Biomass fuel use and indoor air pollution in homes in Malawi

Occup Environ Med. 2009 Nov;66(11):777-83. doi: 10.1136/oem.2008.045013. Epub 2009 Aug 10.

Abstract

Background: Air pollution from biomass fuels in Africa is a significant cause of mortality and morbidity both in adults and children. The work describes the nature and quantity of smoke exposure from biomass fuel in Malawian homes.

Methods: Markers of indoor air quality were measured in 62 homes (31 rural and 31 urban) over a typical 24 h period. Four different devices were used (one gravimetric device, two photometric devices and a carbon monoxide (HOBO) monitor. Gravimetric samples were analysed for transition metal content. Data on cooking and lighting fuel type together with information on indicators of socioeconomic status were collected by questionnaire.

Results: Respirable dust levels in both the urban and rural environment were high with the mean (SD) 24 h average levels being 226 microg/m(3) (206 microg/m(3)). Data from real-time instruments indicated respirable dust concentrations were >250 microg/m(3) for >1 h per day in 52% of rural homes and 17% of urban homes. Average carbon monoxide levels were significantly higher in urban compared with rural homes (6.14 ppm vs 1.87 ppm; p<0.001). The transition metal content of the smoke was low, with no significant difference found between urban and rural homes.

Conclusions: Indoor air pollution levels in Malawian homes are high. Further investigation is justified because the levels that we have demonstrated are hazardous and are likely to be damaging to health. Interventions should be sought to reduce exposure to concentrations less harmful to health.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Air Pollution, Indoor / analysis*
  • Biomass*
  • Developing Countries
  • Dust / analysis
  • Energy-Generating Resources
  • Environmental Monitoring / instrumentation
  • Environmental Monitoring / methods
  • Housing*
  • Humans
  • Malawi
  • Particulate Matter / analysis
  • Rural Health / statistics & numerical data
  • Smoke / analysis
  • Urban Health / statistics & numerical data

Substances

  • Dust
  • Particulate Matter
  • Smoke