检查现场干预的有效性和概念贝叶斯网络的不确定性:防止DNAPL和受污染的地下水在现场之外迁移
John F Carriger1, Michael C Brooks2, Carolyn Acheson3
1Office of Research and Development, Center for Environmental Solutions and Emergency Response, Land Remediation and Technology Division, US Environmental Protection Agency, Cincinnati, OH, USA. carriger.john@epa.gov.
概括
概念贝叶斯网络 (CBN) 增强了概念现场模型 (CSM),用于评估和管理受污染的现场. 这些网络澄清了致病关系,以有效地修复密度非水相液体 (DNAPL) 场所.
科学领域:
- 环境科学 环境科学
- 风险评估 风险评估
- 因果推理因果推理
背景情况:
- 概念现场模型 (CSM) 对于管理受污染现场和指导整治至关重要.
- 传统的CSM可以通过结构因果建模来增强,以改善风险评估.
- 密集非水相液体 (DNAPLs) 在地下污染方面存在复杂的挑战.
研究的目的:
- 引入和探索概念贝叶斯网络 (CBN) 作为对传统CSM的进步.
- 证明CBN在理解DNAPL现场修复的因果关系方面的实用性.
- 为环境风险评估提供CBN的新扩展.
主要方法:
- 通过将结构因果建模与CSM集成来开发概念贝叶斯网络 (CBNs).
- 在CBN中包括修改变量,因果路径分析和干预措施.
- 探索扩展,例如将测量变量表示为证据线,并与图像CSM对齐.
主要成果:
- 对于DNAPL站点,CBN可以更清楚地说明源条款,迁移和修复效率之间的因果关系.
- 包括因果路径分析和干预措施在内,为网站动态提供了更强大的理解.
- 扩展允许更好地整合各种数据,并与现有的建模实践保持一致.
结论:
- 概念贝叶斯网络 (CBN) 是一个强大而可适应的工具,用于在地下修复中的知识表示.
- 与传统的CSM相比,CBN显著改善了因果关系的表征,特别是对于复杂的DNAPL站点.
- 进一步扩展CBN有望加强环境风险评估和地下水建模.
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