AAAR 37th Annual Conference October 14 - October 18, 2019 Oregon Convention Center Portland, Oregon, USA
Abstract View
Coupling Laboratory and Field Measurements to Estimate Air Pollutant Emissions from Cookstoves
KELSEY BILSBACK, Rose Eilenberg, Lauren Hoskovec, Michael Johnson, Jack Kodros, Eric Lipsky, Christian L'Orange, Jessica Tryner, Ander Wilson, Allen Robinson, Jeffrey R. Pierce, John Volckens, Colorado State University
Abstract Number: 616 Working Group: Biomass Combustion: Emissions, Chemistry, Air Quality, Climate, and Human Health
Abstract Air pollution from solid-fuel combustion in cookstoves is a leading cause of death and disease worldwide. Currently, emissions measurements used for indoor and outdoor air quality modeling are primarily derived from laboratory experiments; however, most laboratory-derived data underestimate the magnitude and variability of emissions measured during in-home cooking practices. Contrastingly, data collected during in-home cookstove use are realistic; however, field campaigns are logistically difficult, cost prohibitive, and only provide a limited view of emissions within a specific home or region. To address these gaps, we developed methodology that combines (1) statistical models trained on laboratory data and (2) low-cost in-field measurements to estimate fine particulate matter (PM2.5), carbon monoxide, and black carbon. Multiple statistical model forms, with varying complexity, were tested to identify which models could provide the most accurate emissions estimates based on the lowest in-field measurement costs. The models utilized several forms of firepower and modified combustion efficiency (MCE) as predictors. To validate the models, we collected emissions measurements and continuous firepower and MCE measurements from cookstoves in Honduras, Uganda, and India. Continuous firepower was estimated using temperature at the combustion chamber outlet and MCE was estimated using a low-cost gas analyzer. When comparing our model-based estimates to emissions measurements taken in the field, we find that the model estimates are generally accurate enough to predict the International Standards Organization (ISO) emissions tier a given stove will operate at in the field. We also find that including both firepower and MCE measurements in the model, rather than firepower alone, can improve the accuracy of the model-based emissions estimates by 63%. Although further validation is needed, our methodology, which combines laboratory-derived statistical models and minimal in-field monitoring, shows promise for estimating emissions levels observed in the field.