Articles | Volume 10, issue 9
Atmos. Meas. Tech., 10, 3575–3588, 2017
https://doi.org/10.5194/amt-10-3575-2017
Atmos. Meas. Tech., 10, 3575–3588, 2017
https://doi.org/10.5194/amt-10-3575-2017

Research article 29 Sep 2017

Research article | 29 Sep 2017

Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements

Eben S. Cross et al.

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Cited articles

Backus, A., Terrell, K., Wool, J., and Straubel, M.: Health, Environment, Community – A Tour of Dorchester and Surrounding Neighborhoods for Asthma Prevention and Health Equity, Harvard School of Public Health, NIEHS Center for Environmental Health, and GreenDorchester, 2012.
Borrego, C., Costa, A., Ginja, J., Amorim, M., Coutinho, M., Karatzas, K., Sioumis, T., Katsifarakis, N., Konstantinidis, K., and De Vito, S.: Assessment of air quality microsensors versus reference methods: The EuNetAir joint exercise, Atmos. Environ., 147, 246–263, 2016.
Castell, N., Dauge, F. R., Schneider, P., Vogt, M., Lerner, U., Fishbain, B., Broday, D., and Bartonova, A.: Can commercial low-cost sensor platforms contribute to air quality monitoring and exposure estimates?, Environ. Int., 99, 293–302, https://doi.org/10.1016/j.envint.2016.12.007, 2017.
EPA: Evaluation of Emerging Air Pollution Sensor Performance, available at: https://www.epa.gov/air-sensor-toolbox/evaluation-emerging-air-pollution-sensor-performance, 2017.
Hagan, D. H., Issacman-Vanwertz, G., Franklin, J. P., Wallace, L. M. M., Kocar, B. D., Heald, C. L., and Kroll, J. H.: Calibration and assessment of electrochemical air quality sensors by co-location with reference-grade instruments, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2017-296, in review, 2017.
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Short summary
Low-cost air quality sensor technologies offer new opportunities for fast and distributed measurements of air pollution, but a persistent characterization gap remains when it comes to evaluating sensor performance under realistic environmental sampling conditions. We present results from a newly developed integrated AQ-sensor system (ARISense) and demonstrate the utility of using high-dimensional model representation to improve the conversion of raw sensor signal to ambient concentration.