The role of forensic science in the generation of intelligence to address environmental water contamination problems

IF 2.1 Q1 CRIMINOLOGY & PENOLOGY WIREs. Forensic science Pub Date : 2023-09-09 DOI:10.1002/wfs2.1499
Nicolas Estoppey, Fabienne Pfeiffer, Vick Glanzmann, Naomi Reymond, Ines Tascon, Sofie Huisman, William Lacour, Olivier Ribaux, Céline Weyermann
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Abstract

Abstract Water contamination is a growing concern in society. New environmental laws are being enacted to define intolerable human activities, and their enforcement is increasingly supported by forensic science. However, water contamination is a broader security issue that is not only caused by illegal human behavior. Risk‐based approaches are needed to prevent (re)occurrence of incidents and minimize their negative consequences. This can be achieved through the formalization of a monitoring process producing intelligence (i.e., actionable knowledge), crucial to detect recurring incidents, and guiding decision‐makers in their choice of preventive and responsive actions. In this perspective, forensic science has a key role to play in integrating vestiges from water‐contaminating activities (i.e., traces) in such a problem‐solving process. Information conveyed by traces allows detecting similarities among contamination events (i.e., patterns), inferring common causes, and better understanding of mechanisms and consequences of water contamination. The different stages of the process will be described and illustrated through a real case example. Current barriers to the implementation of such a process are then discussed, showing how systemic issues and complexity may prevent the establishment of links across contamination events, thus negatively impacting the generation of intelligence. To overcome these obstacles, we underline the importance to initiate local and size‐limited approaches by implementing relatively simple and flexible systems. New knowledge can be used to improve local situations and help stakeholders to understand the benefits of such a process; then, by a bottom‐up iterative learning process, the approach can be given a greater ambition at a larger scale. This article is categorized under: Forensic Science in Action/Crime Scene Investigation > Special Situations and Investigations Crime Scene Investigation > From Traces to Intelligence and Evidence Forensic Chemistry and Trace Evidence > Forensic Food and Environment Analysis
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法医学在解决环境水污染问题的智能生成中的作用
水污染是社会日益关注的问题。正在制定新的环境法来界定不可容忍的人类活动,其执行越来越多地得到法医科学的支持。然而,水污染是一个更广泛的安全问题,不仅仅是由人类的非法行为造成的。需要基于风险的方法来防止(再次)发生事件并尽量减少其负面后果。这可以通过产生情报(即可操作的知识)的监测过程的正规化来实现,这对于发现反复发生的事件至关重要,并指导决策者选择预防和响应行动。从这个角度来看,在解决问题的过程中,法医科学在整合水污染活动的痕迹(即痕迹)方面发挥着关键作用。通过痕迹传递的信息可以发现污染事件之间的相似性(即模式),推断共同原因,并更好地了解水污染的机制和后果。该过程的不同阶段将通过实际案例进行描述和说明。然后讨论了目前实施这一过程的障碍,显示了系统问题和复杂性如何阻止在污染事件之间建立联系,从而对智能的产生产生负面影响。为了克服这些障碍,我们强调通过实施相对简单和灵活的系统来启动局部和规模有限的方法的重要性。新知识可用于改善当地情况,并帮助利益攸关方了解这一进程的好处;然后,通过自下而上的迭代学习过程,该方法可以在更大的范围内获得更大的抱负。本文分类如下:行动中的法医学/犯罪现场调查>特殊情况与调查犯罪现场调查从痕迹到情报与证据法医化学与微量证据法医食品与环境分析
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