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| Titel |
Determination of NH3 emissions from confined areas using backward Lagrangian stochastic dispersion modelling |
| VerfasserIn |
Christoph Häni, Albrecht Neftel, Jörg Sintermann |
| Konferenz |
EGU General Assembly 2016
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| Medientyp |
Artikel
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| Sprache |
en
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| Digitales Dokument |
PDF |
| Erschienen |
In: GRA - Volume 18 (2016) |
| Datensatznummer |
250126294
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| Publikation (Nr.) |
 EGU/EGU2016-5995.pdf |
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| Zusammenfassung |
| Employing backward Lagrangian stochastic (bLS) dispersion modelling to infer emission
strengths from confined areas using trace gas concentration measurements is a convenient
way of emission estimation from field measurements (see Wilson et al., 2012 and references
therein). The freely available software ’WindTrax’ (www.thunderbeachscientific.com),
providing a graphical interface for the application of a bLS model, has spurred its utilisation
in the past decade. Investigations include mainly methane (CH4) and ammonia (NH3)
emissions based on experimental plots with dimensions between approximately 102 to
104 m2. Whereas for CH4 deposition processes can be neglected, NH3 has a strong affinity
to any surface and is therefore efficiently deposited. Neglecting dry deposition will
underestimate NH3 emissions, e.g. with a standard WindTrax approach. We extended the bLS
model described in Flesch et al. (2004) by a dry deposition process using a simple,
one-directional deposition velocity approach. At every contact of the model trajectories with
ground level (here at the height of the roughness length Zo), deposition is modelled
as:
Fdep = vdep × CT raj
(1)
where vdep represents deposition velocity, and CTraj is the actual concentration of the
specific trajectory at contact. A convenient way to model vdep is given by a resistances
approach. The deposition velocity is modelled as the inverse of the sum of a series of
different resistances to deposition. The aerodynamic resistance is already implicitly included
in the bLS model, thus vdep is given as:
v = ---1---
dep Rb + Rc
(2)
Rb and Rc represent resistances of different model layers between Zo and the surfaces where
deposition take place. With this approach we analysed a dataset from measurements with an
artificial NH3 source that consisted of 36 individual orifices mimicking a circular area source
with a radius of 10 m. The use of three open-path miniDOAS (Sintermann et al., submitted
to AMT) systems allowed to measure a line integrated vertical concentration profile
downwind of the source. The inclusion of the deposition process is necessary for a consistent
interpretation of the measurements.
References
Flesch, T.K., Wilson, J.D., Harper, L.A., Crenna, B.P., Sharpe, R.R., 2004. Deducing
ground-to-air emissions from observed trace gas concentrations: A field trial. J. Appl.
Meteorol. 43 (3), 487–502.
Wilson, J.D., Flesch, T.K., Crenna, B.P., 2012. Estimating Surface-Air Gas Fluxes by
Inverse Dispersion Using a Backward Lagrangian Stochastic Trajectory Model, in: Lin, J.,
Brunner, D., Gerbig, C., Stohl, A., Luhar, A., Webley, P. (Eds.), Lagrangian Modeling of
the Atmosphere. American Geophysical Union, Washington, D. C., pp. 149–162. |
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