Issue |
E3S Web Conf.
Volume 116, 2019
International Conference on Advances in Energy Systems and Environmental Engineering (ASEE19)
|
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Article Number | 00004 | |
Number of page(s) | 8 | |
DOI | https://doi.org/10.1051/e3sconf/201911600004 | |
Published online | 24 September 2019 |
Sensor network for PM2.5 measurements on an academic campus area
1
Wrocław University of Science and Technology, Faculty of Environmental Engineering, Wyb. Wyspianskiego 27, 50-370 Wrocław, Poland
2
INSYSPOM, ul. Duńska 9, 54-427 Wrocław, Poland
3
Wrocław University of Science and Technology, Faculty of Computer Science and Management, Wyb. Wyspianskiego 27, 50-370 Wrocław, Poland
* Corresponding author: marek.badura@pwr.edu.pl
Fine particulate matter (PM2.5) pose a serious threat to health. Therefore it should be monitored to assess its health impacts and to take actions to reduce its pollution. However, the traditional regulatory measuring stations are not able to capture the spatial and temporal variability of PM2.5 concentrations. The opportunity to improve the resolution of PM2.5 data is based on dense networks of miniaturized low-cost sensors. The article presents the sensor network for campus area of Wrocław University of Science and Technology. This system consists of 20 sensor nodes, distributed both on a narrow scale (14 devices on the main campus area) and on a wide scale (devices on campuses in distant parts of the city). Sensor devices have been equipped with optical sensors A003 from Plantower company and with heated inlets. Dedicated website with a map is used to present the up-to-date information about air quality to the public. Messages on air quality are based on air quality index, calculated every 15 minutes. The article demonstrates also few results of preliminary measurements, when episodes of elevated PM2.5 concentrations were observed. Sensor nodes proved to be an useful tool to monitor the changes of air pollution during such events.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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