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Chen X, Chen Z, Ngo HH, Mao Y, Cao K, Shi Q, Lu Y, Hu HY. Comparison of inactivation characteristics between Gram-positive and Gram-negative bacteria in water by synergistic UV and chlorine disinfection. Environ Pollut 2023; 333:122007. [PMID: 37302789 DOI: 10.1016/j.envpol.2023.122007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/28/2023] [Revised: 04/23/2023] [Accepted: 06/08/2023] [Indexed: 06/13/2023]
Abstract
Disinfection is essential in water and wastewater treatment process as a guarantee for microbial safety. This study systematically investigated: (i) the inactivation characteristics of bacteria widely existed in water, including Gram-negative bacteria (Escherichiacoli) and Gram-positive bacteria (Staphylococcus aureus and Bacillus subtilis spores), by sequential UV and chlorine disinfection processes (UV-Cl and Cl-UV), simultaneous UV and chlorine disinfection process (UV/Cl); and (ii) the disinfection mechanisms on different bacteria. The combination of UV and chlorine disinfection could inactive bacteria at lower doses, but showed no synergistic effect on E. coli. Contrarily, disinfection results indicated that UV/Cl performed an obvious synergistic effect on highly disinfectant-resistant bacteria (e.g. S. aureus and B. subtilis spores). Specifically, UV/Cl at the UV dose of 9 mJ/cm2 and chlorine dose of 2 mg-Cl/L could inactivate S. aureus completely. Moreover, the effectiveness of UV/Cl on the removal of indigenous bacteria in actual water conditions was also confirmed. In short, the study provides significant theoretical and practical implications for ensuring microbial safety during water treatment and use.
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Affiliation(s)
- Xiaowen Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing, 100084, PR China.
| | - Huu Hao Ngo
- School of Civil and Environmental Engineering, University of Technology Sydney, Broadway, NSW, 2007, Australia
| | - Yu Mao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China
| | - Kefan Cao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China
| | - Qi Shi
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China
| | - Yun Lu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing, 100084, PR China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing, 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing, 100084, PR China; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Jiangsu, Suzhou, 215163, PR China
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Cao KF, Chen Z, Sun YG, Huang BH, Shi Q, Mao Y, Wu YH, Lu Y, Hu HY. Modeling and optimization of synergistic ozone-ultraviolet-chlorine process for reclaimed water disinfection: From laboratory tests to software simulation. Water Res 2023; 243:120373. [PMID: 37494748 DOI: 10.1016/j.watres.2023.120373] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/27/2023] [Revised: 06/26/2023] [Accepted: 07/15/2023] [Indexed: 07/28/2023]
Abstract
The ozone-ultraviolet (UV)-chlorine process is a highly effective method of disinfection in water reuse system, but currently still lacks precise quantification and accurate control. It is difficult to determine the dosage of each disinfectant because of the complex interactions that occur between disinfection units and the complicated mathematical calculation required. In this study, we proposed a dosage optimization model for ozone-UV-chlorine synergistic disinfection process. The model was able to identify the cost-effective doses of the disinfectants under the constraints of microbial inactivation, decolorization, and residual chlorine retention requirements. Specifically, the simulation of microbial inactivation rates during synergistic disinfection process was accomplished through quantification of the synergistic effects between disinfection units and the introduction of enhancement coefficients. In order to solve this optimization model rapidly and automatically, a MATLAB-based software program with graphical user interface was developed. This software consisted of calibration unit, prediction unit, assessment unit, and optimization unit, and was able to simulate synergistic ozone-UV-chlorine process and identify the optimal dose of ozone, UV, and chlorine. Validation experiments revealed good agreements between the experimental data and the results calculated by the developed software. The developed software is believed to help the water reclamation plants improve disinfection efficiency and reduce the operational costs of synergistic disinfection processes.
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Affiliation(s)
- Ke-Fan Cao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, China.
| | - Yi-Ge Sun
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China
| | - Bang-Hao Huang
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China
| | - Qi Shi
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China
| | - Yu Mao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China
| | - Yin-Hu Wu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, China
| | - Yun Lu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Room 524, Beijing 100084, China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, China; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Jiangsu, Suzhou 215163, China.
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Venis RA, Basu OD. Elution and disinfection of silver and zinc nanoparticles in co-fired ceramic water filters. Sci Total Environ 2023; 887:163317. [PMID: 37146831 DOI: 10.1016/j.scitotenv.2023.163317] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Revised: 03/12/2023] [Accepted: 04/02/2023] [Indexed: 05/07/2023]
Abstract
Ceramic water filters (CWFs) are decentralized water treatment technologies commonly used in resource-restricted geographies. Inclusion of silver nanoparticles (AgNP) assists with disinfection but can substantially increase costs. This research investigates AgNP supplementation with zinc oxide (ZnO) as a low-cost bactericide alternative. CWF disks were impregnated with varying AgNP and/or ZnO concentrations and challenged against Escherichia coli. Effluent bacteria were enumerated and monitored over 72 h while eluted metal concentrations were measured and scaled according to surface area to establish 'pot-equivalent' estimates (0-50 ppb Ag and 0-1200 ppb Zn). Ag addition correlated to subsequent measured release values, though Zn impregnation did not. Background Zn was thus evidently present. Meanwhile, the eluted metal concentration related to disinfection: a CWF with a pot-equivalent elution estimate of 2 ppb Ag and 156 ppb Zn achieved a Log Removal Value (LRV) of 2.0 after 60 min of filtration and 1.9 after 24 h of storage while a CWF with a pot-equivalent elution estimate of 20 ppb Ag and 376 ppb Zn achieved LRVs of 3.1 and 4.5 after the same filtration and storage times, respectively. Clay elemental composition may therefore impact filter performance more than previously considered This trend was further confirmed by batch experiments with Ag and Zn in concentrations of 0-20 ppb Ag and 0-800 ppb Zn, respectively: bacterial regrowth was only observed when Ag and Zn were each below 5 ppb and 160 ppb while 1 ppb Ag and 800 ppb Zn maintained complete disinfection for 72 h. Increased Zn concentrations thus reduced Ag required to maintain disinfection over time. Overall, it is recommended to include Zn with Ag for CWF to improve short-term and long-term disinfection efficacy and associated water safety.
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Affiliation(s)
- Robbie A Venis
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada.
| | - Onita D Basu
- Department of Civil and Environmental Engineering, Carleton University, Ottawa, ON K1S 5B6, Canada
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Chen X, Chen Z, Liu H, Huang N, Mao Y, Cao K, Shi Q, Lu Y, Hu HY. Synergistic effects of UV and chlorine in bacterial inactivation for sustainable water reclamation and reuse. Sci Total Environ 2022; 845:157320. [PMID: 35839898 DOI: 10.1016/j.scitotenv.2022.157320] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2022] [Revised: 06/30/2022] [Accepted: 07/08/2022] [Indexed: 06/15/2023]
Abstract
Disinfection is a necessity in water and wastewater treatment and reclamation. This study examined the inactivation of a disinfectant resistant but widely existed opportunistic pathogen in reclaimed water, Staphylococcus aureus (S. aureus), by sequential UV and chlorine disinfection or simultaneous UV and chlorine disinfection (UV/Cl). It was identified that UV/Cl greatly promoted the inactivation efficacy and inhibited photoreactivation of S. aureus by the generation of free radicals (i.e. OH and Cl), which reached a 7-log10 reduction at UV and chlorine doses of 18 mJ/cm2 and 2 mg-Cl/L, respectively. The changes of bacterial viability and morphology and the increase of extracellular ATP concentration confirmed the enhancement of cell membranes damages (>21.4 %) due to free radicals generated in UV/Cl process, which caused a dramatic reduction in metabolic activity and suppressed the photoreactivation. Furthermore, this study demonstrated that UV/Cl effectively removed heterotrophic plate count bacteria and aromatic organic fluorophores in reclaimed water samples. This study is of significant theoretical and applicable importance in guaranteeing safe microbial levels for water reclamation and reuse.
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Affiliation(s)
- Xiaowen Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China.
| | - Hai Liu
- School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, and Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, PR China
| | - Nan Huang
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Yu Mao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Kefan Cao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Qi Shi
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Yun Lu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Jiangsu, Suzhou 215163, PR China
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Cao KF, Chen Z, Shi Q, Wu YH, Lu Y, Mao Y, Chen XW, Li K, Xu Q, Hu HY. An insight to sequential ozone‑chlorine process for synergistic disinfection on reclaimed water: Experimental and modelling studies. Sci Total Environ 2021; 793:148563. [PMID: 34175603 DOI: 10.1016/j.scitotenv.2021.148563] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 06/15/2021] [Accepted: 06/16/2021] [Indexed: 06/13/2023]
Abstract
Water reclamation plants (WRPs) are facing the challenges of ensuring microbial safety and require efficient disinfection systems. Sequential ozone‑chlorine disinfection is supposed to be a favorable alternative for reclaimed water disinfection. This study compared the inactivation efficiency of E.coli by single ozone, single chlorine, and sequential ozone‑chlorine disinfection approaches. Notably, a single ozone or chlorine process could only achieve a log removal rate of up to 5 log, whereas the sequential ozone‑chlorine disinfection could completely inactivate microorganisms (7.3 log). For sequential ozone‑chlorine disinfection, the efficiency of chlorination was improved by 2.4%-18.5%. The synergistic effect mainly attributed to the elimination of chlorine consuming substances by ozone. Through the chlorine decay model (CRS) fitting and calculating the integral CT value, the enhancement ability of ozone to chlorine disinfection was quantified. By introducing an enhancement coefficient (β), a succinct and accurate model was established to estimate the inactivation rate of sequential ozone‑chlorine disinfection (mean absolute percentage error: 0.035). The results and methodology of this study are informative to optimize the disinfection units of WRPs.
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Affiliation(s)
- Ke-Fan Cao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China.
| | - Qi Shi
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China
| | - Yin-Hu Wu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yun Lu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Yu Mao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Xiao-Wen Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Kuixiao Li
- Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Research and Development Center, Beijing Drainage Group Co., Ltd, Beijing 100124, PR China
| | - Qi Xu
- Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Research and Development Center, Beijing Drainage Group Co., Ltd, Beijing 100124, PR China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Research Institute for Environmental Innovation (Suzhou), Tsinghua, Jiangsu, Suzhou, 215163, PR China.
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Shi Q, Chen Z, Liu H, Lu Y, Li K, Shi Y, Mao Y, Hu HY. Efficient synergistic disinfection by ozone, ultraviolet irradiation and chlorine in secondary effluents. Sci Total Environ 2021; 758:143641. [PMID: 33261863 DOI: 10.1016/j.scitotenv.2020.143641] [Citation(s) in RCA: 33] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/23/2020] [Revised: 11/08/2020] [Accepted: 11/09/2020] [Indexed: 05/03/2023]
Abstract
Disinfection of secondary effluents is vital to provide a sustainable aquatic environment, minimize microbial risks and guarantee public and environmental safety. This study investigated the effectiveness of six treatment trains including single and combined disinfection processes (i.e., ozone alone, ultraviolet (UV) irradiation alone, chlorine alone, sequential ozone-UV, sequential ozone-chlorine and sequential ozone-UV-chlorine) on bacterial inactivation, as well as bulk water quality parameters such as color, turbidity, absorbance at 254 nm (UV254), dissolved organic carbon (DOC) and fluorescence based on samples collected from an actual water reclamation plant (WRP). For the single disinfection processes, when the ozone, UV and chlorine doses reached 5 mg/L, 15 mJ/cm2 and 4 mg/L, respectively, the log removal of Escherichia coli (E. coli) reached 5 log. A trailing phenomenon was observed with further increases in the disinfectant dosage. Under the combined treatment scenarios, ozone pretreatment resulted in substantial removal of color, turbidity, UV254, fluorescence excitation-emission matrix (FEEM) and chlorine consuming organics, thus enhancing the efficiency of subsequent UV irradiation or chlorine treatments. In the sequential ozone-UV-chlorine experiments, E. coli inactivation reached 7 log with ozone, UV and available chlorine of 3 mg/L, 5 or 10 mJ/cm2 and 2.5 mg/L, respectively. On the basis of the results from the actual WRP, the estimated operating cost per unit for the disinfection systems is 0.065 CNY/t, which is economical for long-term operation.
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Affiliation(s)
- Qi Shi
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Zhuo Chen
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China.
| | - Hai Liu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; School of Environment, Guangzhou Key Laboratory of Environmental Exposure and Health, Jinan University, Guangzhou 510632, PR China; Guangdong Key Laboratory of Environmental Pollution and Health, Jinan University, Guangzhou 510632, PR China
| | - Yun Lu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Kuixiao Li
- Research and Development Center, Beijing Drainage Group Co., Ltd, Beijing 100124, PR China
| | - Yulong Shi
- Research and Development Center, Beijing Drainage Group Co., Ltd, Beijing 100124, PR China
| | - Yu Mao
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China
| | - Hong-Ying Hu
- Environmental Simulation and Pollution Control State Key Joint Laboratory, State Environmental Protection Key Laboratory of Microorganism Application and Risk Control (SMARC), School of Environment, Tsinghua University, Beijing 100084, PR China; Beijing Laboratory for Environmental Frontier Technologies, Beijing 100084, PR China; Shenzhen Environmental Science and New Energy Technology Engineering Laboratory, Tsinghua-Berkeley Shenzhen Institute, Shenzhen 518055, PR China.
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