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Array of Things: Characterizing low-cost air quality sensors for a city-wide instrument
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  • Mark Potosnak,
  • Pinaki Banerjee,
  • Rajesh Sankaran,
  • Veerabhadra Kotamarthi,
  • Robert Jacob,
  • Peter Beckman,
  • Charlie Catlett
Mark Potosnak
DePaul University

Corresponding Author:[email protected]

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Pinaki Banerjee
Cook County
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Rajesh Sankaran
Argonne National Laboratory
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Veerabhadra Kotamarthi
Argonne National Laboratory
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Robert Jacob
Argonne National Laboratory
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Peter Beckman
Argonne National Laboratory
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Charlie Catlett
Argonne National Laboratory
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Abstract

The Array of Things (AoT) is a collaborative effort among leading scientists, universities, local government and communities in Chicago to collect real-time data on the city’s environment, infrastructure, and activity for research and public use. The AoT is composed of nodes that will measure and sense the urban environment of Chicago and provide openly accessible data in near real time. One component of each node is the ChemSense board, which uses chemical sensors to measure five gas-phase species: ozone, nitrogen dioxide, carbon monoxide, sulfur dioxide and hydrogen sulfide. In addition, the ChemSense board provides information on total reducing gases and total oxidizing gases. The nodes also include meteorological information and cameras that will provide pedestrian and traffic counts using computer vision algorithms. Because the ChemSense boards rely on low-cost sensors, characterizing the sensor responses is critical to understanding the applicability of the AoT for urban air quality issues. As a first step, a node with the ChemSense board was installed at an EPA air quality monitoring site within the City of Chicago, which is run by the Cook County Department of Environment and Sustainability. The EPA site has Federal Reference Method monitors for ozone, nitrogen dioxide and sulfur dioxide. After collecting collocation data for seven months, the results are promising for ozone, but much less so for sulfur dioxide. For nitrogen dioxide, unexplained spikes not observed in the EPA data drive a poor fit. Results from the collocation project will be used to consider larger issues for characterizing the air quality component of the AoT.