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SmartAQnet 2020: A New Open Urban Air Quality Dataset from Heterogeneous PM Sensors

Li, Chaofan ORCID iD icon 1; Budde, Matthias; Tremper, Paul ORCID iD icon 1; Schäfer, Klaus; Riesterer, Johannes; Redelstein, Johanna; Petersen, Erik; Khedr, Mohamed; Liu, Xiangsheng; Köpke, Marcel; Hussain, Sajjad; Ernst, Felix 2; Kowalski, Michal; Pesch, Markus; Werhahn, Johannes; Hank, Markus; Philipp, Andreas; Cyrys, Josef; Schnelle-Kreis, Jürgen; ... mehr

Abstract:

The increasing attention paid to urban air quality modeling places higher requirements on urban air quality datasets. This article introduces a new urban air quality dataset—the SmartAQnet2020 dataset—which has a large span and high resolution in both time and space dimensions. The dataset contains 248,572,003 observations recorded by over 180 individual measurement devices, including ceilometers, Radio Acoustic Sounding System (RASS), mid- and low-cost stationary measuring equipment equipped with meteorological sensors and particle counters, and low-weight portable measuring equipment mounted on different platforms such as trolley, bike, and UAV.


Postprint §
DOI: 10.5445/IR/1000152095
Veröffentlicht am 19.12.2022
Originalveröffentlichung
DOI: 10.14644/dust2021.001
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Meteorologie und Klimaforschung – Atmosphärische Umweltforschung (IMK-IFU)
Institut für Telematik (TM)
Scientific Computing Center (SCC)
Publikationstyp Zeitschriftenaufsatz
Publikationsdatum 21.03.2022
Sprache Englisch
Identifikator ISSN: 2283-5954
KITopen-ID: 1000152095
HGF-Programm 46.21.05 (POF IV, LK 01) HMC
Erschienen in ProScience
Verlag Digilabs S.a.s.
Band 8
Projektinformation HEPTA (HGF, HGF IVF2016 STRATPART, PIE-0016)
Bemerkung zur Veröffentlichung 4th International Conference on Atmospheric Dust - DUST2021, Monopoli, Italien, 4-7.10.2021
Externe Relationen Abstract/Volltext
Konferenz
Video
Forschungsdaten/Software
Schlagwörter Air Quality; Dataset; Aerosol; Particulate Matter; Open Data
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