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Time series analysis is a useful statistical tool in the assessment of climate variability and climate change. This study applied a time series analysis to rainfall and temperature data in the Bayelsa State of Nigeria. Since NIMET has only one gauging station in the state, Climate Research (CRU 0.5x 0.5) gridded data for 28 locations from 1956 to 2016 were used. They were sorted, validated with NiMet data, and utilized for analyses of various time series techniques such as Mann-Kendal, Spearman's Rho, Linear Regression, Thei-Sen Slope Cumulative sum, Cumulative Deviation, Rank Sum, Student's (t-test) and spectral analysis. The results obtained revealed that there had been increasing temperature and abrupt climatic changes in the state, especially in the 1976-1985 decade, with 1980 as the most probable year of abrupt change. The hottest decade was 1986-1995, with an average temperature change of 0.14856 °C /decade, while the coolest decade was 1976-1985 with an average Temperature change of -0.01723 °C /decade. Also, there had been some changes in rainfall, with the wettest decade occurring in 1986-1995 with an average rainfall change of 61 mm/decade, while the driest decade occurred in 1976-1985 with an average rainfall change of 14.08 mm/decade. The output of spectral analysis showed that the most Significant Periodicity for Rainfall and Temperature was 15 years. The result further revealed that there was high rainfall variability with a coefficient of variability of 62.74%. These rainfall fluctuations have implications for coastal flooding, quality, and quantity of available groundwater in the state. These results are useful to planners and policymakers in creating awareness of climate change's impact on rainfall in the study area. [ABSTRACT FROM AUTHOR]

This work investigated the performance of locally available brewer's spent grain (BSG) as an adsorbent for the removal of Fe (III) from aqueous solution. The brewer's spent grain (BSG) was collected, processed and characterized using scanning electron microscope (SEM) and X-ray fluorescence (XRF) to assess its potential for the removal of Fe (III). Thereafter, batch adsorption technique was employed to evaluate the effects of adsorption variables such as pH, initial metal ion concentration, adsorbent dosage and contact time on the sorption efficiency of BSG. The maximum adsorption time was fixed at 120minutes with a stirring speed of 100rpm. Experimental data obtained were then analyzed using selected isotherms and kinetic models such as Langmuir isotherm, Freundlich isotherm, Pseudo-First order and Pseudo-Second order kinetic models. SEM result revealed the presence of microporous structure within the surface of BSG thus making it a good candidate for metal ion removal. Based on the linear coefficient of determination (r2), it was observed that the experimental data fitted well with the Langmuir isotherm model (r2 = 0.9940 for raw BSG and 0.9946 for the treated BSG). In addition, the reaction mechanism that accompanies the adsorption of Fe (III) unto BSG was best described by the pseudo-second order kinetic model (r2 = 0.9823 for raw BSG and 0.981 for the treated BSG). Finally, maximum adsorption efficiencies of 66% and 77% were obtained for both the raw and treated BSG for optimum adsorption time of 120 minutes, pH 8.0 and adsorbent dose of 1.0g/50ml solution. [ABSTRACT FROM AUTHOR]

The flood frequency analysis of River Okhuwan at Ugonoba site in Benin Owena River Basin in Nigeria was carried out using annual maximum stream flow series for 20 years (1989-2008). The objective of the study was to determine the best fit probability distribution model applicable to the site from amongst three selected 3-parameter distribution models namely: Generalized Extreme Value distribution (GEV), Generalized Logistic distribution (GLO) and Generalized Pareto distribution (GPA) whose parameters were estimated by the method of L-moments. The best fit distribution was selected based on result of four goodness-of-fit tests applied to the candidate distributions. The results indicate that GPA is the best fit distribution model for analyzing the annual maximum flood series at the study site for return period less than or equal to 25 years but for return periods between 25 years and 200 years, GLO or GEV is recommended in that order. [ABSTRACT FROM AUTHOR]

The high cost, adverse effects on the environment and low efficiencies of the physical, chemical and thermal techniques currently being used to remediate hydrocarbon contaminated soils calls for evaluation of plant based methods. In this work, phytoremediation study was made with laterite soil artificially contaminated with motor oil. Three replicates of 3 kg of the air dried soil fertilized with 10% (w/w) organic fertilizer were each contaminated with 200ml of motor oil thoroughly mixed and placed in a 35 cm high plastic bowl. Six young plants of sweet potato were transplanted to each of the plastic bowl and allowed eight weeks to grow and stabilize. Hydrocarbon removal from the soil in the presence of the plant species were measured at two weekly intervals for a period of 16 weeks. Our results indicate that sweet potato plant (Ipomoea batatas) can grow, sustain growth and survive in the contaminated soil environment; the plant reduced the initial TPH content in the soil from 75.46mg/g to 19.876mg/g in 16 weeks. It is predicted that it will take about 27 weeks to reduce the TPH content to zero. The study concluded that sweet potato plant (Ipomoea batatas) has potential phytoremediation application in remediating hydrocarbon contaminated soils. [ABSTRACT FROM AUTHOR]

Regional flood frequency analysis was conducted for catchments within Upper Benue river basin in Nigeria using the Index flood (IF) procedure utilizing discharge data collected from six gauging stations located within the region tested to be hydrologically homogeneous. The annual maximum discharges of the gauging stations were analyzed to develop: a regional frequency curve; regional regression equations to estimate peak annual flow for specified return periods (QT) and a regional regression equation to estimate the mean annual flood (Q2.33) using catchment parameters. The regional regression equation developed for the mean annual flood (Q2.33) has standard error (Se) and coefficient of determination (R²) values of 0.08175 and 0.9613 respectively. The equation can be applied to sites whether gauged or ungauged within the region to estimate the design flood (QT) needed for hydrologic modeling and engineering design of hydraulic structures. The IF procedure is particularly useful in developing countries where missing or inadequate data situation exist. [ABSTRACT FROM AUTHOR]

The annual maximum series of flow discharge data for three flow gauging stations located at River Donga at Manya,, River Donga at Donga and River Bantaji at Suntai within Upper Benue River Basin in Nigeria were fitted each with three probability distribution models namely ;Log normal, Extreme value Type 1 and Log Pearson Type III. The model results were subjected to four specific measures of error in prediction (i.e., RMSE, RRMSE, CC and MAE) and a scoring scheme on the basis of which best fit model for each station was selected. The best fit probability distribution models for the stations are Extreme value Type 1 (EV-I), Log Pearson Type III and Log normal for the stations at River Donga at Manya, River Donga at Donga and River Bantaji at Suntai respectively. The models can provide estimates of flood quantiles for planning, design, construction and operation of water resources projects within the river systems. [ABSTRACT FROM AUTHOR]

Biogas kinetic models are often used to characterize substrate degradation and prediction of biogas production potential. Most of these existing models are however difficult to apply to substrates they were not developed for since their applications are usually substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for better understanding of the anaerobic co-digestion of food waste and maize husk for biogas production. Biodegradability constant (k) was estimated as 0.11 d(-1) using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model were found to be in good correspondence, both in value and trend with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were inhibited/unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as an alternative model for anaerobic digestion feasibility studies and plant design., (Copyright © 2015 Elsevier Ltd. All rights reserved.)