Study of an Oily Water Treatment Process in a Pilot Hybrid System Combining Air Flotation and a Constructed Wetland: Data Analysis, Efficiency Optimization and Scale-Up

Filho, Alexandre Augusto Paredes Selva; Nascimento, Laís A.; Rufino, Raquel Diniz; Luna, Juliana Moura de; Brasileiro, Pedro Pinto Ferreira; Silva, Rita de Cássia Freire Soares da; Benachour, Mohand; Santos, Valdemir Alexandre dos; Sarubbo, Leonie Asfora

doi:10.30638/eemj.2021.025

Cited by 2 publications

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“…In order to curb the continued deterioration of the wetland environment, the Chinese government has taken a series of measures to promote the construction of ecological civilisation at all levels and to strengthen wetland protection and restoration. Since China acceded to the Convention on Wetlands in 1992, it has actively fulfilled the purposes and obligations of the Convention, promoted wetland protection and restoration, and facilitated the high-quality development of wetlands and the sustainable development of wetlands [6]. In accordance with the requirements of the Wetland Protection Law on the preparation of wetland protection planning, it is formed on the basis of summarising and evaluating the national wetland protection work in the "13th Five-Year Plan", and is formed after in-depth investigation and research, and after fully soliciting opinions.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

2024

Teh. vjesn.

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Wetland restoration work is crucial for ecosystem development, and how to scientifically evaluate wetland restoration programmes is the key to improve the effectiveness of wetland restoration. In order to solve the problems of inadequate judgement and human influence in the evaluation of wetland restoration programmes, this paper proposes a wetland restoration programme evaluation model based on Fuzzy Neural Network method, which is based on fuzzy theory and combines the adaptive function and self-learning function of neural network to evaluate three wetland restoration programmes. The results show that programme B is better than programmes A and C and is suitable for long-term application in wetland restoration work in this area. It is concluded that the use of Fuzzy Neural Network model to evaluate the wetland restoration programmes is more accurate, more personalised, and has a better operation rate, which is an important means of evaluating the wetland restoration programmes and an important guideline to carry out the wetland work.

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Section: Introductionmentioning

confidence: 99%

A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

2024

Teh. vjesn.

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“…A parallel sigmoidal (PS) model was applied by Blagojev et al to describe the biosorption process and confirm its applicability to different types of biomass and various types of heavy metal ion [54]. Selva Filho et al developed a two-parameter model based on a central composite rotatable design to find the optimal oil-water separation efficiency, involving floating macrophytes of the species Eichhornia crassipes in constructed wetlands [55]. The Box-Behnken experimental design model was applied by Jaafari and Yaghmaeian to plan biosorption experiments with heavy metals adsorbing onto the freshwater algae Chlorella coloniales to determine the effects of independent parameters, such as metal concentration, time of reaction, and algae dose, as well as to optimize these variable [56].…”

Section: Introductionmentioning

confidence: 99%

Modeling and Optimization of Heavy Metals Biosorption by Low-Cost Sorbents Using Response Surface Methodology

Ferţu

Bulgariu

2022

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This paper exploits, through modeling and optimization, the experimental laboratory data on the biosorption of heavy metal ions Pb(II), Cd(II), and Zn(II) from aqueous media using soybean and soybean waste biomasses. The biosorption modeling was performed using the Response Surface Methodology, followed by optimization based on numerical methods. The aim of the modeling was to establish the most probable mathematical relationship between the dependent variables (the biosorption efficiency of the biosorbents when adsorbing metal ions, R(%), and the biosorption capacity of sorbents, q(mg/g)) and the process parameters (pH; sorbent dose, DS (g/L); initial metal ion concentration in solution, c0 (mg/L); contact time, tc (min); temperature, T (°C)), validated by methodologies specific to the multiple regression analysis. Afterward, sets of solutions were obtained through optimization that correlate various values of the process parameters to maximize the objective function. These solutions also confirmed the performance of soybean waste biomass in the removal of heavy metal ions from polluted aqueous effluents. The results were validated experimentally.

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Study of an Oily Water Treatment Process in a Pilot Hybrid System Combining Air Flotation and a Constructed Wetland: Data Analysis, Efficiency Optimization and Scale-Up

Cited by 2 publications

References 0 publications

A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

A Fuzzy Neural Network Approach for Evaluation of Wetland Restoration Programmes

Modeling and Optimization of Heavy Metals Biosorption by Low-Cost Sorbents Using Response Surface Methodology

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