Food Wastes As Adsorbent Materials for Water Decontamination: The Use of Kiwi Peels To Remove Emerging Pollutants and Textile Dyes
Bibliographic record
Abstract
The high rate of resource consumption and large amounts of produced wastes have been reported to drive towards an ecological collapse. Interestingly, a circular economy approach could reduce this environmental concern avoiding the waste management, and all outputs (products, by-products, wastes) would become inputs (material and energy) to other processes. When the model is based on the production of renewable biological resources, and these resources are converted into value added products, the concept of bio-circular economy take place. [1,2] It means to develop an economy plan based on the production from biological resources with a sustainable transformation of wastes, offering alternatives to their dumping, burning, composting etc. About this purpose, the use of fruit Peels as food/agricultural wastes have attained interest, as adsorbent materials for water purification, avoiding their disposal according to the principles of Green Chemistry and Sustainable Development.[3] For this purpose, this work proposes, among wastes, the use of Kiwi Peels to remove emerging pollutants (not regulated substances that could affect both human health, and the whole environment, causing severe problems [1,2]) and textile dyes from water. Indeed, among the explored wastes, Kiwi Peels removed the largest number of contaminants. Kiwi Peels were characterized by adopting in synergy FTIR-ATR, TG and SEM analyses, before and after their use, and as result they are proposed as recyclable adsorbent. To infer information about the behaviour of Kiwi Peels during water treatments, model contaminants were selected and investigated (Ciprofloxacin, CIP, and Direct Blue 78, DB); so, the role of several parameters affecting the process was assessed. The thermodynamic, the adsorption isotherms and kinetics were also studied. Finally, to extend the lifetime of Kiwi Peels, desorption experiments were carried out by using hot water or salt solutions. 10 cycles of adsorption/desorption were studied, evidencing the recycling of both pollutants and Kiwi Peels (Figure 1). Moreover, another aspect investigated in this work regards the possibility of using Advance Oxidation Processes (AOPs) to induce the pollutants solid-state photodegradation as an alternative approach for adsorbent regeneration. Also, in this case, FTIR-ATR, SEM, and TG analyses were used in synergy for investigating the adsorbent features after the AOPs’ application. If, on the one hand, the SEM and FTIR-ATR results revealed the absence of important post-treatment changes, on the other hand, the TGA suggested some modifications. Finally, mixtures of pollutants were also studied and in the case of dyes, dyeing experiments were also performed, evidencing the dye ability to colour cotton fibers after the colour recycling (Figure 2). Particularly, the experiments of dyeing were executed during the Kiwi Peels desorption in hot water at 323 K, without further additives
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".