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Conference paper

Biogas production via microalgal biomass anaerobic fermentation – Experimental and modelling approach: Effect of metal nanoparticles

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1College of Power and Energy Engineering, Harbin Engineering University, Harbin 150001, China

2Department of Mechanical Engineering, Faculty of Engineering, Islamic University of Madinah, Madinah, P.O. Box.170, Kingdome of Saudi Arabia

3Massachusetts Institute of Technology Portugal Program, Faculty of Engineering, University of Porto, Portugal

Published
28 February 2019
Pages
312-319
Received
28 February 2019
DOI
10.65582/set.2018.031
Access
Open access, © 2018 Copyright WSSET
Download PDF8 pages · 869 KB

Abstract

An interesting raw biomass, other than conventional organic wastes used for the production of bioenergy, is Aquatic Algal. An alternative process for collective bioenergy production and depollution is linking an anaerobic digester to a microalgal culture. The concerns about expansion in bioenergy sector during past decade have driven a number of scientists and researchers to pursue innovative solutions for its production. Nanotechnology is one of the emerging branches of science. It can be applied in bioenergy field for the purpose of feedstock modification and more efficient catalysis. This study investigates influence of metal nanoparticles (NPs) on biogas production from green microalgae Enteromorpha. The concentration of metallic NPs (Co and Ni) was 1mg/L. An anaerobic fermentation was carried out batch-wise with working volume, operating temperature, mixing rate and hydraulic retention time as 500ml, 37oC, 150rpm and 170 hours, respectively. The results showed that NPs has moderate positive influence in biogas production until 60 hours of retention time but significantly improve afterward. The cumulative biogas production by Control, Co NPs and Ni NPs was 488, 535 and 618 ml, respectively. The anaerobic digestion performance with NPs was mathematically evaluated by using modified Gompertz model and Logistic Function model. The kinetic parameters, such as the biogas production potential (Bp), the maximum biogas production rate (MBPR) and the biogas production delay time (BPDT) were calculated for each experimental case. The values of the performance indicators confirmed that both the models fitted with experimental data. Akaike Information Criterion (AIC) test was performed which ascertains that Logistic Function model has better predicting ability for microalgae biomass anaerobic fermentation.

Keywords. anaerobic digestion; biogas; green microalgae; kinetic models; nanoparticles (NPs)

© 2018 Copyright WSSET

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