Emissions Comparison of loose biomass briquettes with cow dung and cactus binders

Reuben Shuma, Daniel M. Madyira

Research output: Contribution to journalConference articlepeer-review

15 Citations (Scopus)

Abstract

Fossil fuel combustion is related to the increased global warming challenge. Coal was identified first as a fossil fuel historically in China dating back to 4000 before Christ (BC). Since then, 96 % of energy extraction was through coal until 2000 when other energy sources became more dominant. Coal dependency has since declined by 30 % but remains the most deployed fuel today. To mitigate the negative effects of continued coal combustion, the need has been identified to introduce more carbon neutral fuels such as biomass. Biomass is the only energy source that has enough carbon reserves to replace coal today. Biomass is carbon neutral due to its renewable nature hence offers significant environmental benefits. The use of inorganic fertilizers in the production of some loose agricultural and forestry residues that can be harnessed for energy poses pollution challenges. This work conducts a comparative study of the combustion and emissions behaviour of loose biomass briquettes produced from agricultural and forestry residues bonded by cow dung and cactus. The aim is to characterise emission content, particulate matters and the gases emitted during combustion. This provides a basis of comparison with coal-based emissions. Cactus bonded briquettes were found to have low emissions on CO2, CO NOx and SO2 and cow dung bonded briquettes were found to have higher emissions compared to cactus briquettes.

Original languageEnglish
Pages (from-to)130-136
Number of pages7
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

  • Biomass
  • Carbon
  • Emission
  • Fossil fuels
  • Particulate matter

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence

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