ObjectivesTo investigate how the two main electronic (e-) cigarette solvents—propylene glycol (PG) and glycerol (GL)—modulate the formation of toxic volatile carbonyl compounds under precisely controlled temperatures in the absence of nicotine and flavor additives.MethodsPG, GL, PG:GL = 1:1 (wt/wt) mixture, and two commercial e-cigarette liquids were vaporized in a stainless steel, tubular reactor in flowing air ranging up to 318°C to simulate e-cigarette vaping. Aerosols were collected and analyzed to quantify the amount of volatile carbonyls produced with each of the five e-liquids.ResultsSignificant amounts of formaldehyde and acetaldehyde were detected at reactor temperatures ≥215°C for both PG and GL. Acrolein was observed only in e-liquids containing GL when reactor temperatures exceeded 270°C. At 318°C, 2.03±0.80 μg of formaldehyde, 2.35±0.87 μg of acetaldehyde, and a trace amount of acetone were generated per milligram of PG; at the same temperature, 21.1±3.80 μg of formaldehyde, 2.40±0.99 μg of acetaldehyde, and 0.80±0.50 μg of acrolein were detected per milligram of GL.ConclusionsWe developed a device-independent test method to investigate carbonyl emissions from different e-cigarette liquids under precisely controlled temperatures. PG and GL were identified to be the main sources of toxic carbonyl compounds from e-cigarette use. GL produced much more formaldehyde than PG. Besides formaldehyde and acetaldehyde, measurable amounts of acrolein were also detected at ≥270°C but only when GL was present in the e-liquid. At 215°C, the estimated daily exposure to formaldehyde from e-cigarettes, exceeded United States Environmental Protection Agency (USEPA) and California Office of Environmental Health Hazard Assessment (OEHHA) acceptable limits, which emphasized the need to further examine the potential cancer and non-cancer health risks associated with e-cigarette use.

Pneumonia is a leading killer of children younger than 5 years despite high vaccination coverage, improved nutrition, and widespread implementation of the Integrated Management of Childhood Illnesses algorithm. Assessing the effect of interventions on childhood pneumonia is challenging because the choice of case definition and surveillance approach can affect the identification of pneumonia substantially. In anticipation of an intervention trial aimed to reduce childhood pneumonia by lowering household air pollution, we created a working group to provide recommendations regarding study design and implementation. We suggest to, first, select a standard case definition that combines acute (≤14 days) respiratory symptoms and signs and general danger signs with ancillary tests (such as chest imaging and pulse oximetry) to improve pneumonia identification; second, to prioritise active hospital-based pneumonia surveillance over passive case finding or home-based surveillance to reduce the risk of non-differential misclassification of pneumonia and, as a result, a reduced effect size in a randomised trial; and, lastly, to consider longitudinal follow-up of children younger than 1 year, as this age group has the highest incidence of severe pneumonia.

BACKGROUND: High quality personal exposure data is fundamental to understanding the health implications of household energy interventions, interpreting analyses across assigned study arms, and characterizing exposure-response relationships for household air pollution. This paper describes the exposure data collection for the Household Air Pollution Intervention Network (HAPIN), a multicountry randomized controlled trial of liquefied petroleum gas stoves and fuel among 3,200 households in India, Rwanda, Guatemala, and Peru. OBJECTIVES: The primary objectives of the exposure assessment are to estimate the exposure contrast achieved following a clean fuel intervention and to provide data for analyses of exposure-response relationships across a range of personal exposures. METHODS: Exposure measurements are being conducted over the 3-y time frame of the field study. We are measuring fine particulate matter [PM < 2:5 lm in aerodynamic diameter (PM 2:5)] with the Enhanced Children's MicroPEM™ (RTI International), carbon monoxide (CO) with the USB-EL-CO (Lascar Electronics), and black carbon with the OT21 transmissometer (Magee Scientific) in pregnant women, adult women, and children <1 year of age, primarily via multiple 24-h personal assessments (three, six, and three measurements, respectively) over the course of the 18month follow-up period using lightweight monitors. For children we are using an indirect measurement approach, combining data from area monitors and locator devices worn by the child. For a subsample (up to 10%) of the study population, we are doubling the frequency of measurements in order to estimate the accuracy of subject-specific typical exposure estimates. In addition, we are conducting ambient air monitoring to help characterize potential contributions of PM 2:5 exposure from background concentration. Stove use monitors (Geocene) are being used to assess compliance with the intervention, given that stove stacking (use of traditional stoves in addition to the intervention gas stove) may occur. CONCLUSIONS: The tools and approaches being used for HAPIN to estimate personal exposures build on previous efforts and take advantage of new technologies. In addition to providing key personal exposure data for this study, we hope the application and learnings from our exposure assessment will help inform future efforts to characterize exposure to household air pollution and for other contexts.

Household air pollution (HAP) generated from solid fuel combustion is a major health risk. Direct measurement of exposure to HAP is burdensome and challenging, particularly for children. In a pilot study of the Household Air Pollution Intervention Network (HAPIN) trial in rural Guatemala, we evaluated an indirect exposure assessment method that employs fixed continuous PM 2.5 monitors, Bluetooth signal receivers in multiple microenvironments (kitchen, sleeping area and outdoor patio), and a wearable signal emitter to track an individual's time within those microenvironments. Over a four-month period, we measured microenvironmental locations and reconstructed indirect PM 2.5 exposures for women and children during two 24-h periods before and two periods after a liquefied petroleum gas (LPG) stove and fuel intervention delivered to 20 households cooking with woodstoves. Women wore personal PM 2.5 monitors to compare direct with indirect exposure measurements. Indirect exposure measurements had high correlation with direct measurements (n = 62, Spearman ρ = 0.83, PM 2.5 concentration range: 5-528 µg/m 3). Indirect exposure had better agreement with direct exposure measurements (bias: −17 µg/m 3) than did kitchen area measurements (bias: −89 µg/m 3). Our findings demonstrate that indirect exposure reconstruction is a feasible approach to estimate personal exposure when direct assessment is not possible.