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首页> 外文会议>Sixth International in Situ and On-Site Bioremediation Symposium, 6th, Jun 4-7, 2001, San Diego, California >STATISTICAL MODELING OF SULFATE REMOVAL IN MINE DRAINAGE TREATMENT
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STATISTICAL MODELING OF SULFATE REMOVAL IN MINE DRAINAGE TREATMENT

机译：矿山排水处理中硫酸盐去除的统计模型

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Sulfate-reducing reactive walls installed in-situ in the path of acid mine drainage (AMD) contaminated groundwater, present a promising passive treatment technology. However, a rigorous and methodical selection of the most appropriate reactive mixture composition still needs to be investigated. The aim of this study was the modeling of the sulfate-reduction rate in order to assess the variables that significantly affect it. Reactivity of 17 mixtures was assessed in batch reactors (in duplicates) using a synthetic AMD. Results indicate that within 41 days, sulfate concentrations decreased from initial concentrations of 2000-3200 mg/L to final concentrations of < 90 mg/L, while metal removal efficiencies ranged between 51 - 84 % for Ni and 73 - 93 % for Zn. The generated sulfate-reduction rate predictive model, which had very satisfactory parameters (R~2 = 0.90, F = 62.3 (p-level <10~(-13))) identified reactive mixture carbon sources as the critical variables for sulfate-reduction rate.
机译：在酸性矿井排水（AMD）污染的地下水路径中原位安装的硫酸盐还原反应墙，是一种很有前途的被动处理技术。然而，仍然需要研究最合适的反应混合物组成的严格和系统的选择。这项研究的目的是对硫酸盐还原速率进行建模，以评估对其产生重大影响的变量。使用合成AMD在间歇反应器（一式两份）中评估了17种混合物的反应性。结果表明，在41天之内，硫酸盐浓度从初始浓度2000-3200 mg / L降低到最终浓度<90 mg / L，而金属的去除效率在Ni的51-84％和Zn的73-93％之间。生成的硫酸盐还原率预测模型具有非常令人满意的参数（R〜2 = 0.90，F = 62.3（p-level <10〜（-13））），确定了反应混合物碳源是硫酸盐还原的关键变量。率。

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