4.7 Article

Extended environmental multimedia modeling system assessing the risk carried by pollutants in interacted air-unsaturated-groundwater zones

期刊

JOURNAL OF HAZARDOUS MATERIALS
卷 381, 期 -, 页码 -

出版社

ELSEVIER
DOI: 10.1016/j.jhazmat.2019.120852

关键词

Extended environmental multimedia modeling system (EEMMS); Groundwater; Unsaturated -saturated system interaction; Monte carlo method (MCM); Risk quotient (RQ); Risk assessment tool; Landfill leachate

资金

  1. Discovery Grant of Natural Sciences and Engineering Research Council of Canada (NSERC) [RGPIN/156161]
  2. Fuling District Science and Technology Planning Project [FLKJ,2018BBB3017]

向作者/读者索取更多资源

Simulation of the transport of hazardous pollutants in a variety of media is a challenge. In this paper, a novel Extended Environment Multimedia Modeling and Analysis System (EEMMS) for migration of pollutants from landfill through unsaturated site to groundwater is presented. The developed EEMMS consists of four pathways modules: air, landfill, unsaturated zone and groundwater zone. The finite element method in EEMMS framework is used to analyze these four pathways and the results are compared to the finite difference model and analytical model. The effectiveness of EEMMS has been verified through a case study of Trail Road landfill site. The simulation of uncertainty was conducted with a quantitative technique of Monte Carlo Method. The Risk Quotient (RQ) results show that the low-risk area covers 10,000 square meters, where the predicted concentrations of benzene are between 1 and 1.2 mu g L-1. However, the high-risk area covers almost 200,000 square meters. Contrary to FEM, the majority of the FDM and analytical predictions were too high and fell outside the high boundary of the experimental result. The EEMMS is a unique risk assessment tool that can be used for impacts on water resource quality, biodiversity, fate of pollutants in ecosystem, climate change, etc.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据