An integrated use of Macroalgae as bioproducts source and biosorbent for environmental applications

Marine macroalgae are available in large quantities in many regions of the world and have been widely investigated as potential biosorbents for the removal of metals in wastewaters. However, few studies have been published on the biosorption of metals with seaweeds waste after the extraction of bioactive compounds.

This dissertation presents the study about: 1) the valorisation of macroalgae biomass based on the biorefinery concept giving rise to added-value byproducts like polyphenols and polysaccharides, and 2) the use of the produced waste to remove Cu(II) from contaminated wastewaters.

Chemical characterization of the two seaweeds studied, Ascophyllum nodosum and Ulva rigida, was performed. A.nodosum presented a higher percentage of ashes (13.8 ± 0.1 %) than U.rigida (10.9 ± 0.2 %). Regarding the percentage of polysaccharides, A. nodosum presented a lower percentage (45 ± 2 %) than U. rigida (48.7 ± 0.1 %). About the polyphenolic content, A. nodosum presented a higher value (0.95 mg GAE g-1) than U.rigida (0.33 mg GAE g-1).

FTIR analyses of Ascophyllum nodosum, before and after Cu(II) biosorption, identified some of the main functional groups that play a key role in metal biosorption: carboxyl functional group – COOH and alcohol functional group - OH. FTIR analyses of Ascophyllum nodosum were performed before and after extraction of polyphenols, indicating that the lack of this bioactive compounds reduced the hydroxyl stretches.

Preliminary biosorption tests for Cu(II) removal by Ascophyllum nodosum before and after extraction of polyphenols, present best results with A. nodosum virgin at pH values of 4 and 5. The adsorbed amount values obtained were in a range between 2.13- 2.25 mg g-1.

The biosorption kinetics was found to be fast, with more than 50% of Cu(II) maximum adsorption equilibrium capacity attained within 15 minutes and equilibrium reached after 30 minutes. This kinetic data was fitted to pseudo first-order and pseudo second-order models.