Soil Science Centre, Wageningen University and Research Centre, 6700 AA Wageningen, The Netherlands.
Environ Sci Technol. 2010 Feb 15;44(4):1340-6. doi: 10.1021/es902615w.
Ion binding models such as the nonideal competitive adsorption-Donnan model (NICA-Donnan) and model VI successfully describe laboratory data of proton and metal binding to purified humic substances (HS). In this study model performance was tested in more complex natural systems. The speciation predicted with the NICA-Donnan model and the associated uncertainty were compared with independent measurements in soil solution extracts, including the free metal ion activity and fulvic (FA) and humic acid (HA) fractions of dissolved organic matter (DOM). Potentially important sources of uncertainty are the DOM composition and the variation in binding properties of HS. HS fractions of DOM in soil solution extracts varied between 14 and 63% and consisted mainly of FA. Moreover, binding parameters optimized for individual FA samples show substantial variation. Monte Carlo simulations show that uncertainties in predicted metal speciation, for metals with a high affinity for FA (Cu, Pb), are largely due to the natural variation in binding properties (i.e., the affinity) of FA. Predictions for metals with a lower affinity (Cd) are more prone to uncertainties in the fraction FA in DOM and the maximum site density (i.e., the capacity) of the FA. Based on these findings, suggestions are provided to reduce uncertainties in model predictions.
离子结合模型,如非理想竞争吸附-唐南模型(NICA-Donnan)和模型 VI,成功地描述了质子和金属与纯化腐殖物质(HS)结合的实验室数据。在本研究中,模型性能在更复杂的自然系统中进行了测试。NICA-Donnan 模型预测的形态和相关不确定性与土壤溶液提取物中的独立测量进行了比较,包括游离金属离子活性以及溶解有机物质(DOM)中的富里酸(FA)和腐殖酸(HA)分数。潜在的重要不确定性来源是 DOM 组成和 HS 结合特性的变化。土壤溶液提取物中 DOM 的 HS 分数在 14%至 63%之间变化,主要由 FA 组成。此外,针对单个 FA 样品优化的结合参数显示出很大的变化。蒙特卡罗模拟表明,对于与 FA 亲和力高的金属(Cu、Pb),预测金属形态的不确定性主要归因于 FA 结合特性(即亲和力)的自然变化。对于亲和力较低的金属(Cd),预测更易受到 DOM 中 FA 分数和 FA 的最大配位数(即容量)的不确定性的影响。基于这些发现,提出了一些建议来降低模型预测的不确定性。