Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)
Questions such as <q>what is the contribution of road traffic emissions to climate change?</q> or <q>what is the impact of shipping emissions on local air quality?</q> require a quantification of the contribution of specific emissions sectors to the concentration of radiat...
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Copernicus Publications
2017-07-01
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Series: | Geoscientific Model Development |
Online Access: | https://www.geosci-model-dev.net/10/2615/2017/gmd-10-2615-2017.pdf |
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Article |
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DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
V. Grewe V. Grewe E. Tsati M. Mertens C. Frömming P. Jöckel |
spellingShingle |
V. Grewe V. Grewe E. Tsati M. Mertens C. Frömming P. Jöckel Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) Geoscientific Model Development |
author_facet |
V. Grewe V. Grewe E. Tsati M. Mertens C. Frömming P. Jöckel |
author_sort |
V. Grewe |
title |
Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) |
title_short |
Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) |
title_full |
Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) |
title_fullStr |
Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) |
title_full_unstemmed |
Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52) |
title_sort |
contribution of emissions to concentrations: the tagging 1.0 submodel based on the modular earth submodel system (messy 2.52) |
publisher |
Copernicus Publications |
series |
Geoscientific Model Development |
issn |
1991-959X 1991-9603 |
publishDate |
2017-07-01 |
description |
Questions such as <q>what is the contribution of road traffic emissions to
climate change?</q> or <q>what is the impact of shipping emissions on local air
quality?</q> require a quantification of the contribution of specific
emissions sectors to the concentration of radiatively active species and air-quality-related
species, respectively. Here, we present a diagnostics
package, implemented in the Modular Earth Submodel System (MESSy), which keeps
track of the contribution of source categories (mainly emission sectors) to
various concentrations. The diagnostics package is implemented as a submodel
(TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts –
Hamburg (ECHAM)/MESSy Atmospheric Chemistry).
It determines the contributions of 10 different source categories to the
concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon
monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals
( = tagged tracers). The source categories are mainly emission sectors and
some other sources for completeness. As emission sectors, road traffic,
shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning,
and lightning are considered. The submodel obtains information on the
chemical reaction rates, online emissions, such as lightning, and wash-out
rates. It then solves differential equations for the contribution of a source
category to each of the seven tracers. This diagnostics package does not feed
back to any other part of the model. For the first time, it takes into
account chemically competing effects: for example, the competition between
NO<sub><i>x</i></sub>, CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show
that the results are in-line with results from other tagging schemes and
provide plausibility checks for concentrations of trace gases, such as OH and
HO<sub>2</sub>, which have not previously been tagged. The budgets of the tagged
tracers, i.e. the contribution from individual source categories (mainly
emission sectors) to, e.g., ozone, are only marginally sensitive to changes
in model resolution, though the level of detail increases. A reduction in
road traffic emissions by 5 % shows that road traffic global tropospheric
ozone is reduced by 4 % only, because the net ozone productivity
increases. This 4 % reduction in road traffic tropospheric ozone
corresponds to a reduction in total tropospheric ozone by
≈ 0.3 %, which is compensated by an increase in tropospheric
ozone from other sources by 0.1 %, resulting in a reduction in total
tropospheric ozone of ≈ 0.2 %. This compensating effect compares
well with previous findings. The computational costs of the TAGGING submodel are
low with respect to computing time, but a large number of additional tracers
are required. The advantage of the tagging scheme is that in one simulation
and at every time step and grid point, information is available on the
contribution of different emission sectors to the ozone budget, which then
can be further used in upcoming studies to calculate the respective radiative
forcing simultaneously. |
url |
https://www.geosci-model-dev.net/10/2615/2017/gmd-10-2615-2017.pdf |
work_keys_str_mv |
AT vgrewe contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 AT vgrewe contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 AT etsati contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 AT mmertens contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 AT cfromming contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 AT pjockel contributionofemissionstoconcentrationsthetagging10submodelbasedonthemodularearthsubmodelsystemmessy252 |
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doaj-fe16ed02054e4d0ea4b1c068d80f57b22020-11-25T02:40:30ZengCopernicus PublicationsGeoscientific Model Development1991-959X1991-96032017-07-01102615263310.5194/gmd-10-2615-2017Contribution of emissions to concentrations: the TAGGING 1.0 submodel based on the Modular Earth Submodel System (MESSy 2.52)V. Grewe0V. Grewe1E. Tsati2M. Mertens3C. Frömming4P. Jöckel5Deutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDelft University of Technology, Aerospace Engineering, Section Aircraft Noise and Climate Effects, Delft, the NetherlandsDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyDeutsches Zentrum für Luft- und Raumfahrt, Institut für Physik der Atmosphäre, Oberpfaffenhofen, GermanyQuestions such as <q>what is the contribution of road traffic emissions to climate change?</q> or <q>what is the impact of shipping emissions on local air quality?</q> require a quantification of the contribution of specific emissions sectors to the concentration of radiatively active species and air-quality-related species, respectively. Here, we present a diagnostics package, implemented in the Modular Earth Submodel System (MESSy), which keeps track of the contribution of source categories (mainly emission sectors) to various concentrations. The diagnostics package is implemented as a submodel (TAGGING) of EMAC (European Centre for Medium-Range Weather Forecasts – Hamburg (ECHAM)/MESSy Atmospheric Chemistry). It determines the contributions of 10 different source categories to the concentration of ozone, nitrogen oxides, peroxyacytyl nitrate, carbon monoxide, non-methane hydrocarbons, hydroxyl, and hydroperoxyl radicals ( = tagged tracers). The source categories are mainly emission sectors and some other sources for completeness. As emission sectors, road traffic, shipping, air traffic, anthropogenic non-traffic, biogenic, biomass burning, and lightning are considered. The submodel obtains information on the chemical reaction rates, online emissions, such as lightning, and wash-out rates. It then solves differential equations for the contribution of a source category to each of the seven tracers. This diagnostics package does not feed back to any other part of the model. For the first time, it takes into account chemically competing effects: for example, the competition between NO<sub><i>x</i></sub>, CO, and non-methane hydrocarbons (NMHCs) in the production and destruction of ozone. We show that the results are in-line with results from other tagging schemes and provide plausibility checks for concentrations of trace gases, such as OH and HO<sub>2</sub>, which have not previously been tagged. The budgets of the tagged tracers, i.e. the contribution from individual source categories (mainly emission sectors) to, e.g., ozone, are only marginally sensitive to changes in model resolution, though the level of detail increases. A reduction in road traffic emissions by 5 % shows that road traffic global tropospheric ozone is reduced by 4 % only, because the net ozone productivity increases. This 4 % reduction in road traffic tropospheric ozone corresponds to a reduction in total tropospheric ozone by ≈ 0.3 %, which is compensated by an increase in tropospheric ozone from other sources by 0.1 %, resulting in a reduction in total tropospheric ozone of ≈ 0.2 %. This compensating effect compares well with previous findings. The computational costs of the TAGGING submodel are low with respect to computing time, but a large number of additional tracers are required. The advantage of the tagging scheme is that in one simulation and at every time step and grid point, information is available on the contribution of different emission sectors to the ozone budget, which then can be further used in upcoming studies to calculate the respective radiative forcing simultaneously.https://www.geosci-model-dev.net/10/2615/2017/gmd-10-2615-2017.pdf |