Uncertainty propagation methods in dioxin/furans emission estimation models

Abstract : In this paper we propose a comparison between two different approaches for uncertainty propa-gation in Environmental Impact Assessment (EIA) procedures. Both a purely Probabilistic (PMC) and a Hy-brid probabilistic-possibilistic Monte Carlo method (HMC) are applied on an estimation model of dio-xin/furans emission from a waste gasification plant. The analysis shows that when input variables affected by scarcity of information are present, HMC seems to be a valid alternative method that properly propagates un-certainty from data to output avoiding arbitrary and subjective assumptions on the input probability distribu-tion functions. HMC could improve the transparency of the EIA procedure with positive effects on the com-municability and credibility of its predictions.
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G. Ripamonti, G. Lonati, Piero Baraldi, F. Cadini, Enrico Zio. Uncertainty propagation methods in dioxin/furans emission estimation models. ESREL 2011, Sep 2011, Troyes, France. pp.2222 - 2229. ⟨hal-00658104⟩

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