Forest residues are increasingly considered recoverable biomass resources for circular and low-carbon cement-based materials. However, life cycle assessment (LCA) findings remain difficult to compare because studies differ in residue definitions, system boundaries, functional units, allocation rules, biogenic-carbon treatment, logistics assumptions, and durability modelling. This structured integrative methodological review synthesizes peer-reviewed studies and relevant methodological guidance identified through targeted searches of the Web of Science Core Collection and Scopus, with literature coverage restricted to publications available from 1 January 2018 to 25 December 2025. Foundational standards and directly relevant methodological sources were also considered where they supported functional-unit interpretation, allocation, biogenic-carbon accounting, spatial LCA, durability-to-LCA translation, or end-of-life modelling. The review focuses on three cement-based routes: wood-derived aggregates or fillers, wood-waste ash as a supplementary cementitious material, and forest-residue-derived biochar additives. The reviewed evidence is mapped to a three-tier functional-unit hierarchy: per kg dry residue input for process-level screening, per m3 of concrete meeting a declared performance class for technology comparison, and per tonne CO2-eq mitigated for policy interpretation. A worked numerical example illustrates how pathway ranking can change when strength or service-life equivalence is imposed. The review also develops a context-sensitive allocation framework, a structured summary of biogenic-carbon conventions, and a GIS–LCA workflow that accounts for supply radius, infrastructure, data scarcity, and regional variability. Durability is linked to LCA through exposure-conditioned indicators, service-life models, maintenance inventories, and material-specific end-of-life scenarios. Uncertainty treatment is specified through data-quality appraisal, scenario and sensitivity analysis, and Monte Carlo propagation where defensible parameter distributions are available. The GIS–LCA structure is presented as a methodological decision-support proposal rather than as a universally validated pathway-ranking model.
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