English
español
Please use this identifier to cite or link to this item:
http://hdl.handle.net/10261/215825
Share/Impact:
Statistics |
![]() ![]() |
|
Visualizar otros formatos: MARC | Dublin Core | RDF | ORE | MODS | METS | DIDL | DATACITE | ||
|
Title: | Impact of soft hydrothermal pre-treatments on the olive mill solid waste characteristics and its subsequent anaerobic digestion |
Authors: | Fernández-Rodríguez, M. J.; Lama-Calvente, D. de la; Jiménez-Rodríguez, A.; Pino-Mejías, R.; Borja Padilla, Rafael ![]() ![]() |
Keywords: | Autoclaving Soluble chemical oxygen demand Polysaccharides Phenol inhibition Kinetic study |
Issue Date: | 4-Jun-2020 |
Publisher: | Springer |
Citation: | Biomass Conversion and Biorefinery (2020) |
Abstract: | The aim of this study was to investigate the effect of a soft hydrothermal pre-treatment (SHP) on olive mill solid waste (OMSW) and its subsequent anaerobic digestion (AD). OMSW was pre-treated in an autoclave at temperatures of 121 °C and 133 °C and excess pressures of 1.1 and 2.1 bars, respectively at heating times of 15, 20, and 30 min. The digestibility of pre-treated and untreated OMSW was determined in terms of methane potential through using biochemical methane potentials tests (BMP). Important solubilization of high-valuable compounds such as hydroxytyrosol and 3,4-dihydroxyphenylglycol was observed after pre-treatments. SHP showed a significant reduction in fiber length and width (p < 0.05). A higher polysaccharides solubilization was observed in treatment at 121 °C compared with that observed at 133 °C. SHP carried out at 121 °C, 1.1 bar (30 min) (pre-treatment A1), allowed obtaining the highest methane yield (380 ± 5 mL CH4/g VS), which was 12.3% higher than that obtained for untreated OMSW. Pearson correlation (PEC) and principal component analysis (PCA) were carried out. PEC showed a positive correlation with phenol vanillic acid and PCA grouped pre-treatment A1 with polysaccharides solubilization. The influence of the SHP conditions on the AD of OMSW was assessed through the monitoring of process performance and calculation of kinetic parameters by using the transference function model. |
Description: | 4 Figuras.-- 5 Tablas |
Publisher version (URL): | http://dx.doi.org/10.1007/s13399-020-00759-1 |
URI: | http://hdl.handle.net/10261/215825 |
ISSN: | 2190-6815 |
E-ISSN: | 2190-6823 |
Appears in Collections: | (IG) Artículos |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
PostP_2020_BCB_Impact.pdf | 1,19 MB | Adobe PDF | ![]() View/Open |
Show full item record
Review this work
Review this work
WARNING: Items in Digital.CSIC are protected by copyright, with all rights reserved, unless otherwise indicated.