A CO-based method to determine the regional biospheric signal in atmospheric CO2. Issue 1 (1st January 2017)
- Record Type:
- Journal Article
- Title:
- A CO-based method to determine the regional biospheric signal in atmospheric CO2. Issue 1 (1st January 2017)
- Main Title:
- A CO-based method to determine the regional biospheric signal in atmospheric CO2
- Authors:
- Oney, Brian
Gruber, Nicolas
Henne, Stephan
Leuenberger, Markus
Brunner, Dominik - Abstract:
- Abstract : Regional-scale inverse modeling of atmospheric carbon dioxide (CO2 ) holds promise to determine the net CO2 fluxes between the land biosphere and the atmosphere. This approach requires not only high fidelity of atmospheric transport and mixing, but also an accurate estimation of the contribution of the anthropogenic and background CO2 signals to isolate the biospheric CO2 signal from the atmospheric CO2 variations. Thus, uncertainties in any of these three components directly impact the quality of the biospheric flux inversion. Here, we present and evaluate a carbon monoxide (CO)-based method to reduce these uncertainties solely on the basis of co-located observations. To this end, we use simultaneous observations of CO2 and CO from a background observation site to determine the background mole fractions for both gases, and the regional anthropogenic component of CO together with an estimate of the anthropogenic CO/CO2 mole fraction ratio to determine the anthropogenic CO2 component. We apply this method to two sites of the CarboCount CH observation network on the Swiss Plateau, Beromünster and Lägern-Hochwacht, and use the high-altitude site Jungfraujoch as background for the year 2013. Since such a background site is not always available, we also explore the possibility to use observations from the sites themselves to derive the background. We contrast the method with the standard approach of isolating the biospheric CO2 component by subtracting theAbstract : Regional-scale inverse modeling of atmospheric carbon dioxide (CO2 ) holds promise to determine the net CO2 fluxes between the land biosphere and the atmosphere. This approach requires not only high fidelity of atmospheric transport and mixing, but also an accurate estimation of the contribution of the anthropogenic and background CO2 signals to isolate the biospheric CO2 signal from the atmospheric CO2 variations. Thus, uncertainties in any of these three components directly impact the quality of the biospheric flux inversion. Here, we present and evaluate a carbon monoxide (CO)-based method to reduce these uncertainties solely on the basis of co-located observations. To this end, we use simultaneous observations of CO2 and CO from a background observation site to determine the background mole fractions for both gases, and the regional anthropogenic component of CO together with an estimate of the anthropogenic CO/CO2 mole fraction ratio to determine the anthropogenic CO2 component. We apply this method to two sites of the CarboCount CH observation network on the Swiss Plateau, Beromünster and Lägern-Hochwacht, and use the high-altitude site Jungfraujoch as background for the year 2013. Since such a background site is not always available, we also explore the possibility to use observations from the sites themselves to derive the background. We contrast the method with the standard approach of isolating the biospheric CO2 component by subtracting the anthropogenic and background components simulated by an atmospheric transport model. These tests reveal superior results from the observation-based method with retrieved wintertime biospheric signals being small and having little variance. Both observation- and model-based methods have difficulty to explain observations from late-winter and springtime pollution events in 2013, when anomalously cold temperatures and northeasterly winds tended to bring highly CO-enriched air masses to Switzerland. The uncertainty of anthropogenic CO/CO2 emission ratios is currently the most important factor limiting the method. Further, our results highlight that care needs to be taken when the background component is determined from the site's observations. Nonetheless, we find that future atmospheric carbon monitoring efforts would profit greatly from at least measuring CO alongside CO2 . … (more)
- Is Part Of:
- Tellus. Volume 69:Issue 1(2017)
- Journal:
- Tellus
- Issue:
- Volume 69:Issue 1(2017)
- Issue Display:
- Volume 69, Issue 1 (2017)
- Year:
- 2017
- Volume:
- 69
- Issue:
- 1
- Issue Sort Value:
- 2017-0069-0001-0000
- Page Start:
- Page End:
- Publication Date:
- 2017-01-01
- Subjects:
- limited-area atmospheric modeling -- inverse modeling -- measurement -- atmospheric carbon -- climate change -- terrestrial biosphere -- anthropogenic emissions -- model-data fusion
Atmospheric chemistry -- Periodicals
Atmospheric physics -- Periodicals
Meteorology -- Periodicals
Air -- Pollution -- Meteorological aspects -- Periodicals
Chimie de l'atmosphère -- Périodiques
Météorologie physique -- Périodiques
Météorologie -- Périodiques
Air -- Pollution -- Meteorological aspects
Atmospheric chemistry
Atmospheric physics
Meteorology
Meteorologie
Chimie de l'atmosphère
Météorologie physique
Météorologie
Meteorology
Electronic journals
Computer network resources
Periodicals
Ressource Internet (Descripteur de forme)
Périodique électronique (Descripteur de forme)
551.505 - Journal URLs:
- http://www.blackwellpublishing.com/journal.asp?ref=0280-6509&site=1 ↗
http://www.ingenta.com/journals/browse/mksg/teb ↗
http://firstsearch.oclc.org ↗
http://firstsearch.oclc.org/journal=0280-6509;screen=info;ECOIP ↗
http://search.ebscohost.com/login.aspx?direct=true&db=a9h&jid=HYW&site=ehost-live ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1600-0889 ↗
https://www.tandfonline.com/toc/zelb20/current ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1080/16000889.2017.1353388 ↗
- Languages:
- English
- ISSNs:
- 0280-6509
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 8789.000150
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British Library HMNTS - ELD Digital store - Ingest File:
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