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模型化分配和去除雨水滞留池和生物过滤器中重金属(Cu、Zn)的不确定性量化。

Quantification of uncertainty in modelled partitioning and removal of heavy metals (Cu, Zn) in a stormwater retention pond and a biofilter.

机构信息

Department of Environmental Engineering (DTU Environment), Technical University of Denmark, Building 113, Miljoevej, 2800 Kgs. Lyngby, Denmark.

出版信息

Water Res. 2012 Dec 15;46(20):6891-903. doi: 10.1016/j.watres.2011.08.047. Epub 2011 Sep 1.

Abstract

Strategies for reduction of micropollutant (MP) discharges from stormwater drainage systems require accurate estimation of the potential MP removal in stormwater treatment systems. However, the high uncertainty commonly affecting stormwater runoff quality modelling also influences stormwater treatment models. This study identified the major sources of uncertainty when estimating the removal of copper and zinc in a retention pond and a biofilter by using a conceptual dynamic model which estimates MP partitioning between the dissolved and particulate phases as well as environmental fate based on substance-inherent properties. The two systems differ in their main removal processes (settling and filtration/sorption, respectively) and in the time resolution of the available measurements (composite samples and pollutographs). The most sensitive model factors, identified by using Global Sensitivity Analysis (GSA), were related to the physical characteristics of the simulated systems (flow and water losses) and to the fate processes related to Total Suspended Solids (TSS). The model prediction bounds were estimated by using the Generalized Likelihood Uncertainty Estimation (GLUE) technique. Composite samples and pollutographs produced similar prediction bounds for the pond and the biofilter, suggesting a limited influence of the temporal resolution of samples on the model prediction bounds. GLUE highlighted model structural uncertainty when modelling the biofilter, due to disregard of plant-driven evapotranspiration, underestimation of sorption and neglect of oversaturation with respect to minerals/salts. The results of this study however illustrate the potential for the application of conceptual dynamic fate models base on substance-inherent properties, in combination with available datasets and statistical methods, to estimate the MP removal in different stormwater treatment systems and compare with environmental quality standards targeting the dissolved MP fraction.

摘要

从雨水排水系统减少微污染物(MP)排放的策略需要准确估计雨水处理系统中潜在的 MP 去除量。然而,影响雨水径流水质建模的高不确定性也会影响雨水处理模型。本研究通过使用概念性动态模型,确定了估算储留池和生物滤池内铜和锌去除量的主要不确定性来源,该模型估计了 MP 在溶解相和颗粒相之间的分配以及基于物质固有特性的环境归宿。两个系统的主要去除过程(分别为沉降和过滤/吸附)和可用测量的时间分辨率(综合样本和污染图)不同。通过全局敏感性分析(GSA)确定的最敏感模型因子与模拟系统的物理特性(流量和水损失)以及与总悬浮固体(TSS)相关的归宿过程有关。通过广义似然不确定性估计(GLUE)技术估计了模型预测范围。对于池塘和生物滤池,复合样本和污染图产生了相似的预测范围,表明样本的时间分辨率对模型预测范围的影响有限。GLUE 突出了在生物滤池建模时模型结构不确定性,这是由于忽略了植物驱动的蒸散作用、对吸附作用的低估以及对矿物质/盐类的过饱和现象的忽视。然而,本研究的结果说明了基于物质固有特性的概念性动态归宿模型与可用数据集和统计方法相结合,应用于估算不同雨水处理系统中 MP 去除量并与针对溶解 MP 部分的环境质量标准进行比较的潜力。

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