2.2 Analytical Taxonomy for Industrial Cluster Emissions
This study establishes an analytical taxonomy to evaluate deep decarbonization across hard-to-abate industrial installations through spatial clustering and techno-economic optimization. Methodologically, shifting from conventional sectoral classifications to geographically aggregated cluster models captures plant-level energy consumption and localized emissions while accounting for infrastructure economies of scale ("Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry," 2022). By utilizing geographical information system mapping to identify spatial adjacencies, the evaluation protocol models localized energy sources and sinks, facilitating sectoral coupling between manufacturing facilities and regional logistics networks ("Taxonomy for Industrial Cluster Decarbonization: An Analysis for the Italian Hard-to-Abate Industry," 2022). Furthermore, the framework incorporates an integrated resource optimization module that models cost-optimal transition pathways for heavy industrial manufacturing, explicitly focusing on cement, methanol, and primary materials ("Integrated Decarbonization of Hard-to-Abate Industry Utilizing Biomass Reliefs Burden on Power Sector," 2024). This optimization protocol evaluates the deployment of carbon capture, transport, and storage infrastructure alongside biomass feedstocks and low-carbon hydrogen, assessing the operational impacts of alternative feedstock allocations on power sector electricity demands ("Integrated Decarbonization of Hard-to-Abate Industry Utilizing Biomass Reliefs Burden on Power Sector," 2024). Additionally, the comparative framework incorporates policy intervention dimensions to assess how regulatory instruments and clean technology commercialization mechanisms support drop-in and material-specific technological substitutions ("Decarbonizing Industry: Policy Approaches to Eliminate Hard-to-Abate Emissions," 2024). Through this combined spatial and techno-economic structure, the research establishes a robust protocol for assessing heavy industrial transformation in sovereign transition contexts.