Nov 17, 2017 | 15:00—16:30
Air pollution is traditionally monitored by networks of static measurement stations operated by official authorities. These stations are highly reliable and accurately measure a wide range of air pollutants with expensive analytical instruments. Large size, high price, and laborious maintenance of these complex measurement systems severely limit the number of installations resulting in a low spatial resolution of the available pollution information.
In the last few years, low-cost solid-state gas sensors became available on the market. We integrated these sensors in ten lightweight air quality monitoring stations and deployed them on top of trams in Zurich to increase spatial coverage of the urban area. In this talk I will focus on three main challenges we faced in this deployment: 1) pre-deployment sensor testing and compensation for cross-sensitivities, 2) automatic calibration of low-cost sensors to improve data quality, and 3) data analysis and predictions to construct high resolution air pollution maps.
I will give an overview of the theory behind the developed methods and evaluate their performance on a data set comprising 400 million measurements collected in Zurich over three years. Generated pollution maps received a lot of attention in the local media and are now part of the public service offered by the City of Zurich.