.74 18.2 ± 0.76 14.8 ± 0.79 20.1 ± 0.76 22 ± 0.66 19.7 ± 0.72

25.4 ± 0.83 27.3 ± 1.00 26 ± 0.95 28.1 ± 0.87 28.9 ± 0.74 27.3 ± 0.80

35.5 ± 0.94 36.5 ± 1.21 37.2 ± 1.11 36 ± 0.82 35.7 ± 0.96 35.2 ± 0.82

Autumn

1 2 3 4 5 ref

3.5 4.5 9.6 6.5 8.1 5.3

11.6 ± 0.88 11.5 ± 0.76 9.6 ± 0.86 13.3 ± 1.04 14 ± 0.62 12.2 ± 0.57

19.7 ± 1.72 18.7 ± 1.58 17.8 ± 1.84 20 ± 1.62 19.9 ± 1.13 19 ± 0.99

Winter

1 2 3 4 5 ref

1.6 ± 0.73 1.1 ± 1.18 3.7 ± 1.06 0.4 ± 1.22 1.7 ± 1.22 1.1 ± 1.28

± ± ± ± ± ±

0.63 0.75 1.17 0.65 0.66 1.20

5.3 5.5 4.4 6.2 7.2 5.3

± ± ± ± ± ±

1.12 1.47 1.15 1.31 1.32 1.26

± ± ± ± ± ±

0.72 0.67 0.71 0.69 1.10 0.96

12.2 ± 1.47 12.1 ± 1.75 12.4 ± 1.35 12 ± 1.44 12.4 ± 1.45 11.7 ± 1.34

during the night-time was greater than that during the daytime. This result concurs with the results of previous studies in other urban environments [5,25,34,35]. Petralli et al. [36] showed the relationship between urban planning indicators and minimum temperature is stronger than maximum temperature, providing further evidence to indicate that the effect of land use/cover is greater on minimum (or overnight) temperatures compared to maximum (or daytime) temperatures. The results of the statistical analysis showed that significant differences between daily minimum temperature at the reference and intra-urban sites were more frequent than significant differences in daily maximum temperature. This further supports the claim that land use/cover has a greater impact on minimum

temperature compared to maximum temperature. This point has also been reported by Eliasson and Svensson [28] who analysed € teborg, Sweden. The reason for this efdata from 30 stations in Go fect is that lightly urbanised surroundings are more exposed and cool rapidly during the night. In contrast, the urban environment takes longer to cool [5,12,37] because radiant loss is restricted by structures, in addition to the release of excess heat which has been stored within urban surfaces during the day [5]. We believe that the effect of surface cover on maximum air temperature is low in an arid area because the amount of energy received by the environment from solar radiation (net all-wave radiation Q*) plus anthropogenic heat (QF) is much more than the amount of energy consumed in the evapotranspiration process (QE) during the daytime. When the minimum temperature occurs during the night-time, due to a lack of radiation and, as a result, an overall energy reduction in the environment, any plant cover has considerable influence on air temperature. This is because during the night-time, the amount of energy in the environment from radiation emitted by the land surface and objects on it at green sites are consumed by the evapotranspiration process and therefore, the air temperature is more reduced. The only energy received by the environment at night is longwave radiation emitted from land and urban surfaces, with little contribution from the sky. The quantity of this energy depends on the sky view factor (SVF, %) and on the characteristics of materials, such as albedo, emissivity and thermal inertia [38]. Therefore, the energy of the environment during night hours is more influenced by land use/cover type, but during daytime, the major energy contribution is from solar radiation which is identical throughout the city. 4.2. The effect of vegetation on the intra-urban air temperature The lower temperatures at STN1 and STN3 compared with other stations (Figs. 3 and 4) and the results of the statistical analysis (Table 3) indicated there was a cooling effect attributable to green cover on the urban air temperature in the arid area studied. Similar findings have been reported previously [24,36,39e43]. In warm months, the Tmin.d of sites with greater vegetation coverage (STN1, 2 and 3) were significantly cooler than that of the reference station and the Tavg.d of park stations (STN1 and STN3) were significantly cooler than the reference station. Throughout the day and night,

Fig. 5. Monthly average value of diurnal temperature range (DTR) over the 42 month monitoring period.

P. Shojaei et al. / Building and Environment 125 (2017) 451e463 Table 3 Results from statistical analysisa between the reference station (STNref) and intraurban stations (STN1, 2, 3, 4, and 5).

DTmin.d(i-ref)

DTavg.d(i-ref)

DTmax.d(i-ref)

STN1

STN2

STN3

STN4

STN5

January February March April May May June July August September October November December

0.3ns 0.4ns 1.1ns 2.1*

0.2ns 0.1ns 0.5ns 1*

1.9* 2.6* 3.4* 3.6*

1.9* 1.6* 0.8ns 0.5ns

3.5* 2.9* 1.9* 1.8*

3.05* 4.1* 4.8* 4.3* 4* 3.6* 1.7* 1.09*

1.73* 2* 2.1* 1.6* 1.4* 1.9* 0.19ns 0.4ns

3.9* 5.3* 5.3* 5.1* 4.7* 4.5* 2.6* 2*

0.1ns 0.16ns 0.05ns 0.3ns 0.6ns 0.5ns 0.7ns 1*

1.6* 1.8* 1.5* 2.2* 2.9* 2.6* 2.5* 2.7*


0.1ns 0.08ns 0.3ns 0.7ns

0.3ns 0.3ns 0.06ns 0.1ns

0.9* 0.9ns 1.3* 1.1*

1.1* 1* 0.6ns 0.7ns

2.2* 1.9* 1.4* 1.2*

1.3* 1.9* 2.6* 2* 1.7* 1.4* 0.6ns 0.28ns

0.2ns 0.2ns 0.3ns 0.08ns 0.3ns 1.2* 0.4ns 0.12ns

1.3* 1.8* 1.8* 1.5* 1.3* 1.7* 1.1* 0.9*

0.5ns 0.5ns 0.2ns 0.6ns 0.8* 0.8ns 0.7ns 0.8ns

1.1* 1* 0.9* 1.4* 1.7* 1.9* 1.7* 1.9*


0.5ns 0.6ns 0.6ns 0.7ns

0.4ns 0.5ns 0.6ns 1.2ns

0.2ns 0.7ns 0.8ns 1.4ns

0.4ns 0.5ns 0.5ns 1*

0.8ns 0.9ns 0.8ns 0.6ns

0.3ns 0.3ns 0.3ns 0.3ns 0.6ns 0.7ns 0.6ns 0.6ns

1.3* 1.7* 1.4* 1.5ns 0.8ns 0.6ns 0.6ns 0.18ns

1.2* 1.7* 1.6* 2.1* 2.1* 1.2ns 0.1ns 0.3ns

0.9 ns 0.9 ns 0.5ns 0.7ns 1* 1.1* 0.7ns 0.7ns

0.5ns 0.2ns 0.2ns 0.6ns 0.6* 1.1* 0.8ns 1.2ns

a Comparison of means was done with Independent Sample T-test. Significant air temperature differences on the 5% level are indicated with an asterisk (*).

the highest DTh(i-ref) values occurred in summer and were observed at park sites (STN1 and STN3, see Fig. 3). The percentage of green cover at STN1, 2 and 3 (64%, 57% and 71%, respectively) were more than four times that of the reference station (12%). Evapotranspiration process at STN1, 2 and 3 reduced the sensible heat flux and as a result reduced local temperatures. Tree shading in daylight hours can also be expected to have reduced solar radiation absorption and, as a result, reduced air temperature [26,44,45]. The significant increase of Tmax.d at STN3 in daytime hours during warm months, despite its widespread green coverage (71%, Fig. 3), was probably due to a proximity to desert areas in the north and east of Isfahan. Desert areas are characterized by a high difference in day and night temperatures [46]. The statistical analysis showed that significant differences in daily air temperature between the reference station and the intraurban stations in warm months were more frequent than in cool months for the arid study area (Table 3). In this context, Martin et al. [47], Brazel and Johnson [48], Erell and Williamson [5] and Stabler et al. [34] presented the same results. In cool months, only the Tmin.d and Tavg.d of the sparse forest park (STN3) were significantly cooler than the reference station (Table 3). In these months, the cooling effects of green areas decrease due to vegetation cover reduction. The effect of deciduous trees (park, STN1) and evergreen trees (forest park, STN3) on air

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temperature is different during the year. In cool months, the cooling effect of vegetation at STN1 reduces when the vegetation goes into a dormant state, and this site was therefore more affected by anthropogenic heat from the city center. STN3 was less influenced because of the use of evergreen trees which results in a lower temperature compared to STN1. Other reasons suggested for the lower values of temperature difference at various stations in cool months compared to warm months (Figs. 3 and 4), can be due to the more windy and cloudy weather conditions observed during cool months [49]. There may also be an increase in thermal admittance during wet months which reduces cooling rate [37]. 4.3. The effect of urban impervious surfaces on air temperature The results of this research showed that impervious urban surfaces increase air temperature. These results align with earlier studies of urban areas [36,50e53]. In a majority of the hourly observations at night-time in spring and summer, the commercialresidential site (STN5) was warmer than the reference site and in autumn and winter, the commercial and residential sites (STN4 and STN5) were warmer than the reference site (Fig. 3). Based on statistical analysis, Tmin.d and Tavg.d at STN5 were significantly warmer than those at the reference station in all months (Table 3). Also, the Tmin.d of STN4 was significantly warmer than that at the reference station in cool months. In warm months, the Tmin.d of STN4 was typically higher than the reference, but the difference was not significant (Table 3). The impervious surface coverage at STN4, STN5 and the reference station were 76%, 88% and 24%, respectively (Table 1). It is known that there is a reduction of albedo due to paved and roofed surfaces [9,54e56]. It is also understood that there are multiple reflections of incoming radiation from three-dimensional structures in urban areas [5,54,57]. Both these factors increase energy absorption and energy reservation by the urban canopy and therefore lead to a sensible heat increase during daytime compared to the reference area. During night-time, the stored energy in urban impervious surfaces is emitted into the environment as long-wave radiation [38] which increases the surrounding temperature. Energy losses are also reduced due to the decreased sky view factor below roof level [58] in dense urban areas. In contrast, long-wave radiation leaves the suburban environment easily. Also, the reduction of evaporation because of rapid drainage of rainfall runoff from impermeable and watertight urban construction materials enhances sensible heat. The maximum of Tavg.m and Tmin.m in all months occurred at the commercialeresidential site (STN5) followed by the residential site (STN4) (except Tavg.m of STN4 in July). STN5 had the highest Tavg.m and Tmin.m because it had the highest impervious surface area coverage. Based on monthly observations of traffic around each of the sites, it also had higher impact from vehicular traffic compared to other sites. Both impervious area and traffic contributes to temperature increase in urban areas [59]. 4.4. The effect of land cover on timing of daily minimum and maximum temperature While it is well understood that urban land use/cover affects temperature, this research is the first to report that it also affects the timing of daily minimum and maximum temperature. Recognition of this impact is useful for urban planners and city managers, particularly for estimating thermal comfort hours and provides a better understanding of the effects of land cover on air temperature in an urban environment. During all seasons, on average, the daily maximum temperature

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Fig. 6. The difference between the timing of (a) daily maximum temperature and (b) daily minimum temperature at the intra-urban and the reference station over the 42-month measuring period. Daily data (marker dots), seasonal data (bigger markers).

at the reference site occurred after the intra-urban sites (mean DTEmax(ref-i) have positive quantities, see Fig. 6a). The mean time difference was the highest at STN5, equal to 78 min in summer (Fig. 6a). The cause of this may be attributed to conditions that influence the timing of maximum temperature i.e. when the amount of incoming solar energy equals the amount of outgoing earth energy [60]. In urban areas, the amount of outgoing radiation is increased due to high thermal absorption of impervious surfaces. As a result, the amount of output energy from land in the urban area probably becomes equal to the amount of incoming energy at an earlier time of day. In the other words, the hourly warming rate at the intraurban sites is probably higher than the reference site. As a result, the maximum temperature in the urban environment can occur earlier than the lightly developed suburb. In warm seasons, on average, the Tmax.d at the most developed location (the commercialresidential site, STN5) occurred before other sites (i.e. the mean DTEmax(ref-5) was the highest compared to the other DTEmax(ref-i) in spring and summer in Fig. 6a).

The mean of DTEmax(ref-i) at STN1 was about zero, indicating that the daily maximum temperature at this park site occurred, on average, at the same time as the reference site (Fig. 6a). This is probably due to a high humidity level in the park environment (mean monthly relative humidity ranged from 40% in Jun to 65% in Jan) due to frequent irrigation and the presence of open water (4.2%, Table 1). Moisture has a high thermal admittance and thus has low temperature fluctuations [1]. The increased humidity at STN1 may be preventing rapid changes of temperature and as a result, counteract the influences of land output energy increase on the timing of maximum temperature. In contrast, the TEmax of the sparse forest park (STN3), where there is no surface water and less frequent irrigation is potentially more influenced by urban land use/cover. In cool seasons, there was little difference between the mean DTEmax(ref-i) at intra-urban stations (Fig. 6a). Based on 30 years of weather data recorded by the Iran Meteorological Organization, precipitation occurs in cool months more frequently than in warm months. The TEmax in cool months, can be easily influenced by an


increase in humidity, precipitation and cloud cover [60] in different points of city. Therefore, the effect of land use/cover on TEmax can reduce in cool months. On average, in warm seasons the daily minimum temperature at the reference site occurred shortly after the intra-urban sites (Fig. 6b). Runnalls and Oke [61] presented a graph for average hourly warming/cooling rates ( C/h) for Vancouver, Canada which showed that in the hours after sunrise, the cooling/warming rate in the urban area reached a positive quantity sooner than in a rural area. On the other hand, the rate of temperature change in the urban area alters from a negative to a positive quantity sooner than in the rural area. This concurs with our observations that the Tmin.d in the intra-urban area occurred earlier than in the suburb. We believe the air temperature at the intra-urban sites starts to increase sooner than at the reference site due to the effects of urban land use/cover on temperature increase in daytime. In cool seasons, the average value of DTEmin(ref-i) at various sites was almost on the X-axis indicating that the timing of daily minimum temperature was similar at all stations (Fig. 6b). In cool months, it seems the timing of Tmin.d was more influenced by shading rather than land cover/use type due to the low angle of the sun at the time of sunrise. The timing of Tmin.d can also be affected by cloud cover in cool seasons. 4.5. Air temperature difference of intra-urban and suburb in daytime hours In this research, on average, the temperature of all intra-urban sites was higher than the suburban reference site for most hours during daytime throughout the year (Fig. 3). Erell and Williamson [5] reported similar findings for Adelaide, Australia, indicating a higher temperature in the city center compared to a rural area for daytime hours in winter. By contrast, in earlier studies conducted by Jauregui et al. [62], Svensson and Eliasson [16], Saaroni et al. [63] and Steinecke [64], the intra-urban temperature was lower than that in a less developed area in day hours. The reasons for the cooling of temperatures in the city compared to the suburb, otherwise known as the “urban cool island” [65e67] may be due to a number of factors: canyon shading [5,37,67,68], water bodies [63,69], moisture produced by urban activities [62], evapotranspiration [63,69] and when there is no substantial anthropogenic heat flux (QF) [5]. The ratio of building height to street width (H/W) at the monitored sites was low (on average 1.5) [70] and the air at street level is more exposed to solar radiation compared to areas with a deeper street canyon [71]. In addition to this, the Zayandehrod River passing through Isfahan was dry for almost 90% of measurement period. These two factors of temperature reduction during day hours can be considered negligible in this study. As stated in Section 4.1, the latent heat flux (QE) represents a small proportion of the total energy balance during daytime and is unable to create significant temperature differences. However, the wide green cover within the city park area (STN1) counteracted partly the anthropogenic heat effects during daytime (Fig. 3). The anthropogenic heat rate for mid-latitude cities had been reported at values between 15 and 167 W m2 per annum, on average [72e74]. We did not calculate values of anthropogenic heat flux (QF) in this study but it may be assumed to be high in Isfahan due to the high levels of urban density and high levels of air pollution [75]. In general, all intra-urban stations were cooler than the reference station over a period of one to 2 h before sunset; this was observed in all seasons except winter. Ahrens [60] has shown that in the hours prior to sunset, outgoing longwave radiation from ground and objects (such as buildings) reaches a maximum which

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leads to the occurrence of Tmax.d. In this study, around the timing of Tmax.d, the air temperature in the urban area was cooler than that at the suburban reference site in all seasons except winter. This can be explained by the differences between TEmax of the intra-urban and the reference sites (Section 4.4). The urban environment air temperature reaches a maximum value when the reference site air temperature is warming continuously. Following this, the intraurban temperature is reducing, while the temperature at the reference site continues to increase toward a maximum value. Therefore, in the time approaching sunset, the suburb air temperature can be warmer than the urban air temperature. As noted above, there was no difference between the temperature of the intra-urban area and reference site before sunset in winter. We suggest that this is due to the anthropogenic heat flux is likely to exceed the net radiant flux in winter [10] and therefore the temperature at the intra-urban sites keep increasing compared to the reference site temperature, including around the time of sunset. However, it should be noted that the air temperature differences among various sites in winter were minimal throughout the study period (Section 4.2). 4.6. The effect of land use/cover type on daily temperature range In this research, observations during warm months showed that the mean DTR at the reference site was higher than that at the commercial-residental site (STN5) and lower than other intraurban sites. During cool months, the mean DTR at the reference site was higher than that at the residential and commercial sites (STN4 and STN5) and lower than that at the green sites (STN1, STN2 and STN3) (Fig. 5). Erell and Williamson [5] demonstrated that the daily amplitude of air temperature in suburban and rural areas is greater than in intra-urban streets. Although a densely developed street canyon may absorb more solar radiation than an unobstructed flat rural site or lightly developed suburban area due to multiple reflections among canyon surfaces, absorption over a larger surface area in the urban canyon creates a greater thermal mass which can moderate extremes of surface temperature, and hence reduce peaks of sensible heat flux [5]. Other researchers have shown an increase in the minimum temperature in urban areas compared to rural areas [60,76e78] that may be another reason for the higher DTR at the reference suburban site compared to the intra-urban sites. In this research, the increase in DTR at the reference site compared to the crowded residential-commercial center (STN5) confirms the finding of Erell and Williamson [5] and others. However, the DTR of other intra-urban sites (except STN4 in cool months) was larger than that at the reference site. This difference may be due to: 1) the increase of Tmax.d at all intra-urban stations compared to the reference station in this study; 2) the difference in the amount of green cover around intra-urban stations in this study and previous studies [5,76,77], noting that the extent of green cover at STN1 and STN3 has caused a significant reduction in minimum temperature at these stations; 3) the difference in site characteristics in this and other studies - in several of the cited studies [77,79], the difference in DTR was compared between urban and rural sites, but in this research, the comparison was between an urban area and a lightly developed suburban area. As shown in Fig. 5, in all months, DTR at the sparse forest park (STN3) was greater than that at the other stations. This station had the lowest minimum temperature during all seasons and the highest maximum temperature in warm seasons (Fig. 3). This was probably due to the location of STN3 which was located near an undeveloped desert area. As such, despite the wide green coverage, it can reach high maximum temperatures and low minimum temperatures.

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DTR in warm months was higher than in cool months. Also, the difference in mean DTR at various stations in warm months was more than that determined in cool months. During cool months, we suggest that DTR was reduced due to the increase of air humidity and cloud cover compared to warmer months in this region. The study results are important in an arid urban environment where there is a pattern of thermal extremes over the day [46]. Knowledge of the influence of land use/cover on air temperature in arid cities can not only allow urban and environmental planners to develop initiatives to help moderate severe daily temperature fluctuations and enhance thermal comfort but also enable landscape management staff to conserve water by more accurately estimating plant water demand based on local temperature. This is particularly important in the study area of Isfahan, and in other urbanized arid regions where there is intense competition for limited water resources. As a result of this research, further studies will be carried out to estimate landscape evapotranspiration to take into account the influence of land use/cover types on air temperature with the aim of informing strategies to save water. This study has not been without some limitations. First, Isfahan is in an arid area with a highly developed urban center surrounded by relatively bare suburban lands, and as such findings may not be applicable in other urban cities, particularly those in tropical or temperate climates with a more developed and/or vegetated suburban environment. We recommend further investigation be performed at more intra-urban sites to further explore the reasons for land surface cover influences on the timing of maximum and minimum air temperature. We note that this discussion has referred to data collected in other environments to explain potential causes for the observations of temperature in this study. We therefore recommend further research to characterize the components of surface energy balance in an arid urban area. We also recommend further research to consider the influences of wind speed and direction on thermal patterns at the various intra-urban sites and also for different fetches. 5. Conclusion This study showed that change of land cover/use in an arid city can cause an increase or reduction in canopy level air temperature. The observed effects on air temperature were greater on minimum temperature (i.e. during night hours) compared to maximum temperature (i.e. during day hours). The highest difference in the hourly temperature was 12 C, measured at summer nights, between the intra-urban park station and the reference station. The temperature of all intra-urban sites was higher than the lightly developed reference (suburban) site in most hours of day throughout the year. This study was also the first to report that changes of urban land cover/use affect timing of daily minimum and maximum temperature. On average, the daily maximum temperature at the intra-urban sites occurred sooner than at the reference site in all seasons. The maximum mean time difference was 78 min, and occurred between the commercial-residential site and the suburban reference site in summer. The effect of the urban land cover/use on the timing of daily minimum temperature was lower than that on the timing of daily maximum temperature. Statistical analysis showed that there were significant differences (P < 0.05) in daily minimum and average temperature between the intra-urban park sites and the reference station. These significant differences continuous throughout the year where green cover was not dormant in winter (i.e. where green cover was evergreen). The study also showed there were significant differences in daily minimum and average temperature between the residentialcommercial sites and the reference site during the warm months.

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