Influence of absorbent dosage

The influence of iron oxyhydroxides was examined by varying the adsorbent dosage in the range of 3 – 8 g/L and membrane flux was set at 100 L/(m²·h) (Figure 6.8(A)). As(V) contaminated water flows continuously to the reactor containing a comparatively large amount of iron oxyhydroxides. The abundant amount of adsorbent initially dosed into the reactor affects not only the immediate breakthrough and working zone but also the later zones of the breakthrough curve.

With increasing adsorbent dosage, the immediate decrease not only occurs faster but also achieves the lowest As(V) concentration in the reactor (~99.9%). It can be seen from Figure 6.8(A) that the increasing adsorbent dosage has elongated the length of the working zone. For instance, when Mad

is doubled (from 4 to 8 g/L) the time taken to reach C/Cin= 0.1 has been delayed by more than twice. This implies that adding more adsorbent at the start of the experiment is beneficial for longer time operations so that the time interval to supplement fresh or to start regeneration process can be prolonged. Using higher adsorbent dose in hybrid membrane system is also favorable in term of regeneration of adsorbent. It is generally expected that time taken to regenerate the different amounts of adsorbent under strong alkaline conditions are the same.

To investigate the combined effect of adsorbent dosage and hydraulic retention time of adsorbate, a parameter so-called “adsorbent load” has been defined (Eq. 6-6). This parameter represents the ratio of the total amount of adsorbent in the slurry reactor to the influent flow rate.

Adsorbent load =^{V M}_Q^ad (6-6)

Figure 6.8(B) shows the simulated effect of the adsorbent load on the breakthrough time to reach As(V) removal efficiency of 90% (C/Cin = 0.1). The results are shown as a function of membrane flux, for values 200 and 100 L/(m²·h), corresponding HRT of 17 and 34 min. The influence of the operating parameters such as residence time and adsorbent dosage is similar for both adsorbents in the SMAHS.

Figure 6.8. (A) Model prediction for As(V) removal using µGFH (1 – 63 μm) at Cin= 380 µg/L, adsorbent dosage and membrane flux= 100 L/(m²·h); (B) Simulated effect of adsorbent load on breakthrough time of 0.1 for two particle size fractions of µGFH and µTMF. Small filled solid symbols represents the results at 200 L/(m²·h), whereas large unfilled solid symbols at 100 L/(m²·h).

The model simulations show a linear relationship between the breakthrough time and adsorbent load. This relationship is almost indistinguishable for the hybrid membrane system at varying residence times and iron oxyhydroxides dose. This implies that with a same particle size fraction,

longer times of higher As(V) removal (90%) can be achieved either at a higher adsorbent dose with smaller residence times or at lower adsorbent dosages with larger residence times. A minimum of one adsorbent load is necessary to achieve 90% removal using iron oxyhydroxides in the SMAHS.

7 Fine-grained arsenic adsorbents as dynamic membrane forming materials The powdered-sized fraction (1-63 µm) of fine-grained iron oxyhydroxides have profound effect on As(V) adsorption rate (Figure 6.2(B)). This particle size fraction of iron oxyhydroxide-based adsorbents might be applied to form pre-deposited DMs to provide new insights into the use of powdered-sized iron oxyhydroxides as DM forming materials for remediation of arsenic polluted water. Hence, pre-deposited DM was formed in-situ by filtering slurry of powdered-sized adsorbents (1 - 63 µm) in ultrapure water at 0.5 bar applied pressure prior to the introduction of the arsenic contained feed solution. In chapter 7.2, the application of powdered-sized µGFH and µTMF pre-deposited DM was investigated in the MF process. The special attention was given to membrane water flux, amount of pre-deposited material per unit area of primary MF membrane, and arsenic feed concentration to find the best-operating conditions for optimum arsenic removal (Chapter 7.3). Moreover, the experimentally determined As(V) removal rates were then modeled using a mathematical model based on the HSDM and adsorbate mass balance over the DM filter (discussed in Chapter 7.1).

Selected contents of this chapter have been published in collaboration with Ioannis A.

Katsoyiannis, and M. Ernst: Journal of Chemical Technology and Biotechnology 2021.

(Usman et al. 2021): https://doi.org/10.1002/jctb.6728

7.1 Formulation of mathematical model

The mass balance over an infinitesimal element of the pre-deposited DM filter in linear coordinates (z) is:

ε_B^∂C_∂t+ v_f ^∂C_∂z − ^{3 (1− ε}_R ^B) k_f (C−C_s ) = 0 (7-1) In Eq. 7-1, time is represented by t, filter velocity is represented by vf, cake layer porosity is represented by ε_B, particle radius is represented by R, mass transfer coefficient due to the external film diffusion is represented by k_f, adsorbate liquid-phase concentrations in the pre-deposited iron oxyhydroxides layer and at the particle external surface are represented by C and Cs, respectively.

In Eq. 7-1, the first term represents the mass in the void fraction (pores), the second term reflects solute entering and exiting the element by advective transport, and the last term represents the sink, i.e., the mass of solute adsorbed by the adsorbent grains. The more details can be found elsewhere (Sontheimer 1988; Sperlich et al. 2008).

This model differs from the former one (discussed in Chapter 6). The adsorbent pre-deposited DM filter act as a fixed-bed adsorption filter, where each adsorbent particle in the adsorbent cake layer accumulates adsorbate such as As(V) from the percolating feed solution as long as the state of equilibrium is not reached. This equilibration process proceeds successively, layer by layer, from the filter inlet to the filter outlet. Moreover, the adsorption process in a pre-deposited DM filter is a time- and distance-dependent process, whereas adsorption in a slurry reactor od the SMAHS is only a time-dependent process.

For model solution, a desktop software FAST 2.0 (Fixed-bed Adsorption Simulation Tool, http://www.fast-software.de/) developed by Sperlich et al. (2008) was applied. This software provides a numerical solution of Eqs. 7-1 and 2-15 to simulate the concentration profiles of anion over time of a fixed-bed adsorption filter packed with an adsorbent used in water treatment.