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| Titel |
Dynamical parameter estimation for a street-canyon air pollution model |
| VerfasserIn |
Jeremy Silver, Jørgen Brandt, Matthias Ketzel |
| 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 |
250049718
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| Zusammenfassung |
| The Operational Street Pollution Model (OSPM) is a street-scale air pollution model for
urban canyons [1] that is widely used in over than 30 cities in more than 17 countries
worldwide [4]. It models the contribution from traffic emissions of a single street to receptor
points at the building façade, and requires as input the city background concentration levels,
street configuration and traffic data. The model is based on a parameterisation of the
important processes within the street canyon (e.g., recirculation vortex, direct plume from
vehicle emissions, traffic produced turbulence, simple NO-NO2 chemistry), with the
assumption of equilibrium for each 1-hour time-step. This assumption is justified due to the
relatively short residence times of the traffic pollution in such street canyons under common
meteorological conditions. As such, there is no dependence in the model states from one
time-step to the next.
We explored the potential for dynamical parameter estimation with the OSPM, using
techniques from data assimilation. In this framework, the time-dependence in the model
states (e.g., concentrations of CO, NO2) results from the dynamical estimation of certain
model parameters (e.g., roughness height, emission factors, fraction of NOx emitted as
NO2) that are otherwise treated as constants. The hypothesis under consideration
is that dynamical parameter estimates can improve the quality of the operational
street pollution forecasts using OSPM in the air-pollution forecasting system THOR
[2].
We implemented an ensemble Kalman filter [3] to dynamically estimate model
parameters. A training period was used during which model parameters were estimated,
followed by a test period when the model forecasts were used for validation. We will present
the results from a series of experiments, and discuss the challenges of parameter estimation in
this context.
References
[1]Â Â Â Berkowicz R. (2000) OSPM – A parameterised street pollution model,
Environmental Monitoring and Assessment, Vol. 65, pp. 323-331.
[2]Â Â Â Brandt, J., Christensen J. H., Frohn L. M. , Palmgren F., Berkowicz R. and
Zlatev Z. (2001) Operational air pollution forecasts from European to local scale.
Atmospheric Environment, Vol. 35, Sup. No. 1, pp. S91-S98, 2001
[3]Â Â Â Evensen, G. (2009) Data Assimilation: The Ensemble Kalman Filter (second
edition). Springer-Verlag, Heidelberg, Germany.
[4]Â Â Â Kakosimos K.E., Hertel O., Ketzel M. and Berkowicz R. (2010) Operational
Street Pollution Model (OSPM) – a review of performed validation studies, and
future prospects. Environmental Chemistry, Vol. 7, 485-503. |
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