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it is the result of normalization and weighting

what does it mean

in openLCA by (320 points)

2 Answers

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by (125k points)
This is the normalised value of impact assessment: impact assessment result divided by the normalisation value, dimensionless.
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by (8.0k points)
Also to add to Andreas's comment, the normalization shows you which impact category has the biggest impact, on the same scale.

Normalization factors can be "How much impact does an average world citizen create during a year", etc.

This shows you that one impact category: Marine ecotoxicity is much more impactful than the other impact categories. I would recommend weighting the scores also, to get a more complete result. Normalized scores are hard to interpret.

By going into the results of your system under contribution analysis, you can track which processes contribute the most to marine ecotoxicity, to understand why the impact is so high.

Good luck
by (7.0k points)
edited by
Hey Matias, thank you for the comment. I also want to add that one has to be careful with weighting, since it can be based on polls, decisions for maturity levels of a method and can be subjective. Normalisation at least is based on fixed numbers from the total emissions and the total population in a given reference year. As an example, weighting in EF 3.1 can lower the toxicity impact categories quite strong for the single score, because USEtox got a very low maturity factor (numbers are still from 2015 I think). But one will lose informations on the toxicity. So it is better to avoid weighting if possible. And maybe using normalisation only to make some rough decisions on impact contributions, but to report always impact values without normalisation and weighting and just see the normalisation/weighting as an additional "nice to have". Of course, sometimes the rules are set due to compliance and normalisation/weighting factos can also differ a lot on how they are created for different methods. It's just an example how these factors can lead to wrong conclusions.
by (8.0k points)
Hello Conrad, this is as well a preference :)
I personally believe weighting can give very useful results. When you take only normalized results, you are also applying a default weighting, that dictates that each impact category is equally important. I do not agree with this "equal weighting" apporach to normalized scores, personally.
There are many arguments for and against each weighting method, but i believe weighting certainly has its uses, and should not be discounted as a tool.
But also yes, the PEF weighting has a lot going against it. I hope they will adress some of the more serious concerns in a new iteration of weighting factors.
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