Institute for Water and Wetland Research, Department of Environmental Science, Radboud University Nijmegen , P.O. Box 9010, NL-6500 GL Nijmegen, The Netherlands.
Environ Sci Technol. 2014 May 20;48(10):5726-36. doi: 10.1021/es500548h. Epub 2014 May 5.
Screening level models for environmental assessment of engineered nanoparticles (ENP) are not generally available. Here, we present SimpleBox4Nano (SB4N) as the first model of this type, assess its validity, and evaluate it by comparisons with a known material flow model. SB4N expresses ENP transport and concentrations in and across air, rain, surface waters, soil, and sediment, accounting for nanospecific processes such as aggregation, attachment, and dissolution. The model solves simultaneous mass balance equations (MBE) using simple matrix algebra. The MBEs link all concentrations and transfer processes using first-order rate constants for all processes known to be relevant for ENPs. The first-order rate constants are obtained from the literature. The output of SB4N is mass concentrations of ENPs as free dispersive species, heteroaggregates with natural colloids, and larger natural particles in each compartment in time and at steady state. Known scenario studies for Switzerland were used to demonstrate the impact of the transport processes included in SB4N on the prediction of environmental concentrations. We argue that SB4N-predicted environmental concentrations are useful as background concentrations in environmental risk assessment.
用于工程纳米粒子（ENP）环境评估的筛选水平模型通常不可用。在这里，我们提出了 SimpleBox4Nano（SB4N）作为此类模型的第一个模型，评估了其有效性，并通过与已知物质流模型的比较进行了评估。SB4N 表达了空气中、雨中、地表水、土壤和沉积物中的 ENP 迁移和浓度，考虑了团聚、附着和溶解等纳米特定过程。该模型使用简单的矩阵代数求解同时的质量平衡方程（MBE）。MBE 使用所有已知与 ENP 相关的过程的一级速率常数来连接所有浓度和转移过程。一级速率常数从文献中获得。SB4N 的输出是每个隔室中自由分散物质、与天然胶体异质团聚体以及更大天然颗粒的 ENP 质量浓度，时间和稳态。使用已知的瑞士情景研究来证明 SB4N 中包含的传输过程对预测环境浓度的影响。我们认为，SB4N 预测的环境浓度可用作环境风险评估中的背景浓度。
