10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

Abstract View


CitySpace Air Sensor Network: Application of High-Time Resolution Data from a Network of Low-Cost Air Sensor Technology to Examine Urban Air Pollution

STEPHEN FEINBERG, Ron Williams, Gayle Hagler, Judy Low, Larry Smith, Ryan Brown, Daniel Garver, Michael Davis, Michael Morton, Joe Schaefer, John Campbell, Tim McArthur, ORISE/ORD-US EPA, RTP, NC

     Abstract Number: 57
     Working Group: Instrumentation

Abstract
Recent advances in air pollution sensor technology have occurred that could help address concerns about nearby sources, support the siting of regulatory monitoring stations, and increase the knowledge of spatiotemporal variation of air pollution and associated health effects. Sensors are now being developed that are much smaller and lower-cost than traditional ambient air monitoring systems, and in some instances with promising performance. Thus, these sensors have the capability of being deployed in a nodal pattern to provide greater coverage of a geographical area. One such example is the CitySpace project conducted by the US EPA and the City of Memphis Health Department. A total of 16 solar and/or land powered sensor pods were developed containing Alphasense OPC-N2 particulate sensors along with ancillary monitoring components and were deployed across Memphis, TN for six months. Six of those sensor pods were determined to meet selection criteria for further analysis based on collocated comparison with a regulatory Tapered element oscillating microbalance (TEOM) monitor. The data from these pods were then normalized to imitate TEOM measurement, and the resultant concentrations were used in an analysis to examine potential contributors to urban air particulate matter. The 1-minute data from the sensor pods were used to perform a receptor modeling technique called Nonparametric Trajectory Analysis (NTA). The NTA results from the network of sensors were used to explore which regions within the study area were associated with high measured concentrations and what potential sources are within those regions.