• Creating graphical models with processes, flows, stocks, subsystems, text fields, system boundary and legend (best practice examples).
  • Using multiple data layers (goods, substances, energy).
  • Considering multiple periods of time.
  • Using subgoods (sum of subgoods = good) instead of substances (sum of considered substances ≤ good).
  • Manual entry of data (masses, volumes, energies, concentrations, transfer coefficients).
  • Semi-automatical import/export of data by using MS Excel as interface.
  • Using predefined or user defined units (for mass, volume, energy and time).
  • Considering data uncertainties (assumed to be normally distributed).
  • Documentation of components and values used in the STAN model (e.g. the source of data).
  • Performing calculations by using mathematical statistical tools such as nonlinear data reconciliation (to adjust conflicting measurements or estimates) and error propagation (to compute the uncertainty of unknown quantities that can be calculated).
  • Detecting errors in a model.
  • Scaling MFA results with respect to the sum of imports flows, the sum of export flows or an arbitrary chosen factor.
  • Displaying the results of the MFA as Sankey-style diagram.
  • Exporting system graphs in various graphical formats.
  • Accessing and using the database of STAN files on www.stan2web.net.

Exercises covered:

  • Regional Material Flow Analysis (basic MFA)
  • Regional Glass Bottle Household (subsystems and scaling of data)
  • Waste Management Strategy (scenario analysis with subsystems)
  • Waste Incineration Plant (substance flow analysis for Cd, importing data, data reconciliation)
  • MFA on Company Level (error propagation)
  • Regional Phosphorous Fluxes (challenging substance flow analysis)
  • Costs & Money (using the energy layer to model money flows)
  • MFA with Subgood Layers (using subgoods)
  • Error Finding Mission (strategies to detect errors)
  • Stock Modelling (combing Excel and STAN models)


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