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Data Assimilation and Air Quality Forecasting

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Author: Eskes, H. · Timmermans, R. · Curier, L. · Ruyter de Wildt, M. de · Segers, A. · Sauter, F. · Schaap, M.
Type:bookPart
Date:2014
Publisher: Springer Netherlands
Place: Dordrecht
Source:Steyn, D.G.Builtjes, P.J.H.Timmermans, R.M.A., Air Pollution Modeling and its Application XXII, 189-192
series:
NATO Science for Peace and Security Series C: Environmental Security
Identifier: 526142
doi: doi:10.1007/978-94-007-5577-2__32
ISBN: 978-94-007-5577-2
Keywords: Geosciences · Geological Survey Netherlands · Energy · Urban Mobility & Environment · CAS - Climate, Air and Sustainability · ELSS - Earth, Life and Social Sciences

Abstract

Lotos-Euros is a chemistry transportmodel developed in the Netherlands, and is used for air quality assessments and forecasts. Operational air quality forecasts for the Netherlands concerning ozone and PM10 are made available on the RIVM webpage (http://www.lml.rivm.nl/verw.html) and are used to warn the population in case of predicted exceedances of air quality standards. Lotos-Euros is also contributing to the model-ensemble based air quality forecasts for Europe (MACC project, http://macc-raq.gmes-atmosphere.eu/index.php?op=get). Currently, the system is expanded to assimilate routine surface observations from European networks as well as satellite observations such as OMI NO2. The Ozone Monitoring Instrument (OMI) is a Dutch-Finnish instrument on the NASA EOS-Aura mission, and has a capability to detect boundary-layer NO2 with a unique resolution of about 20 km. The assimilation in Lotos-Euros is based on the ensemble Kalman filter technique in which model parameters such as the NOx emissions, VOC emissions, PM sources, ozone boundary conditions and/or deposition velocities are adjusted to improve the comparison with the observations. In our contribution we will discuss the experiences with the assimilation of NO2 tropospheric columns from the OMI instrument. In particular we will focus on the model-OMI comparisons over Europe, the analysis improvements, the analysed emissions and the impact of OMI NO2 data assimilation on other constituents such as ozone.