Uncertainty assessment of VOC emissions from paint in The Netherlands using the NUSAP system.

We demonstrate an innovative approach to uncertainty assessment known as the NUSAP system, to assess qualitative and quantitative uncertainty for the case of emissions of volatile organic compounds (VOC) from paint in The Netherlands. Using expert elicitation, we identified key sources of error, critical assumptions, and bias in the monitoring process. We assessed pedigree and probabilistic uncertainty of all input quantities. We used four pedigree criteria to assess the strength of the knowledge base: proxy representation, empirical basis, methodological rigour and degree of validation. Using Monte Carlo analysis, we assessed sensitivity and propagation of uncertainty. Results for sensitivity and pedigree were combined in a 'NUSAP Diagnostic Diagram', which effectively highlighted the assumption for VOC percentage of imported paint as the weakest spot in the monitoring of VOC emissions. We conclude that NUSAP facilitates systematic scrutinization of method and underlying assumptions and structures creative thinking on sources of error and bias. It provides a means to prioritise uncertainties and focus research efforts on the potentially most problematic parameters and assumptions, at the same time identifying specific weaknesses in the knowledge base. With NUSAP, nuances of meaning about quantities can be conveyed concisely and clearly, to a degree that is not possible with statistic methods only.

Combining quantitative and qualitative measures of uncertainty in model-based environmental assessment: the NUSAP system.

This article discusses recent experiences with the Numeral Unit Spread Assessment Pedigree (NUSAP) system for multidimensional uncertainty assessment, based on four case studies that vary in complexity. We show that the NUSAP method is applicable not only to relatively simple calculation schemes but also to complex models in a meaningful way and that NUSAP is useful to assess not only parameter uncertainty but also (model) assumptions. A diagnostic diagram can be used to synthesize results of quantitative analysis of parameter sensitivity and qualitative review (pedigree analysis) of parameter strength. It provides an analytic tool to prioritize uncertainties according to quantitative and qualitative insights in the limitations of available knowledge. We show that extension of the pedigree scheme to include societal dimensions of uncertainty, such as problem framing and value-laden assumptions, further promotes reflexivity and collective learning. When used in a deliberative setting, NUSAP pedigree assessment has the potential to foster a deeper social debate and a negotiated management of complex environmental problems.