This technical report documents an initial, working implementation of a Bayesian framework for balancing BONSAI – a large hybrid Supply-Use Table (HSUTs), developed in the “Getting the Data Right” project.
The aims are twofold: Firstly, to demonstrate feasibility and scalability. The current Stan im- plementation successfully balances HSUTs with more than 1.8 Million flows on a High Performance Cluster and produces posterior samples that can in principle be propagated to environmental footprints. The second aims of this report is to make assumptions and simplifications trans-parent. Several aspects of the model are deliberately simple (e.g. data-driven priors for flows, global uncertainty parameters for transfer coefficients and conversion factors, a basic set of soft constraints). These choices are documented, together with ideas for how they could be refined.
The report and the results should therefore be read as a proof-of-concept and technical baseline, rather than a final, fully validated methodology.
