Up-cycling tomato pomace by thermochemical liquefaction – A response surface methodology assessment. (January 2022)

• Record Type: Journal Article
• Authors: Vidal, Margarida; Bastos, David; Silva, Luciana; Gaspar, Daniela; Paulo, Ivo; Matos, Sandro; Vieira, Salomé; Bordado, João Moura; Galhano dos Santos, Rui
• Is Part Of: Biomass and bioenergy. Volume 156(2022)
• Publication Date: 2022-01
• Subjects: Tomato pomace -- Liquefaction -- RSM -- Model -- Bio-oil; Biomass energy -- Periodicals; Biomass -- Periodicals; Energy-Generating Resources -- Periodicals; Bioénergie -- Périodiques; 333.9539
• DOI: 10.1016/j.biombioe.2021.106324
• Languages: English
• ISSNs: 0961-9534

Abstract

Abstract: Tomato pomace is a waste from the tomato processing industry, for which there are few solutions to upcycle it. The tomato pomace thermochemical liquefaction was modelated using response surface methodology, combined with central composite face-centred (CCF), obtaining a model with a high adjusted R-squared (0.97) and a very good p-value (less than 0.001). The liquefaction process was conducted for 1–5 h at temperatures ranging from 100 to 160 °C. The process was supported by an acid catalyst, p-toluene sulfonic acid, with concentrations from 0.5 to 3% w/w. The model suggested that the highest conversions are reached at 160 °C, for a catalyst concentration from 2.5% to 3%, and for processes lasting more than 3 h. The bio-oil obtained was characterized by FTIR-ATR, elemental analysis, thermogravimetric analysis, and the higher heating value was computed. The bio-oil' HHV was estimated at 32.32 MJ/kg, 1.42 times higher than that of tomato pomace. The study indicates that thermochemical liquefaction can be a process to value the tomato pomace, turning it into bio-fuel or value-added chemicals. Graphical abstract: Image 1 Highlights: The conversion of tomato pomace into bio-oil was accomplished. The bio-oil was obtained via thermochemical liquefaction with high conversion rates. The process was modelated using Response Surface Methodology for process optimization.