Constraining OH concentrations with Satellite data and Machine learning to Investigate CH4 Trends (COSMIC)
Lead Research Organisation:
University of Leeds
Abstract
Atmospheric methane (CH4) is the second most important anthropogenically produced greenhouse gas after carbon dioxide, contributing to global warming. Global concentrations of CH4 continue to rise, however we do not fully understand the global variations in concentrations due to uncertainties in the drivers of its sources and sinks. CH4 has a global warming potential 82 times higher than carbon dioxide (CO2) on a 20-year timescale and record-breaking atmospheric increases in concentrations observed in 2020 and 2021 highlight the urgency in improving our understanding of changes in CH4 in our atmosphere.
CH4 has a mixture of natural and anthropogenic sources, these include wetlands, biomass burning, landfills and gas production. The main sink of CH4, the hydroxyl radical (OH), contributes to large uncertainties in the CH4 budget. Recent studies on the large rise of CH4 concentrations in 2020 have highlighted the influence of other atmospheric species on OH concentration and in turn, its impact on the lifetime of CH4. For example, during lockdown the decrease in NOx (NO and NO2), which contributes to air pollution, reduced OH concentrations which then increased the lifetime of CH4. This adds further complexity to understanding the role of OH on global concentrations of CH4.
OH has a short lifetime in the atmosphere (~1s) and is very challenging to measure. Global OH concentrations have previously been estimated using concentrations of methyl chloroform as a proxy, however its near-removal from the atmosphere due to the Montreal Protocol means that is becoming a less viable method. Therefore, it is time for new methods to be developed to constrain OH.
In this fellowship, I will provide the first long-term global tropospheric OH concentration estimates that have been optimised by combining machine learning techniques with satellite data of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and formaldehyde (CH2O), and a state-of-the-art chemical transport model (CTM), TOMCAT. Using this method will not only provide global gap-free tropospheric concentrations of OH but will include tropospheric concentrations of NO2, CO, O3 and CH2O. Advances in understanding of trends in tropospheric composition, particularly in relation to OH will improve model simulations of atmospheric CH4 and reduce uncertainties in its main sink.
The research will take advantage of this new OH dataset to investigate recent changes in CH4 concentrations and understand the role air quality has had on its atmospheric lifetime. I will conduct a comprehensive long-term study to analyse global trends in atmospheric CH4, while also focusing on specific case studies, including the years 2020 and 2021. The study will adapt to current trends in CH4 due to the rapidly evolving nature of this research field. This fellowship will not only deepen our understanding of atmospheric CH4 but also contribute to research in tropospheric composition, climate science, and inform European environmental policy-making through stakeholder engagement with the European Commission.
CH4 has a mixture of natural and anthropogenic sources, these include wetlands, biomass burning, landfills and gas production. The main sink of CH4, the hydroxyl radical (OH), contributes to large uncertainties in the CH4 budget. Recent studies on the large rise of CH4 concentrations in 2020 have highlighted the influence of other atmospheric species on OH concentration and in turn, its impact on the lifetime of CH4. For example, during lockdown the decrease in NOx (NO and NO2), which contributes to air pollution, reduced OH concentrations which then increased the lifetime of CH4. This adds further complexity to understanding the role of OH on global concentrations of CH4.
OH has a short lifetime in the atmosphere (~1s) and is very challenging to measure. Global OH concentrations have previously been estimated using concentrations of methyl chloroform as a proxy, however its near-removal from the atmosphere due to the Montreal Protocol means that is becoming a less viable method. Therefore, it is time for new methods to be developed to constrain OH.
In this fellowship, I will provide the first long-term global tropospheric OH concentration estimates that have been optimised by combining machine learning techniques with satellite data of nitrogen dioxide (NO2), carbon monoxide (CO), ozone (O3) and formaldehyde (CH2O), and a state-of-the-art chemical transport model (CTM), TOMCAT. Using this method will not only provide global gap-free tropospheric concentrations of OH but will include tropospheric concentrations of NO2, CO, O3 and CH2O. Advances in understanding of trends in tropospheric composition, particularly in relation to OH will improve model simulations of atmospheric CH4 and reduce uncertainties in its main sink.
The research will take advantage of this new OH dataset to investigate recent changes in CH4 concentrations and understand the role air quality has had on its atmospheric lifetime. I will conduct a comprehensive long-term study to analyse global trends in atmospheric CH4, while also focusing on specific case studies, including the years 2020 and 2021. The study will adapt to current trends in CH4 due to the rapidly evolving nature of this research field. This fellowship will not only deepen our understanding of atmospheric CH4 but also contribute to research in tropospheric composition, climate science, and inform European environmental policy-making through stakeholder engagement with the European Commission.
People |
ORCID iD |
| Emily Dowd (Principal Investigator / Fellow) |