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Integration of membrane processes for the recovery and separation of polyphenols from winery and olive mill wastes using green solvent-based processing

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Winery and olive mill industries generate large amounts of wastes causing important environmental problems. The main aim of this work is the evaluation of different membrane separation processes like microfiltration, ultrafiltration, nanofiltration, and reverse osmosis for the recovery of polyphenols from winery and olive mill wastes in aqueous solutions. Membrane processes were tested separately in a closed-loop system, and by an integration in a concentration mode sequential design (open-loop). Feed flow rate was varied from 1 to 10 mL min-1, and permeate samples were taken in order to measure the polyphenols concentration. The separation and concentration efficiency were evaluated in terms of total polyphenol content, and by polyphenols families (hydroxybenzoic acids (HB), hydroxycinnamic acids (HC), and flavonoids (F)), using high performance liquid chromatography. Results showed that MF and UF membranes removed suspended solids and colloids from the extracts. NF was useful for polyphenols separation (HB rejections were lower than for HC and F: HB rejections of 50 and 63% for lees filters and olive pomace extracts, respectively), and RO membranes were able to concentrate polyphenols streams (86 and 95% rejection from lees filters and olive pomace, respectively). Membranes sequential designs for lees filters and olive pomace extracts, using a selective membrane train composed by UF, NF and RO membranes, were able to obtain polyphenol rich streams and high-quality water streams for reuse purposes.

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Journal of Environmental Management, 2022, vol. 307, p. 114555

# metadata.dc.rights[].value
cc-by-nc-nd (c) Tapia-Quirós et al., 2022

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Articles publicats en revistes  (Enginyeria Química i Química Analítica)

# metadata.dc.title[].value
Integration of membrane processes for the recovery and separation of polyphenols from winery and olive mill wastes using green solvent-based processing