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Wyświetlanie 1-2 z 2
Tytuł:
Wastewater Treatment Methods for Effluents from the Confectionery Industry – an Overview
Autorzy:
Zajda, Magdalena
Aleksander-Kwaterczak, Urszula
Powiązania:
https://bibliotekanauki.pl/articles/124113.pdf
Data publikacji:
2019
Wydawca:
Polskie Towarzystwo Inżynierii Ekologicznej
Tematy:
confectionery industry
wastewater treatment
biological oxygen demand
chemical oxygen demand
low-cost material
Opis:
Wastewater from the confectionery industry is characterized by daily and seasonal variability of composition and quantity which adversely affects the process of their disposal. Confectionery plants discharge about 300-500 m3 per month of technological wastewater. Sewage from the confectionery industry belongs to biologically degradable. It is characterized by high values of chemical oxygen demand (COD) and biological oxygen demand (BOD). The article reviews various methods used to treat wastewater from the confectionery industry. Attention was paid to the applicability of a particular method, its advantages and disadvantages and the costs of implementation. The technology of industrial wastewater treatment uses both mechanical and physicochemical methods as well as biological ones. Techniques of sewage treatment usually consist of several stages which use different processes. Low-cost materials such as natural minerals, agricultural waste, industrial waste, biosorbents, and others contribute to the improvement of aerobic sewage conditions. The main weakness of typical sewage treatment plants is their large area, high investment, and exploitation costs. Therefore, a good solution may be the use of the membrane biological reactor which combines the classical technique of activated sludge and filtration on micro-filtering membranes.
Źródło:
Journal of Ecological Engineering; 2019, 20, 9; 293-304
2299-8993
Pojawia się w:
Journal of Ecological Engineering
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Performance prediction and control for wastewater treatment plants using artificial neural network modeling of mechanical and biological treatment
Autorzy:
Alnajjar, Hussein Y.H.
Üçüncü, Osman
Powiązania:
https://bibliotekanauki.pl/articles/27311558.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
artificial neural network
wastewater treatment
total phosphorus
total nitrogen
biological oxygen demand
sztuczna sieć neuronowa
oczyszczanie ścieków
fosfor całkowity
azot całkowity
zapotrzebowanie na tlen
Opis:
Biological treatment in wastewater treatment plants appears to be one of the most crucial factors in water quality management and planning. Though, measuring this important factor is challenging, and obtaining reliable results requires signifi cant eff ort. However, the use of artifi cial neural network (ANN) modeling can help to more reliably and cost-effectively monitor the pollutant characteristics of wastewater treatment plants and regulate the processing of these pollutants. To create an artifi cial neural network model, a study of the Samsun Eastern Advanced Biological WWTP was carried out. It provides a laboratory simulation and prediction option for flexible treatment process simulations. The models were created to forecast influent features that would affect effluent quality metrics. For ANN models, the correlation coefficients R-TRAINING and R-ALL are more than 0.8080. The MSE, RMSE, and MAPE were less than 0.8704. The model’s results showed compliance with the permitted wastewater quality standards set forth in the Turkish water pollution control law for the environment where the treated wastewater is discharged. This is a useful tool for plant management to enhance the quality of the treatment while enhancing the facility’s dependability and efficiency.
Źródło:
Archives of Environmental Protection; 2023, 49, 2; 16--29
2083-4772
2083-4810
Pojawia się w:
Archives of Environmental Protection
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-2 z 2

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