Application of a breakthrough biosorbent for removing heavy metals from synthetic and real wastewaters in a lab-scale continuous fixed-bed column
Introduction
As a consequence of global industrialisation and extensive use of machines in many industries, heavy metal pollution of the environment has now become a chronic worldwide problem and major threat to human health. Heavy metal ions such as cadmium, lead, zinc, nickel, copper, mercury and chromium or their compounds are now recognised as serious toxic pollutants due to their non-biodegradability and constant presence in the food chain.
In recent decades, the annual global release of heavy metal reached 22,000 tons (metric tons) for cadmium, 939,000 tons for copper, 783,000 tons for lead and 1,350,000 tons for zinc (Ansari et al., 2014). Therefore, it is very urgent to treat industrial wastewater effluents, before they are discharged into the environment. It is essential that such action is in accordance with effective health and environmental regulations developed for various bodies of water (Shanmugaprakash and Sivakumar, 2015, Kalavathy and Miranda, 2010). To remediate heavy metal polluted effluents, a wide range of physicochemical/biological treatment technologies are currently employed in various industries (e.g. chemical precipitation, extraction, ion-exchange, filtration, reverse osmosis, membrane bioreactor and electrochemical techniques). Nonetheless, these existing methods are not effective enough in low concentrations and might be very expensive as a result of high chemical reagent and energy requirements, as well as the disposal problem of toxic secondary sludge (Montazer-Rahmati et al., 2011, Aksu et al., 2007). Recently, attention has focused on cheap agro-industrial wastes and by-products such as biosorbents (Bhatnagar et al., 2015, Bhatnagar and Sillanpaa, 2010). Although numerous studies on biosorption of heavy metals in batch systems have been published, in order to evaluate the feasibility of biosorption processes for real world applications, continuous biosorption studies in packed bed columns would be more useful (Bhatnagar et al., 2015). Additionally, a large volume of wastewater can be continuously treated using a defined quantity of adsorbent in the column. Reuse of biosorbent is also possible which makes the treatment process cheaper and more sustainable (Aksu et al., 2007).
This study’s main aim was to examine chemically modified multi-metal binding biosorbent (MMBB) in a packed bed column. Its biosorptive potential for removing heavy metals in batch system has been documented in previous studies (Abdolali et al., 2016, Abdolali et al., 2015). In the present work, the influences of bed height, flow rate and initial concentration on packed bed reactors performance have been investigated and the possibility of regeneration and reuse studied. To evaluate the ability and applicability of MMBB in a real life situation, the MMBB packed-bed column was applied to a real wastewater. Moreover, Thomas, Dose Response and Bed Depth Service Time (BDST) models were applied for experimental data to simulate the breakthrough curves and to find the column capacity in order to predict the scale-up of a unit plant.
Section snippets
Synthetic water and real wastewater
The synthetic stock solutions containing Cd, Cu, Pb and Zn were prepared by dissolving cadmium, copper, lead and zinc nitrate salt, Cd(NO3)2·4H2O, Cu3(NO)2·3H2O, Pb(NO3)2 and Zn(NO3)2·6H2O in Milli-Q water. All the reagents used for analysis were of analytical reagent grade from Scharlau (Spain) and Chem-Supply Pty Ltd (Australia). Concerning the removal of any inaccuracies in metal concentration, all stock solutions with metal concentrations of 3000 mg/L were examined by MP-AES to correct their
Results and discussion
The breakthrough curve showed the relative concentrations (Ct/Ci) on the y-axis versus time (t in min) on the x-axis. The column studies were conducted at the optimum pH value of 5.5 ± 0.1 (from the previous batch system studies (Abdolali et al., 2016, Abdolali et al., 2015) for synthetic solutions to be representative of environmentally relevant conditions. The pH value of real wastewater did not change after adding the heavy metal salts because it was 5.9 ± 0.1 and above the optimal pH. All the
Conclusions
Although all of the predictive models explained the dynamic behaviour of the breakthrough curves fairly well, the Thomas model strongly correlated the experimental data, as deduced from the statistical calculated parameters (i.e. R2 > 0.99). Furthermore, the BDST model was utilised successfully for the evaluation of the column’s performance. The results obtained from column regeneration demonstrated that reusing the modified MMBB is feasible. This study also indicated that modified MMBB could
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