Abstract
Bioadsorption is an organic technique as different bioadsorbents prepared from agricultural waste, forest waste, industrial waste and algae can be utilized for the greatest expulsion of substantial metals from wastewater. In the present study, an attempt has been made to remove the chromium concentration in synthetic wastewater using rice husk and saw dust as adsorbent synthesized from agricultural waste. The rice husk was collected from an agricultural production process industry and sawdust collected from the local wood shop was used for adsorption of chromium after grinding and then passing through a sieve size of 300 µm. The maximum chromium removal efficiency of 90.7% and 82% have been observed using rice husk and saw dust as adsorbent, respectively, with an adsorbent dosage of 3 g at an initial chromium concentration of 10 mg/L. The maximum Cr removal of 92.1% has been observed at a pH value of 6 and minimum Cr removal of 75.8% has been found at a pH value of 2 using rice husk as adsorbent. Also, the maximum Cr removal efficiency of 85% has been observed at pH 6 and minimum Cr removal efficiency of 55% has been observed at pH 2 using saw dust as an adsorbent. The adsorption isotherm Langmuir and Freundlich model has also been used in order to fit the obtained data. The correlation coefficients for the removal of chromium from aqueous solution using rice husk and saw dust adsorbent has also been computed. From the present study, it can be compared that the correlation coefficients indicates the fact that Langmuir isotherm provides a better model as compared to the Freundlich model for rice husk as an adsorbent. The adsorption in such a system is based on monolayer sorption on to the surface limiting the finite number of identical sorption sites.
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Hussain, A., Tiwari, D., Heider, Z. (2021). Removal of Chromium from Synthetic Wastewater Using Synthesized Low-Cost Adsorbents. In: Singh, D., Awasthi, A.K., Zelinka, I., Deep, K. (eds) Proceedings of International Conference on Scientific and Natural Computing. Algorithms for Intelligent Systems. Springer, Singapore. https://doi.org/10.1007/978-981-16-1528-3_25
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