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Assessment of ground-based atmospheric observations for verification of greenhouse gas emissions from an urban region.

Authors :
McKain K
Wofsy SC
Nehrkorn T
Eluszkiewicz J
Ehleringer JR
Stephens BB
Source :
Proceedings of the National Academy of Sciences of the United States of America [Proc Natl Acad Sci U S A] 2012 May 29; Vol. 109 (22), pp. 8423-8. Date of Electronic Publication: 2012 May 18.
Publication Year :
2012

Abstract

International agreements to limit greenhouse gas emissions require verification to ensure that they are effective and fair. Verification based on direct observation of atmospheric greenhouse gas concentrations will be necessary to demonstrate that estimated emission reductions have been actualized in the atmosphere. Here we assess the capability of ground-based observations and a high-resolution (1.3 km) mesoscale atmospheric transport model to determine a change in greenhouse gas emissions over time from a metropolitan region. We test the method with observations from a network of CO(2) surface monitors in Salt Lake City. Many features of the CO(2) data were simulated with excellent fidelity, although data-model mismatches occurred on hourly timescales due to inadequate simulation of shallow circulations and the precise timing of boundary-layer stratification and destratification. Using two optimization procedures, monthly regional fluxes were constrained to sufficient precision to detect an increase or decrease in emissions of approximately 15% at the 95% confidence level. We argue that integrated column measurements of the urban dome of CO(2) from the ground and/or space are less sensitive than surface point measurements to the redistribution of emitted CO(2) by small-scale processes and thus may allow for more precise trend detection of emissions from urban regions.

Details

Language :
English
ISSN :
1091-6490
Volume :
109
Issue :
22
Database :
MEDLINE
Journal :
Proceedings of the National Academy of Sciences of the United States of America
Publication Type :
Academic Journal
Accession number :
22611187
Full Text :
https://doi.org/10.1073/pnas.1116645109