Alternatives to costly fossil fuel have witnessed rekindled interest because of the depletion of fossil reserves and environmental concerns. In this study, non-edible vegetable oil from Khaya Senegalensis (KS), which grows well in semi-arid zones was converted to biodiesel via transesterification under the reaction condition of 1.25 % catalyst and 1:6 Oil-methanol molar ratio. FTIR, GC-MS and NMR techniques were concurrently used to monitor common or similar peaks in the conversion process in an extensive cross comparison to validate other techniques' results. Furthermore, the composition of conventional diesel with the vegetable biodiesel produced were simultaneously analyzed. The results showed that conversion peaks were aligned, and successful delivered 82.02 % yield. The results from FTIR, GC-MS and NMR investigations all agreed, on the conversion of triglyceride molecules in the crude KS oil to fatty methyl esters in the biodiesel. Both produced biodiesel and conventional diesel were observed to contain alkanes and alkenes functional groups, that impart good fuel properties.

Drone aircrafts, also known as an Unmanned Aerial Vehicle (UAV) or Unmanned Aircraft Systems (UAS) has gained more importance in environmental monitoring as well as in telecommunication infrastructure theft response around the world. The study aims at identifying the type of sensors that can be mounted on drones for effective telecommunication infrastructure theft detection and prevention. The various parts of drone and configuration were tested. Sensors capable of detecting telecommunication infrastructures in the visible, infra-red, near infra-red, laser fluoro-sensor were all evaluated. The ability of the UAV to continuously and successfully patrol along or beside telecommunication infrastructure reveals that it takes about 5 minutes for the UAV to complete a programmed 150m autonomous patrol. During power test, result showed that for every 150m programmed patrol, 15 minutes of solar charging is required to restore the battery back to its initial voltage. It was concluded that a drone can properly be used for telecommunication infrastructure theft response operations. Appropriate sensors mounted on the drone can detect telecommunication infrastructure theft and can also access locations which are not readily accessible and other aerial patrol platform. The limitation of drones is the payload capability and its inability to operate well in windy weather since data collection with drone are faster, cheaper and easier during telecommunication infrastructure theft response operations. It is highly recommended to mount the suitable sensor capable of detecting telecommunication theft and vandalization even during nighttime operations.

Underwater Wireless Sensor Networks (UWSNs) rely on small, energy-constrained sensors deployed at varying sea depths for applications such as surveillance, environmental monitoring, and data collection. However, high energy consumption and end-to-end delay, exacerbated by dynamic depth and turbidity variations, significantly impact communication efficiency. Existing protocols, such as the Neighboring-Based Energy-Efficient Routing Protocol (NBEER), attempt to optimize energy usage but fail to adapt to these environmental changes, leading to reduced network performance. To address this, an Improved Energy-Based Efficient Routing Protocol (IEBERP) was developed, integrating a Distributed Underwater Clustering Scheme (DUCS) for efficient cluster formation and a Strata Adaptation Scheme (SAS) to dynamically reassign displaced nodes to the nearest cluster head (CH) after depth or turbidity changes. The protocol was simulated in MATLAB (R2024b), and results showed significant performance improvements over NBEER, achieving 9.68 TEC, 81.45 PDR, 46.42 E2ED, 234 NAN, and 35,191 NPR, compared to NBEER’s 12.60 TEC, 78.50 PDR, 53.00 E2ED, 198.30 NAN, and 22,500 NPR. These results highlight IEBERP’s enhanced energy management and adaptive clustering, leading to improved routing efficiency, reduced latency, and higher packet delivery rates. This makes IEBERP a promising solution for reliable and energy-efficient communication in dynamic underwater environments.

This study investigates the impact of three key factors - irrigation deficit percentage, NPK application rate, and tillage - on soil moisture content, a crucial parameter in agricultural productivity. To achieve this, a field experiment was conducted at Nnamdi Azikiwe University's Department of Agricultural and Bioresources Engineering Experimental Site/Farm Workshop, Awka. The experiment utilized a central composite design in response surface methodology, incorporating three factors: irrigation deficit percentage, NPK application rate, and tillage. This design enabled the researchers to examine the individual and interactive effects of these factors on soil moisture content. The results of the study revealed that the model was highly significant, with an R-squared value of 0.9084. This indicates that approximately 91% of the variation in soil moisture content could be explained by the model. Furthermore, the analysis showed that irrigation deficit percentage, NPK application rate, and tillage were all significant factors influencing soil moisture content. However, the interaction terms between these factors were found to be non-significant. A key outcome of this study was the development of predictive models for soil moisture content under different tillage conditions, namely No Tillage, Conservative Tillage, and Conventional Tillage. These models could be employed to forecast soil moisture content for specified levels of irrigation deficit percentage and NPK application rate under each tillage condition. The findings of this research provide valuable insights into the effects of irrigation deficit percentage, NPK application rate, and tillage on soil moisture content. These insights could be applied to inform agricultural practices in similar regions, ultimately contributing to improved crop yields and sustainable agricultural management.

This research investigates bio-oil production from soursop seed through pyrolysis, with process modelling and optimization conducted using RSM via Box-Benkhen design. Soursop seeds were oven-dried, ground, and sieved into various particle sizes within 1.0 to 6 mm range before undergoing pyrolysis at temperatures between 400 to 600 °C under inert nitrogen gas flow rates between 1.0 to 1.5 L/min. A Box-Behnken design under Response Surface Methodology (RSM) was used to model and optimize the effects of temperature, particle size, and inert gas flow on bio-oil yield. Proximate and ultimate analyses characterized the feedstock, while SEM revealed a porous structure favorable for pyrolysis. Bio-oil was characterized using FTIR and GC-MS to identify key functional groups and fatty acid composition. Proximate analysis showed the seeds had high volatile matter and fixed carbon, indicating good potential for pyrolysis. Ultimate analysis revealed carbon, hydrogen, nitrogen, oxygen, and sulphur contents of 51.29%, 5.90%, 0.50%, 42.30%, and 0.01%, respectively. Scanning Electron Microscopy (SEM) showed a rough, porous structure with oil-like droplets on the surface, which enhanced pyrolysis efficiency by providing a larger reactive surface area and improving devolatilization rates. The experimental design considered temperature, particle size, and gas flow rate combinations, with the bio-oil yield as the response. Results showed that increases in these parameters significantly affected bio-oil production. The maximum observed yield of 33.1% was achieved at 500°C, 6 mm particle size, and 1.0 L/min gas flow. The RSM model showed a high degree of fit with an R² value of 0.9875, adjusted R² of 0.9715, and predicted R² of 0.8007. Optimization predicted a maximum yield of 31.43% under conditions of 461.84°C, 3.84 mm particle size, and 1.02 L/min flow rate, with a desirability of 1.0. Experimental results closely matched these predictions, validating the model. Similarly, FTIR analysis indicates that the predominant monounsaturated fatty acid made up 45.55% of the total fatty acid content, which depicts that the oil belongs to the linoleic acid group. Furthermore, the FTIR analysis reveals that the alkene group contributes to increased reactivity and combustion efficiency, boosts the octane number of the bio-oil, and decreases the boiling point of the oil. Therefore, the FTIR and GC-MS analysis findings confirm that the bio-oil was within ASTM specifications.

Global lubricant demand is on the increase and the continual consumption of mineral oil-based lubricant has devastating environmental impact. Despite the identification of animal fat and vegetable oil as alternatives to mineral oil-based lubricants, there is concern about its sustainability due to the food-versus-lubricant debate. Thus, non-edible vegetable oil-based lubricant development has become a topical area of research. In this paper, the study of physicochemical, rheological, temperature, thermo-oxidative stability, corrosion inhibition and biodegradability properties of castor oil extracted from Nigerian grown castor bean seeds was conducted using standard test methods. The results show that castor oil has specific gravity of 0.955, free fatty acid value of 19.74 mg KOH/g, pH of 5.76, saponification value of 185.41 mg KOH/g and Iodine value of 92.1 gI2/100g oil. An assessment of the rheological and temperature properties of the castor oil gave kinematic viscosity at 400C and 1000C as 280.6 cSt and 77.5 cSt respectively, viscosity index of 33.4, pour point of -23.20C, cloud point of -12.40C and flash point of 2820C. The peroxide value of the castor oil was 8.92 meq/Kg and it was of corrosion grade 0. The castor oil has higher viscosity at 400C, lower viscosity index, and poor physicochemical properties compared to the SAE 20W50. The properties of the castor oil require improvement except its cold flow, flash point and corrosion inhibition properties. The castor oil is highly biodegradable while the SAE 20W50 has poor biodegradability. Therefore, castor oil conforms to ISO VG220 grade lubricant and qualifies to be called a biolubricant.

Integrating intermittent renewable energy sources into the power grid poses significant challenges to grid stability and reliability. This study examines the integration of Energy Storage Systems (ESS) into power grids to enhance stability and performance. A simulation framework was developed to analyze the technical and economic viability of Battery Energy Storage Systems (BESS) and Pumped Hydro Storage (PHS) systems. The results demonstrate the effectiveness of ESS in alleviating voltage fluctuations, frequency deviations, and grid disturbances. A diversified energy storage portfolio with optimized siting and innovative market mechanisms maximizes the benefits of ESS integration. The study reveals that BESS excel in rapid response times and scalability, while PHS systems offer superior economic benefits. This study pioneers a comprehensive simulation framework integrating technical, economic, and regulatory aspects to optimize Energy Storage Systems (ESS) integration, providing novel insights into maximizing grid stability and performance amidst escalating renewable energy integration. The findings provide valuable insights for policymakers, industry stakeholders, and researchers seeking to optimize energy storage strategies for resilient, sustainable, and efficient power systems.

Tannery wastewater is characterized by its high organic load and toxicity, primarily due to the presence of putrescible matter and heavy metals. This study aimed to simulate a comprehensive treatment process for tannery wastewater using Sewage Treatment Operation Analysis over Time (STOAT) software. The quality of treated wastewater from the simulation was evaluated against the National Environmental Standards and Regulations Enforcement Agency (NESREA) discharge standards to meet environmental safety requirements. The treatment system incorporated a multi-stage approach, including physical preliminary treatment units, chemical primary treatment, and biological secondary treatment. Additionally, the system featured a biogas production section and sludge dewatering units to maximize resource recovery. The simulation effectively modeled the treatment processes, capturing operational dynamics and interactions across the treatment units. Key pollutants, such as biochemical oxygen demand (BOD), total suspended solids (TSS), ammonia, and nitrate were monitored. Additionally, the study explored the impact of hydraulic retention time (HRT) on treatment efficiency. The results indicated that all parameters met NESREA's permissible discharge limits at various residence times. Similarly, the observed trends aligned with findings reported in the literature. Furthermore, the biogas yield from the simulation was 0.27 kg/m³ of tannery influent, with a maximum methane purity of 41%. Digested sludge was generated at a rate of 0.072 m³/m³ of tannery influent. However, extending digester residence time did not significantly enhance biogas yield or methane concentration, suggesting the need for process optimization or pre-treatment strategies. This research demonstrates the effectiveness of STOAT as a simulation tool for designing tannery wastewater treatment processes, ensuring compliance with stringent regulatory standards while optimizing resource recovery through biogas generation and sludge management. The findings emphasize the necessity of integrating physical, chemical, and biological treatment processes to enhance contaminant removal and improve the sustainability of tannery wastewater management.

Milk derived from animal sources often contains anti-nutrient elements such as α-lactoglobulin, β-lactoglobulin, lactose and cholesterol, which can contribute to various health challenges. Plant-based milk alternatives, such as tiger-nut milk, offer a healthier option but often face limitations like short shelf life and high storage costs. This study aimed to investigate the drying kinetics and proximate composition of tiger-nut milk powder. Tiger-nut tubers were processed into milk from brown varieties and subsequently dried at 50, 60, and 70°C. Data obtained were fitted to five commonly applied drying mathematical models (Newton, Logarithmic, Page, Henderson and Pabis) to determine the one which predicted the drying kinetics of the milk more accurately. The dried powder was then analyzed for its proximate composition, including moisture content, crude fiber, carbohydrates, protein, lipids, ash, and pH using standardized procedures developed by Association of Official Analytical Chemists (AOAC). The best fit model for the drying kinetics analysis was determined using the coefficient of determination (R²), with the Page model having the highest R² values of 0.998-0.999. This analysis revealed that the Page model accurately describes the drying behavior, with both drying time and equilibrium moisture content decrease as the drying temperature increases. The results also indicated that tiger-nut milk powder contains a moderate protein content (7.12-7.26%), a high carbohydrate content (63.68-64.17%), and relatively low levels of lipids (6.12-6.24%) and ash (1.42%). These findings suggest that tiger-nut milk powder has the potential to be a valuable plant-based food alternative. Future research should focus on determining its specific mineral composition, bioactive compounds, and potential health benefits.

This study assesses the water resources potential within the Maiduguri catchment of the Lake Chad Basin by analyzing a 20-year using rainfall data between 1999 to 2018 and streamflow data between 1981 to 2000 (each over a 20 year period). The results indicates that monthly rainfall was generally higher between 1999 and 2011, followed by a significant decline from 2012 to 2018. This shift suggests a progressive extension of aridity from the Lake Chad region into the Sudan Savannah, likely influenced by the effects of climate change. Flooding events were recorded in 16 of the 20 years analyzed. Streamflow analysis of River Ngadda, which traverses Maiduguri, revealed an average discharge of 6,201.2 m³/s over the study period, with a 7-year span of flooding. Additionally, storage apportionment data were evaluated to inform water resource management in the region.