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Hello everyone,

I am trying to run a Monte Carlo Simulation. At first, I have determined the uncertainty distribution for all input-flows by using the pedigree matrix approach.

When I run the MCS, I only receive results, for the emissions (output flows) that are dependent from the input-flows (which makes absolutely sense to me).

My question is, do I also have to assign uncertainty distributions to direct emissions (output flows), since they are not connected via parameters to the input flows?

And what about product and reference flows (output flows)?

If yes, can you please explain why I must do this? It does not make sense to me in context of the MCS…

 

Thank you for your help!

Best, Leoni

in openLCA by (140 points)

1 Answer

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by (69.6k points)
Hi Leoni,

welcome - well also emissions e.g. as output flows can be uncertain, and openLCA calculates the overall emissions for your system under study, and obtains a final aggregated result for the emission flows which is also uncertain. This speaks for specifying uncertainty also for output flows.

The only point is that some emissions depend directly on input flows (CO2 emissions from driving a car on the fuel consumed, e.g.) which is typically not reflected in LCA datasets, and thus these flows are simulated indepenently, which overestimates the uncertainty for them. Since this dependency applies only for some cases, I would say it is still ok to consider that output flows are uncertain.

Quantitative references: the entire process data set is scaled to the amount of the qr, so this one amount is not uncertain because it is decided by the modeler or the dataset creator.

Best wishes,

Andreas
by (140 points)
Hi Andreas,

thank you very much for your detailed response.
Your support is really appreciated!

Best regards,
Leoni
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