The Urban Heat Island (UHI) Phenomenon in Cebu City, Philippines: An Initial Study

The Urban Heat Island (UHI) Phenomenon in Cebu City, Philippines:

An Initial Study

Rowell Shih*1 and Danilo T. Dy2

University of San Carlos

Cebu City, Philippines

*corresponding author email address: [email protected]

1Department of Architecture, College of Architecture and Fine

Arts

2Biology Department, College of Arts and Sciences

Running title: UHI phenomenon in Cebu City

Keywords: Economic development, developing economy, mobile

transect technique, urban planning, urban heat stress

Abstract

The Urban Heat Island (UHI) Phenomenon was never considered an

issue in urban planning for Cebu City, in spite of its rapidly

increasing urbanization. This study tries to evaluate some

factors that may contribute to the UHI Phenomenon in Cebu City

using the mobile transect method during the summer period. A

thermometer measuring platform was mounted on top of a vehicle to

measure the different temperatures of a given area in Cebu City.

Preliminary results showed the presence of UHI Phenomenon in Cebu

City (∆T =0.6°C) and can still be considered moderate compared to

other Asian cities. Among the many factors (i.e., temperature,

humidity, elevation, distance to the shoreline and population),

elevation was considered to be a significant predictor of the UHI

Phenomenon in Cebu City. The provision of green spaces and urban

planning are essential in mitigating future heat stress likely to

be experienced by people living in Cebu City.

Introduction

Majority of the world’s population is now living in urban

environments. Due to the conversion of forested areas, the

average temperature of these built-up areas is now higher than

the surrounding rural area; a phenomenon popularity known as the

urban heat island (or UHI) (Oke 2006). The creation of new cities

means the removal of the natural landscape and results in the

eminent climatic conditions known as the urban climate. Urban

climates are notable from those of the lesser built-up areas by

the differences in the air temperature, humidity, precipitation

and finally wind direction and speed. The differences result from

modification of natural landscapes through the construction of

buildings, roads and other highly reflective materials and lead

to different climates within a city and its connecting rural

areas.

The Urban Heat Island Phenomenon has never been an issue for the

Philippines. As a tropical country, temperatures as high as 34 -

35°C are quite normal. Even if there was a UHI phenomenon, the

strong prevailing winds will simply cool our cities, which are

mostly located along the coast. However, rapid growth and

expansion of our urban centers leads to the construction of new

buildings, roads, bridges, parking lots and other man-made

structures replacing the natural ground cover.

There are three types of UHI: The Canopy Layer Heat Island

(CLHI), Boundary Layer Heat Island (BLHI) and the Surface Heat

Island (SHI). The CLHI and the BLHI refers to the warming of the

urban atmosphere whereas the SHI refers to the warming of the

urban surface. Several factors affect the UHI Phenomenon namely:

Human activities, vehicles, air conditioning, industrial

activities, urban geometry, sky-view factor, air pollution, among

others. Urban planners and designers should be aware and be

responsive to the climate variation developments in urban areas

when planning sustainable cities and, if possible, mitigate the

adverse effects of the UHI Phenomenon. In Central Philippines,

Cebu City has seen a large amount of urban development in the

past twenty years. So far, no study was ever conducted on the

nature of the UHI phenomenon and its effect. An initial study to

evaluate the UHI intensity in a rapidly developing metropolis

such as Cebu City should be a sound undertaking. In this

context, we set out to measure the intensity of the Urban Heat

Island (UHI) between several key locations in Cebu City. We

measured several physical variables using the mobile transect

method, collected some secondary data and analyzed which of the

variables were significant predictors of UHI. We also provided

some recommendations for mitigating the UHI phenomenon in Cebu

City.

Materials and Methods

Study area. Cebu City has a land area of 292 square kilometers.

About 56 square kilometers (or 19%) is classified as urban while

235 square kilometers (or 81%) is classified as rural. To the

northeast lies the city of Mandaue; to the west is Toledo City;

to the south is Talisay City. The population of Cebu City is

866,171 (National Statistical Coordination Board, 2010). Cebu

City is subdivided into 80 barangays or barrios, grouped into two

congressional districts with 46 barangays in the northern

district and 34 barangays in the southern district. The study

areas included both the city and one outlying rural area for

comparison. Several mobile routes were initially considered to

cover the southern and northern portions of Cebu City. The

criteria of the routes chosen were as follow: [1] the urban

growth pattern of Cebu City which covers the major highway of the

Cebu South Road and towards the central part of the city; [2] the

areas with the highest population and high human activity; [3]

the amount of vehicular traffic that passes through the area; [4]

safety during data collection. A route was selected to include

most of the barangays with the most number of population and

vehicular and human traffic. The final route chosen for the study

started from Lawaan 3 (representing the rural area), Tabonoc,

Bulacao, Pardo, Basak, Punta Princesa, Tisa, Labangon, Guadalupe,

Capitol, Kamputhaw, Lahug, and IT Park (Fig. 1).

Fig. 1: Map of the study are and the traverse route from Lawaan 3 to IT Park in Cebu City. Map source: Google Earth.

UHI measurements. UHI was quantified by measuring the surface or

the air temperature differences of areas classified as urban

against an area classified as rural. The data on air temperature

were collected on three occasions using mobile traverse surveys

during March 25, April 2 and 4, 2013 between 2100-2300 hours in

which the differences between the urban and rural temperatures

are at their highest (Gómez et al. 1993, Tereshchenko and Filonov

2001). The air temperature and the humidity was collected using

an Extech Hygro-thermometer SD500 datalogger. The instrument has

a temperature range of 0.0-50.0°C, resolution of 0.1% and with an

accuracy of ±0.8°C. The relative humidity has a range of 70-90%,

resolution of 0.1% and with an accuracy of ±4% (of reading) + 1%

RH. The instrument was mounted on top of a vehicle with a height

of 1.4 m and 1.5 m away from the engine. Mobile data measurements

were collected along the defined route. The temperature recorder

was set to log temperature and humidity along with the time stamp

automatically at 2 minute intervals. The vehicle was driven at an

average speed of ±35 km/hr. For each scheduled measurement taken,

meteorological conditions were also noted (wind velocity, cloud

cover) as this will also have an impact on the air temperature

data.

Ideally, measurements should be carried out simultaneously, but

since this is impossible using the mobile measurement techniques

(Conrads and Van der Hage 1971), the only option was to do the

measurements as quick as possible. The sampling difference

between the first (Lawaan 3, Talisay City) and the last point (IT

Park, Lahug) was less than 45 minutes.

Data analysis. The mathematical difference of the in-situ

temperature of a rural area (Lawaan 3) and the in-situ temperature

of the urban sites during a mobile survey was considered a

measure of UHI. Since there were five variables (i.e., relative

humidity, in situ temperature, elevation, distance to the

shoreline, population) collected, a multiple linear regression

(using stepwise selection and verified further using forward

selection) was used to determine which among the variables or a

combination of variables was considered a significant predictor

of UHI. Significance level was set at 95%.

Results and Discussion

During the survey, the weather conditions ranged from clear skies

to cloudy with winds equal to or less than 1 m/s. The less than

45 minutes travel from the rural site (i.e., Lawaan 3) to the

various urban sites during the night was also appropriate. This

was possible considering that Cebu City is not yet very highly

urbanized compared to Metro Manila where traffic is very

horrendous even during nighttime. Overall mean temperature

difference between a rural site and urban areas was 0.6°C; a

value considered as moderate as compared to existing Asian

cities. Surprisingly, elevation was the best predictor of the

UHI phenomenon in Cebu City. The adjusted Coefficient of

Determination (R2) was 0.15. The regression coefficient was -

0.023 (P value=0.013, see Table 2) indicating that slightly

elevated urban sites have lesser ∆T. Our results agreed with the

study of Giannaros et al. (2012) who found that elevation was a major

factor in determining the lowest temperature contrast between two

different stations in the coastal city of Thessaloniki, Greece.

From our study, it appeared that population was not significantly

correlated with UHI. It is possible that the current population

in the city’s barangays may not be as dense as compared to other

Asian cities where land areas are already limited and real estate

developers have to build very tall vertical structures (i.e.,

condominium units) to accommodate the growing city dwellers. In

one study (Steeneveld et al., 2011) in Netherland, for example,

UHI is better correlated with population density of the

neighborhood, since higher population density requires higher

building density leading to enhanced radiation trapping and high

thermal inertia. It is possible that as Cebu City reaches its

peak of development 10-20 years from now, population will be a

significant predictor of UHI. There are also temporal-related

factors that may correlate well with the UHI phenomenon in

urbanized cities. For example, Arnfield (2003) showed that UHI is

stronger during the summer months when the air is warmer and UHI

tend to be higher during nighttime than during the day. These

factors will be collected in future samplings as more stations

will be identified and self-recording thermal instruments can be

securely and strategically placed in different parts of the city.

Table 1. Mean, standard deviation and range (N=3) of variablescollected during the initial study.

Barangays

Statistics

∆T°C

In-situTem-perature,°C

%RH Elevation1, m

Distancetoshoreline, m

Population2

TabunocMean 0.4 28.7 66.3 21 2,396 17,593SD 0.4 0.5 2.6 0 0 0Range 0.7 1.0 4.9 0 0 0

BulacaoMean 0.8 28.8 65.9 23 2,845 26,820SD 0.6 0.4 2.2 0 0 0Range 1.1 0.7 4.1 0 0 0

PardoMean 1.0 29.0 66.0 21 2,535 12,103SD 0.6 0.3 2.3 0 0 0Range 1.2 0.6 4.4 0 0 0

BasakMean 0.8 28.8 66.8 14 1,783 17,756SD 0.7 0.3 1.7 0 0 0Range 1.3 0.5 3.4 0 0 0

PuntaPrincessa

Mean 0.9 28.9 67.9 19 1,926 22,270SD 0.6 0.3 2.3 0 0 0Range 1.2 0.6 4.5 0 0 0

TisaMean 1.0 29.0 67.2 20 2,571 35,600SD 0.6 0.3 2.1 0 0 0Range 1.2 0.6 4.1 0 0 0

LabangonMean 1.0 29.0 67.9 23 1,515 31,643SD 0.7 0.3 2.1 0 0 0Range 1.3 0.6 4.0 0 0 0

Guadalupe

Mean 0.5 28.5 68.8 34 2,991 60,400SD 0.8 0.4 1.9 0 0 0Range 1.5 0.7 3.7 0 0 0

CapitolSite

Mean 0.6 28.6 69.6 36 3,089 15,308SD 0.5 0.5 2.6 0 0 0Range 0.9 0.9 4.8 0 0 0

Kamputhaw

Mean 0.2 28.2 70.1 45 2,550 21,765SD 0.8 0.2 2.7 0 0 0Range 1.5 0.3 4.9 0 0 0

Lahug Mean 0.4 28.4 44.1 49 3,651 35,157

SD 0.6 0.5 26.1 0 0 0Range 1.0 0.8 45.3 0 0 0

IT Park

Mean -0.1

27.9 71.4 38 2,979 No data

SD 0.6 0.3 2.9 0 0Range 1.2 0.6 5.3 0 0

1Data from Google Earth2Data from National Statistical Coordination Board (2010)

Table 2. Statistical results showing the significant effectof elevation on ∆T.

UnstandardizedCoeff.

StandardizedCoeff.

B Std.Error

Beta t Sig.

Constant 1.276 0.267 4.77 0.000ELEVATION -0.023 0.009 -0.412 -2.64 0.013

Conclusion and Recommendations

In the recent past, the urban heat island (UHI) was almost a

relatively unknown phenomenon in the field of urban planning. In

this preliminary study, we provided initial evidence that some

areas in Cebu City are slowly developing their own urban heat

climate. Even though it is a coastal city, the cooling effect of

coastal waters may, in the long run, only exert a limited

influence in moderating urban microclimate. The dense built up

of urban spaces, traffic, the lack of open or green spaces,

construction activities, urban morphology and meteorological

conditions related to climate change, among others, may

significantly contribute more heat stress to rapidly developing

urban centers such as Cebu City. Clearly, a more expanded UHI

study to include other variables currently not included in this

initial study is necessary. We also recommend urban planners and

designers to take into account the anthropogenic factors and the

importance of open green spaces to reduce the development of UHI.

The health and comfort of the people must be considered as an

objective in urban development studies in Cebu City. No doubt as

the city grows, so too will the effects of UHI.

Acknowledgments.

We thanked Ma.Kristina Oquinena and Hyacinth Suarez for valuable

discussions. We also acknowledged the valuable suggestions

provided by Dr. Rico C. Ancog of the University of the

Philippines at Los Baños. This is a research contribution of the

University of San Carlos, Cebu City, Philippines.

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