Michael Okpara University of Agriculture

Ugwu E.I., Agunwamba J.C.

Metal ion contamination in wastewater is an issue of global concern. The conventional methods of heavy metal removal from wastewater have some drawbacks, ranging from generation of sludge to high cost of removal. Adsorption technique for copper(II), zinc(II), and chromium(VI) using activated carbon has been found efficient. However, it is not economical on a large scale. This, therefore, necessitates the search for economical and readily available plant biomass-based activated carbons for the sequestration of the metal ions. This review presents the state of the art on the adsorption of copper(II), zinc(II), and chromium(VI) from industrial wastewater. Based on the literature review presented, the groundnut husk and corncob based activated carbons were found to possess the maximum adsorption capacities for copper(II), zinc(II), and chromium(VI) removal, when compared with the other plant biomass-based activated carbons. The high values of the adsorption capacities obtained were as a result of the isotherms and pH of the adsorbent as well as the initial concentration of the metal solutions. From the review, the equilibrium data fitted better with Langmuir and Freundlich isotherms than with other isotherms. Research gaps were identified which include a need to investigate the kinetic and the thermodynamic behaviors of the metal ions onto the studied adsorbents. Furthermore, a comparative analysis of the three types of activation of the adsorbents should be investigated using single and multi-metals. The optimization of particle size, contact time, temperature, initial concentration, and adsorbent dosage for adsorption of copper(II), zinc(II), and chromium(VI) onto the studied adsorbents using response surface methodology is equally required.

Ndukwu M.C., Onyenwigwe D., Abam F.I., Eke A.B., Dirioha C.

The paper presents an active mix-mode wind-powered fan solar dryer (AWPFS) with a passive mix-mode non-wind-powered solar dryer (PNWPS) evaluated with pre-treated potato slices. The two dryers were tested with and without glycerol as thermal energy storage. The objective was to present a non-electricity powered active solar dryer using only clean energy sources. Evaluation of the dryer took place at ambient temperature range of 24–50 °C and humidity of 10–52%. The results indicate that drying with AWPFS integrated with glycerol showed shorter drying time than drying with AWPFS only or PNWPS. Dipping the potato in a salt solution and blanching for 30 s before drying quickened the drying rate of the potato compared to other treatments. The energy consumed for drying ranged from 4.10 to 4.98 MJ, while the specific energy consumption ranged from 2.846 to 3.686 kWh/kg. The drying efficiencies ranged from 25.031% to 31.5%, while the exergy efficiency ranged from 14.5 to 80.9%. With low electricity penetration density across Africa, this dryer with naturally powered fan will help crop processors dry their product faster and about 15.3–290.4 $/year could be saved at 10–100% rate of usage • First time energy and exergy of solar dryer with wind generator power fan source and glycerol as heat storage were studied. • Drying with the combination of wind generator and thermal storage proved more energy effective. • Glycerol has positive effect on the drying time but increased energy consumption. • About 15.3–290.4 $/year could be saved at a rate of usage of 10–100% if the solar dryers are adopted.

Ndukwu M.C., Simo-Tagne M., Abam F.I., Onwuka O.S., Prince S., Bennamoun L.

The aim of this study is to present a new hybrid solar-biomass dryer and carry out thermal analysis based on energy and exergo-sustainability analysis considering all the available exergy stream of solar radiation, air stream through the collector, and exergy of the moisture in the product. The research also presented the environmental impact and economic analysis of using the dryer. Performance evaluations show that at collector efficiency of 20.81%-21.89 %, the developed solar dryers can save between 10 - 21hrs of drying time in drying 5 mm thick plantain slices to 15 % moisture content from initial moisture content of 66 % w.b when compared to drying under the open sun. The improvement potential ranged from 0.036 to 20.6W while the waste exergy ratios and sustainability index ranged from 0.38 - 0.55 and 2.3-6.11 respectively. Application of the solar dryers can save between 44 -3074 of CO2 entering the atmosphere per year while 2.94 to 205.43$ could also be saved at 10-100% rate of usage when compared to diesel fired dryer. The total energy consumption for drying ranges between 5.52 and 35.47 MJ, while the specific energy consumption ranged from 4.3 to 26.2 kWh/kg. The exergy efficiency ranges from 5.6 - 95.13 % during the sunshine hours.

Oyedotun K.O., Ighalo J.O., Amaku J.F., Olisah C., Adeola A.O., Iwuozor K.O., Akpomie K.G., Conradie J., Adegoke K.A.

Global carbon reduction targets can be facilitated via energy storage enhancements. Energy derived from solar and wind sources requires effective storage to guarantee supply consistency due to the characteristic changeability of its sources. Supercapacitors (SCs), also known as electrochemical capacitors, have been identified as a key part of solving the problem. In addition, SCs can provide solutions to charging electric vehicles much faster than is possible using lithium-ion batteries. Nevertheless, further research into high-performance supercapacitor development is urgently needed to enable their use for effective large electricity storage. In general, energy utilization will subsequently depend on consumers/industries that are generating, storing and utilizing energy more effectively, with SCs being identified as one of the emerging technologies for intermittent energy storage, harvesting and high-power delivery. In this review, we have highlighted the historical information concerning the evolution of supercapacitor technology and its application as an energy storage device. A detailed account of the device’s electrode materials/electrolytes, processes, designs, and various applications is discussed. The primary characteristics of the energy storage system, such as capacitance/capacity, operating temperature, energy/power density, operating potential, kinetic storage mechanism, cycling lifetime, self-discharge, voltage holding/floating test, and the makeup of the electrode materials, are also briefly discussed. In addition, based on the current research scenario, the potential, challenges, and development patterns for SCs are summarized.

Iroha N.B., Anadebe V.C., Maduelosi N.J., Nnanna L.A., Isaiah L.C., Dagdag O., Berisha A., Ebenso E.E.

Linagliptin (LGP) was investigated as a mild steel (MS) corrosion inhibitor in 1 M HCl solution using combined experimental and theoretical explorations. The investigated molecule was revealed to reduce the corrosion of mild steel in an extremely acidic environment. LGP inhibitory effectiveness is temperature and inhibitor concentration dependent, reducing with rising temperature and increasing with increased LGP concentration. The maximum inhibition efficiencies deduced by weight loss, impedance and potentiodynamic measurements with 7.5 × 10−3 M LGP at 30 °C were 96.3%, 96% and 94%, respectively. The results of polarization measurement suggested a mixed-type inhibitory action of LGP, reducing the anodic/cathodic partial reaction. Adsorption of LGP onto the steel surface obeyed Langmuir isotherm, with a combination of chemical and physical adsorption. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) revealed the adsorbed inhibitor film layer shielding the mild steel from hostile acid ions. DFT/MD simulation approaches were used to investigate the adsorption orientation of LGP's molecule on the mild steel surface in aqueous environment. The experimental routes strongly conform with the theoretical findings.

Chukwuemeka-Okorie H.O., Ekuma F.K., Akpomie K.G., Nnaji J.C., Okereafor A.G.

The toxic effects of anionic dyes such as tartrazine and sunset yellow on humans and the aquatic environment are of serious concern. The need for the removal of these dyes from wastewaters led to the use of adsorption techniques as a cheap and efficient treatment method. Thus, this research was based on the preparation of a low-cost activated carbon derived from cassava sievate designated as CS, which was utilized in the adsorption of sunset yellow and tartrazine from simulated wastewater. The sorption process was carried out under varying process factors in a batch mode. Adsorbent characterization displayed the presence of surface functional groups by the FT-IR and a porous structure as revealed by scanning electron microscopy. Optimum dye uptake was recorded at pH (1.0–2.0), temperature (30–40 °C), CS dosage (0.1 g), and dye concentration (150 mg/L). A maximum CS monolayer uptake of 20.83 and 0.091 mg/g was recorded for tartrazine and sunset yellow dyes, respectively. The pseudo-second-order (R2 > 0.99) and Freundlich (R2 > 0.92) models were most fitted to the kinetics and isotherm data of the uptake of the dyes on CS. The adsorption equilibrium attainment was reached was within 90 min of dye sequestration. The experimental results revealed that both sunset yellow and tartrazine dyes were considerably adsorbed onto the environmentally compatible and low-cost activated carbon derived from cassava sievate.

Simo-Tagne M., Ndukwu M.C., Zoulalian A., Bennamoun L., Kifani-Sahban F., Rogaume Y.

The objective of this paper is to model a natural convection mix-mode solar dryer (NCMMSD) for drying agricultural products in an environment with short sunshine duration. The solar dryer was used to dry red chilli and was operating under the climate of the coastal area of South Eastern Nigeria characterized by low solar radiation intensity with a short duration of sunshine hours. The model took into consideration the thermophysical properties of the drying air and dried red chilli. The simultaneous heat and mass transfer equations were solved using the fourth-order Runge-Kutha method. The numerical solution allows for the determination of temperature and relative humidity of drying air at different points within the dryer as well as the moisture profile of the dried product. The experimental values of moisture ratios, temperature, and relative humidity during the mix-mode solar drying process with and without NaCl were used to validate the proposed model. Numerical simulation results were in close agreement with experimental results. The present model can serve as good reference bases to explain the drying phenomenon of mix-mode solar drying of other agricultural products when necessary thermophysical properties of these products are known. Using this model, the potential of mitigating gross fossil (coal) CO2 in Africa is annually estimated to 1280148 tons of CO2.

Nnaji P.C., Anadebe V.C., Ezemagu I.G., Onukwuli O.D.

In dye-based wastewater decontamination, coagulation-flocculation (CF) induced by Luffa cylindrica seed (LCS) was applied.

Akpomie K.G., Conradie J., Adegoke K.A., Oyedotun K.O., Ighalo J.O., Amaku J.F., Olisah C., Adeola A.O., Iwuozor K.O.

AbstractThe contamination of environmental waters with heavy metals and radionuclides is increasing because of rapid industrial and population growth. The removal of these contaminants from water via adsorption onto metal nanoparticles is an efficient and promising technique to abate the toxic effects associated with these pollutants. Among metal nanoparticle adsorbents, zinc oxide nanoparticles (ZnONPs) have received tremendous attention owing to their biocompatibility, affordability, long-term stability, surface characteristics, nontoxicity, and powerful antibacterial activity against microbes found in water. In this review, we considered the adsorption of heavy metals and radionuclides onto ZnONPs. We examined the isotherm, kinetic, and thermodynamic modeling of the process as well as the adsorption mechanism to provide significant insights into the interactions between the pollutants and the nanoparticles. The ZnONPs with surface areas (3.93 to 58.0 m2/g) synthesized by different methods exhibited different adsorption capacities (0.30 to 1500 mg/g) for the pollutants. The Langmuir and Freundlich isotherms were most suitable for the adsorption process. The Langmuir separation factor indicated favorable adsorption of all the pollutants on ZnONPs. The pseudo-second-order kinetics presented the best for the adsorption of the adsorbates with regression values in the range of 0.986–1.000. Spontaneous adsorption was obtained in most of the studies involving endothermic and exothermic processes. The complexation, precipitation, ion exchange, and electrostatic interactions are the probable mechanisms in the adsorption onto ZnONPs with a predominance of complexation. The desorption process, reusability of ZnONPs as well as direction for future investigations were also presented.

Onyelowe K.C., Iqbal M., Jalal F.E., Onyia M.E., Onuoha I.C.

Artificial neural network (ANN) method has been applied in the present work to predict the California bearing ratio (CBR), unconfined compressive strength (UCS), and resistance value (R) of expansive soil treated with recycled and activated composites of rice husk ash. Pavement foundations suffer from poor design and construction, poor material handling and utilization and management lapses. The evolutions of soft computing techniques have produced various algorithms developed to overcome certain lapses in performance. Three of such algorithms from ANN are Levenberg–Muarquardt Backpropagation (LMBP), Bayesian Programming (BP), and Conjugate Gradient (CG) algorithms. In this work, the expansive soil classified as A-7-6 group soil was treated with hydrated-lime activated rice husk ash (HARHA) in varying proportions between 0.1 and 12% by weight of soil at the rate of 0.1% to produce 121 datasets. These were used to predict the behavior of the soil’s strength parameters (CBR, UCS and R) utilizing the evolutionary hybrid algorithms of ANN. The predictor parameters were HARHA, liquid limit (wL), (plastic limit (wP), plasticity index (IP), optimum moisture content (wOMC), clay activity (AC), and (maximum dry density (δmax). A multiple linear regression (MLR) was also conducted on the datasets in addition to ANN to serve as a check and linear validation mechanism. MLR and ANN methods agreed in terms of performance and fit at the end of computing and iteration. However, the response validation on the predicted models showed a good correlation above 0.9 and a great performance index. Comparatively, the LMBP algorithm yielded an accurate estimation of the results in lesser iterations than the Bayesian and the CG algorithms, while the Bayesian technique produced the best result with the required number of iterations to minimize the error. And finally, the LMBP algorithm outclassed the other two algorithms in terms of the predicted models’ accuracy.