Effect of organic loading rate on biogas yields of pig slurry in a continuously stirred tank reactor at mesophilic temperature

A. O. Adebayo, S. O. Jekayinfa, N. A. Ahmed, O. Ogunkunle

Research output: Contribution to journalConference articlepeer-review

8 Citations (Scopus)

Abstract

Renewable energy appears to be a way out of the associated challenges of the conventional sources of energy. One of these renewable sources is biogas. Biogas is the gas produced when anaerobic bacteria act on organic matters in the absence of oxygen. Anaerobic digestion has been considered as waste-to-energy technology. In this work, attempt was made to determine the effect of organic Loading Rate (OLR) on biogas production potential of pig slurry using a Continuously-Stirred Tank Reactor (CSTR) operated at mesophilic temperature (37oC). A 12-litre capacity CSTR was loaded with 8 litres pre-cultivated sludge as inoculum, leaving a free space for gas production. The loading of the calculated amount of pig manure into the reactor was commenced at a LR of 1.5goTS/l.d and was increased weekly by 0.5 goTS/l.d until an OLR of 5.0 goTS/l.d was reached. The biogas yields at OLR of 1.5, 2.0, 2.5, 3.0, 3.5, 4.0, 4.5 and 5.0 goTS/l.d were 0.255, 0.190, 0.170, 0.180, 0.170, 0.140, 0.120 and 0.140 m3/kgODM, respectively, with corresponding methane yields of 0.153, 0.12, 0.11, 0.11,0.11, 0.09, 0.08, and 0.09 lCH4/goDM. Biogas yield of 0.255m3/kgoDM was recorded as the highest at an OLR of 1.5 goTS/l.d. Summarily, pig manure was found to be best digested at OLR of 1.5 goTS/l.d in a CSTR at mesophilic temperature.

Original languageEnglish
Pages (from-to)337-342
Number of pages6
JournalProcedia Manufacturing
Volume35
DOIs
Publication statusPublished - 2019
Event2nd International Conference on Sustainable Materials Processing and Manufacturing, SMPM 2019 - Sun City, South Africa
Duration: 8 Mar 201910 Mar 2019

Keywords

  • Biogas yields
  • CSTR
  • Loading Rate
  • Pig manure
  • Renewable energy

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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