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Now showing items 11-20 of 34
The photocatalytic degradation of carbofuran and Furadan 35-ST: the influence of inert ingredients
(Springer Heidelberg, Heidelberg, 2017)
A comparative study on photocatalytic degradation of the pesticide carbofuran and its commercial product Furadan 35-ST in an aqueous suspension of ZnO, irradiated by long-wave light (315-400 nm), is presented in this study. ...
Sorption of selected pharmaceuticals and pesticides on different river sediments
(Springer Heidelberg, Heidelberg, 2016)
In the present work, the sorption ability of 17 pharmaceutical compounds, two metabolites, and 15 pesticides (34 target compounds in total) onto four different river sediments was investigated separately. Selected compounds ...
Solid-phase extraction of multi-class pharmaceuticals from environmental water samples onto modified multi-walled carbon nanotubes followed by LC-MS/MS
(Springer Heidelberg, Heidelberg, 2017)
In this paper, pristine and chemically treated multi-walled carbon nanotubes (MWCNTs) were employed as solid-phase extraction sorbents for the isolation and enrichment of multi-class pharmaceuticals from the surface water ...
Artificial neural network modelling of biological oxygen demand in rivers at the national level with input selection based on Monte Carlo simulations
(Springer Heidelberg, Heidelberg, 2015)
Biological oxygen demand (BOD) is the most significant water quality parameter and indicates water pollution with respect to the present biodegradable organic matter content. European countries are therefore obliged to ...
Migration of cypermethrin to and through the PET containers and artificial neural network-based estimation of its emission
(Springer Verlag, 2019)
Nowadays, the extensive use of pesticides in crops production puts a significant challenge to minimize its side effects along with safe production, storage, and after-use treatment. This paper reports results related to ...
Modelling of dissolved oxygen content using artificial neural networks: Danube River, North Serbia, case study
(Springer Heidelberg, Heidelberg, 2013)
The aims of this study are to create an artificial neural network (ANN) model using non-specific water quality parameters and to examine the accuracy of three different ANN architectures: General Regression Neural Network ...
Arsenic removal by copper-impregnated natural mineral tufa part II: a kinetics and column adsorption study
(Springer Heidelberg, Heidelberg, 2019)
This batch and column kinetics study of arsenic removal utilized copper-impregnated natural mineral tufa (T-Cu(A-C)) under three ranges of particle size. Non-competitive kinetic data fitted by the Weber-Morris model and ...
The impacts of seawater physicochemical parameters and sediment metal contents on trace metal concentrations in musselsa chemometric approach
(Springer Heidelberg, Heidelberg, 2018)
The concentrations of Al, Ba, Cd, Co, Cr, Cu, Fe, Li, Mn, Ni, Pb, Sr, Zn, and Hg were studied in Mytilus galloprovincialis collected from the coastal area of Montenegro. The impact of seawater temperature, salinity, dissolved ...
Application of experimental design for the optimization of artificial neural network-based water quality model: a case study of dissolved oxygen prediction
(Springer Heidelberg, Heidelberg, 2018)
This paper presents an application of experimental design for the optimization of artificial neural network (ANN) for the prediction of dissolved oxygen (DO) content in the Danube River. The aim of this research was to ...
Nanoscale zerovalent iron (nZVI) supported by natural and acid-activated sepiolites: the effect of the nZVI/support ratio on the composite properties and Cd2+ adsorption
(Springer Heidelberg, Heidelberg, 2017)
Natural (SEP) and partially acid-activated (AAS) sepiolites were used to prepare composites with nanoscale zerovalent iron (nZVI) at different (SEP or AAS)/nZVI ratios in order to achieve the best nZVI dispersibility and ...