Skip to Content
Our misssion: to make the life easier for the researcher of free ebooks.

Quantitative uncertainty and sensitivity analysis

This thesis analyzes the quantitative uncertainty and sensitivity of an intermediate parameter in the OMNIITOX Base Model algorithm which can be used for calculation of characterisation factors to carry out Life cycle assessments (LCA) and Environmental risk assessments (ERA). The quantitative uncertainty of LCA and ERA has been widely recognized, but there exists no estimation of the quantitative uncertainty of the OMNIITOX BM. The purpose of this thesis is to give an example of how large the quantitative uncertainty of an intermediate parameter of OMNIITOX BM can be and which input parameters that contributes the most to this uncertainty. This example could inspire to go further and make a quantitative uncertainty and sensitivity analysis for the complete algorithm, involving all parameters. The methodology that is used in this thesis can be modified to address the issue in more general terms.

First, the intermediate parameter Rate coe cient from air to fresh water in Europe was chosen for further analysis. The uncertainty analysis was limited to the nature specific parameters. For further investigation of the statistical properties of these parameters, the reference chemical Toluene was chosen for the chemical specific input parameters, provided as single point values. The distribution functions for the nature specific input parameters were estimated from information given in literature. A simulation program was implemented in Matlab which runs the algorithm for the chosen intermediate parameter with random numbers from the estimated input parameter distribution functions. The output data was later analyzed with the Matlab-tool d ttool to measure the uncertainty and fit a distribution function to the chosen intermediate parameter. The simulation program also measured the sensitivity of the input parameters with normalized correlation coe cients. The distribution function for the intermediate parameter was later applied to similar intermediate parameters in another simulation program which runs the complete algorithm of OMNIITOX BM. With this program, the uncertainty of the characterisation factors was estimated.

The quantitative uncertainty of the Rate coe cient air to fresh water Europe is remarkably high, with a 95%-confidence interval of [?0.0130, 0.0270], mean = 0.00679 and std = 0.01060 if a normal distribution cut-off fit is chosen for the output data. The input parameters that contributes the most to this uncertainty is Mixing height of air and Particle dry deposition velocity in air. When randomly generating numbers from the distribution function of Rate coe cient air to fresh water Europe in the calculation of characterisation factors, they were insignificantly affected. If an equal distribution was assumed for all rate coe cients as the analyzed intermediate parameter, the uncertainty of the characterisation factors became extremely high.

Download
Quantitative uncertainty and sensitivity analysis