




































In ternationa l
Scholars
Journa ls

 

African Journal of Environmental Economics and Management ISSN 2375-0707 Vol. 7 (2), pp. 001-008, 
February, 2019. Available online at www.internationalscholarsjournals.org © International Scholars Journals 

 

Author(s) retain the copyright of this article. 
 
 

 

Full Length Research Paper 

 

Estimating the wind energy potential over the 
coastal stations of Nigeria using power law and 

diabatic methods 
 

Oluleye A.* and Ogungbenro S. B. 
 

Department of Meteorology, School of Earth and Mineral Sciences, Federal University of Technology, P. M. B. 

704, Akure, Ondo State, Nigeria. 
 

Accepted 24 October, 2018 
 
The suitability of two coastal stations in Nigeria for wind energy generation is presented in this study. To estimate the 

wind speeds at the desired height 70 m for standard wind turbine, two methods; namely power law relationship and 

diabatic evaluation have been considered. It was found that the diabatic evaluation method performed better because 

certain physical conditions of farm site are included in the method. Thus when potential site data are not available 

diabatic method can provide a good approximation of wind speeds. Comparing the energy potential of the two coastal 

stations, Lagos and Calabar in this study, it was found that Lagos has stronger wind speeds than Calabar especially 

during peak periods. The atmospheric condition most suitable to obtain maximum wind speeds was also found to be 

during stable condition. Stable condition occurs mostly in the night time. 

 

Key words: Wind potential energy, wind turbine, power law, diabatic evaluation. 

 
INTRODUCTION 

 
Issues of carbon emissions and climate change in relation to 

power generation and demand have prompted attention to 

renewable sources of energy generation. Recently, 

awareness has been turned to viability of wind powered 

turbines as a source of energy. World largest wind farm was 

completed and commissioned for use in United Kingdom. The 

wind farm in Thanet, located off the Kent coast is capable of 

generating 2 gigawatt (GW) of electricity annually. The 100 

turbines, each measuring more than 300 ft, will power more 

than 200,000 homes. It will increase the amount of energy 

generated from offshore wind in the UK by a third to 1,314 

MW, compared to 1,100 MW in the whole of the rest of the 

world (The Telegraph, 2010). Attention is now being directed 

toward power generation from a renewable source especially 

wind power.  
As of September 2010, the installed capacity of wind 

power in the United Kingdom was over 5 GW. Wind power 

is the second largest source of renewable energy  
 
 
 
*Corresponding author. E-mail: ayogas2003@yahoo.com. 

 
 
 

 
in the UK after biomass. Since most suitable locations for wind 

farm appears to be along the coast, knowledge of mean wind 

profile over the sea and adjacent coast is important. The study 

of wind profile for potential wind power is difficult to assess 

because only surface data at a height of about 10 m 

(reference height) is available. Thus there is a need to 

estimate the wind at sufficient heights for proper evaluation of 

wind power potential. According to Van et al. (1990) 

logarithmic relation can sufficiently describe wind profile over 

sea during adiabatic condition. However, when the sensible 

heat flux and latent heat flux are significantly different from 

zero, stability correction should be made. Such stability 

correction can be calculated using the diabatic method to 

account for change in temperature and moisture associated 

with sensible and latent heat flux. We compare potential 

energy generation using power law relationship and 

diabatic evaluation method to determine the suitability 

of each method for Nigerian coastal wind estimation. 
In this paper we demonstrate the suitability and 

potential of some coastal stations in Nigeria for wind 

energy production. This is motivated by the fact that 

there is no wind farm presently in Nigeria, at least, in 



 
 
 
 

Table 1. Power law exponent p value at various stability categories.  
 

 Stability category A B C D E F 

 z0  = 1 0.17 0.17 0.20 0.27 0.38 0.61 
        

 
 

 

commercial use. Therefore there is need to evaluate the 

potential of some locations to determine their suitability for 

wind power generation. 
 

 
DATA AND METHOD 
 
Monthly wind data over some coastal stations (Lagos, Calabar) 
constitute the major data for this study. 18 years data between 
1991 and 2008 were obtained from the archives of the Nigeria 
Meteorological Agency (NIMET) Oshodi Lagos. The wind speeds 
measured at the reference height of 10 m were used to calculate  

the wind speed uz at heights between 15 and 70 m at the interval 

of 5 m. The power law relationship is given as; 

  
z

2 p  
 

U z   
 

 

 

[1]  
 

U
1 z

1 

 
 

    
 

The exponent p of the power law varies with stability categories 
according to Irwin (1976b) as shown in Table 1; further explanation is 
given in Table 2 according to Turner (1994). Equation [1] was used to 
estimate wind speed from reference height of 10 to 70 m.  

On the other hand, to estimate wind speed using diabatic method, 

we start from the Monin – Obukhov (M-O) similarity theory which 

relates the mean gradient of wind speed, temperature and humidity to 

the universal function of dimensionless stability  
parameter z  L . The gradient functions are, as given by Large and 
Pond (1982); 
 

 kz 
   
U 

 m  z L [2] 
 

       
 

 u*   z  
 

 kz 
  
 

 t  z L 
 

 

     [3] 
 

*   z  
 

 kz 
 
q 

 q  z L [4] 
 

   
 

 q*  z  
  

 

where U ,  , q are the wind speed, the absolute temperature and 
 

absolute humidity respectively. The quantities u* , * and q* are 

friction velocity, temperature scale and humidity scale 

respectively. Absolute temperature profile is approximated by   

Tair  0.01z and L is given by; 

 
 

  u* 
2
 Tv 

L 
  

[5] 
 

kg 
 

 

 *v 
 

 

where Tv the absolute virtual temperature, g is the acceleration due  

to gravity and *v  is the virtual temperature scale. Integration of 
 
equations 2 to 4 gives the profile function for wind speed, 
temperature and humidity. For wind speed, the profile function 
can be written as; 

 

 u 
* 
  z     z  

 

   
  

 
 m 

 
 

 
 

 
 

U z  
  

 

 

[6] 
 

 ln      
 

 k  

z
0     L  

 

Von Karman constant (k = 0.40), z  and  z0 are the height of wind 
  

speed and roughness length respectively. The costal of Nigeria 
can be characterized as regularly covered with large obstacles 
with open spaces roughly equal to obstacle heights, sub – urban 
houses, village and mature forest. Following the Devenport –  

Wieringa roughness classification (Wieringa, 1981) z0 has been 

taken as 1.0 m. In the present case, it required to calculate the 

wind speed U 2 at a specific height z2 , given the wind speed U1 

at the height z1 , thus equation 6 can be rewritten as; 
 
 

        z2 
      z1 

 
 

U 
 U 

 
 

z2   
  

 
z1   

 
 

   

   

  

  
[7]  

 ln  

 

ln  

 

 

 2 1 

 

z 

0 

 
m

    L  

 

z 

0 

 
m

   L  
 

               
  

Where  m is the stream function given as, for unstable condition 

(L<0); 

 1 x 
  2 

1 
 

 

m  
1 x  

 x  2    [8] 
 

 2ln  
 

  

 2tan  

  ln 

2 

  
 

  2      
 

Where x  1 16z L1
 4     

  
 
For stable condition 
 

 m  5z  L
 
For simplicity, L values have been carefully chosen for unstable 
(L<-200) and stable (L>200) (Van et al., 1990) atmospheric 



  
 
 

 
Table 2. Pasquill – Gifford stability categories.  

 
Stability category Classification Natural phenomena Most likely occurrence  

Extremely 
A 

unstable 
 

Moderately 
B 

unstable 

 
C Slightly unstable 

 

D Neutral 

 

E Slightly stable 

 

F Moderately stable 

 
 
Strongly thermal instability 
 

 
Transitional periods, moderate mixing 

 

Transitional periods, slight mixing 

 

Strong winds, overcast day/night transitions 

 

Transitional periods, night time, moderate winds 

 
Clear night-time skies, very limited vertical mixing, 
plume planning and meandering  

  
Late morning to mid afternoon in 
spring and summer 

 

Dry time transitions, all year 

 

Day time transitions, all year 

 
Day time, cloudy; high winds; day 
time transitions, all year 

 
Night-time transition, all year 

 

Night, clear skies, light winds, all year 

 

 
conditions and then, equation 7 was used to construct while in August and September it is down to 75 mm (3 

 

diabatic wind profile from 10 to 70 m at interval of 5 m. The inches) and in January as low as 35 mm (1.5 inches). The 
 

wind power relation was obtained as, (Stull, 2000); main dry season is accompanied by harmattan winds from 
 

      the Sahara Desert, which between December and early 
 

P  1 U 
3
 

  February can be quite strong. The average temperature in 
 

 [9] January is 27°C (79°F) and for July it is 25°C (77° F). On  
   

2     average  the  hottest  month  is  March;  with  a  mean 
 

      temperature of 29°C (84°F); while July is the coole st month 
 

where P ,   and  U are respectively  wind power,  air 
(BBC, 2010).  

 

Calabar is similar to the Lagos in terms of the climate,  
density  and  wind  speed.  Wind  energy  potential  was 

 

during the winter months of November to March, which are 
 

computed by integrating estimated power using trapezoidal usually referred to as the dry season in Nigeria, there could 
 

method.    be occurrence of harmattan dust haze in Calabar but the 
 

      frequency is very low. This means that winds over Calabar 
 

Climate of the study area 
  are  predominantly  south  –  westerly.  In  Summer,  (wet 

 

  season), the patterns of precipitation are typical of the 
 

Lagos  has  a tropical savanna  climate (Köppen climat e 
equatorial zone (Adefolalu, 1984).  

 

  
 

classification  Aw)  that  is  similar  to  that  of  the  rest  of   
 

southern Nigeria. There are two rainy seasons, with the RESULTS  
 

heaviest rains falling from April to July and a weaker rainy   
 

season  in October  and  November.  There is  a  brief 
Wind speed – height structure 

 
 

relatively dry spell in August and September and a longer  
 

  
 

dry  season  from  December  to  March.  Monthly  rainfall 
It is important to state here that the focus of this 

 

between May and July averages over 300 mm (12 in), 
 

 

 

study is on the two extremes of stability category 

for easy comparison between the diabatic and 

power law methods; hence we will not duel on other 

stability categories that transit between the 

extremes (Table 2).  
Wind speeds with heights were estimated using 

the power law relationship for extremely unstable 

and moderately stable conditions as presented in 

Figure 1.  
These two conditions were estimated from 

average monthly wind speeds between 1991 and 

2008 at reference height of 10 m, thus the wind 

speed converges at this height. Under the stability 

category F (moderately stable), estimated wind 

speeds over Lagos increased up to 21 m/s at 

height 70 m whereas in the category A (extremely 

unstable) wind speeds at the same height was just 

about 8 m/s. greater wind speeds are best 

achieved under the category A stability criterion, 

this condition is prevalent in the night time. Over 

Calabar, greater wind speeds estimate was also 



 
 
 

 

 20 
 

 18 
 

(m
/s

) 16 
 

14  
 

 

S
p

e
e
d

 

12 
 

10  
 

 

W
in

d
 

8 
 

6  
 

 

 4 
  

 
2 

 
0        Jan Fe b M ar  Apr  M ay Jun  Jul  Aug Se p Oct Nov De c 

 
M onth 

 

 18 
 

 16 
 

(m
/s

) 14 
 

12  

Sp
ee

d  

10  
 

 

W
in

d
 

8 
 

6  
 

  
 

4 
 

2 
 

0 
 

Jan Feb Mar  Apr  May Jun Jul Aug Sep Oct Nov 
Dec 

 

Month 

 
 
 
 
 
 
 
 

 

 Unstable  
 
 
 
 
 
 
 
 
 

 

 Stable  
 
 
 
 
 
 
 
 

 

 Unstable 
 
 
 
 
 
 
 
 
 

 

 Stable 

 

 
Figure 1. Variation of calculated mean monthly wind speeds in Lagos (upper panel) and Calabar (lower 
panel) using power law relationship. 

 

 

achieved under the category F stability classification, 

however, the wind speeds estimated were lower than the 

values obtained over Lagos. Thus, Lagos is generally 

windier than Calabar based on the 18 years of data 

considered for this study.  
The diabatic estimation for both stable and unstable 

atmospheric condition over Lagos shows that wind speeds 

increased with height up to 18 m/s for stable condition at 

height of 70 m and up to 15 m/s for unstable condition, 

which is similar to the wind – height structure obtained over 

Calabar (Figure 2), however, wind values 

 
 

 

over Calabar are lower than values over Lagos. The value 

for the stable condition using diabatic method is lower than 

the value obtained from power law. In diabatic method a 

number of parameters were included in the estimation of 

wind speeds such as the roughness length, which puts into 

consideration the actual features (obstacles, building) of 

the site that are capable of obstructing free flow of wind. 

Since power law does not include this consideration, the 

estimation from power law is unrealistically high especially 

in stable conditions. Thus for estimate of wind speed in 

stable conditions, diabatic 



                                                  
 

 

12 

 
 

   
 

    
 

(m
/s

) 10 

    

Stable 

 
 

        
 

 

          
 

          
 

            
 

8 

                        
 

                         
 

S
p

ee
d
 

6 
                           

 

W
in

d
                            

 

4 
                           

 

                            
 

 
2 
                          

Unstable 

 
 

                            
 

                           
 

 0                            
 

   

Jan  Fe b  M ar  Apr  M ay Jun  Jul Aug  Se p  Oct  Nov  Dec 

  
 

      
 

                         M onth                         
 

 
10 

   
 

   
 

9     
 

(m
/s

) 

8 

                    

Stable 

 
 

                       
 

 7 
                            

 

                            
 

S
p

ee
d

 

6 
                           

 

                          
 

5 
                           

 

                           
 

W
in

d
 

4 
                           

 

                          
 

3 
                           

 

                           
 

 
2 

                           
 

                           
 

 
1 

                           
 

                           
 

0                           
Unstable 

 
 

  
  

Jan  Feb Mar  Apr  May Jun Jul Aug Sep  Oct Nov Dec 
 

Month 

 
Figure 2. Variation of calculated mean monthly wind speeds in Lagos (upper panel) and Calabar (lower 
panel) using diabatic method. 

 
 
 
method provides a better approximation. 
 

 
Seasonal characteristics of wind speed at height 70 m 

 
The most effective wind in terms of energy generation is 

the wind located at the height of the turbine blades. For 

this investigational purpose, the height 70 m is considered 

as this is the average height of turbine blade in most of 

commercial wind farms (ICREED, 2006), 80 m is the 

current industry norm which is based on wind turbines at 

70 m. In Figure 3 the seasonal variation of wind at height 

70 m is presented. Over Lagos, wind 

 
 

 

speeds estimated using the power law depict a wide 

difference between unstable and stable conditions. Wind 

speeds are always higher in stable condition than unstable. 

The observation over Calabar is similar to that obtained 

over Lagos. However, using the diabatic method, the 

difference between wind speeds estimate under the stable 

and unstable conditions was not much. The wide 

difference in the case of power law may have been due to 

weakness inherent in the method (for example, it does not 

include the effect of building and other friction – causing 

obstacles). Despite the shortcomings, the method has 

shown that there are stronger wind speeds during the 

stable condition than unstable condition. 



  
 
 

 
 

18000 
     Stable 

 

      
Unstable 

 

       
 

 16000       
 

 14000       
 

(J
o

u
le

s
) 

12000       
 

10000       
 

       
 

E
n

e
rg

y
 

8000       
 

6000       
 

       
 

 4000       
 

 2000       
 

 0       
 

 
Jan 

r y 
Jul 

 
ep ov  

 a 
Ma 

 
 

 M  S N 
 

    M onth    
 

 
10000 

     Stable 
 

      
Unstable 

 

       
 

 9000       
 

(J
o

u
le

) 8000       
 

7000 
      

 

E
n

e
rg

y
       

 

6000       
 

 5000       
 

 4000       
 

 
Jan Mar M l S p Nov  

 u  

   y   
 

   a J e  
 

    M onth    
  

 
Figure 3. Variation of mean monthly energy for Lagos (upper panel) and 
Calabar (lower panel). Maximum energy occurs in August and March in 
Lagos and Calabar respectively. 

 
 
 
Diabatic method also revealed similar deduction. Stronger 

wind speeds occur during the stable condition due to the 

thermal stratification of the atmosphere. A statically stable 

atmosphere will offer less friction and enhance wind 

speeds than unstable, mixed atmosphere. Since stable 

condition often occur in the night, it is envisaged that more 

power will be generated from the wind turbine during the 

night.  
The seasonal variation of wind speed at 70 m over 

Lagos using both methods shows a generally increasing 

speed from January to April. It decreases thereafter to 

December except in August when there was slight 

increase. This pattern was followed over Calabar. The 

months of March and April, when wind speeds were 

 
 

 

highest are months of transition between the dry and the 

wet season over the coastal stations, which are usually 

characterised by strong winds. As soon as the wet season 

starts properly, weak winds take over. This explains the 

seasonal characteristics of the wind speeds as noted 

earlier. Thus power generation will peak during the months 

of March and April. The August slight increase in wind 

speed may be due to the characteristic of ‘little dry season’ 

that (usually) occurs during the month. Comparing 

seasonal wind estimation from both power law and diabatic 

methods, it is observed that power law method slightly 

overestimate wind speeds.  
This can be understood from the fact that power law 

does not consider the friction effects usually offer to wind 



  
 
 

 
Table 3. Power generation stations in Nigeria showing the peak and off peak supply. 
Note that there is no wind turbine.  

 
Station Turbine Peak gen (MW) Off peak gen (MW) 

Kainji Hydro 237 204 

Jebba Hydro 435 368 

Shiroro Hydro 408 - 

Egbin Steam 850 785 

Trans Amadi Gas - 20.1 

A.E.S Gas 250 249.3 

Sapele Steam 138 144 

Ibom Gas 81.6 4.3 

Okapi Gas 425 380 

Afam 1-5 Gas 59 60 

Afam VI Gas 299 302 

Delta Gas 200 205 

Geregu Gas 387 260 

Omoku Gas 40.2 12.1 

Omotosho Gas 25.2 25.2 

Olorunsogo phase I Gas 42.3 20.3 

Olorunsogo phase II Gas - 121.6 

Total  3877.4 3160.9 
 

Source: National Mirror, 13 April, 2011. 
 

 

speed by building and trees. For example, over Lagos in 

August, power law estimated a wind speed of about 18 m/s 

where in the same month, using diabatic method, the wind 

speed was about 11 m/s. this can be misleading especially 

when deciding the specification of wind turbine needed at 

these sites. Thus, correct estimation is better done using 

the diabatic method. 
 
 
Monthly pattern of wind energy potential over the 

stations 

 
Accurate estimation of wind speeds at the desired heights 

can help in forecasting the likelihood of power generation 

from a wind farm. Using the estimated wind speed at 70 m, 
expected energy output for Lagos and Calabar are shown 

in Figure 3. The energy outputs for both stations were 

calculated from the wind estimated using diabatic method 

only (for obvious reason). Following the monthly gradual 

increase in wind speeds from January to April, the energy 

potential of the wind speeds also increases in both 

stations. However, the drop in energy potential in June / 

July was shaper over Calabar than Lagos, suggesting that 

within these months energy realisation in a potential wind 

farm located in Lagos will be more than in Calabar. The 

highest peak of energy generation from wind over Lagos 

occurs in August at about 16000 Joules under stable 

condition. The peak energy reduces to about 14000 Joules 

under unstable condition. Over Calabar the peak energy 

occurs in February / March amounting to about 9000 and 

8000 

 
 

 

Joules under stable and unstable conditions respectively. 
 

 
DISCUSSION 

 
The nation’s power generation hit 4,000 mega watts (MW) 

at the beginning of 2011 according to the data released by 
the Power Holding Company of Nigeria (PHCN) in the first 

quarter of the year, power generation increased from 3,800 

MW to 4,000 MW. The improvement according to the data 

was achieved as a result of increased water level of hydro-

electric power stations located at Kainji, Jebba and Shiroro 

(National Mirror, 2011). The commencement of operation 

by the Independent Power Plant (IPP) stations over some 

new locations contributed to the improvement recorded 

during the period (National Mirror, 2011). Despite this 

improvement, power supply in Nigeria remains epileptic as 

there are no 24 h uninterrupted power supply, even to 

industrial areas. It is noted from Table 3 that there is yet no 

wind power harnessed for the purpose of generating 

electricity in Nigeria. A unit turbine will produce at least 

191.11 kW of electricity per hour, in the coastal stations of 

Lagos and Calabar, the average wind speed is about 9.0 
m/s at 70 m, which translate to 478 kW of electricity at 100 

% efficiency, if power is cube of wind speed. Assume the 

wind turbine is operating at 40% efficiency; a wind farm of 

5,000 units will generate about 995 MW. Having at least 

five wind farms will increase the supply by at least 4,775 

MW, which is more than what all existing sources in 

Nigeria are generating (Table 3). 



 
 
 

 

It is important to consider another source of power 

generation to meet the demand for electricity supply. Wind 

energy, which remains hitherto untapped, appears 

promising in solving the problem of electricity shortage. 

Apparently, wind energy potential is exploitable in Nigeria, 

along the costal towns where stronger wind speeds are 

sufficiently available throughout the year.  
Analysis presented in this study showed that night time 

stable condition produces stronger wind speeds. At night 

time, or when the atmosphere becomes stable, wind speed 

close to the ground usually subsides whereas at turbine 

hub altitude it does not decrease that much or may even 

increase. As a result the wind speed is higher and a 

turbine will produce more power than expected from the 

1/7th power law: doubling the altitude may increase wind 

speed by 20 to 60%. A stable atmosphere is caused by 

radiative cooling of the surface and is common in a 

temperate climate: it usually occurs when there is a (partly) 

clear sky at night. When the (high altitude) wind is strong 

(a 10 m (33 ft) wind speed higher than approximately 6 to 7 

m/s (20 to 23 ft/s)) the stable atmosphere is disrupted 

because of friction turbulence and the atmosphere will turn 

neutral. A daytime atmosphere is either neutral (no net 

radiation; usually with strong winds and/or heavy clouding) 

or unstable (rising air because of ground heating — by the 

sun) . Here again the 1/7th power law applies or is at least 

a good approximation of the wind profile. Indiana (USA) 

had been rated as having a wind capacity of 30,000 MW, 

but by raising the expected turbine height from 50 m to 70 

m, the wind capacity estimate was raised to 40,000 MW, 

and could be double that at 100 m. 
 
 

 
Conclusion 

 

Two methods (power law relationship and diabatic) have 

been used to determine the wind energy potential of two 

stations located along the coast of Nigeria. The coastal 

areas are usually windy and they provide suitable location 

for wind farm. Comparing the two methods, wind speeds 

estimated from diabatic method for both stable and 

unstable atmospheric conditions appear to be more 

accurate due to certain physical condition built into the 

method. For example, diabatic method which considered 

the effects of building and obstacles that offer resistance to 

wind is more realistic than power law which makes no 

assumption about physical appearance of potential wind 

farm locations. Furthermore, power law relationship shows 

a wider deviation from reality under unstable atmospheric 

condition. These unavoidable weaknesses in power law 

may lead to erroneous energy calculations. Thus, diabatic 

method of wind speed estimation is suitable when in situ 

measurements are not available at the desired heights. 

 
 
 
 

 

Analysis in this study has shown that Nigerian coastal 

stations are good potential areas for wind farms. The 

coastal stations have an average wind speed of 9 m/s are 

capable of generating about 995 MW of electricity in a 

single farm of 5,000 unit of wind turbine. Five such farms 

will produce as much as the present power generation in 

Nigeria with all source put together. This alone puts wind 

potential energy in a good position in solving the problem 

of inadequate supply of electricity currently facing the 

country. 
 

 
ACKNOWLEDGEMENT 

 
Authors wish to thank the Nigerian Meteorological Agency 

(NIMET) for providing the needed data. 
 
 
REFERENCES 
 
Adefolalu DO (1984). Weather hazards in Calabar – Nigeria. Geol. J., 9:  

359-368. 
ICREED (2006) Indiana's Renewable Energy Resources. 

http://www.indiana cleanpower. org/renewableresources.html. 
Irwin JS (1979b). A theoretical variation of the wind profile power law 

exponent as a function of surface roughness and stability. Atmos. 
Environ., 13: 191-194  

National Mirror (2011). Power generation peaks at 3,877.4 MW. 
Article by Udeme Akpan. Accessed 13, April 2011, pp. 35 - 36.  

Stull R (2000). MeteorologyToday for Scientists and Engineers. 2nd ed.  
Brooks/Cole Thompson Learning, 502 p.  

Telegraph (2010). World's largest offshore wind farm opens off Kent. 

Article by Louise Gray, Environment Correspondent 7:00AM BST 23  
Sep 2010. 
http://www.telegraph.co.uk/earth/earthnews/8018828/Worlds-
largest-offshore-wind-farm-opens-off-Kent.html.  

Turner DB (1994). Workbook of Atmospheric Dispersion Estimates: 
An Introduction to Dispersion Modeling, 2nd Edition, CRC Press, 
London.  

Van AJM, Beljaars ACM, Holtslag AAM, Turkenburg WC (1990). 
Evaluation of stability corrections in the wind speed profiles over 
the north sea. J. Wind Eng. Ind. Aerodyn., 33: 551–566. 

Weather Centre - World Weather - Average Conditions - Lagos". BBC. 
(2010).  
http://www.bbc.co.uk/weather/world/city_guides/city.shtml?tt=TT0005  
10. Retrieved 2010-06-02.  

Weiringa J (1981). Estimation of mesoscale and local scale 
roughness for atmospheric transport modeling. Proceedings from 

the 11
th

 international conference on air pollution modeling and its 
application, November, 1980, Amsterdam, Netherlands, plenum 
press, New York, pp. 279–295. 


