化学
硫酸盐还原菌
胞外聚合物
废水
硫酸盐
木糖
金属
金属氢氧化物
细菌
环境化学
化学工程
环境工程
生物化学
发酵
生物膜
有机化学
生物
环境科学
工程类
遗传学
出处
期刊:Water Research
[Elsevier]
日期:2022-10-09
卷期号:226: 119227-119227
被引量:7
标识
DOI:10.1016/j.watres.2022.119227
摘要
Dissimilatory sulfate reduction-based processes have long been a viable option for treating acidic metal-laden wastewater (AMW). Such processes can be optimized through enhancing sulfidogenic activity and the microbial consortia's resilience against a harsh environment. This study investigated how granular and flocculent sulfate-reducing bacteria (SRB) sludge respond to AMW as well as the mechanisms through which they adapt to the wastewater, with particular focuses on the stability of the sulfidogenic activities, metal removal, and the bacteria's resistance over the long-term: the flocculent SRB lost more than 50% of their treatment capacity after 35 days of treating AMW with the presence of Cd2+, Cu2+, Zn2+, and Ni2+ at 30 mg/L each, under pH = 4.5. In contrast, the granular SRB maintained its metal removal rate at 91% throughout the 161-day trial. Despite the SRB abundance remaining at approximate 40%, organics-partial oxidizing genera (Desulfobulbus and Desulfobacter) began to dominate due to their kinetic advantage. The extracellular glycosyl compositions were revealed to be critical for the stability of the granular structure and microbial activity as the extracellular proteins disintegrated irreversible. Usage the molecular dynamic simulation, the mobility of the metal ions in the SRB granular system was suppressed by the presence of a more diverse glycosyl composition compared with the flocculent system (10-50% diffusion coefficients differences). All of the identified glycosyls (especially xylose and rhamnose) exhibited strong interactions with Cu2+ (-470 kJ mol-1), while the maximum binding strength of Cd2+ to glycosyls was greater than -40 kJ mol-1, suggesting a low Cd2+complexation efficiency. The findings of this study shed light on the defensive mechanisms of SRB granules against multi-metal stress, and provide clues for efficient AMW treatment.
科研通智能强力驱动
Strongly Powered by AbleSci AI