PAA nanofiber membranes in a fixed-bed column

Accepted Manuscript Adsorptive filtration of lead by electrospun PVA/PAA nanofiber membranes in a fixed-bed column Shujuan Zhang, Qiantao Shi, Christos Christodoulatos, George Korfiatis, Xiaoguang Meng PII: DOI: Reference:

S1385-8947(19)30767-3 https://doi.org/10.1016/j.cej.2019.03.294 CEJ 21419

To appear in:

Chemical Engineering Journal

Received Date: Revised Date: Accepted Date:

28 January 2019 21 March 2019 31 March 2019

Please cite this article as: S. Zhang, Q. Shi, C. Christodoulatos, G. Korfiatis, X. Meng, Adsorptive filtration of lead by electrospun PVA/PAA nanofiber membranes in a fixed-bed column, Chemical Engineering Journal (2019), doi: https://doi.org/10.1016/j.cej.2019.03.294

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Adsorptive filtration of lead by electrospun PVA/PAA nanofiber membranes in a fixed-bed column Shujuan Zhanga, Qiantao Shia, Christos Christodoulatosa, George Korfiatis,a Xiaoguang Menga,*

a

Center for Environmental Systems, Stevens Institute of Technology, Hoboken, New Jersey 07030, United States Tel: 001 201-216-8014; Fax: 001 201-216-8303 E-mail: [email protected]

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Abstract Poly(vinyl) alcohol/poly(acrylic) acid (PVA/PAA) nanofiber membranes were fabricated using electrospinning and showed good water stability and mechanical strength. Their application in lead (Pb(II)) removal from water was evaluated in a continuous fixed-bed column under varying conditions. The filtration was more efficient with a low feed concentration and low flow rate in terms of the elevated adsorption capacity and better bed utilization efficiency. The dynamic adsorption process was independent of bed height, so the fibers can be used as multilayer membranes in a fixed-bed column. The saturated column material could be regenerated and reused. The breakthrough curves were well fitted with the dose-response model, and the maximum adsorption capacity was 288 mg/g with the initial Pb(II) concentration of 1 mg/L. When tap water was used, the amount of water that can be treated before the effluent reached 15 g/L increased by three times compared to the treatment of NaCl solutions, and a very high improvement was observed at pH 7 (4.5 L) than pH 5 (2.0 L) in tap water. These differences were further confirmed by the extended X-ray absorption fine structure (EXAFS) spectroscopy, where a decreased coordination number and decreased interatomic distance between Pb and C were observed for tap water. This study provides valuable insights in the application of PVA/PAA nanofiber membranes in a dynamic system for Pb(II) removal, and sheds light on the interatomic behavior between Pb(II) and the nanofiber membranes in a flowthrough system. Keywords Electrospun nanofiber membrane; PVA; PAA; lead filtration; breakthrough curve; EXAFS

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1. Introduction Heavy metal pollution in the aqueous environment has been continuously arousing people’s attention due to its toxic and persistent nature. Even at the level of tens of microgram per liter (µg/L), heavy metals pose threats to the quality of water bodies and health of human beings. Lead (Pb(II)) is one of the most hazardous heavy metals, and the consumption of it may cause problems in nervous, skeletal, circulatory, enzymatic, endocrine, and immune systems [1]. Children are particularly vulnerable to the Pb(II) exposure, and the consequences are related to behavioral disturbances, learning and concentration difficulties, and even diminished intellectual capacity after a long-term low-level lead exposure [2]. The main sources of Pb(II) occurrence in water include mining and smelting of lead ore, industrial effluents, fertilizers, and pesticides [3]. Moreover, Pb(II) can also be leached from broken crystal glass and color cathode ray tubes (CRTs), posing a health hazard to underground water [4, 5]. In particular, the release of Pb(II) from corrosion of lead-containing pipes constitutes an important source in drinking water [6, 7], which makes it even more pressing to develop efficient and cost-effective materials and technologies to remove Pb(II) from pipe effluents. Adsorption is commonly used in heavy metal removal from aqueous environments because of its easy operation, low cost and high heavy metal removal efficiency. Plenty of adsorbents have been investigated for the adsorption of Pb(II) including activated carbon [8], chitosan [9], zeolite [10], sludge biochar [11], titanium dioxide [12], activated alumina [13], and alkali-lignin based materials [14, 15]. However, these materials suffer from disadvantages such as difficulty in regeneration and low adsorption capacity. Recently, nanomaterials have gained much attention as an effective adsorbent for heavy metal removal because of their high surface area to volume ratio, which creates more adsorption sites [16, 17]. One of the most extensively studied 3

nanomaterials is nanofibers, which are easier to handle as a bulk material than other materials such as nanoparticles or nanobeads. Moreover, electrospinning provides a facile way to fabricate fiber membranes with the size in a nanoscale to submicron range [18-21]. During the last decade, numerous efforts have been put into investigating heavy metal ion removal using various electrospun nanofiber membranes, including the nanofibers made from single or composite polymers, and some with the incorporation of inorganic metal oxides [22-24]. For heavy metal cations, poly(acrylic) acid (PAA) is preferable because it contains abundant carboxyl groups, which provide sufficient adsorption sites for cations. Moreover, poly(vinyl) alcohol (PVA) is usually added into the PAA solution to make water stable fibers by crosslinking at 145 oC. Stability and strength of the nanofibers constitute two of the most fundamental properties for their application in water treatment [25]. The electrospun PVA/PAA nanofibers fabricated in this study have a higher water-stability, better mechanical properties, and higher water permeability. In terms of the design and operation of an adsorption system, it can either be a batch-type test, called static adsorption, or a column-type continuous flow filtration, called dynamic adsorption [26]. In batch tests, the nanofiber membrane serves simply as an adsorbent, and metal ions are mainly adsorbed by the surface area of its outer layers, which decreases the effectiveness of adsorbents [27]. In dynamic adsorption, the membrane plays the function of both filtration and adsorption. Compared to batch adsorption, column adsorption is more convenient in industrial applications due to its simplicity, i.e. it does not require any additional processes such as filtration or centrifugation [28]. For the traditionally packed column, it is often accompanied by problems such as high pressure drops resulting from tightly packed small resin particles in a long bed, and low adsorption rates because the majority of the binding sites are located inside the pores of the resinous adsorbents that require intra-particle diffusion [29]. Different from the

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packed column, the adsorptive membrane is characterized by fast mass transfer because of the non-existence of intra-particle diffusion, while the adsorption capacity can still be maintained at the same time [30]. Unfortunately, the research to date has mainly focused on the static adsorption for metal ions using electrospun nanofiber membranes, and only a few researchers have studied the dynamic adsorption process by electrospun nanofibers as the adsorptive membrane. Although electrospun PVA/PAA nanofiber membranes have been synthesized and investigated for heavy metal removal by the batch test, they have never been studied as a customized well-shaped membrane with a specific thickness and diameter and their Pb(II) removal efficacy in dynamic systems under different operational conditions is hardly known. Thus, this study aims to explore the dynamic adsorption behavior of PVA/PAA nanofiber membranes for Pb(II), and understand the microscopic adsorption structure between them in a fixed-bed column. Firstly, the morphological, structural, and mechanical properties of the nanofiber membrane were characterized. Then, the filtration was performed, and the breakthrough curves were fitted using the commonly used models in a fixed-bed column to make predictions for the relative parameters such as the adsorption capacity. Moreover, the effects of feed concentration, flow rate and bed height on breakthrough curves were investigated and the regenerability of the saturated column was studied. In addition, the Pb(II)-spiked tap water was used to test the applicability of the column in a real aqueous environment followed by the spectroscopic analysis of the adsorption structure using extend X-ray absorption fine structure (EXAFS) characterization. This study provided important information on Pb(II) removal by electrospun PVA/PAA nanofibers as adsorptive membranes, and contributed significantly to the understanding of the adsorption interaction in the flow-through system at a microscopic level.

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2. Experimental The chemicals and materials, preparation of electrospun PVA/PAA nanofibers, and EXAFS analysis were detailed in the Text S1, S2, and S3 in the supplementary material, respectively. 2.1. Characterization of PVA/PAA nanofibers 2.1.1. Analysis of morphology, water-stability, porosity, and water permeability Morphology of the surface and cross section of nanofiber membranes was observed by the scanning electron microscope (SEM, Zeiss Auriga) after coating of a thin gold film. The specimens used for the cross-sectional imaging were frozen and cracked in liquid nitrogen before coating of gold. The fiber diameter was averaged by selecting 40 fibers in the SEM image using the ImageJ software. The gravimetric method was used to test the water affinity of crosslinked PVA/PAA nanofiber membranes using the following equation [31]: -

(1)

where Wd and Ws are the mass of fibers before and after immersing in DI water for 48 h, respectively. The porosity of cross-linked PVA/PAA nanofibers was calculated as follows:

-

(2)

where  is the density of fibers, which was calculated by the mass over volume for the regular shaped fiber membranes, and 0 is the density of the PVA/PAA polymer mixture. The calculation of 0 is based on Eq. 3:

6

(3)

where 1 and 2 are the density of each polymer, and 1 and 2 are their corresponding proportion in the polymer mixture. In this study, 1 and 2 were both 0.5. The change in water permeation flux (mL/(cm2 min), which was the quantity of water that passed through the membrane during a certain time period of t, was monitored over 72 h. 2.1.2. Analysis of mechanical property The specimen of the nanofiber membranes was cut into a dumbbell-like shape with rounded junctions at the grip/gage transition, which was a preferred shape to test the mechanical properties of samples [32]. It had a size of 26 mm in gauge length (GL) and 9 mm in width (GW). The specimen was clamped onto a tensile test stand (ESM 303, Mark-10, USA) and stretched at room temperature with a cross-head speed of 25.4 mm/min. The stress was calculated as the load divided by the cross-sectional area while the strain was defined as the applied displacement divided by the gage length [26]. 2.2. Dynamic filtration experiments 2.2.1. Column setup and parameter description The continuous adsorption of Pb(II) by PVA/PAA nanofiber membranes was conducted in a cylindrical dead-end cell with an inner diameter of 1.27 cm. The fiber membranes were cut into discs by a circle punch before they were placed in the cell holder. A layer of PET substrate membrane (14.5 mg) was constructed on each end of the cell to support the membrane, and an O-ring was placed in one end of the cell to prevent leakage. The well-organized cell was then

7

sealed for the solutions to flow through. The flow rate of the feed solutions was controlled by a peristaltic pump and the solutions were pumped in a down-flow mode. The amount of Pb(II) adsorbed on the membrane (q, mg/g) was calculated based on Eq. 4: t

q

-

(4)

where C0 (mg/L) is the initial concentration, Ct (mg/L) is the effluent concentration at time t (min), Q (mL/min) is the flow rate, and X (mg) is the mass of membranes. Ct/C0 = 0.1 was defined as the breakthrough point and Ct/C0 = 0.8 as the saturation point, while qb (mg/g) and qs (mg/g) refer to the adsorption capacity at breakthrough and saturation points, respectively. Bed utilization efficiency (, %) is defined as the ratio of qb to qs, and a higher value indicates a better dynamic adsorption performance. 2.2.2. Effect of feed concentration, flow rate, and bed height, and column regeneration To explore the dynamic Pb(II) adsorption on PVA/PAA nanofiber membranes under various conditions, experiments were performed at different feed concentrations (1, 8, and 40 mg/L), different flow rates (0.22, 0.35, and 0.78 mL/min), and different bed heights (0.00227, 0.00454, and 0.00681 cm). One layer of membrane was used in each experiment except the study of effect of bed height where multiple layers were utilized. In the regeneration test, the Pb(II)-saturated column was regenerated using a 0.01 M HCl solution at a flow rate of 0.35 mL/min followed by rinsing with DI water to remove the residual HCl. The adsorption-desorption process was repeated 4 times. The Pb(II) feed solutions were prepared in 0.01 M NaCl solutions, and the pH of all the feed solutions was adjusted to 5.0  0.2 to prevent the formation of lead precipitates. The effluent was collected periodically and analyzed for the residual Pb(II). 2.2.3. Tap water filtration

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To simulate the real environment, the filtration of tap water spiked with 100 g/L Pb(II) was evaluated. In addition, the filtration using 0.01 M NaCl solution with 100 g/L Pb(II) was also performed under two different pH conditions of 5 and 7. For these studies, two layers of fiber membranes with the density of 1 mg/layer were used with a flow rate of 0.35 mL/min. 2.2.4. Instrumental analysis of Pb(II) The analysis of Pb(II) was conducted using inductively coupled plasma optical emission spectrometry (5100 ICP-OES, Agilent Technologies) and atomic adsorption spectrometry coupled with a GTA 120 graphite tube atomizer (200 Series AA, Agilent Technologies) after samples were acidified to pH < 1 using 65% nitric acid. For both of the instrumental analyses, the accuracy of the results was controlled by analyzing Pb(II) standard solutions with known concentrations, and the difference between the analytical and known values was less than 3% for AA and less than 2% for ICP-OES. The precision of the results was controlled by analyzing each sample two times, and the relative percent difference (RPD) between the two results was less than 5% for AA and less than 1% for ICP-OES. 3. Results and discussion 3.1. Characterization of PVA/PAA nanofiber membranes The morphology of PVA/PAA nanofiber membranes is shown in Fig. 1(A) and (B) with high and low magnifications, respectively. The inset in Fig. 1(B) indicates the frequency distribution of fiber diameters based on 40 selections. The diameter of most fibers was in the range of 450 nm to 550 nm, which was much higher than that of fibers made from a blend with a higher PVA/PAA ratio of 3.75:1. The difference in the fiber size was attributed to the change in the PAA proportion. A similar result was also observed in a study on the electrospun Nafion/PAA

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fibers where more uniform fibers with an increased size were made with the increase of PAA content [33]. Two kinds of fiber membranes with different layer thicknesses, as shown in Fig. 1(C) and (D), were selected to evaluate the porosity. The density of original PVA/PAA polymers was calculated to be 1.34 g/m3 given the PVA polymer density of 1.25 g/m3 and PAA of 1.44 g/m3, derived from polymerdatabase.com. Based on Eq. 2, the porosity of PVA/PAA nanofibers with a thickness of 22.7 and 27.2 m was 71% and 65%, respectively, which were in agreement with those reported in the literature [34, 35]. The porosity was found to decrease with the increased fiber density. The averaged swelling degree using four pieces of fibers was 1.8  0.2, which was much lower than 9.69 reported in the literature, indicating improved water-stability after crosslinking for 2 h compared to 0.5 h [34]. In addition, the water flux did not change over 72-h continuous flow, which again demonstrated the stability of membranes and their compatibility with water.

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Fig. 1. SEM images of PVA/PAA nanofiber membranes: (A) and (B) top view, and diameter distribution in the inset of (B); (C) and (D) cross-sectional view of the fiber membrane with a fiber density of 8.7 g/m2 and 12.6 g/m2 (corresponding to 3.83105 g/m3 and 4.63105 g/m3), respectively.

Mechanical strength is another important factor in evaluating the stability of a material. The result of the tensile strength test of the crosslinked nanofiber membranes is shown in Fig. 2. The water-stable PVA/PAA nanofiber membranes had a higher Young’s modulus (around 280 MPa) compared to that of other PVA-containing nanofibers such as crosslinked PVA/CS and PVA/CS/MWCNTs [36] and crosslinked PEI/PVA nanofibers [37], demonstrating a strong linkage between PVA and PAA in fiber membranes after crosslinking. The good mechanical properties position these membranes as competitive candidates for practical applications.

Fig. 2. Stress-strain curve of cross-linked PVA/PAA nanofiber membranes with a density of 11.87 g/m2. 3.2. Modelling of breakthrough curves Modelling of the experimental filtration data is used to provide mathematical and quantitative approaches for successfully designing a column adsorption process. Four models, namely the Thomas model, the Bohart-Adams model, the Yoon-Nelson model, and the dose-response model, 11

have been frequently used in describing the breakthrough curves for the adsorption of both organic compounds and inorganic ions in a fixed-bed column [38-40]. In this study, these four models were used and evaluated to predict the breakthrough curves of Pb(II) adsorption onto the membranes. The Thomas model is one of the most frequently used models to describe breakthrough curves, assuming the Langmuir isotherm and second-order reversible reaction kinetics [41, 42]. Specifically, it is suitable to estimate the adsorption process where external and internal diffusion is not the rate-limiting step. The Bohart-Adams model assumes that the adsorption rate is proportional to both the residual capacity of the adsorbent and the concentration of the adsorbate [43, 44]. It is only accurate to predict the initial portion of the breakthrough curves (Ct/C0 < 0.15) because of its divergent nature [45, 46]. The Yoon-Nelson model is a relatively simple model and it assumes the rate of decrease in the probability of adsorption for each adsorbate molecule is proportional to the probability of adsorbate sorption and the probability of adsorbate breakthrough on the adsorbent [47, 48]. The dose-response model is originally developed to predict the kinetics of heavy metal removal in a biosorption process [49], and has now been used in explaining the dynamic adsorption for heavy metal ions by various materials. The non-linear fittings of the experimental data were performed in EViews 10. The fitting curves are shown in Fig. 3, and the model equations and parameters are listed in Table 1. It needs to be mentioned that the fittings of Thomas and Yoon-Nelson models overlapped with each other because of the same mathematical structure of these two models despite of the different model parameters. The high coefficient of determination (R2), low standard errors of constants, and low sum of squared errors (SSE) indicate a good fit of the experimental data to all the four models. In particular, the R2 (R2 > 0.997) of the dose-response model was higher than the other three models

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and the standard errors of q0 of the dose-response model were much lower than those of the Thomas model, so the dose-response model was used to simulate the breakthrough curves in the following study. Similar to this result, the dose-response model was found to be better in predicting the dynamic adsorption of Cr(VI) by chitosan nanofiber membranes [27, 50]. For the three columns with different membrane masses, the maximum adsorption capacity predicted by the dose-response model decreased from 266 mg/g to 132 mg/g when the membrane mass increased from 1 mg to 4 mg. The increase in fiber masses was related to elevated thickness and higher density, which sacrificed some pores in fiber membranes. The decrease in porosity not only decreased the contact time of solutions with the membrane but also led to the loss of active sites for Pb(II) adsorption, which might explain the significantly decreased adsorption capacity for the thicker membrane. The difference in Pb(II) removal performance for these membranes demonstrates that the membrane density is a crucial factor to consider in synthesizing this kind of adsorbents.

Fig. 3. Non-linear fittings of breakthrough curves using the Thomas, Yoon-Nelson and doseresponse models (A) and using the Bohart-Adams model (B) for columns with one-layer membrane by different masses. Experimental conditions: 1 mg/L influent Pb(II), pH 5.0 ± 0.2, and flow rate 0.35 mL/min. Table 1 Breakthrough models and model parameters based on non-linear regressions for Pb(II) adsorption on PVA/PAA nanofiber membranes. Model

Model formula

Linearized expression

Parameter

Membrane mass (mg)

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Thomasa

Theoretical q0 (mg/g)

KT (mL/(min mg))

b

Bohart-Adams

1

2

4

299.51

240.50

133.87

(4.91)

(3.92)

(1.24)

4.27 (0.14) 2.43 (0.11) 2.58 (0.09)

R2

0.9927

0.9644

0.9829

SSE

0.044

0.088

0.033

N0 (mg/L)

92480

95621

94239

(933)

(1331)

(639)

6.1310-3

4.9110-3

4.4210-3

KBA (L/(mg min))

(1.1210-4) (1.3010-4) (5.6110-5)

Yoon-Nelsonc

R2

0.9910

0.9810

0.9958

SSE

3.4510-4

8.7210-4

7.9310-5

kYN (min-1)

3.85×10-3

2.18×10-3

2.32×10-3

(1.24×10-4) (9.64×10-5) (8.03×10-5)

Dose-responsed

τ min

951 (16)

R2

0.9927

0.9644

0.9829

SSE

0.044

0.088

0.033

q0 (mg/g)

266.28

225.05

132.02

(2.41)

(1.48)

(0.54)

3.28

2.00

2.68

(0.067)

(0.031)

(0.044)

R2

0.9977

0.9977

0.9983

SSE

0.0134

0.006

0.003

a

1527 (25) 1700 (16)

Note: akT (mL/(min mg)), Thomas rate constant, and q0 (mg/g), predicted adsorption capacity; b KBA (L/(mg min)), Bohart-Adams kinetics constant, N0 (mg/L), maximum volumetric adsorption capacity,  (cm/min), linear velocity of the fluid, and Z (cm), bed height; ckYN (min-1), Yoon and Nelson’s rate constant, and (min), time required for 50% breakthrough; da, doseresponse constant, and q0 (mg/g), maximum adsorption capacity; values in parentheses are standard errors of constants. 3.3. Effect of feed concentration Generally, the change in feed concentration influences the shape of breakthrough curves. In this study, Pb(II) feed concentrations of 1, 8, and 40 mg/L were studied with a constant flow rate of 0.35 mL/min and a constant bed height of 0.00227 cm (Fig. 4A). The breakthrough curves for

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feed concentrations of 8 and 40 mg/L were much steeper than that for 1 mg/L, so the breakthrough in columns with high feed concentrations was reached much earlier (4 min for 40 mg/L and 18 min for 8 mg/L) compared to the low feed concentration (450 min for 1 mg/L). When the breakthrough curves were re-plotted using the absolute amount of Pb(II) fed to the bed (Fig. 4B), the differences between the three curves became much less evident, but Ct/C0 was still lower for 1 mg/L Pb(II) than that for 8 and 40 mg/L Pb(II) with the same absolute amount of Pb(II) loaded onto the bed before reaching the saturation point. In terms of the adsorption capacity, the Pb(II) adsorption capacity for feed concentrations of 1, 8, and 40 mg/L was 136, 47, and 51 mg/g at the breakthrough point, and 288, 176, and 167 mg/g at the saturation point, respectively (Fig. 5). The bed utilization efficiency was 47% for the 1 mg/L Pb(II) feed concentration, which was much higher than that for 8 and 40 mg/L, namely 27% and 31%, respectively. Moreover, these results showed that the adsorption capacity and bed utilization efficiency were similar for the two high Pb(II) concentrations, which indicates that the adsorption capacity of Pb(II) onto the PVA/PAA nanofiber bed was independent on the initial concentration over a certain level. The predicted parameters using the dose-response model were listed in Table 2, and a much higher maximum adsorption capacity was observed for the 1 mg/L Pb(II) while the value was similar for the 8 and 40 mg/L Pb(II). In general, the PVA/PAA nanofiber membranes showed a better filtration performance towards the diluted solutions with a comparatively lower feed concentration.

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Fig. 4. Effect of feed concentration on breakthrough curves: Ct/C0 vs time and the lines represent the dose-response fittings (A); Ct/C0 vs the total amount of Pb(II) fed to the membrane bed (B). Experimental conditions: pH 5.0 ± 0.2, 1 layer of 1 mg/layer membrane, and flow rate 0.35 mL/min.

Fig. 5. Adsorption capacity and bed utilization of PVA/PAA nanofiber membranes for different feed concentrations. Table 2 Parameter values for dose-response fittings under different conditions. Feed concentration (mg/L)a

Flow rate (mL/min)b

Bed height (cm)c

Number of cyclesd

1

8

40

0.22

0.35

0.78

0.00227

0.00454

0.00681

1

2

3

4

q0

266

175

189

254

189

209

189

162

167

189

183

176

177

(mg/g)

(2.34)

(3.16)

(7.28)

(8.02)

(6.94)

(6.56)

(7.28)

(5.85)

(2.45)

(7.28)

(4.80)

(4.35)

(3.43)

3.28

2.52

1.69

1.86

1.69

1.68

1.69

1.76

1.86

1.69

1.79

1.84

1.82

a (0.07)

(0.12)

(0.08)

(0.09)

(0.08)

(0.07)

(0.08)

(0.10)

(0.04)

(0.08)

(0.07)

(0.07)

(0.05)

2

R

0.9981

0.9921

0.9873

0.9863

0.9873

0.9914

0.9873

0.9880

0.9976

0.9873

0.9958

0.9972

0.9971

SSE

0.0141

0.0122

0.0052

0.0068

0.0052

0.0017

0.0052

0.0085

0.0027

0.0052

0.0024

0.0016

0.0018

Note: Values in parentheses are standard errors of constants.

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a

flow rate = 0.35 mL/min, bed height = 0.00227 cm; bfeed concentration = 40 mg/L, bed height = 0.00227 cm; cflow rate = 0.35 mL/min, feed concentration = 40 mg/L; dflow rate = 0.35 mL/min, feed concentration = 40 mg/L, bed height = 0.00227 cm. 3.4. Effect of flow rate The effect of flow rate on the breakthrough curves of Pb(II) adsorption by PVA/PAA nanofiber membranes is shown in Fig. 6. The slopes of the curves became steeper when the flow rate increased from 0.22 to 0.78 mL/min, as shown in Fig. 6(A). This result indicated that the time required for reaching the breakthrough point and the saturation point decreased at a higher flow rate. This phenomenon can be explained by the reduced residence time of Pb(II) solutions in the column with increased flow rate, which is not sufficient to reach equilibrium conditions, leading to an earlier breakthrough time [51]. When Ct/C0 was re-plotted against the number of bed volumes (Fig. 6B), no obvious difference was observed for the breakthrough curves with flow rates of 0.35 and 0.78 mL/min before saturation, indicating the loading of Pb(II) was independent on flow rate over this range. A similar result was also found in a study on the dynamic adsorption of Cr(VI) using electrospun chitosan nanofibers [50]. The independence of breakthrough curves on flow rate offers flexibility in the design of filtration for high throughput process development. Fig. 7 shows the adsorption capacity at breakthrough and saturation points and bed utilization with different flow rates. When the flow rate increased from 0.22 to 0.78 mL/min, the Pb(II) adsorption capacity of PVA/PAA nanofiber membranes decreased from 76 to 55 mg/g at the breakthrough point, and from 223 to 149 mg/g at the saturation point. In terms of bed utilization, the values were similar, and it was slightly higher for the column with the flow rate of 0.78 mL/min because of the dramatically decreased adsorption capacity at the saturation point. In real practice, a sharp breakthrough curve with a high bed utilization efficiency is always desired to

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increase the amount of treated water before the effluent Pb(II) reaches the discharge limit. On the other hand, the adsorption capacity of a bed should be reached as much as possible in order to make full use of the membrane bed [52]. In this study, despite of the high bed utilization efficiency of the column at a higher flow rate, a lower flow rate and longer contact time were optimal for Pb(II) removal because of the higher breakthrough adsorption capacity and better bed utilization.

Fig. 6. Effect of flow rate on breakthrough curves: Ct/C0 vs time and the lines represent the doseresponse fittings (A); Ct/C0 vs the number of bed volumes (B). Experimental conditions: pH 5.0 ± 0.2, 1 layer of 1 mg/layer membrane, and feed concentration 40 mg/L.

Fig. 7. Adsorption capacity and bad utilization of PVA/PAA nanofiber beds with different flow rates.

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3.5. Effect of bed height The effect of bed height on breakthrough curves at a constant flow rate of 0.35 mL/min and a constant feed concentration of 40 mg/L is illustrated in Fig. 8. Specifically, 1, 2 and 3 layers of PVA/PAA nanofiber membranes with the same density were positioned in the dead-end cell, equivalent to a bed height of 0.00227, 0.00454, and 0.00681 cm, respectively. An increase in the bed height shifted the breakthrough curve to the right, and prolonged the breakthrough and saturation time (Fig. 8A). This result could be explained by the more available active sites for adsorption at the higher bed height because of increase in the fiber mass [53]. The treated water volume at breakthrough time increased from 1.2 mL to 3.6 mL when the bed height increased from 0.00227 cm to 0.00681 cm. When the breakthrough curves were re-plotted using the number of bed volumes as the abscissa, the three curves nearly overlapped (Fig. 8B), indicating the increase in bed height or membrane layer did not affect the dynamic adsorption of Pb(II). This conclusion was further confirmed by the similar adsorption capacity at the breakthrough and saturation points and similar bed utilization efficiency as shown in Fig. 9(A). A similar result was also found in a recent study where the change in the number of stacked nanofiber layers did not impact the adsorption capacity [50]. These results demonstrated that the increase in the column height increased the throughput volume of treated water without compromising the adsorption capacity, which creates feasibility for massive usage of the ultra-thin nanofiber membranes in a dynamic column system. The bed depth service time (BDST) model is derived from the simplified Bohart-Adams model, and it is commonly used to determine the service time for a given bed height [54]. The formula of the BDST model is as follows:

19

-

-

(5)

where Cb (mg/L) is the effluent concentration of Pb(II) at the breakthrough point and t (min) is the service time of the column under given conditions. The other parameters are the same as those in the Bohart-Adams model. The minimum theoretical bed height required to keep the effluent concentration at t = 0 below the breakthrough concentration can be calculated by setting t = 0, also known as the critical bed depth (Z0). Its formula is written as: -

(6)

As shown in Fig. 9(B), the experimental data were well fitted using the BDST model, and N0 and KBA were calculated to be 16562 mg/L and 0.235 L/(mg min), respectively. The values of N0 and KBA were higher than those in dynamic adsorption of Pb(II) using other adsorbents such as nanoTiO2 decorated cellulose fibers [29] and nano--Al2O3/chitosan beads [55]. The high value of N0 indicates a fast mass transfer process and high adsorption efficiency for Pb(II), while the high KBA confirmed that bed height had a minor effect on the adsorption capacity [56, 57]. The critical bed depth Z0 was 0.000156 cm based on 10% breakthrough, less than 1/10 of the 1-layer bed height, which again demonstrates the high Pb(II) removal efficiency of PVA/PAA nanofiber membranes.

20

Fig. 8. Effect of bed height on breakthrough curves: Ct/C0 vs time and the lines represent the dose-response fittings (A); Ct/C0 vs the number of bed volumes (B). Experimental conditions: pH 5.0 ± 0.2, feed concentration 40 mg/L, layer density 1 mg/layer, and flow rate 0.35 mL/min.

Fig. 9. Adsorption capacity and bed utilization of PVA/PAA nanofiber membranes with different bed heights (A) and BDST fitting (B). 3.6. Desorption and column regeneration In order to determine the regenerability of PVA/PAA nanofiber membranes, the column was subjected to repeated adsorption/desorption cycles. The desorption curve was obtained by plotting the concentration of Pb(II) in effluent HCl solutions against the sampling time. As shown in the inset of Fig. 10(A) (only one desorption curve was recorded), the desorption rate was fast at first and then slowed down with a decrease in the effluent Pb(II) from  65 mg/L to  2 mg/L in 15 min, and then to 1 mg/L in another 15 min. To do the desorption, only a small amount (5 mL) of 0.01 M HCl solution was required to desorb 96% of Pb(II) from the saturated column, which accounted for only 14% of the treated water (35 mL). Pb in the concentrated acidic solution could then be precipitated and disposed. In terms of regeneration, the breakthrough curves for the four cycles of adsorption-desorption overlapped with each other (Fig. 10A), indicating the exhausted column was readily regenerated without losing active sites for adsorption of Pb(II). The breakthrough and saturation capacity as well as the bed utilization efficiency after regeneration showed no significant difference from that of the original membrane

21

bed (Fig. 10B), which further confirmed that PVA/PAA nanofiber membranes served as a promising material for Pb(II) removal which can be reused for several times without compromising the adsorption capacity.

Fig. 10. Breakthrough curves of regenerated PVA/PAA nanofiber membranes and the lines represent the dose-response fittings (A) and adsorption capacity and bed utilization of the regenerated membranes (B). Experimental conditions: pH 5.0 ± 0.2, feed concentration 40 mg/L, 1 layer of 1 mg/layer membrane, and flow rate 0.35 mL/min. The inset in Fig. 10 (A) shows the desorption curve of saturated membranes. 3.7. Tap water filtration The breakthrough curves for 100 g/L Pb-spiked tap water as well as the NaCl solution are shown in Fig. 11(A). In addition, the breakthrough curves using PET substrates and using the standalone fiber membranes without the support of PET substrates are also included. It was obvious that the removal of Pb(II) by PET substrates was negligible compared to nanofibers under the same operational conditions. Moreover, the column removed much more lead and sustained longer time when tap water was used than NaCl solution at the same pH condition of 5, which might be due to the synergetic interaction of Pb(II) with oxyanions present in tap water [58, 59]. Interestingly, much more water was able to be treated when the pH of tap water increased to 7.0, which is the normal condition of tap water under most circumstances. It is

22

worth pointing out that in the case of the standalone fiber membranes, the breakthrough curve was similar to that of the membrane supported by the substrates only with a slight increase in the effluent concentration. The filtration was stopped before the effluent concentration reached 15 g/L for tap water with pH 7 because of the drop in the permeability of the memebranes. To make easy comparisons, the ability of PVA/PAA nanofiber membranes with and without the support of substrates in removing lead from different aqueous environments was expressed as the volume of filtered water before the effluent concentration reached 15 g/L, which is the maximum contamination level in drinking water regulated by the US Environmental Protection Agency (USEPA). As shown in Fig. 11(B), for membranes without substrates and for tap water at pH 7, the treated water was 3.0 L; membranes with substrates for tap water at pH 7, 4.5 L; membranes with substrates for tap water at pH 5, 2.0 L; and membranes with substrates for the NaCl solution at pH 5, 0.5 L. It followed a trend that the fiber membranes performed better in filtering tap water than pure NaCl solutions, which indicated that the complex matrix of tap water facilitated the removal of Pb(II) rather than inhibiting it. In addition, the removal of lead was promoted by an increase in pH from 5 to 7. Since particulate lead is the major form in tap water at neutral pH [60-62], it demonstrates that the nanofiber membrane played the role of both adsorption and filtration. Although the PET substrates was unable to remove Pb(II) themselves, their support for nanofibers in the cell improved the quality of the effluent water and elongated the life time of the column, which provided a cost-effective and agile way to use the nanofiber membranes in practical applications. This study showed that 1 mg of fiber membranes were able to filter more than 1 L of low lead contaminated tap water, equivalent to more than 347,900 bed volumes, demonstrating their high lead removal capacity.

23

Fig. 11. Breakthrough curves (A) and plots of the effluent concentration against the treated water volume (B) for low Pb(II)-spiked water. Experimental conditions: feed concentration 100 g/L, 2 layers of 1 mg/layer membranes, and flow rate 0.35 mL/min. 3.8. EXAFS analysis To gain a fundamental understanding of Pb(II) removal by filtration using PVA/PAA nanofiber membranes, an EXAFS study was conducted to explore the atomic adsorption structure of Pb(II) on the membranes after the filtration of tap water and 0.01 M NaCl water. Fig. 12(A), (B), and (C) show the Pb-LIII edge k2-weighted EXAFS data, the corresponding magnitude and real part Fourier transformed spectra of nanofibers with adsorbed Pb(II), respectively. Fitting results in Table 3 indicate that the first shell surrounding Pb(II) resulted from 4.6 and 4.5 O atoms with bond lengths of 2.36 and 2.31 Å for NaCl solutions and tap water, respectively. The high coordination number (CN, 4.5-4.6) of O suggested that Pb(II) was complexed with several oxygen-containing functional groups (i.e. carboxyl group) on the PVA/PAA nanofibers. The second shell of 2.3 C atoms at 4.16 Å was detected for Pb(II) from the NaCl solution. However, the CN of C decreased to 0.9 and the interatomic distance between Pb(II) and C decreased to 3.40 Å for tap water. This change might be due to the formation of ternary surface complexation between Pb(II) and other oxyanions in tap water [63-66], which 24

was also observed in the previous X-ray absorption spectroscopy (XAS) study of Pb(II) adsorption on activated carbon [58]. Another shell with 0.4 Pb atom at 3.65 Å was also measured for tap water, which suggested that the particulate lead was formed and effectively intercepted by the nanofibers. These features of nanofibers proved that the PVA/PAA nanofiber membranes showed an outstanding advantage over the commonly used pitcher style Point-of-Use filters, which failed to remove the participate lead in tap water [67].

Fig. 12. Normalized k2-weighted experimental (black symbols) and simulated (blue lines) LIIIedge EXAFS spectra (A), the corresponding Fourier transformed magnitude (B) and real parts of Fourier transform (C) of Pb(II) on electronspun nanofibers after dynamic filtration. Experimental conditions: for Pb(II)-spiked NaCl solutions, 1 mg/L Pb(II) in 0.01 M NaCl solutions at pH 5.0 ± 0.2, 2 layers of 1 mg/layer membranes, and flow rate 0.35 mL/min; for Pb(II)-spiked tap water, 100 g/L in tap water at pH 7.0 ± 0.2, 2 layers of 1 mg/layer membranes, and flow rate 0.35 mL/min. Table 3 Structure parameters derived from Pb LIII-edge EXAFS analysis. Samples

NaCl solution

Tap water

Path

CNa

R (Å)b

σ2 (Å2)c

Pb-O

4.6(11)

2.36(2)

0.004(1)

Pb-C

2.3(4)

4.16(13)

0.012(4)

Pb-O

4.5(12)

2.31(3)

0.005(2)

Pb-C

0.9(2)

3.40(7)

0.010(3)

∆E0 (eV)d

R-factore

-9.3(21)

0.017

-6.0(5)

0.019

25

Pb-Pb

0.4(2)

3.65(16)

0.017(3)

Note: acoordination number; binteratomic distance; cDebye-Waller factor; dthreshold energy shift; e goodness-of-fit parameter: R-factor Σ χdata – χfit)2/Σ χdata)2. The estimated parameter uncertainties are listed in parentheses, representing the errors in the last digit. 4. Conclusion The water stable and mechanically strong PVA/PAA nanofiber membranes were synthesized and used in a fixed-bed column to investigate their dynamic Pb(II) removal performance. The dynamic removal of Pb(II) by the membranes was dependent on the feed concentration, and a relatively lower concentration was desirable for higher adsorption capacity and better bed utilization efficiency. The water flow rate had a minor influence on the filtration within the studied range from 0.22 to 0.78 mL/min. The performance of the column was not affected by bed height, which provided a feasible way to use the fibers as multiply stacked layers in designing a pilot-scale adsorption project. The fixed-bed column can undergo several times of adsorptiondesorption cycles without affecting the adsorption capacity, demonstrating its high economical potential in acting as the recyclable adsorbent for heavy metal removal. The breakthrough curves for the dynamic adsorption were best explained by the dose-response model. The complexity in compositions of tap water facilitated Pb(II) removal due to the synergetic behavior of Pb(II) with oxyanions in tap water. Other than adsorption, the membranes could also play the function of filtration to remove precipitate lead which is the main form in tap water at neutral pH, and this result was also confirmed by the EXAFS analysis which shows a Pb-Pb shell in the structure of membranes after filtration of tap water at pH 7. This feature of PVA/PAA nanofiber membranes make them very competitive compared to the commercially available filters because the latter usually failed to do so. Acknowledgement

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This research used resources of the Advanced Photon Source, a U.S. Department of Energy (DOE) Office of Science User Facility operated for the DOE Office of Science by Argonne National Laboratory under Contract No. DE-AC02-06CH11357. The authors are grateful for the help and support of EXAFS spectra collection from Dr. George Sterbinsky at Advanced Photo Sources. In addition, the support from the I&E Doctoral Fellowship Program at Stevens Institute of Technology is gratefully acknowledged. The authors also thank Prof. Hongjun Wang and his Ph.D. student Lichen Wang from Stevens Institute of Technology for the generous help in the process of making electrospun nanofibers. References [1] X. Zhang, L. Yang, Y. Li, H. Li, W. Wang, B. Ye, Impacts of lead/zinc mining and smelting on the environment and human health in China, Environ. Monit. Assess. 184 (2012) 2261-2273. [2] L. Järup, Hazards of heavy metal contamination, Br. Med. Bull. 68 (2003) 167-182. [3] S. Malar, S.S. Vikram, P.J. Favas, V. Perumal, Lead heavy metal toxicity induced changes on growth and antioxidative enzymes level in water hyacinths [Eichhornia crassipes (Mart.)], Botanical studies 55 (2016) 54. [4] J.T. van Elteren, M. Grilc, M.P. Beeston, M.S. Reig, I. Grgić, An integrated experimentalmodeling approach to study the acid leaching behavior of lead from sub-micrometer lead silicate glass particles, J. Hazard. Mater. 262 (2013) 240-249. [5] C.S. Poon, Management of CRT glass from discarded computer monitors and TV sets, Waste Manage. (Oxford) 28 (2008) 1499. [6] J. Liu, H. Chen, L. Yao, Z. Wei, L. Lou, Y. Shan, S.-D. Endalkachew, N. Mallikarjuna, B. Hu, X. Zhou, The spatial distribution of pollutants in pipe-scale of large-diameter pipelines in a drinking water distribution system, J. Hazard. Mater. 317 (2016) 27-35. [7] S. Chowdhury, M.J. Mazumder, O. Al-Attas, T. Husain, Heavy metals in drinking water: occurrences, implications, and future needs in developing countries, Sci. Total Environ. 569 (2016) 476-488. [8] M.A.P. Cechinel, A.A.U. de Souza, Study of lead (II) adsorption onto activated carbon originating from cow bone, Journal of Cleaner Production 65 (2014) 342-349. [9] W.W. Ngah, L. Teong, M. Hanafiah, Adsorption of dyes and heavy metal ions by chitosan composites: A review, Carbohydr. Polym. 83 (2011) 1446-1456. [10] X. Lu, F. Wang, X.-y. Li, K. Shih, E.Y. Zeng, Adsorption and thermal stabilization of Pb2+ and Cu2+ by zeolite, Ind. Eng. Chem. Res. 55 (2016) 8767-8773. [11] T. Chen, Y. Zhang, H. Wang, W. Lu, Z. Zhou, Y. Zhang, L. Ren, Influence of pyrolysis temperature on characteristics and heavy metal adsorptive performance of biochar derived from municipal sewage sludge, Bioresour. Technol. 164 (2014) 47-54.

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31

32

Highlights 

Electrospun PVA/PAA membranes were studied for dynamic adsorption of Pb(II).



Breakthrough curves were dependent on the feed concentration and flow rate.



The dose-response model could precisely predict the breakthrough curves.



The column effectively removed lead from tap water by adsorption and filtration.



Molecular-level structure and removal mechanism were revealed by EXAFS analysis.

33