Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84 
Copyright © Faculty of Engineering, University of Maiduguri, Maiduguri, Nigeria.  
Print ISSN: 1596-2490, Electronic ISSN: 2545-5818, www.azojete.com.ng 

 

72 
 

THE COOLING SYSTEMS AND WEATHER STATISTICS OF MAIDUGURI AND 

YOLA - NIGERIA  

J. A. Olorunmaiye
1*

 and O. O. Awolola
2
 

1
Department of Mechanical Engineering, University of Ilorin, P.M.B. 1515, Ilorin, Kwara State, Nigeria 
2
Department of Mechanical Engineering, The Federal Polytechnic, Ilaro, P.M.B. 50, Ilaro, Ogun State, 

Nigeria 

*Corresponding author’s email address: adeolorunmaiye@gmail.com, lekanoba@yahoo.com 

Tel.: +234-8036000053, +234-8027955316 

Abstract 

Bin data for dry bulb temperature, relative humidity and two-dimensional bin for dry bulb temperature - relative 

humidity were compiled using a fifteen-year hourly dry bulb temperature and relative humidity data for Maiduguri 

and Yola. The data were collected from Nigerian Meteorological Agency (NiMet), Oshodi, Lagos. The bins sizes of 

1°Cand 5% were used for dry bulb temperature and relative humidity respectively. The number of hours in each 

month in which dry bulb temperature ≥ 32.2°C and relative humidity ≤ 50% during which appreciable evaporative 

cooling can occur and when dry bulb temperature/relative humidity pair was in the comfort zone were determined. 

The modal bin for dry bulb temperature (TDB) and relative humidity (RH) are 25 - 26°Cand 15-20% for Maiduguri 

and 25-26°Cand 90-95% for Yola. April and March are the months that appreciable evaporative cooling usually 

occurs in the chosen locations and evaporative coolers could be applied during the months of March up to May. But 

from July to September the evaporative coolers perform poorly in both locations. During the months of October to 

February, low monthly costs of running the refrigerators and air conditioners significantly different from other 

months of the year, were indicated by the results. 

 

Key words: Bin data, dry bulb temperature, relative humidity, evaporative cooling, comfort zone, 

refrigerators and air conditioners 

1. Introduction 

The world is experiencing increase in ambient temperature which resulted from several human 

activities that releases greenhouse gases in to the atmosphere. This experience termed global 

warming has caused increase in energy and water consumption and equally badly affects human 

wellbeing (Karl and Easterling, 1999). 

Human comfort in the work place is a challenge in temperate zone especially in summer, hence 

there is need to cool occupied spaces. On the other hand in tropical countries like Nigeria, 

cooling is necessary almost all year round, especially in hot and humid weather conditions. 

Besides human discomfort and loss of concentration at work, extreme heat affects health and 

productivity. It is difficult to dissipate heat when dry bulb temperature is extremely high 

especially if the relative humidity is also high (Harris, 1983). Ambient temperature is a factor to 

be considered when performance of certain types of equipment used in cooling systems is an 

issue. There is a reduction of heat rejection of an air cooled condenser of vapour compression 

refrigeration system when the dry bulb temperature of the environment increases (Olorunmaiye 

and Ariyo, 1998). 

 

1.1 Review of Previous Investigation on Global Warming 

A number of studies have been carried out on the effect of global warming on energy utilized by 

cooling systems. Olorunmaiye et al. (2012) investigated the effect of change in ambient 

mailto:adeolorunmaiye@gmail.com
mailto:lekanoba@yahoo.com


Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 

1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 

73 
 

temperature on energy consumption of refrigerators by operating the refrigerator at three ambient 

temperature conditions and they found that energy consumption by refrigerator increases with 

increase in ambient temperature of the space where the refrigerator is operated. Saidur et al. 

(2005) found that among the three independent variables affecting power required for operating 

the refrigerator-freezer (ambient temperature, load in the refrigerator-freezer and the number of 

times the door was opened per hour), ambient temperature had the greatest effect. A report by the 

energy commission of California said that with increase in ambient temperature, higher energy 

utilization was anticipated. (Xu et al., 2009).   

Other studies have been done on weather statistics of some locations in Nigeria by earlier 

researchers which included Maiduguri and Yola. Shoboyejo and Shonubi (1974) used 1951-1965 

meteorological data to compute the outside design condition of air conditioning systems for 

some locations in Nigeria among which were Maiduguri and Yola in which they obtained the 

outside design condition of dry bulb and wet bulb temperatures for 1%, 2½%, and 5% 

confidence values for the four warmest months assuming Gaussian Probability distributions.  

Olorunmaiye and Awolola (2015) used 1995-2009 meteorological data of 18 locations which 

included Maiduguri and Yola to compute 1%, 2½%, and 5% confidence values for dry and wet 

bulb temperatures. The values they obtained for both dry-bulb and wet-bulb temperatures were 

higher than corresponding values obtained by Shoboyejo and Shonubi (1974) for both Maiduguri 

and Yola. 

Statistical analysis of 1995-2009 dry bulb temperature and relative humidity data for Ilorin, was 

done and it was reported (Olorunmaiye and Awolola, 2015) that there is increase in the values 

got when compared with those obtained by Olorunmaiye and Ariyo (1998) which were based on 

1978-1992 dry bulb temperature and relative humidity data for Ilorin. The above results show 

that Nigeria is not excluded from the scourge of global warming and climate change.  

Wet bulb temperature is an important parameter which affects the performance of evaporative 

cooling systems such as earthen pots, evaporative coolers used as refrigerators (Olorunmaiye, 

1995) and evaporative coolers used in dry arid areas for air conditioning (Harris, 1983). High 

degree of evaporative cooling can be experienced when the system is in an environment in which 

high dry bulb temperature (≥32.2°C) and low relative humidity (≤50%) occur concurrently.  

The concept of effective temperature has been developed from the research of the American 

Society of Heating, Refrigeration and Air conditioning Engineers (ASHRAE) relating 

temperature, humidity and air movement to human comfort. Effective temperature lines on wet 

bulb temperature versus dry bulb axes are lines joining different combination of dry bulb 

temperature and relative humidity which give the same feeling of comfort to a high percentage of 

people equally clothed and equally active, for a given air velocity (0.0762-0.1270 m/s for the 

comfort chart for still air) (Harris, 1983). The comfort zone in the chart is between effective 

temperatures of 17.2°C and 23.9°C. The dry bulb temperature and the relative humidity of the 

four corners of the comfort zone are: 18.3°C/70%, 25.7°C/70%, 19.8°C/30%, and 29.1°C/30%. 

Maiduguri is located on latitude 11.85
°
N and longitude 13.08

°
E with an altitude of 345m above 

sea level, Maiduguri falls within the semi-arid zone of West Africa geographically and it 

experiences little rainfall and more of dry season (Abdulrahim et al, 2012). Yola is the capital of 

Adamawa State, Nigeria. The town is situated at an altitude of 186m. The geographical 



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. 
AZOJETE 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

74 
 

coordinates are 09°14'N and 12°28'E. Yola is located on the Benue River and it has a mean 

temperature of 28.3°C (Alexander, 2015)  

The aim of the work reported in this paper is to carry out statistical analysis on 15-year data of 

hourly dry bub temperature and relative humidity of both Maiduguri and Yola in the North East 

Geo-political zone of Nigeria, by compiling the bin data for dry bulb temperature, relative 

humidity and two - dimensional dry bulb temperature/ relative humidity. The proportion of the 

hours in the year when the weather is within the comfort zone and the amount of time a high 

level of evaporative cooling could be experienced will equally be estimated. 
 

2. Materials and Methods 

Fifteen year hourly dry bulb temperature and relative humidity data for Maiduguri (1995-2009) 

and for Yola (1994-2008) were obtained from Nigerian Meteorological Services (NiMet), 

Oshodi, Lagos. The data were keyed into the computer using Microsoft Office Excel 1997-2003 

version. From the meteorological data, the bin data for both dry bulb temperature and relative 

humidity were compiled. Microsoft Excel codes were written to do the compilation of both dry 

bulb temperature and relative humidity bins for both locations while Visual Basic codes were 

written to compile two- dimensional dry bulb temperature/relative humidity bin for the two 

locations. The bins width of 1 degree Celsius for dry bulb temperature and 5 percent for relative 

humidity were employed.  
 

3. Results and Discussion 

(i) Diurnal variation of the monthly average weather conditions 

Figures 1 and 3 show the diurnal variation of the monthly average hourly dry bulb temperature 

for January to December for Maiduguri and Yola respectively. The diurnal variation of the 

monthly average hourly relative humidity for January to December for Maiduguri and Yola are 

shown in Figures 2 and 4. The hours of the day in the abscissae of the sets of graphs are 

Greenwich Mean Time (GMT) since GMT was used as the time base for the data collected from 

Nigerian Meteorological Agency (NiMet). Figures 1 through 4 show that, for any month, as the 

average values of hourly dry bulb temperature increases there is corresponding decrease in the 

average values of hourly relative humidity. Thus there is negative cross correlation coefficients 

of dry bulb temperature and relative humidity for all the months. The variations of relative 

humidity shown in Figures 2 and 4 are caused majorly by diurnal changes in dry bulb 

temperature. As air warms up, the moisture it can carry per unit mass increases and its relative 

humidity is lowest in the afternoon around 15.00 Greenwich Mean Time (GMT) at the highest 

dry bulb temperature and conversely relative humidity is highest at 6.00 GMT at the lowest dry 

bulb temperature, this was equally reported by Olorunmaiye and Ariyo (1998) in respect of Ilorin 

weather conditions based on 1978-1992 data.  



Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 

1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 

75 
 

 

Figure 1: Diurnal variation of monthly-average hourly dry bulb temperature forMaiduguri 

 

Figure 2: Diurnal variation of monthly-average hourly relative humidity for Maiduguri 

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

1ST QUARTER 

Jan Feb Mar

21.0

24.0

27.0

30.0

33.0

36.0

39.0

42.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of  the day (hrs) 

2ND QUARTER 

Apr May Jun

20.0
22.0
24.0
26.0
28.0
30.0
32.0
34.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

3RD QUARTER 

Jul Aug Sep

10.0

15.0

20.0

25.0

30.0

35.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

4TH QUARTER 

Oct Nov Dec

0

10

20

30

40

50

60

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

1ST QUARTER 

Jan Feb Mar

0

20

40

60

80

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

2ND QUARTER 

Apr May Jun

40

50

60

70

80

90

100

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

3RD QUARTER 

Jul Aug Sep

0

20

40

60

80

100

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

4TH QUARTER 

Oct Nov Dec



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. 
AZOJETE 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

76 
 

 

Figure 3: Diurnal variation of monthly-average hourly dry bulb temperature for Yola 

 

Figure 4: Diurnal variation of monthly-average hourly relative humidity for Yola 

 

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

1ST QUARTER 

Jan Feb Mar

20.0

25.0

30.0

35.0

40.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

2ND QUARTER 

Apr May Jun

20.0

22.0

24.0

26.0

28.0

30.0

32.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

3RD QUARTER 
Jul Aug Sep

10.0

15.0

20.0

25.0

30.0

35.0

40.0

0 4 8 12 16 20 24

Te
m

p
e

ra
tu

re
 (°

C
) 

Time of the day (hrs) 

4TH QUARTER 

Oct Nov Dec

0

10

20

30

40

50

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

1ST QUARTER 

Jan Feb Mar

0

20

40

60

80

100

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

2ND QUARTER 

Apr May Jun

60

70

80

90

100

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

3RD QUARTER 

Jul Aug Sep

0

20

40

60

80

100

0 4 8 12 16 20 24

R
e

la
ti

ve
 H

u
m

id
it

y 
(%

) 

Time of the day (hrs) 

4TH QUARTER 

Oct Nov Dec



Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 

1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 

77 
 

(ii) Weather, Bin data and cooling systems 

The bin data compiled for ambient temperature and relative humidity are shown in Figures 5 and 

6, respectively, for both locations.  

 

 

Figure 5: Comparison of Maiduguri and Yola dry bulb temperatures bins 

 

 
Figure 6: Comparison of Maiduguri and Yola relative humidity bins 

 

From Figure 5 the minimum dry bulb temperature for Maiduguri is in 6-7°C bin at an average of 

0.07 hours per year in January during harmattan season, and minimum temperature for Yola 

-50

50

150

250

350

450

550

650

750

0
-5

5
-1

0

1
0

-1
5

1
5

-2
0

2
0

-2
5

2
5

-3
0

3
0

-3
5

3
5

-4
0

4
0

-4
5

4
5

-5
0

5
0

-5
5

5
5

-6
0

6
0

-6
5

6
5

-7
0

7
0

-7
5

7
5

-8
0

8
0

-8
5

8
5

-9
0

9
0

-9
5

9
5

-1
0

0

1
0

0
-1

0
5

N
u

m
b

e
r 

o
f 

h
o

u
rs

 

Relative humidity bin 

Maiduguri Yola

-50

50

150

250

350

450

550

650

750

6
-7

8
-9

1
0

-1
1

1
2

-1
3

1
4

-1
5

1
6

-1
7

1
8

-1
9

2
0

-2
1

2
2

-2
3

2
4

-2
5

2
6

-2
7

2
8

-2
9

3
0

-3
1

3
2

-3
3

3
4

-3
5

3
6

-3
7

3
8

-3
9

4
0

-4
1

4
2

-4
3

4
4

-4
5

4
6

-4
7

4
8

-4
9

N
u

m
b

e
r 

o
f 

h
o

u
rs

 

Dry bulb temperature bin  

Maiduguri Yola



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. 
AZOJETE 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

78 
 

occurred in 12-13°C bin for an average of 0.07 hours in November. The maximum dry bulb 

temperature occurs in 48-49°C bin for an average of 0.07 hours per year and 44-45°C bin for an 

average of 0.57 hours per year, for Maiduguri and Yola respectively. The modal temperature for 

the two locations occurred in 25-26°C bin. The minimum and maximum temperatures are two 

extremes which fortunately occur for few hours per year, otherwise this would have posed a 

great challenge for human comfort. 

The charts in Figure 6 for relative humidity bins for Maiduguri and Yola show that 15-20% RH 

bin and 90-95% RH bin are the modes for Maiduguri and Yola with 725.02 hours and 675.41 

hours respectively. The charts show that most of the time when Maiduguri was dry Yola was 

relatively humid. The ambient air condition will be outside comfort zone about 2930 hours in 

Yola when compared to 1725 hours in Maiduguri and there is need for dehumidification to 

achieve comfort most of the time in Yola. 

Tables 1 and 2 show respectively the two-dimensional dry bulb temperature/relative humidity 

bin data of Maiduguri and Yola. The number in each cell is the average number of hours in a 

year that dry bulb temperature and relative humidity combination are in the bin. The two-

dimensional dry bulb temperature/ relative humidity bin data show the coincidence and 

distribution of dry bulb temperature and relative humidity. This bin data is useful for accurate 

estimation of building cooling loads.  



Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818; 

www.azojete.com.ng 

79 
 

Table 1: Two dimensional dry bulb temperature/relative humidity bin data for Maiduguri 
RH 0-5 5-10 10-15 15-20 20-25 25-30 30-35 35-40 40-45 45-50 50-55 55-60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 95-100 100-105 

Temp                                           

6-7 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

7-8 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.07 0.47 0.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

8-9 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.13 0.27 0.73 0.40 0.33 0.14 0.00 0.00 0.00 0.00 0.00 0.00 

9-10 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.20 0.87 1.20 0.80 0.33 0.40 0.33 0.00 0.00 0.00 0.00 0.00 0.00 

10-11 0.00 0.00 0.00 0.00 0.00 0.07 0.20 0.40 1.33 2.67 3.73 2.87 1.13 1.13 0.60 0.40 0.00 0.00 0.00 0.00 0.00 

11-12 0.00 0.00 0.00 0.13 0.07 0.13 0.07 0.93 3.40 6.47 8.13 4.07 2.27 1.53 0.07 0.13 0.00 0.07 0.00 0.00 0.00 

12-13 0.07 0.00 0.00 0.00 0.20 0.33 1.80 3.60 8.53 10.87 11.00 6.40 4.67 1.66 0.33 0.07 0.07 0.00 0.00 0.00 0.00 

13-14 0.00 0.00 0.00 0.00 0.47 0.93 2.67 8.27 12.80 15.73 12.60 10.87 4.47 1.13 0.46 0.07 0.00 0.00 0.00 0.00 0.00 

14-15 0.00 0.00 0.00 0.13 0.73 1.80 6.60 14.00 21.00 21.13 14.13 11.33 3.67 1.40 0.40 0.20 0.00 0.07 0.00 0.07 0.00 

15-16 0.00 0.00 0.00 0.13 1.27 4.27 11.80 19.46 23.26 23.33 16.73 10.80 3.33 1.07 0.20 0.13 0.00 0.00 0.00 0.00 0.00 

16-17 0.00 0.00 0.07 0.40 2.60 9.26 19.06 22.66 25.06 25.80 21.53 9.20 3.87 0.93 0.60 0.00 0.00 0.00 0.00 0.00 0.00 

17-18 0.00 0.00 0.20 1.27 4.47 12.40 25.71 25.86 23.53 22.00 15.27 8.13 2.67 1.40 0.47 0.00 0.07 0.00 0.00 0.00 0.00 

18-19 0.00 0.00 0.07 1.79 9.40 19.00 30.19 30.20 28.26 20.20 14.73 5.33 3.80 1.27 0.87 0.47 0.40 0.40 0.07 0.00 0.00 

19-20 0.00 0.13 0.27 3.53 12.40 24.33 31.80 31.26 23.86 17.60 11.20 6.67 3.33 1.40 1.34 0.93 0.67 0.20 0.07 0.00 0.00 

20-21 0.07 0.07 1.00 6.80 22.33 35.79 34.79 31.33 24.47 16.67 11.87 7.42 5.02 3.22 2.01 1.34 2.71 1.64 2.39 6.28 0.93 

21-22 0.00 0.07 2.00 9.86 25.53 35.66 33.20 26.26 17.73 13.93 9.37 4.24 5.44 3.98 3.94 3.34 4.99 7.73 15.22 26.81 3.09 

22-23 0.00 0.33 2.20 14.93 35.72 41.40 36.20 23.53 19.07 12.38 7.03 7.39 6.84 6.79 5.66 8.57 14.16 21.69 46.36 52.61 5.37 

23-24 0.07 0.53 4.27 21.33 38.39 47.33 33.26 21.33 12.93 10.17 7.58 6.44 6.74 8.64 10.88 17.38 30.84 51.96 88.81 42.68 1.27 

24-25 0.20 0.20 6.13 28.86 47.06 44.73 33.00 17.67 12.61 8.88 7.54 7.86 8.11 11.93 17.65 36.07 62.02 87.72 88.83 26.77 0.98 

25-26 0.27 0.40 12.13 34.33 48.13 42.60 27.87 16.27 9.94 6.69 6.49 8.08 13.50 19.17 37.81 58.22 82.14 73.36 48.58 14.60 0.68 

26-27 0.20 1.34 15.47 42.06 44.73 35.86 24.34 13.80 8.87 7.61 7.90 12.29 23.87 36.33 54.05 65.33 74.71 40.08 19.19 8.63 0.40 

27-28 0.07 1.93 22.46 48.66 47.13 31.67 21.40 11.53 8.07 8.50 14.07 25.50 41.29 49.67 69.99 60.64 38.96 17.02 10.43 6.19 0.34 

28-29 0.20 3.53 29.06 53.39 43.27 31.33 17.34 9.87 10.16 15.52 25.05 38.58 55.55 58.96 58.86 38.36 16.83 10.82 8.60 3.84 0.54 

29-30 0.27 6.80 35.59 55.13 38.73 22.01 16.73 10.41 12.49 18.71 37.37 51.25 56.36 59.81 41.49 16.46 9.65 6.60 5.66 1.78 0.34 

30-31 0.60 11.46 49.12 59.60 37.73 21.47 16.15 12.01 14.79 32.19 43.65 49.18 62.33 49.59 17.78 6.07 5.45 3.15 3.55 2.34 0.55 

31-32 0.27 13.20 47.19 51.33 30.13 18.15 11.74 12.22 21.04 37.14 44.27 53.53 54.79 23.33 8.43 4.89 3.52 2.60 2.10 2.29 0.28 

32-33 0.60 16.93 51.06 45.73 28.67 15.20 10.40 14.29 31.01 38.77 43.68 46.06 28.52 10.23 4.91 2.92 2.00 2.13 1.59 1.03 0.21 

33-34 1.07 21.33 55.19 47.80 26.20 11.94 11.68 19.80 36.99 39.67 37.72 26.05 10.75 5.08 3.73 1.69 1.49 1.16 1.92 0.97 0.21 

34-35 0.67 22.46 48.93 41.87 24.67 11.21 15.84 30.37 35.48 31.14 21.35 10.60 5.47 2.65 1.42 0.68 1.23 0.68 0.62 0.75 0.28 

35-36 0.40 27.26 49.80 35.53 22.80 13.87 24.29 33.43 31.79 17.47 9.82 5.03 2.39 1.61 0.60 0.75 1.10 0.41 0.35 0.27 0.14 

36-37 0.26 29.93 45.13 31.60 17.27 13.75 31.85 35.57 17.99 6.12 3.04 1.74 1.02 1.42 0.61 0.20 0.21 0.20 0.27 0.33 0.00 

37-38 1.26 27.73 34.93 21.87 14.88 18.91 29.78 18.63 5.98 2.42 1.27 1.27 0.40 0.47 0.46 0.07 0.07 0.20 0.00 0.07 0.07 

38-39 1.27 34.06 30.67 17.27 14.15 22.86 21.68 7.23 1.67 1.27 0.67 0.27 0.53 0.07 0.07 0.19 0.00 0.00 0.00 0.00 0.07 

39-40 1.33 32.60 25.00 12.34 20.03 21.93 12.03 3.14 1.40 0.93 0.47 0.13 0.00 0.13 0.20 0.07 0.00 0.00 0.00 0.07 0.00 

40-41 1.53 30.60 28.07 14.54 18.15 12.35 4.61 1.07 0.13 0.13 0.07 0.13 0.00 0.13 0.07 0.00 0.00 0.00 0.07 0.00 0.00 

41-42 1.66 24.40 18.40 13.61 12.41 5.20 2.53 0.60 0.20 0.27 0.07 0.07 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

42-43 0.27 13.74 10.40 8.07 4.80 2.40 0.53 0.00 0.13 0.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

43-44 0.07 5.93 3.61 1.07 0.93 0.33 0.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

44-45 0.07 1.47 0.73 0.07 0.26 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

45-46 0.00 0.00 0.13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 

46-47 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

47-48 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

48-49 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

 



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. AZOJETE 14(1):72-84. ISSN 1596-
2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

80 
 

Table 2: Two dimensional dry bulb temperature/relative humidity bin data for Yola 

RH 0-5 5-10 

10-

15 

15-

20 

20-

25 

25-

30 

30-

35 

35-

40 

40-

45 

45-

50 

50-

55 

55-

60 60-65 65-70 70-75 75-80 80-85 85-90 90-95 

95-

100 

100-

105 

Temp                                           

12-13 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 

13-14 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.20 0.07 0.40 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

14-15 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.00 0.27 0.13 1.13 0.47 0.53 0.20 0.07 0.00 0.00 0.07 0.00 0.00 

15-16 0.00 0.00 0.00 0.00 0.00 0.00 0.07 0.33 0.40 1.13 3.20 3.00 2.47 1.40 1.00 0.80 0.67 0.13 0.00 0.00 0.00 

16-17 0.00 0.00 0.00 0.00 0.00 0.07 0.20 0.87 1.53 3.27 5.73 6.67 6.67 4.47 4.47 2.53 1.27 0.60 0.00 0.00 0.00 

17-18 0.00 0.00 0.00 0.00 0.00 0.33 0.73 2.13 4.13 8.00 7.87 8.40 9.20 6.73 7.40 5.07 3.20 1.00 0.40 0.07 0.00 

18-19 0.00 0.00 0.00 0.00 0.13 0.93 2.20 4.67 7.67 13.73 14.80 10.73 11.40 12.20 9.13 6.27 5.00 2.33 0.33 0.00 0.00 

19-20 0.00 0.00 0.00 0.07 0.33 1.73 5.47 11.80 12.47 15.93 16.40 15.40 15.07 10.93 8.33 7.13 4.20 2.07 1.13 0.13 0.00 

20-21 0.00 0.00 0.07 0.47 1.40 5.47 10.60 11.07 20.40 18.13 13.67 14.07 16.67 12.07 9.33 6.20 5.47 3.13 1.87 1.69 0.54 

21-22 0.00 0.00 0.07 0.80 3.07 10.80 16.86 19.33 19.60 20.33 17.40 14.87 13.80 12.80 8.20 5.47 5.67 6.01 6.52 18.63 6.82 

22-23 0.00 0.00 0.00 1.20 5.87 14.47 20.40 20.40 30.47 13.80 17.67 15.80 12.20 8.80 8.73 7.13 10.42 11.13 37.21 85.44 16.15 

23-24 0.00 0.00 0.07 1.47 6.13 18.29 23.74 27.87 21.80 19.21 14.87 14.87 9.73 7.94 6.67 11.61 17.34 40.49 117.64 122.44 10.73 

24-25 0.00 0.07 0.41 2.67 8.26 21.29 31.87 25.10 22.63 14.87 14.23 10.53 9.60 9.09 9.41 14.25 39.84 105.74 202.35 115.19 4.21 

25-26 0.07 0.00 0.40 3.00 13.73 30.07 29.36 31.27 19.44 16.76 10.87 9.74 9.87 10.16 12.26 27.85 104.63 174.62 184.49 52.36 2.20 

26-27 0.00 0.13 0.40 4.61 17.89 29.90 38.08 25.86 16.62 14.92 9.57 9.50 9.25 15.70 32.16 63.82 163.63 139.42 84.83 17.65 1.20 

27-28 0.00 0.00 0.67 7.47 21.38 34.50 33.72 25.43 14.75 10.31 9.99 9.26 14.84 23.66 63.36 104.04 141.72 73.85 21.66 6.27 0.80 

28-29 0.00 0.07 1.41 10.81 28.49 36.52 36.16 19.67 15.02 11.33 8.61 12.14 29.75 47.39 106.81 116.34 67.19 30.05 7.42 3.08 0.60 

29-30 0.00 0.22 2.50 13.62 34.14 34.75 29.40 22.71 13.45 9.43 12.45 27.76 42.90 96.34 124.45 78.89 24.59 6.97 2.93 2.20 0.40 

30-31 0.00 0.00 3.81 20.06 40.88 38.67 27.21 18.53 11.42 11.63 19.44 41.32 69.94 139.50 79.97 26.62 7.48 3.88 2.27 1.87 0.47 

31-32 0.00 0.07 6.87 30.63 39.25 37.17 28.33 14.94 9.89 16.10 29.78 52.31 109.04 107.14 31.70 7.95 3.20 1.47 2.40 1.00 0.60 

32-33 0.00 0.27 8.74 31.49 45.13 37.15 24.81 12.35 11.54 20.14 35.24 70.92 95.63 37.01 9.23 3.76 1.80 1.33 1.15 0.87 0.40 

33-34 0.00 0.61 11.78 38.92 46.48 31.23 20.86 14.04 16.59 29.40 53.48 62.01 36.86 12.30 2.53 1.00 1.14 0.47 0.47 0.27 0.27 

34-35 0.00 0.75 14.58 39.12 42.49 32.35 20.17 18.40 23.80 39.07 46.72 26.04 6.77 2.28 0.74 0.74 0.74 0.49 0.28 0.21 0.07 

35-36 0.00 1.28 18.98 38.52 39.11 26.57 17.10 16.61 27.74 41.32 22.56 5.69 1.21 0.33 0.13 0.21 0.56 0.15 0.14 0.00 0.00 

36-37 0.00 1.29 18.59 33.55 33.66 19.71 17.55 24.33 31.02 27.82 4.86 0.48 0.28 0.20 0.22 0.22 0.56 0.35 0.07 0.00 0.00 

37-38 0.00 1.99 19.70 32.44 22.07 15.53 16.93 26.16 31.60 10.51 0.55 0.00 0.13 0.21 0.47 0.49 0.20 0.07 0.00 0.00 0.00 

38-39 0.00 2.45 24.60 24.46 16.29 12.74 20.88 28.17 14.86 2.56 0.56 0.20 0.07 0.42 0.50 0.20 0.00 0.07 0.07 0.00 0.00 

39-40 0.07 3.68 22.37 21.17 16.71 16.05 22.16 16.83 4.00 0.21 0.07 0.07 0.28 0.35 0.07 0.07 0.07 0.00 0.00 0.00 0.00 

40-41 0.00 4.27 19.49 17.43 15.30 17.98 13.54 4.69 0.27 0.07 0.21 0.00 0.07 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 

41-42 0.00 4.17 11.10 10.84 11.01 7.56 4.61 1.49 0.40 0.13 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

42-43 0.00 1.66 8.46 5.36 4.99 2.77 0.36 0.07 0.00 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

43-44 0.00 0.28 0.36 1.77 0.99 0.36 0.07 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

44-45 0.00 0.00 0.07 0.49 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 

 



Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 

1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 

81 
 

(iii) Evaporative cooling 

When a place has dry bulb temperature equal to or higher than 32.2°C with coincident relative 

humidity of less than 50%, there will be appreciable evaporative cooling. 

The number of hours in each month for both locations in which a high level of evaporative cooling 

could occur (dry bulb temperature ≥ 32.2°C with relative humidity ≤ 50%) are shown in Figure 7. 

From Tables 1 and 2, the number of hours for TDB and RH within these ranges for both Maiduguri 

and Yola are shown inside the lower rectangles and the total number of hours are1978.34 and 

1686.68 hours respectively for Maiduguri and Yola. These figures compare well with results 

obtained from the addition of monthly average number of hours for Maiduguri and Yola in Figure 7. 

 
Figure 7: Number of hours in which a high degree of evaporative cooling can take place 

 
Figure 8: Number of hours in which the weather is within the comfort zone 

0

50

100

150

200

250

300

350

400

450

1 2 3 4 5 6 7 8 9 10 11 12

N
u

m
b

e
r 

o
f 

h
o

u
rs

 

Month of the year 

Maiduguri Yola

0

50

100

150

200

250

300

350

400

1 2 3 4 5 6 7 8 9 10 11 12

N
u

m
b

e
r 

o
f 

h
o

u
rs

 

Month of the year 

Maiduguri Yola



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. 
AZOJETE 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

82 
 

 
Figure 9: Number of hours in which the dry bulb temperature is less than 25°C 

 

(iv) Comfort zone and ventilation  

The average number of hours in the year in which the weather condition lies within the comfort 

zone is the addition of the hours bounded by the upper rectangles in Tables 1 and 2 and the totals 

are 1498.04 and 1449.03 hours for Maiduguri and Yola respectively. The monthly number of hours 

of this is shown Figure 8 for both locations which added up to be 1498.05 and 1448.48 hours for 

Maiduguri and Yola respectively. The small differences (1498.05 – 1498.04) and (1448.48 – 

1449.03) are due to computational errors. October, November and December are the three months 

having highest number of hours per month in the comfort zone for Maiduguri. While the four 

months with highest number of hours per month in the comfort zone for Yola are November, 

December, January and February; these months are in the hammattan season for Yola. In 

Maiduguri, August and September have the lowest number of hours in the comfort zone. While the 

lowest number of hours in the comfort zone for Yola occur in August to October.  

When weather is within the comfort zone, only ventilation is needed for human comfort which 

could be achieved by natural breeze or fans driven by electric motor.   Air conditioning systems will 

be expected to work for the highest number of hours and thus consume highest amount of energy 

per month in the months of August and September for Maiduguri and Yola respectively, since they 

have the lowest number of hours in the comfort zone. On the other hand, the cooling units are 

expected to work for minimum number of hours for December and January in Maiduguri and 

October and November in Yola, leading to minimal energy consumption. 

Figure 9 shows the number of hours in each month in which dry bulb temperature is less than 25°C 

for both cities. Since the indoor design dry-bulb temperature for comfort air conditioning systems is 

24°C, the hours having dry-bulb less than 25°C are the hours in which it is not necessary to put on 

an air conditioner. 

 

0

50

100

150

200

250

300

350

400

450

500

1 2 3 4 5 6 7 8 9 10 11 12

N
u

m
b

e
r 

o
f 

h
o

u
rs

 

Month of the year 

Maiduguri Yola



Arid Zone Journal of Engineering, Technology and Environment, March, 2018; Vol. 14(1):72-84. ISSN 

1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 

83 
 

The transmission heat gain resulting from temperature difference between the outside air and the air 

in the space being cooled and air change heat gain due to door opening and infiltration are important 

components of the cooling load of a cooling system. The numbers of hours when the ambient 

temperature is above 25°C can be used as an indicator of the magnitude of these heat gains. From 

Figure 9, the refrigerator can be expected to consume minimum energy per months in the months of 

December and January at both Maiduguri and Yolaand maximum energy in May and April at 

Maiduguri and Yola respectively. 
 

4. Conclusions 

Dry-bulb temperature and relative humidity data for Maiduguri and Yola have been analysed to 

produce one dimensional bin data for both variables and also TDB/RH two-dimensional bin data. 

There are higher numbers of hours in the comfort zone in December and January for Yola while the 

best period for comfort is November for Maiduguri; the two lowest number of hours for comfort 

zone occur in August and September for the two locations. Evaporative coolers will work best at 

both Maiduguri and Yola from March to May. The poorest performance of evaporative cooler will 

occur from July to September. From October to February, the monthly cost of running refrigerators 

and air conditioners will be lowest compared to other months of the year since these are months 

having low RH and also low TDB. 
 

Acknowledgement  

The authors acknowledge with appreciation the provision of the weather data by Nigerian 

Meteorological Agency, (NiMet), Oshodi, Lagos, Nigeria. 
 

References 

Abdulrahim, AT., Mshelia,RB., Stephen, OG., Kyauta, ET. 2012. Heat stress as a measure of 

human level of comfort in a semi- arid zone, Maiduguri, Nigeria.  World Journal of Engineering and 

Pure and Applied Sciences; 2(3): 107-111. 

Alexander, CB. 2015. Statistical Analysis of Seasonal Temperature Variation and Thunderstorm 

Activity over Yola North-East Nigeria. American Journal of Educational Research, 3(7): 873-880. 

doi: 10.12691/education-3-7-10. 

Harris, NC.,1983. Modern Air Conditioning Practice. 3
rd

 Edition, McGraw-Hill Book Co. Ltd., 

Singapore 

Karl, TR. and Easterling, DR., 1999. Climate Extreme selected review and future research 

directions. Climate Change, 42: 309 - 325  

Olorunmaiye, JA.,1995. Experimental Investigation of an Evaporative Cooler. Technical 

Publication of the Nigerian Society of Engineers – Ilorin Branch: 15 – 23 

Olorunmaiye, JA. and Ariyo, DO. 1998. Analysis of weather data of Ilorin for refrigeration and Air 

conditioning. Centrepoint, 8(1): 1-14  



Olorunmaiye and Awolola. The cooling systems and weather statistics of Maiduguri and Yola – Nigeria. 
AZOJETE 14(1):72-84. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng 

 

84 
 

Olorunmaiye, JA. and Awolola, OO. 2015. Evaluation of Outside Air Design Dry and Wet bulb 

Temperatures for Air Conditioning Systems in Nigeria. Technical Transactions of the Nigerian 

Society of Engineers, 49(2): 54-66 

Olorunmaiye, JA., Awolola, OO. and Opadiji, JF. 2012. Experimental investigation of the effect of 

change in ambient air temperature on power consumption of domestic refrigerator. Nigerian Journal 

of Technological Development 9(2): 96-105 

Saidur, R., Chew, WC. and Masjuki, HH. 2005. Development and Validation of Refrigerator-

Freezers Energy Consumption Model with the Aid of RSM, Journal of Energy and Environment, 

4:11-19. 

Soboyejo, ABO. and Shonubi, FA. 1974. Evaluation of Outside Design Conditions for Air-

conditioning system Design in Nigeria, The Nigeria Engineer, 9(1): 5-11 

Xu, P., Huang, Y., Miller, N., and Schlegel, N., 2009. California Energy Commission Report, Effect 

of global climate change on building energy consumption and its implication on building energy 

codes and policy in California.