Determination of removal efficiencies from Ni, Pb, Zn, wastewaters using perlite and zeolite

The heavy metals found in the water and the wastewater is one of the most crucial problems on account of public health and environmental protection. Due to the increasing industrialisation, the amount of heavy metals found in the wastewater is increasing gradually. The heavy metals mix into the wastewater as a result of the production facilities done by the industries such as electro-plating, pharmacologic production and metal industries. The border values of the heavy metals are 3 mg Ni/L for nickel and 3 mg Zn/L for zinc and 0,5 mg Pb/L for the lead in various sectors in the wastewaters in Turkey. The high concentrations of the heavy metals lead to various forms of cancer and chronic illnesses in human lives. There are several methods for the removal of heavy metals from the water and the wastewaters. The most common methods used are ion alternation, ultra filtration, chemical decomposition, reverse osmosis and adsorption. In this study, by using the experimental data obtained from the experimental studies the heavy metal nickel in the wastewater and its adsorption with perlite and zeolite was analysed, and an artificial neural network (ANN) aiming at predicting the removal of each heavy metal nickel, zinc and lead was developed and the availability of this model was tested. In the developed ANN model, the input concentration, contact time, the amount of adsorbent are taken as the input variables and the efficiency of nickel, zinc and lead removals were taken as the output variables. Consequently, the developed ANN model was efficient on account of predicting the efficiency of the removal nickel, zinc and lead concentrations. Although in a wastewater containing lead heavy metal the zeolite obtains a more efficient removal, the removal couldn?t be done only with the natural material perlite. However, the efficiency of perlite was better in each of the two heavy metals zinc and nickel.