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In-Depth Information
Chapter 13
A Geostatistically
Based Probabilistic Risk
Assessment Approach
Claudia Cherubini
Politecnico di Bari, Italy
ABStrAct
Most data required for cleanup risk assessment are intrinsically characterized by a high degree of
variability and uncertainty. Moreover, typical features of environmental datasets are the occurrence of
extreme values like a few random 'hot spots' of large concentrations within a background of data below
the detection limit. In the field of environmental pollution risk assessment constitutes a support method
for decisions inherent the necessity to carry out a procedure of remediation of an area. Therefore it would
be adequate to provide the analysis with elements that allow to take into account the nature of the data
themselves, particularly their uncertainty. In this context, this chapter focuses on the application of an
uncertainty modeling approach based on geostatistics for the parameters which enter as input in the
probabilistic procedure of risk assessment. Compared with a traditional approach, the applied method
provides the possibility to quantify and integrate the uncertainty and variability of input parameters in the
determination of risk. Moreover, it has proved to be successful in catching and describing in a synthetic
way the relations and tendencies that are intrinsic in the data set, characteristics that are neglected by
a traditional classical approach.
IntroductIon
reached by means of remediation interventions
for human health protection. Nevertheless, in the
execution of a risk assessment, the required data
are characterized for the most part by a high degree
of variability and in most cases, especially when
a in-depth site assessment study is not carried out,
also by a substantial level of uncertainty. Moreover,
in many environmental applications, a few random
The risk assessment is an efficient decision sup-
port method in the evaluation on the necessity to
remediate a contaminated area; it serves as a tool
for the definition of the concentration value to be
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