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通过实际建模改进ASM2d的预测。

Improving the predictions of ASM2d through modelling in practice.

作者信息

Larrea L, Irizar I, Hidalgo M E

机构信息

Section of Environmental Engineering, CEIT, San Sebastián, Spain.

出版信息

Water Sci Technol. 2002;45(6):199-208.

PMID:11989872
Abstract

The paper presents the adjustments carried out on the structure and in some default values of the kinetic coefficients of the ASM2d model in order to get an improved prediction for the experimental results obtained in pilot scale plants studies with different activated sludge treatment processes for carbon, nitrogen and phosphorous removal. In order to predict the high effluent filtered COD experimentally observed in high rate processes for carbon removal, a new model structure has been proposed, incorporating into the carbon model a soluble fraction of the slowly biodegradable substrate. Studies with the step feed and the alternating processes showed simultaneous nitrification-denitrification in aerated reactors which was predicted with increased values in the oxygen saturation coefficients for heterotrophic and autotrophic biomass. Both processes also showed loss of the denitrification capacity under unfavourable conditions, such us rains and low anoxic fraction, which required a very large decrease in the value of the reduction factor for denitrification so as to improve the predictions for effluent nitrate experimental results. Regarding phosphorus removal, the ASM2d model showed a satisfactory predictive capacity. For improved predictions of phosphorus release in anaerobic conditions, high values of the rate constant for storage of X(PHA) and low values of the anaerobic hydrolysis reduction factor were used. For phosphorus uptake in aerobic and anoxic conditions satisfactory predictions were obtained using the default values.

摘要

本文介绍了对ASM2d模型的结构和一些动力学系数默认值进行的调整,以便对中试规模工厂中采用不同活性污泥处理工艺进行碳、氮和磷去除研究时获得的实验结果做出更好的预测。为了预测在高速率碳去除工艺中实验观察到的高出水过滤化学需氧量(COD),提出了一种新的模型结构,即将缓慢可生物降解底物的可溶部分纳入碳模型。对分段进水和交替工艺的研究表明,曝气反应器中同时存在硝化-反硝化现象,这可通过提高异养和自养生物量的氧饱和系数值来预测。这两种工艺在不利条件下(如下雨和低缺氧分数)也显示出反硝化能力的损失,这就需要大幅降低反硝化还原系数的值,以改善对出水硝酸盐实验结果的预测。关于磷的去除,ASM2d模型显示出令人满意的预测能力。为了更好地预测厌氧条件下的磷释放,采用了较高的X(PHA)储存速率常数和较低的厌氧水解还原系数值。在好氧和缺氧条件下吸收磷时,使用默认值获得了令人满意的预测结果。

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