Traffic reduction and air-quality improvement are among the main goals of several projects worldwide. This article presents a fine particle monitoring based on heterogeneous air quality mobile sensors and an advanced data concentrator (AdDC), so that the level of pollution in the urban area, where few accurate fixed measurement stations are present, can be assessed with better accuracy. Some urban buses are used to carry low-cost sensors, thus implementing a mobile sensor network and increasing the time and space resolution of air quality information. The data obtained by these low-cost sensors are significantly affected by uncertainties, also due to atmospheric factors, such as humidity. The proposed AdDC processes all the obtained measurements and exploits the information obtained by the accurate fixed stations to improve the accuracy of the low-cost mobile sensors. In particular, a new compensation methodology, specifically targeted to the fine particles monitoring, is proposed. The monitoring of relative humidity is added, with the relevant on-the-fly calibration, so that the measured values can be used to correct the effects of humidity on PM2.5 sensors. The validity of the proposed system is proven by means of simulations performed on an appropriate set up.

Improved Fine Particles Monitoring in Smart Cities by Means of Advanced Data Concentrator

Castello P.;Muscas C.;Pegoraro P. A.;Sulis S.
2021-01-01

Abstract

Traffic reduction and air-quality improvement are among the main goals of several projects worldwide. This article presents a fine particle monitoring based on heterogeneous air quality mobile sensors and an advanced data concentrator (AdDC), so that the level of pollution in the urban area, where few accurate fixed measurement stations are present, can be assessed with better accuracy. Some urban buses are used to carry low-cost sensors, thus implementing a mobile sensor network and increasing the time and space resolution of air quality information. The data obtained by these low-cost sensors are significantly affected by uncertainties, also due to atmospheric factors, such as humidity. The proposed AdDC processes all the obtained measurements and exploits the information obtained by the accurate fixed stations to improve the accuracy of the low-cost mobile sensors. In particular, a new compensation methodology, specifically targeted to the fine particles monitoring, is proposed. The monitoring of relative humidity is added, with the relevant on-the-fly calibration, so that the measured values can be used to correct the effects of humidity on PM2.5 sensors. The validity of the proposed system is proven by means of simulations performed on an appropriate set up.
2021
Air pollution sensors; air quality; data processing; fine particles monitoring; measurement uncertainty; public transportation; smart city
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11584/304812
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