Characterizing indoor air quality and identifying factors influencing air quality at home microenvironment in Dhaka city

In low- and middle-income countries, indoor air pollution stands as a significant contributor to morbidity and mortality, prompting research into the factors influencing exposure at home in urban environments. Thus, this study was designed to investigate the indoor air quality and identifying factors influencing indoor air quality which help in targeting intervention to reduce indoor home air quality. The study conducted in Dhaka city involved 43 homes, where continuous monitoring of PM 2.5 concentration was carried out over a 24-hour period. Various factors related to home characteristics (i.e., home area and cooking fuel type), ventilation practices (i.e., duration of window opening), and indoor activities (i.e., cooking frequency, daily average cooking duration per meal, cleaning, smoking and use of mosquito coil and spray) were assessed to explore their impact on indoor air quality. Through the multiple linear regression model, the relationship between the factors and indoor pollutant concentrations was analyzed. The average PM 2.5 concentration recorded in this investigation was five time higher in comparison to the World Health Organization's (WHO) 24-hour guideline level for ambient air pollution. Four factors including outdoor air, home area, cooking duration and cleaning frequency were found to be significantly linked to indoor concentrations, collectively explaining 64% of the variability in indoor PM 2.5 levels. Outdoor air infiltration emerged as the most influential predictor of indoor levels, contributing significantly to indoor concentrations. The identified factors could assist in targeting interventions to reduce microenvironmental PM 2.5 concentration at home. • Indoor PM 2.5 concentration was quantified in 43 homes. • Average PM 2.5 concentration was five times higher than WHO's guideline for ambient air pollution. • Outdoor PM 2.5 infiltration majorly contributes to indoor PM 2.5 levels. • Model-identified factors may support targeting intervention strategy.