Volatile fatty acid production from saline cooked mussel processing wastewater at low pH

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The production of VFA using as substrate the wastewater produced in a cooked mussel processing factory, containing large COD (13.7 ± 3.2 g COD/L), salt concentrations (21.8 ± 2.8 g NaCl/L) and characterized by low pH (4.6 ± 0.6) was evaluated. This wastewater was fed to a 5-L completely stirred tank reactor operated in continuous mode. The conversion efficiency of its COD content into volatile fatty acids (VFA) was evaluated. The maximum acidification of 43% (total VFA on soluble COD basis) was obtained when an organic loading rate of 2.5 ± 0.4 g COD/(L·d) was applied to the reactor and corresponded to a VFA volumetric productivity of 0.72 ± 0.07 g CODVFA/(L·d). Under steady-state conditions, the obtained mixture of VFA was composed by 80:18:2 as acetic:propionic:butyric acids (percentage of VFA on soluble COD basis). Carbohydrates were degraded up to 96% while protein fermentation did not take place, probably due to the low pH value, limiting the maximum acidification of the wastewater. Batch experiments showed that the increase of the pH from 4.2 to 4.9 by the addition of NaHCO3 resulted in the improvement of the acidification and changed the VFA mixture composition. Thus, this study demonstrates the opportunity of using complex substrates, as cooked mussel processing wastewater, to produce rich-VFA streams under unfavourable operational conditions, such as high salinity and low pH

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Fra-Vázquez, A., Pedrouso, A., Val del Rio, A., & Mosquera-Corral, A. (2020). Volatile fatty acid production from saline cooked mussel processing wastewater at low pH. The Science of the Total Environment, 732, 139337. doi:10.1016/j.scitotenv.2020.139337

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This research was supported by the Spanish Government (AEI) through the FISHPOL (CTQ2014-55021-R) and TREASURE (CTQ2017-83225-C2-1-R) projects. The authors belong to the Galician Competitive Research Group GRC ED431C 2017/29 and to the CRETUS Strategic Partnership (ED431E 2018/01). All these programs are co-funded by the FEDER (EU). Special thanks to Dr. Thelmo A. Lú-Chau for his contribution to the statistical analysis of data.

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