A0823
Title: Spatial correction of low-cost sensors observations for fusion of air quality measurements
Authors: Jean-Michel Poggi - University Paris-Saclay Orsay (France) [presenting]
Bruno Portier - INSA Rouen Normandie (France)
Michel Bobbia - Atmo Normandie (France)
Abstract: The context is the statistical fusion of air quality measurements coming from different monitoring networks. The first one consists of high-quality reference sensors, and the second consists of low-quality micro-sensors. Pollution maps are obtained by correcting the output of numerical models with the measurements from the monitoring stations of the air quality networks. Increasing the density of sensors would then improve the quality of the reconstructed map. Usually, a geostatistical approach is used for the fusion of the measurements, but the first step is to correct the measurements of the micro-sensors, thanks to those given by the reference sensors, by prior offline fitting of a model issued from a costly and sometimes impossible colocation period. The proposal complements these approaches by considering the online spatial correction of microsensors. The basic idea is to use the reference network to correct the measurements of network 2: first, the reference measurements are estimated by kriging only the measurements of network 2; then, the residuals of the estimation on network 1 are calculated; and finally, the correction to be applied to the microsensors is obtained by kriging these residuals. This sequence of steps can then be iterated or not, and the role of the networks can be alternated or not during the iterations. This algorithm is first presented, then studied by simulation and finally applied to a real data set.
