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Title

How to measure uncertainties in environmental risk assassment

AuthorsDarbra, Rosa María; Eljarrat, Ethel CSIC ORCID ; Barceló, Damià CSIC ORCID
KeywordsEnvironmental risk assessment
Fuzzy logic
Monte Carlo
Probability theory
Uncertainty
Issue Date1-Apr-2008
PublisherElsevier
CitationTRAC - Trends in Analytical Chemistry
AbstractEnvironmental risk assessment is an essential element in any decision-making process in order to minimize the effects of human activities on the environment. Unfortunately, often environmental data tends to be vague and imprecise, so uncertainty is associated with any study related with these kind of data.
Essentially, uncertainty in risk assessment may have two origins – randomness and incompleteness. There are two main ways to deal with these uncertainties – probability theory and fuzzy logic.
Probability theory is based on a stochastic approach, using probability functions to describe random variability in environmental parameters.
Fuzzy logic uses membership functions and linguistic parameters to express vagueness in environmental issues.
We discuss the best way to deal with uncertainties in the environmental field and give examples of probabilistic and fuzzy-logic approaches applied to environmental risk assessment.
Description9 pages, 1 figure, 1 table.
Publisher version (URL)http://dx.doi.org/10.1016/j.trac.2008.02.005
URIhttp://hdl.handle.net/10261/27505
DOI10.1016/j.trac.2008.02.005
ISSN0165-9936 (Print)
Appears in Collections:(IDAEA) Artículos

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