Table 3.2. Obtained parameters from the adsorption isotherms fit to both models.
Langmuir
Freundlich
Adsorbent-adsorbate
qmáx
KL
R2
KF
n
R2
Azolla-Cu
0.457
14.19
0.9837
0.399
4.70
0.8895
46
Bioremediation for Sustainable Environmental Cleanup
Figure 3.4. Experimental data and non-linear fit of the used models to the copper on Azolla adsorption isotherms.
3.5 Adsorption Column Design
In metal biosorption studies it is common to work in batch systems due to the speed of the process to
obtain results and to be able to work on a very small scale in terms of the use of both the adsorbent
and the adsorbate. The results obtained from these tests allow, from different modulizations, to
attain parameters that permit quantifying the efficiency of adsorption in the elimination of specific
adsorbates, as well as the maximum adsorption capacity. However, for larger scale processes,
biosorption in fixed bed columns with continuous flow is preferable. These systems are in non-
equilibrium and the concentration profiles in both the effluent and the fixed phase vary not only with
time but also with space.
The fluid dynamic behavior of a fixed-bed column is described by means of concentration
profiles of the adsorbate in the effluent versus time or volume. The curves obtained are a function
of the adsorbent geometry, the operating conditions and also the adsorption data at equilibrium.
The relative concentration curve (C/C0) of the metal in the effluent versus total volume (or time) is
known as breakthrough curve (BTC), and is obtained by passing a solution containing the solute to
be adsorbed with an initial concentration C0 through a column (fixed bed) packed with the adsorbent
particles, measuring the output concentration C at different times.
The characteristics of the breakthrough curve are very important in the sense that the operation
and dynamic response in a continuous reactor can be determined (Salamatinia et al. 2008). The
breakthrough curve shows the performance of a fixed bed reactor from the point of view of the