An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation

Lasse Johansson; Ari Karppinen; Mona Kurppa; Anu Kousa; Jarkko V Niemi; Jaakko Kukkonen

doi:10.1016/j.envsoft.2022.105460

An operational urban air quality model ENFUSER, based on dispersion modelling and data assimilation

Environ Model Softw. 2022 Oct:156:105460. doi: 10.1016/j.envsoft.2022.105460.

Authors

Lasse Johansson¹, Ari Karppinen¹, Mona Kurppa¹, Anu Kousa², Jarkko V Niemi², Jaakko Kukkonen^{1

3}

Affiliations

¹ Atmospheric Composition Research, Finnish Meteorological Institute, Helsinki, Finland.
² Helsinki Region Environmental Services Authority HSY, Ilmalantori 1, FI-00240, Helsinki, Finland.
³ Centre for Atmospheric and Climate Physics Research, And Centre for Climate Change Research, University of Hertfordshire, College Lane, Hatfield, AL10 9AB, UK.

Abstract

An operational urban air quality modelling system ENFUSER is presented with an evaluation against measured data. ENFUSER combines several dispersion modelling approaches, uses data assimilation, and continuously extracts information from online, global open-access sources. The modelling area is described with a combination of geographic datasets. These GIS datasets are globally available with open access, and therefore the model can be applied worldwide. Urban scale dispersion is addressed with a combination of Gaussian puff and Gaussian plume modelling, and long-range transport of pollutants is accounted for via a separate regional model. The presented data assimilation method, which supports the use of AQ sensors and incorporates a longer-term learning mechanism, adjusts emission factors and the regional background values on an hourly basis. The model can be used with reasonable accuracy also in urban areas, for which detailed emissions inventories would not be available, due to the data assimilation capabilities.

Keywords: Air quality; Data assimilation; Dispersion modelling.