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Mathematical Modeling of Leachates from Ash Ponds of Thermal Power Plants

机译:火力发电厂灰池渗滤液的数学模型

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The present study describes the development of empirical models for the prediction of various trace metals i.e., Mn, Cu, Fe, Zn and Pb found in the leachates generated from the ash ponds of various thermal power plants. The dispersion phenomenon of these trace metals followed first order reaction rate kinetics. The empirical models for individual trace metals derived from the lab scale models data correlate well with the real field data with regression coefficients varying from 0.93 to 0.98. The predicted concentrations of the trace metals varied within ±3% of the observed values in the leachates generated from the ash ponds of four thermal power plants with standard deviation varying from 0.001 to 0.032. The empirical models derived from the study can be applied for prediction of trace metals in leachates generated from similar thermal power plants.
机译:本研究描述了用于预测各种痕量金属的经验模型的发展,这些痕量金属是从各种火力发电厂的灰池产生的渗滤液中发现的锰,铜,铁,锌和铅。这些痕量金属的分散现象遵循一级反应速率动力学。从实验室规模模型数据得出的单个痕量金属的经验模型与真实数据具有很好的相关性,回归系数在0.93至0.98之间变化。四个火力发电厂的灰池产生的渗滤液中痕量金属的预测浓度在观测值的±3%范围内变化,标准偏差为0.001至0.032。该研究得出的经验模型可用于预测类似热电厂产生的渗滤液中的痕量金属。

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