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

The first set of experiment was performed to identify the optimal pH under batch conditions with fixed values of initial lead concentration, resin dose and temperature. After identifying the optimal pH, the subsequent experiments were conducted to optimize the suitable condition with respect to the column removal of lead. The effect of height of the resin bed and flow rate of the metal solution was evaluated at different operational conditions. Column experiments were carried out in a reactor made of acrylic and fitted with inlet and exit ports. The column reactor was fabricated with a 2.4 cm internal diameter and 50 cm length. The resin particles, Dowex 50 WX8, were packed within the column reactor. The initial lead solution with a known concentration was injected through the column in upflow mode, in order to assure complete wetting of the particles. The performance factors, namely, Percentage Lead Removal efficiency (PLRE) and the lead uptake were calculated using the Equations (1) and (2), where and are, respectively, the initial and final concentrations of lead (mg/L), m is the mass of the resin and V is the volume of the sample solution.
formula
(1)
formula
(2)

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).

Figure 1

Effect of initial pH of the solution for the removal of Lead by Dowex 50 WX8.

Figure 1

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.

Figure 2

Breakthrough curves for lead removal at different flow rates.

Figure 2

Breakthrough curves for lead removal at different flow rates.

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).

Figure 3

Breakthrough curves at different bed depth.

Figure 3

Breakthrough curves at different bed depth.

Column modeling

Two models, namely Bed Depth Service Time (BDST) model and Thomas model were used in column system modeling. The BDST relation developed by Hutchins (Alyuz & Veli 2009) and currently used is given by:
formula
(3)
where t is the breakthrough time (h), N0 is the exchange capacity (mg/ L), Ci is the initial concentration (mg/L), U0 is the superficial fluid velocity (mm/ h), Z is the height of the fixed bed (mm), and Z0 is the length of the dynamic bed mass-transfer zone (mm), which is equivalent to the ion exchange front where sorbent material is partly saturated. This latter parameter corresponds to the critical bed depth, defined as the theoretical minimum depth of the resin sufficient to prevent an untimely release of pollutant in the effluent solution.
The linearized form of the Thomas model is given as follows:
formula
(4)
where KT is the Thomas rate constant (ml/h·mg), q0 is exchange capacity of the bed (mg/g) and Q is the volumetric flow rate (L/h). KT and q0 were determined from a plot of ln ((C0/C)-1) against time and obtained from slope and intercept at a given flow rate. In this study a series column tests were performed to determine the breakthrough curves with varying bed depths and flow rates. The BDST model is based on physically measuring the capacity of the bed at different breakthrough values. This simplified design model ignores the intra particle mass transfer resistance and external film resistance such that the adsorbate is adsorbed onto the adsorbent surface directly (Runping et al. 2008). The BDST model describes a relation between the service time of the column and the packed-bed column. The results obtained were presented in Figure 4 by a plot of service time versus bed depth at different flow rates. The column service time was selected as the time when the normalized concentration, Ceq/Ci reached 0.05. The service time increased when the bed depth increased from 6 to 18 cm at the same flow rate The breakthrough time increased with increasing bed depth which could be due to the increase in exchange sites and need more time to reach saturation. The values of BDST model parameters were presented in Table 1. The dynamic bed capacity of the column (N0) decreases with decrease in the flow rate. The value of Ka characterizes the rate of transfer from the fluid phase to the solid phase and it was found to be directly proportional to flow rate. Figure 5 present Thomas model plot for lead removal at different flow rates. The model parameters were estimated and given in Table 1. The rate constant (KT) increased with increasing flow rate and confirmed the reduction in transport resistance. It was observed that the values of exchange capacity of the bed (q0) decreased with increase in flow rates. Decrease in residence time was found to be responsible for this observation.
Table 1

Model parameters

Flow rate (mL/min)Thomas model
BDST model
R2KT × 103 (ml/ h·mg)qo (mg/g)R2No (mg/ L)Ka × 103 (L/mg h)
0.974 12.50 9.914 0.998 5,728.62 7.50 
0.967 9.65 13.665 0.979 3,983.58 2.07 
0.954 8.11 14.860 0.963 2,831.70 1.50 
Flow rate (mL/min)Thomas model
BDST model
R2KT × 103 (ml/ h·mg)qo (mg/g)R2No (mg/ L)Ka × 103 (L/mg h)
0.974 12.50 9.914 0.998 5,728.62 7.50 
0.967 9.65 13.665 0.979 3,983.58 2.07 
0.954 8.11 14.860 0.963 2,831.70 1.50 
Figure 4

BDST model plot for Lead removal.

Figure 4

BDST model plot for Lead removal.

Figure 5

Thomas model plot for Lead removal.

Figure 5

Thomas model plot for Lead removal.

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.

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