(Perchloroethylene) from the Aqueous Phase by Adsorption on

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Removal of a chlorinated volatile organic compound (perchloroethylene) from aqueous phase by adsorption on activated carbon Marianne Miguet, Vincent Goetz, Gael Plantard, and Yves Jaeger Ind. Eng. Chem. Res., Just Accepted Manuscript • Publication Date (Web): 23 Sep 2015 Downloaded from http://pubs.acs.org on September 26, 2015

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Industrial & Engineering Chemistry Research

Removal of a chlorinated volatile organic compound (perchloroethylene) from aqueous phase by adsorption on activated carbon

Marianne MIGUET1,2,*, Vincent GOETZ1, Gaël PLANTARD1,3, Yves JAEGER2 1

CNRS Promes, Rambla de la Thermodynamique Tecnosud, 66100 Perpignan, France

2

Veolia eau, 765 rue Henri Becquerel, 34967 Montpellier, France

3

Université de Perpignan Via Domitia, 52 avenue Paul Alduy, 66860 Perpignan, France

* Corresponding author: [email protected] (M. Miguet).

Abstract The remediation of groundwater contaminated by common pollutant perchloroethylene (PCE) is reported. The studied process is adsorption using a fixed-bed column packed with granular activated carbon (GAC). An original setup was designed to perform the isotherms. Small particle sizes and fullscale GAC were tested. Adsorption capacity decreases with increasing particle size in the presence of natural organic matter. Columns running in dynamic-mode PCE in-feed were used to test three operating conditions. Sampling along the columns was used to monitor PCE concentration in the liquid phase at different column lengths. A large dataset was collected. A mathematical model based on mass balance of PCE was adopted to predict the adsorption dynamics under various operating conditions. Global mass transfer coefficients were identified to find the best fit with the experimental data. The model was reliable and accurate over the whole dataset. The performances of the fixed bed were evaluated in terms of operation time, total volume of decontaminated water and degree of GAC utilization. The results showed that a trade-off has to be found between these performance parameters. The model developed here can be used to design full-scale fixed-bed columns and optimize the three key parameters.

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Keywords: activated carbon; perchloroethylene; isotherm; fixed-bed column

1. Introduction

Chlorinated volatile organic compounds like perchloroethylene (PCE) are common micropollutants in groundwater [1-4] and are not susceptible to biological treatment due to their high toxicity. PCE has been introduced into the environment due to human activities since the early 20th century. PCE is widely used as a solvent for processes such as metal degreasing and dry cleaning [1]. PCE releases into the environment are through leakage and spillage, and it is now widely found in groundwater at existing and former industrial sites and disposal areas worldwide [1, 2, 5]. PCE is recognized as one of the most ubiquitous groundwater contaminants and its toxicity and persistence are of great concern [1, 6, 7]. PCE concentrations in polluted groundwater are typically around 10 µg.L-1 [2, 8] but can reach 10 mg.L-1 (and up to 80 mg.L-1) near places where contamination occurred by pouring the solvent [3, 8]. Drinking water treatment processes have to separate pollutants from groundwater to guard against adverse effects on human health and the environment. Adsorption on granular activated carbon (GAC) is a popular and efficient technology for removing micropollutants such as PCE [1, 9-12]. The adsorption process using GAC in a fixed-bed column is well known and widely used for micropollutants in order to get drinking water [13-16]. However, despite their toxicity and occurrence, PCE and a similar pollutant like trichloroethylene (TCE) have rarely been studied in fixed-bed adsorbers. The dearth of papers dealing with fixed-bed columns and PCE likely reflects the fact that the high volatility of PCE makes it difficult to handle and thus difficult to trial in experiments. Mathematical models can be used to predict the performance of a full-scale column, but they are not accurate enough if not calibrated on experimental data [14], which creates a need for reliable data on PCE breakthrough behavior. Many batch equilibrium isotherms have been reported but they overestimate full-scale GAC adsorber performances [17]. Bench-scale columns are rare and their operating conditions are far from industrial-process reality. The few studies on these experimental data, as listed below, have tested very small amounts of GAC, and either the


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columns were under-scaled or the inlet concentrations were over-scaled in relation to environmental levels of polluted water. Pavoni et al. [18] worked with a mix of micropollutants including PCE and TCE, but the column was run in batch mode and the bed length was less than 20 cm. Yu & Chou [2] used only 1 g of GAC in a column of less than 5 cm height with water polluted by PCE and TCE. Sotelo et al. [19] studied TCE at extremely high concentration (over 400 mg.L-1) and the mass of GAC was between 10 and 20 g. Pota & Mathews [20] worked on TCE with a bed length of less than 15 cm. All these experiments were performed over periods of just a few days, with the longest study still under a month, and they demonstrate that experiments are the only reliable means of obtaining useful parameters [18]. Pilot studies offer the most reliable predictions of full-scale adsorber performance, but they are expensive and require a particularly long time. Here we aimed at obtaining reliable and accurate data using bench-scale columns with operating conditions in the range of industrial-process and the same GAC particle size (1–2 mm) as used at full scale. This work set out with two objectives: (i) to determine a reliable method to estimate the adsorption capacity of GAC for a volatile compound; (ii) to form a database of breakthrough curves using fullsize GAC particle size (1–2 mm) and a common yet rarely-studied pollutant (PCE). Operating conditions such as empty bed contact time (EBCT) and superficial velocity were chosen to be in the range of typical values used in industrial treatment. Inlet concentration was set to a value close to 0.5 mg.L-1 to be in the range of the groundwater concentration found near the point source in the aquifer. The effect of superficial velocity on breakthrough was investigated. A mathematical model based on the experimental data was adopted in order to predict full-scale on-site treatment performances.

2. Materials and Methods 2.1. Perchloroethylene (PCE) and granular activated carbons (GAC) Batch experiments were performed using PCE-doped stock solutions produced with ultrapure water or groundwater. The groundwater was sampled by drilling and was already contaminated with PCE at concentrations between 10 and 40 µg.L-1. The PCE stock solutions were prepared by adding a defined



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volume (50 µL) of PCE (Sigma-Aldrich, 99.9%) into a 500 mL headspace-free glass vessel of water and sealing with a Teflon cap. PCE concentration in these ultrapure-water or groundwater-based stock solutions was between 70 and 100 mg.L-1. Column experiments were performed with tap water continuously doped via a syringe pump and a syringe filled with pure PCE (Sigma-Aldrich, 99.9%). PCE concentrations in solution were measured by ultra-high-performance liquid chromatography on a system (UHPLC UltiMate 3000) equipped with a UV–Vis detector and an Accucore C18 column (100×2.1 mm, 2.6 µm particle size). Analytes were separated with a mixture of acetronitril:water (72:28, v/v) at a flow rate of 0.4 mL.min-1 in isocratic elution mode with detection at λ = 199 nm. Calibration curves were determined by repeating the same injection of the standard (purchased from Dr. Ehrenstorfer) three times for each point. Limit of detection was calculated as a signal-to-noise ratio of 3. Limit of quantification was 200 µg.L-1. The GAC selected for the study was Aquacarb®, manufactured by Chemviron Carbon Company. It is certified for the treatment of drinking water and commonly used in water treatment processes. The raw material of Aquacarb is coconut shell, apparent density is 450 kg.m-3, surface area is 1100 m².g-1 and micropore area is 870 m².g-1. The micropore area represents 80% of the surface area. The GAC is mainly a microporous materials. A 1–2 mm GAC particle range was selected by mechanical sieving. A part of these 1–2 mm particles was milled and sieved to obtained smaller particle sizes (112–200 µm, 300–500 µm and 500 µm–1 mm diameter ranges). The particles were then dried by heating up to 230°C under low pressure (50 µmHg) using a Micrometrics ASAP 2000 apparatus.

2.2. Experimental setup Batch adsorption experiments The PCE/Aquacarb isotherms were obtained using a test bench set-up shown in Figure 1. The stainless-steel closed circuit consisted in a storage tank connected in series with the GAC cartridge. VOCs are particularly difficult to handle due to their very high volatility, so we designed the test bench to remain airtight while allowing sampling during the experiments.


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Initially, the fluid loop was completely filled with water and was PCE-free (Figure 1). Then, stock PCE solution was injected into the bench via the injection valve (1) while the same volume of PCEfree water left the setup (purge valve (5)). Pollutant concentration was homogenized in the entire bench via pathway A in the loop using a pump (4) and a 1-litre stirred tank(2). Volumetric flow was of 13 L.min-1. Temperature was controlled by a thermostatic bath (2). At this stage, the GAC was not in contact with the pollutant solution. Initial concentration was checked by analyzing samples taken with the sampling valve (3). Once the solution was stabilized, it was channeled through the GAC cell (6) via pathway B. Concentration was monitored during adsorption by sampling (3). The stability of the pollutant concentration in the liquid phase indicated that the equilibrium was reached between the two phases (solid phase on the GAC and the liquid phase). Equilibrium was considered as reached when the slope of the concentration profiles in the liquid phase reached a horizontal asymptote. The equilibrium criterion was determined from preliminary experiments series made under different conditions: range of sizes and water properties. This criteria set that the equilibrium is reached when the slope is lower than 0.4 mg.L-1.h-1 over two successive samplings with sampling-to-sampling interval of minimum 0.5 hour. It should be noted that achieving perfect balance on the concentration profiles is extremely long in liquid phase. Unlike adsorption phenomenon in gas phase, diffusion mechanisms are very limiting. Adsorption capacity was determined by mass balance on PCE in the liquid phase. The values of the adsorption capacity and the corresponding equilibrium concentration were reported on the isotherm. Then, a PCE stock solution re-injected into the setup and the same protocol (homogenization of the initial concentration and monitoring of the concentration during adsorption until equilibrium) was repeated. A new isotherm point was defined with higher adsorption capacity and equilibrium concentration values. This process was re-iterated until the saturation of the GAC. Adsorption capacity, i.e. amount of PCE adsorbed per unit of adsorbent (q), was calculated using the following equation: q=

C − C V m

(1)



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where C0 is initial PCE concentration (mg.L-1), Ct is PCE concentration at time t (mg.L-1), V is volume of the test bench (L) and m is weight of adsorbent (g). The determination of the equilibrium with a systematic kinetic criterion is innovative for a liquidphase isotherm. The usual method for establishing an isotherm is the bottle-point technique based on the principle of adding different adsorbent masses to bottles containing adsorbate solution. A fixed time is considered as equilibrium time and adsorption capacity is determined with the adsorbed concentration calculated from the mass balance considering the initial and equilibrium solute concentrations in the liquid [2, 19, 21]. The isotherms in this study were built with a process that mimics the standard operating mode adopted for gas nitrogen adsorption by GAC with the commercial Micrometrics ASAP apparatus. PCE adsorption onto the GAC occurred in successive steps in the test bench, leading to successive equilibrium conditions between the liquid and solid phases. This novel technique makes it possible to build the entire isotherm from the lowest to the highest equilibrium concentrations with the same GAC sample. The airtight setup also ensures a correct mass balance without solute loss to air. Finally, the kinetic criterion can be used to compare different adsorbents with different equilibrium times.

Fixed-bed column adsorption experiments The experiments were performed in dynamic mode using three fixed-bed columns (Figure 2). Flow was continuous via a tapwater feed (1). The chlorine was removed from tapwater via a GAC-filled column (2). The pollutant concentration was added to the tapwater via a syringe pump (3) and mixed via a static mixer (4) and two stirred tanks (5). The syringe pump made it possible to set inlet PCE concentration from 0.5–5 mg.L-1. Tapwater doped with PCE was fed to the fixed-bed columns in upward direction. All three adsorption columns shared identical dimensions (7), i.e. 50 cm height and 2 cm internal diameter. The volumetric flow in each column was regulated by a needle valve (6). A series of airtight micro-valves at the inlet and along each column (7) made it possible to take samples during the experiments and to establish the concentration profiles. A bed of GAC (8) received the outlet of the columns to avoid any pollution of the water system.


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Dynamic experiments were performed at flow rates of 0.6, 1.6 and 3.4 L.h-1 with particles of 1-2 mm size. Inlet PCE concentration was fixed at about 0.6 mg.L-1, a value close to the concentrations found near the source of pollution in the aquifer. Note that the high volatility of the PCE made it difficult to hold the imposed inlet concentration at 0.6 mg.L-1 and deviations of up to 0.2 mg.L-1 from the control concentration were measured during the 6-month experiment. Characteristic parameter values of dynamic adsorption are summarized in Table 1. Note that the empty bed contact time (EBCT) in liquid separation processes based on adsorption in fixed-bed full-scale treatments typically ranges from 5 to 30 min and superficial velocity is usually between 5 and 15 m.h-1 [14, 22, 23]. The operating conditions used here were in the range typically recorded for industrial packed-bed treatments.

3. Results and Discussion 3.1. Batch adsorption experiments Equilibrium adsorption was described using the Langmuir isotherm. Langmuir isotherm theory is based on the assumption of a monolayer adsorption occurring on a homogeneous surface [24]. Langmuir’s isotherm model is represented by the following equation: q =

q bC 1 + bC

(2)

where qe is adsorption capacity at equilibrium (mg.g-1), qm is maximum monolayer adsorption capacity (mg.g-1), Ce is equilibrium concentration (mg.L-1) and b is a constant related to energy of adsorption (L.mg-1). The uncertainties were calculated based on the uncertainties on the measurements (scale and HPLC) and on the mass of activated carbon (desorbed mass). Level of uncertainty was 2.05% on concentrations and 12.35% on adsorption capacities. Equilibrium adsorption isotherms of PCE diluted in ultrapure water at 25°C are reported in Figure 3 showing the isotherms over the entire measurement range up to 30 mg.L-1 and a close-up of the isotherms at the beginning of the concentrations up to 2 mg.L-1. The close-up is interesting as most environmental concentrations of polluted water tend to be lower than a few mg.L-1. The adsorption



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capacity was calculated with a particle diameter of 112–200 µm. Two isotherms were obtained under the same conditions to test the experiment repeatability. The Langmuir fittings were performed with qm=510 mg.g-1 and b=1.224 L.mg-1 for the first isotherm (- -) and qm=454 mg.g-1 and b=1.495 L.mg-1 for the second isotherm (─).The repeatability of the measurements was reliable. Both isotherms show an IUPAC type-I pattern characterized by a horizontal plateau until saturation, which is typical for a predominantly microporous network and monolayer adsorption. The ultimate goal is to use the GAC (Aquacarb) to treat groundwater. In order to quantify the possible influence of water composition, experiments were performed with the same conditions (particle size and temperature) but with groundwater. The tested groundwater was sampled from a drilling site already contaminated by the pollutant and doped with PCE. A series of 6 isotherms were performed with groundwater sampled over a 12-month period, as reported in Figure 4. Groundwater composition is less stable than the ultrapure water. This groundwater composition fluctuation was responsible for the variations in the measurements as it was the only variable parameter. The Langmuir fitting was performed using characteristic experimental data of all 6 isotherms. The values of the parameters were qm=518 mg.g-1 and b=0.798 L.mg-1. Note that despite the variations in groundwater composition, the experimental data were in the range of uncertainties of the mean isotherm fitted by the Langmuir model. The measured adsorption capacities were slightly lower with groundwater than with ultrapure water, likely due to the natural organic matter (NOM) found in groundwater. Similar results are reported in other studies. The decrease in adsorption capacity of activated carbons in the presence of NOM is well documented in the literature [25-27]. Summers et al. [28] and Carter el al. [29] studied the effects of organic matter on TCE adsorption by GAC and also concluded that adsorption capacity decreased in the presence of NOM. Adsorption capacity is a required data in order to describe the working mode of a fixed-bed column during separation. The usual GAC particle size in the industry is 1–2 mm. In order to be as close as possible to the operating condition in the industry, adsorption isotherms were performed in the same conditions (groundwater, 25°C) but different particle diameters, i.e. 300–500 µm, 500 µm–1 mm and 1–2 mm. A small particle size (112–200 µm) was used in the previous experiments because the kinetics is faster with finer particles. As a matter of fact, the average equilibrium times for each size


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were 5.5 hours for 1-2 mm, 4.5 hours for 500 µm–1 mm, 3 hours for 300–500 µm and 1.5 hour for 112–200 µm. The isotherms with different particle diameters are reported in Figure 5. We had expected to see similar isotherms, as adsorption capacity is assumed to be unaffected by particle size [21], but we actually found a sharp decrease in adsorption capacity with increasing particle size. Adsorption capacity was 230 mg.g-1 for a particle size of 112–200 µm but dropped to 165 mg.g-1 for a particle size of 1–2 mm at an equilibrium concentration of 1 mg.L-1 (typical of highly-contaminated water in environmental samples). This strong 30% decrease cannot be neglected. Other studies have focused on adsorption capacity with real water and different particle sizes. Corwin & Summers [30] investigated the adsorption capacity of activated carbon particles with various sizes for bisphenol A in presence of dissolved organic matter (at an organic matter concentration of 2 to 2.5 mg.L-1) and showed that GAC adsorption capacity is dependent on particle size when organic matter is present. This behavior is attributed to pore blockage, the reason being that organic matter would block or clog a part of the porous net, resulting in a larger available surface area for adsorption of finer particles. The microporous surface area behind the obstructed pores increases with increasing particle size. This phenomenon results in a lower adsorption capacity at larger particle sizes with real water and the presence of organic matter. Similar results have been observed by different authors investigating the adsorption of bromate [31] and zinc and nickel [32] onto activated carbon with various particle sizes. Note that the concentration of total organic carbon in the groundwater used in this study ranged from 1 to 2 mg.L-1, which is close to the organic matter concentration in the work of Corwin & Summers. Table 2 lists the literature values from previous studies that have estimated the adsorption capacity of GAC with PCE and TCE. The adsorption capacities measured here were in the range of these literature values.

3.2. Fixed-bed column adsorption experiments The design of a fixed-bed adsorption column requires an understanding of the dynamic behavior of the fixed-bed process. As time proceeds, the pollutant saturates the GAC in the packed bed near the inlet, and a concentration profile known as the mass transfer zone (MTZ) develops and moves through



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the bed. The fluid-phase concentration drops from the feed value to zero within this zone. The MTZ is defined as the depth of fixed-bed GAC required to reduce the contaminant concentration from the initial inlet concentration to a value close to zero at a given velocity. Upstream of the MTZ, the adsorbent is in equilibrium with the feed. Downstream, the adsorbent is in its initial state. Eventually, the MTZ arrives at the outlet and the pollutants appear in the outlet. The time needed for the outlet concentration to reach the treatment objective is the operation time. MTZ is directly linked to the quality of separation and defined as the useful length of bed that is used before regeneration or replacement of the adsorbents. Beyond the concentration profiles in the fluid, the quality of the separation can be qualified by the shape of the breakthrough curve corresponding to the concentration profile at the outlet of the column over time. This profile defines the breakthrough time when the pollutant begins to appear in the outlet.

3.2.1.Mathematical modeling The well-known one-dimensional formalism is considered with concentration gradients (in both the fluid and the solid phase) in the direction of fluid flow. Basically, pollutant mass transfer from the liquid bulk phase to the solid phase is the result of two resistances in series, i.e. diffusion in the fluid film around the particle and intraparticle mass transfer. Both phenomena are considered in the linear driving force formalism commonly adopted for adsorption in a microporous adsorbent [21, 33-35]. Axial diffusion in the fluid was compared to forced convection with the Péclet number (Pe). Pe number was found to be high (from 8.3.105 to 4.6.106), thus clearly showing that rate of axial diffusion is negligible compared to rate of convection for the three columns. The mass balance applied to the pollutant in the bulk liquid (3) and solid phases (4) leads to the following partial differential equations: dC ρ v dC = − kq − q − dt ε ε dx dq = kq − q dt

(3)

(4)

where C is pollutant concentration in the bulk phase (mg.L-1), ρGAC is apparent density of the activated carbon (g.L-1), k is global mass transfer coefficient (s-1), qe is amount of pollutant adsorbed at


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the equilibrium (mg.g-1), q is mean pollutant composition in the particle (mg.g-1), ε is bed porosity (-) and v is superficial velocity (m.s-1). The value of qe is given by the isotherm derived with a particle size diameter of 1–2 mm and groundwater (Figure 5). Initial and boundary conditions are: t = 0 Cx, t = 0 qx, t = 0

(5)

x = 0 Cx, t = C

(6)

Solving the system of differential equations (3 and 4) provides the concentration profiles in the fluid and solid phases as a function of time regardless of operating conditions. The global mass transfer coefficient (k) is the only unknown parameter in the description of the transfer of the pollutant between the two phases. k was identified for each case by minimizing a least squares criterion that compares the calculated liquid concentration profiles against the experimental results (equation 7). /

C&'( ) C*+,( 1 criterion = # $% n C&'(

.

012

(7)

where Cexp is experimental concentration (mg.L-1), Ccal is calculated concentration (mg.L-1) and n is number of experimental data (9 data per week per column, i.e. 7 in-column concentrations, 1 inlet concentration and 1 outlet concentration).

3.2.2.Concentration profiles We ran a set of lab-scale columns to verify that the model presented above stays reliable under different operating conditions. To this end, three columns were operated in parallel, and the parameters studied were liquid flow rate, superficial velocity and EBCT. These parameters are dependent and the correlations between them are as follows: v= EBCT =

Q A

(8)

v HA = Q Q

(9)

where Q is flow rate (m3.s-1), A is section of the column (m2), EBCT is empty bed contact time (s), V is the volume of the column (m3) and H is bed height (m).



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Eqs. (8) and (9) lead to: EBCT × v = H

(10)

The concentration profiles were obtained by monitoring the concentrations over the whole column. Samples were taken via the micro-valves (Figure 2) at the inlet (1 sample), along the column (7 samples), and at the outlet (1 sample). A concentration profile at time t is the set of the 9 measurements taken on a whole column at t. Figure 6 reports the concentration profiles thus obtained for the three columns at different times. The MTZ position is measured between two points: the highest column length where the inlet concentration is measured and the column length where the concentration is zero. The example of column 2, corresponding to an EBCT of 6 min and a velocity of 5 m.h-1, is selected to describe the concentration profiles during the experiment. At the beginning of the experiment, the contaminants were adsorbed onto the GAC at the inlet and the MTZ started at the entrance of the column. The concentration profile at day 14 shows that the MTZ was still beginning at the entrance and ended at a 35–40 cm into the column. As the experiment went on, the GAC at the beginning of the fixed-bed was in equilibrium with the liquid phase and did not adsorb any more pollutant. The MTZ then moved toward the outlet. At day 70, the inlet concentration was measured up to 10 cm column length and the breakthrough had already been reached. At day 112, the inlet concentration was measured up to 15 cm column length and the GAC approached the equilibrium conditions throughout the entire column. At day 175, outlet concentration was almost equal to inlet concentration and the column could not remove any more pollutant. All three columns reproduced a similar pattern of concentration profile evolution, but the shape and the length of the MTZ were dependent on EBCT, i.e. 16 min for column 1, 6 min for column 2 and 3 min for column 3. Superficial velocity is inversely proportional to EBCT according to Eq. 10, i.e. 2 m.h-1 for column 1, 5 m.h-1 for column 2 and 11 m.h-1 for column 3. MTZ length can be estimated as about 30 cm for column 1, 50 cm for column 2 and is more than 50 cm for column 3. MTZ height was larger at low values of EBCT and high levels of superficial velocity, respectively. Column 3 was stopped after day 70 of the experiment with over 65% saturation at the outlet.


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Figure 6 also gives comparison between simulated and experimental results after identification of the mass transfer coefficients. The k values giving the best fit to the experimental dataset were k=6.107

s-1 (column 1), k=5.10-7 s-1 (column 2) and k=6.10-7 s-1 (column 3). If we consider concentration

instead of adsorption capacity in equation 4, k can also be expressed in m.s-1. Table 1 reports these k' values in m.s-1 and in s-1. These k' values are consistent with previous studies. Nurbas et al [36] identified an overall mass transfer coefficient of 1.10-6 m.s-1 for adsorption of Cu2+ ion onto Caalginate particles. Other authors considered only the external mass transfer coefficient and found values between 5.0.10-9 m.s-1 and 7.9.10-6 m.s-1 (adsorption of sugars such as glucose onto zeolites [37]) and 8.2.10-6 m.s-1 (adsorption of amylase onto an anion exchanger [38]). The very similar k values found here are probably the result of a combination of two phenomena: a main adsorption rate limitation due to internal diffusion inside the porous network of the particles and a very close flow regime in all three columns leading to a similar external mass transfer coefficient in the thin film around particle. The particle Reynolds number Rep that identifies the flow regime is given by: Re' =

ρvd' εμ

(11)

where ρ is fluid-phase density, v is superficial velocity, ε is bed porosity, dp is particle diameter and µ is fluid-phase viscosity. The Rep values of the three columns are between 2 and 11 (see Table 1). The flow is laminar for Rep < 1 but inertial for 10 < Rep < 250-300. The transition to turbulent flow in a packed bed is difficult to identify and depends on the size and shape of particles and on the bed characteristics. Various studies have shown that turbulent flow exists beyond Rep=300-400 [39-41]. The Rep values in the three studied conditions indicate that the flows were at the beginning of the inertial flow regime in all columns studied here.

Whatever the case studied, it can be seen that the simple model proposed here fits the experimental results with a reasonable degree of accuracy. The fittings for the three columns are consistent with the experimental results. This model based on mass balance is reliable, even if deviations are observed, especially in the case of the highest velocity when column 3 reaches saturation.



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3.2.3 Breakthrough curves The data are also collected in breakthrough curves to describe the performances of the fixed-bed. The breakthrough curves plot concentration versus time, where concentration is measured at a fixed point in the column. Column breakthrough is shaped by many factors, including pollutant and adsorbent. As these factors were already fixed in this study, we investigated the effect of the velocity on column performance. Breakthrough time varies according to objective, but generally equates to a very low contaminant concentration in the effluent, so breakthrough point is often taken as 5% of inlet concentration. The steepness of the breakthrough curve determines the extent to which the capacity of a fixed-bed can be used for a given pollutant–adsorbent system. The shape of the curve is a relevant characteristic and one of the criteria that makes it possible to evaluate the efficiency and quality of separation of the pollutant from the effluent [42]. Experimental data and simulations presented in Figure 7 cover the total duration of the experiments (70 days for column 3 and 175 days for columns 1 and 2). Our experimental set-up enabled sampling at various column lengths and breakthrough curves were obtained at each sampling point along each fixed bed. Here, we chose to work to column lengths of 30, 40 and 50 cm for the breakthrough curves. Taking various column lengths is like having various separate columns with different EBCTs for each length. Figure 7 a) shows the three column breakthrough curves for a column length of 30 cm. As expected, the breakthrough curves are very different. The results of the column 1 indicate an outlet concentration close to zero up to almost 100 days in operation. Outlet concentrations of columns 2 and 3, with higher velocities, were rapidly above zero after just a few days in operation. The curve for column 3 was very steep and reached complete saturation in around 100 days. The curve for column 2 was less steep and reached complete saturation at around 200 days. Column 1, with the smallest velocity, gave the widest slope and was far from reaching complete saturation at the end of the 6month experiment. Simulation suggests column 1 would take more than a year to reach saturation. In


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these operating conditions, column 1 took 3.5-times longer to reach complete saturation than the fastest breakthrough curve of column 3. In contrast to superficial velocity, EBCT varies with bed height. Figures 7 b) and 7 c) show the results for column lengths of 40 and 50 cm, respectively. Columns 2 and 3 gave non-zero outlet concentrations early after beginning the experiment, whereas column 1 had the first breakthrough concentration after more than 150 days. The breakthrough curves got steeper with higher velocities. These results highlight the well-known role of operating parameters, i.e. EBCT and velocity. These factors determine the shape and slope of the breakthrough curve. Simulations were run with the same global mass transfer coefficient k as presented above (k=6.10-7 s-1 for column 1, k=5.10-7 s-1 for column 2 and k=6.10-7 s-1 for column 3). The fitted plots are acceptable and match the experimental data for all three columns at the different column lengths. After validation, the simulation tools were used to extrapolate breakthrough beyond the experimental duration until complete saturation of the columns with a reasonable degree of confidence (Figure 7).

3.2.4 Performance of the fixed-bed column Once validated, the mathematical model can be used to predict the adsorption behavior of a wide variety of fixed-bed column processes. The performances investigated are efficiency of GAC utilization, operation time, and total decontaminated volume depending on superficial velocity. As stated earlier, the typical velocities used in the industrial process are between 5 and 15 m.h-1 [14, 22, 23] and our experimental data and simulations were obtained in this range of values. Operation time is the time taken for the column outlet to reach the treatment objective, which is key to the performances of fixed-bed adsorbers as it defines the time when the GAC has to be replaced or regenerated. Designers want maximal velocity to treat the highest volume as fast as possible. Figure 8 plots operation time (treatment objective set at C/C0=0.05) versus velocity. The curve was determined by simulation with a global mass transfer coefficient considered as constant and equal to 6.10-7 s-1 and in the case of a column length of 50 cm. The two experimental points correspond to columns 2 and 3. The experimental operation time of the column 1 estimated at 226 days by simulation is not plotted as it was not reached during the 6-month experiment. The curve fits the experimental data reasonably



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well. The simulation shows that operation time drops from 230 to 11 days when velocity increases from 2 to 10 m.h-1. Breakthrough goes over the treatment objective in less than a day for a velocity higher than 14 m.h-1. Separation requires specific conditions leading to an MTZ inside the column, which fails to occur when velocity is too high. A very high velocity has a detrimental effect by increasing the MTZ resulting in a faster breakthrough. To be relevant, operation time has to be associated with total volume of decontaminated water, which is plotted in Figure 9. The two experimental points represent the volume decontaminated by columns 2 and 3. As stated earlier, column 1 did not reach the treatment objective (C/C0=0.05) during the 6-month experiment. The volume goes from 3.5 m³ with a velocity of 2 m.h-1 to 1 m³ with a velocity of 9 m.h-1. A shorter velocity enables a higher treated volume. The goal of this type of process is to treat the largest volume possible, so according to this parameter, velocity should be as low as possible. The treated volume parameter shows an opposite trend compared to operation time, which highlights the need to find a trade-off between operation time and total volume of decontaminated water.

Another important parameter characterizing a fixed-bed adsorber is the degree of GAC utilization which is quantified by carbon usage rate (CUR): CUR =

m Q. t ?

(12)

where tb is operation time and m is mass of GAC. With an extremely short MTZ and a very steep breakthrough curve, the column is completely saturated when the pollutant reaches the outlet. This represents the smallest CUR: all the contaminants are adsorbed onto the GAC, and this condition matches the best use of the adsorbent. The GAC is in equilibrium with inlet concentration throughout the column. As expected, and as is well known for adsorption-based separation processes, the GAC is best used with low velocity. The CUR versus velocity plot obtained by simulation is reported in Figure 10 for a column length of 50 cm, a global mass transfer coefficient of 6.10-7 s-1, and a treatment objective set at C/C0=0.05. The long contact time increased the mass transfer between the GAC and the pollutant. Adsorption capacity was


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enhanced by this longer contact time and became higher. The duration of the experiment was not long enough to obtain the experimental CUR of column 1, but the CUR of columns 2 and 3 are reported in Figure 10. The CUR profile simulated as a function of velocity is consistent with the experimental data. The minimal values were obtained for a MTZ much smaller than the column length, and the adsorption capacity q upstream of the MTZ is close to qe. The maximal values match the operating conditions of an MTZ approaching or larger than bed length. The good use of the GAC is achieved with a low CUR, i.e. a low velocity. This parameter follows the opposite trend to operation time but the same trend as total volume of decontaminated water.

The CUR parameter can be considered representative of yield on the GAC, decontaminated volume as representative of yield on the water, and operation time as a means to evaluate the time required for the process. It is possible to use these three performance graphs to design a suitable column while finding the best trade-off between process yields and process duration.

4. Conclusion

Here we investigated the decontamination of PCE-polluted water with a GAC commonly used for water treatment (Aquacarb). Batch-mode isotherms were measured using an original setup. The method is repeatable and reliable. Isotherms performed with ultrapure water and groundwater showed a slightly lower adsorption capacity with groundwater. It was demonstrated that adsorption capacity decreased with increasing particle size in the presence of natural organic matter. This evolution is due to pore blockage. Organic matters block or clog a part of the porous net, resulting in a larger available surface area for adsorption of finer particles. These differences highlight the importance of performing an isotherm under actual operating conditions. In order to build a significant dataset, three columns were run for six months under operating conditions in the range of industrial packed-bed treatments. Results outputs were the concentration profiles and breakthrough curves at various column lengths and EBCTs. Our mathematical model



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based on mass balance fitted the results with a reasonable degree of accuracy for the various operating conditions tested. This model was used to simulate the data and fit the concentration profiles and breakthrough curves. The identification of the mass transfer coefficient (the only adjustable parameter) for the three columns gave very similar values (centered around k=6.10-7 s-1). The identified mass transfer coefficient can be used in the range of the tested velocities which is the range used in the industrial process. Fixed-bed column performances were evaluated in terms of operation time, total volume of decontaminated water and degree of GAC utilization. Both the dataset and the mathematical model were used to assess these performance criteria. A fast treatment process means poor use of the GAC and a lower decontaminated volume. The design of a fixed-bed column hinges on finding a trade-off between characteristic performance criteria of the separation process.

Acknowledgements

The authors would like to thank Veolia Eau for funding this research. In addition, the authors would like to thank the technician Jean-Jacques Huc (UPVD) for his contribution to this study.

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Tables and figures

Figure 1: Test bench set-up for batch adsorption experiments: injection valve (1), stirred tank in a thermostatic bath (2), airtight sampling valve (3), pump (4), purge valve (5) and GAC cell (6). There are two pathways: A) PCE solution homogenization and B) GAC in contact with the PCE solution. Figure 2: Test bench set-up for dynamic adsorption experiments: continuous flow (tapwater) (1), chlorine removal (2), syringe pump with PCE (3), static mixer (4), stirred tanks (5), needle valves (6), adsorption columns and sampling valves (7) and bed of GAC (8). Figure 3: Experimental isotherms with Aquacarb and ultrapure water at 25°C, particle diameter of 112–200 µm (○ and *) with Langmuir fitting ((‒) and (- -)) Figure 4: Experimental six isotherms with Aquacarb and groundwater at 25°C, particle diameter of 112–200 µm (□) with Langmuir fitting (‒) Figure 5: Experimental isotherms with Aquacarb and groundwater at 25°C, particle diameter of 300–500 µm (∆) with Langmuir fitting (‒ •), particle diameter of 500 µm–1 mm (◊) with Langmuir fitting (- -), particle diameter of 1–2 mm (○) with Langmuir fitting (‒ ‒), and particle diameter of 112– 200 µm with Langmuir fitting (‒) Figure 6: Concentration profiles at different times: (a) column 1 (EBCT 16 min, 2 m.h-1) based on experimental data (points) and simulated concentrations with k=6.10-7 s-1 (curves); (b) column 2 (EBCT 6 min, 5 m.h-1) based on experimental data (points) and simulated concentrations with k=5.10-7 s-1 (curves); (c) column 3 (EBCT 3 min, 11 m.h-1) based on experimental data (points) and simulated concentrations with k=6.10-7 s-1 (curves) Figure 7: Breakthrough of columns 1 (EBCT 16 min, 2 m.h-1) (◊), 2 (EBCT 6 min, 5 m.h-1) (□) and 3 (EBCT 3 min, 11 m.h-1) (○) and fitting with k=6.10-7 s-1 for column 1 (•••), k=5.10-7 s-1 for column 2 (— ••) and k=6.10-7 s-1 for column 3 (─): (a) at 30 cm column length; (b) at 40 cm column length; (c) at 50 cm column length. Figure 8: Operation time versus velocity with a column length of 50 cm and a treatment objective of C/C0=0.05, experimental data (□) and fitting with k=6.10-7 s-1 (─)


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Figure 9: Total volume of decontaminated water versus velocity with a column length of 50 cm and a treatment objective of C/C0=0.05, experimental data (□) and fitting with k=6.10-7 s-1 (─) Figure 10: Carbon usage rate versus velocity with a column length of 50 cm and a treatment objective of C/C0=0.05, experimental data (□) and fitting with k=6.10-7 s-1 (─)

Table 1: Characteristic parameters of dynamic adsorption Table 2: Adsorption capacity of different activated carbons for PCE and TCE



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For Table of Contents Only


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Figure 1

1

ACS Paragon Plus Environment


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Figure 2

1


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Figure 3

1



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Figure 4

1


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Figure 5

1



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Figure 6 a)

Figure 6 b)

Figure 6 c)

1


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Figure 7 a)

Figure 7 b)

Figure 7 c)

1



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Figure 8

1


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Figure 9

1



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Figure 10

1


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Table 1 Column 1

Column 2

Column 3

Superficial velocity (m.h-1)

2

5

11

EBCT (mn)

16

6

3

Flow rate (L.h-1)

0.6

1.6

3.4

Bed height (cm)

50

Bed apparent density (g.L-1)

450

Particle diameter (mm)

1-2

GAC mass (g)

68

[PCE] (mg.L-1)

0.6 ± 0.2 6.10-7

5.10-7

6.10-7

8.3.10-6

7.0.10-6

8.3.10-6

2.1

5.2

11.1

k (s-1) k' (m.s-1) Rep

1



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Page 38 of 38

Table 2

Reference

Erto et al., 2010 Sotelo et al., 2004

Erto et al., 2010

Temperature 10°C 20°C 35°C 50°C 25°C

20°C

Bembnowska et al., 2003

30°C

Yu and Chou, 2000

20°C

Activated Carbon

Particle size

Pollutant

Aquacarb 207 No TCE EA information GAC-1240 Aquacarb 207EA Filtrasorb 400 GCN 1240 Organorb-10 Organosorb10AA Organorb10CO DTO AG-5 WD-EXTRA Filtrasorb 400

0.5-1.5mm TCE

No TCE information

0.5-1.3mm PCE No TCE information PCE 1-2 mm 500 µm - 1 mm

Present study

25°C

Aquacarb

PCE 300-500 µm 112-200 µm

1


Ce (mg.L-1) 1 1 1 1 1 1

qe (mg.g-1) 80 50 40 25 90 45

1 1 1 1

90 100 45 40

1

80

1 1 1 0.2 0.2 0.2 0.5 1 0.2 0.5 1 0.2 0.5 1 0.2 0.5 1

30 10 10 20 38 47 101 165 53 115 187 69 143 223 71 148 230

Equilibrium time No information 15 h

No information

20 h 5h 5.5 h

4.5 h

3h

1.5 h

(Perchloroethylene) from the Aqueous Phase by Adsorption on

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