1 MOE Key Laboratory of Resources and Environmental Systems Optimization, North China Electric Power University, Beijing, 102206, China.
2 Center for Energy, Environment and Ecology Research, UR-BNU, School of Environment, Beijing Normal University, Beijing, 100875, China. Electronic address: huang@iseis.org.
3 Department of Building, Civil and Environmental Engineering, Concordia University, Montreal, Quebec, H3G 1M8, Canada.
4 Department of Civil Engineering, Memorial University of Newfoundland, St. John's, A1C 5S7, Canada.
5 Institute for Energy, Environment and Sustainable Communities, University of Regina, Regina, S4S 0A2, Canada.
6 State Key Joint Laboratory of Environmental Simulation and Pollution Control, CEEER-URBNU, College of Environment, Beijing Normal University, Beijing, 100875, China.

Exploring the decentralized treatment of sulfamethoxazole-contained poultry wastewater through vertical-flow multi-soil-layering systems in rural communities.

Water Res. 2021 Jan 01; 188:116480

Authors: Song P, Huang G, An C, Xin X, Zhang P, Chen X, Ren S, Xu Z, Yang X

Abstract

Sulfamethoxazole (SMX) is the most widely distributed sulfonamide antibiotics detected in decentralized poultry wastewater in rural communities. As an economically-feasible and eco-friendly technology for decentralized wastewater treatment in rural areas, vertical-flow multi-soil-layering (MSL) system was promising to mitigate the ecological and human health risks from SMX in such areas. The treatment of SMX-contained poultry wastewater by using MSL systems was investigated for the first time, and the main and interactive effects of related multiple variables on system performance were explored through factorial analysis, including material of permeable layer, concentration of SMX, and pH of influent. Results indicated that SMX concentration and pH of influent showed significantly negative effects on SMX removal. Medical stone used in MSL systems with larger surface area could intensify the SMX removal compared to anthracite. MSL systems showed stable performances on SMX removal with the best SMX removal efficiency more than 91%. A novel stepwise-cluster inference (SCI) model was developed for the first time to map the multivariate numeric relationships between state variables and SMX removal under discrete and nonlinear complexities. It was demonstrated that the effect of SMX in wastewater with high concentration was significant on the differentiation of soil bacteria composition in MSL systems based on microbial diversity analysis. These results can help better understand the mechanism of SMX removal in MSL systems from perspectives of factorial analysis, numeric modeling, and microbiological change.

PMID: 33065414 [PubMed - indexed for MEDLINE]