Determinants of Solid Fuel Use and Emission Risks among Households: Insights from Limpopo, South Africa.

Rebecca O Adeeyo, Joshua N Edokpayi, Tom E Volenzo, John O Odiyo, Stuart J Piketh
Author Information
  1. Rebecca O Adeeyo: Environmental Science Unit, Faculty of Science, Engineering and Agriculture, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa.
  2. Joshua N Edokpayi: Department of Earth Sciences, Faculty of Science, Engineering and Agriculture, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa. ORCID
  3. Tom E Volenzo: Department of Earth Sciences, Faculty of Science, Engineering and Agriculture, University of Venda, Private Bag X5050, Thohoyandou 0950, South Africa. ORCID
  4. John O Odiyo: Office of the DVC-Research, Innovation, Commercialisation, and Internationalisation (RICI), Vaal University of Technology, Vanderbijlpark 1900, South Africa.
  5. Stuart J Piketh: School of Geo and Spatial Sciences, North-West University, Potchefstroom 2520, South Africa. ORCID

Abstract

Emissions from residential solid fuels reduce ambient air quality and cause indoor air pollution resulting in adverse human health. The traditional solid fuels used for cooking include coal, straws, dung, and wood, with the latter identified as the prevalent energy source in developing countries. Emissions from such fuel sources appear to be significant hazards and risk factors for asthma and other respiratory diseases. This study aimed at reporting factors influencing the choice of dominant solid fuel for cooking and determine the emission risk from such solid fuel in three villages of Phalaborwa, Limpopo province, South Africa. The study used descriptive analysis to show the relationship between the socio-economic variables and the choice of cooking fuel at the household level. Multiple correspondence analysis (MCA) was used further to detect and represent underlying structures in the choice of dominant fuels. MCA shows the diversity and existing relationship of how variables are related analytically and graphically. Generalised linear logistic weight estimation procedure (WLS) was also used to investigate the factors influencing choice of fuel used and the inherent emission risks. In the three villages, wood was the prevalent cooking fuel with 76.8% of participant households using it during the summer and winter seasons. Variables such as low monthly income, level of education, and system of burning are revealed as strong predictors of wood fuel usage. Moreover, income, water heating energy, types of wood, and number of cooking hours are significant ( ≤ 0.05) in influencing emission from wood fuel in the community. A notable conclusion is that variables such as income, education status and system of burning are determinants of wood fuel usage in the three villages, while income, water heating energy, types of wood and number of hours influence vulnerability to household emission and possible health risks in the use of solid energy sources.

Keywords

References

  1. Environ Sci Pollut Res Int. 2018 Sep;25(25):24778-24786 [PMID: 29926328]
  2. Inhal Toxicol. 2007 Jan;19(1):67-106 [PMID: 17127644]
  3. S Afr Med J. 2007 Aug;97(8 Pt 2):764-71 [PMID: 17952235]
  4. Environ Health Perspect. 2006 Mar;114(3):373-8 [PMID: 16507460]
  5. Environ Res. 2017 Jul;156:47-56 [PMID: 28319817]
  6. Inhal Toxicol. 2018 Aug - Aug;30(9-10):327-334 [PMID: 30516398]
  7. Environ Res. 2018 Oct;166:112-116 [PMID: 29885612]
  8. Sao Paulo Med J. 2013;131(1):27-34 [PMID: 23538592]
  9. PLoS One. 2016 Aug 10;11(8):e0160804 [PMID: 27508389]
  10. Eur Respir J. 2006 Mar;27(3):542-6 [PMID: 16507854]
  11. Eur Respir J. 2015 Dec;46(6):1577-88 [PMID: 26405285]
  12. Environ Health Perspect. 2001 Jun;109 Suppl 3:389-94 [PMID: 11427388]
  13. BMC Public Health. 2014 Oct 31;14:1122 [PMID: 25358245]
  14. Environ Health Perspect. 2002 Jan;110(1):109-14 [PMID: 11781172]
  15. J Alzheimers Dis. 2019;68(4):1371-1390 [PMID: 31006689]
  16. Part Fibre Toxicol. 2009 Nov 06;6:29 [PMID: 19891791]
  17. Indoor Air. 2018 Mar;28(2):228-237 [PMID: 28983961]
  18. PLoS One. 2016 Jul 07;11(7):e0157984 [PMID: 27389398]
  19. Oecologia. 2014 Jul;175(3):1029-40 [PMID: 24805202]
  20. Environ Res. 2021 Mar;194:110683 [PMID: 33450236]
  21. Environ Sci Pollut Res Int. 2018 May;25(13):12299-12302 [PMID: 29627958]
  22. Thorax. 2000 Jun;55(6):518-32 [PMID: 10817802]
  23. Environ Sci Technol. 2002 Mar 1;36(5):833-9 [PMID: 11918004]
  24. Cien Saude Colet. 2019 Aug 05;24(8):3079-3088 [PMID: 31389554]
  25. Ann Glob Health. 2020 Mar 20;86(1):32 [PMID: 32211302]
  26. Int J Environ Res Public Health. 2012 Jun;9(6):2252-65 [PMID: 22829802]

Grants

  1. E349/Eskom colloborations

Word Cloud

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