Reliable NO2 measurements from low-cost air quality sensors deployed in large networks
Presented By: Geoff Henshaw, Aeroqual
Description: Dense low-cost sensor networks are becoming increasingly popular and offer novel opportunities to measure air quality at the neighbourhood scale in near real-time. However, the success of these networks strongly depends on the reliability of the data. We extend a management and data correction framework previously developed for O3 to NO2 measurements from electrochemical sensors deployed in a dense network in Southern California (~100 sensors). The framework is based on the idea that data from low-cost sensors can be remotely corrected using data from a reliable proxy site (e.g. a regulatory monitoring site). A proxy site is a site where the probability distribution of the measurements of interest is similar to that at the sensor site. A suitable proxy site for NO2 proved to be a site with similar land use (e.g. distance to motorway) characteristics to the sensor site of interest. We show that the three NO2 sensor response parameters, offset, O3 response slope and NO2 response slope can be estimated by minimising the Kullback-Leibler divergence between sensor and proxy NO2 distributions. Using this approach, we were able to remotely detect and correct for sensor drift and improve the accuracy of the data from the electrochemical NO2 sensors. Using the corrected data we were able to detect local-scale effects on air quality that were not captured by the more sparsely distributed stations.