Scholarly works
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Item Assessing Wildfire Occurrence in West Africa with Atmospheric Co₂ Removal(2025-06) Uzoma E.K.; Otunla T. A.; Nymphas E. F.; Ogunsola O. E.; Adeniyi M. O.The increase in wildfire occurrence is one of the consequences of the recent global temperature rise. Understanding wildfire occurrence in West Africa under atmospheric carbon dioxide removal is significant because of its implications on climate systems, ecosystems, agriculture, and socioeconomic development. This study projected the impacts of atmospheric carbon dioxide removal on fire occurrence in West Africa by analyzing the CNRM ESM1 C1 model output for the Carbon Dioxide Removal Model Inter-comparison Project (CDRMIP). Four climatological periods–1990–2019 (reference period), 2040 – 2069, 2070–2099 and 2100-2129 were analyzed using four fire indices. The periods 2040–2069, 2070–2099, and 2100–2129 have 42%, 45.9%, and 49.4% of “No Fire” category among other categories, respectively, with the Lebanese Index. With Mark 4 Grassland Fire Danger Index, a low category of fire risk is also predominant at 95.6%, 96.4%, and 66.1% for 2040–2069, 2070–2099, and 2100–2129, respectively. None of the indices projected a case of high, very high, or extreme risk in any period. “Low risk” category is predominant with all indices, particularly in Cote D’Ivoire, Ghana, Burkina Faso, Togo, Benin, and Nigeria. The low-risk category for fire occurrence during carbon dioxide removal in West Africa suggests a favorable outcome for the region’s ecosystems, agriculture, and communities. The study highlights the potential benefits of CDR beyond carbon removal, such as enhanced resilience, sustained productivity, and reduced vulnerability to climate-induced hazards like wildfires.Item Wind Characteristics and Potentials of Two-Parameter Weibull Distribution and Maximum Entropy-Based Distribution Functions at an Equatorial Location(2022) Otunla, T.A.; Umoren A. K.Thorough knowledge of the wind characteristics and variations are of great importance in the development of wind energy resource in any location. This study examines the wind characteristics and assess the potential of two distribution functions in a low wind equatorial region of West Africa. High resolution wind speed and direction data were obtained from a site in Nsukka, a location chosen in the region of study. Diurnal, seasonal and annual variations of both the wind speed and directions were examined. The potentials of two-parameter Weibull distribution and another distribution function based on Maximum Entropy principle (MEP) were assessed using R2 and root mean squared error (RMSE). The results indicated that day-time is windier than night-time. The transitions months of February, March and April have the highest wind speed. The dry season has greater energy potential than rainy season. The predominant wind direction lay within the sectors: South-South-West and East. The predominant wind sector for February, March and April is South-East. The R2 for daily, sub-seasonal day-time and night-time, monthly, and annual ranged between 0.90 and 0.99 for both MEP-based and Weibull distributions. The daily, sub-seasonal day-time and night-time, monthly, and annual RMSE also ranged between 0.011 to 0.075 for MEP-based and Weibull distribution respectively. Thus, both MEP-based and Weibull two-parameter distribution functions can be used to model wind data at the location of study.Item "Evaluation of soil thermal diffusivity algorithms at two equatorial sites in West Africa"(2021) Otunla, T.A.; Oladiran, E. O.This study presents comparisons between six algorithms used in the calculation of apparent thermal diffusivity (Kh ) of the topsoil during measurement campaigns conducted at two equatorial sites. It further investigates the effects of transient and seasonal variations in soil moisture content (i) on the estimation of Kh. The data used comprise soil temperatures (T) measured at depths of 0.05 m and 0.10 m, and i within the period of transition from the dry season to the wet season at Ile Ife (7.55° N, 4.55° E), and for the peak of the wet season at Ibadan (7.44° N, 3.90° E). The thermal diffusivity, Kh, was calculated from six algorithms, of: harmonic, arctangent, logarithmic, amplitude, phase, and conduction-convection. The reliability of these algorithms was tested using their values to model T at a depth of 0.10 m, where direct measurements were available. The algorithms were further evaluated with statistical indices, including the empirical probability distribution function of the differences between the measured and modeled temperatures (DT). The maximum absolute values of DT for the six algorithms investigated were: 0.5°C, 0.5°C, 0.5°C, 1°C, 1°C and 1°C, respectively. Kh showed an increasing trend as i increased from the dry season to the peak of the wet season, with R2 = 0.70 for the harmonic algorithm. The accuracy of all of the algorithms in modeling T reduced with transient variations of i. The harmonic, arctangent and logarithmic algorithms were the most appropriate for calculating Kh for the region of study. The empirical relation between i and Kh and the values of Kh obtained in this study can be used to improve the accuracy of meteorological and hydrological models.Item Estimation of daily solar radiation at equatorial region of West Africa using a more generalized Angström‑based broadband hybrid model(2020) Otunla, T.A.A well-calibrated simple and economical viable Ȧngström–Prescott model has long been accepted to be more accurate than other surface meteorological data-based models. The major limitation is that it is site dependent. This study exploited the appropriateness of a more generalized Ȧngström-based broadband hybrid model in the estimation of solar radiation at seven stations in equatorial region of West Africa. This model features parametric equations that explicitly and accurately account for clear-sky damping processes in the atmosphere. It empirically estimates cloudy sky radiation extinctions using relative sunshine duration. A new cloud transmittance calibration curve that followed the cloud cover patterns of the region of study was also tried. The result indicated that the new cloud transmittance could be unique to equatorial region of West Africa. The performance of the hybrid model, after modification using the new cloud transmittance equation, was tested using mean bias error and root mean squared error. The performance was found to be comparable to the site-dependent, locally calibrated, Ȧngström–Prescott model at the calibration stations, and even better at validation stations. The same performance test comparisons with the original version of the hybrid model, and four other site-independent models: globally calibrated, FAO-recommended Ȧngström–Prescott models, Hay and Gopinathan models indicated the modified version of the hybrid model as betterItem "Assessment of Wind Speed Distributions and Turbine Characteristics in Equatorial West Africa"(2026-03) Otunla, T.A.Wind nullity, low wind, and bi- or multi-modality are common characteristics at high temporal resolution, especially in Equatorial regions. The traditional two-parameter Weibull (Weibull) distribution function (DF) is not designed to capture such peculiarities. Hourly mean wind speed data for eight locations that cut across different climate zones in an Equatorial region of West Africa have been analyzed using Weibull and Maximum Entropy Principle-based (MEP) distribution functions (DFs). Wind characteristics, such as power density, null wind speed, and modal distributions, together with turbine efficiency, capacity, and availability factors, were also assessed at a wind turbine hub height of 73 m using standard statistical tools. The results indicated that null wind speed and/or bimodality were present in the wind distributions at Abuja, Akure, Akungba, Nsukka, Makurdi, and Yola. The results of the assessments of the two DFs show that the MEP DF generated much better results across all time scales (R2: 0.83 - 0.98; RMSE: 0.0037 - 0.0109 m/s2) than the Weibull DF (R2: 0.47 - 0.98; RMSE: 0.0038 - 0.0191 m/s2), especially for locations where null wind speed and bimodality were prominent in the wind data distribution. MEP DF results further indicated that annual and rainy season periods were better modeled than the dry season in all the locations. The overall effect of all the turbine characteristics on annual and seasonal scales is that sufficient winds were available (Availability factor: 0.733 - 0.97; Capacity factor: 0.350 - 0.778) at the rated power for energy production in all the climate zones.Item Assessment of Air Quality Conditions in an Area in the Gulf of Guinea, Ibadan, Using Low-Cost Sensors(2025) Otunla, T.A.Air quality monitoring is essential for the determination of the potentialnegative impacts of air pollution on humans and the environment. This study investigated the contribution of particulate matter (PM 2.5 and 10) to air quality in an area in the Gulf of Guinea, far south of Sahara. The study used the hourly data of PM 2.5 and 10 concentrations and other auxiliary data in 2021 from the PurpleAir sensors. These PM concentration data were first converted into Air Quality Index (AQI) using appropriate method of aggregation. Subsequently, the AQI was used to categorize the ambient air into six classes that range between “Good" to "Severe" conditions. Results indicated higher prevalence of "Good “to “Satisfactory" AQI conditions during the peak of the rainy season (June, July and August), characterized by low PM concentrations, whereas the harmattan season (December, January and February) exhibited a higher prevalence of "Very Poor" to "Severe" conditions, characterized by high PM concentrations. High AQI and PM concentrations were attributable to organic PM Saharan dust in the harmattan season, while low AQI and PM concentrations in the rainy season were associated with localized anthropogenic sources. Thus, the low-cost sensor PurpleAir was able to capture the expected seasonal patterns peculiar to the study region.Item Worst month rain rate characterization for line-of-sight link performance in tropical locations(2021) Osita, I.; Nymphas,E.F.Communication equipment operating in the 30 to 300GHz frequencies avails large bandwidth and high speed data transmission but suffers greatly from attenuation by rain. The design of radio communication equipment has been based on predicted rain rate from the International Telecommunication Union-Radio (ITU-R) recommendations. This equipment fails in the tropics due to the differences in tropical and temperate rainfall structure on which the ITU-R recommendation is based. Five minutes rainfall data from two tropical locations in Nigeria – Jos (9.93 oN, 8.89oE, 1280 m) and Minna (9.61 oN, 6.56 oE, 223 m) were analysed. The 1- minute and ITU-R predicted rain rate (RR) were obtained with the Lavergnat and Gole model and MatLab rain rate statistics respectively while the logarithmic scale was used to convert the RR to exceedance time percentages (0.001 to 1%). The two parameter conversion factors, Q1 and β were generated with the ITU-R P. 841-6 recommendation; these were compared with the conversion factors recommended by ITU-R for global rain rate application. The results showed that at 0.01% exceedance, the ITU-R predicted rain rate for Jos and Minna were 87.1mm/hr and 91.6mm/hr respectively while the estimated rain rate from these locations were 84.5mm/hr and 110.0mm/hr respectively. The ITU-R conversion factor for the computation of the mean annual worst month from mean annual rain rate percentage exceedence were Q1 = 2.83 and β = - 0.15 while these parameters at Jos is, Q1 = 3.17 and β = - 0.19 and at Minna, Q1 = 3.12 and β = - 0.18. The results showed that there is a very strong relationship between the distribution of rain rate in the worst month and the annual rain rate distribution with coefficient of determination of 0.9994 and 0.9984 respectively. Thus for optimum link design budgeting, the modified values of Q and β should be adopted in these locations in order to enhance radio equipment performance in Nigeria.Item Characterization of tropical rainfall structure for some selected locations in Nigeria(2021) Osita, I.; Nymphas,E.F.Rainfall rate for any location is required for rain attenuation modeling for the region of interest. The characteristics of tropical rainfall structure in Nigeria have been investigated. The data was collected from the Tropical Data Acquisition network (TRODAN) set up by the Center for Atmospheric Research (CAR) in Nigeria. The rainfall rates were measured at 5-minutes integration time. The results were then compared with those predicted by the ITU-R model, and those from other tropical locations. The results revealed that the ITU-R model performs best only in the Southern Guinea Savannah (SGS) region of the country. In other geographical locations, the ITU-R model either under-estimates or over-estimates rainfall rates. The Cumulative Distribution Functions (CDFs) at the 0.01% time of exceedence showed that the percentage difference in the measured rain rate and the ITU-R estimates varied from a minimum of 4.89% in SGS to a maximum of 22.93% in the Derived Savannah (DS). At the 0.001% of time, these differences varied from a minimum of 11.90% to a maximum of 38.80% in these respective regions. These results and others from the tropics suggest the need for the modification of the ITU-R model for predicting rain attenuation in the tropical region to take into account the peculiar characteristics of rainfall in the region.Item Comparison analyses of different models used to determine soil thermal conductivity and diffusivity at nimex site, Ibadan(2021) Nwaokoro,E.; Nymphas,E.F.Soil thermal properties regulate the separation of energy fluxes at the ground surface and they control the exchange of energy and mass between the soil and the atmosphere. The knowledge of these properties is needed in order to ascertain the heat flux distribution in the soil under steady and non-steady conditions. In this study, which lasted for 11 months starting from March 2006 to January 2007, we estimated soil thermal conductivity and thermal diffusivity at Nigeria Mesoscale Experiment (NIMEX) site, Ibadan using Johansen and Kersten models and Horton Numerical method. The aim of this work is to compare the results obtained from these models and to ascertain the level of agreement of the results. The result showed that for Johansen and Kersten models, the highest mean values of thermal conductivity and thermal diffusivity were obtained in the month of September 2006. For Johansen model the values are 4.18±0.08 Wm-1K-1 and 4.56±5.57*10-8m2s-1 for thermal conductivity and thermal diffusivity respectively and for Kersten model the thermal conductivity and thermal diffusivity values are 1.00±0.05 Wm-1K-1 and 1.07±0.22*10-8 m2s-1 respectively. This may be due to the observed increase in the soil moisture content within this month. The result obtained using Horton Numerical method showed that the highest mean thermal conductivity and thermal diffusivity values of 9.76 ±3.00 Wm-1K-1 and 10.70±3.30*10-8m2s-1 respectively were obtained in the month of December 2006 while the lowest mean values of -0.44 ±14.68 Wm-1K-1 for thermal conductivity and 0.10±12.70*10-8m2s-1 for thermal diffusivity were obtained in the month of September contrary to the results obtained with the first two models. The negative mean thermal conductivity value of -0.44 ±14.68 Wm-1K-1 obtained in the month of September 2006 using Horton Numerical method was probably due to the increase in soil moisture content which is as a result of increase in the amount of rainfall within this month that lowered the temperature at the near soil surfaces. Kersten model is in agreement with Johansen model but has low values making it unsuitable for very low soil moisture. Johansen model is likely the best model for estimating thermal conductivity and diffusivity.Item An artificial neural network estimation of global solar radiation at Ibadan, Nigeria using meteorological data(2020) Nymphas, E.F.; Udomboso, C.G.This paper estimates global solar radiation (Rs) from routinely measured meteorological parameters in the city of Ibadan, Nigeria, using artificial neural network method. Six combinations were used to estimate Rs namely (i) daily mean air temperature (T) and day of the year as inputs and global solar radiation as output, ((ii) daily mean relative humidity (RH) and day of the year as inputs and Rs as output (iii) daily mean T, daily mean RH and day of the year as inputs and Rs as output (iv) daily mean minimum relative humidity (RHmin) and day of the year as inputs and Rs as output, (v) daily mean minimum temperature (Tmin), daily RHmin and day of the year as inputs and Rs as output (vi) daily mean maximum temperature (Tmax), daily mean Tmin, daily mean RHmin, daily maximum relative humidity (RHmax) and day of the year as inputs and Rs as output. The neural network was trained with 3653 measured data between 1995 and 2004 and tested with data for 731 days between 2003 and 2004. The data for testing the neural network were not used for the training. The results obtained showed that the combination of RHmin, RHmax and day of the year gave the best estimate of Rs with MSE of 3.4124. This is followed by RHmin and day of the year with MSE of 3.4424. Daily mean air temperature and day of the year could not mimic the measured Rs; it gave MSE of 5.3345. It is concluded that Rs can be estimated for locations where only temperature and relative humidity data are available.