AI Article Synopsis

  • The research aims to optimize a green microfiltration (MF) procedure for recovering valuable antioxidant compounds from olive oil washing wastewater, aligning with Circular Economy principles.
  • Key operational factors affecting the MF process were analyzed using statistical methods, achieving optimal flow rates and conditions that support both efficiency and sustainability.
  • The final results indicated a significant recovery of antioxidant compounds while minimizing energy consumption, demonstrating the process's potential for environmentally friendly wastewater treatment in the olive oil industry.

Article Abstract

This research is focused on modelling and optimization of the performance of a 'green procedure' based on microfiltration (MF) technology, for recovery of high added-value antioxidant compounds (TACs) from two-phase olive-oil washing wastewater (OOWW) and its treatment. Concern of olive oil industry to improve the production process in line with Circular Economy is vital to make it respectful with the environment including the management of the generated effluents. Key operational factors of the MF process were studied, modelled and optimized by multifactorial statistical analysis. Box-Behnken design was implemented and data analyzed by ANOVA and interpreted by RSM methodology. MF flux was ulteriorly modelled by a second-grade quadratic fitting equation comprising the significant operating variables, being them pressure and tangential velocity. Optimized flow achieved 10962.4 L/hm at 8.5 bar, 4.2 L/min tangential velocity, ambient temperature (25 °C) and raw pH (5.13). Finally, multiple-response permitted to optimize up to 67% TSS rejection and minimum rejection of TACs of 22.9%, upon 3.57 bar, 4.2 m/s, 23.4 °C and effluent pH of 5.1, meaning the recovery of 77.1% of TACs from OOWW in the permeate stream, up to 1207.1 mg/L. Results show that the proposed process allows a reduction in energy consumption by using the raw effluent with unmodified pH and ambient temperature.

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Source
http://dx.doi.org/10.1016/j.jenvman.2022.115227DOI Listing

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