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通过鸟粪石沉淀提高氨氮去除的预测。

Improving the prediction of ammonium nitrogen removal through struvite precipitation.

机构信息

College of Environmental Science and Engineering, South China University of Technology, Guangzhou Higher Education Mega Center, Guangzhou 510006, People's Republic of China.

出版信息

Environ Sci Pollut Res Int. 2012 Feb;19(2):347-60. doi: 10.1007/s11356-011-0520-6. Epub 2011 Jul 13.

Abstract

PURPOSE

Both an optimization statistical model and a chemical thermodynamic equilibrium computer model were proposed to develop, improve, and optimize struvite precipitation process.

METHODS AND RESULT

The NH(4)-N in synthetically prepared wastewater was removed using struvite precipitation technology. A quadratic statistical modeling, response surface methodology (RSM), was applied to investigate the improvement availability for high-level removal of ammonium-nitrogen by struvite precipitation. Then, a chemical equilibrium model, Visual MINTEQ, was used to calculate the equilibrium speciation and saturation index in aqueous solution and solid phases. In addition, the availability of Mg(2+), NH(4)(+), and PO(4)(3-) ions as a function of pH was modeled. The predicted and experimental data indicated that the two models might describe the experiments well. The results showed that pH was an important parameter in ammonium-nitrogen removals at low initial NH(4)-N concentration. P/N molar ratio was a limiting factor on struvite precipitation at high initial NH(4)-N concentration.

CONCLUSION

Within the ranges of the investigated factors, Visual MINTEQ program can be proposed to predetermine the concentration of ammonium precipitated by struvite, and RSM can be used to predict total NH(4)-N removal by both struvite precipitation and ammonia volatilization from our investigated system operated at high pH and opened to the atmosphere.

摘要

目的

提出了优化统计模型和化学平衡计算机模型,以开发、改进和优化鸟粪石沉淀工艺。

方法与结果

采用鸟粪石沉淀技术去除合成废水中的 NH(4)-N。应用二次统计建模、响应面法(RSM)研究了鸟粪石沉淀法提高高浓度铵氮去除率的可行性。然后,使用化学平衡模型 Visual MINTEQ 计算水溶液和固相中的平衡形态和饱和度指数。此外,还对 Mg(2+)、NH(4)(+)和 PO(4)(3-)离子作为 pH 的函数的可用性进行了建模。预测和实验数据表明,这两个模型可能很好地描述了实验。结果表明,pH 是低初始 NH(4)-N 浓度下去除铵氮的重要参数。在高初始 NH(4)-N 浓度下,P/N 摩尔比是鸟粪石沉淀的限制因素。

结论

在研究的因素范围内,可采用 Visual MINTEQ 程序预先确定鸟粪石沉淀的铵浓度,RSM 可用于预测我们在高 pH 值下运行并与大气相通的系统中通过鸟粪石沉淀和氨挥发去除总 NH(4)-N。

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