Effect of pH on Pollutants Removal of Ship Sewage Treatment in an Innovative Aerobic-Anaerobic Micro-Sludge MBR System

Cai, Yuhang; Ben, Teng; Zaidi, Asad A.; Shi, Yue; Zhang, Kun; Lin, Aqiang; Liu, Chen

doi:10.1007/s11270-019-4211-0

Cited by 22 publications

(3 citation statements)

References 50 publications

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“…For the present study, high throughput sequencing was employed to analyze the microbial community. FastDNA® Spin Kit was used to acquiring the DNA samples followed by quality evaluation using the technique of absorbance ratio at A260/A280 and A260/A230 using a NanoDrop ND-2000 spectrophotometer [29,30]. Then the DNA samples were passed through a screening to select only those with a ratio >1.8 and 2.0 for A260/280 and A260/230, respectively.…”

Section: Methodsmentioning

confidence: 99%

Nanoparticles Synergistic Effect with Various Substrate Pretreatment and their Comparison on Biogas Production from Algae Waste

Zaidi

Khan

AlMohamadi

et al. 2021

Bull. Chem. React. Eng. Catal.

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Algae waste is one of the potential substrates for biogas and biohydrogen production and can comprehend multiple benefits of waste treatment and resource utilization. In view of the key bottlenecks such as low substrate degradation rate and poor productivity of algae waste production process, this study analyzes the combined effect of two metallic and metallic oxide nanoparticles with different substrate pretreatment methods (autoclave, ultrasonic, and microwave methods) to investigate the effect of anaerobic digestion of green algae (Enteromorpha). The results showed that out of the three pretreatment methods, microwave pretreatment and nanoparticles' synergistic effect significantly increases biogas production. The microbial community composition at the phylum level was analyzed. It was observed that the Firmicutes were most abundant across all samples. The relative abundance of Firmicutes for control, Ni NPs + MW, Co NPs + MW, and Fe3O4 NPs + MW groups were 51.78, 70.37, 75.77, and 83.93%, respectively. The second most abundant was of Bacteroidetes that also contributes to hydrogen production. This relatively high abundance of Firmicutes and Bacteroidetes promises its potential applications in a hydrogen production facility. Copyright © 2021 by Authors, Published by BCREC Group. This is an open access article under the CC BY-SA License (https://creativecommons.org/licenses/by-sa/4.0).

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Section: Methodsmentioning

confidence: 99%

Nanoparticles Synergistic Effect with Various Substrate Pretreatment and their Comparison on Biogas Production from Algae Waste

Zaidi

Khan

AlMohamadi

et al. 2021

Bull. Chem. React. Eng. Catal.

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“…Ren et al [84] used a Backpropagation Neural Network (BPNN) model to simulate the removal of COD f ilt and COD by conducting a pilot-scale submerged MBR to treat high-strength Chinese traditional medicine wastewater and confirmed that the model can accurately predict the removal rates and help to obtain the optimum operational conditions. Cai et al [85] conducted an aerobic-anaerobic micro-sludge MBR (O-AMSMBR) to study the effect of pH on pollutant removal performance of a reactor using Wavelet Neural Network (WNN) and BPNN models and showed that pH is a key factor affecting the COD and TN removal efficiencies of O-AMSMBR. To optimize the processing efficiency of MBRs, they further studied the effects of various ecological factors on effluent marine domestic sewage by implementing an air-lift multilevel circulation MBR and analyzed their impacts on the O-AMSMBR performance using the BPNN model [86].…”

Section: Laboratory-scale Researchmentioning

confidence: 99%

A Review on Applications of Artificial Intelligence in Wastewater Treatment

Wang,

Cheng,

Liu

et al. 2023

Sustainability

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In recent years, artificial intelligence (AI), as a rapidly developing and powerful tool to solve practical problems, has attracted much attention and has been widely used in various areas. Owing to their strong learning and accurate prediction abilities, all sorts of AI models have also been applied in wastewater treatment (WWT) to optimize the process, predict the efficiency and evaluate the performance, so as to explore more cost-effective solutions to WWT. In this review, we summarize and analyze various AI models and their applications in WWT. Specifically, we briefly introduce the commonly used AI models and their purposes, advantages and disadvantages, and comprehensively review the inputs, outputs, objectives and major findings of particular AI applications in water quality monitoring, laboratory-scale research and process design. Although AI models have gained great success in WWT-related fields, there are some challenges and limitations that hinder the widespread applications of AI models in real WWT, such as low interpretability, poor model reproducibility and big data demand, as well as a lack of physical significance, mechanism explanation, academic transparency and fair comparison. To overcome these hurdles and successfully apply AI models in WWT, we make recommendations and discuss the future directions of AI applications.

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“…MBR technology is still facing many challenges concerning complex operational requirements and uncontrollability of marine environment. Many influencing factors, like temperature, HRT, pH, influent pollutants loading rate and C/N ratio, were considered to affect the removal efficiency of MBR [16,17]. In marine pollution aspect, constant pollutants shock and unstable C/N ratio are two significant characteristics of ship domestic sewage [18].…”

Section: Introductionmentioning

confidence: 99%

Effect of Volume Loading Rate and C/N on Ship Domestic Sewage Treatment by Two Membrane Bioreactors

Cai

Zaidi

Sun

et al. 2019

Period. Polytech. Chem. Eng.

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Design of ship sewage treatment systems that not only satisfy the use of small space on board but also meets International Maritime Organisation (IMO) latest emission standards is still a challenging problem for ship industry. This study provides a comparative disquisition between two different MBR reactors i.e, air-lift multilevel circulation membrane reactor (AMCMBR) and anaerobic/anoxic/aerobic membrane reactor (AOA-MBR) for domestic sewage treatment. The influence of pollutants volume loading rate (VLR) and C/N on effluent chemical oxygen demand (COD), ammonium nitrogen (NH4+-N) and TN for marine domestic sewage was analyzed. The results revealed that AMCMBR showed better removal efficiencies for COD and TN than AOA-MBR. The volume of AMCMBR was only half of the AOA-MBR. In addition, high average value of mixed liquor volatile suspended solids (MLVSS)/mixed liquid suspended solids (MLSS) (i.e. 0.75) of AMCMBR indicated high biomass and good pollutants removal achieved by this reactor. An interesting phenomenon was found in the study regarding Urease activity for the two reactors. Urease activity for AMCMBR in different working conditions all exceeded AOA-MBR and there exist no clear difference of NR activities between AMCMBR and AOA-MBR except for low C/N ratio (i.e. 6 and 4). This phenomenon proved that AMCMBR has a greater performance for treating ship domestic wastewater.

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Effect of pH on Pollutants Removal of Ship Sewage Treatment in an Innovative Aerobic-Anaerobic Micro-Sludge MBR System

Cited by 22 publications

References 50 publications

Nanoparticles Synergistic Effect with Various Substrate Pretreatment and their Comparison on Biogas Production from Algae Waste

Nanoparticles Synergistic Effect with Various Substrate Pretreatment and their Comparison on Biogas Production from Algae Waste

A Review on Applications of Artificial Intelligence in Wastewater Treatment

Effect of Volume Loading Rate and C/N on Ship Domestic Sewage Treatment by Two Membrane Bioreactors

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