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By i kveldslys



More than half of the world’s population is living in cities. According to the WHO air quality database, 80% of people living in urban areas that monitor air pollution are exposed to air quality levels that exceed WHO limits. Narrowing down to cities in low- and middle-income countries with more than 100 000 inhabitants, this number increases to 98%. To revert urban air pollution a clear understanding of the local situation is essential. Low-income cities, which are most impacted by unhealthy air, usually have less resources available for a good reference network. It is here where a combination of low-cost sensors and satellite data can make a difference.

Integration of different data sources of air quality observations is far from trivial. Observations about air quality are available from a wide variety of data sources, however they all have different sampling coverage and frequencies as well as different spatial representativities. Low-cost air quality sensors have emerged over recent years and provide a possibility for acquiring air quality observations at high spatial detail in urban areas, however they often suffer from substantial uncertainties. Satellites observe air pollution in the troposphere, and its relation with surface concentrations must first be solved for urban air quality monitoring applications. So far, only very few studies aim at joining heterogeneous data sources of urban air quality, and to our knowledge no previous work has provided practical solutions which can be implemented in cities everywhere.

The primary scientific objective of the proposed project is to investigate how Sentinel-5P/TROPOMI satellite data (especially tropospheric NO2 columns) can be better exploited for monitoring and mapping urban air quality at scales relevant for human exposure. The end goal is to deliver hourly air quality maps of NO2 for our selected test cities at 100 m resolution. The chosen cities (Oslo and Madrid) have extensive reference monitoring stations for air quality, and, in the case of Oslo, embedded low-cost sensor networks measuring NO2. This enables us to test the performance of the assimilation of TROPOMI observations under different in-situ network configurations. It will show us what the added value of satellite observations will be when these assimilation systems are applied to cities with poorer or non-existent monitoring networks.