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Experimental and theoretical consideration of the factors influencing cationic pollutants retention by seashell waste
Author(s) -
Egerić Marija,
Smičiklas Ivana,
Mraković Ana,
Jović Mihajlo,
ŠljivićIvanović Marija,
Antanasijević Davor,
Ristić Mirjana
Publication year - 2018
Publication title -
journal of chemical technology and biotechnology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.64
H-Index - 117
eISSN - 1097-4660
pISSN - 0268-2575
DOI - 10.1002/jctb.5516
Subject(s) - sorption , pollutant , chemistry , metal , environmental chemistry , cationic polymerization , leachate , environmental science , adsorption , organic chemistry
BACKGROUND Seashell waste (SW) is rich in biogenic calcium carbonate and potentially can substitute geological sources in various applications, such as the separation of heavy metals and radionuclides from contaminated solutions. This study aims to compare SW sorption efficiency towards different chemical species (Cu 2+ , Zn 2+ , Pb 2+ and Sr 2+ ) and to evaluate the effects of various factors based on the experimental data and modeling approach. RESULTS The reaction of SW with aqueous metal solutions is a combination of several processes that result in metal retention, Ca 2+ release, and changes in pH. SW demonstrates variable selectivity for investigated cations, depending on their concentrations and reaction times. Maximum sorption capacities declined in the order Zn 2+ > Pb 2+ ≈ Sr 2+ > Cu 2+ . The model based on general regression neural network (GRNN) architecture was developed, which enabled prediction of removal efficiency taking into account the process specific, metal specific parameters and their non‐linear interactions. Initial concentration and covalent radius of a cation exhibit the highest, while the initial pH the lowest significance. CONCLUSION Ecological problems caused by SW accumulation in coastal areas could be mitigated by mastering technologies for their practical utilization. The results obtained facilitate the understanding of cationic pollutants removal by SW in the range of experimental conditions, while the GRNN approach demonstrates advantages in modeling complex sorption processes. © 2017 Society of Chemical Industry