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大型城市污水处理厂中细菌群落结构、相关功能作用及水体健康评估

Assessment of Bacterial Community Structure, Associated Functional Role, and Water Health in Full-Scale Municipal Wastewater Treatment Plants.

作者信息

Tyagi Inderjeet, Tyagi Kaomud, Ahamad Faheem, Bhutiani Rakesh, Kumar Vikas

机构信息

Centre for DNA Taxonomy, Molecular Systematics Division, Zoological Survey of India, Kolkata 700053, West Bengal, India.

Department of Environmental Science, Keral Verma Subharti College of Science (KVSCOS), Swami Vivekanand Subharti University, Meerut 250005, Uttar Pradesh, India.

出版信息

Toxics. 2024 Dec 24;13(1):3. doi: 10.3390/toxics13010003.

Abstract

The present study collected wastewater samples from fourteen (14) full-scale wastewater treatment plants (WWTPs) at different treatment stages, namely, primary, secondary, and tertiary, to understand the impact of WWTP processes on the bacterial community structure, their role, and their correlation with environmental variables (water quality parameters). The findings showed that the bacterial communities in the primary, secondary, and tertiary treatment stages are more or less similar. They are made up of 42 phyla, 84 classes, 154 orders, 212 families, and 268 genera. , , , , , , , , , , and , among others, dominated the bacterial community structure in all treatment stages. The biochemical oxygen demand was 7-12 times, chemical oxygen demand (COD) was 6 times, and total suspended solids (TSS) was 3.5 times higher in the wastewater than what the Central Pollution Control Board (CPCB) in New Delhi, India, allows as standard discharge. The correlation analysis using the Pearson r matrix and canonical correspondence analysis (CCA) also confirmed the fact that these water quality parameters (especially BOD and COD) play a pivotal role in deciphering the community structure in WWTPs.

摘要

本研究从14个不同处理阶段(即一级、二级和三级)的全尺寸污水处理厂收集废水样本,以了解污水处理厂工艺对细菌群落结构、其作用以及它们与环境变量(水质参数)之间相关性的影响。研究结果表明,一级、二级和三级处理阶段的细菌群落或多或少相似。它们由42个门、84个纲、154个目、212个科和268个属组成。 等在所有处理阶段的细菌群落结构中占主导地位。废水中的生化需氧量比印度新德里中央污染控制委员会(CPCB)允许的标准排放量高7至12倍,化学需氧量(COD)高6倍,总悬浮固体(TSS)高3.5倍。使用Pearson r矩阵和典范对应分析(CCA)进行的相关性分析也证实了这些水质参数(尤其是生化需氧量和化学需氧量)在解读污水处理厂群落结构中起着关键作用这一事实。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/670c/11768911/a8e22e167e0f/toxics-13-00003-g001.jpg

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