Efficiency of a new hybrid multi-soil-layering eco-friendly technology for removing pollutants from domestic wastewater under an arid climate

Zidan, Khadija; Mandi, Laila; Hejjaj, Abdessamed; Sbahi, Sofyan; Fels, Abdelhafid El Alaoui El; Ouazzani, Naaila; Assabbane, Ali

doi:10.1016/j.jwpe.2022.103482

Cited by 11 publications

(3 citation statements)

References 51 publications

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“…To treat rural domestic wastewater, Wang et al [17] added sludge-based biochar materials into SMBs, which strengthened the MSL system performance, and the removal efficiencies of COD, ammonia nitrogen, TN, and TP were 80%, 90%, 65%, and 92%, respectively. Zidan et al [38] employed a hybrid MSL system treating domestic wastewater. The hybrid MSL system is composed of a vertical flow MSL unit in series with a subsurface horizontal flow MSL unit.…”

Section: Domestic Wastewatermentioning

confidence: 99%

Progress in Multi-Soil-Layering Systems for Wastewater Treatment

Ma,

Wu,

Feng

et al. 2024

Sustainability

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The use of decentralized wastewater treatment technologies is a reasonable solution for rural areas. As a decentralized treatment technology, the multi-soil-layering (MSL) system has recently drawn an increasing amount of attention owing to its merits, such as a high hydraulic load rate, small land area occupation, low probability of clogging, low investment, and low operation cost. This review summarizes the progress in MSL systems in the past decade, focusing on the directions of efforts for system optimization, the latest applications of MSL systems to various wastewater treatments, and the integration of MSL with other technologies. The great application potential of MSL systems is illustrated, and future research directions regarding better application of MSL systems are provided.

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Section: Domestic Wastewatermentioning

confidence: 99%

Progress in Multi-Soil-Layering Systems for Wastewater Treatment

Ma,

Wu,

Feng

et al. 2024

Sustainability

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“…Traditional sewage treatment processes usually include steps such as physical treatment, chemical treatment and biological treatment. In the physical treatment, sewage through the grid, sand tank and other equipment to remove solid substances, and then into the chemical treatment stage, through the addition of chemical agents to remove dissolved organic matter and nutrients [9] . Finally, the sewage enters the biological treatment stage, where pollutants such as organic matter and nitrogen and phosphorus are further removed by the microbial communities such as suspended biofilm or activated sludge [10] .…”

Section: Traditional Sewage Treatment Processmentioning

confidence: 99%

Analysis of the diversity of microbial communities in typical domestic sewage

2023

erej

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This review paper mainly introduces the relationship between domestic sewage treatment and microbial communities. First, the paper provides an overview of the source and composition of domestic sewage and the importance of microbial diversity in domestic sewage treatment. Then, the paper summarizes the current research status of microbial communities in typical domestic sewage. In the second part, the paper explores the factors affecting the microbial diversity in domestic sewage [i] . Then, in the third part, the paper describes the diversity of microbial communities in typical domestic sewage, respectively from the biological classification community composition and functional classification community composition. In the fourth part, the paper explores the ecological functions of microbial communities in domestic sewage. Finally, in the fifth part, the paper analyzes the influence of the traditional sewage treatment process and the new sewage treatment technology on the microbial community, and introduces the indicator role and assessment method of the microbial community. It provides an important reference for further research and optimization of domestic sewage treatment.

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“…ML has been used in various environmental disciplines due to its ability to simulate the behavior of aquatic systems, such as wastewater treatment plants [22,23]. Wastewater treatment plays a key role in the economy and conservation of water resources, as well as in the environmental protection of aquatic environments.…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

El Alaoui El Fels,

Mandi,

Kammoun

et al. 2023

Water

Self Cite

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The concept of using wastewater as a substitute for limited water resources and environmental protection has enabled this sector to make major technological advancements and, as a result, has given us an abundance of physical data, including chemical, biological, and microbiological information. It is easier to comprehend wastewater treatment systems after studying this data. In order to achieve this, a number of studies use machine learning (ML) algorithms as a proactive approach to solving issues and modeling the functionalities of these processing systems while utilizing the experimental data gathered. The goal of this article is to use textual analysis techniques to extract the most popular machine learning models from scientific documents in the “Web of Science” database and analyze their relevance and historical development. This will help provide a general overview and global scientific follow-up of publications dealing with the application of artificial intelligence (AI) to overcome the challenges faced in wastewater treatment technologies. The findings suggest that developed countries are the major publishers of articles on this research topic, and an analysis of the publication trend reveals an exponential rise in numbers, reflecting the scientific community’s interest in the subject. As well, the results indicate that supervised learning is popular among researchers, with the Artificial Neural Network (ANN), Random Forest (RF), Support Vector Machine (SVM), Linear Regression (LR), Adaptive Neuro-Fuzzy Inference System (ANFIS), Decision Tree (DT), and Gradient Boosting (GB) being the machine learning models most frequently employed in the wastewater treatment domain. Research on optimization methods reveals that the most well-known method for calibrating models is genetic algorithms (GA). Finally, machine learning benefits wastewater treatment by enhancing data analysis accuracy and efficiency. Yet challenges arise as model training demands ample, high-quality data. Moreover, the limited interpretability of machine learning models complicates comprehension of the underlying mechanisms and decisions in wastewater treatment.

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Efficiency of a new hybrid multi-soil-layering eco-friendly technology for removing pollutants from domestic wastewater under an arid climate

Cited by 11 publications

References 51 publications

Progress in Multi-Soil-Layering Systems for Wastewater Treatment

Progress in Multi-Soil-Layering Systems for Wastewater Treatment

Analysis of the diversity of microbial communities in typical domestic sewage

Artificial Intelligence and Wastewater Treatment: A Global Scientific Perspective through Text Mining

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