Data-Driven Optimisation of Integrated Engineered Biochars in Sub-Saharan Africa (SSA) Ecosystem for Sustainable Energy, Food, Water and Health Nexus: Focus on South Africa, Ghana and Kenya

Sub-Saharan Africa (SSA) faces challenges of poverty, hunger, disease, and shortages in water, food, and energy supply. These issues undermine the aspirations of the UN SDGs and Africa's 2063 Development Agenda. Seed donations, the supply of food parcels and chemical fertilizers, and free basic electricity and water have attempted to address these challenges. However, they target specific sectors with limited and unsustainable coverage. Engineered biochar, a type of charcoal often made from the pyrolysis of plant waste, is a promising solution to ensure water, food, and energy security, thereby improving the health, environmental, economic, and social well-being of communities. Engineered biochar is used to improve soil health, clean water, improve air quality, produce bio-oil, store energy, and capture carbon, among other uses. Although the benefits of engineered biochar are known, a better understanding of its functions could optimize how it is used. This research will assess the current status of engineered biochar production—particularly its characterization and application—focusing on water, food, energy, and health. Our research group will: - Assess existing commercial technologies to produce engineered biochar. - Determine the availability and carbon neutrality of the engineered biochar used. - Perform life cycle and needs assessments to establish the environmental impacts, benefits, opportunities, and challenges of engineered biochar. - Conduct economic analyses to learn how using engineered biochar could improve health and save money for healthcare institutions. - Calculate the contribution of engineered biochar towards food production and security. - Establish the role of engineered biochar in helping industries work together and its place in the circular economy, where resources are used for as long as possible. We will use a mixed-methods approach, combining laboratory experiments, sample collection, and data modeling alongside interviews and questionnaires. Results from previous studies will be pooled for meta-analysis to identify knowledge gaps and guide our research.