Abstract
Lead contamination of water streams, a potential threat to ecosystem, was treated using a cation exchange resin under continuous conditions in a upflow column. The optimal pH for maximum lead removal was identified through the batch experiments. Neutral pH was found to be favorable due to non-existence of competing hydrogen ions and absence of hydroxide containing precipitate formations. The effects of flow rates (4.0 to 8.0 mL/ min) and the resin bed depth (6 to 18 cm) were studied under optimal pH and fixed initial lead concentration of 50 mg/L. The breakthrough curves were plotted and analyzed in detail. Bed Depth Service Time (BDST) and Thomas model were fitted to the experimental data and the model parameters were determined. The maximum exchange capacity of the bed (q0) was determined as 14.60 mg/g at a flow rate of 4 mL/min and a bed height of 12 cm and the Thomas model constant decreased with decrease in flow rate. BDST model parameters, namely, N0 and Ka, increased with increase in flow rates. BDST proved to be a better fit compared to Thomas model under the entire range of operating conditions tested.
INTRODUCTION
Environmental degradation due to heavy metal release is categorized as a serious issue due to the bioresistant and recalcitrant nature of the pollutants. Industrial and economic growth of the nations led to increased use of metals and resulted in enhanced manufacturing of metals. Many priority metal pollutants were identified and Lead is as one of the toxic pollutants used in manufacture of pigments, batteries etc (Hanafiah et al. 2006). Release of lead into the ecosystem is attributed to machinery, cable sheathing, battery making and alloying industries. The permissible limit for lead in potable water is fixed as 0.01 ppm in USA and Canada by WHO (Wajima 2014). Exposure to lead is reported to cause damages to nervous system, liver and renal failure. Heavy metal removal including lead has been attempted through physico-chemical methods like precipitation, sorption, coagulation, flocculation, ion-exchange and membrane based techniques. High cost, more requirement chemicals, poor efficiency, unsuitability to lower metal concentrations and secondary pollution creation are identified as the disadvantages which restricted the use of these methods (Rajamohan et al. 2014). Removal of metals using passive uptake by materials of biological origin was reported in many studies (Rajamohan & Rajasimman 2015). Studies on removal of lead using sulfur impreganated paper sludge (Wajima 2014), carbon aerogel (Kadirvelu et al. 2008) Escherichia coli genetically engineered with mice metallothionein I (Cantu et al. 2011), Sodium Hydroxide Modified Auricularia auricular Spent Substrate (Song et al. 2017), Cucumis melo (Akar et al. 2012) and Ficus benghalensis L (Surisetty et al. 2013) are reported. Ion exchange is a method which involves specific exchange of metal cations and proposed as an alternative due to its specificity and higher efficiency of metal removal (Wang et al. 2009; Shaomin et al. 2010). The main objective of this research was to removal lead using cation exchange resin, Dowex 50 in a continuous reactor. The effect of operating parameters, namely flow rate and bed height on the reactor performance was studied. Column data was modeled to understand the breakthrough patterns and bed exhaustion time.
MATERIALS AND METHODS
Resin
he resin, Dowex 50 WX8 (Fisher scientific, USA), was used in this study for the removal of lead ions. Dowex 50 WX8 is a strong-acid cation exchange resin available in the form of brown beads and is in the size range of +60 to +170 mesh. The resin was purchased and used without any modification.
Metal solution
Lead nitrate, (Sigma Aldrich, USA) was used as the source of lead for the preparation of aqueous solutions. They were used without any further purification. HCl and NaOH were used to adjust pH. All chemicals used were of analytical grade.
Experiments



Estimation of lead
The metal solution was filtered to remove the resin and the clear filtrate was analysed to determine the residual metal concentration using atomic absorption spectrophotometer (Perkin Elmer, 3110, USA).
RESULTS AND DISCUSSION
Effect of pH
Ion exchange is a separation process whose efficiency is related to ionic speciation of target pollutants. pH is considered as an important parameter which influences ionization properties and precipitation of molecules (Chunhua & Caiping 2011). The effect of initial pH on lead removal was investigated in the range of 4.0 to 11.0 at fixed conditions of temperature (30 °C), initial lead concentration (50 mg/L), resin dose (2 g/L) and shaking speed (300 rpm). These experiments are carried out to determine the optimum pH required for the removal of lead ions by the Dowex 50 WX8 cation resin.
Figure 1 represents the effect of pH on the removal of metal ions at equilibrium. The optimal pH for maximum lead removal efficiency was identified as 7.0 and the maximum removal efficiency was 88%. Lower metal removal at acidic pH in the range of 4.0 to 6.0 was reported to the excessive presence of competing hydrogen ions. Studies reported the decrease in dissociation degree of exchange group at low pH conditions and will eventually result in depleted exchange capacity between H+ and heavy metals ions (Chunhua & Caiping 2011). Decrease in metal exchange at alkaline pH (>7.0) could be due to the formation of a precipitate of metal hydroxide and hydrolyzation (Wang et al. 2009).
Effect of initial pH of the solution for the removal of Lead by Dowex 50 WX8.
Effect of flow rate
Flow rate is reported to influence the mass transfer gradient existing inside the ion exchange column and vary the time of contact between the resin surface and metal ions. The effect of flow rate on lead removal in an ion exchange column was investigated with an initial metal concentration of 50 mg/l, bed depth of 12 cm and temperature of 35 °C. The ion exchange column was operated with different flow rates until no further metal removal was observed. The breakthrough curve for the exchange column was determined by plotting the ratio of against time. It was inferred from the Figure 2 that when the flow through the column increases from 4.0 to 8.0 ml/min, the breakthrough point was attained earlier. The breakthrough curves generally occurred faster with higher flow rate (Runping et al. 2008) and therefore, breakthrough time for reaching saturation was increased significantly with a decrease in the flow rate. The study on column removal of congo red reported that at a lower flow rate of influent, the contact time between metal solution and resin particles was more and resulted in higher removal of metal ions in the column. Because of which breakthrough point shifted to right more with a decrease in the flow rate. The variation in the slope of the breakthrough curve and adsorption capacity can be explained on the basis of mass transfer principles.
Effect of bed depth
Bed depth is an important operating variable as it reflects the length of mass transfer zone available for the metal ions. In order to study the effect of bed height on lead removal, three different bed heights, namely 6, 12 and 18 cm, were employed. The influent lead solution of fixed concentration (50 mg/l) was passed through the fixed-bed column at a constant flow rate of 6 ml/min. Figure 3 presents the breakthrough time variations with changes in resin bed height. Decrease in resin bed height resulted in steeper breakthrough curves with sharper slopes. Due to limited availability of binding sites at low bed depths, the breakthrough times were shortened. At low bed depth, the metal ions were reported not to have sufficient time to diffuse into the surface of the resin (Xiao et al. 2016). Figure 3 described that the slope of breakthrough curve decreased with increasing bed height and resulted in a broadened mass transfer zone. Better metal removal at the maximum resin bed depth was related to an increase in the surface area bio sorbent, which provides more binding sites for sorption (Runping et al. 2008).
Column modeling
Model parameters
Flow rate (mL/min) . | Thomas model . | BDST model . | ||||
---|---|---|---|---|---|---|
R2 . | KT × 103 (ml/ h·mg) . | qo (mg/g) . | R2 . | No (mg/ L) . | Ka × 103 (L/mg h) . | |
8 | 0.974 | 12.50 | 9.914 | 0.998 | 5,728.62 | 7.50 |
6 | 0.967 | 9.65 | 13.665 | 0.979 | 3,983.58 | 2.07 |
4 | 0.954 | 8.11 | 14.860 | 0.963 | 2,831.70 | 1.50 |
Flow rate (mL/min) . | Thomas model . | BDST model . | ||||
---|---|---|---|---|---|---|
R2 . | KT × 103 (ml/ h·mg) . | qo (mg/g) . | R2 . | No (mg/ L) . | Ka × 103 (L/mg h) . | |
8 | 0.974 | 12.50 | 9.914 | 0.998 | 5,728.62 | 7.50 |
6 | 0.967 | 9.65 | 13.665 | 0.979 | 3,983.58 | 2.07 |
4 | 0.954 | 8.11 | 14.860 | 0.963 | 2,831.70 | 1.50 |
Regeneration of the resin
Regeneration of resin is an important requirement for economic feasibility of this separation process. Reusability of the resin was verified by repeating the metal removal –regeneration cycle for five times. Regeneration was done by 0.1 M HCl solution and the 98.1% lead removal was achieved in the first cycle. Removal efficiency decreased to 79% in cycle 5 which could be due to the depletion of ion exchange sites or lack of enough regenerating solution.
CONCLUSION
This research study demonstrated the successful application of strong acid cationic resin; Dowex 50 WX8, to remove Pb (II) from aqueous solutions. The removal efficiency was observed to be the highest in solution of initial pH 7 for Pb (II) and decreased both in acidic and alkaline environments. Column removal of lead was studied with respect to variations in flow rate and bed depth. The breakthrough curves have been determined at various flow rates and bed heights at 35 °C. The breakthrough and exhaustion times increased with the increase in the height of the bed, as more binding sites are available. For a given bed height, the higher the flow rate is, the lower are the breakthrough and exhaustion times. Thomas and BDST models were applied to experimental data obtained from dynamic studies performed on fixed columns to predict the breakthrough curves. The model parameters were evaluated and BDST model represented lead removal in a better way with fairly higher values of R2.