Data Sheet 1_The food-system carbon data layer: integrating automated life-cycle-assessment digital twins into urban digital twins.pdf

We advance a two-part hypothesis: that the integration is analytically feasible on publicly available life cycle inventory data, and that its operational viability is governance-dependent under emerging regulatory instruments. The framework addresses four challenges: boundary alignment between cradle-to-gate product carbon footprint models and urban metabolism accounting; uncertainty propagation from inventory data-gap proxies and machine learning classifiers through to city-scale dashboards, preserving producer-level variance rather than collapsing it into ordinal grades; semantic harmonization across the vocabularies of procurement records, supplier bills of materials and inventory databases; and human-centered representation for planners, procurement officers and public health authorities with heterogeneous data literacy.

Four worked urban use cases on publicly available inventory data illustrate the framework, and we specify the interoperability conditions for viable integration. The use cases establish analytical feasibility, meaning the architecture is specifiable and computable on open data; they are not an empirical validation against a deployed urban digital twin, which we identify as the next required step. H1 is stated with four checkable success criteria, two carrying declared numerical thresholds, and H2 with the panel that would test it.</p>