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Understanding recent methane growth rate variability using a Lagrangian transport model

Applicant Schnadt Poberaj Christina
Number 129179
Funding scheme Marie Heim-Voegtlin grants
Research institution Luftfremdstoffe / Umwelttechnik 500 - Mobility, Energy and Environment EMPA
Institution of higher education Swiss Federal Laboratories for Materials Science and Technology - EMPA
Main discipline Climatology. Atmospherical Chemistry, Aeronomy
Start/End 01.05.2010 - 30.04.2012
Approved amount 222'542.00
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Keywords (6)

Atmospheric methane; Trends and variability; Methane emissions; Climate change; Global Lagrangian transport model; Multi-annual simulations

Lay Summary (English)

Lead
Lay summary
Atmospheric methane (CH4) is the second most important well-mixed greenhouse gas in terms of radiative forcing after carbon dioxide (CO2). CH4 has a global warming potential that exceeds the one of CO2 by a factor of 23, potentially making it an even more important contributor to climate change if concentrations continued to rise over the next decades.
The aim of the project is to improve the understanding of recent global atmospheric CH4 growth rate variability particularly focusing on the CH4 increase since 2007, and to quantify CH4 emissions in different regions of the world. In the context of climate change, CH4 emissions from natural wetlands and their dependency on meteorological conditions are of special importance and will be given particular weight in the project. The outcome of this study will help to improve confidence in projections of future CH4 and the potential impact on climate and atmospheric chemistry.
A global particle dispersion model will be applied, combined with a simple CH4 budget taking up surface emissions from different sources and removing it by reaction with the hydroxyl radical (OH), the main sink of atmospheric CH4. CH4 surface emissions from anthropogenic activities, biomass burning, and wetlands will be prescribed to force the model toward the desired atmospheric state. OH fields will be provided by a simulation with a state-of-the-art global chemistry-climate model.
Every particle transported by the global particle dispersion model will carry with it different CH4 tracers representing concentrations from different source categories additionally separated by region where required. Global monthly mean fields for each tracer will be produced by the model offering detailed insight into the contributions from different source categories and regions to the total CH4 burden. A series of multi-annual simulations will be carried out for the period 2004-2008 to improve the understanding of the roles of individual emission sources and meteorology. For this purpose, results from one reference simulation, forced by varying meteorology and emissions describing atmospheric CH4 as realistically as possible, will be compared to results from several sensitivity simulations, in which individual emission sources will be kept constant.
Another important part of the study will be time dependent quantification of CH4 emissions using a mathematical optimisation procedure called inverse modelling. The inversion will provide new insights into the role of interannual and seasonal variability in emissions, in particular from wetlands and biomass burning, to the observed variability in CH4 growth rates.

Direct link to Lay Summary Last update: 21.02.2013

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Abstract

Methane is the second most important well-mixed greenhouse gas in terms of radiative forcing after carbon dioxide. The aim of the project is to improve the understanding of the interannual variability and the recent increase of the global atmospheric methane abundance, and to quantify methane emissions. A global particle dispersion model will be applied, extended by a simple methane budget taking up surface emissions from different sources and removing it by reaction with the hydroxyl radical, the main sink of atmospheric methane. A series of simulations will be carried out for the period 2004-2008 to improve understanding of the relative roles of individual emission sources and meteorology. In addition, interannual variability of emissions from different methane sources will be quantified using the inverse modelling approach. This study will help to improve confidence in projections of future methane and the potential impact on climate and atmospheric chemistry.
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