• Energy Research

The adoption of clean cooking technologies goes beyond mere product acquisition and requires attention to issues of cooking traditions, user engagement, gender dynamics, culture, and religion to effect correct and consistent use.

Smoky cookfires contribute to global climate change and kill approximately four million people annually. While many studies have examined the effects of fuel-efficient cookstoves, this study does so while selling stoves at market prices. After introducing a fuel-efficient cookstove, fuelwood use and household air particulates declined by 12% and by smaller percentages after adjusting for observer-induced bias, or the Hawthorne effect. These reductions were less than laboratory predictions and fell well short of World Health Organization pollution targets. Even when introducing a second stove, most households continued to use their traditional stoves for most cooking. Future research should focus on improving the usability of fuel-efficient cookstoves and/or policies that assist consumers to shift to safer fuels like gas or electricity coupled with mechanisms to disable the existing smoky cookfire.

Consumers’ failure to adopt products with health and wellbeing benefits apparently far greater than their costs has consistentlychallenged the widespread use of health-improving technologies. A sales offer combining free trial, time payments, and the option of returning the product can overcome barriers such as liquidityconstraints and poor information about benefits and usability. We tested this sales offer (and alternatives) in an experiment with a fuel-efficient charcoal stove in urban Uganda and a fuel-efficient wood stove in rural Uganda. This offer dramatically increased uptake—in urban Kampala, from 4 to 46%, and in rural Mbarara, from 5 to 57%.

Understanding the daily use patterns of traditional and nontraditional cooking technologies is essential for researchers and policy makers attempting to reduce indoor air pollution and environmental degradation from inefficient cookstoves. This paper describes field methods and proposes a new algorithm for converting temperature data generated from stove use monitors into usage metrics for both traditional and nontraditional stoves. Central to our technique is recording the visual on/off status of a stove anytime research staff observes the stove. The observations are regressed against temperature readings in a logistic regression to estimate the probability that a temperature reading indicates usage. Using this algorithm we correctly predict 89% of three stone fire observations and 94% of Envirofit observations. The logistic regression correctly classifies more observations than published temperature analysis algorithms. This is the first published algorithm for converting temperature data for traditional stoves such as three stone fires.