The impact of aviation emissions to urban air quality in Europe – Detailed airport-city analysis
report
Aviation causes emissions of NOx, SO2 and PM that have a negative impact on air
quality. To investigate the extent of this impact, simulations with the chemical
transport model (CTM) LOTOS-EUROS (LE) have been performed to model the
atmospheric concentrations of NO2, SO2, PM10 and PM2.5 in 2018. The concentrations
of these pollutants were simulated for six cities in Europe (London, Paris,
Amsterdam, Frankfurt am Main, Munich and Brussels) with large airports (Heathrow,
Charles de Gaulle, Schiphol, Frankfurt am Main, Munich and Zaventem).
For LE, and CTMs in general, the quality of the input data could determine to a
large extent how well modelled atmospheric pollutant concentrations reflect
reality. Arguably the most important of these inputs is the emission dataset, that
describes how quantities of pollutants emissions are temporally and spatially
represented in the model. An initial exploration into the most suitable emission
dataset led to the conclusion that the GrETA (Gridding Emission Tool for ArcGIS)
and ER (Emission Registration) datasets were most equipped for 1x1 km resolution
simulations so should be used whenever available (i.e., Amsterdam, Frankfurt am
Main and Munich). Alternatively, when this set is not available, a CAMS-REG v5.1
1x1 km dataset could be used (London, Paris and Brussels)
quality. To investigate the extent of this impact, simulations with the chemical
transport model (CTM) LOTOS-EUROS (LE) have been performed to model the
atmospheric concentrations of NO2, SO2, PM10 and PM2.5 in 2018. The concentrations
of these pollutants were simulated for six cities in Europe (London, Paris,
Amsterdam, Frankfurt am Main, Munich and Brussels) with large airports (Heathrow,
Charles de Gaulle, Schiphol, Frankfurt am Main, Munich and Zaventem).
For LE, and CTMs in general, the quality of the input data could determine to a
large extent how well modelled atmospheric pollutant concentrations reflect
reality. Arguably the most important of these inputs is the emission dataset, that
describes how quantities of pollutants emissions are temporally and spatially
represented in the model. An initial exploration into the most suitable emission
dataset led to the conclusion that the GrETA (Gridding Emission Tool for ArcGIS)
and ER (Emission Registration) datasets were most equipped for 1x1 km resolution
simulations so should be used whenever available (i.e., Amsterdam, Frankfurt am
Main and Munich). Alternatively, when this set is not available, a CAMS-REG v5.1
1x1 km dataset could be used (London, Paris and Brussels)
Topics
TNO Identifier
995525
Publisher
TNO
Collation
83 p.