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Titel |
Global NOx emission estimates using OMI NO2 data and ensemble-based data assimilation |
VerfasserIn |
Kazuyuki Miyazaki, Henk Eskes |
Konferenz |
EGU General Assembly 2011
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Medientyp |
Artikel
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Sprache |
Englisch
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Digitales Dokument |
PDF |
Erschienen |
In: GRA - Volume 13 (2011) |
Datensatznummer |
250052625
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Zusammenfassung |
A data assimilation system has been developed to analyze global NOx emissions using OMI
tropospheric NO2 column data and a global chemical transport model CHASER. The data
assimilation system employs an ensemble Kalman filter approach to analyze the surface
emission of NOx. OMI tropospheric NO2 column data retrieved at KNMI with its averaging
kernel and retrieval error information are used to optimize daily NO2 emissions at every
model grid point with a horizontal resolution of 2.8 degree, during the year 2005-2006. A
super observation approach is employed to fill spatial-scale gaps between the model and OMI
data, which provides representative data for data assimilation. In the data assimilation system,
surface emissions and its ensemble perturbations are analyzed using OMI data during
data assimilation step, providing an ensemble of emissions used for next forecast
step. Then, concentrations of chemical species are simulated using the updated
emission at forecast step. This approach allows to accumulate observation information
through data assimilation cycle and to represent indirect relationship (caused by
chemical and transport processes) between the emission and tropospheric column
concentration.
The data assimilation results are validated by comparing analyzed NO2 concentrations
with independent data, tropospheric columns obtained from SCIAMACHY and vertical
profiles obtained during INTEX-B aircraft campaign. We have confirmed that spatiotemporal
variations in NO2 concentration are more realistically represented by the data assimilation
than the model simulation, by correcting a priori emission obtained based on bottom-up
estimations. The data assimilation tends to increase NOx emissions over Southern and
Western Europe, Eastern China, Eastern and Southern USA, and Central Africa, and to
decrease it over Northern and Eastern Europe, and Japan, during both winter and
summer. OmF (or OmA) analysis revealed great reductions in both bias and mean
difference by the data assimilation, especially over polluted areas. Comparisons
with vertical profiles measured from INTEX-B imply that the assimilation of OMI
tropospheric NO2 column data provides a distinct improvement in the NO2 analysis with a
slight improvement in the ozone analysis in the lower troposphere. These results
demonstrate improvements in NOx emissions by the data assimilation. Moreover, the
augmentation of chemically related species (e.g., ozone, HNO3) into a state vector and/or
multi-species data assimilation may be able to further improve the chemical balance of
analyzed fields and NOx emission estimates. The impacts of augmenting various
species and of assimilating OMI NO2 data obtained from different retrievals and
other chemical species data (e.g., satellite ozone data) will be further discussed. |
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