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Hello GreenDelta team,

I'm a new OpenLCA user and I bought the ECOINVENT 3.9.1 database. I noticed that for processes that have waste output flows, the value of the geometric mean, present in the uncertainty distribution, is negative. This causes problems in Monte Carlo analysis. Is there a way to work around this problem? There will be updates that will fix this bug.

Thanks for the reply
in openLCA by (300 points)

3 Answers

0 votes
by (107k points)
edited by

Yes you are right! This is indeed a bug and we'll fix it.

In meantime, if you want, this changes the sign for negative geometric means:

update tbl_exchanges set PARAMETER1_VALUE = PARAMETER1_VALUE*(-1) where PARAMETER1_VALUE < 0 and DISTRIBUTION_TYPE = 1

Edit: Apply this via

in openLCA, copy into the sql window and then execute:

by (300 points)
Does this mean that the statistical analysis with the montecarlo method is quite inaccurate? I was expecting means/medians close to my calculation value and small standard deviation values.
Presenting such a calculation in a report, I think it's a sign of big errors, isn't it?

Thanks for the reply
0 votes
by (300 points)

Dear GreenDelta Team,

even using the script, the results of the analysis and those of the Montecarlo analysis, for a process already present and set within the database, are clearly different.

The analysis gives a result of 5.508 Kg CO2 eq, while the Montecarlo analysis gives a result of -1.100E9. I would like to understand why this happens.

Thanks in advance

I attach the images.

by (300 points)
Dear Andreas thanks for the updates
0 votes
by (2.9k points)

As Andreas wrote in the last comment, we spoke with ecoinvent and we will upload a revised version of the database to Nexus in the following days and send a communication.

We did a quick analysis with the revised version of the example that you posted. Since the impact method is not know from your picture, EF 3.1 is chosen, which also contains your selected impact category "climate change - global warming potential (GWP100)".


Results in the revised version:

Standard Calculation: Result 5.597

Monte Carlo Simulation: Mean 5.862, Median 5.849, Standard deviation 0.283, 5% Percentile 5.440, 95% Percentile 6.338

by (300 points)
Thanks a lot, Mr. Conrad Spindler. We look forward to the next release!!!