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Analysis of the fate and transport of nC_(60) nanoparticles in the subsurface using response surface methodology

机译:使用响应面法分析nC_(60)纳米粒子在地下的命运和迁移

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摘要

Predicting the distribution of engineered nanomaterials (ENMs) in the environment will provide critical information for risk assessment and policy development to regulate these emerging contaminants. The fate and transport of ENMs in natural subsurface environments are complicated by various factors, such as hydraulic gradient, initial release concentration, nanoparticle size, and collision efficiency factor. Based on advanced statistical methodologies (i.e., response surface methodology (RSM)), we explore simple relationships between key factors that control ENM transport (collision efficiency factor, particle size, hydraulic gradient, and initial release concentration) and key parameters that describe the ENM concentration distribution in porous media (maximum standardized concentration, the mass percentage of injected nanoparticle attached in the aquifer, the x-centroid of aqueous phase nC_(60) plume, and the x-centroid of attached phase nC_(60) distribution). Hypothetical scenarios for the release of nanoparticles into an aquifer were simulated numerically with randomly generated permeability fields that were based on mildly and highly heterogeneous sites. RSM was used to develop polynomial regression equations based on a statistical experimental design. High R-squared values (greater than 0.9) of the regression equations were obtained for all the models developed based on the mildly heterogeneous site. On the highly heterogeneous site, the R-squared value of the regression equation for the percentage of nanoparticles attached (by mass) was more than 0.9.The ability to accurately estimate aqueous phase ENM concentration distribution using simple regression equations is particularly critical for risk assessment Even though the correlations developed in this study were site and scenario specific, this work represents a first effort of applying RSM for predicting the distribution of engineered nanomaterials in porous media.
机译:预测环境中工程纳米材料(ENM)的分布将为风险评估和政策制定提供重要信息,以规范这些新兴污染物。 ENM在自然地下环境中的命运和运输受到各种因素的影响,例如水力梯度,初始释放浓度,纳米颗粒尺寸和碰撞效率因子。基于先进的统计方法(即响应面方法(RSM)),我们探讨了控制ENM传输的关键因素(碰撞效率因子,粒径,水力梯度和初始释放浓度)与描述ENM的关键参数之间的简单关系在多孔介质中的浓度分布(最大标准化浓度,附着在含水层中的注入纳米颗粒的质量百分比,水相nC_(60)羽流的x重心以及附着相nC_(60)的x重心)。使用随机生成的基于轻度和高度非均质位点的渗透率场,数值模拟了将纳米颗粒释放到含水层中的假想情况。 RSM用于基于统计实验设计来开发多项式回归方程。对于基于轻度异质位点开发的所有模型,均获得了较高的R平方值(大于0.9)的回归方程。在高度异质性位置上,纳米颗粒附着百分比(质量)的回归方程的R平方值大于0.9。使用简单的回归方程准确估算水相ENM浓度分布的能力对于风险评估尤为关键即使在这项研究中开发的相关性是针对特定地点和特定情况的,但这项工作还是应用RSM预测工程纳米材料在多孔介质中分布的第一步。

著录项

  • 来源
    《Journal of Contaminant Hydrology》 |2013年第9期|60-69|共10页
  • 作者单位

    Department of Civil Engineering, University of Nebraska, Lincoln, 362R Whittier Building, 2200 Vine Street, Lincoln, NE 68583, United States;

    Department of Statistics, University of Nebraska, Lincoln. 343D Hardin Hall North, Lincoln, NE 68583, United States;

    Department of Civil Engineering, University of Nebraska, Lincoln, 362R Whittier Building, 2200 Vine Street, Lincoln, NE 68583, United States;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);美国《生物学医学文摘》(MEDLINE);美国《化学文摘》(CA);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    nC_(60) nanoparticles; Mobility; Subsurface; Response surface methodology; Design of experiments;

    机译:nC_(60)纳米粒子;流动性地下;响应面方法;实验设计;

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