Department of Environmental Science and Engineering, Center for Environmental Studies, Kyung Hee University, Yongin 446-701, Republic of Korea; Korea Railroad Research Institute, 76, Cheoldobangmulgwan-ro, Uiwang-si, Gyeonggi-do, Republic of Korea.
Key Laboratory of Microorganism Application and Risk Control (MARC) of Shenzhen, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, Guangdong, PR China.
Bioresour Technol. 2017 Mar;227:227-238. doi: 10.1016/j.biortech.2016.11.127. Epub 2016 Dec 21.
A modified AOB-NOB-NO-SMP model able to quantify nitrous oxide (NO) emissions and soluble microbial product (SMP) production during wastewater treatment is proposed. The modified AOB-NOB-NO-SMP model takes into account: (1) two-step nitrification by ammonia-oxidizing bacteria (AOB) and nitrite-oxidizing bacteria (NOB), (2) NO production by AOB denitrification under oxygen-limited conditions and (3) SMP production by microbial growth and endogenous respiration. Validity of the modified model is demonstrated by comparing the simulation results with experimental data from lab-scale sequencing batch reactors (SBRs). To reliably implement the modified model, a model calibration that adjusts model parameters to fit the model outputs to the experimental data is conducted. The results of this study showed that the modeling accuracy of the modified AOB-NOB-NO-SMP model increases by 19.7% (NH), 51.0% (NO), 57.8% (NO) and 16.7% (SMP) compared to the conventional model which does not consider the two-step nitrification and SMP production by microbial endogenous respiration.
提出了一种能够量化废水处理过程中氧化亚氮(NO)排放和可溶性微生物产物(SMP)生成的改进 AOB-NOB-NO-SMP 模型。改进的 AOB-NOB-NO-SMP 模型考虑了:(1)氨氧化菌(AOB)和亚硝酸盐氧化菌(NOB)的两步硝化作用,(2)在氧限制条件下 AOB 反硝化产生的 NO,以及(3)微生物生长和内源呼吸产生的 SMP。通过将模拟结果与来自实验室规模序批式反应器(SBR)的实验数据进行比较,验证了改进模型的有效性。为了可靠地实施改进模型,进行了模型校准,调整模型参数以使模型输出与实验数据拟合。研究结果表明,与不考虑两步硝化和微生物内源呼吸产生 SMP 的传统模型相比,改进的 AOB-NOB-NO-SMP 模型的 NH、NO、NO 和 SMP 的建模精度分别提高了 19.7%、51.0%、57.8%和 16.7%。