Hello Everyone,
I am currently conducting a sensitivity analysis for a Life Cycle Assessment (LCA) study and have encountered an intriguing issue. During the analysis, I observed an inconsistent shift in one direction for a specific parameter on the tornado plot. Specifically:
Increasing the parameter by 10% resulted in a 45% increase in the overall output model.
Decreasing the parameter by 10% led to a 25% increase in the overall output model.
These results seem counterintuitive to me. Does this behavior make sense within the context of sensitivity analysis? Has anyone experienced similar findings or can provide insights into this phenomenon?
Additionally, if you know of any articles or literature that discuss such anomalies in sensitivity analysis, I would greatly appreciate it if you could share them with me.
Thank you for your assistance!
Dear Adam
Very interesting what you say, but I am afraid that it is not clear enough.
First, what are you trying to demonstrate doing a sensitivity analysis(SA) in LCA. Are you stydying different products and their LCA?
What is what you call 'parameter'? In SA you work with alternatives and criteria and what you increase are some of the criteria
What is the 'overal output'? Is that the ranking of alternatives? And how do you measure the output?
Are you suing the same 'parameter' for both increases?
I am very interested in this problem, thank you for your answer
I like that result. It must be correct. It is exciting to try to develop a hypothesis to explain it! :)
Interesting Andrew
Could you please let us know how you reach that comclusion?
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