Wastewater Treatment
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2021 ◽  
Vol 68 (1) ◽  
Ming Li ◽  
Kaitang Hu ◽  
Jin Wang

AbstractFlocculation is an important method to treat paper manufacturing wastewater. Coagulants and flocculants added to wastewater facilitate the aggregation and sedimentation of various particles in the wastewater and lead to the formation of floc networks which can be easily removed using physical methods. The goal of this paper is to determine the optimal hydraulic conditions using machine learning in order to enable efficient flocculation and improve performance during the treatment of deinking wastewater. Experiments using polymerized aluminum chloride as flocculant to treat deinking wastewater were carried out. Based on the orthogonal array test, 16 different combinations of hydraulic conditions were chosen to investigate the performance of flocculation, which was indicated by the turbidity of the solution after treatment. To develop a model representing the relationship between the hydraulic conditions and the performance of wastewater treatment, the machine learning methods, support vector regression and Gaussian process regression, were compared, whereby the support vector regression method was chosen. According to the fitness function derived from the support vector regression model, a genetic algorithm was applied to evaluate the optimal hydraulic conditions. Based on the optimal conditions determined by the genetic algorithm and real-life experience, a set of hydraulic conditions were implemented experimentally. After treatment under higher stirring speed at 120 rpm for 1 min and lower stirring speed at 20 rpm for 5 min at a temperature of 20 °C, the turbidity of deinking wastewater was measured as 1 NTU. The turbidity reduction was as high as 99.6%, which indicated good performance of the deinking wastewater treatment.

AMB Express ◽  
2021 ◽  
Vol 11 (1) ◽  
Jing Lu ◽  
Yiguo Hong ◽  
Ying Wei ◽  
Ji-Dong Gu ◽  
Jiapeng Wu ◽  

AbstractAnaerobic ammonium oxidation (anammox) process has been acknowledged as an environmentally friendly and time-saving technique capable of achieving efficient nitrogen removal. However, the community of nitrification process in anammox-inoculated wastewater treatment plants (WWTPs) has not been elucidated. In this study, ammonia oxidation (AO) and nitrite oxidation (NO) rates were analyzed with the incubation of activated sludge from Xinfeng WWTPs (Taiwan, China), and the community composition of nitrification communities were investigated by high-throughput sequencing. Results showed that both AO and NO had strong activity in the activated sludge. The average rates of AO and NO in sample A were 6.51 µmol L−1 h−1 and 6.52 µmol L−1 h−1, respectively, while the rates in sample B were 14.48 µmol L−1 h−1 and 14.59 µmol L−1 h−1, respectively. The abundance of the nitrite-oxidizing bacteria (NOB) Nitrospira was 0.89–4.95 × 1011 copies/g in both samples A and B, the abundance of ammonia-oxidizing bacteria (AOB) was 1.01–9.74 × 109 copies/g. In contrast, the abundance of ammonia-oxidizing archaea (AOA) was much lower than AOB, only with 1.28–1.53 × 105 copies/g in samples A and B. The AOA community was dominated by Nitrosotenuis, Nitrosocosmicus, and Nitrososphaera, while the AOB community mainly consisted of Nitrosomonas and Nitrosococcus. The dominant species of Nitrospira were Candidatus Nitrospira defluvii, Candidatus Nitrospira Ecomare2 and Nitrospira inopinata. In summary, the strong nitrification activity was mainly catalyzed by AOB and Nitrospira, maintaining high efficiency in nitrogen removal in the anammox-inoculated WWTPs by providing the substrates required for denitrification and anammox processes.

10.2196/33365 ◽  
2021 ◽  
Vol 10 (11) ◽  
pp. e33365
Mahbub-Ul Alam ◽  
Sharika Ferdous ◽  
Ayse Ercumen ◽  
Audrie Lin ◽  
Abul Kamal ◽  

Background The widespread and unrestricted use of antibiotics has led to the emergence and spread of antibiotic-resistant bacteria (ARB), antibiotic-resistance genes (ARGs), and antibiotic residues in the environment. Conventional wastewater treatment plants (WWTPs) are not designed for effective and adequate removal of ARB, ARGs, and antibiotic residues, and therefore, they play an important role in the dissemination of antimicrobial resistance (AMR) in the natural environment. Objective We will conduct a systematic review to determine the most effective treatment strategies for the removal of ARB, ARGs, and antibiotic residues from the treated effluent disposed into the environment from WWTPs that receive municipal, hospital, and domestic discharge. Methods We will search the MEDLINE, EMBASE, Web of Science, World Health Organization Global Index Medicus, and ProQuest Environmental Science Collection databases for full-text peer-reviewed journal articles published between January 2001 and December 2020. We will select only articles published in the English language. We will include studies that measured (1) the presence, concentration, and removal rate of ARB/ARGs going from WWTP influent to effluent, (2) the presence, concentration, and types of antibiotics in the effluent, and (3) the possible selection of ARB in the effluent after undergoing treatment processes in WWTPs. At least two independent reviewers will extract data and perform risk of bias assessment. An acceptable or narrative synthesis method will be followed to synthesize the data and present descriptive characteristics of the included studies in a tabular form. The study has been approved by the Ethics Review Board at the International Centre for Diarrhoeal Disease Research, Bangladesh (protocol number: PR-20113). Results This protocol outlines our proposed methodology for conducting a systematic review. Our results will provide an update to the existing literature by searching additional databases. Conclusions Findings from our systematic review will inform the planning of proper treatment methods that can effectively reduce the levels of ARB, ARGs, and residual antibiotics in effluent, thus lowering the risk of the environmental spread of AMR and its further transmission to humans and animals. International Registered Report Identifier (IRRID) PRR1-10.2196/33365

2022 ◽  
Vol 154 ◽  
pp. 111895
Hadis Marami ◽  
Li He ◽  
Shahin Rafiee ◽  
Benyamin Khoshnevisan ◽  
Panagiotis Tsapekos ◽  

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