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In Sub-Saharan Africa, around 80% of residential energy demand is for cooking, with over 760 million people without access to clean cooking fuels and stoves. Particulate matter smaller than 2.5 microns (PM2.5) is a significant pollutant from biomass burning and is linked to respiratory and cardiovascular diseases, as well as adverse pregnancy outcomes. Energy poverty further reinforces gender disparities, keeps children from schools, causes environmental degradation, and interferes with social and economic development. Lack of access to and inadequate adoption of clean cooking stoves and fuels are key barriers to improved air quality. This paper presents a field experiment nested within a large-scale health efficacy trial. The aim of the experiment was to evaluate the effects of access to air quality data and dynamic feedback on indoor air pollution (IAP) and personal exposure. Ninety households in Rwanda were enrolled and provided with an air quality sensor and feedback device, which measured real-time indoor air quality as PM2.5 for sixteen weeks. After six weeks, PM2.5 levels were provided dynamically to households through a display and an auditory alarm. We examined the effects of receiving this feedback on IAP and personal exposure. While access to air quality data did not, in aggregate, improve PM2.5 levels, we did observe several promising correlations worthy of further investigation. The associations between personal exposure or rainfall and increased PM2.5 were reduced after households had access to air quality data. We hypothesized that the behavior changes required to observe these effects—opening doors and windows and moving away from cooking sources—are easy and immediate, in contrast to the costs and complex logistics of entirely eliminating biomass cooking. The types of behavior changes that would directly impact household air pollution and exposure require more than just awareness and willingness to act.

Evaluating the Effects of Access to Air Quality Data on Household Air Pollution and Exposure—An Interrupted Time Series Experimental Study in Rwanda