Atmospheric Measurement Techniques
Atmospheric Measurement Techniques
AMT
Articles | Volume 19, issue 1
Articles | Volume 19, issue 1
https://doi.org/10.5194/amt-19-63-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/amt-19-63-2026
© Author(s) 2026. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 19, issue 1
Research article
 | 
05 Jan 2026
Research article |  | 05 Jan 2026

Comparing spatial and temporal variabilities between the Vaisala AQT530 monitor and reference measurements

Roubina Papaconstantinou, Spyros Bezantakos, Michael Pikridas, Moreno Parolin, Melina Stylianou, Chrysanthos Savvides, Jean Sciare, and George Biskos

Viewed

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 1,224 (including HTML, PDF, and XML)
HTML PDF XML Total Supplement BibTeX EndNote
1,065 126 33 1,224 39 14 11
  • HTML: 1,065
  • PDF: 126
  • XML: 33
  • Total: 1,224
  • Supplement: 39
  • BibTeX: 14
  • EndNote: 11
Views and downloads (calculated since 14 May 2025)
Cumulative views and downloads (calculated since 14 May 2025)

Viewed (geographical distribution)

Since the preprint corresponding to this journal article was posted outside of Copernicus Publications, the preprint-related metrics are limited to HTML views.

Total article views: 1,224 (including HTML, PDF, and XML) Thereof 1,142 with geography defined and 82 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 
Latest update: 17 Mar 2026
Download
Short summary
We evaluate the ability of the Vaisala AQT530 (Air Quality Transmitter) 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 (particulate matter) 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.
Read more
Share