Phytoremediation of nitrogen and phosphorus pollutants from glass industry effluent by using water hyacinth (Eichhornia crassipes (Mart.) Solms): Application of RSM and ANN techniques for experimental optimization

The present study aimed to assess the efficiency of the water hyacinth ( Eichhornia crassipes (Mart.) Solms) plant for the reduction of nitrogen and phosphorus pollutants from glass industry effluent (GIE) as batch mode phytoremediation experiments. For this, response surface methodology (RSM) and a...

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Vydáno v:	Environmental science and pollution research international Ročník 30; číslo 8; s. 20590 - 20600
Hlavní autoři:	Singh, Jogendra, Kumar, Pankaj, Eid, Ebrahem M., Taher, Mostafa A., El-Morsy, Mohamed H. E., Osman, Hanan E. M., Al-Bakre, Dhafer A., Kumar, Vinod
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.02.2023
Témata:	Aquatic Pollution Atmospheric Protection/Air Quality Control/Air Pollution Biodegradation, Environmental Earth and Environmental Science Ecotoxicology Eichhornia Eichhornia crassipes Environment Environmental Chemistry Environmental Health Environmental Pollutants glass industry logit analysis Neural Networks, Computer Nitrogen Phosphorus phytoremediation plant density Plants prediction Research Article response surface methodology total phosphorus Waste Water Technology Water Management Water Pollutants, Chemical - analysis Water Pollution Control Artificial neural network Response surface method Glass industry effluent Phytoremediation Eichhornia crassipes
ISSN:	1614-7499, 1614-7499
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