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Vitenskapelig tidsskriftspublikasjon

A framework for advancing independent air quality sensor measurements via transparent data generating process classification

Bannan, Thomas J.; Chacón-Mateos, Miriam; Edwards, Pete M.; Ferracci, Valerio; Kilic, Dogushan; Lewis, Alastair C.; Malings, Carl; Martin, Nicholas A.; Popoola, Olalekan; Rosales, Colleen Marciel F.; Schmitz, Sean; Schneidemesser, Erika von; Schneider, Philipp

Publikasjonsdetaljer

Tidsskrift: npj Climate and Atmospheric Science, vol. 8, 285, 2025

Doi: doi.org/10.1038/s41612-025-01161-2
Arkiv: hdl.handle.net/11250/3212328

Sammendrag:
We propose operational definitions and a classification framework for air quality sensor-derived data, thereby aiding users in interpreting and selecting suitable data products for their applications. We focus on differentiating independent sensor measurements (ISM) from other data products, emphasizing transparency and traceability. Recommendations are provided for manufacturers, academia, and standardization bodies to adopt these definitions, fostering data product differentiation and incentivizing the development of more robust, reliable sensor hardware.