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

Laurent Spinelle, Michel Gerboles, Maria Gabriella Villani, Manuel Aleixandre, Fausto Bonavitacola

Research output: Contribution to journalArticle

87 Citations (Scopus)


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 CO2that the best agreement between sensors and reference measurements was observed for supervised learning techniques compared to linear and multilinear regression.
Original languageEnglish
Pages (from-to)706 - 715
Number of pages10
JournalSensors and Actuators, B: Chemical
Publication statusPublished - 1 Jan 2017


All Science Journal Classification (ASJC) codes

  • Electronic, Optical and Magnetic Materials
  • Instrumentation
  • Condensed Matter Physics
  • Surfaces, Coatings and Films
  • Metals and Alloys
  • Electrical and Electronic Engineering
  • Materials Chemistry

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