Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements
The environments in which we live, work, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality (AQ), measurements must be fast (real time), scalable, and reliable (with known accuracy, precision, and stability over time). Lower-cost...
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Copernicus Publications
2017-09-01
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Series: | Atmospheric Measurement Techniques |
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author | E. S. Cross L. R. Williams D. K. Lewis D. K. Lewis G. R. Magoon T. B. Onasch M. L. Kaminsky D. R. Worsnop J. T. Jayne |
author_facet | E. S. Cross L. R. Williams D. K. Lewis D. K. Lewis G. R. Magoon T. B. Onasch M. L. Kaminsky D. R. Worsnop J. T. Jayne |
author_sort | E. S. Cross |
collection | DOAJ |
description | The environments in which we live, work, and play are subject to
enormous variability in air pollutant concentrations. To adequately
characterize air quality (AQ), measurements must be fast (real time), scalable,
and reliable (with known accuracy, precision, and stability over time).
Lower-cost air-quality-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 the
public about pollution sources and inspire policy makers to address
environmental justice issues related to air quality. In this paper, initial
results obtained with a recently developed lower-cost air-quality-sensor
system are reported. In this project, data were acquired with the ARISense
integrated sensor package over a 4.5-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
(EC) sensor measurements of CO, NO, NO<sub>2</sub>, and O<sub>3</sub> at an urban neighborhood
site with pollutant concentration ranges (parts per billion by volume, ppb; 5 min averages, ±1<i>σ</i>):
[CO] = 231 ± 116 ppb (spanning 84–1706 ppb),
[NO] = 6.1 ± 11.5 ppb (spanning 0–209 ppb),
[NO<sub>2</sub>] = 11.7 ± 8.3 ppb (spanning 0–71 ppb), and
[O<sub>3</sub>] = 23.2 ± 12.5 ppb (spanning 0–99 ppb). Through
the use of high-dimensional model representation (HDMR), we show that
interference effects derived from the variable ambient gas concentration mix
and changing environmental conditions over three seasons (sensor flow-cell
temperature = 23.4 ± 8.5 °C,
spanning 4.1 to
45.2 °C; and
relative humidity = 50.1 ± 15.3 %, spanning
9.8–79.9 %) can be effectively modeled for the Alphasense CO-B4,
NO-B4, NO2-B43F, and Ox-B421 sensors, yielding (5 min average) root mean
square errors (RMSE) of 39.2, 4.52, 4.56, and 9.71 ppb, respectively. Our
results substantiate the potential for distributed air pollution measurements
that could be enabled with these sensors. |
first_indexed | 2024-12-15T00:06:14Z |
format | Article |
id | doaj.art-1499b44524f04732afe396c7fe9838b6 |
institution | Directory Open Access Journal |
issn | 1867-1381 1867-8548 |
language | English |
last_indexed | 2024-12-15T00:06:14Z |
publishDate | 2017-09-01 |
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series | Atmospheric Measurement Techniques |
spelling | doaj.art-1499b44524f04732afe396c7fe9838b62022-12-21T22:42:42ZengCopernicus PublicationsAtmospheric Measurement Techniques1867-13811867-85482017-09-01103575358810.5194/amt-10-3575-2017Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurementsE. S. Cross0L. R. Williams1D. K. Lewis2D. K. Lewis3G. R. Magoon4T. B. Onasch5M. L. Kaminsky6D. R. Worsnop7J. T. Jayne8Center for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USADepartment of Chemistry, Connecticut College, New London, CT 06320, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USAMassachusetts Institute of Technology, Cambridge, MA 02139, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USACenter for Aerosol and Cloud Chemistry, Aerodyne Research, Inc., Billerica, MA 01821, USAThe environments in which we live, work, and play are subject to enormous variability in air pollutant concentrations. To adequately characterize air quality (AQ), measurements must be fast (real time), scalable, and reliable (with known accuracy, precision, and stability over time). Lower-cost air-quality-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 the public about pollution sources and inspire policy makers to address environmental justice issues related to air quality. In this paper, initial results obtained with a recently developed lower-cost air-quality-sensor system are reported. In this project, data were acquired with the ARISense integrated sensor package over a 4.5-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 (EC) sensor measurements of CO, NO, NO<sub>2</sub>, and O<sub>3</sub> at an urban neighborhood site with pollutant concentration ranges (parts per billion by volume, ppb; 5 min averages, ±1<i>σ</i>): [CO] = 231 ± 116 ppb (spanning 84–1706 ppb), [NO] = 6.1 ± 11.5 ppb (spanning 0–209 ppb), [NO<sub>2</sub>] = 11.7 ± 8.3 ppb (spanning 0–71 ppb), and [O<sub>3</sub>] = 23.2 ± 12.5 ppb (spanning 0–99 ppb). Through the use of high-dimensional model representation (HDMR), we show that interference effects derived from the variable ambient gas concentration mix and changing environmental conditions over three seasons (sensor flow-cell temperature = 23.4 ± 8.5 °C, spanning 4.1 to 45.2 °C; and relative humidity = 50.1 ± 15.3 %, spanning 9.8–79.9 %) can be effectively modeled for the Alphasense CO-B4, NO-B4, NO2-B43F, and Ox-B421 sensors, yielding (5 min average) root mean square errors (RMSE) of 39.2, 4.52, 4.56, and 9.71 ppb, respectively. Our results substantiate the potential for distributed air pollution measurements that could be enabled with these sensors.https://www.atmos-meas-tech.net/10/3575/2017/amt-10-3575-2017.pdf |
spellingShingle | E. S. Cross L. R. Williams D. K. Lewis D. K. Lewis G. R. Magoon T. B. Onasch M. L. Kaminsky D. R. Worsnop J. T. Jayne Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements Atmospheric Measurement Techniques |
title | Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements |
title_full | Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements |
title_fullStr | Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements |
title_full_unstemmed | Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements |
title_short | Use of electrochemical sensors for measurement of air pollution: correcting interference response and validating measurements |
title_sort | use of electrochemical sensors for measurement of air pollution correcting interference response and validating measurements |
url | https://www.atmos-meas-tech.net/10/3575/2017/amt-10-3575-2017.pdf |
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