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.

Effect of ultrasound pre-treatment in the anaerobic co-digestion of cattle manure with food waste and sludge.

This paper presents a study of the effect of applying ultrasound pre-treatment in the production of methane when co-digesting mixtures of cattle manure with food waste and sludge. A series of experiments were carried out under mesophilic and thermophilic conditions in continuously stirred-tank reactors containing 70% cattle manure, 20% food waste and 10% sewage sludge. Ultrasound pre-treatment allows operating at lower HRT, achieving higher volumetric methane yields: 0.

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).