Indoor Air Pollution in Ghana

Overview

In this project, I investigate indoor fine particulate matter and nitrogen dioxide through direct air quality monitoring and develop a method to assess household-level factors that contribute to indoor air pollution in homes in Accra, Ghana.

Background

Introduction to Biomass Burning
Over 50% of the global population (approximately 3 billion individuals) relies on solid biomass fuels, such as wood, coal, crop residues, and animal dung, for cooking and heating, primarily in the developing world.

Air Pollution from Biomass Fuel Burning
Incomplete combustion of these biomass fuels indoors due to open fires or inefficient appliances leads to high levels of toxic pollutants such as fine particulate matter (PM2.5), carbon monoxide (CO), sulfur dioxide (SO2), oxides of nitrogen (NOx), and volatile organic compounds (VOCs) which are all considered household air pollutants (HAPs).

Air Pollution and Community Risks
HAPs can contribute to economic risks and health outcomes such as respiratory and cardiovascular ailments and premature mortality. Air pollution not only impacts human health but also has associated environmental and ecosystem impacts; therefore, it is vital to implement effective air quality management to mitigate air pollution. Few studies have been conducted to understand the problem of indoor air pollution in Ghana, where most studies used fuel usage, stove type, or smoke exposure as measures of pollutant exposure.

Collaborations
Air Quality Research team at the University of Ghana

Methodology

I conducted a field study to measure exposure to indoor fine particulate matter and nitrogen dioxide for homes in the Accra Metropolitan region from July to November 2024. I, monitored air pollution for a one-week period in the living and kitchen areas of 55 households.

Recruitment
Households were recruited through women participating in an ongoing birth cohort study in Accra.

Questionnaire
I administered a questionnaire for all homes, which consists of a survey and a daily cooking activity log. The questionnaire collected household data on cooking activity, access to appliances, household demographics, and other important data that could be related to indoor air pollution.

Statistical Analysis
I used multiple regression modeling to understand the main household factors that are associated with indoor PM2.5.