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Virtual water quality monitoring at inactive monitoring sites using Monte Carlo optimized artificial neural networks: A case study of Danube River (Serbia)
(Elsevier Science Bv, Amsterdam, 2019)
Rationalization of water quality monitoring stations nowadays is applied in many countries. In some cases, missing data from abandoned/inactive stations, spatial and temporal, could be very important, hence the use of ...
Honeybees as sentinels of lead pollution: Spatio-temporal variations and source appointment using stable isotopes and Kohonen self-organizing maps
(Elsevier, Amsterdam, 2018)
In this study, honeybees were used to determine spatio-temporal variations and origin sources of Pb. Lead concentrations and isotopic composition were used in combination with selected statistical methods. The sampling was ...
Emerging contaminants in sediment core from the Iron Gate I Reservoir on the Danube River
(Elsevier, Amsterdam, 2019)
The Iron Gate I Reservoir is the largest impoundment on the Danube River. It retains gt 50% of the incoming total suspended solids load and the associated organic contaminants. In the sediment core of the Iron Gate I ...
Chemometrics in biomonitoring: Distribution and correlation of trace elements in tree leaves
(Elsevier, Amsterdam, 2016)
The concentrations of 15 elements were measured in the leaf samples of Aesculus hippocastanum, Tilia spp., Betula pendula and Acer platanoides collected in May and September of 2014 from four different locations in Belgrade, ...
Consolidated vs new advanced treatment methods for the removal of contaminants of emerging concern from urban wastewater
(Elsevier Science Bv, Amsterdam, 2019)
Urban wastewater treatment plants (WWTPs) are among the main anthropogenic sources for the release of contaminants of emerging concern (CECs) into the environment, which can result in toxic and adverse effects on aquatic ...
A linear and non-linear polynomial neural network modeling of dissolved oxygen content in surface water: Inter- and extrapolation performance with inputs' significance analysis
(Elsevier Science Bv, Amsterdam, 2018)
Accurate prediction of water quality parameters (WQPs) is an important task in the management of water resources. Artificial neural networks (ANNs) are frequently applied for dissolved oxygen (DO) prediction, but often ...
Occurrence and fate of emerging wastewater contaminants in Western Balkan Region
(Elsevier B.V., 2008)
This paper reports on a comprehensive reconnaissance of over seventy individual wastewater contaminants in the region of Western Balkan (WB; Bosnia and Herzegovina, Croatia and Serbia), including some prominent classes of ...
PM10 emission forecasting using artificial neural networks and genetic algorithm input variable optimization
(Elsevier Science Bv, Amsterdam, 2013)
This paper describes the development of an artificial neural network (ANN) model for the forecasting of annual PM10 emissions at the national level, using widely available sustainability and economical/industrial parameters ...
Steroid-based tracing of sewage-sourced pollution of river water and wastewater treatment efficiency: Dissolved and suspended water phase distribution
(Elsevier B.V., 2022)
In this work, the environmental distribution of steroid compounds and the level of sewage-derived contamination were assessed using sterol ratios in the confluence area of two major rivers in the Serbian capital, where raw ...