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This study investigates, for the first time, the anaerobic digestion of food waste in Kuwait to optimize methane production through a combination of artificial neural network (ANN) modelling and continuous reactor experiments. The ANN model, utilizing eight hidden neurons and a 70-20-10 split for training, validation and testing sets, yielded mean squared error values of 0.0056, 0.0048 and 0.0059 and coefficient of determination ( R²) values of 0.9942, 0.9986 and 0.9892, respectively. Methane percentages in biogas were predicted using six parameters: biomass type, pH, organic loading rate (OLR), hydraulic retention time (HRT), temperature and reactor volume. To validate the ANN results, continuous reactor experiments were conducted under an OLR of 3 kg VS m⁻³ d⁻¹ and HRT of 20 days at varying temperatures (35°C, 40°C, 45°C, 50°C and 55°C). The experiments demonstrated optimal methane production in the mesophilic range, with ANN predictions closely aligning with experimental data up to 45°C. However, deviations were observed at higher temperatures, particularly under thermophilic conditions beyond 50°C. This study provides novel insights into waste-to-energy initiatives in Kuwait and highlights the potential of integrating computational models with empirical data to enhance biogas production processes.
This study investigates, for the first time, the anaerobic digestion of food waste in Kuwait to optimize methane production through a combination of artificial neural network (ANN) modelling and continuous reactor experiments. The ANN model, utilizing eight hidden neurons and a 70-20-10 split for training, validation and testing sets, yielded mean squared error values of 0.0056, 0.0048 and 0.0059 and coefficient of determination ( R²) values of 0.9942, 0.9986 and 0.9892, respectively. Methane percentages in biogas were predicted using six parameters: biomass type, pH, organic loading rate (OLR), hydraulic retention time (HRT), temperature and reactor volume. To validate the ANN results, continuous reactor experiments were conducted under an OLR of 3 kg VS m⁻³ d⁻¹ and HRT of 20 days at varying temperatures (35°C, 40°C, 45°C, 50°C and 55°C). The experiments demonstrated optimal methane production in the mesophilic range, with ANN predictions closely aligning with experimental data up to 45°C. However, deviations were observed at higher temperatures, particularly under thermophilic conditions beyond 50°C. This study provides novel insights into waste-to-energy initiatives in Kuwait and highlights the potential of integrating computational models with empirical data to enhance biogas production processes.
Produced water (PW), often labeled as the oil and gas industry's ‘silent threat,’ can damage ecosystems and human well-being when left untreated. In this context, the strategic management of PW emerges as a pivotal necessity within the oil and gas sector, aiming to mitigate potentially catastrophic consequences. This paper explores contemporary trends in PW management while pioneering a visionary path forward through an Energy-Water-Food Nexus approach, which contributes to achieving the Sustainable Development Goals (SDGs). This paper diverges from the conventional review format; instead, it takes on the role of a critical analysis. It meticulously exposes the constraints and obstacles inherent in traditional PW treatment methods, underscoring the imperative for sustainable alternatives. This analytical approach involves a range of evaluative criteria, including, but not limited to, energy consumption, operational costs, environmental consequences, and the overarching alignment with broader sustainability objectives. The paper strongly advocates for exploring sustainable avenues and adopting a circular PW management approach, viewing them as pivotal strategies for overcoming these challenges and achieving greater harmony with sustainability goals. The significance of water scarcity in the GCC countries and its profound implications for regional food security underscores the pressing need for innovative solutions. In this context, the oil and gas sector emerges as a valuable resource, generating substantial volumes of produced water with untapped potential. Our findings unveil a spectrum of promising applications for produced water, extending beyond the energy sector to address critical challenges. Notably, produced water exhibits remarkable utility in diverse domains: agricultural irrigation, municipal and industrial usage, livestock farming, surface water management (including evaporation ponds and stream discharge), and groundwater recharge. Furthermore, our research highlights the promise of green technology, exemplified by constructed wetlands, as a practical, nature-based solution for produced water treatment. Additionally, by leveraging nanotechnology, we can achieve finer control over contaminants and pollutants, ensuring a higher degree of water quality. Lastly, our study delves into the prospect of harnessing bioenergy from produced water, specifically biomethane, through anaerobic digestion technology. These multifaceted sustainable options align with the circular management of produced water and can significantly impact the energy-water-food nexus, contributing to the region's sustainable development goals. This paper highlights how innovative PW management can catalyze the attainment of various SDGs while enhancing the synergy between industry and the environment. It envisions a paradigm shift in PW management, advocating for environmentally friendly, resilient, and intelligent systems that facilitate circular utilization. This perspective bridges oil and gas industrial growth and sustainability, offering a transformative path that promotes circular economics, resource conservation, and environmental protection, all within the framework of the Energy-Water-Food Nexus.
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