Advancing circular economy and renewable energy integration in abattoir waste management: a sustainable framework for global adaptation

Purpose Abattoir waste remains a major environmental and public health challenge in many developing countries because of uncontrolled discharge, high biological oxygen demand/chemical oxygen demand loads and methane emissions. However, its resource potential for renewable energy remains largely untapped. The purpose of this study is to develop and validate a circular economy–renewable energy (CE–RE) framework that converts abattoir waste from an ecological liability into a sustainable resource, supporting Nigeria’s energy transition and broader climate and development goals. Design/methodology/approach A mixed-methods approach integrated field surveys of 192 respondents across three abattoirs in Ogun State with direct waste quantification, Buswell-based biogas modelling, financial feasibility analysis and a Delphi-based expert validation. The framework was evaluated across technical, economic, environmental, institutional and social dimensions to ensure practical applicability. Findings Waste loads of 1.2–3.2 tonnes/day produced methane yields of 192–512 m³/day (3,800–10,240 kWh/month), with co-digestion improving output by 15%–25%. Financial modelling showed strong viability (internal rates of return 17%–21%; payback 4–5 years). CE–RE integration lowered effluent pollution, reduced zoonotic risks and produced nutrient-rich digestate. Social analysis highlighted opportunities for gender-responsive cooperatives to enhance inclusion and economic participation. Originality/value This study offers one of the first empirically grounded CE–RE frameworks for abattoir systems in the Global South, integrating technical modelling with financial, institutional and social inclusion considerations. Its key contribution lies in providing a scalable and policy-ready framework that supports Nigeria’s Energy Transition Plan and demonstrates a replicable pathway for waste-to-energy adoption in resource-constrained settings.