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描述多环芳烃在污染土壤柱中进行非平衡迁移的参数:可估计性分析、相关性及优化

Parameters describing nonequilibrium transport of polycyclic aromatic hydrocarbons through contaminated soil columns: estimability analysis, correlation, and optimization.

作者信息

Ngo Viet V, Michel Julien, Gujisaite Valérie, Latifi Abderrazak, Simonnot Marie-Odile

机构信息

Université de Lorraine, Laboratoire Réactions et Génie des Procédés, UMR 7274, 1 rue Grandville, BP20451, 54001 Nancy Cedex, France; CNRS, Laboratoire Réactions et Génie des Procédés, UMR 7274, 1 rue Grandville, BP20451, 54001 Nancy Cedex, France; Laboratoire d'Hydrologie et de Géochimie de Strasbourg, Université de Strasbourg/EOST, CNRS, 1 rue Blessig, F-67084 Strasbourg Cedex, France.

Université de Lorraine, Laboratoire Réactions et Génie des Procédés, UMR 7274, 1 rue Grandville, BP20451, 54001 Nancy Cedex, France; CNRS, Laboratoire Réactions et Génie des Procédés, UMR 7274, 1 rue Grandville, BP20451, 54001 Nancy Cedex, France; INERIS, Direction des Risques Chroniques, Unité "Comportement des contaminants dans les sols et matériaux", Parc Technologique Alata, BP2, 60550 Verneuil en Halatte, France.

出版信息

J Contam Hydrol. 2014 Mar;158:93-109. doi: 10.1016/j.jconhyd.2014.01.005. Epub 2014 Jan 25.

Abstract

The soil and groundwater at former industrial sites polluted by polycyclic aromatic hydrocarbons (PAHs) produce a very challenging environmental issue. The description of PAH transport by means of mathematical models is therefore needed for risk assessment and remediation strategies at these sites. Due to the complexity of release kinetics and transport behavior of the PAHs in the aged contaminated soils, their transport is usually evaluated at the laboratory scale. Transport parameters are then estimated from the experimental data via the inverse method. To better assess the uncertainty of optimized parameters, an estimability method was applied to firstly investigate the information content of experimental data and the possible correlations among parameters in the two-site sorption model. These works were based on the concentrations of three PAHs, Acenaphthene (ACE), Fluoranthene (FLA) and Pyrene (PYR), in the leaching solutions of the experiments under saturated and unsaturated flow conditions. The estimability results showed that the experiment under unsaturated flow conditions contained more information content for estimating four transport parameters than under the saturated one. In addition, whatever the experimental conditions for all three PAHs the fraction of sites with instantaneous sorption, f, was highly correlated with the adsorption distribution coefficient, Kd. The very strong correlation between the two parameters f and Kd suggests that they should not be simultaneously calibrated. Transport parameters were optimized using HYDRUS-1D software with different scenarios based on the estimability analysis results. The optimization results were not always reliable, especially in the case of the experiment under saturated flow conditions because of its low information content. In addition, the estimation of transport parameters became very uncertain if two parameters f and Kd were optimized simultaneously. The findings of the current work can suggest some reasons behind the optimization problems and indicate the type of experimental information additionally needed for parameter identification. To overcome the parameterization issues of PAH non-equilibrium transport, the experimental design, timescale, and model refinement need further improvement. The conclusions presented in this paper are not limited necessarily to PAHs, but may also be relevant to other organic contaminants with similar leaching behavior.

摘要

受多环芳烃(PAHs)污染的 former industrial sites 的土壤和地下水产生了一个极具挑战性的环境问题。因此,需要通过数学模型来描述 PAH 的迁移,以便对这些 sites 进行风险评估和修复策略制定。由于老化污染土壤中 PAHs 的释放动力学和迁移行为复杂,其迁移通常在实验室规模进行评估。然后通过反演方法从实验数据中估计迁移参数。为了更好地评估优化参数的不确定性,应用了一种可估计性方法,首先研究实验数据的信息含量以及双位点吸附模型中参数之间的可能相关性。这些工作基于饱和和非饱和流动条件下实验浸出液中三种 PAHs,苊(ACE)、荧蒽(FLA)和芘(PYR)的浓度。可估计性结果表明,非饱和流动条件下实验对于估计四个迁移参数比饱和条件下实验包含更多信息含量。此外,无论三种 PAHs 的实验条件如何,具有瞬时吸附的位点分数 f 与吸附分配系数 Kd 高度相关。参数 f 和 Kd 之间的极强相关性表明它们不应同时进行校准。基于可估计性分析结果,使用 HYDRUS - 1D 软件在不同情景下对迁移参数进行了优化。优化结果并不总是可靠的,特别是在饱和流动条件下的实验中,因为其信息含量较低。此外,如果同时优化参数 f 和 Kd,迁移参数的估计会变得非常不确定。当前工作的研究结果可以揭示优化问题背后的一些原因,并指出参数识别额外需要的实验信息类型。为了克服 PAH 非平衡迁移的参数化问题,实验设计、时间尺度和模型改进需要进一步完善。本文给出的结论不一定仅限于 PAHs,也可能与具有类似浸出行为的其他有机污染物相关。

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