Temperature dataloggers as stove use monitors (SUMs): Field methods and signal analysis

We report the field methodology of a 32-month monitoring study with temperature dataloggers as Stove Use Monitors (SUMs) to quantify usage of biomass cookstoves in 80 households of rural Guatemala. The SUMs were deployed in two stoves types: a well-operating chimney cookstove and the traditional open-cookfire. We recorded a total of 31,112 days from all chimney cookstoves, with a 10% data loss rate. To count meals and determine daily use of the stoves we implemented a peak selection algorithm based on the instantaneous derivatives and the statistical long-term behavior of the stove and ambient temperature signals. Positive peaks with onset and decay slopes exceeding predefined thresholds were identified as “fueling events”, the minimum unit of stove use. Adjacent fueling events detected within a fixed-time window were clustered in single “cooking events” or “meals”. The observed means of the population usage were: 89.4% days in use from all cookstoves and days monitored, 2.44 meals per day and 2.98 fueling events. We found that at this study site a single temperature threshold from the annual distribution of daily ambient temperatures was sufficient to differentiate days of use with 0.97 sensitivity and 0.95 specificity compared to the peak selection algorithm. With adequate placement, standardized data collection protocols and careful data management the SUMs can provide objective stove-use data with resolution, accuracy and level of detail not possible before. The SUMs enable unobtrusive monitoring of stove-use behavior and its systematic evaluation with stove performance parameters of air pollution, fuel consumption and climate-altering emissions.

► Small, unobtrusive temperature dataloggers were used as Stove Use Monitors (SUMs).
► We measured with SUMs sustained use of 80 chimney stoves in Guatemala for 2.6 years.
► To count meals we analyzed slopes and statistics of stove and ambient temperature signals.
► SUMs require standardized placement, data management and validated analysis algorithms.
► SUMs give objective stove-use data with unparalleled resolution, accuracy and detail.