https://repository.biust.ac.bw:443 The BIUSTRE digital repository system captures, stores, indexes, preserves, and distributes digital research material. 2026-07-22T23:14:54Z https://repository.biust.ac.bw/handle/123456789/749 Investigating the potential of biogas production from BIUST wastewater treatment sludge by co-digestion with slaughterhouse waste Othusitse, Nhlanhla; Dlamini, Gcinumuzi; Jonas, Mbako; Mamvura, Tirivaviri; Agachi, Paul S. Wastewater treatment is a necessity in any community and civilization particularly where water is a scarce natural resource. The Botswana International University of Science and Technology is habitat to a community of just under 5000 people and has its own dedicated wastewater treatment plant. Currently this plant is managed by the university and boasts of 7 ponds. The plant follows a conventional four stage process; starting off with screening and grit removal, then removal of suspended solids through sedimentation, breakdown of organic matter through biological processes, then lastly filtration, disinfection, and use of chemical treatment to ensure compliance with quality standards before final discharge. This research aims at the third stage of biological processing to explore potential for biogas production potential from BIUST wastewater treatment sludge (WTS). Presently the anaerobic digestion ponds are open to the atmosphere and therefore release methane to the atmosphere adding to greenhouse gas emissions. To investigate, four different ratios of sludge (SL) to slaughterhouse waste (SHW) (1:1, 1:3, 3:1, 2:3) were co-digested, and the two substrates mono digested. The experiment was conducted over a retention time of 32 days in 2L reactor vessels. The results for bio-methane potential revealed that sludge: slaughterhouse waste 1:3 accumulated the highest volume of biogas (10,446.4 NmL CH4/gVS), sludge on its own accumulated the lowest volume of biogas (3,134.9 NmL CH4/gVS). The ratio of 2:3 exhibited the most optimal physiochemical properties for biogas production, promising a high turnover of gas produced. The premeditated assumption was later discovered to be false, as the volume accumulated was relatively low (3435.8 NmL CH4/ gVS) only increasing by 9.6% compared to the lone digestion of sludge. Ratio of 3:1 yielded a biogas of 5,686.1 NmL CH4/gVS, showing an 81% increase in biogas yield compared to mono-digestion of sludge. Therefore, co-digestion of sludge with slaughterhouse waste at a 3:1 ratio shows great potential for biogas production from BIUST waste treatment sludge. 2024-07-22T00:00:00Z https://repository.biust.ac.bw/handle/123456789/748 Hybrid machine learning and genetic algorithms for environmental impact and energy management to enhance mining sustainability Parvathareddy, Sravani; Yahya, Abid; Amuhaya, Lilian Livutse; Ravi, Samikannu The mining industry confronts the challenge of balancing economic prosperity and environmental sustainability. This research presents a comprehensive approach that leverages big data analytics and machine learning techniques to address this challenge. Unlike traditional approaches that focus on mitigating impacts post-occurrence, our method advocates for proactive measures throughout operational phases. We introduce a cohesive system integrating advanced technologies to analyze vast datasets, including real-time environmental sensor data, satellite imagery, company reports, and government records. The framework encompasses data pre-processing, model building, analysis, and recommendations. To predict environmental outcomes and assess sustainability, we employ a genetic algorithm (GA) and machine learning tools such as XGBoost, support vector regressor (SVR), and K-nearest neighbors (KNN) regressor algorithms. Data pre-processing ensures data accuracy and consistency. We use clustering and recommendation algorithms for analysis and suggestions, identify improvement areas, and propose environmental management solutions. This methodology underscores the importance of empowering stakeholders to anticipate environmental consequences, mitigate potential hazards, and continuously improve sustainability initiatives through real-time insights. By integrating big data analytics and machine learning, we enhance the environmental sustainability of mining operations, fostering a harmonious balance between environmental stewardship and economic returns. The benefits of our system are manifold, including improved environmental management, reduced environmental risks, and enhanced sustainability practices in the mining industry, thereby highlighting the crucial role of stakeholders in this process. 2024-07-22T00:00:00Z https://repository.biust.ac.bw/handle/123456789/747 Physiological and ecological responses of the larger grain borer, Prostephanus truncatus (Horn), to changing environments: implications for its population dynamics and management Mlambo, Shaw The rapid change in environments owing to anthropogenic activities and climate change has reshaped the geographical range and status of different insect pests of economic importance. Further, the mechanisms by which conspecific and allospecific species phenotypes vary and how that influences species adaptation in novel environments are poorly understood. The larger grain borer, Prostephanus truncatus (Horn) (Coleoptera: Bostrichidae), is one of the quarantine pests which poses serious threats to stored maize and dried cassava tubers and has continued to expand its ranges in Africa. However, physiological and ecological data required to map the dispersal pathways and factors limiting geographical distribution of such pests in diverse environments are largely understudied. A combination of literature reviews, field (questionnaire survey and pest monitoring through pheromone baited traps) and laboratory studies were conducted to determine (i) the presence and geographical range of P. truncatus in Botswana (Chapter 2), (ii) local farmers’ knowledge, practices and perceptions on cereal postharvest management including the efficacy of current storage technologies against P. truncatus (Chapter 3), (iii) the drivers and implications of P. truncatus and Spodoptera frugiperda biological invasions in Africa (Chapter 4), (iv) effects of increasing temperatures on the transgenerational (Chapter 5) and intergenerational (Chapter 6) responses of P. truncatus, (v) feeding rates and effects of maternal host preferences on progeny fitness (Chapter 7) and (vi) effects of intra- an interspecific competition on P. truncatus’ physiological and ecological performance (Chapter 8). Standardised physiological (critical thermal maxima [CTmax], critical thermal minima [CTmin], heat knockdown time [HKDT], upper lethal temperatures [ULTs]) and ecological performance (% maize grain damage, % grain weight loss, progeny production, % insect feeding dust) traits were measured under controlled temperature and relative humidity conditions in climate chambers. Results confirmed, for the first time, the presence of P. truncatus in Botswana, but its distribution is still patchy. Although the pest seems not yet well-established inland, the current farmer practices dominated by use of botanical pesticides makes them vulnerable if P. truncatus was to become dominant. Lack of information and awareness of the dangers that P. truncatus pose and lack of improved grain storage facilities further expose local smallholder farmers to this threat. Laboratory assays showed behaviourally plastic responses to increased temperatures and varying xvii hosts. First, trait-dependent thermal plasticity responses are passed on to offspring through transgenerational and intergenerational plastic physiological responses which mediate P. truncatus progeny fitness. Alongside, maternal experiences or decisions by offspring through transgenerational plasticity act as signals for adaptation to a host. Ecological performance of P. truncatus was high at 25 and 30℃ in response to temperature suggesting high pest activity under elevated temperature conditions. This may mean that P. truncatus poses serious threats to food security with increasing temperatures under climate change. However, damage was highly suppressed at higher suboptimal temperatures of 35℃. Prostephanus truncatus failed to survive on mopane wood suggesting that the wood may not be a suitable host for the pest. The study shows P. truncatus physiological adaptative responses to changes in the environment and climate and calls for concerted efforts to monitor the pest inland, forewarn farmers of the dangers of the pest and train them on appropriate efficacious grain storage technologies to manage the pest. This work contributes insights into the ecology and physiology of P. truncatus, which are important in developing models for early warning and control, as well as integrated national and regional pest management strategies against the pest. Thesis (PhD Biological Sciences and Biotechnology)--Botswana International University of Science and Technology, 2025 2025-09-01T00:00:00Z https://repository.biust.ac.bw/handle/123456789/746 Modelling and optimisation of ultra-fine grinding of Copper Sulphide ore. Moyo, Nkosilamandla The global demand of base metals has been steadily on the rise since the fourth industrial revolution, and in the past 20 years, the rise has sharply increased, driven by the paradigm energy transition from traditional fossils utilization to green sustainable technologies. Base metals play are key in these sectors particularly in structural developments, smart materials for the health sector and as key elements in the renewable energy storage facilities, energy transmission and in the automotive industry. Copper is an essential base metal, particularly in driving energy transition and electrification, in electronics and technology advancements, in urbanization and infrastructure growth etc. For instance, the utilization of copper in electric vehicles is reported as 2-4 times that of internal combustion engine cars therefore its demand has been steadily on the rise. Mining sector remain crucial to the development of Southern African economies, Botswana having its economy being driven by the diamond industry, however, observing the dangers of relying on diamonds, the government has since set its sights towards diversification of its industrial sector. This starts with the prominent mining sector, by promoting and resuscitating once operational base metals mines, particularly reviving the copper industry, which currently is the second mined mineral in the country. Copper reserves in Botswana are predominantly sulphide ores therefore they have been beneficiated through the pyrometallurgy route. However, with the depletion of rich ore bodies, and the imposed environmental laws set to reduce climate effects resulting from anthropogenic emissions, the traditional route has not been favorable anymore. This led to the country exporting its resources solely in concentrate form, losing some valuable revenue in that transaction, therefore the need to extract, separate and purify base metals from these concentrates is more beneficial for the nation. Hydrometallurgy technologies developed in the late 20th century to the beginning of the 21st century, e.g. the Activox, CESL technologies, have demonstrated effective extraction, countering the traditional drawbacks of sulphide mineral leaching. This work looks therefore into adoption of the Activox technology for the efficient beneficiation of copper in Botswana. The Activox technology is parent to two daughter processes, the ultra-fine grinding process and the oxidative pressure acid leaching. The scope of this work dwelt on the primary process, the ultra-fine grinding process, an energy intensive process, for the mechanical activation of the mineral surfaces for effective extraction of copper form its mineral matrix. Due to equipment constraints faced, the work was conducted using a 5litre laboratory ball mill, with the aim of modelling and optimizing the process, i.e. the product grind quality and energy consumption. This was achieved through hybrid modelling, i.e. machine learning modelling surrogated with statistical modelling. The StatEase Design Expert software was utilized for statistical modelling while the Artificial Neural Network and Artificial Neuro-Fuzzy Inference System packages in Matlab 2021a were used. The UFG process is highly complex, as evidenced by increasing research conducted on it, assessing the impact of various factors on its efficiency, both in grinding extent and energy consumption, e.g. rotational speed, powder filling, media type, media size, media filling, solids/liquids ratio and use of viscosity modifiers etc. In this study, the effects of grinding media size, milling speed, milling time and media filling ration were tested experimentally on the efficiency of the process on both counts. The outright realization herein was that media size greatly impacts the process, and this aligned with reports from literature with the generalisation for machine learning. particle size grammar xvii | P a g e that fine media best suits fine milling, and the effect of this was also noticed in energy consumption as lengthy milling periods were needed with coarse media for effective grinding compared to fine media. Further analysis of the observations from experiments using fine media showed that the base factor of importance was the media filling ratio, from which mill speed and milling time impacts relied on. This was a positive realisation as it highlighted the potential of improved production rate at maximum filling of the media, subject to optimisation of this filling rate using the attainable region as thus recommended in this work. Modelling of the processed led to effective optimisation, firstly after realisation of 20μm being the optimum P80 grind size, compared to the technology’s 10μm from characterization. As such, the hybrid modelling exercise was effectively done, with validation results when using a different sulphide ore, of 97.34% for P80 predictions using the ANFIS technique while that of SE at 85.71% using the ANN technique. The ascertain the validity of this optimisation, a cost benefit analysis was conducted, and it proved that with optimizing the process from 10μm to 20μm, a 24.45% energy saving could be realized. This translates to a massive saving especially in a process that is energy intensive as such this could lead to the feasible adoption of the technology, leading to reviving the economy, creating more employment opportunities. To fully stamp on this optimisation, a comparison of the leaching at 10μm and 20μm is required to ascertain the extraction efficiency as validation of the entire work. 2025-06-01T00:00:00Z