2.1 Spatial Synthesis and Geographical Information Mapping
A rigorous evaluation of industrial decarbonization within topographically constrained regions necessitates moving beyond conventional sectoral classifications toward a spatially resolved cluster taxonomy [2]. By categorizing heavy industrial installations according to geographical proximity and localized energy exchanges, this methodological approach captures thermodynamic interactions and infrastructural synergies that traditional macro-level models overlook [2]. Spatial boundaries are demarcated around contiguous industrial valleys to assess aggregate thermal demands, shared logistical corridors, and potential common-carrier hydrogen infrastructure [5]. The analytical architecture applies multi-criteria comparative assessment across published industrial datasets, evaluating primary emissions profiles, high-enthalpy heat requirements, and proximity to regional electrical transmission corridors [2]. Rather than assuming uniform fuel switching across all manufacturing facilities, the model classifies processes into distinct tiers based on whether hydrogen serves as a chemical feedstock, a high-temperature combustion agent, or an auxiliary carrier for co-located heavy freight operations [5]. Integrating these spatial classifications allows the systematic comparison of localized decentralized generation against centralized pipeline import pathways, ensuring that topographical obstacles and grid limitations typical of Alpine terrain are rigorously incorporated into the feasibility assessment [2].