Validation of wet chemistry method as alternative to gas chromatography for biogas methane content determination
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Keywords

anaerobic digestion
gas chromatography
linear regression
validation
wet chemistry

How to Cite

Ibrahim, T. H., Betiku, E., Solomon, B. O., Oyedele, J. O., Olaifa, G. O., & Adekunle, A. A. (2023). Validation of wet chemistry method as alternative to gas chromatography for biogas methane content determination. ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY AND ENVIRONMENT, 19(1), 23-32. Retrieved from https://www.azojete.com.ng/index.php/azojete/article/view/700

Abstract

Anaerobic digestion technology has the potential for simultaneous waste treatment and biogas generation. Its rate of dissemination and adoption in most developing countries has however, slowed down for many years partly due to inadequate research facilities such as advanced gas measuring equipment, and associated cost of analyses. This study, therefore, tested and validated the use of classical wet chemistry analysis method (CWCAM) as a readily accessible and cheaper alternative to gas chromatographic method (GCM), for determining the proportion of methane (CH4) in produced biogas. Biogas samples were simultaneously collected every week in 5 ml and 20 ml hypodermic syringes, from a digester in which cassava vinasse (CV) was being codigested with poultry droppings (PD), using ruminal fluids of cattle (RFC) as inoculum. While samples in 5ml syringes were analyzed using the GCM, the 20 ml samples were analyzed using the CWCAM, to determine the percentage of methane in the biogas samples collected each week. The corresponding volumes, corrected to standard temperature and pressure (STP) condition was then calculated. The results from both analytical methods were statistically analyzed and compared using the Data Analysis tool in Microsoft Office Excel. The difference in results from the two methods ranged from -3 to +2.9% with CWCAM giving slightly higher values of methane percentage. Overall, a relatively high coefficient of determination (R2 = 0.9728) and low standard error (SE = 1.4) of the regression equation between the two sets of results indicate that the two methods may be used interchangeably.

 

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