Articles | Volume 18, issue 16
https://doi.org/10.5194/amt-18-4061-2025
https://doi.org/10.5194/amt-18-4061-2025
Research article
 | Highlight paper
 | 
28 Aug 2025
Research article | Highlight paper |  | 28 Aug 2025

Calibration and performance evaluation of PM2.5 and NO2 air quality sensors for environmental epidemiology

Miriam Chacón-Mateos, Héctor García-Salamero, Bernd Laquai, and Ulrich Vogt

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Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on egusphere-2025-587', Laurent Spinelle, 02 Apr 2025
    • AC1: 'Reply on RC1', Miriam Chacón-Mateos, 18 May 2025
  • RC2: 'Comment on egusphere-2025-587', Sebastian Diez, 08 Apr 2025
    • AC2: 'Reply on RC2', Miriam Chacón-Mateos, 18 May 2025

Peer review completion

AR: Author's response | RR: Referee report | ED: Editor decision | EF: Editorial file upload
AR by Miriam Chacón-Mateos on behalf of the Authors (18 May 2025)  Author's response   Author's tracked changes   Manuscript 
ED: Referee Nomination & Report Request started (22 May 2025) by Albert Presto
RR by Laurent Spinelle (27 May 2025)
RR by Sebastian Diez (27 May 2025)
ED: Publish as is (09 Jun 2025) by Albert Presto
AR by Miriam Chacón-Mateos on behalf of the Authors (29 Jun 2025)
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Executive editor
Low-cost sensors have been increasing used to measure air pollutants in environmental epidemiology. This work investigated the calibration and performance evaluation of PM2.5 and NO2 sensors, and introduced novel methodologies for field sensor validation during deployment. The manuscript is thorough and systematic in data treatment, and could be used a best practice guide for the application of sensors to air pollution and epidemiological studies.
Short summary
This study evaluates PM2.5 and NO2 sensors for their use in health studies. Sensors were calibrated using data from reference instruments, and regression and machine learning models were evaluated, identifying opportunities and limitations in model transferability in both indoor and outdoor environments and showcasing the importance of integrating metadata such as activity logs and diffusive tubes to improve data validation and interpretation during deployment in the houses of the participants.
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