study on the effect of evapotranspiration cooling on the...

Int. J. of Sustainable Water & Environmental SystemsVolume 8, No. 2 (2016) 59-64

* Corresponding AuthorE-mail: [email protected]© 2016 International Association for Sharing Knowledge and SustainabilityDOI: 10.5383/swes.8.02.005

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aSchool of Energy, Geoscience, Infrastructure and Society, Heriot-Watt University, P. O. Box 294 345, Dubai, UAEbCSIRO Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation (CSIRO), P.O. Box 56,

Graham Road, Highett, Victoria 3190, Australia

AbstractThe aesthetic values of green parks and gardens are well understood by landscape architects and horticulturalists. However,quantitative evidence supporting the added climatic value of urban green infrastructures in its potential forevapotranspiration cooling remains under researched and remains as a topic necessary for further investigation. The benefitof evapotranspiration cooling has recently received increasing attention amongst urban planners and building designersdue to the current agenda on sustainable urban development and the aim to reduce greenhouse gas emission. Studies at thesingle building scale claim that mean and peak energy demand of buildings are reduced with the application of vegetatedand reflective roofs, green walls, but there are few studies on the interaction between evapotranspiration and local airmovement in the urban built environment at neighborhood scales to quantify these benefits. This study seeks to explorewhether modifications of the urban microclimate to counteract heat wave is possible by increasing the total amount ofvegetative cover using computational fluid dynamics (CFD) modelling at a neighborhood scale. A 3D transient Reynolds-average Navier-Stokes (RANS) simulation with the realizable κ-ε turbulence model on a high resolution grid of 875,000unstructured grids was conducted. The effect of transpiration cooling of vegetation on possible heat wave mitigation andthermal comfort improvement in an actual urban environment of Parramatta, Western Sydney is analyzed throughout threeconsecutive days during a heat wave period. Possible peak temperature reduction in the local urban environment isexplored. Simulation results of the study show up to 4.65C reduction in peak air temperature with an averaged 2.88Ccan be observed during three day heat wave period with the doubling vegetation coverage scenario. This effort would helpboth public and government level for better urban development and environmental planning in the future.

Keywords: Evapotranspiration Cooling, Urban Vegetation, Urban Heat Islands, Heatwave, Neighbourhood Scale,Computational Fluid Dynamics

1. Introduction

With rapid urbanization process globally, large amounts ofgreen space in the urban areas and its adjacent suburbs issubstituted by impermeable hard surfaces of roads and concretebuilding blocks etc. Without the presence of water evaporationfrom replaced vegetation and permeable surfaces as coolingsinks, these hard surfaces due to absorbing heat from suneventually become relatively hot in summer. A later heat

release from these surfaces together with other anthropogenicheat have undeniably increased urban temperature, intensifiedthe summer urban heat islands (UHI) effect, deteriorated thecomfort conditions and consequently made the urban areas morevulnerable to the impact of heat waves. According to Oke(1982), factors that contribute to a UHI include increased short-wave radiation gain, amplified long-wave radiation gain fromthe sky, decreased long-wave radiation loss, anthropogenic heat

Study on the Effect of Evapotranspiration Cooling on the UrbanThermal Environment in Parramatta, Western Sydney

Jun Han a,*, Dong Chen b, and Xiaoming Wang b

Han et al. / Int. J. of Sustainable Water & Environmental Systems, 8 (2016) 59-64

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sources, increased heat storage, less evapotranspiration anddecreased turbulent heat transport. In Western Sydney, recenturban expansion moves further to the west. It is necessary toquantify the potential transpiration cooling effect fromvegetation, in order to quantitatively guide the urban green spaceplanning and increase the awareness for green space protection.The Urban Heat Island effect can be a significant health threatto urban dwellers as heat-related stress accounts for around 1100premature deaths per year in the UK – increasing noticeably inexceptionally hot years (Doick and Huchings, 2013). In recentyears, urban greening and cool surfaces have attractedsubstantial interests in mitigating the impact of heatwaves(Rosenfeld et al., 1998; Akbari et al., 2001; Liu and Bass, 2005;Rosenzweig et al., 2005; Yu and Hien, 2006; Luber, 2008;Alexandri and Jones, 2008; Memon et al., 2008; Bowler et al.,2010; Wong and Lau 2013). Urban greening can mitigate heatby shading and evapotranspiration. Cool surfaces such asreflective roofs and paving surfaces reduce heat absorption inurban areas. The interests in studying the impact of urbanvegetation may be categorized into three scales: the urban,neighbourhood and building scale.Using urban climate modelling, Chen et al. (2014) assessed thepotential impact of vegetation on the urban scale ambientenvironment in Melbourne Central Business Districts (CBD).Simulation results suggest that average seasonal summertemperatures can be reduced in the range of around 0.5 and 2Cif the city were replaced by vegetated suburbs and parklands,respectively. It is noted that the typical spatial resolution of anurban scale climate modelling is 1 km. This indicates that, withurban scale climate modelling, the characteristics and the effectsof vegetation are averaged within 1 km 1 km grids.At the building scale, it has long been recognised that properarrangement of trees and shrubs around residential buildings canreduce indoor temperatures during summer (Meier, 1990).Using dynamic building simulations, Ren et al. (2014)investigated the potential benefits of the provision of local treeshade around residential buildings to reduce the impact ofheatwaves on occupant health and the energy required forcooling. The simulations were carried out for a residential homeunder various urban greening and tree shade scenarios for the2009 (Melbourne) and 2011 (Sydney) heatwaves. It was foundthat doubling the urban green coverage of the CBD inMelbourne and Parramatta, together with proper tree shadingaround a residential home may reduce the total annual hours of‘severe’ heat-related health risk by 14% and 44.6%,respectively. The building scale simulations took into accountthe averaged climate data from the urban scale climatemodelling results of Chen et al. (2014) as well as the effects oftree shade adjacent to the building. At the neighborhood scale,observational approaches with filed measurement andComputational Fluid Dynamics simulation were performed tounderstand the effect of urban greening and evaporative coolingon the urban microclimate, and effect of wind velocity patternon the temperature field (Toparlar, et al. 2015). At themesoscale, an atmospheric modal equipped with a sophisticatedland-surface scheme was used to study the potential impact ofvegetation under different vegetation coverage, specifically 0,33%, 67%, and 100%, on the urban thermal environment and thewind generated by urban-rural contrasts (Avissa, 1996).Research results showed that temperature reduction of 5 K underno wind condition at 3 pm can be achieved with vegetationcoverage of 33%. The temperature reduction range can evenextend to 10 K with vegetation coverage of 67%.

It is noted that in the previous studies by Chen et al. (2014) andRen et al. (2014), the effects of the arrangement of vegetationand trees around a group of buildings, i.e., the neighborhoodscale, were not investigated. The interaction betweenevapotranspiration and local air movement cannot beinvestigated with the urban scale and the single building scalemodelling techniques.In this study, computational fluid dynamics (CFD) simulationswere used to investigate the vegetation effects at theneighborhood scale in Parramatta, NSW.

2. CFD and Model Representation

In this study, a commercial CFD package, FLUENT release 15.0(ANSYS 2013), was used for the flow fields and heat transfersimulations for a selected site at the Parramatta CBD area, amajor business district in the metropolitan area of Sydney. Thesite under consideration is located in the suburb Parramatta,Greater Western Sydney NSW, 23 km west of the Sydneycentral business district. Recent major upgrades have been madearound the Parramatta railway station. This region is composedof new transport interchange facilities, residential andcommercial building stock with several street canyons and a fewhighrise buildings. Figure 1 and Figure 2 shows the GoogleEarth view and the 3D building model of the selected site inFLUENT.

Figure 1 – 3D Representation of a Neighborhood Site atParramatta, NSW: (A) Google Earth View; (B) Computational

Model


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Figure 2 – The 3D Building Model under Study (Using CAD&GIS Digital Data)

The site extends approximately 500 m and 350 m in the east westdirection and the north south direction respectively. Underneaththe buildings, a 1 meter soil layer is included in the simulationmodel to account for the thermal mass of the ground. The overallcomputational domain is a 36 edged polygon cylinder with adiameter of 1000 m and a height of 400 m. The k- model wasused for turbulence modelling. The 36 edge faces of the polygoncylinder were assigned to be the inlets and outlets of the air flowbased on the wind direction in each hour. Power law urban windspeed profile was used at the inlets. The wind directions, windspeeds as well as the air temperatures at the inlets were obtainedfrom the urban scale climate modelling using The Air PollutionModel (TAPM) (Thatcher M and Hurley, 2012).

Figure 3 – Face Grids of the Buildings and Spatial Discretization ofthe Ground for a Neighborhood Site at Parramatta, NSW

The influences of solar radiation and buoyancy effect have beentaken into account using the inherent calculators embedded inFLUENT. A total of 875,000 unstructured grids were used in thesimulation. Figure 3 shows the face grids of buildings and theground. In order to minimise the computation time, substantialefforts were devoted to the optimisation of the grid allocationand boundary condition automation. It was found that it tookapproximate five hours of CPU time for modelling each physicalhour without using high performance parallel computing. Eachsimulation was planned to be carried out for a total of 72physical hours from 0:00am, 2 February 2011 to 00:00am, 5February 2011 during the 2011 Sydney heatwave period.Consequently, a simulation for the three-day heat waves periodwill take over two weeks of CPU time. Currently, the authors are

accessing supercomputer resources to speed up the simulations.Under the high performance parallel computing, the CUP timefor simulating airflow of 1 hour takes approximately 45 minutes.

3. Boundary Conditions

In addition to the computer resource requirement, majordifficulties encountered during the CFD modelling of theneighbourhood scale are: (a) the lack of accurate historyof the soil moisture conditions and thusevapotranspiration; and (b) difficulties in modelling theheat transfer in the ground soil. Due to the computationresource requirement, it is impossible to simulationseveral months or even several weeks in physical timewith CFD modelling. Consequently, the history ofmoisture content and the temperature distribution in theground soil cannot be obtained from the current CFDsimulations. In this study, the long wave radiation fromthe ground surface to the sky (affected by both (a) and (b))and the evapotranspiration cooling effect of vegetation(mainly affected by (a)) were taken from the urban scaleclimate simulation results, considering that the urbanclimate model can model these parameters for a wholeyear. The evapotranspiration cooling from vegetation iscalculated from The Air Pollution Model (TAPM), whichis a PC-based, nestable, prognostic meteorological and airpollution model, (Thatcher and Hurley, 2012). Thesimulation results from TAPM have been used as inputheat flux boundary condition on the ground to account forthe evapotranspirational cooling due to vegetationcoverage. The wind profile is calculated according toSwami 1988, the data sources of wind speed is measuredat an airport with a 10 m mast, so the formula adoptedsimplifies to

bb

bb

haf

10 (1)

where and are the terrain constants for the buildingterrain, which is given in the table below. For suburbanterrain category considered in this study, the constantswere determined as = 0.67 and = 0.25 .

Table 1. The Terrain Constants for Various Building TerrainsTerrain Category

Exposed Open Suburban Urbana 1.00 0.85 0.67 0.47b 0.15 0.20 0.25 0.35

The entire computational domain is a 36 edged polygoncylinder with a diameter of 1000 m and a height of 400 m.The 36 edge faces of the polygon cylinder were assignedto be the inlets and outlets of the air flow based on thewind directions, wind speeds as well as the airtemperatures at the inlets were obtained from the urbanscale climate modelling.The meteorological data of Parramatta, NSW includingwind directions, speed and evapotranspiration coolingheat flux, solar irradiation are used as the model input, andare shown in the Figure 4-7. The evapotranspirationcooling flux is applied as heat source in the CFD model in

X Y

Z

N


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the form of user-defined functions (UDF) complied witha C++ computer code.

Figure 4 the Temperature Profile for Inlet of Air Flow Over 3 Days

Figure 5 the Velocity Profile for Inlet of Air Flow Over 3 Days

Figure 6 Input Heat Flux of Vegetation Cooling from the Urban

Climate Model (UCM-TAPM)

Figure 7 the Solar Radiation Level Over Three Consecutive Days

It is generally believed that air movement is crucial forunderstand and predict the urban heat flux, ambient airtemperature, thermal comfort in the urban built environment.The wind flow around the building blocks has an importantimpact on the evaporating cooling from plants, and wind flowstagnation is also an important factor for the convective heattransfer process. Figure 9 shows the wind flow stagnations andturbulence vertex at some locations. Hot spot in summer is likelyto happen in these areas.

4. Simulation Results

For each selected neighborhood site, simulations were carriedout for two vegetation arrangements, i.e., one with the existingvegetation coverage and the other with increased (doubled)vegetation coverage. In this report, preliminary results for thesimulation of the Parramatta site with the existing vegetationcoverage and increased vegetation coverage are presented.Figures 8 and 9 demonstrate the simulated surface temperaturesand steam lines for 3D and 2D respectively at 11:00 am on 2February 2011.

Figure 8 Simulated Surface Temperature [K] for 2011. 3D Viewfrom South

Time (hour)

Tem

pera

ture

(Deg

C)

0 10 20 30 40 50 60 7022

24

26

28

30

32

34

36

38

40

Ambient Temperature

Day 1 Day 2 Day 3

Time(hour)

Velo

city(

m/s)

0 10 20 30 40 50 60 70

1

2

3

4

Wind Speed

Time(hour)

Evap

orat

ion

cool

ing

(w/m

2)

0 10 20 30 40 50 60 70

50

100

150

200

250

300

Time (hour)

Sola

rRad

iatio

n

0 10 20 30 40 50 60 700

100

200

300

400

500

600

700

YX

Z

Temperature

309308307305304303301300


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Figure 9 Air Temperature [K] at 2 m above Ground

4.1 Effect of Vegetation Coverage

Figure 10 the Detailed Location of Inspected Data Points (3 × 3) at

a Height of 2m

There are 9 sampling points are located in various inspectedpoints representing various locations including street canyon,near or far from a condensed building block. The arrangementfor the selected points across the calculation domain is shown inFigure 10. The detailed coordinate for each selected points havebeen listed in the Table 2.

Figure 11 shows the air temperature averaged over the nineselected locations of the local built environment at Parramatta,NSW throughout the heatwave period. These temperatures werepredicted at a height of 2 meters, as shown in Figure 11. Here,Case A is the increased vegetation coverage scenario bydoubling the existing coverage, and Case B is the existingvegetation coverage scenario. The highest average ambienttemperature (44.65C) was observed at 15:00 2 February 2011for case of existing vegetation coverage – Case B. While thehighest average ambient temperature was around 40.0C forCase A with doubling vegetation coverage. It was found the peak

ambient temperature reduction of 4.65C for the first day of heatwave period can be achieved by doubling vegetation coverage.Averaged peak temperature reduction during three day heatwave is observed around 2.88C with doubling the existingvegetation coverage.

Table 2. The Coordinates of Each Inspected Point

X(m) Y(m) Z(m)

A1 -277.178 153.834 2.00

A2 18.3378 153.134 2.00A3 278.944 154.897 2.00

B1 -275.831 41.7541 2.00B2 20.3598 50.6835 2.00

B3 274.184 52.7131 2.00

C1 -276.436 -79.9049 2.00

C2 22.486 -91.7736 2.00C3 282.282 282.282 2.00

Due to current constraint in the calculation power, a thickness of1 meter of soil was selected for simulating the ground heattransfer. In the future study, the thickness of soil should beincreased to 10 meters to more accurately predict heatconduction through soil and the thermal storage capacity.

5. Conclusions

This study presented results of computational fluid dynamics(CFD) simulations for the effect of vegetation on local climateat the neighborhood scale (around 500 m). As air movement iscrucial for understand and predict the urban heat flux, ambientair temperature, thermal comfort in the urban built environment.Neighborhood scale CFD model and physiological equivalenttemperature are used to assess the thermal comfortimprovement. Simulation results of the study show up to 4.65Creduction in peak air temperature with an averaged 2.88C canbe observed during three day heat wave period with doublingvegetation coverage. This effort would help both public andgovernment level for better urban development andenvironmental planning in the future. It was found that CFDsimulation at the neighborhood scale has several challenges:computer resources requirements, accurate history of soilmoisture conditions and thus evapotranspiration, ground heattransfer etc.

Acknowledgement

This study was partly funded by the Horticulture AustraliaLimited using the Nursery Industry Levy (Project No.:NY11013 and NY12018) and CSIRO Land and Water Flagship.The authors would express their appreciation to Dr. Peter Wittat Mineral Resources of CSIRO for providing valuessuggestions and the high-performance parallel-computingfacilities.

Temperature

309308307305304303301300


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Figure 11 Averaged Temperatures Throughout Three Consecutive Days With Different Vegetation Coverage

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