AAAR 35th Annual Conference October 17 - October 21, 2016 Oregon Convention Center Portland, Oregon, USA
Abstract View
Development and Evaluation of an Ultrasonic Personal Aerosol Sampler (UPAS)
JOHN VOLCKENS, Casey Quinn, David Leith, John Mehaffy, Charles Henry, Dan Miller-Lionberg, Colorado State University
Abstract Number: 198 Working Group: Aerosol Exposure
Abstract Assessing personal exposure to air pollution has long proven challenging due to limitations posed by wearable aerosol monitors: cost, noise, and weight. The objective of this work is to develop an ultrasonic personal aerosol sampler (UPAS) to overcome many of these technological limitations. The UPAS is a time-integrated monitor that features a novel micro-pump that is silent during operation. A suite of on-board sensors measure air flow, temperature, pressure, relative humidity, light intensity, and acceleration. Rapid development of the UPAS was possible through recent advances in low-cost electronics, open-source programming, and additive manufacturing. These advances enabled the development of a prototype air sampler that overcomes the cost (bill of materials under $300), weight (190g), and noise (<45 dB) issues of traditional personal sampling devices. The operating range of the pump spans 4kPa of static pressure head and 3 L/min of flow; the mass flow sensor was accurate within 10% between 0.1 and 3 L/min. The UPAS battery lasted approximately 25 hr at 1.0 L/min and 45 hr at 2.0 L/min. The size cut of the PM2.5 cyclone agreed well with the published EPA federal reference criterion (within 5% for the majority of ambient particle size distributions). Laboratory tests demonstrate excellent agreement with equivalent federal reference method samplers for gravimetric analysis of PM2.5 across a broad range of concentrations (20-800 ug/m3). A simple linear regression between the UPAS and federal reference samplers gave a slope of 0.996 with an intercept of 3.7 ug/m3. The UPAS shows promise for increasing our ability to assess personal PM exposures by reducing the size, weight, and cost of the sampler. As a result, sampling can be conducted at scales that are more relevant to epidemiologic and community-based research.