遇见数据集

Ultrafine Particle Dataset Collected by the OpenSense Zurich Mobile Sensor Network

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Zenodo2018-09-13 更新2026-04-07 收录
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<strong>Ultrafine Particle Dataset Collected by the OpenSense Zurich Mobile Sensor Network</strong> This dataset contains over 2 and a half years (04/2012-12/2014, &gt;36 Mio samples) worth of ultra-fine particle (UFP) concentration measurements collected by a mobile senor network. The sensors are mounted on top of 10 streetcars in the city of Zurich, Switzerland. <strong>Hardware:</strong> <strong>Ultrafine particle sensor</strong>: MiniDiSC (see also: Martin Fierz et al. Design, Calibration, and Field Performance of a Miniature Diffusion Size Classifier. Aerosol Science and Technology, Volume 45, 2011.) <strong>GPS receiver</strong>: u-blox EVK-6p<br> <strong>Sensor Data<br> ------------------</strong><br> <strong>ufp_data</strong><strong>*.csv column format:</strong> Time of day: yyyy.mm.dd HH:MM Latitude WGS84 Longitude WGS84 HDOP: horizontal dilution of precision, uncertainty of the GPS position Tram ID Number of particles [#/ccm] Average particle diameter [nm] LDSA: lung deposited surface area [um2 /cm3] <strong>Data quality:</strong><br> The data has been post-processed by performing a periodic null-offset calibration and filtering samples during malfunction. <strong>High-Resolution Maps<br> --------------------------------</strong> The data has been used to create high-resolution ultrafine particle concentration maps. Four maps, which show the seasonal average particle concentration over seasonal periods, can be found in ufp_seasonal_maps_201204_201304.csv. <strong>ufp_map*.csv column format:</strong> Latitude WGS84 Longitude WGS84 Estimated number of particles [#/ccm] <strong>Map quality</strong> Please have a look at the papers in References 1. and 2. (Hasenfratz et al. 2014 and 2015) for a detailed evaluation of the maps. <strong>References<br> ----------------</strong><br> The dataset has been used and is described in more detail in the following publications: David Hasenfratz et al.<em> Pushing the Spatio-Temporal Resolution Limit of Urban Air Pollution Maps.</em> IEEE International Conference on Pervasive Computing and Communications (PerCom). Budapest, Hungary, March 2014. Best Paper Award. David Hasenfratz et al. <em>Deriving High-Resolution Urban Air Pollution Maps Using Mobile Sensor Nodes. </em>Pervasive and Mobile Computing. Elsevier, 2015. David Hasenfratz et al. <em>Demo Abstract: Health-Optimal Routing in Urban Areas.</em> ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN). Seattle, USA, April 2015. Michael Müller et al. <em>Statistical modelling of particle number concentration in Zurich at high spatio-temporal resolution utilizing data from a mobile sensor network. </em>Atmospheric Environment. Elsevier, 2016. For further information, visit: http://www.opensense.ethz.ch

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2018-09-13
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