Usage and impacts of the Envirofit HM-5000 cookstove.

Burning solid fuels to fulfill daily household energy needs results in chronic exposure to household air pollution (HAP), which is among the world's greatest health risks. This paper presents the results of a cross-sectional study of cookstove usage, fuel consumption, and indoor PM2.5 concentrations in rural and urban Honduran homes cooking with the Envirofit HM-5000 metal plancha stove (n = 32) as compared to control households using baseline cooking technologies (n = 33). Temperature-based stove usage measurements showed high HM-5000 acceptance, with significant displacement of the traditional cookstoves at both the urban (99%, P < .05) and rural study sites (75%, P < .05). However, longer-term usage data collected in peri-urban households showed that participants cooked on the HM-5000 more frequently during the 3-day monitoring period than during the following 3 weeks. Average indoor PM2.5 was 66% lower in HM-5000 households as compared to control households (P < .05). Lower indoor PM2.5 concentrations observed in participant homes as compared to control households, supported by high usage and traditional stove displacement, suggest the potential for the HM-5000 to yield health improvements in adopting Honduran households.

Machine-learned modeling of PM2.5 exposures in rural Lao PDR.

This study presents a machine-learning-enhanced method of modeling PM2.5 personal exposures in a data-scarce, rural, solid fuel use context. Data collected during a cookstove (Africa Clean Energy (ACE)-1 solar-battery-powered stove) intervention program in rural Lao PDR are presented and leveraged to explore advanced techniques for predicting personal exposures to particulate matter with aerodynamic diameter smaller than 2.5 µm (PM2.5). Mean 48-h PM2.5 exposure concentrations for female cooks were measured for the pre- and post-intervention periods (the "Before" and "After" periods, respectively) as 123 µg/m3 and 81 µg/m3. Mean 48-h PM2.5 kitchen air pollution ("KAP") concentrations were measured at 462 µg/m3 Before and 124 µg/m3 After. Application of machine learning and ensemble modeling demonstrated cross-validated personal exposure predictions that were modest at the individual level but reasonably strong at the group level, with the best models producing an observed vs. predicted r2 between 0.26 and 0.31 (r2 = 0.49 when using a smaller, un-imputed dataset) and mean Before estimates of 119-120 µg/m3 and After estimates of 86-88 µg/m3. This offered improvement over one typical method of predicting exposure - using a kitchen exposure factor (the ratio of exposure to KAP)- which demonstrated an r2 ~ 0.03 and poorly estimated group average values. The results of these analyses highlight areas of methodological improvement for future exposure assessments of household air pollution and provide evidence for researchers to explore the advantages of further incorporating machine learning methods into similar research across wider geographic and cultural contexts.

The MMT bag for emission source sampling: design and evaluation.

This paper presents the design and evaluation results for a metal-coated multilayer Tedlar (MMT) bag that was developed for the collection of source emissions. The applicability of the MMT bag was evaluated for a number of important greenhouse relevant gases: CO, CO2, CH4, N2O, and total hydrocarbons (THCs). The bag was tested for durability and stability for a range of concentrations of the tested compounds using both laboratory-prepared samples and real source samples. The results show that all tested compounds were more stable when stored in the MMT bag than when stored in a regular Tedlar bag. These compounds can be stored at room temperature for at least 3 months without significant changes in concentration. When properly packed, the MMT bag is durable and may be shipped by air. The MMT bag is lower in cost, lighter in weight, and easier to clean, and it requires less devices during the subsequent laboratory analysis compared with a stainless steel canister, which is often used to collect air and source samples.