Title
A multi-component data assimilation experiment directed to sulphur dioxide and sulphate over Europe
Author
Barbu, A.L.
Segers, A.J.
Schaap, M.
Heemink, A.W.
Builtjes, P.J.H.
TNO Bouw en Ondergrond
Publication year
2009
Abstract
Fine particulate matter (PM) is relevant for human health and its components are associated with climate effects. The performance of chemistry transport models for PM, its components and precursor gases is relatively poor. The use of these models to assess the state of the atmosphere can be strengthened using data assimilation. This study focuses on simultaneous assimilation of sulphate and its precursor gas sulphur dioxide into the regional chemistry transport model LOTOS-EUROS using an ensemble Kalman filter. The process of going from a single component setup for SO2 or SO4 to an experiment in which both components are assimilated simultaneously is illustrated. In these experiments, solely emissions, or a combination of emissions and the conversion rates between SO2 and SO4 were considered uncertain. In general, the use of sequential data assimilation for the estimation of the sulphur dioxide and sulphate distribution over Europe is shown to be beneficial. However, the single component experiments gave contradicting results in direction in which the emissions are adjusted by the filter showing the limitations of such applications. The estimates of the pollutant concentrations in a multi-component assimilation have found to be more realistic. We discuss the behavior of the assimilation system for this application. The model uncertainty definition is shown to be a critical parameter. The increased complexity associated with the simultaneous assimilation of strongly related species requires a very careful specification of the experiment, which will be the main challenge in the future data assimilation applications. © 2008 Elsevier Ltd. All rights reserved.
Subject
Environment
Data assimilation
Ensemble Kalman filter
LOTOS-EUROS model
Sulphate
Sulphur dioxide
Air filters
Applications
Control theory
Experiments
Kalman filters
Nonmetals
Permanent magnets
Sulfur
Sulfur determination
Uncertainty analysis
Data assimilation
Ensemble Kalman filter
LOTOS-EUROS model
Sulphate
Sulphur dioxide
Sulfur dioxide
atmospheric modeling
climate effect
data assimilation
health impact
Kalman filter
particulate matter
pollutant transport
pollution monitoring
sulfate
sulfur dioxide
Eurasia
Europe
To reference this document use:
http://resolver.tudelft.nl/uuid:99bb4401-b9dc-41e8-a8fb-3d0c00c39ee7
TNO identifier
241423
ISSN
1352-2310
Source
Atmospheric Environment, 43 (9), 1622-1631
Document type
article