Unique real-time sensor network for densely monitoring air pollutants in Munich

With the help of 50 self-developed sensor systems, the spatial distribution of air pollutants such as NOx and particulate matter will be monitored in the inner city of Munich. This will help us to understand the metabolism of urban air pollutants.

Funded by the Bavarian State Ministry of the Environment and Consumer Protection we are currently setting up a densely populated sensor network to monitor air pollutants in Munich.

Our group has developed a compact and stand-alone sensor system that is automatically measuring nitrogen dioxide (NO2), nitrogen monoxide (NO), carbon monoxide (CO), ozone (O3) and particulate matter (PM) using electrochemical cells (for all gases) and optical particle counter (for PM). All systems are connected to the internet (Internet of Things, IoT) to obtain the data in real-time. Our server will analyze these data and create a real-time air quality map of the study area (Maxvorstadt) with a very high spatial and temporal resolution.

In order to ensure high data quality, the sensor are calibrated twice per week using highly precise reference instruments that are also used in the governmental air quality monitoring stations, combined with novel machine learning algorithms. Until the mid of 2020, the network will be set up to continuously monitor the air quality in Munich in a much higher spatial resolution as it is done nowadays.

Zollitsch, D., Chen, J., Dietrich, F., Voggenreiter, B., Setili, L. and Wenig, M.: Low-Cost Air Quality Sensor Network in Munich, in Geophysical Research Abstracts, https://doi.org/10.5194/egusphere-egu2020-19276, 2020.

Zhu, Y., Chen, J., Bi, X., Kuhlmann, G., Chan, K. L., Dietrich, F., Brunner, D., Ye, S., and Wenig, M.: Spatial and temporal representativeness of point measurements for nitrogen dioxide pollution levels in cities, Atmos. Chem. Phys. Discuss., doi.org/10.5194/acp-2019-1198, 2020.