the impact of the projected changes in temperature on heating and cooling requirements in buildings...

Applied Energy 88 (2011) 3737–3746

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Applied Energy

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The impact of the projected changes in temperature on heating and coolingrequirements in buildings in Dhaka, Bangladesh

Monjur Mourshed ⇑Department of Civil and Building Engineering, Loughborough University, Loughborough, Leicestershire LE11 3TU, United Kingdom

a r t i c l e i n f o

Article history:Received 13 January 2011Received in revised form 24 April 2011Accepted 14 May 2011Available online 8 June 2011

Keywords:Climate change impactsBuilt environmentDhakaCooling degree-daysHeating degree-daysWeather data

0306-2619/$ - see front matter � 2011 Elsevier Ltd. Adoi:10.1016/j.apenergy.2011.05.024

⇑ Tel.: +44 1509 228792.E-mail address: [email protected]

a b s t r a c t

Dhaka, the capital of Bangladesh, is a fast growing megacity with a population of 12.8 million. Due to itstropical location, dense urban morphology and higher than average density of population, buildings inDhaka are likely to be adversely affected by the projected changes in climate, in particular by theincreases in temperature. Buildings play a vital role in most aspects of our lives and their energy con-sumption patterns affect climate change mitigation and adaptation strategies. It is important to under-stand the likely impact of the projected increases in temperature on cooling and heating requirementsin buildings in future climates. In this research, global projections on changes in temperature are tempo-rally downscaled using a statistically averaged baseline present-day hourly weather data to generatefuture weather data in three timeslices: 2020s, 2050s and 2080s. Time series data for the present-dayand future climates are analyzed as well as heating and cooling degree-days are calculated.

Analysis shows that heating degree-days decrease whereas cooling degree-days continue to increase infuture climates. The magnitude of change in monthly cooling degree-days is uneven and is greater in win-ter months than in summer and monsoon. Increased occurrences of temperatures above comfort thresh-old throughout the year are likely to have significant consequences for human health and wellbeing. Theseverity and duration of outdoor temperatures in the form of increased cooling degree-days in future cli-mates will result in a surge in demand for energy for comfort cooling, which will add further stress to thealready stressed energy infrastructure in the country. Prompt actions from stakeholders are, therefore,essential to enhance the resilience of Dhaka’s buildings to climate change.

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1. Introduction

Bangladesh is cited as one of the countries most vulnerable toanthropogenic climate change [1] despite being responsible foronly 0.15% of global CO2 emissions [2]. The flat and low-lyingtopography with high population density makes it particularly vul-nerable to the impacts of climate change such as sea level changesand increased occurrences of floods and extreme weather events.The projected magnitudes of these impacts appear to be substan-tial in the case of Bangladesh [3] and have the potential to threatenthe very existence of a large percentage of population, either bycausing death and damage [1,4] or by affecting livelihoods [5]. Evi-dence suggests that the government and development stakehold-ers are aware of the high magnitude climate change impacts andto some extent the means to adapt to these impacts [6,7]. Thedevelopment of policies and strategies to tackle the impacts of cli-mate change has focussed only on the rapid and instantaneousdisasters such as floods and extreme weather events that can causevisible disruptions to socio-economic systems. Long term gradual

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changes in climate such as increases in temperature and their im-pact on buildings and associated systems have not yet been prior-itized or emphasized in the policies. One of the reasons behind thisis the lack of research based evidence, which this research seeks toaddress.

The built environment is an important factor in understandingthe cause and impacts of climate change. Buildings account forapproximately 40% of global energy consumption and correspond-ing carbon emissions [8], the release of which in the atmosphere isthe primary reason for anthropogenic climate change. On the otherhand, changes in climate will impact on buildings, which in turnwill affect the occupants. Understanding how buildings behave inthe present-day and future climates is, therefore, key to reducinganthropogenic carbon emissions as well as to adapt to the inevita-ble climate change [9]. The first step in assessing a building’sbehavior in different climates is to understand the nature and mag-nitude of changes in climate parameters, the projections of whichare done through the application of climate modeling techniquesat various temporal and spatial resolutions. The underlying scienceof climate modeling has advanced over the past years [10] in termsof: the dynamical cores; horizontal and vertical resolutions ofmodels; incorporation of more processes (e.g., the modeling of

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3738 M. Mourshed / Applied Energy 88 (2011) 3737–3746

aerosols, land surface processes, etc.); and improved parameteriza-tion of physical processes [3]. However, the outputs from globaland regional climate models need to be downscaled further fortemporal granularity (hourly) to assess the performance of build-ings in future climates.

Dhaka, the capital of Bangladesh, is characterized by a high con-centration of people with a dense urban morphology. Its popula-tion stood at 12.8 million in 2008 [11], which is projected toincrease to 20 million in 2020, making it the third largest city inthe world [12]. Rapid urbanization coupled with relatively weakplanning control and building regulations resulted in densely con-structed buildings with poor thermal and/or ventilation perfor-mances, even in reference to the present day climate. Theurbanization in Dhaka since the 1970s is illustrated in Fig. 1 withthe help of two satellite images of the city and surrounding areas– one from 1972 and the other from 2001. Vegetation and wetlandswere abundant in 1972, which shrank in size and were almostwholly replaced by roads and buildings by 2001. The city is sur-rounded by relatively wide rivers in all sides except in the North.The city could, therefore, grow northwards without incurring addi-tional cost for land and infrastructure development. Weak trans-port infrastructure meant that there was an undue pressure onland in inner city areas for maximizing the built-up area. The char-acteristics of dense residential developments in Dhaka have beeninvestigated in a recent article [13], in which the author demon-strated how contemporary mid (=6 stories) to high rise (<6 stories)buildings lacked adequate open spaces to allow natural ventilationand lighting in interior spaces. Buildings in Dhaka are, therefore,likely to be adversely affected by any increase in temperature. In-creased pressure on land for new buildings to house the influx ofmigrants from rural areas will worsen the situation.

With regard to climate, Dhaka is characterized by high temper-atures, high humidity, heavy rainfall and marked seasonal varia-tions. According to Köppen–Geiger climate classification Dhaka’sclimate is classified as Aw or tropical wet and dry [14]. Overall,there are three main seasons in Bangladesh [4]:

� A hot summer season from March to June. Climate characteris-tics include high temperatures, a high rate of evaporation anderratic heavy rainfall.� A hot and humid monsoon season from June to October with

heavy rainfall accounting for around two thirds of the annualrainfall.� A cooler and drier winter season from November to March.

The energy demand from a building is influenced by a largenumber of variables ranging from weather parameters (e.g., tem-

Fig. 1. Satellite images of Dhaka in 1972 and 2001 showing changes in land characterisimage on 28 December 1972 and (b) Landsat-7/ETM + image on 29 January 2001. Sourc

perature, solar radiation, wind, moisture content of air, etc.) tothe characteristics of the building (e.g., envelope, form, shape,materials, construction, etc.), its occupants (e.g., occupancy, activ-ities, etc.) and its systems (e.g., type, performance, control sched-ules etc.). Analysis methods based on degree-days offer aconvenient way to estimate energy demand, as it requires signifi-cantly less input processing than full dynamic building simulation,thereby reducing the potential for input errors while improving thetransparency of the model [16]. The method also allows the assess-ment of the impact of the projected temperature increases in fu-ture climates on building energy demand; i.e., climatesensitivities, in a manageable way. This is because of the fact thatchanges in heating and cooling degree-days of a location can act assurrogates for trends in building energy consumption [17].

This research is aimed at investigating the projected changes inDhaka’s temperature in the 21st century and how this may affectheating and cooling requirements in buildings. The concept ofheating and cooling degree-days is applied. Projections from Inter-governmental Panel on Climate Change (IPCC) models are tempo-rally downscaled using a statistically averaged baseline present-day hourly weather data to generate future weather data in threetimeslices: 2020s, 2050s and 2080s. Heating and cooling degree-days are calculated from the generated hourly data to investigatetemporal changes in degree-days and the implications these mayhave on building energy demand.

2. Methodology

2.1. Degree-days

The concept of degree-days has been widely used to estimateweather related energy consumption and in some cases the corre-sponding CO2 emissions due to space cooling or heating in build-ings at various locations worldwide [18–22]. The estimate can beused for benchmarking a building’s expected performance againstother buildings of similar characteristics, as well as to set energybudgets or negotiate energy tariffs. The other use of degree-daysis the ongoing monitoring and analysis of weather related energyconsumption and corresponding CO2 emissions of existing build-ings based on historical data [16], which can assist in evaluatinga building’s performance during operation and identify changesin consumption patterns; provide some building and system char-acterizations; and to set future energy consumption and emissionstargets. The trend of changes in degree-days in future climates is,therefore, indicative of the magnitude of the impact of the pro-jected increases in temperature on buildings.

tics, representative of the rapid urbanization during this period: (a) Landsat-1-MSSe: [15].

1 This is the resolution at which model dynamics and physics are solved in theatmospheric component of HadCM3; i.e., the Hadley Centre Atmospheric Model,version 3 (HadAM3).

M. Mourshed / Applied Energy 88 (2011) 3737–3746 3739

2.1.1. Calculating degree-daysDegree-days are defined as the summation of temperature dif-

ferences over time, between a reference temperature and the out-door air temperature. They capture both the severity and durationof outdoor temperatures. The reference or base temperature is alsotermed as the balance point temperature; i.e., the outdoor temper-ature at which the cooling or heating system does not need to runin order to maintain comfort conditions in a building [23]. Theheating system needs to operate when the outdoor temperatureis below the heating base temperature. The cooling system, onthe other hand, operates when the outdoor temperature is abovethe cooling base temperature. The calculation of heating and cool-ing degree-days from hourly weather data is given in Eqs. (1) and(2) respectively. This method is known as the degree-hour or hourlymethod.

Dh;d ¼P24

i¼1ðhb;h � ho;iÞ24

for ðhb;h � ho;iÞ > 0 ð1Þ

where Dh,d is the daily heating degree-days for one day (�C day), hb,h

is the heating base temperature (�C) and ho,i is the outdoor air tem-perature at the ith hour of the day (�C).

Dc;d ¼P24

i¼1ðho;i � hb;cÞ24

for ðho;i � hb;cÞ > 0 ð2Þ

where Dc,d is the daily cooling degree-days for one day (�C day), hb,c

is the cooling base temperature (�C) and ho,i is the outdoor air tem-perature at the ith hour of the day (�C).

Monthly heating and cooling degree-days, Dh,m and Dc,m, for aparticular month are the sums of daily heating and cooling de-gree-days over that period. Similarly, annual heating and coolingdegree-days, Dh,a and Dc,a, are the sums of monthly degree-daysover the twelve months of the year. In cases where hourly meteo-rological data are not available, degree-days can be calculated fromreduced datasets such as mean daily temperatures or meanmonthly temperatures. In fact, the standard method of calculatingdegree-days varies around the world. In the US, published degree-days are calculated from mean daily temperatures [23]. The UKMeteorological Office (UKMO) publishes degree-days data for UKlocations using daily maximum and minimum temperatures [24].In cases where daily data are not available, monthly mean temper-ature and standard deviation of temperature can be used to calcu-late monthly degree-days [25]. The hourly method of calculatingdegree-days is more accurate than traditional methods. For thisreason degree-days are calculated in this research from hourlyweather data for the present-day and morphed hourly data for fu-ture climates.

2.1.2. Estimating energy consumption using degree-daysSince the heat loss from a building is directly proportional to the

indoor-to-outdoor temperature difference, the energy consump-tion of a heated building over a period of time is related to thesum of these temperature differences over the period. The energydemand from heating systems for the heating season or for a par-ticular period (usually a month) can be found from the Eq. (3).

Fh ¼24U0Dh

gð3Þ

where Fh is the energy demand from the heating system for the per-iod considered (kW h), g is the overall seasonal heating system effi-ciency (–), Dh is the heating degree-days for the period underconsideration (�C day) and U0 is the overall building heat loss coef-ficient (kW K�1).

The estimation of energy demand of a cooled building is slightlydifferent from the estimation of heating energy demand. Energybalance of a cooled building has a significant relationship to the

fresh air or latent components of the cooling demand. Therefore,a singular heat gain co-efficient, similar to the heat loss coefficient(U0) in Eq. (3), cannot be used. One solution is to estimate energyconsumption of the chiller, the calculation of which will varydepending on system type. A discussion on the variation of calcu-lation procedures for various cooling systems can be found in Refs.[16,19]. A generalized method of calculation is given in Eq. (4) tocalculate energy demand from the cooling system for a particularperiod or cooling season by estimating the energy consumptionof the chiller.

Fc ¼24 _mcpDc

CoPð4Þ

where Fc is the energy demand from the cooling system for the per-iod considered (kW h), Dc is the cooling degree-days for the periodunder consideration (�C day), _m is the mass flow rate of air (kg s�1),cp is the specific heat of air (kJ kg�1 K�1) and CoP is the averageCoefficient of Performance of the plant (–).

2.1.3. Determining the base temperatureTraditionally, degree-day data are published at a building base

temperature of 15.5 �C in the UK [16] for 18 regions. Variable basedegree-day data have recently been made available for 77 regions,weekly and monthly, at a range of building base temperatures from10.5 �C to 20 �C [26]. In the US, heating and cooling degree-daydata are published by the American Society of Heating, Refrigerat-ing and Air-Conditioning Engineers (ASHRAE) at base temperatures18.3 �C and 10 �C respectively [23]. The choice of base temperaturedepends on building construction techniques as well as climatevariables such as humidity, wind regime, etc. for the particular re-gion [17]. The use of building specific base temperature is, there-fore, important for correct energy vs. degree-days correlationsand should take into account the correct (and practical) energy bal-ance of the building [27]. For this reason degree-days are calcu-lated in this research at variable base temperatures ranging from10 �C to 20 �C for heating and from 10 to 28 �C for cooling de-gree-days at an interval of 0.5 �C. The determination of buildingspecific base temperature is out of scope of this paper; however,discussions on methods such as the use of building performancelines can be found in Refs. [16,27].

2.2. Construction of weather data for future climates

2.2.1. DownscalingThe projections from global climate models are coarse in terms

of spatial and temporal resolutions. For example, the Hadley CentreCoupled Model, version 3 (HadCM3) from UKMO, which is used inthe IPCC assessment report [3], has a spatial resolution of3.75� � 2.5� (longitude–latitude)1 and generates monthly changefields as outputs [28]. The outputs need to be temporally and spa-tially downscaled for use in estimating building energy demand. Bel-cher et al. [29] developed one such downscaling method calledmorphing that combines present-day observed weather data withoutputs from climate models. The procedure has been shown toyield weather time series that encapsulates the average weatherconditions of future climate scenarios, whilst providing realisticweather sequences. In this method, the present-day design weatherdata are adjusted by the changes to climate projections by global cir-culation models (GCM) and regional climate models (RCM). The lim-itation of such method is that it retains the character and variabilityof the present-day climate, whereas the future climate may have adifferent character. However, the generated data have been found

Temperature (°C)

Occ

urre

nce

(hr)

5 10 15 20 25 30 35 40 450

200

400

600

800

1000

1200Present2020s2050s2080s

Fig. 2. Distribution of hourly temperatures in the present-day and future climates.


to be meteorologically self-consistent and coherent with the currentbest projections. Examples of the application of the morphing meth-od can be found in Refs. [30–32].

2.2.2. Morphing of weather dataThe underlying methodology for weather data morphing con-

sists of three generic operations depending on the weather param-eter to be changed: shift; linear stretch (scaling); and shift andstretch [29].

The shift and stretch operation is used in this research to adjustpresent-day dry bulb temperature by using IPCC projections for themonthly change of the diurnal mean, minimum and maximum drybulb temperatures. This enables the integration of predicted varia-tions of the diurnal cycle. In this operation, the present-day weath-er variable, x0 is shifted by adding the projected absolute monthlymean change, Dxm, and stretched by the monthly diurnal variationof this parameter, to generate the future-climate weather variable,x [29]:

x ¼ x0 þ Dxm þ amðx0 � hx0imÞ ð5Þ

where hx0im is the monthly mean related to the present-day weath-er variable x0, and am is the ratio of the monthly variances of x0 andDxm.

2.2.3. Data sourcesIPCC has adopted six basic global emissions scenarios, which

depend on different assumptions for future economic growth, re-source consumption, technology implementation, social equityand global population development [33]. These scenarios essen-tially represent possible development pathways of human activi-ties and function as a baseline for climate change modeling. Theoutputs from the IPCC A2 scenario (medium–high emissions) forthe corresponding grid for Dhaka [34] have been used in this study.The A2 storyline is described as comprising a heterogenous worldwhere the underlying theme is self-reliance and preservation of lo-cal identities [33]. The scenario assumes that fertility patternsacross regions converge very slowly, which result in continuouslyincreasing global population. Economic development is consideredto be primarily regionally oriented and per capita economic growthand technological change are more fragmented and slower than inother storylines. Baseline weather data; i.e., present-day dry bulbtemperature (observed weather data), were obtained from the So-lar and Wind Energy Resource Assessment (SWERA) [35] in TypicalMeteorological Year (TMY) format. The advantage afforded by theuse of the TMY data is the encapsulation of typical weather condi-tions as these are produced using an objective statistical algorithmto select the most typical month from the long-term record. Com-parative discussions on various TMY methodologies can be foundin Refs. [36,37].

3. Results and discussion

3.1. Dry bulb temperatures in future climates

Fig. 2 shows the number of hours in a year that a particular tem-perature occurs; i.e., the frequency distribution of temperatures inthe four investigated climates: present-day, 2020s, 2050s and2080s. The distribution was calculated at an interval width of1 �C. The distribution of temperature shifts to the right under theinvestigated future climates, indicating warmer temperatures. Thisis in line with general projections that the climate is getting war-mer [3]. The distributions in the present-day and future climatesare similar in pattern; i.e., no significant widening or narrowingof the distribution occurs in future climates. The peak in the distri-bution that shows the most frequent temperature is about 28 �C in

the present-day climate, which increases to about 29 �C, 30 �C and31 �C in the 2020s, 2050s and 2080s, respectively. The number ofhours of occurrence of the peak temperature is also increasing,from 1036 h in the present-day to 1097 h in the 2080s.

Fig. 3 shows daily temperature ranges for the present-day andmorphed future climates in the 2020s, 2050s and 2080s. Althoughthe climates are generally getting warmer throughout the year, theincrease in winter temperatures is more than that of the summertemperatures. Diurnal variations are generally greater during win-ter months (November to March) than summer (March to June)and monsoon (June to October) months in the present-day climate.This meteorological pattern is retained in future climates. How-ever, with the increase in temperature, in particular in the 2080sclimate, the length of winter season is shortened. The warmingof the winter months are explored further in Fig. 4, which showschanges in the daily mean temperature in future climates fromthe present-day baseline climate. Polynomial curve-fits of the datahighlight this trend in different climates with marked seasonalvariations. The greatest change of about 30% occurs in the 2080sin December whereas the greatest change in July is about 11% forthe same climate. Increased winter temperatures in future climatesare likely to result in building overheating throughout the year asopposed to during summer and monsoon in the present-day cli-mate. Overheating is explored further in the following section.

3.2. Overheating

Building overheating is a serious concern for buildings in Dhaka,even in the present-day climate. Most buildings are at risk of over-heating throughout the year, apart from the months: January andDecember. The situation is particularly worse for buildings withhigh internal gains such as commercial and educational buildings.The majority of buildings in Dhaka are of solid wall constructionwithout any thermal insulation, which increase solar gain in build-ings. Fan-assisted ventilation is the primary means for maintainingcomfort conditions in most buildings. However, the installation ofrefrigerant-based comfort cooling, in particular in commercialbuildings, is increasing.

Various approaches have been taken in past research to defineoverheating criteria [38,39], which were predominantly based onthe definition of acceptable thresholds of thermal comfort condi-tions. Since temperature is one of the key weather variables thataffect thermal comfort, exceedance of certain temperatures for cer-tain durations are usually used as an indicator of overheating. In aprevious UK study on overheating [30], the comfort threshold tem-peratures of 25 �C and 28 �C have been used. The criteria used werethat internal temperatures should not exceed 25 �C for more than5% and/or exceed 28 �C for more than 1% of the occupied periodin the year. On the other hand, research [40] indicates that comfort

Tem

pera

ture

( °C

) (a)

(b)

1 31 59 90 120 151 181 212 243 273 304 334 365

51015202530354045

Tem

pera

ture

(°C

)

(c)

51015202530354045

Tem

pera

ture

(°C

)

(d)

51015202530354045

Tem

pera

ture

(°C

)

Day (−)1 31 59 90 120 151 181 212 243 273 304 334 365

51015202530354045

Fig. 3. Minimum and maximum daily temperatures in the four investigated climates: (a) present-day, (b) 2020s, (c) 2050s and (d) 2080s.

1 31 59 90 120 151 181 212 243 273 304 334 3650

5

10

15

20

25

30

35

R2=0.84238

R2=0.8736

R2=0.89555

Day (−)

Cha

nge

(%)

2020s 2050s 2080s

J F M A M J J A S O N D

Fig. 4. Change in daily mean temperature in future climates along with cubiccurve-fits of the data.

20 25 30 35 40 450

20

40

60

80

100

Temperature (°C)

Tim

e in

the

year

(%)

28 °C threshold

25 °C threshold

61.6 67.3 75.184.7

31.0 41.2

54.3

71.9

Present2020s2050s2080s

Fig. 5. Exceedance of overheating threshold temperatures in the present-day andfuture climates.


thresholds are higher in tropical humid locations such as Dhakaand tolerance to higher temperatures is above what is typical incold or temperate climates. However, the thresholds of 25 �C and28 �C are used in this study primarily because internal tempera-tures are often higher than external temperatures in a naturallyventilated building [38] during occupied hours as internal gainscontribute to the rise in indoor temperature.

Fig. 5 shows the percentage of time in the year above 20 �C inthe four investigated climates. In the present-day climate, temper-atures above 20 �C occur for about 85% of the time in the year,

rising to about 95% in the 2080s climate. The first overheatingthreshold temperature, 25 �C, is exceeded for 67.3%, 75.1% and84.7% of the time in the year in the present-day, 2020s, 2050sand 2080s, respectively. The second overheating threshold temper-ature, 28 �C, is exceeded for 31%, 41.2%, 54.3% and 71.9% of the timein the year in the present-day, 2020s, 2050s and 2080s,respectively.

The exceedance of overheating threshold temperatures at thismagnitude highlights the fact that the goal of any design and/orrefurbishment of buildings in Dhaka could first be to minimize

Fig. 6. Annual cooling degree-days, Dc,a, at different cooling base temperature, hb,c,in the present-day and future climates.


internal and solar heat gains. Natural ventilation or even fan-assisted mechanical ventilation may not be adequate for comfortcooling and ventilation for majority of the buildings with moderateto high internal gains.

3.3. Degree-days

The present-day climate of Dhaka is characterized by high tem-peratures; hence the cumulative heating degree-days for this loca-tion is significantly less than the cumulative cooling degree-days.Annual heating degree-days, Dh,a, at various heating base temper-ature, hb,h, for the present-day, 2020s, 2050s and 2080s are givenin Table 1. At the widely used hb,h = 15.5 �C, Dh,a is 34 �C-day forthe present-day and is reduced to 13 �C-day, 3 �C-day and 0 �C-day in the 2020s, 2050s and 2080s, respectively. Therefore, theneed for heating can be eliminated for all applications exceptwhere strict comfort conditions need to be maintained. For thisreason, further investigations on degree-days in this research focusonly on cooling degree-days.

3.3.1. Cooling degree-daysAnnual cooling degree-days at all investigated base tempera-

tures tend to increase in future climates. Fig. 6 shows the variationsin the number of cooling degree-days in the four investigated cli-mates at base temperatures: 10 �C, 13 �C, 16 �C, 19 �C, 22 �C and25 �C. At hb,c = 10�C, the ASHRAE reference base temperature forcooling [23], annual cooling degree-days, Dc,a for the present-day,2020s, 2050s and 2080s are 5946 �C-day, 6306 �C-day, 6797 �C-day and 7577 �C-day, respectively. At hb,c = 15.5 �C, the UK refer-ence base temperature [16], Dc,a for the present-day, 2020s,2050s and 2080s are 3911 �C-day, 4250 �C-day, 4732 �C-day and5697 �C-day, respectively. The magnitude and monthly variationsof change in degree-days in different climates are discussed inthe following sections.

Monthly cooling degree-days, Dc,m, in the present-day, 2020s,2050s and 2080s are given in Tables 2–5, respectively. In the pres-ent-day, Dc,m in August is the greatest at base temperatures be-tween 10 �C and 20 �C. At base temperatures between 21 �C and25 �C, Dc,m in June is the greatest. In the 2020s, Dc,m in August isthe greatest at all base temperatures except 28 �C. In the 2050s,Dc,m in August is the greatest at all base temperatures but in the2080s, Dc,m in April is the greatest at all base temperatures. Themonthly variations are illustrated in Fig. 7, which shows the flat-tening tendency of the curve between April and October in futureclimates. In the 2080s, monthly cooling degree-days are similar inmagnitude between March and October, suggesting a consistentlyhigh demand for cooling.

3.3.2. Change in cooling degree-daysChanges in monthly cooling degree-days at different base tem-

peratures in future climates from the baseline present-day climateis shown in Fig. 8. Monthly variations in change are uneven anddisparate at different base temperatures. Increases in monthlycooling degree-days in the 2020s are almost even across the

Table 1Annual heating degree-days, Dh,a, in the present-day, 2020s, 2050s and 2080s.

Climate Annual heating degree-days, Dh,a (�C-day)Heating base temperature, hb,h (�C)

10 12 14 15.5 16 18 20

Present-day 0 3 13 34 44 102 1902020s 0 0 4 13 18 57 1262050s 0 0 1 3 5 22 642080s 0 0 0 0 0 3 17

months of the year but an uneven trend appears to emerge inthe 2050s onwards. Monthly cooling degree-days in winter monthsincrease more than the cooling degree-days in monsoon months,except October. Changes in cooling degree-days for winter months(November to March) are higher at low base temperatures (e.g.,hb,c = 10 �C) than those at high base temperatures (e.g., hb,c = 25 �C).As winter gets warmer in future climates the occurrences of tem-peratures above low base temperatures increases.

Percentage changes in monthly cooling degree-days at differentbase temperatures, representing the magnitude of change in futureclimates against the baseline present-day climate, are illustrated inFig. 9. The magnitude of change in cooling degree-days are similarin shape to the magnitude of change in daily mean temperature infuture climates (see Fig. 4). Percentage changes in cooling degree-days at high base temperatures (e.g., hb,c = 25 �C) are higher thanthose at low base temperatures (e.g., hb,c = 10 �C). Dc,m at higherbase temperatures is low in winter months in the present-day;therefore, small changes in the value in future climates translatesto large percentage changes; e.g., the percentage change inmonthly cooling degree-days in January in the 2080s at hb,c = 25 �Cis 925% but the actual change is only 37 �C-day (41 � 4 = 37).

3.4. Hot spells

In addition to the risk of overheating (see Fig. 5), the occurrenceof hot spells will be prevalent in future climates, well beyond themonths typically considered as hot. A hot spell has previously beendefined as a period when the previous three or five days have hadtemperatures exceeding 25 �C for more than 3 h [30]. According tothis definition, Dhaka experiences almost continuous hot spellsthroughout the year, except for a few days in January and Decem-ber, even in the present-day climate. The severity (i.e., the differ-ences between outdoor temperatures and the referencetemperature) and the duration (i.e., the time this difference per-sists) of hot spells tend to increase in future climates, which willadd further complexities in the energy efficient design and opera-tion of a resilient built environment. Vulnerable groups of peoplesuch as babies, young children, elderly and people at-risk (e.g., peo-ple who are confined to bed or who has preexisting psychiatric ill-ness) will be particularly affected by the excessive heat [41,42].

3.5. Building energy demand

It is evident that energy use for maintaining comfort conditionsin buildings in Dhaka will continue to grow under future climates.Heating degree-days and corresponding energy demand is verylow in the present-day and can be eliminated altogether in the fu-ture. Cooling degree-days and corresponding energy demand, on

Table 2Monthly cooling degree-days, Dc,m, in the present-day.

Month Monthly cooling degree-days, Dc,m (�C-day)Cooling base temperature, hb,c (�C)

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

January 265 235 206 178 152 128 107 89 72 57 44 32 22 14 8 4February 339 310 282 253 225 197 171 147 125 104 85 67 51 38 27 18March 513 481 449 417 385 353 321 289 258 227 197 168 140 115 92 72April 562 531 500 469 438 407 376 345 314 283 252 222 192 163 137 112May 578 546 514 482 450 418 386 354 322 290 258 226 195 164 136 108June 600 569 538 507 476 445 414 383 352 321 290 259 228 197 166 136July 589 557 525 493 461 429 397 365 333 301 269 237 205 173 141 109August 610 578 546 514 482 450 418 386 354 322 290 258 226 194 162 130September 578 547 516 485 454 423 392 361 330 299 268 237 206 175 145 114October 560 528 496 464 432 400 368 336 304 272 240 208 177 146 117 90November 431 400 369 338 307 276 245 214 184 155 127 101 79 60 44 31December 318 286 254 223 192 162 136 112 90 71 55 41 29 19 12 7

Table 3Monthly cooling degree-days, Dc,m, in the 2020s.


10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25




10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25



the other hand, will continue to increase under future climates andlikely to affect the already stressed energy infrastructure in thecountry. Most of the cooling energy demand may have to be metthrough electricity, a carbon intensive form of energy. This willhave serious consequences for energy security as the existing elec-tricity infrastructure in Bangladesh is deemed as inadequate evento meet present demand. Only 43% of the population is served bythe grid and per capita electricity consumption in 2007 was143.6 kW h, which was one of the lowest in the world [43]. Elec-tricity consumption is likely to increase with the growth in grossdomestic product (GDP) and income. Increasing demand for energyfor comfort cooling is likely to exacerbate the situation. Unless

significant investments are made in research and developmenton low carbon cooling solutions, the impact of increased tempera-tures on buildings is likely to affect the country’s energy securityand carbon emissions.

As cooling energy demand is proportional to cooling degree-days for the corresponding period, it can be asserted that coolingenergy consumption in a building in Dhaka with a balance pointtemperature of 10 �C will increase by 6%, 14% and 28% in the2020s, 2050s and 2080s, respectively. Similarly, for buildings witha balance point temperature of 25 �C, cooling energy consumptionwill increase by 23%, 59% and 127% in the 2020s, 2050s and 2080s,respectively. Percentage changes in annual cooling degree-days;



10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25


Fig. 7. Monthly cooling degree-days at different cooling base temperature, hb,c in different climates: (a) Present-day, (b) 2020s, (c) 2050s and (d) 2080s.

Fig. 8. Change in monthly cooling degree-days in future climates from the baseline present-day climate at different cooling base temperature, hb,c: (a) 10 �C, (b) 13 �C, (c)16 �C, (d) 19 �C, (e) 22 �C and (f) 25 �C.


i.e., probable changes in cooling energy consumption, for basetemperatures between 10 �C and 25 �C for future climates aregiven in Table 6.

4. Adaptation of buildings to increased temperatures

Environmental design of buildings needs to be of high qualityto tackle the challenges of overheating and hot spells. Tempera-tures in a poorly designed building can be in excess of the out-

door temperatures during hot spells. It has been suggested thatthrough proper use of thermal storage and solar shading, it mightbe possible to keep the building close to the daily mean temper-ature, or even lower, for the duration of hot spells [30]. In thesestrategies, higher air temperatures are offset by cooler mean radi-ant temperatures and enhanced air movement [38]. However, thesmall diurnal variation; i.e., the difference between daily maxi-mum and minimum temperatures (see Fig. 3), during summerand monsoon seasons, may restrict the effectiveness of suchstrategies.

Fig. 9. Percentage change in cooling degree-days in future climates for various base temperatures, hb,c: (a) 10 �C, (b) 13 �C, (c) 16 �C, (d) 19 �C, (e) 22 �C and (f) 25 �C.

Table 6Percentage change in annual cooling degree-days at different base temperature, hb,c, in the 2020s, 2050s and 2080s from the baseline present-day climate.

Climate Change in annual cooling degree-days, Dc,a (%)Cooling base temperature, hb,c (�C)

10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25

2020s 6 6 7 7 8 8 9 10 10 11 13 14 15 17 20 232050s 14 15 16 18 19 20 22 23 25 28 31 34 38 44 50 592080s 28 29 31 34 36 39 43 46 51 55 61 69 78 90 106 127


It will be challenging to design buildings for natural or hybridventilation in Dhaka. Cooling loads comprising solar and internalheat gains will play an important role in the ability of a buildingto be naturally ventilated or to be adapted to the projected in-creases in temperature. In the UK, natural ventilation systems aresaid to be able to meet total heat loads (combined solar and inter-nal heat gains) averaged over the day of around 30–40 W m�2 [38].This threshold of total loads will be even lower for Dhaka becauseof the prevalence of high temperatures and poor thermal perfor-mance of building envelopes. Careful design of the building fabric[44] including the size and orientation of windows; thermal insu-lation [45] and solar shading [46] may assist in reducing solar heatgain. Internal heat gains from people, equipment and lighting canbe designed to avoid coincident solar and internal gains. It hasbeen suggested that natural ventilation systems become ineffec-tive if average coincident internal gains over the day exceed about15–20 W m�2 [47]. The minimization of the coincidence of thegains will determine how effective the strategies for the controlof gains are; e.g., the responsiveness of the artificial lighting systemto the availability of daylight. The location of heat-emitting busi-ness equipment in a space will be as important as the specificationof their energy efficiency.

As outdoor temperatures will be higher than indoor zone set-point temperature for most of the times in a year, pre-cooling ofthe air could be desirable at least for the hotter months of the year.Due to high solar resource availability (4.73 kW h m�2 day�1 onaverage in Dhaka [48]), solar absorption cooling [49,50] could bea viable alternative to energy intensive refrigeration based coolingsystems. However, research needs to be carried out on the perfor-mance of such systems in meeting the demand and whether thesystems need to be co-located with significant heat sources (e.g.,waste heat from industrial processes) or coolth storage to cope

with the lack of solar radiation during the night. Among other solu-tions, thermo-active building systems (TABS) that employ buildingstructure (wall, floor and ceiling) and its thermal storage capacityfor building energy management [51] can offer desired energy effi-ciency while providing required thermal comfort.

In order to direct building activities, both new-build and retrofitconstructions, in a sustainable direction, building regulations needto be updated to incorporate measures to adapt to the projected in-creases in temperature in future climates. Updates to the existingbuilding regulations [52] need to be evidence based and could ben-efit from the developments and research [53,54] in other countries.

5. Conclusion

Present-day statistically averaged weather data for Dhaka, Ban-gladesh is morphed with the projections for medium–high emis-sions scenario (IPCC A2 storyline) from the IPCC HadCM3 climatemodel to generate future hourly time series of temperature inthe 2020s, 2050s and 2080s. Corresponding heating and coolingdegree-days at different base temperatures for the baseline pres-ent-day and future climates are calculated from the time series.The distribution of temperature shifts to the right under future cli-mates; i.e., higher temperatures occur more than lower tempera-tures, which is indicative of the overall warming of the climate.The increase in temperature is likely to result in increased occur-rences of building overheating; e.g., temperatures above 28 �C oc-cur for about 71.9% of the time of the year in the 2080s, comparedto 31.0% in the present-day. Continuous hot spell is likely to be acommon feature in future climates. The combination of overheat-ing and the increased occurrence of hot spells will be a challengefor energy efficient and low carbon building design and operation.


Heating degree-days are traditionally low in Dhaka due to theprevalence of high temperatures throughout the year. Heating de-gree-days continue to decrease in future climates. On the otherhand, cooling degree-days continue to increase. However, there ex-ists an uneven variation of monthly cooling degree-days at differ-ent base temperatures. Percentage changes in cooling degree daysduring winter months are consistently higher at all base tempera-tures than those of the summer and monsoon months. Correspond-ing cooling energy demand increases in all future climates.

The thermal performance of the majority of buildings in Dhakais poor; e.g., single glazed windows without adequate solar shad-ing. Hence solar heat gains are in excess of what can be efficientlytackled by natural or hybrid ventilation systems. The projected in-creases in temperature are likely to exacerbate the situation. Asbuildings have a typical lifespan of 50–100 years, prompt actionsto regulate the environmental performance of buildings are neces-sary to enhance the resilience of Dhaka’s buildings to climatechange.

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