Effect of Microwave Pretreatment on BMP of Decanter Cake from Palm Oil Mill Factory
Thaniya Kaosol1 & Worawuth Rungarunanotai1 Show affiliations
- Environmental Engineering Program, Department of Civil Engineering, Faculty of Engineering, Prince of Songkla University, Songkhla, Thailand
American Journal of Applied Sciences, Volume 13, Issue 5, pp. 609–617 · doi.org/10.3844/ajassp.2016.609.617
Abstract
Anaerobic digestion is an effective method for treating decanter cake in the biogas production. Decanter cake usage is limited by its slow fiber degradation for anaerobic digestion process. The aim of this study is to study the possibility of using microwave pretreatment to enhance decanter cake digestibility. The power and heating time are the parameters that influence the biogas production and methane yield. The Biochemical Methane Potential (BMP) tests are used in this study to find the optimization setting of a microwave pretreatment for decanter cake solubilization and anaerobic digestibility. The results show that the microwave pretreatment provides a better performance in terms of COD solubilization and anaerobic digestibility. The increasing power and heating time can improve the biogas production and methane yield for microwave pretreated decanter cake under anaerobic digestion process. Finally, the optimum power and heating time used in the microwave pretreatment, found in this study, is 160 watts and 8 min for methane yield under the anaerobic digestion process. The highest methane yield is 309.9 mL CH4/g COD removed. The microwave pretreated decanter cake at 160 watts of power and 8 min of heating time can improve the methane yield with an improvement of 24.6% in comparison with the non-microwave pretreated decanter cake. It can be concluded that the microwave pretreatment of decanter cake from palm oil mill factory could be the rapid and environmental method for biogas production enhancement.
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Kaosol, T. & Rungarunanotai, W. (2016). Effect of Microwave Pretreatment on BMP of Decanter Cake from Palm Oil Mill Factory. American Journal of Applied Sciences, 13(5), 609–617. https://doi.org/10.3844/ajassp.2016.609.617
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