Abstract

Contaminated sediments may induce long-term risks to humans and ecosystems due to the accumulation of priority and emerging inorganic and organic pollutants having toxic and bio-accumulation properties that could become a secondary pollution source. This study focused on the screening of novel bio-based materials to be used in the decontamination of marine sediments considering technical and environmental criteria. It aimed to compare the environmental impacts of cellulose-based adsorbents produced at lab scale by using different syntheses protocols that involved cellulose functionalization by oxidation and branching, followed by structuring of an aerogel-like material via Soxhlet extraction and freeze-drying or their combination. As model pollutants, we used 4-nitrobenzaldehyde, 4-nitrophenol, methylene blue, and two heavy metals, i.e., cadmium and chromium. When comparing the three materials obtained by only employing the Soxhlet extractor with different solvents (without freeze-dying), it was observed that the material obtained with methanol did not have a good structure and was rigid and more compact than the others. A Life Cycle Assessment (LCA) was conducted to evaluate the environmental performance of the novel materials. Apart from the hierarchical categorization of the materials based on their technical and environmental performance in eliminating organic pollutants and heavy metal ions, it was demonstrated that the cellulose-based material obtained via Soxhlet extraction with ethanol was a better choice, since it had lower environmental impacts and highest adsorption capacity for the model pollutants. LCA is a useful tool to optimize the sustainability of sorbent materials alongside lab-scale experiments and confirms that the right direction to produce new performant and sustainable adsorbent materials involves not only choosing wastes as starting materials, but also optimizing the consumption of electricity used for the production processes. The main results also highlight the need for precise data in LCA studies based on lab-scale processes and the potential for small-scale optimization to reduce the environmental impacts.

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