Database-Driven AHP-Weighted Screening of Biomass Densification Technologies Under Corporate Environmental Responsibility-Oriented Scenarios

Technology pre-screening for biomass densification requires combining heterogeneous equipment specifications without overstating incomplete environmental or economic evidence. Within a Corporate Environmental Responsibility (CER) decision context, this study presents a database-driven, Analytic Hierarchy Process (AHP)-weighted multicriteria scoring model applied to an archival dataset of 73 commercial densification systems from 19 manufacturers, accessed primarily in December 2016. The sample comprised 29 hydraulic briquetting, 23 mechanical briquetting, 19 rotary pelletizing, and two ring-die pelletizing systems. Three database-derived class-level criteria were used: median nominal specific installed power (NSIP), interpreted only as a capacity-normalized nameplate-power proxy; median maximum declared production capacity; and mean declared feedstock-category breadth. Three author-defined normative weighting scenarios emphasized NSIP, production capacity, and declared feedstock breadth, respectively. The predefined pairwise-comparison matrices were internally consistent (λmax = 3.0183, CI = 0.00915, CR = 0.01577). Mechanical briquetting ranked first in the NSIP-priority and production-capability scenarios (0.7665 and 0.8635), whereas hydraulic briquetting ranked first in the feedstock-breadth scenario (0.6297). Under ±20% one-at-a-time weight perturbations, the baseline winner was retained in 83.3%, 100%, and 66.7% of variants for S1, S2, and S3, respectively. These rankings are illustrative outcomes of an archival screening model, not evidence of actual energy efficiency, CER performance, economic feasibility, or investment superiority; current operational, cost, emissions, reliability, local-feedstock, and stakeholder data are required for project-specific decisions.