在这项研究中，表面络合模型用于预测砷酸盐、天然有机物和氢氧化铁去除二氧化硅。还讨论了表面电位的估算以及硬度、天然有机物、二氧化硅和硫酸盐对砷酸盐去除的预测影响。该模型准确预测了在一系列环境下，通过吸附和混凝从合成水和天然水中去除砷酸盐的情况。在二氧化硅存在的情况下，精确模拟砷去除需要明确考虑单体和二聚体二氧化硅物种。预计天然有机物和二氧化硅会通过竞争、阴离子表面电荷的发展，以及在表面电位不利时通过阻碍絮凝，显著降低砷酸盐的去除。准确的表面络合模型可能是模拟许多污染物混凝性能的有力工具。包括20个参考文献、表格、图表和附录。

Surface complexation modeling was examined in this study for prediction of arsenate, natural organic matter, and silica removal by ferric hydroxides. Estimation of surface potential and the predicted effect of hardness, natural organic matter, silica, and sulfate on arsenate removal were also addressed. The model accurately predicted arsenate removal from synthetic and natural water by adsorption and coagulation under a range of circumstances. Accurate modeling of arsenic removal in the presence of silica required explicit consideration of both monomeric and dimeric silica species. Natural organic matter and silica are predicted to significantly reduce arsenate removal by competition, development of anionic surface charge, and by hindered flocculation when surface potential is unfavorable. Accurate surface complexation models could be a powerful tool in modeling coagulation performance for a number of contaminants. Includes 20 references, tables, figures, appendix.