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This study assessed the performance of modeling approaches to estimate personal exposure in Kenyan homes where cooking fuel combustion contributes substantially to household air pollution (HAP). We measured emissions (PM2.5, black carbon, CO); household air pollution (PM2.5, CO); personal exposure (PM2.5, CO); stove use; and behavioral, socioeconomic, and household environmental characteristics (eg, ventilation and kitchen volume). We then applied various modeling approaches: a single‐zone model; indirect exposure models, which combine person‐location and area‐level measurements; and predictive statistical models, including standard linear regression and ensemble machine learning approaches based on a set of predictors such as fuel type, room volume, and others. The single‐zone model was reasonably well‐correlated with measured kitchen concentrations of PM2.5 (R2 = 0.45) and CO (R2 = 0.45), but lacked precision. The best performing regression model used a combination of survey‐based data and physical measurements (R2 = 0.76) and a root mean‐squared error of 85 µg/m3, and the survey‐only‐based regression model was able to predict PM2.5 exposures with an R2 of 0.51. Of the machine learning algorithms evaluated, extreme gradient boosting performed best, with an R2 of 0.57 and RMSE of 98 µg/m3.

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Background: Globally, an estimated 3.6 billion people rely on solid fuels for cooking over open fires or in simple cookstoves. Universal access to clean cooking fuels and technology by 2030 is a United Nations’ Sustainable Development Goal. Methods: The Mediae Company created a home makeover television and radio show, Shamba Chef, designed to promote modern, cleaner, safer cooking methods and improved nutrition in Kenya, which reached 5 million homes in late 2017. This was accompanied by a mobile phone platform called iChef. Researchers evaluated the effects of Shamba Chef on cookstove purchase, use, and attitudes, beliefs, and intentions. Results: The study revealed dose–response effects of Shamba Chef exposure on several key outcomes. Exposure to the program was associated with an awareness of improved biomass stoves (OR 4.4; 95% CI 2.8 to 6.9), and aspirations to own an improved biomass stove (OR 2.0; 95% CI 1.4 to 2.9). Receiving information about modern stoves from two or more sources generated greater awareness of liquefied petroleum gas (LPG) stoves (OR 2.0; 95% CI 1.3 to 3.1). The qualitative study revealed that Shamba Chef explained how the stoves worked, communicated their benefits, and encouraged participants to trust and purchase those cookstoves. Conclusion: Shamba Chef was successful in influencing determinants of cookstove purchase and use, and there is evidence from the qualitative study that it influenced the purchase and use of improved biomass stoves.

A catalytic rocket stove was developed to reduce emissions and improve efficiency compared to open cooking fires or traditional semienclosed cookstoves, called poyos, typical of rural Guatemala. Traditional stoves often emit particulate matter and carbon monoxide at sufficient levels to cause respiratory illnesses and other health problems. Using focus group results, the stove was tailored to the needs of Guatemalan cooks. Field trial participants were provided with stove training to ensure that stoves were operated correctly. Somewhat surprisingly, the field trial demonstrated a high level of user acceptance in rural Guatemala, where users cooked 93% of the time with the catalytic stove despite having to change some cooking practices. In the field trial, the stove reduced emissions by as much as 68% and improved fuel efficiency by as much as 61% during real-world cooking events relative to the traditional poyo. An additional qualitative portion of the field study identified strengths and weaknesses of the stove that are being addressed as part of an iterative design process.