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Prikaz rezultata 11-20 od 33
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 ...
Prediction of municipal solid waste generation using artificial neural network approach enhanced by structural break analysis
(Springer Heidelberg, Heidelberg, 2017)
This paper presents the development of a general regression neural network (GRNN) model for the prediction of annual municipal solid waste (MSW) generation at the national level for 44 countries of different size, population ...
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 ...
Characterization of PM(2.5)sources in a Belgrade suburban area: a multi-scale receptor-oriented approach
(Springer Heidelberg, Heidelberg, 2020)
Designated as the most harmful for health, PM(2.5)aerosol fraction was a subject of our study. It was collected for all four seasons during 2014/15 in the suburban area of Belgrade (Serbia) and analysed for Al, Si, P, S, ...
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 ...
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 ...
Estimation of NMVOC emissions using artificial neural networks and economical and sustainability indicators as inputs
(Springer Heidelberg, Heidelberg, 2016)
This paper describes the development of an artificial neural network (ANN) model based on economical and sustainability indicators for the prediction of annual non-methane volatile organic compounds (NMVOCs) emissions in ...
Non-thermal plasma and ultrasound-assisted open lactic acid fermentation of distillery stillage
(Springer Heidelberg, Heidelberg, 2019)
Stillage is the main by-product of bioethanol production and the cost of its treatment significantly affects the economy of bioethanol production. A process of thermal sterilization before lactic acid fermentation (LAF) ...
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 ...
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 ...