Articles | Volume 16, issue 12
https://doi.org/10.5194/amt-16-3313-2023
© Author(s) 2023. 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-16-3313-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Field evaluation of low-cost electrochemical air quality gas sensors under extreme temperature and relative humidity conditions
Roubina Papaconstantinou
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Marios Demosthenous
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Spyros Bezantakos
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Neoclis Hadjigeorgiou
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Marinos Costi
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Melina Stylianou
Medisell Co Ltd, 2033 Nicosia, Cyprus
Elli Symeou
Medisell Co Ltd, 2033 Nicosia, Cyprus
Chrysanthos Savvides
Department of Labour Inspection, Ministry of Labour Welfare and Social Insurance, 1463 Nicosia, Cyprus
George Biskos
CORRESPONDING AUTHOR
Climate and Atmosphere Research Centre, The Cyprus Institute, 2121 Nicosia, Cyprus
Faculty of Civil Engineering and Geosciences, Delft University of Technology, 2628CN Delft, the Netherlands
Related authors
Roubina Papaconstantinou, Spyros Bezantakos, Michael Pikridas, Moreno Parolin, Melina Stylianou, Chrysanthos Savvides, Jean Sciare, and George Biskos
EGUsphere, https://doi.org/10.21203/rs.3.rs-5349649/v1, https://doi.org/10.21203/rs.3.rs-5349649/v1, 2025
Short summary
Short summary
We evaluate the ability of the Vaisala AQT530 monitors, comprising of low-cost sensors, to detect spatial and temporal differences. Collocated with reference instruments over 19 months in Nicosia, results showed that CO and PM sensors captured daily, hourly, and monthly spatial trends. NO2, NO, and O3 sensors were less reliable due to environmental effects. Still, all sensors tracked monthly temporal variations at the same location, with PM2.5 showing the strongest agreement with reference data.
Elie Bimenyimana, Jean Sciare, Michael Pikridas, Konstantina Oikonomou, Minas Iakovides, Emily Vasiliadou, Chrysanthos Savvides, and Nikos Mihalopoulos
EGUsphere, https://doi.org/10.5194/egusphere-2025-3234, https://doi.org/10.5194/egusphere-2025-3234, 2025
This preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).
Short summary
Short summary
Long-term (2015–2023) source apportionment analysis reveals that reduction in PM10 concentration levels from traffic in Cypriot cities is completely offset by the concomitant increase of uncontrolled PM from local sources (road dust resuspension, and domestic wood burning), along with rising Middle East PM from fossil fuel emissions. This poses a major challenge for Cyprus to comply with the stricter PM10 limits set by the new EU air quality directive.
Fabian Schmidt-Ott, Anne Maisser, Alexandros Lekkas, Dimitris Papanastasiou, and George Biskos
EGUsphere, https://doi.org/10.5194/egusphere-2025-3253, https://doi.org/10.5194/egusphere-2025-3253, 2025
Short summary
Short summary
We characterized a novel Atmospheric-Pressure-Interface Time-of-Flight (TOF) Mass Spectrometer. By accumulating ions in a trap prior the TOF mass analyzer, we achieve a limit of detection in the 10-3 to 10-6 ppq range with temporal resolutions in the order of 1 s to 10 min, respectively. This makes it highly relevant for atmospheric measurements, as it enables probing short-lived, low-concentration species of high importance in atmospheric chemistry and new particle formation.
Andreas Eleftheriou, Petros Mouzourides, Panayiotis Kouis, Nikos Kalivitis, Itzhak Katra, Emily Vasiliadou, Chrysanthos Savvides, Panayiotis Yiallouros, and Marina K.-A. Neophytou
EGUsphere, https://doi.org/10.5194/egusphere-2025-2739, https://doi.org/10.5194/egusphere-2025-2739, 2025
This preprint is open for discussion and under review for Natural Hazards and Earth System Sciences (NHESS).
Short summary
Short summary
Desert dust storms are a significant environmental concern in the Eastern Mediterranean. This study compared eleven forecasting models to see how well they predict dust levels in the atmosphere. By checking their results against in-situ and satellite measurements, we found that some models work better than others, but none are perfect. These findings can help improve forecasting systems, making them more reliable and useful for protecting public health and preparing for extreme dust events.
Roubina Papaconstantinou, Spyros Bezantakos, Michael Pikridas, Moreno Parolin, Melina Stylianou, Chrysanthos Savvides, Jean Sciare, and George Biskos
EGUsphere, https://doi.org/10.21203/rs.3.rs-5349649/v1, https://doi.org/10.21203/rs.3.rs-5349649/v1, 2025
Short summary
Short summary
We evaluate the ability of the Vaisala AQT530 monitors, comprising of low-cost sensors, to detect spatial and temporal differences. Collocated with reference instruments over 19 months in Nicosia, results showed that CO and PM sensors captured daily, hourly, and monthly spatial trends. NO2, NO, and O3 sensors were less reliable due to environmental effects. Still, all sensors tracked monthly temporal variations at the same location, with PM2.5 showing the strongest agreement with reference data.
Aliki Christodoulou, Iasonas Stavroulas, Mihalis Vrekoussis, Maximillien Desservettaz, Michael Pikridas, Elie Bimenyimana, Jonilda Kushta, Matic Ivančič, Martin Rigler, Philippe Goloub, Konstantina Oikonomou, Roland Sarda-Estève, Chrysanthos Savvides, Charbel Afif, Nikos Mihalopoulos, Stéphane Sauvage, and Jean Sciare
Atmos. Chem. Phys., 23, 6431–6456, https://doi.org/10.5194/acp-23-6431-2023, https://doi.org/10.5194/acp-23-6431-2023, 2023
Short summary
Short summary
Our study presents, for the first time, a detailed source identification of aerosols at an urban background site in Cyprus (eastern Mediterranean), a region strongly impacted by climate change and air pollution. Here, we identify an unexpected high contribution of long-range transported pollution from fossil fuel sources in the Middle East, highlighting an urgent need to further characterize these fast-growing emissions and their impacts on regional atmospheric composition, climate, and health.
George K. Georgiou, Theodoros Christoudias, Yiannis Proestos, Jonilda Kushta, Michael Pikridas, Jean Sciare, Chrysanthos Savvides, and Jos Lelieveld
Geosci. Model Dev., 15, 4129–4146, https://doi.org/10.5194/gmd-15-4129-2022, https://doi.org/10.5194/gmd-15-4129-2022, 2022
Short summary
Short summary
We evaluate the skill of the WRF-Chem model to perform high-resolution air quality forecasts (including ozone, nitrogen dioxide, and fine particulate matter) over the Eastern Mediterranean, during winter and summer. We compare the forecast output to observational data from background and urban locations and the forecast output from CAMS. WRF-Chem was found to forecast the concentrations and diurnal profiles of gas-phase pollutants in urban areas with higher accuracy.
Rima Baalbaki, Michael Pikridas, Tuija Jokinen, Tiia Laurila, Lubna Dada, Spyros Bezantakos, Lauri Ahonen, Kimmo Neitola, Anne Maisser, Elie Bimenyimana, Aliki Christodoulou, Florin Unga, Chrysanthos Savvides, Katrianne Lehtipalo, Juha Kangasluoma, George Biskos, Tuukka Petäjä, Veli-Matti Kerminen, Jean Sciare, and Markku Kulmala
Atmos. Chem. Phys., 21, 9223–9251, https://doi.org/10.5194/acp-21-9223-2021, https://doi.org/10.5194/acp-21-9223-2021, 2021
Short summary
Short summary
This study investigates new particle formation (NPF) in the less represented region of the Mediterranean basin using 1-year measurements of aerosol particles down to ~ 1 nm in diameter. We report a high frequency of NPF and give examples of interesting NPF features. We quantify the strength of NPF events by calculating formation rates and growth rates. We further unveil the atmospheric conditions and variables considered important for the intra-monthly and inter-monthly occurrence of NPF.
Cited articles
AIRPARIF: https://commercialisation.esa.int/wp-content/uploads/2020/11/Air-quality-monitoring-in-the-City-of-Paris_Basthiste.pdf (last access: 8 March 2022), 2018.
Aleixandre, M. and Gerboles, M.: Review of Small Commercial Sensors for
Indicative Monitoring of Ambient Gas, Chem. Engineer. Trans., 30, 169–174,
https://doi.org/10.3303/CET1230029, 2012.
Alphasense: Humidity Extremes: Drying Out and Water Absorption, Alphasense Application Note AAN106, https://www.alphasense.com/wp-content/uploads/2013/07/AAN_106.pdf, 2013.
Alphasense: Correcting for background currents in four electrode toxic gas sensors, Alphasense Application Note AAN803-05, 2019.
Bauerová, P., Šindelářová, A., Rychlík, Š., Novák, Z., and Keder, J.: Low-Cost Air Quality Sensors: One-Year Field Comparative Measurement of Different Gas Sensors and Particle Counters with Reference Monitors at Tušimice Observatory, Atmosphere, 11, 492, https://doi.org/10.3390/atmos11050492, 2020.
Bílek, J., Bílek, O., Maršolek, P., and Buček, P.: Ambient Air Quality Measurement with Low-Cost Optical and EC Sensors: An Evaluation of
Continuous Year-Long Operation, Environments, 8, 114, https://doi.org/10.3390/environments8110114, 2021.
Borrego, C., Costa, A. M., Ginja, J., Amorim, M., Coutinho, M., Karatzas,
K., Sioumis, Th., Katsifarakis, N., Konstantinidis, K., De Vito, S., Esposito, E., Smith, P., André, N., Gérard, P., Francis, L. A., Castell, N., Schneider, P., Viana, M., Minguillón, M. C., Reimringer, W., Otjes, R. P., von Sicard, O., Pohle, R., Elen, B., Suriano, D., Pfister, V., Prato, M., Dipinto, S., and Penza, M.: Assessment of air quality microsensors versus
reference methods: the EuNetAir joint exercise, Atmos. Environ., 147,
246–263, https://doi.org/10.1016/j.atmosenv.2016.09.050, 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?, J. Environ.
Int., 99, 293–302, https://doi.org/10.1016/j.envint.2016.12.007, 2017.
Collier-Oxandale, A., Feenstra, B., Papapostolou, V., Zhang, H., Kuang, M.,
Der Boghossian, B., and Polidori, A.: Field and laboratory performance
evaluations of 28 gas-phase air quality sensors by the AQ-SPEC program, Atmos. Environ., 220, 117092, https://doi.org/10.1016/j.atmosenv.2019.117092, 2020.
Cross, E. S., Williams, L. R., Lewis, D. K., Magoon, G. R., Onasch, T. B., 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., 10, 3575–3588, https://doi.org/10.5194/amt-10-3575-20177, 2017.
DLI Annual Technical Report Air Quality 2020:
https://www.airquality.dli.mlsi.gov.cy/sites/default/files/2021-12/Annual%20Air%20Quality%20Technical%20Report%202020_0.pdf (last access: 30 May 2023), 2020.
Duvall, R. M., Hagler, G. S. W., Clements, A. L., Benedict, K., Barkjohn, K.,
Kilaru, V., Hanley, T., Watkins, N., Kaufman, A., Kamal, A., Reece, S.,
Fransioli, P., Gerboles, M., Gillerman, G., Habre, R., Hannigan, M., Ning,
Z., Papapostolou, V., Pope, R., Quintana, P. J. E., and Lam Snyder, J.:
Deliberating Performance Targets: Follow-on workshop discussing PM10, NO2, CO, and SO2 air sensor targets, Atmos. Environ., 246, 118099,
https://doi.org/10.1016/j.atmosenv.2020.118099, 2021.
EC: DIRECTIVE 2008/50/EC OF THE EUROPEAN PARLIAMENT AND OF THE COUNCIL, Official Journal of the European Union, L 152/1, https://eur-lex.europa.eu/legal-content/EN/TXT/HTML/?uri=CELEX:32008L0050&from=en (last access: 20 April 2023), 2008.
Greater London Authority: Guide for monitoring air quality in London, https://www.london.gov.uk/sites/default/files/air_quality_monitoring_guidance_january_2018.pdf (last access: 23 November 2022), 2018.
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.
Jerrett, M., Donaire-Gonzalez, D., Popoola, O., Jones, R., Cohen, R. C.,
Almanza, E., de Nazelle, A., Mead, I., Carrasco-Turigas, G., Cole-Hunter,
T., Triguero-Mas, M., Seto, E., and Nieuwenhuijsen, M.: Validating novel air
pollution sensors to improve exposure estimates for epidemiological analyses
and citizen science, Environ. Res., 158, 286–294,
https://doi.org/10.1016/j.envres.2017.04.023, 2017.
Jiao, W., Hagler, G., Williams, R., Sharpe, R., Brown, R., Garver, D., Judge, R., Caudill, M., Rickard, J., Davis, M., Weinstock, L., Zimmer-Dauphinee, S., and Buckley, K.: Community Air Sensor Network (CAIRSENSE) project: evaluation of low-cost sensor performance in a suburban environment in the southeastern United States, Atmos. Meas. Tech., 9, 5281–5292, https://doi.org/10.5194/amt-9-5281-2016, 2016.
Juginovic, A., Vukovic, M., Aranza, I., and Bilos, V.: Health impacts of air
pollution exposure from 1990 to 2019 in 43 European countries, Sci. Rep.-UK, 11, 22516, https://doi.org/10.1038/s41598-021-01802-5, 2021.
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.
Lelieveld, J., Berresheim, H., Borrmann, S., Crutzen, P. J., Dentener, F.
J., Fischer, H., Feichter, J., Flatau, P. J., Heland, J., Holzinger, R.,
Korrmann, R., Lawrence, M. G., Levin, Z., Markowicz, K. M., Mihalopoulos,
N., Minikin, A., Ramanathan, V., De Reus, M., Roelofs, G. J., Scheeren, H.
A., Sciare, J., Schlager, H., Schultz, M., Siegmund, P., Steil, B.,
Stephanou, E. G., Stier, P., Traub, M., Warneke, C., Williams, J., and
Ziereis, H.: Global air pollution crossroads over the Mediterranean, Science, 298, 794–799, https://doi.org/10.1126/science.1075457, 2002.
Lelieveld, J., Pozzer, A., Pöschl, U., Fnais, M., Haines, A., and
Münzel, T.: Loss of life expectancy from air pollution compared to other
risk factors: a worldwide perspective, Cardiovasc. Res., 116, 1910–1917,
https://doi.org/10.1093/cvr/cvaa025, 2020.
Lewis, A. C., 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, https://doi.org/10.1039/c5fd00201j, 2015.
Li, J., Hauryliuk, A., Malings, C., Eilenberg, S. R., Subramanian, R., and
Presto, A. A.: Characterizing the Aging of Alphasense NO2 Sensors in
Long-Term Field Deployments, ACS Sens., 6, 2952–2959,
https://doi.org/10.1021/acssensors.1c00729, 2021.
Liang, Y., Wu, C., Jiang, S., Li, Y. J., Wu, D., Li, M., Cheng, P., Yang, W.,
Cheng, C., Li, L., Deng, T., Sun, J. Y., He, G., Liu, B., Yao, T., Wu, M., and Zhou, Z.: Field comparison of EC gas sensor data correction algorithms for ambient air measurements, Sensor. Actuat. B-Chem., 327, 128897,
https://doi.org/10.1016/j.snb.2020.128897, 2021.
Masson, N., Piedrahita, R., and Hannigan, M.: Quantification Method for
Electrolytic Sensors in Long-Term Monitoring of Ambient Air Quality,
Sensors, 15, 27283–27302, https://doi.org/10.3390/s151027283, 2015.
Mead, M. I., Popoola, O. A. M., Stewart, G. B., Landshoff, P., Calleja, M.,
Hayes, M., Baldovi, J. J., McLeod, M. W., Hodgson, T. F., Dicks, J., Lewis, A., Cohen, J., Baron, R., Saffell, J. R., and Jones, R. L.: The use of EC sensors for monitoring urban air quality in low-cost, high-density networks, Atmos. Environ., 70, 186–203, https://doi.org/10.1016/j.atmosenv.2012.11.060, 2013.
Pang, X., Shaw, M. D., Lewis, A. C., Carpenter, L. J., and Batchellier, T.: EC ozone sensors: A miniaturised alternative for ozone measurements in
laboratory experiments and air-quality monitoring, Sensor. Actuat. B-Chem., 240, 829–837, https://doi.org/10.1016/j.snb.2016.09.020, 2017.
Papaconstantinou, R., Demosthenous, M., Bezantakos, S., Hadjigeorgiou, N., Costi, M., Stylianou, M., Symeou, E., Savvides, C., and Biskos, G.: Field evaluation of low-cost electrochemical air quality gas sensors under extreme temperature and relative humidity conditions, Version 1, Zenodo [data set], https://doi.org/10.5281/zenodo.7998118, 2023.
Peltier, R., Castell, N., Clements, A., Dye, T., Hüglin, C., Kroll, J.,
Lung, Shih-Chun C., Ning, Z. Parsons, M., Penza, M., Reisen, F., and
Schneidemesser, E.: An update on low-cost sensors for the measurement of
atmospheric composition, Chairperson, Publications Board World
Meteorological Organization (WMO), Geneva 2, Switzerland, ISBN 978-92-63-11215-6, 2020.
Popoola, O. A. M., Stewart, G. B., Mead, M. I., and Jones, R. L.: Development of a baseline-temperature correction methodology for EC sensors and its
implications for long-term stability, Atmos. Environ., 147, 330–343,
https://doi.org/10.1016/j.atmosenv.2016.10.024, 2016.
Smith, K. R., Edwards, P. M., Evans, M. J., Lee, J. D., Shaw, M. D.,
Squires, F., Wilde, S., and Lewis, A. C.: Clustering approaches to improve
the performance of low cost air pollution sensors, Faraday Discuss., 200,
621–637, https://doi.org/10.1039/c7fd00020k, 2017.
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, Sensor. Actuat. B-Chem.,
215, 249–257, https://doi.org/10.1016/j.snb.2015.03.031, 2015.
Spinelle, L., Gerboles, M., Villani, M. G., Aleixandre, M., and Bonavitacola, F.:
Field calibration of a cluster of low-cost commercially available sensors
for air quality monitoring. Part B: NO, CO and CO2, Sensor. Actuat. B-Chem., 238, 706–715, https://doi.org/10.1016/j.snb.2016.07.036, 2017.
Vrekoussis, M., Pikridas, M., Rousogenous, C., Christodoulou, A.,
Desservettaz, M., Sciare, J., Richter, A., Bougoudis, I., Savvides, C., and
Papadopoulos, C.: Local and regional air pollution characteristics in Cyprus:
A long-term trace gases observations analysis, Sci. Total Environ., 845,
157315, https://doi.org/10.1016/j.scitotenv.2022.157315, 2022.
Walker, S. E. and Schneider, P.: A study of the relative expanded uncertainty
formula for comparing low-cost sensor and reference measurements, NILU,
ISBN: 978-82-425-2997-8, 2020.
WMO (World Meteorological Organization): Low-cost sensors for the
measurement of atmospheric composition: overview of topic and future applications, edited by: Lewis, A. C., von Schneidemesser, E., and Peltier, R. E., Geneva, Switzerland, ISBN 978-92-63-11215-6, 2018.
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
In this paper, we investigate the performance of low-cost electrochemical gas sensors. We carried out yearlong measurements at a traffic air quality monitoring station, where the low-cost sensors were collocated with reference instruments and exposed to highly variable environmental conditions with extremely high temperatures and low relative humidity (RH). Sensors provide measurements that exhibit increasing errors and decreasing correlations as temperature increases and RH decreases.
In this paper, we investigate the performance of low-cost electrochemical gas sensors. We...