College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China; College of Architecture and Environment, Sichuan University, Chengdu, 610000, China; Shaoxing Research Institute, Zhejiang University of Technology, Shaoxing, 312000, Zhejiang, China.
College of Environment, Zhejiang University of Technology, Hangzhou, 310014, China.
J Environ Manage. 2023 Nov 1;345:118717. doi: 10.1016/j.jenvman.2023.118717. Epub 2023 Aug 1.
Anaerobic membrane bioreactor (AnMBR) shows great potential for textile wastewater treatment, but high salinity in the influent may undermine its performance. This study evaluated the impact of salinity on the treatment performance of an upflow anaerobic sludge blanket (UASB) configured AnMBR using a flat sheet ceramic membrane. The salinity was stepwise increased (0, 5, 10 and 20 g/L) in four phases of the AnMBR operation. Results indicated that increased salinity jeopardized the COD removal efficiency of AnMBR from 92% to 73%, but had a marginal effect on dye removal efficacy (90-96%). Low salinity (5 g/L) boosted the biogas production whilst high salinity (>10 g/L) had a negative impact. Additionally, the increase of salinity resulted in the soluble microbial production (SMP) concentration soar and membrane fouling rate increase, peaking at a salinity of 10 g/L (Phase III) and recovering back to a lower level at a salinity of 20 g/L (Phase IV). This indicated a transition occurrence at a salinity of 10 g/L (Phase III). The microbial diversity analyses further suggested a transition from salinity-sensitive microbes (Aminiphilus, Caldatribacterium, Mesotoga, Methanobrevibacter, Methanobacterium, Methanosaeta) to salinity-tolerant microbes (Longilinea, Ignavibacterium, Rhodovarius, Bosea and Flexilinea). This transition can be associated with the increase SMP concentration and more severe membrane fouling in Phase III, which were mitigated after a new equilibrium was reached when the microbial consortium acclimatized to the high salinity. Finally, a machine learning model of the Adaboost algorithm was established to predict COD removal under different salinities. Importantly, this study revealed that AnMBR process performance and membrane operation can be maintained for high salinity textile wastewater treatment with a halophilic microbial community growth under high-salinity selection pressure.
厌氧膜生物反应器（AnMBR）在处理纺织废水方面具有巨大的潜力，但进水的高盐度可能会影响其性能。本研究评估了盐度对采用平板陶瓷膜的上流式厌氧污泥床（UASB）配置的 AnMBR 处理性能的影响。AnMBR 的操作过程分为四个阶段，盐度逐步增加（0、5、10 和 20 g/L）。结果表明，盐度升高使 AnMBR 的 COD 去除效率从 92%降至 73%，但对染料去除效果（90-96%）影响不大。低盐度（5 g/L）促进了沼气的产生，而高盐度（>10 g/L）则产生负面影响。此外，盐度的增加导致可溶性微生物产物（SMP）浓度飙升和膜污染速率增加，在盐度为 10 g/L（第三阶段）时达到峰值，然后在盐度为 20 g/L（第四阶段）时恢复到较低水平。这表明在盐度为 10 g/L（第三阶段）时发生了转变。微生物多样性分析进一步表明，从对盐度敏感的微生物（Aminiphilus、Caldatribacterium、Mesotoga、Methanobrevibacter、Methanobacterium、Methanosaeta）过渡到对盐度耐受的微生物（Longilinea、Ignavibacterium、Rhodovarius、Bosea 和 Flexilinea）。这种转变可能与第三阶段 SMP 浓度的增加和更严重的膜污染有关，当微生物群落适应高盐度后，新的平衡建立，这些问题得到缓解。最后，建立了 Adaboost 算法的机器学习模型，以预测不同盐度下的 COD 去除率。重要的是，本研究表明，在高盐度选择压力下，嗜盐微生物群落的生长可以维持 AnMBR 工艺性能和膜运行，用于处理高盐度纺织废水。
