Spatial characterization of microbial sulfur cycling in horizontal-flow constructed wetland models.

Chemosphere(2022)

引用 1|浏览5
暂无评分
摘要
Constructed wetlands (CWs) are a cost-effective technology for wastewater treatment in which plant-microorganism relationships play a key role in transforming pollutants. However, there is little knowledge about the spatial organization of microbial metabolic processes in CWs. Here we show the structuring of microbial transformation of inorganic sulfur compounds (ISCs) in two horizontal subsurface-flow CW models fed with sulfate-rich artificial wastewater. One model was fully planted with Juncus effusus, while the other was planted only in the middle to investigate further the influence of the plant on ISC transformations. Chemical analyses revealed that sulfate reduction and re-oxidation of sulfide/sulfur occurred simultaneously along the flow paths, with net reduction at the beginning of the CWs, where organic carbon from the influent was still present, and predominant re-oxidation in the downstream sections. Porewater ISC concentrations hardly differed between the two CWs. However, analysis of the bacterial communities showed that sulfur cycling in the fully planted CW was much higher. Total bacterial abundances were about 50 times and 3-4 orders of magnitude higher in the rhizoplane than in porewater and on gravel, respectively, as quantified by qPCR determination of the 16S rRNA gene. Sequencing of 16S rRNA gene amplicons revealed that bacterial communities on the roots and in the porewater differed substantially, apparently a consequence of the fluxes of oxygen and exudates from the roots. Furthermore, we observed partitioning of ISC transforming bacteria into different niches of the CWs. The results of the chemical and microbial analyses collectively support that extensive sulfur cycling occurred in the rhizospheres of the CW models. The study is relevant to the treatment of sulfur-containing wastewater and the elucidation of microbial communities involved in biogeochemical activities to improve water quality.
更多
查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要