Articles | Volume 14, issue 11
https://doi.org/10.5194/amt-14-7221-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-14-7221-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Unravelling a black box: an open-source methodology for the field calibration of small air quality sensors
Seán Schmitz
CORRESPONDING AUTHOR
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Sherry Towers
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Guillermo Villena
Physikalische und Theoretische
Chemie/FK4, Bergische Universität Wuppertal, Gaussstrasse 20, 42119 Wuppertal, Germany
Alexandre Caseiro
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
Robert Wegener
Forschungszentrum Jülich GmbH, Institute of Energy and Climate
Research, IEK8: Troposphere, 52425 Jülich, Germany
Dieter Klemp
Forschungszentrum Jülich GmbH, Institute of Energy and Climate
Research, IEK8: Troposphere, 52425 Jülich, Germany
Ines Langer
Institut für Meteorologie, Freie Universität Berlin,
Carl-Heinrich-Becker Weg 6–10, 12165 Berlin, Germany
Fred Meier
Chair of Climatology, Institute of Ecology, Technische Universität Berlin, Rothenburgstraße 12, 12165 Berlin, Germany
Erika von Schneidemesser
Institute for Advanced Sustainability Studies e. V. (IASS), Berliner Strasse 130, 14467 Potsdam, Germany
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Cited articles
Akaike, H.: Information theory and an extension of the maximum likelihood
principle, 2nd International Symposium on Information Theory, Budapest,
Hungary, Akadémiai Kiadó, 267–281, 1973.
Barcelo-Ordinas, J. M., Doudoub, M., Garcia-Vidala, J., and Badache, N.:
Self-Calibration Methods for Uncontrolled Environments in Sensor Networks: A
Reference Survey, Ad Hoc Netw., 88, 142–159, 2019.
Bigi, A., Mueller, M., Grange, S. K., Ghermandi, G., and Hueglin, C.: Performance of NO, NO2 low cost sensors and three calibration approaches within a real world application, Atmos. Meas. Tech., 11, 3717–3735, https://doi.org/10.5194/amt-11-3717-2018, 2018.
Breiman, L.: Random Forests, Mach. Learn., 45, 5–32, 2001.
Carslaw, D. C. and Taylor, P. J.: Analysis of air pollution data at a mixed
source location using boosted regression trees, Atmos. Environ., 43,
3563–3570, 2009.
Cordero, J. M., Borge, R., and Narros, A.: Using statistical methods to
carry out in field calibrations of low cost air quality sensors, Sensors and
Actuators B: Chemical, 267, 245–254, 2018.
Ghasemi, A. and Zahediasl, S.: Normality Tests for Statistical Analysis: A
Guide for Non-Statisticians, Int. J. Endocrinol. Metabol., 10, 486–489, 2012.
Hagan, D. H., Isaacman-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 regulatory-grade instruments, Atmos. Meas. Tech., 11, 315–328, https://doi.org/10.5194/amt-11-315-2018, 2018.
Karagulian, F., Barbiere, M., Kotsev, A., Spinelle, L., Gerboles, M.,
Lagler, F., Redon, N., Crunaire, S., and Borowiak, A.: Review of the
Performance of Low-Cost Sensors for Air Quality Monitoring, Atmosphere, 10,
506, https://doi.org/10.3390/atmos10090506, 2019.
Kizel, F., Etzion, Y., Shafran-Nathan, R., Levy, I., Fishbain, B.,
Bartonova, A., and Broday, D. M.: Node-to-node field calibration of wireless
distributed air pollution sensor network, Environ. Pollut., 233, 900–909,
2018.
Kumar, P., Morawska, L., Martani, C., Biskos, G., Neophytou, M., Di
Sabatino, S., Bell, M., Norford, L., and Britter, R.: The rise of low-cost
sensing for managing air pollution in cities, Environ. Int., 75, 199–205,
2015.
Landrigan, P. J., Fuller, R., Acosta, N. J. R., Adeyi, O., Arnold, R., Basu,
N., Baldé, A. B., Bertollini, R., Bose-O'Reilly, S., Boufford, J. I.,
Breysse, P. N., Chiles, T., Mahidol, C., Coll-Seck, A. M., Cropper, M. L.,
Fobil, J., Fuster, V., Greenstone, M., Haines, A., Hanrahan, D., Hunter, D.,
Khare, M., Krupnick, A., Lanphear, B., Lohani, B., Martin, K., Mathiasen, K.
V., McTeer, M. A., Murray, C. J. L., Ndahimananjara, J. D., Perera, F.,
Potočnik, J., Preker, A. S., Ramesh, J., Rockström, J., Salinas, C.,
Samson, L. D., Sandilya, K., Sly, P. D., Smith, K. R., Steiner, A., Stewart,
R. B., Suk, W. A., van Schayck, O. C. P., Yadama, G. N., Yumkella, K., and
Zhong, M.: The Lancet Commission on pollution and health, The Lancet, 391,
462–512, 2018.
Lewis, A., Lee, J. D., Edwards, P. M., Shaw, M. D., Evans, M. J., Moller, S.
J., Smith, K. R., Buckley, J. W., Ellis, M., Gillot, S. R., and White, A.:
Evaluating the performance of low cost chemical sensors for air pollution
research, Faraday Discuss., 189, 85–103, 2016.
Lewis, A., von Schneidemesser, E., and Peltier, R.: Low-cost sensors for the
measurement of atmospheric composition: overview of topic and future
applications, WMO, Geneva, Switzerland, 2018.
Malings, C., Tanzer, R., Hauryliuk, A., Kumar, S. P. N., Zimmerman, N., Kara, L. B., Presto, A. A., and R. Subramanian: Development of a general calibration model and long-term performance evaluation of low-cost sensors for air pollutant gas monitoring, Atmos. Meas. Tech., 12, 903–920, https://doi.org/10.5194/amt-12-903-2019, 2019.
Masiol, M., Squizzato, S., Chalupa, D., Rich, D. Q., and Hopke, P. K.:
Evaluation and Field Calibration of a Low-cost Ozone Monitor at a Regulatory
Urban Monitoring Station, Aerosol Air Qual. Res., 18, 2029–2037,
2018.
Miskell, G., Salmond, J. A., and Williams, D. E.: Solution to the Problem of
Calibration of Low-Cost Air Quality Measurement Sensors in Networks, ACS
Sens., 3, 832–843, 2018.
Morawska, L., Thai, P. K., Liu, X., Asumadu-Sakyi, A., Ayoko, G., Bartonova,
A., Bedini, A., Chai, F., Christensen, B., Dunbabin, M., Gao, J., Hagler, G.
S. W., Jayaratne, R., Kumar, P., Lau, A. K. H., Louie, P. K. K., Mazaheri,
M., Ning, Z., Motta, N., Mullins, B., Rahman, M. M., Ristovski, Z., Shafiei,
M., Tjondronegoro, D., Westerdahl, D., and Williams, R.: Applications of
low-cost sensing technologies for air quality monitoring and exposure
assessment: How far have they gone?, Environ. Int., 116, 286–299, 2018.
Muller, C. L., Chapman, L., Johnston, S., Kidd, C., Illingworth, S., Foody,
G., Overeem, A., and Leigh, R. R.: Crowdsourcing for climate and atmospheric
sciences: current status and future potential, Int. J. Climatol., 35, 3185–3203, 2015.
Peterson, P. J. D., Aujla, A., Grant, K. H., Brundle, A. G., Thompson, M.
R., Vande Hey, J., and Leigh, R. J.: Practical Use of Metal Oxide
Semiconductor Gas Sensors for Measuring Nitrogen Dioxide and Ozone in Urban
Environments, Sensors (Basel), 17, 1653, https://doi.org/10.3390/s17071653, 2017.
Rai, A. C., Kumar, P., Pilla, F., Skouloudis, A. N., Di Sabatino, S., Ratti,
C., Yasar, A., and Rickerby, D.: End-user perspective of low-cost sensors
for outdoor air pollution monitoring, Sci. Total Environ., 607–608, 691–705, 2017.
Scherer, D., Ament, F., Emeis, S., Fehrenbach, U., Leitl, B., Scherber, K.,
Schneider, C., and Vogt, U.: Three-Dimensional Observation of Atmospheric
Processes in Cities, Meteorol. Z., 28, 121–138, 2019a.
Scherer, D., Antretter, F., Bender, S., Cortekar, J., Emeis, S., Fehrenbach,
U., Gross, G., Halbig, G., Hasse, J., Maronga, B., Raasch, S., and Scherber,
K.: Urban Climate Under Change [UC]2 – A National Research Programme for
Developing a Building-Resolving Atmospheric Model for Entire City Regions,
Meteorol. Z., 28, 95–104, 2019b.
Schmitz, S., Towers, S., Villena, G., Caseiro, A., Wegener, R., Klemp, D., Langer, I., Meier, F., and von Schneidemesser, E.: Unraveling a black box: An open-source methodology for the field calibration of small air quality sensors (1.0.0), Zenodo [code], https://doi.org/10.5281/zenodo.4317521, 2020a.
Schmitz, S., Towers, S., Villena, G., Caseiro, A., Wegener, R., Klemp, D., Langer, I., Meier, F., and von Schneidemesser, E.: Unraveling a black box: An open-source methodology for the field calibration of small air quality sensors (1.0.0), Zenodo [data set], https://doi.org/10.5281/zenodo.4309853, 2020b.
Schmitz, S., Caseiro, A., Kerschbaumer, A., and von Schneidemesser, E.: Do
new bike lanes impact air pollution exposure for cyclists? – a case study
from Berlin, Environ. Res. Lett. 16, 084031 pp., https://doi.org/10.1088/1748-9326/ac1379, 2021.
Smith, K. R., Edwards, P. M., Evans, M. J., Lee, J. D., Shaw, M. D.,
Squires, F., Wilde, S., and Lewis, A.: Clustering approaches to improve the
performance of low cost air pollution sensors, Faraday Discuss., 200,
621–637, 2017.
Smith, K. R., Edwards, P. M., Ivatt, P. D., Lee, J. D., Squires, F., Dai, C., Peltier, R. E., Evans, M. J., Sun, Y., and Lewis, A. C.: An improved low-power measurement of ambient NO2 and O3 combining electrochemical sensor clusters and machine learning, Atmos. Meas. Tech., 12, 1325–1336, https://doi.org/10.5194/amt-12-1325-2019, 2019.
Snyder, E. G., Watkins, T. H., Solomon, P. A., Thoma, E. D., Williams, R.
W., Hagler, G. S., Shelow, D., Hindin, D. A., Kilaru, V. J., and Preuss, P.
W.: The changing paradigm of air pollution monitoring, Environ. Sci. Technol., 47, 11369–11377, https://doi.org/10.1021/es4022602, 2013.
Spinelle, L., Gerboles, M., Villani, M. G., Aleixandre, M., and
Bonavitacola, F.: Field calibration of a cluster of low-cost available
sensors for air quality monitoring, Part A: Ozone and nitrogen dioxide,
Sensors and Actuators B: Chemical, 215, 249–257, 2015.
R Core Team: R: A language and environment for statistical computing, R Foundation for Statistical Computing, Vienna, Austria, 2019.
Wager, S., Hastie, T., and Efron, B.: Confidence Intervals for Random
Forests: The Jackknife and the Infinitesimal Jackknife, J. Mach. Learn. Res., 15, 1625–1651, 2014.
Williams, R., Kilaru, V., Snyder, E., Kaufman, A., Dye, T., Rutter, A.,
Russell, A., and Hafner, H.: Air Sensor Guidebook, U.S. Environmental
Protection Agency, Washington, DC, 2014.
Zimmerman, N., Presto, A. A., Kumar, S. P. N., Gu, J., Hauryliuk, A., Robinson, E. S., Robinson, A. L., and R. Subramanian: A machine learning calibration model using random forests to improve sensor performance for lower-cost air quality monitoring, Atmos. Meas. Tech., 11, 291–313, https://doi.org/10.5194/amt-11-291-2018, 2018.
Short summary
The last 2 decades have seen substantial technological advances in the development of low-cost air pollution instruments. This study introduces a seven-step methodology for the field calibration of low-cost sensors with user-friendly guidelines, open-access code, and a discussion of common barriers. Our goal with this work is to push for standardized reporting of methods, make critical data processing steps clear for users, and encourage responsible use in the scientific community and beyond.
The last 2 decades have seen substantial technological advances in the development of low-cost...