Open AccessEffect of Autoclave Pretreatment on Biogas Production through Anaerobic Digestion of Green Algae
Author(s) -
Renjie Feng,
QiaoYan Li,
Asad A. Zaidi,
Hao Peng,
Yue Shi
Publication year - 2021
Publication title -
periodica polytechnica. chemical engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.322
H-Index - 19
eISSN - 1587-3765
pISSN - 0324-5853
DOI - 10.3311/ppch.18064
Subject(s) - anaerobic digestion , pulp and paper industry , biogas , biomass (ecology) , raw material , bioenergy , gompertz function , autoclave , chemistry , environmental science , biodegradation , biofuel , food science , waste management , microbiology and biotechnology , mathematics , biology , agronomy , methane , engineering , statistics , organic chemistry
Anaerobic Digestion (AD) is one of the most widely used methods in the field of sustainable bioenergy production from various feedstock. One such feedstock is algae waste which has become an increasingly serious environmental problem. AD of algal biomass is hindered by the presence of resistant cell walls; hence a pretreatment step is usually required to decompose the cell wall structure. This study uses green algae (Enteromorpha) and anaerobic sludge as raw materials to explore the impact of autoclave (AC) pretreatment on biogas production. AC pretreatment was performed at 120 °C and 80 °C. The cumulative biogas production of the 120 °C AC pretreatment, 80 °C AC pretreatment and control group were 600 mL, 450 mL and 400 mL, respectively. The results showed that AC pretreatment improved the biodegradability of biomass as 120 °C AC pretreatment group achieved higher degradation rate of cells (95.99 %). The energy evaluation showed that the net energy ratio of the 120 °C AC pretreatment group was 1.07, indicating high overall energy gain via AD process. The experimental data is further modeled by using Modified Gompertz Model (MGM) and Logistic Function Model (LFM). To check the applicability of better model for this AD process, an Akaike Information Criteria (AIC) test was performed. AIC showed that the MGM is basically consistent with the experimental data and more reliable for prediction modeling of Enteromorpha AD.