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Abstract

Anaerobic digestion (AD) is an adequate alternative to treat wastewater generated from fruit and vegetable processing (FVWW); likewise, in recent years, artificial wetlands (AWs) have been applied as a post-treatment process for anaerobi-cally pre-treated wastewater. The objective of this work was to design a sustainable treatment system for FVWW composed of upflow anaerobic reactors (UASB) with phase separation and an AW system that receive the anaerobically pretreated effluent. Using the design methodologies for the UASB reactors and artificial wetlands with sub-surface flow (AW-SSF), the parameters of the combined AD-AW system that treat a wastewater flow of 300 m3∙d–1 were calculated. The UASB acidogenic system was adjusted to a hydraulic retention time (HRT) of 10 h and organic loading rate (OLR) of 13.84 kg COD m–3∙d–1; meanwhile, the methanogenic and cascade UASB reactors with OLRs of 10.0 and 3.0 kg COD m3∙d–1, and HRTs of 11 and 10 h, respectively, achieve a high COD removal efficiency (above 94%), and an overall biogas production rate of 1.53 m3 of biogas per m3 of reactor capacity per day. According to the results obtained with the theoretical design, anaerobic-wetland combined system achieves an overall efficiency greater than 98%. The wastewater treated by the pro-posed system will allow the reuse of 30% of the water used in the washing of fruits and vegetables.

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Authors and Affiliations

Yans Guardia-Puebla
ORCID: ORCID
Edilberto Llanes-Cedeño
ORCID: ORCID
Suyén Rodríguez-Pérez
Quirino Arias-Cedeño
ORCID: ORCID
Víctor Sánchez-Girón
ORCID: ORCID
Gert Morscheck
Bettina Eichler-Löbermann
ORCID: ORCID
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Abstract

A multiple regression model approach was developed to estimate buffering indices, as well as biogas and methane productions in an upflow anaerobic sludge blanket (UASB) reactor treating coffee wet wastewater. Five input variables measured (pH, alkalinity, outlet VFA concentration, and total and soluble COD removal) were selected to develop the best models to identify their importance on methanation. Optimal regression models were selected based on four statistical performance criteria, viz. Mallow’s Cp statistic (Cp), Akaike information criterion ( AIC), Hannan– Quinn criterion ( HQC), and Schwarz–Bayesian information criterion ( SBIC). The performance of the models selected were assessed through several descriptive statistics such as measure of goodness-of-fit test (coefficient of multiple determination, R2; adjusted coefficient of multiple determination, Adj-R2; standard error of estimation, SEE; and Durbin–Watson statistic, DWS), and statistics on the prediction errors (mean squared error, MSE; mean absolute error, MAE; mean absolute percentage error, MAPE; mean error, ME and mean percentage error, MPE). The estimated model reveals that buffering indices are strongly influenced by three variables (volatile fatty acids (VFA) concentration, soluble COD removal, and alkalinity); while, pH, VFA concentration and total COD removal were the most significant independent variables in biogas and methane production. The developed equation models obtained in this study, could be a powerful tool to predict the functionability and stability for the UASB system.
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Authors and Affiliations

Yans Guardia-Puebla
1
ORCID: ORCID
Edilberto Llanes-Cedeño
2
ORCID: ORCID
Ana Velia Domínguez-León
3
Quirino Arias-Cedeño
1
ORCID: ORCID
Víctor Sánchez-Girón
4
ORCID: ORCID
Gert Morscheck
5
Bettina Eichler-Löbermann
5
ORCID: ORCID

  1. University of Granma, Study Center for Applied Chemistry, Cuba
  2. Faculty of Architecture and Engineering, International SEK University, Quito, Ecuador
  3. Language Center, University of Granma, Cuba
  4. College of Agricultural, Food and Biosystems Engineering, Technical University of Madrid, Spain
  5. Faculty of Agronomy and Crop Science, University of Rostock, Germany

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