Towards Dynamic Life Cycle Assessment of Solar Energy Systems: An IoT Data Infrastructure with Hash-Chained Provenance and Stakeholder-Prioritised Indicators

Life cycle assessment (LCA) of photovoltaic systems rests largely on aggregated, time-invariant inventories. In Colombia, registered solar projects grew by 128.6% between 2018–2022 and 2022–2025, while environmental follow-up remains self-reported and semi-annual. We report IMPACT Energy.CO, a data infrastructure designed to enable dynamic LCA and installed in the production environment of the national hydrocarbons agency. It normalises heterogeneous telemetry onto a versioned vocabulary, hash-chains derived indicators and includes a headless openLCA connector. It was tested before the transfer and its telemetry path was exercised against a test instance only; no field telemetry has entered an inventory and no telemetry-to-openLCA run is evidenced, so the evidence supports an enabling proof of concept. Of 144 candidates, 32 indicators were screened; experts scored all 32 and communities 24. On fifteen shared social indicators, scored with non-equivalent instruments, the two rankings show no resolvable association ($\rho =-0.07$); in exploratory analysis the expert ranking is ordered by stakeholder category (Kendall’s ${\tau }_b=0.63$). Under an explicit criterion, energy and carbon payback time, ranked second and third by the experts, are the only screened environmental indicators an assessment engine cannot return as results. Re-scaling published values of the International Energy Agency Photovoltaic Power Systems Programme to Caribbean irradiance lowers the generation-normalised global warming potential of monocrystalline silicon modules by 32% (95% propagation interval 20–42%), and carbon payback varies three- to four-fold across official grid emission factors.