Ecological energetics of tropical intensive green roof

Energy and Buildings 43 (2011) 2696–2704

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Ecological energetics of tropical intensive green roof C.Y. Jim ∗ , S.W. Tsang Department of Geography, The University of Hong Kong, Pokfulam Road, Hong Kong

a r t i c l e

i n f o

Article history: Received 28 April 2011 Received in revised form 17 June 2011 Accepted 19 June 2011 Keywords: Intensive green roof Tropical green roof Ecological energetics Passive cooling Thermal insulation Canopy microclimate

a b s t r a c t Few green roof studies cover intensive and tropical types and specific canopy microclimate. We examined the ecological energetics of a sky woodland in humid-tropical Hong Kong. Environmental sensors monitored the microclimatic and soil parameters for 14 months. Key biophysical variables of transpiration, wind, light, and through-canopy energy flux are modeled to investigate seasonal and weather effects. The woodland forms a cloistered subcanopy environment with rather stable microclimate. Transpiration and latent heat loss are enhanced by solar radiation and low relative humidity, but less by wind. On sunny days, about 20% of incident solar radiation can reach the soil surface. The canopy reflected more nearinfrared radiation (NIR) than photosynthetically active radiation (PAR), highlighting a hitherto neglected passive-cooling mechanism. The highest transpiration rate occurs in autumn rather than summer due to dry-mild weather. The woodland canopy could reduce 300 W m−2 energy flux into the substrate. The canopy warmed by solar energy transmits heat to subcanopy air. Latent and sensible heat loss in the subcanopy domain is suppressed, thus dampening the passive-cooling effect. The capability of the tropical intensive green roof to reduce temperature is relatively inefficient comparing with temperate region counterparts. The findings could inform design and choice of green roofs. © 2011 Elsevier B.V. All rights reserved.

1. Introduction Green roofs are increasingly recognized as a modern and ecofriendly technology to cope with climate change and some common urban environmental problems. They could prevent solar energy penetration into buildings, trim the cooling load, and reduce the electricity consumption for air-conditioning systems [1–3]. The benefits of green roof include cooling ambient, surface and indoor temperature and alleviating the urban heat island effect [4,5], reducing rainwater runoff and flood risk, and improving stormwater quality [6–8], creating green amenity spaces especially in compact urban areas [9], increasing lifespan of roofing materials [10,11], and providing habitats and stepping stones for wildlife and enhancing urban biodiversity [9]. In addition, life cycle assessment and valuation analysis indicate a positive economic benefit from vegetated roofs [12–15]. Modern green roofs can be classified as intensive and extensive systems depending on the plant species, construction materials, management and use. Intensive green roof involves planting trees and shrubs that require a deeper substrate of >20 cm and more horticultural maintenance. In contrast, a shallow soil substrate of <20 cm can sustain the grass, herb or drought-tolerant sedum

∗ Corresponding author. Tel.: +852 2859 7020; fax: +852 2559 8994. E-mail address: [email protected] (C.Y. Jim). 0378-7788/$ – see front matter © 2011 Elsevier B.V. All rights reserved. doi:10.1016/j.enbuild.2011.06.018

vegetation of extensive green roofs which only need minimal maintenance. Both intensive and extensive types employ similar materials and structure from bottom upwards: root barrier, drainage, filter, water storage (rockwool), substrate, and vegetation [5]. The merits of intensive green roofs outweigh the extensive type in terms of biomass quality and complexity, biodiversity, microclimatic effect, and landscape and aesthetic value. Intensive green roofs can provide more amenable habitats for birds and insects. The thick soil allows planting of large and woody plants such as trees and shrubs. Accessible green roofs could improve the quality of life in densely built-up urban areas by providing otherwise deficient green spaces. However, intensive green roofs are uncommonly installed due to high roof-loading requirement and installation and maintenance costs [16,17]. Deep understanding of the multiple environmental and economic benefits of green roofs could facilitate the dissemination of the technological innovation. Whereas extensive green roofs have been studied assiduously by researchers and practitioners, less interest has been shown towards intensive ones. The energy and thermal performance of tropical green roofs also deserves more attention. This paper examines the ecological energetics of an intensive green roof, a sky woodland, in Hong Kong in the context of the humid-subtropical climatic zone. We evaluated the microclimatic and biophysical properties of an intensive green roof under different weather and seasonal conditions, and explored its heat

C.Y. Jim, S.W. Tsang / Energy and Buildings 43 (2011) 2696–2704

Fig. 1. The rooftop woodland site showing the locations of the three environmental monitoring stations. The sensors installed at each station are listed in Table 1.

flux patterns and thermal benefits. The findings could inform future design of intensive green roofs and promote its adoption. 2. Experimental design An intensive green roof was designed for the experimental study on the rooftop of a newly constructed electricity substation building situated in the heavily built-up core of urban Hong Kong. The one-story building is 10 m tall with a roof area of 120 m2 . The surrounding buildings, separated by wide roads, are mainly high-rise residential blocks up to 30 storeys in height. The site is characterized by a low building coverage of about 50%, and it well exposed to sunshine with a high sky view factor. The high live-load requirements of the intensive roof equipped with a 1 m thick soil layer amounts to static load of 21 kPa at saturation. As the green roof design started before construction, it was possible to strengthen the reinforced concrete roof slab with additional pre-stressed steel bars. A native woodland was installed on the top with heavy standard planting materials (2–3 m tall saplings) of indigenous tree species with a final height of 5–10 m. Evergreen species were chosen to reduce the seasonal variations in canopy cover and biomass density. Twenty trees were planted closely together to form the interlocking woodland canopy that can generate its own internal microclimate. The construction was completed in late 2007, and the sky woodland was installed in spring 2008. The sky woodland adopted contemporary green roof design and materials based on ecological principles [16]. The schematic drawing of the experimental setup is presented in Fig. 1. Scientific instruments were installed at three monitoring stations, namely

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at the core and edge of the vegetated site and an adjacent bareroof control plot, to monitor key microclimatic and soil attributes (Table 1). They include direct solar radiation, photosynthetically active radiation (PAR), air temperature, dew point temperature, relative humidity, substrate moisture, wind speed, and temperatures at different heights or depths: air at 15 and 160 cm, soil and vegetation surface, soil interior at 10, 50 and 90 cm depth, water storage (rockwool), tile surface (at the bottom below the root barrier), and concrete slab interior (embedded in the concrete) temperatures. Readings were taken automatically at 15-min interval and stored in data loggers. The sky woodland was programmed to irrigate on a daily basis, and watering was turned off when a rainfall sensor has received an accumulated antecedent rainfall of 10 mm. The study period ran from January 2009 to March 2010 to cover a wide range of seasonal and weather conditions. Our study examined some key biophysical quantities computed from the monitoring data, including plant energy budgets, plant transpiration, light environment of canopy layer, and heat flux penetration. This study presents the biophysical dynamics of an intensive green roof that can be used to evaluate its performance under different weather conditions. Some typical days are chosen to evaluate the weather effects over four seasons: 30 March 2009 (Spring sunny), 25 March 2009 (Spring rainy), 2 August 2009 (Summer sunny), 5 August 2009 (Summer rainy), 26 September 2009 (Autumn sunny), 28 September 2009 (Autumn rainy), 4 January 2009 (Winter sunny), and 29 December 2009 (Winter rainy). The selection criteria for these representative days are: (1) Autumn and winter rainy days: >10 mm cumulative daily rainfall; (2) Spring and summer rainy days: >40 mm cumulative daily rainfall; (3) Autumn and winter sunny days: >500 W m−2 of average solar radiation; and (4) Spring and summer sunny days: >700 W m−2 of average solar radiation.

3. Biophysical dynamics The plant leaf temperature depends on the changing environmental conditions. Most plant leaves have small masses and contain a limited amount of water. Leaves experience wide temperature fluctuations because of the relatively low heat capacity. Plant leaves must respond to external environmental influences, such as solar radiation, wind, relative humidity, and air temperature, to counteract stresses and remain functional.

Table 1 The environmental sensors at three monitoring stations established on the rooftop woodland experimental site. Monitoring stationa

Sensor Environmental attribute

Model & brand

Measurement parameter and position

Soil moisture sensor

S-SMC, Onset Hobo, USA

Air temperature sensor Soil temperature sensor

S-TMB, Onset Hobo, USA S-TMB, Onset Hobo, USA

Concrete temperature sensor Infrared temperature sensor

8160.TF, Lufft, Germany SI-111, Apogee, USA

Soil moisture at 10 cm, 50 cm and 90 cm depth Rockwool moisture Air temperature at 15 cm and 160 cm height Soil temperature at 10 cm, 50 cm and 90 cm depth Tile temperature (green roof bottom under root barrier) Concrete roof slab internal temperature Surface temperature of soil with groundcover vegetation Surface temperature of tree canopy Surface temperature of bare concrete roof Relative humidity at 15 cm and 160 cm height Dew point temperature at 15 cm and 160 cm height Intensity and duration of solar radiation Wind speed and wind direction

Relative humidity sensor Dew point sensor Pyranometer Anemometer

S-THB, Onset Hobo, USA S-THB, Onset Hobo, USA S-LIB, Onset Hobo, USA S-WCA, Onset Hobo, USA

Core √ √ √ √ √ √ √ √ √ √

Edge

Control

√

√

√ √ √ √ √

√ √ √ √ √

a The core monitoring station is situated at the center of the rooftop woodland, and the edge at its perimeter wall; the control is set up on the bare concrete rooftop of an adjacent stairwell. The positions of the three stations are shown in Fig. 1

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C.Y. Jim, S.W. Tsang / Energy and Buildings 43 (2011) 2696–2704

3.1. Transpiration

of zero plane displacement, roughness length can be approximated by one-tenth of the average height of the canopy.

The transpiration of living leaves occurs through stomata to allow the diffusion of carbon dioxide from the air for photosynthesis. Water vapor between mesophyll cells diffuses across the leaf boundary layer to the atmosphere during transpiration. Campbell and Norman18 indicate that the transpiration rate (mol m−2 s−1 ) can be computed as E = gv

es (TL ) − ea pa

(1)

where  is the latent heat of vaporization for water (44 kJ mol−1 ), pa is the air pressure, es and ea are the vapor pressures at the leaf surface and in the air, and gv is the vapor conductance (mol m−2 s−1 ). The vapor conductance is the average surface and boundary conductance for the entire leaf. The abaxial and adaxial conductance values are different for most plant species. Campbell and Norman [18] approximate the vapor conductance as gv =

0.5gvab s gva gvab s + gva

+

0.5gvad s gva gvad s + gva

(2)

where the superscripts ab and ad refer to the conductance on abaxial and adaxial leaf surfaces. The vapor conductance in air is given by



gva = 1.4 · 0.147

u . d

(3)

The latent heat loss can be rewritten in terms of relative humidity as gv

es (TL ) − es (Ta ) es (Ta )(1 − Hr ) + gv pa pa

es (T ) = a exp

T +c

(4)

(5)

where T is Celsius temperature. The constants a = 0.611 kPa, b = 17.502, and c = 240.97 ◦ C, are specified for environmental biophysics applications. 3.2. Wind at the canopy top Wind is essential to terrestrial life in the Earth. For instance, wind could influence the rate of heat transportation and evaporation of living organisms to maintain proper body temperature. The wind speed increases with the height of observation from nearly zero on the ground surface. Campbell and Norman describe the wind speed as a logistic function in term of observation height z [18]. Mathematically, it can be expressed as u∗ z−d u(z) = ln 0.4 zm

 z

u(z) = u(h) exp a

(6)

where u* is the friction velocity (ms−1 ), d is the zero plane displacement (m), and zm is the roughness length (m). This equation is only valid for the case of observation height greater than the sum of roughness length and plane displacement and is appropriate for the atmospheric surface layer (<100 m). The zero plane displacement d is the height above the ground that the wind speed is diminished by the vegetation. It is approximated by multiplying 0.65 to the average height of the canopy. The roughness length is a measure of the roughness of vegetation surface. Like the empirical relation

h



−1

(7)

where u(h) is the wind speed at the top of the canopy with the height h and a is the attenuation coefficient for plant. Empirical research [18] shows that the attenuation coefficient can be approximated as



a≈

0.2Lt h lm

(8)

where Lt is the leaf area index, and lm is the mean distance between leaves. If the average leaf width is w, it can be modeled as lm =

where Hr is the relative humidity. Using Tetens’ formula [18], the empirical relation between vapor pressure and temperature is given by

 bT 

Eq. (6) describes the microenvironment above the canopy layer and assumes zero wind speed near the top of the canopy. However, this is apparently incorrect as the wind can blow into the canopy. The wind speed within the canopy layer is an important factor in roof greening research because it affects plant evapotranspiration and thermal insulating performance. In order to estimate the wind effect within the canopy, the mathematical formulations can be separated into two layers: above and below the canopy. The wind effect at the top of the canopy has been discussed in the above subsection. According to Campbell and Norman [18], the wind speed within the canopy can be modeled as



es (TL ) − ea es (TL ) − es (Ta ) es (Ta ) − ea = gv + gv pa pa pa = gv

3.3. Wind below the canopy

4wh . Lt

(9)

Typically, the attenuation coefficient for trees is from 1.0 to 1.2. Therefore, the computed wind speed within the canopy can be used in the latter part of calculation in soil evaporation. 3.4. Light transmission through the canopy The leaf could shield some of incident solar radiation reaching the soil surface. However, most leaves are not oriented horizontally in the nature. They are randomly distributed at different orientations. The extinction coefficient is the ratio between the mean beam flux density on an average illuminated leaf in the canopy at a particular zenith angle and the beam flux density on the horizontal plane above the canopy. If a leaf is perfectly horizontal-oriented, the extinction coefficient is expected to be 1. Campbell [19] generalizes the conventional form of extinction coefficient to ellipsoidal as



Kbe ( ) =

x2 + tan2

x + 1.774(x + 1.182)−0.733

(10)

where x is the ratio of average projected areas of canopy elements on horizontal and vertical surfaces. The typical value ranges from 0.6 to 2.5. When solar radiation reaches the leaf surface, reflection and transmission of radiation are observed. The transmission of total solar radiation for a dense canopy layer, including direct and diffused, can be described by an empirical relation [20] as √ bt = exp[− ˛Kbe ( )L]

(11)

where ˛ is the radiation absorptivity of leaves, and L is the depth of canopy layer to the soil surface. Typical values for ˛ are 0.8 for PAR and 0.2 for near-infrared radiation (NIR).

C.Y. Jim, S.W. Tsang / Energy and Buildings 43 (2011) 2696–2704

3.5. Light reflection by the canopy A certain amount of solar radiation reaching the leaf surface may reflect back to atmosphere. Goudriaan [21] suggests the modified reflection coefficient for a dense canopy layer as 2Kbe ( ) H (12)  Kbe ( ) + 1 cpy √ √ H = 1 − ˛/1 + ˛ is the canopy hemispherical reflecwhere cpy tion coefficient. The PAR and NIR wavelength bands should be treated separately due to different properties of spectral absorption. Solar albedo value ˛ is the reflecting power of plant. The estimate of solar albedo value is found by averaging the canopy hemispherical reflection coefficients at PAR and NIR wavelength bands as b ( ) =

˛=

1 H 1 H (NIR)  (PAR) + cpy 2 cpy 2

(13)

H (PAR) and H (NIR) are the canopy hemispherical reflecwhere cpy cpy tion coefficients at PAR and NIR wavelength bands respectively.

3.6. Energy flux through the canopy

I = QT + QS + IT + IR

(14)

where QT is the latent heat loss by canopy transpiration, QS is the sensible heat, IR is the solar radiation reflected, and IT is the solar radiation transmitted into the subcanopy space. Newton’s law of cooling is commonly used to describe the convection effect that depends on the temperature difference between two layers [18]. Mathematically, it can be expressed as QS = cp gHa (TS − Ta )



QG = −

u . d

T (z) − T (z + z) z

(16)

(20)

where  is the thermal conductivity of soil–water–air mixture, and z is the soil depth measured from the soil surface. In the present experiment, the readings of soil temperature are taken by temperature sensors underneath the soil layers. The infinitesimal soil depth is 0.1 m. Empirical evidence shows that the thermal conductivity of a soil–water–air mixture can be modeled as  ≈ max[418 exp(−log10 |

p | − 2.7), 0.172]

(21)

where p is the moisture potential that depends on the soil moisture. Generally, the empirical form of moisture potential is used for the calculation: p

=

p,s

wg,s wg

b

(22)

where p,s is the moisture potential when the soil is saturated with liquid water, wg is the volumetric water content of the soil, wg,s is the maximum volumetric water content that a given soil type can hold, and b is a scaling parameter that relates to the soil type used in the experiment. As sandy loam is used in the present green roof experiment, the parameters used in the calculation are b = 4.9, wg,s = 0.435 m3 , and p,s = 0.218 m. The convectional energy exchange can be found by measuring the temperature difference between two observation heights as QS = cp gHa (T  S − Ta )

(23)

where TS is the soil surface temperature, Ta is the air temperature at 1.6 m above the soil surface. The latent heat loss due to soil evaporation can be estimated from the Bowen ratio ˇ that indicates the relationship between sensible and latent heat as

(15)

where cp is the specific heat of air (29.3 J mol−1 C−1 ), gHa is the convection conductance, TS is the canopy surface temperature, and Ta is the air temperature. Empirically, the convection conductance relates to wind speed u and zero-plane displacement d in form of gHa = (1.4)(0.135)

where Ip is the solar radiation absorbed by plants for photosynthesis. The energy flux below the canopy consists of soil heat flux, soil evaporation, and conventional energy exchange between the soil surface and shielded cavity. The soil heat flux can be calculated from measuring the difference of soil temperature at infinitesimal depth z. The soil heat flux formula in discretized form can be expressed as [22]



Solar radiation arriving at the Earth can be classified into short-wavelength and long-wavelength. The nuclear fusion of sun produces strong shortwave radiation. Of the shortwave radiation reaching the Earth’s surface, a fraction is returned to the atmosphere as longwave radiation. The energy balance for net solar radiation on the surface of the canopy is the sum of incident and reflected shortwave and longwave radiation. It could transform into latent heat, sensible heat, and the energy flux on the canopy layer as

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QE =

QS

(24)

ˇ

The Bowen ratio for a wet surface ranges from 0 to 0.2 [23]. The energy fluxes above (Eabove ) and below (Ebelow ) the canopy are given as Eabove = I − Ir − QS − QT , and

(25)

Various surfaces have different reflection properties. The albedo value is the ratio of reflected radiation from the surface to the incident radiation. The reflected solar radiation from the canopy can be considered as

Ebelow = IT + Q

IR = ˛I

Eqs. (1)–(13) describe major biophysical quantities in the present research. Modern sensors have been installed to take readings for the calculations. In the following discussion, the green roof microenvironment is examined under different weather and seasonal conditions.

(17)

where ˛ is the solar albedo value for trees, which is defined in Eq. (13). Since some of the solar radiation could transmit through the canopy, transmission coefficient ϕ is used to describe the fraction of solar radiation entering the subcanopy domain. Mathematically, it can be written as IT = ϕI.

(18)

The balance of solar radiation is therefore given as I = IR + IT + Ip

(19)



 S + QE

+ QG .

(26)

4. Results and discussion

4.1. Transpiration Transpiration is a physical mechanism that contributes to plant thermal regulation. The liquid water in the soil moves from roots to substomatal cavities to sustain the transpiration process. The transpiration rate depends on both internal and external factors,

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40

90

50

23:00

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Time

Fig. 4. Seasonal and diurnal relative humidity of the sky woodland.

Fig. 2. Seasonal and diurnal latent heat loss of the rooftop woodland canopy.

including soil water availability, photosynthesis, solar energy, and wind speed. The average air pressure is assumed to be 101 kPa in the present research. The leaves are hypostomatous with zero adaxial conductance and an abaxial conductance of 0.5 mol m−2 s−1 . The annual transpiration shows a cyclic pattern over four seasons. Based on the experimental data, it is not surprising that the highest transpiration rate is observed in autumn rather than in summer because of the low relative humidity and mild air temperature. The relative humidity averages at 50% in autumn compared with 80% in summer. The air temperature averages at 23 ◦ C in autumn compared with 15 ◦ C in winter. Fig. 2 depicts the daily latent heat loss by transpiration in four seasons. The seasonal transpiration rates on sunny days in descending sequence are: autumn, summer, winter, and spring. The transpiration rate peaks in autumn due to a high level of PAR (Fig. 3), and low relative humidity (Fig. 4). PAR is the light spectrum of solar radiation ranging from 400 to 700 nm that are used by chlorophyll to convert carbon dioxide to sugars during photosynthesis. The opened stomata allow the diffusion of carbon dioxide into substomatal cavities for gaseous exchange. In the process, water vapor can diffuse from the leaf tissue to external environment through stomata through transpiration. The dry weather at 60% relative humidity in autumn could expedite water vapor diffusion to increase water loss. A relatively high transpiration rate is observed on summer sunny day because the intensive PAR promotes active production of

400

sugars via photosynthesis. On winter sunny day, the transpiration rate is lower than autumn and summer because of low PAR level. The mild solar radiation reduces photosynthetic rate although the relative humidity is the lowest in winter. The lowest transpiration rate is observed in spring amongst the four sunny days selected in this analysis. The high relative humidity is the crucial factor that dampens the transpiration rate. Wind is not a major factor of transpiration rate in the four seasons. Fig. 5 shows the sunny and rainy wind speed measured at canopy top. The wind speed is relatively higher on rainy days than on sunny ones. The wind speed on rainy and sunny days averages at 3 ms−1 and 1 ms−1 respectively. The correlation coefficients between wind and transpiration at −0.1 to 0.1 (p ≤ 0.05) is weak. Although wind speed is higher on rainy days, the associated high relative humidity suppresses transpiration. The transpiration rate on rainy days is notably lower than on sunny days (Fig. 2). The highest transpiration rate occurs on the summer rainy day. The high summer air temperature, ranging from 29 to 36 ◦ C, increases the transpiration rate. The rise in kinetic energy of water molecules inside the stomatal cavities could increase water loss and latent heat loss. Interestingly, the lowest transpiration rate is observed on the autumn rainy day. The relatively humid weather with weak PAR as shown in Figs. 3 and 4 subdues transpiration. The remaining curves of latent heat loss in Fig. 2 fluctuate within a narrow amplitude because of high relative humidity and weak PAR. Unlike the green roof in the temperate region, our experiment shows that the transpiration rate of an intensive green roof in the humid-subtropical region, dominated by the Monsoon climate

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Fig. 5. Seasonal and diurnal wind speed above the canopy of the sky woodland.

C.Y. Jim, S.W. Tsang / Energy and Buildings 43 (2011) 2696–2704

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system, depends mainly on PAR and relative humidity. Wind has relatively little impact on the transpiration process. Our intensive green roof registers latent heat loss by transpiration from 5 to 35 mol m−2 s−2 , which is about 60% less than an extensive green roof in the same climatic zone [24]. The differences indicate that the thermal dissipation of intensive green roof through transpiration is relatively inefficient in humid-subtropical weather conditions. This is attributed to the dense packing of tree leaves, high relative humidity especially in summer, frequent rainfall in the long wet and warm season, and the microenvironment shielded by the canopy to reduce the latent heat loss of soil evaporation. 4.2. Wind Modeling the variation of wind speed for the canopy is often divided into two layers: above and below the canopy. Fig. 5 shows daily variation of wind speed above the canopy, and Figs. 6 and 7 at 0.15 m and 1.6 m above the soil surface. The wind friction velocity is 0.33 in our experiment. The experimental data show that the wind speed varies from an average of 0.1 ms−1 near the soil surface to 2 ms−1 at a height of 10 m. The low wind speed near the ground below the canopy is the result of drag force and skin friction in the layer of air interacting with the surface. Our experiment shows that the sky woodland canopy is well shielded from the influence of the external environment. Above the canopy, the wind speed increases

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Spring sunny (20090330) Summer sunny (20090802) Autumn sunny (20090926) Winter sunny (20090104)

Fig. 8. Seasonal and diurnal air temperature and relative humidity at 0.15 m above the soil surface of the sky woodland. The left y-axis refers to the lower groups of lines; the right y-axis refers to the upper group of lines.

rapidly because the frictional force of vegetation decreases notably with height. Below the woodland canopy, the wind speed increases with height from the soil surface. The wind speed at 0.15 m and 1.6 m demonstrates very similar patterns. Comparing Fig. 5 with Fig. 2, the wind above the canopy could slightly increase the convective latent heat loss. However, the roughness of the canopy layer decreases wind speed in the microenvironment within the woodland canopy. Figs. 5–7 show that the wind above the canopy is about one order of magnitude higher than below the canopy. The densely planted trees of the sky woodland have created its own microclimate and maintained it in a relatively stable state. Figs. 8 and 9 show the variations of air temperature at 0.15 m and 1.6 m above the soil surface. The experimental results show that wind speed is slightly correlated with subcanopy air temperature, with a coefficient of −0.1 to 0.1 (p ≤ 0.05). For the sunny days, the wind speed at 0.15 m and 1.6 m is lower than the rainy days in four seasons. The wind speed on sunny days ranges from 0.025 to 0.15 ms−1 at 0.15 m and 0.05–0.5 ms−1 at 1.6 m respectively. In contrast, the wind speed on rainy days ranges from 0 to 0.25 ms−1 at 0.15 m and 0.95 ms−1 at 1.6 m. At these two heights, the relative humidity on sunny days varies from 40% to 80%, which

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Fig. 9. Seasonal and diurnal air temperature and relative humidity at 1.6 m above the soil surface of the sky woodland. The left y-axis refers to the lower groups of lines; the right y-axis refers to the upper group of lines.

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The woodland canopy could intercept solar radiation and trim its transmission to the soil surface. In this study, the light transmission through and reflection by the canopy are examined. The variations in the light environment could provide data to estimate the energy flux through the canopy. Eqs. (10)–(11) describe the physics of light transmission through canopy layer. The plant emissivity of 0.97 was used in the calculation and the result is presented in Fig. 10. The light transmission peaks in summer, followed by spring, autumn, and winter. The weather effect (sunny or rainy) has little impact on the diurnal pattern of light transmission as the interception depends mainly on leaf density and canopy texture. If the canopy is dense, a good proportion of solar radiation cannot penetrate it to reach the ground. However, the seasonal effect on light transmission is significant. The fraction of light transmission varies from 0.17 in winter to 0.27 in summer because the light transmission depends on the solar zenith angle as suggested by Eq. (10). Generally, the summer sunny and rainy days have similar trends in light transmission, and the transmission reaches the maximum at noon in four seasons. The light reflection depends on the absorptivity of plant leaves. The typical values of plant absorptivity at PAR and NIR wavelength used in Eq. (12) were 0.8 and 0.2 respectively. The PAR and NIR bands are treated separately in biophysics because of their different spectral properties on light reflection of leaves. According to Campell and Norman [18], this approach could give a better estimate of the solar albedo value. The woodland canopy preferentially reflects more NIR than PAR, providing an additional dimension to the passive cooling benefit of the intensive green roof. Figs. 11 and 12 show the light reflection respectively at PAR and NIR bands in four seasons. The leaf reflection at NIR band is about four times higher than PAR because most of PAR is absorbed by leaves for photosynthesis. The reflection curves at PAR band resemble the NIR band. The overall values are low for both bands because the reflection coefficient depends on the solar zenith angle as suggested by Eq. (12). In addition, the physical properties of light are different at PAR and NIR bands as suggested by Eq. (13). The aver-

age albedo value is therefore used in the calculating light reflection of the sky woodland. Fig. 13 shows the changes in average solar albedo value over four seasons. The curves are similar to the reflection curves of PAR and NIR bands. The albedo values on sunny and rainy days vary from 0.19 to 0.26. The winter sunny and rainy days have the highest albedo amongst the seasons, whereas the summer sunny and rainy days have the lowest. The spring and autumn albedo values lie between summer and winter. The results suggest that the use of a constant solar albedo value in estimating living-plant reflectance,

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are higher than the ambient humidity of 40% to 70%. The subcanopy air temperature is slightly lower than ambient temperature (Fig. 12). Overall, the woodland canopy forms a protective shield to the enveloped microclimate of the sky woodland. However, the protected subcanopy microenvironment could reduce soil evaporation and hence dampen the latent heat dissipation benefit of the green roof.

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commonly adopted in cognate studies, may not be accurate due to notable seasonal variations. The average albedo value from our findings is used in the ensuing calculation of energy flux through the woodland canopy. 4.4. Energy flux through the woodland canopy The canopy of the intensive green roof could shield the microenvironment underneath and reduce the solar radiation reaching the roof slab. By measuring the air temperature and radiation flux at different heights, the energy flux through different foliage-branch layers of the woodland canopy can be estimated. In order to evaluate the contribution of the canopy in thermal insulation, we focus on the energy flux above and below the canopy. Eqs. (14)–(26) describe the physics of energy flux through the woodland canopy. The computed results of energy flux above and below the canopy are presented respectively in Figs. 14 and 15. The positive value means energy flowing down through the canopy. For the energy flux above the canopy, the peak reaches 550 W m−2 on the spring sunny day, followed by autumn, summer, and winter. The seasonal peaks range from 400 to 550 W m−2 . The incident solar radiation reaches the tree canopy layer, some of which could transmit through the canopy. A portion of the incident solar radiation is absorbed by tree leaves for photosynthesis. The remaining incident solar radiation is transformed into sensible and latent heat. The humid weather in spring reduces the transpiration rate as shown

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in Fig. 2, resulting in the highest energy influx into the canopy in spring. On rainy days in the four seasons, the energy influx remains low as the sun is screened by clouds. Negative value of energy flux is observed at the night time. The energy flux through the canopy reaches its peak on autumn sunny day. The dry weather in autumn expedites the evaporation rate and latent heat loss. For the energy flux below the woodland canopy, a positive value means energy flowing from the canopy towards the soil surface. It peaks on summer sunny day and the seasonal peak ranges from 170 to 270 W m−2 (Fig. 15). The subcanopy microclimate is noticeably different from the macroclimate. Unlike the energy flux above the canopy, the ranking of seasonal peak of energy flux below the canopy is summer, autumn, spring and winter. The summer peak is mainly caused by air temperature increase at 1.6 m underneath the canopy shield. The air temperature at 1.6 m is strongly correlated with leaf temperature (correlation coefficient = 0.96; p ≤ 0.05). The solar radiation heats up the leaves, and then the absorbed heat is diffused into the subcanopy layer. On rainy days, the energy flux reverses, and it moves from the soil surface towards the canopy in autumn, spring, and summer. In contrast, the upward energy loss in winter is mild. As the sun is covered by clouds on rainy days, the incident solar radiation is weak, thus trimming the amount received by the green roof. The highest energy loss occurs in autumn mainly because of the low relative humidity (Fig. 4). The thermal insulation by the woodland canopy can be estimated by finding the difference in the energy fluxes above and below the canopy. Figs. 14 and 15 indicate that the canopy could reduce about 300 W m−2 of energy flux from flowing into the substrate and building. The shielded subcanopy space has created a rather well cloistered microenvironment. The subcanopy microclimate is different from the macroclimate notably in wind, light environment, convection, evaporation and transpiration. On sunny days, the woodland canopy could effectively prevent excess solar radiation from reaching the soil surface. Besides the reflected portion, a notable amount of solar radiation is absorbed by trees for photosynthesis, which could expedite the transpiration process to enhance latent heat loss. On rainy days, the canopy could prevent the heat loss from soil substrate, particularly in autumn. Comparing with roof greening studies in temperate regions [3], the thermal insulation and passive cooling effect of the subtropical intensive green roof is not as significant. Figs. 14 and 15 indicate that about 100 W m−2 of heat loss from soil substrate is observed in autumn and summer rainy days, associated with a noticeable amount of heat gain from the sun in spring and summer. 5. Conclusion To recapitulate briefly, this study examined the ecological energetics of an intensive green roof in the humid-subtropical region. It distinguishes from the extensive type in having a relatively lower transpiration rate and less latent heat loss. The seasonal effect is significant for transpiration, light environment, solar albedo value of tree, and energy flux through the canopy. On the other hand, the weather effect plays an important role in canopy latent heat loss and energy flux. The main research findings are concluded as follows: (1) The wind does not play a major role in facilitating transpiration rate in the four seasons, as indicated by a rather low correlation coefficient between the wind above the canopy and transpiration. On sunny days, the sensible heat loss through air convection is not significant because of low wind speed. Although the wind speed is higher on rainy days, the effect of evaporative cooling is partly offset due to suppression by high relative humidity.

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(2) The highest transpiration rate occurs in autumn rather than in summer. The dry weather coupled with sufficient PAR in autumn enhances the transpiration process. The accelerated diffusion of water vapor through stomata during photosynthesis increases the latent heat loss. However, the thermal dissipation capability of the intensive green roof in the humid-subtropical climate through the transpiration process is relatively inefficient. This relative deficiency is attributed to the dense packing of tree leaves and high relative humidity in summer. (3) The rooftop woodland forms a shielded space below its canopy to create a rather well cloistered microenvironment. The wind speed decreases notably below the canopy due to drag force and skin friction between the air layer and its interacting surfaces. The experimental data show that the latent and sensible heat loss in the subcanopy domain is dampened. The partly trapped air below the woodland canopy could store the energy released from the substrate in autumn and summer to buffer the heat loss of the building during rainy days. (4) Only about 20% of the incident solar radiation could be transmitted through the rooftop woodland canopy to reach the soil surface, thus providing substantial shading and associated cooling effect. About 6% of PAR and as much as 40% of NIR are reflected by the canopy back to the atmosphere. Moreover, the woodland canopy preferentially reflects more NIR than PAR, providing an additional dimension to the passive cooling benefit of the intensive green roof. (5) The dynamic solar albedo value is estimated in the present study. Averaging the canopy hemispherical reflection coefficients between PAR and NIR could provide a more realistic albedo value in calculating energy flux through the canopy. This approach is regarded as an improvement over the commonly adopted constant albedo value, as it takes into account the physical properties of light at different wavelength bands. (6) The energy flux is examined at above and below the woodland canopy. The canopy could prevent about 300 W m−2 of energy flux from flowing through the substrate and into the building. However, the shielded space below the canopy could reduce the sensible and latent heat loss directly from the soil to reduce the thermal insulating properties of the intensive green roof. The strong correlation between tree leaf temperature and air temperature at 1.6 m above the soil surface indicates heating of the canopy by solar energy, and the subsequent diffusion of the absorbed heat down to the subcanopy shielded realm. The warm air under the canopy may subdue the thermal insulation performance of the intensive green roof. (7) As the use of passive cooling has several noticeable merits [25], the scientific findings in the present research could inform the design and choice of green roofs in tropical cities. Acknowledgements We would like to acknowledge with gratitude the research grants furnished generously by the China Light and Power Company Limited, Stanley Ho Alumni Challenge Fund, the Government Matching Grant, and the laborious field work assistance kindly provided by Jeannette Liu and W.Y. Wong.

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