Literature DB >> 29990903

Treatment of rural domestic wastewater using multi-soil-layering systems: Performance evaluation, factorial analysis and numerical modeling.

Pei Song1, Guohe Huang2, Chunjiang An3, Ju Shen1, Peng Zhang4, Xiujuan Chen4, Jian Shen4, Yao Yao4, Rubing Zheng1, Chaoxing Sun1.   

Abstract

The discharge of wastewater in rural areas without effective treatment may result in contamination of surrounding surface water and groundwater resources. This study explored the wastewater treatment performance of multi-soil-layering (MSL) systems through interactive factorial analysis. MSL systems showed good performances under various operating conditions. The COD and BOD5 removal rates in MSL systems could reach 98.53 and 93.66%, respectively. The performances of MSL systems in TP removal stayed at high levels ranged from 97.97 to 100% throughout the experiments. The NH4+ - N removal rates of the well performed MSL systems reached highest levels ranging from 89.96 to 100%. The TN removal rates of aerated MSL systems ranged from 51.11 to 64.44% after 72 days of operation. The independent effects of bottom submersion, microbial amendment and aeration, as well as most interactions were significant. The performance of MSL systems was mainly affected by bottom submersion and aeration as well as their interactions. Aeration was the most positive factor for the removal of organic matter, TP and NH4+ - N. However, oxygenated environment was unfavorable for NO3- - N removal. In the submerged area with limited oxygen, the microbial transformation of NO3- - N still occurred. A stepwise-cluster inference model was developed for tackling the multivariate nonlinear relationships in contaminant removal processes. The results can help obtain a better understanding of the complicated processes among contaminant removal in MSL systems.
Copyright © 2018. Published by Elsevier B.V.

Entities:  

Keywords:  Interactive factorial analysis; Multi-soil-layering system; Operating factors; Rural wastewater; Stepwise-cluster inference

Year:  2018        PMID: 29990903     DOI: 10.1016/j.scitotenv.2018.06.331

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  1 in total

1.  River Management for Local Governments in China: From Public to Private.

Authors:  Jiangfan Liu; Xiongzhi Xue
Journal:  Int J Environ Res Public Health       Date:  2018-10-04       Impact factor: 3.390

  1 in total

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