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5 Uncertainty Assessment

by Monte Carlo

Simulation*

With the contribution of Luiz Alexandre Kulay
and Yolanda Pla

5.1 INTRODUCTION

The high uncertainty present in the implementation of life-cycle and environmental
risk assessment studies introduces a crucial limitation when interpreting the envi-
ronmental impact and damage estimations provided by these methodologies. Within
this particular context this chapter presents a strategic procedure to better deal with
an uncertainty assessment based on the stochastic model of Monte Carlo (MC)
simulation. Initially, we will present an overview about the importance of imple-
menting uncertainty assessments in studies of life-cycle assessment (LCA) and
impact pathway analysis (IPA). Then, the basic statistical concepts related to MC
simulation are introduced. This section also compares some of the best known
commercial software packages that apply MC simulation to uncertainty evaluation.
The third section describes the core of the uncertainty assessment strategic proce-
dures. Finally, in the last section, we will use the municipal solid waste incineration
process (MSWI) in Tarragona, Spain, as the practical case study of risk assessment
for explaining the procedure better.

5.2 TYPES OF UNCERTAINTIES IN ENVIRONMENTAL
IMPACT ANALYSIS
The various sources of uncertainty in environmental impact analysis can be system-
atically classified in accordance with the following categories (Huijbregts, 1998).

5.2.1 PARAMETER UNCERTAINTY

A life-cycle inventory (LCI) analysis and the models that calculate fate, exposure
and effect within an impact and risk assessment usually need a large amount of data.

* Extracts of this chapter are reprinted from Environment International, 28, Sonnemann, G.W., Pla, Y.,
Schuhmacher, M., and Castells, F., pp. 9–18, 2002a; and Journal of Cleaner Production 11, Sonnemann,
©
G.W., Schuhmacher, M., and Castells, F., pp. 279–292, 2002b. 2002 with permission from Elsevier.

© 2004 CRC Press LLC