Targeting assessment sensitivity analysis

As well as guiding problem formulation, sensitivity analysis can be valuable in optimizing the use of resources. By revealing which uncertainties have the most influence on the results of the assessment, sensitivity analysis can also help target additional research or monitoring and by revealing which of the controllable sources of variability have the most influence, sensitivity analysis can help identify and evaluate practical options for managing risk. 

What are the key sources of uncertainty in the exposure assessment This question can also be posed as Which exposure factors contribute the most to the overall uncertainty in the inventory This insight can be used, in turn, to target resources to reduce the largest and most important uncertainties. There are various ways to answer this question, including various forms of sensitivity analysis. For example, in the context of a probabilistic uncertainty simulation for an overall exposure assessment, various statistical methods can be used to determine which input distributions are responsible for contributing the most to the variance of the output. 

Here the critical process variables are identified from the selected list of process variables. The model library or process data (if available) are used for this analysis. To perform the sensitivity analysis, the process operational model is simulated through ICAS-MoT. The effect of each process variable on the target product properties is analyzed systematically through open loop simulation. The operational objectives have to be assessed first. If an operational objective is not achieved, then the process variables have to be analyzed. The variables which violate the operational limit and have a major effect on the product quality are considered as the critical process variables. For some of the variables which can not be modeled the sensitivity analysis has to be performed qualitatively through inference from the knowledge base and/or by the use of process data. All the critical process variables need to be monitored and controlled. For some of the critical variables that can not be measured in real time, other correlated properties have to be measured so that all critical variables can be measured and controlled by using the correlations to the measurable variables. 

In most cases, the data for a targeting assessment come from a single cross-sectional survey, and hence are insufficient to estimate the MPCT reliably. In such cases, analysts can carry out a sensitivity analysis, estimating the before transfer counterfactual consumption based on a range of possible MPCT values. E. Tesliuc (2004) provides an example of... 

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