A Long-Term Comparison between the AethLabs MA350 and Aerosol Magee Scientific AE33 Black Carbon Monitors in the Greater Salt Lake City Metropolitan Area.

Black carbon (BC) or soot contains ultrafine combustion particles that are associated with a wide range of health impacts, leading to respiratory and cardiovascular diseases. Both long-term and short-term health impacts of BC have been documented, with even low-level exposures to BC resulting in negative health outcomes for vulnerable groups. Two aethalometers-AethLabs MA350 and Aerosol Magee Scientific AE33-were co-located at a Utah Division of Air Quality site in Bountiful, Utah for just under a year. The aethalometer comparison showed a close relationship between instruments for IR BC, Blue BC, and fossil fuel source-specific BC estimates. The biomass source-specific BC estimates were markedly different between instruments at the minute and hour scale but became more similar and perhaps less-affected by high-leverage outliers at the daily time scale. The greater inter-device difference for biomass BC may have been confounded by very low biomass-specific BC concentrations during the study period. These findings at a mountainous, high-elevation, Greater Salt Lake City Area site support previous study results and broaden the body of evidence validating the performance of the MA350.

Health assessment of future PM2.5 exposures from indoor, outdoor, and secondhand tobacco smoke concentrations under alternative policy pathways in Ulaanbaatar, Mongolia.

INTRODUCTION: Winter air pollution in Ulaanbaatar, Mongolia is among the worst in the world. The health impacts of policy decisions affecting air pollution exposures in Ulaanbaatar were modeled and evaluated under business as usual and two more-strict alternative emissions pathways through 2024. Previous studies have relied on either outdoor or indoor concentrations to assesses the health risks of air pollution, but the burden is really a function of total exposure. This study combined projections of indoor and outdoor concentrations of PM2.5 with population time-activity estimates to develop trajectories of total age-specific PM2.5 exposure for the Ulaanbaatar population. Indoor PM2.5 contributions from secondhand tobacco smoke (SHS) were estimated in order to fill out total exposures, and changes in population and background disease were modeled. The health impacts were derived using integrated exposure-response curves from the Global Burden of Disease Study. RESULTS: Annual average population-weighted PM2.5 exposures at baseline (2014) were estimated at 59 µg/m3. These were dominated by exposures occurring indoors, influenced considerably by infiltrated outdoor pollution. Under current control policies, exposures increased slightly to 60 µg/m3 by 2024; under moderate emissions reductions and under a switch to clean technologies, exposures were reduced from baseline levels by 45% and 80%, respectively. The moderate improvement pathway decreased per capita annual disability-adjusted life year (DALY) and death burdens by approximately 40%. A switch to clean fuels decreased per capita annual DALY and death burdens by about 85% by 2024 with the relative SHS contribution increasing substantially. CONCLUSION: This study demonstrates a way to combine estimated changes in total exposure, background disease and population levels, and exposure-response functions to project the health impacts of alternative policy pathways. The resulting burden analysis highlights the need for aggressive action, including the elimination of residential coal burning and the reduction of current smoking rates.

Small, Smart, Fast, and Cheap: Microchip-Based Sensors to Estimate Air Pollution Exposures in Rural Households.

Over the last 20 years, the Kirk R. Smith research group at the University of California Berkeley-in collaboration with Electronically Monitored Ecosystems, Berkeley Air Monitoring Group, and other academic institutions-has developed a suite of relatively inexpensive, rugged, battery-operated, microchip-based devices to quantify parameters related to household air pollution. These devices include two generations of particle monitors; data-logging temperature sensors to assess time of use of household energy devices; a time-activity monitoring system using ultrasound; and a CO2-based tracer-decay system to assess ventilation rates. Development of each system involved numerous iterations of custom hardware, software, and data processing and visualization routines along with both lab and field validation. The devices have been used in hundreds of studies globally and have greatly enhanced our understanding of heterogeneous household air pollution (HAP) concentrations and exposures and factors influencing them.