Jiang Tao, Myngheer Silvie, De Pauw Dirk J W, Spanjers Henri, Nopens Ingmar, Kennedy Maria D, Amy Gary, Vanrolleghem Peter A
BIOMATH, Department of Applied Mathematics, Biometrics and Process Control, Ghent University, Coupure Links 653, B-9000 Gent, Belgium.
Water Res. 2008 Dec;42(20):4955-64. doi: 10.1016/j.watres.2008.09.037. Epub 2008 Oct 11.
MBR biochemical conditions have an effect on membrane fouling and SMP have been attributed to be the main MBR foulant. Thus, predicting the SMP concentration is essential for understanding and controlling MBR fouling. However, existing SMP models are mostly too complex and over-parameterized, resulting in inadequate or absent parameter estimation and validation. This study extends the existing activated sludge model No. 2d (ASM2d) to ASM2dSMP with introduction of only 4 additional SMP-related parameters. Dynamic batch experimental results were used for SMP parameter estimation leading to reasonable parameter confidence intervals. Finally, the ASM2dSMP model was used to predict the impact of operational parameters on SMP concentration. It would found that solid retention time (SRT) is the key parameter controlling the SMP concentration. A lower SRT increased the utilization associated products (UAP) concentration, but decreased the biomass associated products (BAP) concentration and vice versa. A SRT resulting in minimum total SMP concentration can be predicted, and is found to be a relatively low value in the MBR. If MBRs operate under dynamic conditions and biological nutrient removal is required, a moderate SRT condition should be applied.
膜生物反应器(MBR)的生化条件会对膜污染产生影响,溶解性微生物产物(SMP)被认为是MBR主要的污染物。因此,预测SMP浓度对于理解和控制MBR膜污染至关重要。然而,现有的SMP模型大多过于复杂且参数过多,导致参数估计和验证不足或缺失。本研究在现有的活性污泥2d模型(ASM2d)基础上进行扩展,引入仅4个与SMP相关的额外参数,构建了ASM2dSMP模型。利用动态批次实验结果对SMP参数进行估计,得出合理的参数置信区间。最后,使用ASM2dSMP模型预测运行参数对SMP浓度的影响。研究发现,固体停留时间(SRT)是控制SMP浓度的关键参数。较低的SRT会增加利用相关产物(UAP)浓度,但会降低生物量相关产物(BAP)浓度,反之亦然。可以预测出能使总SMP浓度达到最低的SRT值,且该值在MBR中相对较低。如果MBR在动态条件下运行且需要进行生物脱氮除磷,应采用适中的SRT条件。