An R-Based GIS Multi-Criteria Decision Analysis Framework with Monte Carlo Stability: Biorefinery Site Selection for Peat-Alternative Growing Media in Ireland

This study investigated where peat alternative biorefineries should be sited across the Republic of Ireland to scale bio-based growing media supply chains while considering environmental and planning constraints. A constraint-first GIS Multi-Criteria Decision Analysis (MCDA) implemented in R combined county-level feedstock supply (wood residues, straw/tillage residues, grass biomass, brewer’s spent grain and energy crops) with accessibility from national roads and rail; exclusion buffers were applied around built-up areas, water bodies and reservoirs, heritage features and airports. For each county an exclusion share was calculated and an 80% unconstrained area threshold was used to remove unsuitable counties; weighted overlay suitability scores were then computed for the remaining counties. An 800-iteration Monte Carlo weight sampling simulation quantified robustness, producing selection frequency maps and uncertainty bands to identify candidates that are sensitive to weighting assumptions. The highest masked suitability scores were the counties of Wexford, Cork, Galway, Kerry, and Mayo, showing that realistic spatial constraints materially change biorefinery site selection outcomes compared with biomass-only rankings. The scientific novelty is a fully reproducible, county scale, constraint-led MCDA implemented entirely in R and simulated with Monte Carlo diagnostics to generate auditable, policy-ready maps. The approach is relevant to national policy because it focuses limited analytical and planning resources on the most promising regions and highlights where regulatory or land-use interventions may be required; however, results remain contingent on buffer distances, feedstock bioresources, and weighting choices and therefore require ground verifications and finer-scale remote sensing data, permitting review and stakeholder engagement before site selection and investment. If applied, the framework can help prioritise investments to reduce peat use in horticulture and may deliver carbon and biodiversity co-benefits, subject to local assessment and mitigation. Future work should integrate this spatial screening with detailed logistics modelling, socioeconomic feasibility studies and participatory planning to translate county-scale suitability into operational biorefinery projects.