Pasar al contenido principal

Main navigation

  • Sobre El ITEFI
  • Investigación
  • Formación y empleo
  • OpenLab
  • Servicios científico técnicos
  • Directorio

Field calibration of a cluster of low-cost commercially available sensors for air quality monitoring Part. B: NO, CO and CO2

low-cost gas sensors
validation
measurement uncertainty
multivariate linear regression
artificial neural network
air quality directive
L Spinelle, M Gerboles, M G Villani, M Aleixandre, F Bonavitacola
Sensors and Actuators B: Chemical, vol. 238, 2017, pp. 706-715
http://doi.org/10.1016/j.snb.2016.07.036

In this work the performances of several field calibration methods for low-cost sensors, including linear/multi linear regression and supervised learning techniques, are compared. A cluster of either metal oxide or electrochemical sensors for nitrogen monoxide and carbon monoxide together with miniaturized infra-red carbon dioxide sensors was operated. Calibration was carried out during the two first weeks of evaluation against reference measurements. The accuracy of each regression method was evaluated on a five months field experiment at a semi-rural site using different indicators and techniques: orthogonal regression, target diagram, measurement uncertainty and drifts over time of sensor predictions. In addition to the analyses for ozone and nitrogen oxide already published in Part A [1], this work assessed if carbon monoxide sensors can reach the Data Quality Objective (DQOs) of 25% of uncertainty set in the European Air Quality Directive for indicative methods. As for ozone and nitrogen oxide, it was found for NO, CO and CO2 that the best agreement between sensors and reference measurements was observed for supervised learning techniques compared to linear and multilinear regression.

Acknowledgements

The authors wish to acknowledge the collaboration of our JRC colleagues C. Grüning and G. Manca for the CO2 measurements and F. Lagler, N. R. Jensen and A. Dell’Acqua for carrying out air pollution measurements. This study was carried out within the EMRP Joint Research Project ENV01 MACPoll. The EMRP is jointly funded by the EMRP participating countries within EURAMET and the European Union.

SENSAVAN
NOySI
Departamento de Acústica y Evaluación No Destructiva (DAEND)
  • GAA: Grupo de Acústica ambiental
  • G CARMA: Grupo de Caracterización de materiales mediante evaluación no destructiva
  • ULAB: Ultrasonidos para el análisis de líquidos y bioingeniería
Departamento de Tecnologías de la Información y Las Comunicaciones (DTIC)
  • GiCP: Grupo de investigación en Ciberseguridad y Protección de la Privacidad
  • GICSI: Grupo de investigación en Criptología y Seguridad de la Información
    • LCQE: Laboratorio de Comunicaciones Cuánticas
  • PSUM: Grupo de Procesamiento de Señal en sistemas Ultrasónicos Multicanal
Departamento de Sensores y Sistemas Ultrasónicos (DSSU)
  • GSTU: Grupo de Sistemas y tecnologías ultrasónicas
  • NoySI: Grupo de Nanosensores y Sistemas Inteligentes
  • RESULT: Resonadores ultrasónicos para cavitación y micromanipulación
  • SENSAVAN: Grupo de Tecnología de Sensores Avanzados
  • QE: Electrónica Cuántica
Laboratorios
  • Laboratorio de Acústica
  • Laboratorio de Metrología Ultrasónica Médica (LMUM)
  • Laboratorio de Comunicaciones Cuánticas
  • Laboratory for International Collaboration in Advanced Biophotonics Imaging

Instituto de Tecnologías Físicas y de la Información Leonardo Torres Quevedo  - ITEFI
C/ Serrano, 144. 28006 - Madrid • Tel.: (+34) 91 561 88 06  Contacto  •  Intranet
EDIFICIO PARCIALMENTE ACCESIBLE POR PERSONAS CON MOVILIDAD REDUCIDA