@misc{10481/91953,
year = {2024},
month = {2},
url = {https://hdl.handle.net/10481/91953},
abstract = {Nowadays, the environmental challenges associated with plastics are becoming increasingly
prominent, making the exploitation of alternatives to landfill disposal a pressing concern. Particularly,
polyvinyl chloride (PVC), characterized by its high chlorine content, poses a major environmental
risk during degradation. Furthermore, PVC recycling and recovery present considerable challenges.
This study aims to optimize the PVC pyrolysis valorization process to produce effective adsorbents
for removing contaminants from gaseous effluents, especially CO2. For this purpose, PVC waste
was pyrolyzed under varied conditions, and the resulting solid fraction was subjected to a series of
chemical and physical activations by means of hydroxides (NaOH and KOH) and nitrogen. Characterization
of the PVC-based activated carbons was carried out using surface morphology (SEM), N2
adsorption/desorption, elemental analysis, and FTIR, and their capacity to capture CO2 was assessed.
Finally, neuro-fuzzy models were developed for the optimization of the valorization technique.
The resulting activated carbons exhibited excellent CO2 adsorption capabilities, particularly those
activated with KOH. Optimal activation conditions include activations at 840 ºC with NaOH at a
ratio of 0.66 and at 760 ºC using either NaOH or KOH with ratios below 0.4. Activations under these
experimental conditions resulted in a significant increase in the adsorption capacity, of up to 25%, in
the resulting samples.},
organization = {Project PDC2022-133808-I00, funded by MCIN/AEI/10.13039/501100011033 and the European Union “NextGeneration EU”/PRTR},
organization = {Juan de la Cierva Fellowship (FJC2021-048044-I, funded by MCIN/AEI/10.13039/501100011033 and the EU “NextGenerationEU/PRTR”)},
publisher = {MDPI},
keywords = {PVC},
keywords = {CO2 capture},
keywords = {Activated carbon},
title = {Recycling PVC Waste into CO2 Adsorbents: Optimizing Pyrolysis Valorization with Neuro-Fuzzy Models},
doi = {10.3390/pr12030431},
author = {Jiménez García, Emilia A. and Pérez Huertas, Salvador and Pérez Muñoz, Antonio and Calero De Hoces, Francisca Mónica and Blázquez García, Gabriel},
}