As part of its mission to derive value from biowaste streams, Prevent Waste Alliance has initiated a project to develop Black Soldier Fly (BSF) technology in Uganda, Ethiopia, and Ivory Coast. This collaborative effort is being implemented by Africa Circular in partnership with Trinomics, Eclose, and EAWAG, and is funded by GIZ and the Climate and Clean Air Coalition (CCAC).
The project team is responsible for developing a guide for BSF operators and a general methodology for assessing BSF feasibility, which will be piloted, tested, and prototyped in the target countries. Another key objective is to capture and replicate best practices and lessons learned across African countries.
In addition to reducing greenhouse gas emissions, the project aims to address food security, create livelihoods, empower women and youth, and tackle environmental and waste management challenges. The goal is to lay the groundwork for future BSF initiatives in the selected countries, fostering favorable institutional and economic conditions, enhancing cooperation among stakeholders, and mainstreaming waste-based BSF farming. The project seeks to raise awareness, knowledge, and skills related to BSF waste processing, identify implementation areas in the selected countries, and advocate for integrating BSF technology into waste management policies, low-carbon strategies, and national climate mitigation goals.
This multi-year project began in February 2024 and is scheduled to conclude by 2025. In the first phase, kick-off workshops were conducted in each of the countries, bringing together relevant stakeholders to explore opportunities, identify existing enabling ecosystems including policy and legislative frameworks, and address capacity gaps in infrastructure and technical skills for optimal production.
The workshops also provided a platform to discuss how BSF technology could align with existing composting initiatives, analyze the flow of waste from food processing (e.g., brewery, dairy waste, juicing factories), and design a feasible business model.
For more information, please reach out to the Email: [email protected]
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