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CitySpace Air Sensor Network: Application of High-Time Resolution Data from a Network of Low-Cost Air Sensor Technology to Examine Urban Air Pollution
Citation:
Feinberg, S., R. Williams, G. Hagler, J. Low, L. Smith, R. Brown, D. Garver, M. Davis, M. Morton, J. Schaefer, J. Campbell, AND T. McArthur. CitySpace Air Sensor Network: Application of High-Time Resolution Data from a Network of Low-Cost Air Sensor Technology to Examine Urban Air Pollution. 2018 International Aerosol Conference, St. Louis, MI, September 02 - 07, 2018.
Impact/Purpose:
CitySpace was a deployment of a network of 17 air sensor pods in Memphis, TN from October 2016 to March 2017 to evaluate the use of a sensor network in a mid-size city and data from these sensor pods were used to perform a spatiotemporal analysis of PM in Memphis.
Description:
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.
