Operational reality of waste-based power generation: a utilization-centered case study of tire pyrolysis and corn stover biomass under identical market conditions

• Real-world operational data replace feasibility-stage assumptions in waste-based power generation. • Two waste-to-electricity technologies are evaluated under identical investor and market conditions • Capacity utilization is identified as the governing variable linking production stability, economics, and emissions. • Low utilization dramatically increases unit costs and gate-to-gate CO 2 intensity in tire pyrolysis. • Utilization-aware assessment is essential for realistic waste-to-energy policy and investment decisions. Waste-based power generation technologies are frequently evaluated using feasibility-stage assumptions that overlook operational constraints. This study presents a utilization-centered operational case study of two waste-to-electricity investments—a waste tire pyrolysis plant and a corn stover combustion biomass power plant—implemented by the same investor in Türkiye under identical market conditions. Using realized field data (40 months for pyrolysis; 18 months for biomass), the analysis examines how capacity utilization governs economic performance and emission intensity beyond technology type alone. The pyrolysis facility exhibits persistent production volatility with average utilization near 40%, whereas the biomass plant stabilizes and reaches approximately 70% within its first year. Despite process improvements, pyrolysis fails to convert installed capacity into sustained electricity output, resulting in higher unit costs and emission intensity. The findings demonstrate that realized capacity utilization—rather than nominal efficiency or technology classification—determines operational sustainability and recovery performance in waste-to-energy systems. Unlike feasibility-based or model-driven studies, this analysis is based on complete operational datasets covering the full lifecycle of both facilities from commissioning, including all instability and constraint-driven operating conditions.