2019-08-25T16:12:55Z
https://digital.csic.es/dspace-oai/request
oai:digital.csic.es:10261/27505
2016-02-16T08:37:44Z
com_10261_5062
com_10261_5
col_10261_5064
How to measure uncertainties in environmental risk assassment
Darbra, Rosa María
Eljarrat, Ethel
Barceló, Damià
Environmental risk assessment
Fuzzy logic
Monte Carlo
Probability theory
Uncertainty
9 pages, 1 figure, 1 table.
Environmental 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.
This Study was funded by the European Union through the projects RISKBASE (GOCE 036938), AQUATERRA (Project number 505428) and by the Spanish Ministry of Education and Science through the project CEMAGUA (CGL2007-64551/HID).
Peer reviewed
2010-09-08T13:12:38Z
2010-09-08T13:12:38Z
2008-04-01
Artículo
TRAC - Trends in Analytical Chemistry
0165-9936 (Print)
http://hdl.handle.net/10261/27505
10.1016/j.trac.2008.02.005
eng
http://dx.doi.org/10.1016/j.trac.2008.02.005
openAccess
139109 bytes
application/pdf
Elsevier