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Organic-waste valorization is essential to the energy transition and circular bioeconomy. This study characterizes its technological innovation landscape through quantitative patent surveillance, focusing on technological maturity, geographic concentration, applicant structure, and innovation convergence. The Lens database was searched for granted patents published between 2000 and 2025. After four-stage screening, 36,074 records from 48 jurisdictions were analysed using logistic growth modelling, the Herfindahl–Hirschman Index (HHI), patent-family analysis, citation analysis, Cooperative Patent Classification mapping, and term co-occurrence analysis. Cumulative activity followed a logistic trajectory (upper asymptote, 43,728; growth rate, 0.217; inflection year, 2018.2; R 2 = 0.9992), indicating post-inflection consolidation; annual grants peaked at 2341 in 2018. The United States and European Patent Office accounted for 69.3% and 20.3% of records, respectively, representing 89.6% jointly. The HHI among the fifteen leading applicants was 768.9, indicating low concentration across biotechnology, petroleum, chemical, industrial, consumer-goods, and public-research sectors. Jurisdictional breadth was weakly and negatively associated with forward citations (Spearman's ρ = −0.082, p < 0.001), suggesting that international protection reflects anticipated commercial reach more than technological influence. Four technical clusters were identified: thermochemical conversion (42.9%), biotechnological conversion (31.2%), waste and water treatment (17.0%), and bio-based materials (8.8%). The materials cluster increased from 6.5% of annual records in 2010 to 17.2% in 2024, while co-occurrence patterns revealed convergence between thermochemical and biological technologies. These findings provide reproducible, multi-jurisdictional evidence for technology strategy, policy design, and transfer opportunities in resource-rich but technologically constrained regions. This design also enables comparison across jurisdictions and supports evidence-based technology transfer decisions.
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Polo et al. (2026) studied this question.
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