Woman cooking on a mud stove.

Woman cooking on a mud stove in Ghana. Exposure to particulate matter is greater when cooking indoors. Photo: Kwameghana / CC BY-SA

The health burden from exposure to fine particulate matter (PM2.5) is disproportionately concentrated in low- and middle-income countries. To evaluate strategies to reduce PM2.5 exposure, the contribution of different sources, both indoor and outdoor, to overall personal PM2.5 exposure needs to be identified. Despite this, exposure to PM2.5 from indoor and outdoor origin are most often considered separately.

This work presents the first application of a microenvironmental modelling approach in a sub-Saharan African city (Accra, Ghana) to estimate personal PM2.5 exposures to population groups disaggregated by gender and age and identify the key factors determining these exposures. Time-activity profiles for each population group were combined with PM2.5 concentrations estimated for three home microenvironments using a dynamic microenvironmental model, INDAIR, and for work, school and transport microenvironments using a steady-state model to estimate personal PM2.5 exposures.

In Accra, cooking using charcoal, compared to liquified petroleum gas (LPG), was estimated to result in substantially higher home PM2.5 concentrations, and higher personal PM2.5 exposure for the female adult and child population groups, compared with the male population groups. In households cooking using charcoal, more than 60% of total personal PM2.5 exposure was estimated to be due to residential cooking for the child and female population groups, which reduces to less than 10% when LPG was used for cooking, with the remaining contribution from PM2.5 of outdoor origin. The key parameters to which personal PM2.5 exposure estimates are sensitive are the air exchange rate between indoor and outdoors, the kitchen volume, and charcoal emission rates.

This study therefore informs on the additional data collection and measurements that could substantially enhance the parameterization of micro-environmental models for application in low- and middle-income countries where a limited number of studies have been conducted, and improve their utility in assessing strategies to reduce personal air pollution exposure of different population groups.