The effects of different landscape configurations on thermal stress are evaluated using measured data from two adjacent, semi-enclosed courtyard spaces. By computing the energy exchange between the urban environment and a hypothetical pedestrian in the space, the reductions in physiological thermal stress, and in turn perceived thermal discomfort, are estimated and compared with the rate of irrigation required by each vegetative treatment to achieve them.
2.1. Experimental setup
The observational study was conducted at the Sede-Boqer campus of Ben-Gurion University, located in the Negev Highlands of southern Israel (30°50′N, 34°40′E; 475-m elevation). Daily temperatures during the summer period (measurements were conducted during July to August) range on average from an early morning minimum of 20 °C to an afternoon peak of 33 °C, with relative humidity averaging 35% at 14:00 and increasing to about 90% at night. Prevailing winds are consistently from the northwest, reaching maximum velocity in the late afternoon and evening (Bitan and Rubin, 1994).
The experiment was designed to compare a number of different landscape treatments under relatively controlled conditions, such that their microscale effects could be identified and distinguished from the background effects of the larger built-up area. For this purpose, two adjacent courtyard spaces were selected which had virtually identical geometry and material properties (Meir et al., 1995); one, however, had been planted with three mature trees, whereas the other was devoid of vegetation. Both spaces were surrounded by single-story buildings and elongated in plan along an approximately north–south axis, with a cross-sectional aspect ratio of approximately H/W = 0.5 (Figure 1).
In addition to their original disposition, the courtyards were modified in two ways: a ground cover treatment consisting of grass sod on a shallow soil underlayment was placed alternately in each of the two spaces, and an overhead shading mesh was installed in the courtyard without trees. This yielded a total of six distinct landscape configurations which could be monitored over the course of the summer period, each combining one of the three overhead treatments (‘trees’, ‘exposed’ and ‘mesh’) with one of two ground treatments (‘grass’ and ‘bare’). The six study cases and their parameters are summarized in Tables I and II, respectively.
Table I. The six landscape configurations analysed
| ||Ground surface treatment|
| ||Bare paving and soil||Irrigated grass|
| ||Shade mesh||‘Mesh-bare’||‘Mesh-grass’|
Table II. Physical parameters of the various landscape elements
|Parameter||Ground surfaces||Overhead treatments|
| ||Bare||Grass||Trees||Shade mesh|
|Area ratios||30% soil, 70% pavement||90% grass||70% coverage||70% coverage|
|Albedo||0.60 (walls), 0.55 (ground)||0.22||—||—|
The ground surface in the two courtyards initially consisted of light grey concrete paving tiles (covering about 70% of the area) and exposed loess soil occupying the remainder. One of the courts had three trees planted along its centre line, two of which were Prosopis-Juliflora (a variety of mesquite) and the third Tipuana-Typu (rosewood). Both species are common in hot-arid regions and are considered economical water consumers: the nominal pan coefficient (defined as the ratio between the tree's evapotranspiration per unit horizontal area and evaporation from a Class A pan) is 0.2 for Prosopis-Juliflora and 0.3 for Tipuana-Tipu (Kremmer and Galon, 1996). Both tree species have a medium leaf density that allows ventilation and sufficient solar penetration for grass to grow in their shade.
The grass subsequently planted in the two courtyards was Durban grass with a measured pan evaporation coefficient of approximately 0.8, which is typical of values for short-cut grass cited in previous studies (Brutseart, 1982; Pearlmutter et al., 2009). Durban grass was selected mainly for its ability to grow in the shade, with a minimum requirement of only 3 h of direct sunlight per day. This variety also has especially shallow roots, which made it suitable for planting in the form of sod units on a thin soil layer approximately 3 cm in depth. The grass and underlayment were placed on polyethylene sheeting, covering about 90% of the total ground area of each court.
The trees and the grass were irrigated separately: a drip irrigation system was installed around each tree trunk, providing water to the root zone in the surrounding soil but isolated from the grass layer. Water sprinklers for the grass were located in each court and activated each morning at 6:00. The duration and rate of watering by the two irrigation systems were determined on the basis of preliminary experiments, with the objective of providing an amount of water sufficient to compensate for daily water loss through evapotranspiration (as detailed in Section 3.2). The impermeable polyethylene sheeting under the grass ensured that spray from the sprinklers would not reach the tree roots and that drip irrigation around the trees would not be available to the grass.
Micrometeorological variables and water consumption were monitored in the two courtyards over a 45-day period during July to August 2007, with each landscape configuration monitored for a period of at least 3–4 consecutive days. Instruments were located at the mid-point of each of the two canyon-like spaces, between the two Prosopis-Juliflora trees in the west courtyard and at the same relative location in the east court. Dry-bulb and wet-bulb temperatures were measured using copper-constantan thermocouples in aspirated psychrometers, placed at a height of 1.5 m. Wind velocity was measured using a Campbell 014A cup anemometer in the bare court, and with a Young 81 000 3-D ultrasonic anemometer in the court with trees. Radiant temperatures of the various built and vegetated surfaces were measured in the two courtyards using shielded ultra-fine thermocouples (attached to wall, paving, soil, lower tree branch and roof surfaces) and an IR thermometer (for the grass surface). Incoming solar radiation was measured with a Kipp and Zonen CM5 pyranometer and net all-wave radiation was recorded with an REBS Q7.1 net radiometer, both located at a height of 1 m above the adjacent building's flat roof. All readings were recorded with Campbell CR21X and CR23X data loggers. Reference climatic data for the given measurement days were obtained from the nearby meteorological station.
Evaporation from the grass was estimated using custom-made mini-lysimeters, whose dimensions and material were optimized to ensure representative measurement of evapotranspiration from the grass–soil volume (Grimmond et al., 1992). The instruments consisted of rectangular (5 × 10 cm) galvanized metal pans with a vertical depth of 3 cm embedded in the grass–soil layer, which was of similar thickness. The evapotranspiration rate was determined from the periodic change in lysimeter weight, measured hourly with a high-resolution electronic scale starting immediately following the daily irrigation at 6:00.
Transpiration from the trees was measured by the sap flow (thermal dissipation) method, which relates transpiration to the rate of sap flow in the tree trunk (Gash and Granier, 2007). The method uses a pair of cylindrical temperature probes inserted into the sapwood, with the upper probe heated by the Joule effect at a constant rate and the lower (reference) probe unheated, with the rate of sap flow calculated as a function of the difference in temperature between the two probes. To account for variations in sap flow among different parts of the tree, transpiration was calculated from the average temperature difference of three pairs of probes located in each tree at the same height (approximately 0.8 m), at equal intervals around the trunk.
2.2. Computation of thermal stress
A variety of models have been used to assess outdoor thermal comfort, often through the use of a hypothetical, ‘physiologically equivalent’ temperature (e.g. Hoppe, 1993, 1999). Such measures typically portray radiant effects using the mean radiant temperature (MRT), which is difficult to quantify in an outdoor urban context due to the multiplicity of radiating surfaces together with the high intensity of solar and atmospheric radiation. Although the measurement of MRT using globe thermometers of varying diameters and materials has received wide attention in recent studies (Ali-Toudert and Mayer, 2006, 2007; Thorsson et al., 2007; Kenny et al., 2008), this approach is still subject to uncertainties given the extreme variability of air flow and convective heat transfer that is typical in the urban canopy layer.
In the present study, pedestrian thermal stress is quantified using the index of thermal stress (ITS), originally developed by Givoni (1963) and implemented in urban canyon-type settings by Pearlmutter et al. (2007). Rather than deriving a hypothetical temperature, the ITS directly expresses the overall energy exchange between a pedestrian's body and its surroundings under warm conditions. Expressed in watts of equivalent latent heat, the index is a measure of the rate at which the body must secrete sweat to maintain thermal equilibrium, accounting for radiation Rn and convection C as well as for the body's internal heat generation (based on metabolism M and work W) and the efficiency of sweat evaporation f, as limited by atmospheric humidity:
The instantaneous exchange of energy by radiation and convection is computed in W/m2 of body surface using a vertical cylinder to represent a standing pedestrian in the centre of the space (Pearlmutter et al., 1999). The body's net radiation balance Rn is composed of absorbed direct (Kdir), diffuse (Kdif) and reflected (Kref) short-wave components; long-wave absorption from the sky and other downward-radiating elements (Ld), from horizontal ground surfaces (Lh) and from vertical wall surfaces (Lv); and long-wave emission from the body to the environment (Ls):
The absorption of short-wave radiation is based on measured global and diffuse radiation, shading and view factors (a function of courtyard geometry) and the albedo of built and vegetative surfaces (Table II) and of the body itself (αs). Long-wave absorption from surfaces (including the ground, walls, tree canopy, and shading mesh) is calculated on the basis of view factors, measured surface temperatures and estimated emissivity values for all relevant materials, whereas emission from the body is based on a constant skin-clothing temperature of 35 °C. Absorption of downward long-wave emission from the sky dome is calculated from measured meteorological values and relevant sky view factors. A detailed description of the calculation of individual radiation components is given by Pearlmutter et al. (2006).
Convective energy exchange (in W/m2 of body area) is a function of the skin–air temperature differential (Ts − Ta) and an empirical heat transfer coefficient hc based on wind speed V:
In nearly all cases, C represents a net dissipation of heat from the body since courtyard air rarely reaches a temperature above 35 °C, which was taken as a constant for Ts.
To calculate the level of thermal stress from the environmental loads Rn and C, component flux densities in W/m2 are multiplied by the DuBois body surface area to yield fluxes in watts, and summed with the net metabolic heat gain (taken as a constant 70 W for a standing person). The evaporative cooling efficiency f is computed from an empirical relation based on the vapour pressure of the surrounding air (as well as wind speed and a clothing coefficient), as detailed by Pearlmutter et al. (2007).
The level of physiological stress represented by the ITS has also been correlated with subjective thermal discomfort on a thermal sensation scale ranging from ‘comfortable’ to ‘very hot’ (Givoni, 1963; Pearlmutter et al., 2007). According to this scale, a limit to comfort is found at an ITS value of approximately 160 W, with the thresholds for ‘warm’ and ‘hot’ conditions occurring at successive increments of about 120 W each (Table III).
Table III. Correlation between ITS and thermal sensation level (Pearlmutter et al., 2007)
|Index of thermal stress (W)||Thermal sensation|
|> 400||Very hot|
While climatic conditions were relatively consistent throughout the summer monitoring period, minor differences were accounted for by normalizing the ITS results from individual days relative to a reference dataset taken from the adjacent meteorological station. For each landscape configuration, a representative daily cycle was selected and hourly ITS values were adjusted proportionally based on the ratio between the equivalent value computed from simultaneous measurements at the ‘open’ site (ITSref) and the average of reference values for that hour over the set of selected days:
Daily water consumption was normalized according to the same procedure, based on Class A pan evaporation at the meteorological station.