State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China; University of Chinese Academy of Sciences, Beijing, 100049, China.
State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China; Puding Karst Ecosystem Research Station, Chinese Academy of Sciences, Puding, 562100, China.
Environ Res. 2022 Sep;212(Pt B):113338. doi: 10.1016/j.envres.2022.113338. Epub 2022 Apr 18.
Leachate from wet phosphogypsum (PG) stack should be properly managed to mitigate the negative environmental impact of phosphoric industry. Accurate prediction of leachate amount is the prerequisite for efficient leachate management. In this study, a model using water balance analysis to predict leachate production from wet PG stack is established. The extruded water, which is related to PG deformation, is innovatively introduced as a variable in the model to account for the porewater's contribution. Model simulation suggested that at the early stage, fresh water need to be added to PG to facilitate the transfer or PG slurries; however, as the leachate accumulates in the tailings pond, a net discharge of PG is required starting at the fourth year for the studied PG stack. Model simulation also indicated that the leachate generation increased gradually over time and that the leachate generation in each month could deviate from the average leachate generation during the life cycle of the stack. The model output matches with measured values reasonably well, which confirmed the model's accuracy. Sensitivity analysis indicated that average precipitation and evaporation are the two most important factors that determine leachate generation rate. Monthly leachate generation rates vary significantly within the year, as the precipitation and evaporation vary in different seasons. The highest leachate generation rates were reached in rainy seasons and the lowest rates were reached in wintery months. This study could be used to optimize the PG leachate managements and to mitigate the PG related pollution to the environment.
磷石膏堆场沥滤液应妥善管理，以减轻磷化工对环境的负面影响。准确预测沥滤液的产生量是有效管理沥滤液的前提。本研究建立了一个利用水量平衡分析预测湿法磷石膏堆场沥滤液产生量的模型。模型创新性地引入了与磷石膏变形有关的挤出水量作为一个变量，以考虑孔隙水的贡献。模型模拟表明，在早期阶段，需要向磷石膏中添加淡水以促进磷石膏浆的转移；然而，随着沥滤液在尾矿库中的积累，从第四年开始，研究中的磷石膏堆场就需要净排放磷石膏。模型模拟还表明，沥滤液的产生量随时间逐渐增加，并且每个月的沥滤液产生量可能偏离堆场寿命周期内的平均沥滤液产生量。模型输出与实测值吻合较好，证实了模型的准确性。敏感性分析表明，平均降水量和蒸发量是决定沥滤液产生速率的两个最重要因素。由于不同季节的降水量和蒸发量不同，一年内的每月沥滤液产生量差异很大。最高的沥滤液产生速率出现在雨季，最低的速率出现在冬季。本研究可用于优化磷石膏堆场沥滤液管理，减轻磷石膏对环境的污染。
