Journal cover Journal topic
Atmospheric Measurement Techniques An interactive open-access journal of the European Geosciences Union

Journal metrics

  • IF value: 2.989 IF 2.989
  • IF 5-year<br/> value: 3.489 IF 5-year
    3.489
  • CiteScore<br/> value: 3.37 CiteScore
    3.37
  • SNIP value: 1.273 SNIP 1.273
  • SJR value: 2.026 SJR 2.026
  • IPP value: 3.082 IPP 3.082
  • h5-index value: 45 h5-index 45
doi:10.5194/amt-2017-138
© Author(s) 2017. This work is distributed
under the Creative Commons Attribution 3.0 License.
Research article
05 May 2017
Review status
This discussion paper is under review for the journal Atmospheric Measurement Techniques (AMT).
Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements
Eben S. Cross1, David K. Lewis1,2, Leah R. Williams1, Gregory R. Magoon1, Michael L. Kaminsky3, Douglas R. Worsnop1, and John T. Jayne1 1Center for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821 USA
2Department of Chemistry, Connecticut College, New London, CT 06320 USA
3Massachusetts Institute of Technology, Cambridge, MA 02139 USA
Abstract. The environments in which we live, work, breathe, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality, measurements must be fast (real-time), scalable, and reliable (with known accuracy, precision, and stability over time). Low-cost AQ sensor technologies offer new opportunities for fast and distributed measurements, but a persistent characterization gap remains when it comes to evaluating sensor performance under realistic environmental sampling conditions. This limits our ability to inform stakeholders about pollution sources and inspire policy makers to address environmental justice air quality issues. In this paper, initial results obtained with a recently developed low-cost air quality sensor system are reported. In this project, data were acquired with the ARISense integrated sensor package over a 4-month time interval during which the sensor system was co-located with a state-operated (Massachusetts, USA) air quality monitoring station equipped with reference instrumentation measuring the same pollutant species. This paper focuses on validating electrochemical sensor measurements of CO, NO, NO2, and O3. Through the use of High Dimensional Model Representation (HDMR), we show that interference effects derived from changing environmental conditions and the ambient-gas concentration mix encountered at an urban neighborhood site can be effectively modelled for the Alphasense CO-B4, NO-B4, NO2-B43F, and Ox-B421 sensors, improving the credibility of air pollutant measurements made with these sensors.

Citation: Cross, E. S., Lewis, D. K., Williams, L. R., Magoon, G. R., Kaminsky, M. L., Worsnop, D. R., and Jayne, J. T.: Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements, Atmos. Meas. Tech. Discuss., doi:10.5194/amt-2017-138, in review, 2017.
Eben S. Cross et al.
Eben S. Cross et al.
Eben S. Cross et al.

Viewed

Total article views: 490 (including HTML, PDF, and XML)

HTML PDF XML Total Supplement BibTeX EndNote
336 143 11 490 16 2 10

Views and downloads (calculated since 05 May 2017)

Cumulative views and downloads (calculated since 05 May 2017)

Viewed (geographical distribution)

Total article views: 490 (including HTML, PDF, and XML)

Thereof 486 with geography defined and 4 with unknown origin.

Country # Views %
  • 1

Saved

Discussed

Latest update: 29 May 2017
Publications Copernicus
Download
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.
Low-cost air quality sensor technologies offer new opportunities for fast and distributed...
Share