微生物种群生物学
反硝化细菌
人工湿地
蛋白质细菌
环境科学
群落结构
反硝化
流出物
相对物种丰度
湿地
生态学
修正案
微生物生态学
基因组
环境工程
生物
氮气循环
环境化学
化学
丰度(生态学)
社区
微生物
制浆造纸工业
作者
Huanhuan Xu,Guangzhou Wang,Peiyuan Deng,Yaoshen Fan,Yuping Han
标识
DOI:10.1016/j.eti.2025.104580
摘要
Constructed wetlands (CW) enhanced with nanoscale zero-valent iron supported biochar (nZVI-Biochar) composites showed promise for efficient nitrate-nitrogen (NO₃ - -N) removal, yet the microbial mechanisms and predictive modeling of such systems remained unclear. In this study, four CW configurations were established to evaluate NO₃ - -N removal performance: CK-CW (quartz sand only), C-CW (quartz sand + biochar), FE-CW (quartz sand + nZVI), and CFE-CW (quartz sand + nZVI-Biochar). Denitrification efficiency was assessed under varying operational conditions, including carbon-to-nitrogen (C/N) ratio, hydraulic retention time (HRT), and pH. Microbial community composition and functional gene abundance were analyzed via 16S rRNA high-throughput sequencing and quantitative PCR (qPCR). A random forest model with 10-fold cross-validation was employed to predict NO₃ - -N concentrations and identify key influencing factors, while microbial assembly mechanisms were elucidated using the null model-based iCAMP framework. Results indicated that under optimized conditions (C/N=10, HRT=1 d, pH=7), CFE-CW achieved the highest NO₃ - -N removal, attributed to the enrichment of denitrifying bacteria ( Proteobacteria , Actinobacteriota ) and elevated expression of key nitrogen-cycle genes ( amoA , narG , nirS , nosZ ). A random forest model accurately predicted effluent NO₃ - -N (R²=0.99), identifying TN and NH₄ + -N as dominant factors. The addition of nZVI-Biochar strengthened homogeneous selection indicating a heightened influence of environmental filtering by the amendment on shaping the microbial community structure and promoting phylogenetic clustering within microbial communities. Network analysis revealed that nZVI-Biochar supplementation enhanced microbial community stability and optimized ecological interactions. This integrated analysis demonstrates that nZVI-Biochar optimizes constructed wetlands by enabling accurate performance prediction and revealing underlying microbial mechanisms. • nZVI-Biochar composites drastically boost nitrate removal in constructed wetlands. • Mechanitic insights reveal enhanced microbial diversity and electron exchange. • Eflluent nitrate levels are reliably forecasted by a random forest model. • Ecological analysis identifies drift and homogenizing selection as key processes.
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