QUANT: A Three-Year, Multi-City Air Quality Dataset of Commercial Air Sensors and Reference Data for Performance Evaluation

The QUANT dataset embodies a thorough initiative to assess the performance of commercial air quality sensors relative to reference measurements over three years (December 2019 to October 2022), across three UK urban sites: London, Manchester, and York. This collection showcases a wide spectrum of meteorological and ambient conditions, offering a rich dataset for detailed analysis. As a pivotal component of the UK Research and Innovation Clean Air programme, QUANT's structured methodology scrutinized 49 sensor systems from 14 manufacturers. The project unfolded in two phases: the Main QUANT phase, dedicated to the prolonged evaluation of selected sensor devices, and the Wider Participation Study, which extended an invitation to commercial entities for an equitable evaluation. This dataset integrates hourly records from (i) reference monitors at each site, (ii) QUANT sensor data, and (iii) specially deployed duplicate reference instruments, essential for delving into sensor performance subtleties and calibration accuracy. It encompasses measurements of gases (NO, NO2, O3), particulate matter (PM1, PM2.5, PM10), and critical meteorological parameters (humidity, temperature, atmospheric pressure). Comprising data files with both sensor and reference information, alongside metadata files that delineate locations, deployment dates, and details of sensors and reference instruments, this dataset provides a holistic resource for air quality monitoring and evaluative studies.

External deposit wit Zenodo.