Articles | Volume 9, issue 11
Atmos. Meas. Tech., 9, 5281–5292, 2016
Atmos. Meas. Tech., 9, 5281–5292, 2016

Research article 01 Nov 2016

Research article | 01 Nov 2016

Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States

Wan Jiao1, Gayle Hagler1, Ronald Williams1, Robert Sharpe2, Ryan Brown3, Daniel Garver3, Robert Judge4, Motria Caudill5, Joshua Rickard6, Michael Davis7, Lewis Weinstock8, Susan Zimmer-Dauphinee9, and Ken Buckley9 Wan Jiao et al.
  • 1US Environmental Protection Agency (EPA), Office of Research and Development, Research Triangle Park, NC 27711, USA
  • 2ARCADIS US, Inc., Durham, NC 27713, USA
  • 3US EPA, Region 4, Atlanta, GA 30303, USA
  • 4US EPA, Region 1, Boston, MA 02109, USA
  • 5US EPA, Region 5, Chicago, IL 60604, USA
  • 6US EPA, Region 8, Denver, CO 80202, USA
  • 7US EPA, Region 7, Lenexa, KS 66219, USA
  • 8US EPA, Office of Air Quality Planning and Standards, Research Triangle Park, NC 27711, USA
  • 9Georgia Environmental Protection Division, Atlanta, GA 30354, USA

Abstract. Advances in air pollution sensor technology have enabled the development of small and low-cost systems to measure outdoor air pollution. The deployment of a large number of sensors across a small geographic area would have potential benefits to supplement traditional monitoring networks with additional geographic and temporal measurement resolution, if the data quality were sufficient. To understand the capability of emerging air sensor technology, the Community Air Sensor Network (CAIRSENSE) project deployed low-cost, continuous, and commercially available air pollution sensors at a regulatory air monitoring site and as a local sensor network over a surrounding  ∼ 2 km area in the southeastern United States. Collocation of sensors measuring oxides of nitrogen, ozone, carbon monoxide, sulfur dioxide, and particles revealed highly variable performance, both in terms of comparison to a reference monitor as well as the degree to which multiple identical sensors produced the same signal. Multiple ozone, nitrogen dioxide, and carbon monoxide sensors revealed low to very high correlation with a reference monitor, with Pearson sample correlation coefficient (r) ranging from 0.39 to 0.97, −0.25 to 0.76, and −0.40 to 0.82, respectively. The only sulfur dioxide sensor tested revealed no correlation (r < 0.5) with a reference monitor and erroneously high concentration values. A wide variety of particulate matter (PM) sensors were tested with variable results – some sensors had very high agreement (e.g., r =  0.99) between identical sensors but moderate agreement with a reference PM2.5 monitor (e.g., r =  0.65). For select sensors that had moderate to strong correlation with reference monitors (r > 0.5), step-wise multiple linear regression was performed to determine if ambient temperature, relative humidity (RH), or age of the sensor in number of sampling days could be used in a correction algorithm to improve the agreement. Maximum improvement in agreement with a reference, incorporating all factors, was observed for an NO2 sensor (multiple correlation coefficient R2adj-orig = 0.57, R2adj-final = 0.81); however, other sensors showed no apparent improvement in agreement. A four-node sensor network was successfully able to capture ozone (two nodes) and PM (four nodes) data for an 8-month period of time and show expected diurnal concentration patterns, as well as potential ozone titration due to nearby traffic emissions. Overall, this study demonstrates the performance of emerging air quality sensor technologies in a real-world setting; the variable agreement between sensors and reference monitors indicates that in situ testing of sensors against benchmark monitors should be a critical aspect of all field studies.

Short summary
Emerging lower cost and miniaturized sensors have potential to increase spatial and temporal information on air pollution. To evaluate these technologies, air quality sensor devices were collocated with regulatory-grade instruments in a suburban outdoor setting in the southeastern United States. Additionally, a multi-node sensor network, with several nodes solar-powered and wirelessly transmitting data, was established to test the feasibility of high density, continuous air monitoring.