2017
DOI: 10.5194/gmd-10-2471-2017
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An emission module for ICON-ART 2.0: implementation and simulations of acetone

Abstract: Abstract. We present a recently developed emission module for the ICON (ICOsahedral Non-hydrostatic)-ART (Aerosols and Reactive Trace gases) modelling framework. The emission module processes external flux data sets and increments the tracer volume mixing ratios in the boundary layer accordingly.The performance of the emission module is illustrated with simulations of acetone, using a simplified chemical depletion mechanism based on a reaction with OH and photolysis only. In our model setup, we calculate a tro… Show more

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Cited by 25 publications
(28 citation statements)
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“…The ART extensions allow for an online treatment of aerosol dynamics and atmospheric chemistry. The model application of this study is accompanied by significant further developments of the emission parameterizations regarding mineral dust and BVOCs (Weimer et al, 2017). Furthermore, a parameterization for…”
Section: Model Framework and Setupmentioning
confidence: 99%
“…The ART extensions allow for an online treatment of aerosol dynamics and atmospheric chemistry. The model application of this study is accompanied by significant further developments of the emission parameterizations regarding mineral dust and BVOCs (Weimer et al, 2017). Furthermore, a parameterization for…”
Section: Model Framework and Setupmentioning
confidence: 99%
“…These tracers can also be used to investigate fundamental composition-circulation feedbacks. The selection is an extension of the set of parameterisations described in Rieger et al (2015) and Weimer et al (2017).…”
Section: Implementation Of Passive and Chemical Tracers In Icon-artmentioning
confidence: 99%
“…ICON-ART extends the numerical weather and climate prediction system ICON with (gas-phase) chemistry, aerosol dynamics and related feedback processes. A compre-hensive treatment of feedback processes between chemistry, aerosols, clouds and radiation can now be included in recent and future studies (Gasch et al, 2017;Rieger et al, 2017;Weimer et al, 2017;Eckstein et al, 2017).…”
Section: Introductionmentioning
confidence: 99%
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“…The selection is an extension of the set of parameterisations described in Rieger et al (2015) and Weimer et al (2017).…”
mentioning
confidence: 99%