Removal of PAHs, TSS, oils and fats from ammonium-rich coke wastewater by granular filtration.

Coke wastewater is a complex industrial wastewater due to its high content of toxic compounds such as cyanides, thiocyanates, phenols, tar, oils, and fats. After a series of treatments, wastewater with a high ammonium content is obtained (around 4,150 mg·L-1). A stripping process is used to reduce it.

Impact of COVID-19 restrictions on hourly levels of PM10, PM2.5 and black carbon at an industrial suburban site in northern Spain.

Due to the COVID-19 pandemic, lockdown restrictions were established around the world. Many studies have assessed whether these restrictions affected atmospheric pollution. Comparison between them is difficult as the periods of time considered are generally not the same and thus, different conclusions may be reached.

Removal of fluoride from coke wastewater by aluminum doped chelating ion-exchange resins: a tertiary treatment.

Coke wastewater is one of the most problematic industrial wastewaters, due to its large volume and complex pollutant load. In this study, ion exchange technology was investigated with the objective of reducing the fluoride content of the effluent from a coke wastewater treatment plant (26.7 mg F/L).

Knowledge extraction from a nitrification denitrification wastewater treatment plant using SOM-NG algorithm.

SOM-NG is a hybrid algorithm that is able to carry out visualization of process data, nonlinear function approximation, classification and clustering. The supervised version of SOM-NG produces a new type of 2D lattices called gradient planes which are useful to determine the dynamics of a target variable according to the remaining training variables. In this way, it is an interesting tool for data mining in order to extract knowledge from databases for nonlinear systems.

Comparing feed-forward versus neural gas as estimators: application to coke wastewater treatment.

Numerous papers related to the estimation of wastewater parameters have used artificial neural networks. Although successful results have been reported, different problems have arisen such as overtraining, local minima and model instability. In this paper, two types of neural networks, feed-forward and neural gas, are trained to obtain a model that estimates the values of nitrates in the effluent stream of a three-step activated sludge system (two oxic and one anoxic).

Life cycle analysis of Municipal Solid Waste management possibilities in Asturias, Spain.

Directive 1994/62 concerning packaging and packaging waste and Directive 1999/31 related to waste disposal will substantially modify the management and treatment of Municipal Solid Waste (MSW) in Europe. In this study, a life cycle analysis has been carried out of the different possibilities of managing Municipal Solid Waste in Asturias. The "Integrated Waste Management" (IWM-1) model was employed, analysing the different alternatives for collection and treatment of MSW.