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Updated: May 1, 2026

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QUANT: a long-term multi-city commercial air sensor dataset for performance evaluation.

Sebastian Diez1,2, Stuart Lacy3, Josefina Urquiza4,5

  • 1Centro de Investigación en Tecnologías para la Sociedad, Universidad del Desarrollo, Santiago, CP, 7550000, Chile. sebastian.diez@udd.cl.

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The QUANT study evaluated 49 commercial air quality sensor systems, creating a large open-access dataset for analyzing sensor performance in urban environments. This data aids policymakers and manufacturers in improving air quality monitoring and technology.

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Area of Science:

  • Environmental Science
  • Atmospheric Chemistry
  • Sensor Technology

Background:

  • Commercial air quality sensors are increasingly used, but their real-world performance requires extensive evaluation.
  • A comprehensive, open-access dataset is needed to benchmark sensor systems and inform their deployment.

Purpose of the Study:

  • To conduct the most extensive open-access evaluation of commercial air quality sensor systems.
  • To create a high-quality, publicly accessible dataset of sensor performance across diverse urban conditions.

Main Methods:

  • Evaluated 49 sensor systems from 14 manufacturers over three years at three UK urban sites.
  • Collected high time-resolution data for gases (NO, NO2, O3, CO, CO2), particulate matter (PM1, PM2.5, PM10), and meteorological parameters.
  • Enhanced dataset integrity using reference monitors and calibrated manufacturer data.

Main Results:

  • Generated a unique, open-access dataset detailing the performance of numerous commercial air quality sensors.
  • Demonstrated the dataset's utility in supporting the development of a UK code of practice and sensor certification.

Conclusions:

  • The QUANT study provides a robust resource for analyzing real-world air quality sensor performance.
  • The open-access dataset empowers stakeholders to make informed decisions regarding sensor technology and air quality management.