High-resolution maps of air pollutants

Nitrogen dioxide (NO2) is an important air pollutant with a high spatial and temporal variability. High-resolution NO2 maps with smaller than 1 km resolution of near-surface NO2 concentrations are an important tool for air quality monitoring in urban areas and in epidemiological studies that analyse the impact of air pollutants on public health. We use different approach for retrieving high-resolution maps from airborne and space-based instruments.
Downscaling satellite observations
https://www.empa.ch/documents/56101/617885/DownNO2_small.jpg/98b076cd-fdad-4c83-842e-c52ac77dd7fb?t=1630051233000

The Sentinel-5P/TROPOMI satellite instruments measures NO2 maps at 6 km resolution, which is already quite high but still coarser than the required 1 km resolution. In addition, since remote sensing instruments measure vertical columns instead of near-surface concentrations, we developed machine learning algorithm that downscale TROPOMI NO2 observations. Our algorithm creates hourly maps of griddied near-surface NO2 concentrations at 100 m resolution. We used the extreme gradient-boosted tree ensemble method, which was trained with in situ NO2 ground measurements to predict NO2 concentrations using NO2 satellite images, land use data, meteorological fields and topographical information. The maps can be used as input for air pollution control and epidemiological studies.

GAW Symposium 2021, Session 3 from Minsu Kim on Vimeo.

Airborne imaging remote sensing
https://www.empa.ch/documents/56101/617885/apex_no2_zurich_small.png/c78a17a2-eac2-418f-8543-8c3f348a5836?t=1492026054000
Airborne imagers already have a spatial resolution of about 100 m, but they measure the vertically integrated column instead of near-surface concentrations. We use APEX NO2 measurements combined with 3D radiative transfer and city-scale dispersion modelling to retrieve NO2 vertically integrated columns and relate them to near surface-concentrations.
Publications
  • Kim, M.; Brunner, D.; Kuhlmann, G. Importance of satellite observations for high-resolution mapping of near-surface NO2 by machine learning. Remote Sens. Environ. 2021, 264, 112573 (13 pp.). https://doi.org/10.1016/j.rse.2021.112573

PD Dr. Gerrit Kuhlmann
Senior Scientist

Telefon: +41 58 765 4753

Prof. Dr. Dominik Brunner

Telefon: +41 58 765 4944