Department of Terrestrial Ecology, National Environmental Research Institute, University of Aarhus, Vejlsøvej 25, P.O. Box 314, DK-8600 Silkeborg, Denmark.
Sci Total Environ. 2010 Aug 15;408(18):3852-9. doi: 10.1016/j.scitotenv.2009.11.010. Epub 2009 Nov 27.
This paper helps bridge the gap between scientists and other stakeholders in the areas of human and environmental risk management of chemicals and engineered nanomaterials. This connection is needed due to the evolution of stakeholder awareness and scientific progress related to human and environmental health which involves complex methodological demands on risk management. At the same time, the available scientific knowledge is also becoming more scattered across multiple scientific disciplines. Hence, the understanding of potentially risky situations is increasingly multifaceted, which again challenges risk assessors in terms of giving the 'right' relative priority to the multitude of contributing risk factors. A critical issue is therefore to develop procedures that can identify and evaluate worst case risk conditions which may be input to risk level predictions. Therefore, this paper suggests a conceptual modelling procedure that is able to define appropriate worst case conditions in complex risk management. The result of the analysis is an assembly of system models, denoted the Worst Case Definition (WCD) model, to set up and evaluate the conditions of multi-dimensional risk identification and risk quantification. The model can help optimize risk assessment planning by initial screening level analyses and guiding quantitative assessment in relation to knowledge needs for better decision support concerning environmental and human health protection or risk reduction. The WCD model facilitates the evaluation of fundamental uncertainty using knowledge mapping principles and techniques in a way that can improve a complete uncertainty analysis. Ultimately, the WCD is applicable for describing risk contributing factors in relation to many different types of risk management problems since it transparently and effectively handles assumptions and definitions and allows the integration of different forms of knowledge, thereby supporting the inclusion of multifaceted risk components in cumulative risk management.
本文有助于弥合化学物质和工程纳米材料人类和环境风险管理领域科学家与其他利益相关者之间的差距。这种联系是必要的，因为利益相关者意识的演变和与人类和环境健康相关的科学进展涉及到风险管理的复杂方法要求。同时，可用的科学知识也越来越分散在多个科学学科中。因此，对潜在风险情况的理解越来越多面化，这再次对风险评估人员提出了挑战，需要对众多相关风险因素给予“正确”的相对优先级。因此，一个关键问题是开发能够识别和评估可能输入风险水平预测的最坏情况风险条件的程序。因此，本文提出了一种概念建模程序，能够在复杂的风险管理中定义适当的最坏情况条件。分析的结果是一个系统模型的集合，称为最坏情况定义（WCD）模型，用于建立和评估多维风险识别和风险量化的条件。该模型可以通过初始筛选水平分析帮助优化风险评估计划，并指导与知识需求相关的定量评估，以更好地支持环境和人类健康保护或风险降低方面的决策。WCD 模型通过使用知识图映射原理和技术来评估基本不确定性，从而改进完整的不确定性分析。最终，WCD 适用于描述与许多不同类型的风险管理问题相关的风险促成因素，因为它透明有效地处理假设和定义，并允许不同形式的知识的集成，从而支持在累积风险管理中纳入多方面的风险成分。
