遗传算法
环境化学
沉积物
海水
稀土
有机质
地球化学模拟
河口
地质学
离子强度
化学
矿物学
地下水
生态学
海洋学
水溶液
地貌学
生物
物理化学
有机化学
岩土工程
作者
Rémi Marsac,Charlotte Catrouillet,Mélanie Davranche,Martine Bouhnik‐Le Coz,Nicolas Briant,Noémie Janot,Alba Otero-Fariña,J.E. Groenenberg,Mathieu Pédrot,Aline Dia
出处
期刊:Chemical Geology
[Elsevier BV]
日期:2021-02-06
卷期号:567: 120099-120099
被引量:34
标识
DOI:10.1016/j.chemgeo.2021.120099
摘要
Rare earth elements (REE) naturally occur at trace levels in natural systems but, due to their increasing use in modern technologies, they are now released into the environment, and considered as emerging contaminants. Therefore, the development of numerical predictive models of their speciation in various physico-chemical conditions is required to predict their behavior, transport and potentially toxic effects on ecosystems. Because REE speciation is largely affected by natural organic matter, such as humic acids (HA), this study aimed at calibrating an advanced humic-ion binding model (Model VII) to allow predicting REE-HA binding in various pH conditions, ionic strength and [REE]/[HA], as well as presence of competitor ions. First, REE complexation to monodentate O-containing ligands was evaluated using the Irving-Rossotti equation, which provided constraints for the optimization of REE-HA binding parameters for Model VII. Predictive capacities of Model VII were demonstrated by successfully modeling the effects of various cations (Al3+, Fe3+, Cu2+ and Ca2+) and carbonates on REE-HA binding. The large range of physico-chemical conditions for which Model VII is applicable suggest that the present model parameters might be used to more accurately predict the role played by NOM on REE speciation in very contrasting environments, such as in groundwaters, rivers, estuaries, seawater, soils or sediments. Therefore, this study provides a valuable numerical tool to predict the fate of REE in the environment.
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