Null-Space Monte Carlo Particle Backtracking to Identify Groundwater Tetrachloroethylene Sources
Null-Space Monte Carlo Particle Backtracking to Identify Groundwater Tetrachloroethylene Sources
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DOI：
10.3389/fenvs.2020.00142
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发表时间：
2020-09
期刊：
影响因子：
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通讯作者：
L. Colombo;L. Alberti;Pietro Mazzon;M. Antelmi
中科院分区：
文献类型：
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作者：
L. Colombo;L. Alberti;Pietro Mazzon;M. Antelmi
地球仪大多数城市地区的地下水经常受到有毒物质的污染。在各种污染源中，工业造成的影响最大，因为有毒化合物主要通过泄漏的储罐或管道释放到地下。一些污染物（通常是氯化碳氢化合物）往往会在地下持续存在，难以生物降解。因此，几十年前泄漏的物质仍在影响地下水。米兰及其周边地区（功能性城市区）是一个很好的例子，该地区在世纪以来一直拥有各种规模的工业，其中许多工业导致氯化烃污染地下水。虽然最大的工业设施的位置是众所周知的，但在许多情况下，在没有进行直接调查的情况下，很难确定许多较小的来源。此外，地下水污染的大、小、已知和未知来源的重叠影响使得确定每一种来源的贡献具有挑战性。为了确定负责公共供水威尔斯，数值模型（MODFLOW-2005）的四氯乙烯污染的几个点源的贡献已经实施和校准使用PEST在米兰功能区的西北部。在污染物输运模拟中，确定性方法由于其应用的简单性仍然比随机方法更受青睐。然而，后者被认为是最适合于处理具有高度不确定性的问题，如水文地质参数分布。采用零空间蒙特卡罗分析，400套不同的水力传导系数场随机产生，其中只有336个选择使用目标函数阈值。随后，通过将颗粒置于污染井中，对每个公认的水力传导系数场进行颗粒回溯。颗粒通过的数量被认为与每个未知点源对目标孔中识别的四氯乙烯污染的贡献成比例。该研究提供了一种方法，以帮助公共当局找到负责在地下水中检测到的四氯乙烯污染的“更可能”的区域，并集中在米兰的特定部门的环境调查。
Groundwater in most urban areas around the globe is often contaminated by toxic substances. Among the various sources of contamination, industries cause the heaviest impact when toxic compounds are released underground, mainly through leaking tanks or pipelines. Some contaminants (typically chlorinated hydrocarbons) tend to persist within the underground and are hard to biodegrade. As a result, substances that leaked decades ago are still impacting groundwater. Milano and its surroundings (Functional Urban Area) is a good example of an area that has been hosting industries of all dimensions for over a century, many of them contributing to groundwater contamination from chlorinated hydrocarbons. While the position of the biggest industrial facilities is well-known, many smaller sources are hard to identify in many cases where direct surveys have not been undertaken. Furthermore, the overlapping effects of big, small, known, and unknown sources of groundwater contamination make it challenging to identify the contribution of each. In order to identify the contribution of several point sources responsible for tetrachloroethylene contamination in public water supply wells, a numerical model (MODFLOW-2005) has been implemented and calibrated using PEST in the northwestern portion of the Milano Functional Urban Area. In contaminant transport modeling, the deterministic approach is still favored over the stochastic approach because of the simplicity of its application. Nevertheless, the latter is considered by the authors as the most suitable for dealing with problems characterized by high uncertainty, such as hydrogeological parameter distributions. Adopting a Null-Space Monte Carlo analysis, 400 different sets of hydraulic conductivity fields were randomly generated of which only 336 were selected using an objective function threshold. Subsequently, particle backtracking was performed for each of the accepted hydraulic conductivity fields, by placing particles in a contaminated well. The number of particle passages is considered as being proportional to the contribution of each unknown point source to the tetrachloroethylene contamination identified in the target well. The study provides a methodology to help public authorities to locate the “more probable than not” area responsible for the tetrachloroethylene contamination detected in groundwater and to focus environmental investigations in specific sectors of Milano.