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

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Chaofan Li*, Matthias Budde, Paul Tremper, Klaus Schafer, Johannes Riesterer, Johanna Redelstein, Erik Petersen, Mohamed Khedr, Xiangsheng Liu, Marcel Kopke, Sajjad Hussain, Felix Ernst, Michal Kowalski, Markus Pesch, Johannes Werhahn, Markus Hank, Andreas Philipp, Josef Cyrys, Jürgen Schnelle-Kreis, Hans Grimm, Volker Ziegler, Annete Peters, Stefan Emeis, Till Riedel, Michael Beigl

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.

Keywords: Air Quality; Dataset; Aerosol; Particulate Matter; Open Data

Proscience vol. 8

Pp 1-10

DOI: 10.14644/dust2021.001