Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)

In addition to CO 2 , the climate impact of aviation is strongly influenced by non-CO 2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO 2 emission effects...

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Published in:Geoscientific Model Development
Main Authors: V. Grewe, C. Frömming, S. Matthes, S. Brinkop, M. Ponater, S. Dietmüller, P. Jöckel, H. Garny, E. Tsati, K. Dahlmann, O. A. Søvde, J. Fuglestvedt, T. K. Berntsen, K. P. Shine, E. A. Irvine, T. Champougny, P. Hullah
Format: Article in Journal/Newspaper
Language:English
Published: Copernicus Publications 2014
Subjects:
Online Access:https://doi.org/10.5194/gmd-7-175-2014
https://doaj.org/article/be6fe06cff9940f298ac87f96d91cbc2
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spelling ftdoajarticles:oai:doaj.org/article:be6fe06cff9940f298ac87f96d91cbc2 2023-05-15T17:36:51+02:00 Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0) V. Grewe C. Frömming S. Matthes S. Brinkop M. Ponater S. Dietmüller P. Jöckel H. Garny E. Tsati K. Dahlmann O. A. Søvde J. Fuglestvedt T. K. Berntsen K. P. Shine E. A. Irvine T. Champougny P. Hullah 2014-01-01T00:00:00Z https://doi.org/10.5194/gmd-7-175-2014 https://doaj.org/article/be6fe06cff9940f298ac87f96d91cbc2 EN eng Copernicus Publications http://www.geosci-model-dev.net/7/175/2014/gmd-7-175-2014.pdf https://doaj.org/toc/1991-959X https://doaj.org/toc/1991-9603 1991-959X 1991-9603 doi:10.5194/gmd-7-175-2014 https://doaj.org/article/be6fe06cff9940f298ac87f96d91cbc2 Geoscientific Model Development, Vol 7, Iss 1, Pp 175-201 (2014) Geology QE1-996.5 article 2014 ftdoajarticles https://doi.org/10.5194/gmd-7-175-2014 2022-12-30T21:46:48Z In addition to CO 2 , the climate impact of aviation is strongly influenced by non-CO 2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO 2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number ... Article in Journal/Newspaper North Atlantic Directory of Open Access Journals: DOAJ Articles Geoscientific Model Development 7 1 175 201
institution Open Polar
collection Directory of Open Access Journals: DOAJ Articles
op_collection_id ftdoajarticles
language English
topic Geology
QE1-996.5
spellingShingle Geology
QE1-996.5
V. Grewe
C. Frömming
S. Matthes
S. Brinkop
M. Ponater
S. Dietmüller
P. Jöckel
H. Garny
E. Tsati
K. Dahlmann
O. A. Søvde
J. Fuglestvedt
T. K. Berntsen
K. P. Shine
E. A. Irvine
T. Champougny
P. Hullah
Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
topic_facet Geology
QE1-996.5
description In addition to CO 2 , the climate impact of aviation is strongly influenced by non-CO 2 emissions, such as nitrogen oxides, influencing ozone and methane, and water vapour, which can lead to the formation of persistent contrails in ice-supersaturated regions. Because these non-CO 2 emission effects are characterised by a short lifetime, their climate impact largely depends on emission location and time; that is to say, emissions in certain locations (or times) can lead to a greater climate impact (even on the global average) than the same emission in other locations (or times). Avoiding these climate-sensitive regions might thus be beneficial to climate. Here, we describe a modelling chain for investigating this climate impact mitigation option. This modelling chain forms a multi-step modelling approach, starting with the simulation of the fate of emissions released at a certain location and time (time-region grid points). This is performed with the chemistry–climate model EMAC, extended via the two submodels AIRTRAC (V1.0) and CONTRAIL (V1.0), which describe the contribution of emissions to the composition of the atmosphere and to contrail formation, respectively. The impact of emissions from the large number of time-region grid points is efficiently calculated by applying a Lagrangian scheme. EMAC also includes the calculation of radiative impacts, which are, in a second step, the input to climate metric formulas describing the global climate impact of the emission at each time-region grid point. The result of the modelling chain comprises a four-dimensional data set in space and time, which we call climate cost functions and which describes the global climate impact of an emission at each grid point and each point in time. In a third step, these climate cost functions are used in an air traffic simulator (SAAM) coupled to an emission tool (AEM) to optimise aircraft trajectories for the North Atlantic region. Here, we describe the details of this new modelling approach and show some example results. A number ...
format Article in Journal/Newspaper
author V. Grewe
C. Frömming
S. Matthes
S. Brinkop
M. Ponater
S. Dietmüller
P. Jöckel
H. Garny
E. Tsati
K. Dahlmann
O. A. Søvde
J. Fuglestvedt
T. K. Berntsen
K. P. Shine
E. A. Irvine
T. Champougny
P. Hullah
author_facet V. Grewe
C. Frömming
S. Matthes
S. Brinkop
M. Ponater
S. Dietmüller
P. Jöckel
H. Garny
E. Tsati
K. Dahlmann
O. A. Søvde
J. Fuglestvedt
T. K. Berntsen
K. P. Shine
E. A. Irvine
T. Champougny
P. Hullah
author_sort V. Grewe
title Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
title_short Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
title_full Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
title_fullStr Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
title_full_unstemmed Aircraft routing with minimal climate impact: the REACT4C climate cost function modelling approach (V1.0)
title_sort aircraft routing with minimal climate impact: the react4c climate cost function modelling approach (v1.0)
publisher Copernicus Publications
publishDate 2014
url https://doi.org/10.5194/gmd-7-175-2014
https://doaj.org/article/be6fe06cff9940f298ac87f96d91cbc2
genre North Atlantic
genre_facet North Atlantic
op_source Geoscientific Model Development, Vol 7, Iss 1, Pp 175-201 (2014)
op_relation http://www.geosci-model-dev.net/7/175/2014/gmd-7-175-2014.pdf
https://doaj.org/toc/1991-959X
https://doaj.org/toc/1991-9603
1991-959X
1991-9603
doi:10.5194/gmd-7-175-2014
https://doaj.org/article/be6fe06cff9940f298ac87f96d91cbc2
op_doi https://doi.org/10.5194/gmd-7-175-2014
container_title Geoscientific Model Development
container_volume 7
container_issue 1
container_start_page 175
op_container_end_page 201
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