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Cited by 340

The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.

Large-Scale Controls of Methanogenesis Inferred from Methane and Gravity Spaceborne Data

Bloom, A. Anthony, Palmer, Paul I., Fraser, Annemarie, Reay, David S., Frankenberg, Christian·2010·Science

Abstract

Measuring Methanogenesis: After carbon dioxide, methane is the second most important greenhouse gas, and an important species in terms of its role in atmospheric chemistry. The sources and sinks of methane, particularly the natural ones, are too poorly quantified, however, even to explain why the decades-long, steady increase of its concentration in the atmosphere was interrupted between 1999 and 2006. Bloom et al. (p. 322 ) use a combination of satellite data, which indicate water table depth and surface temperature, and atmospheric methane concentrations to determine the location and strength of methane emissions from wetlands, the largest natural global source. The constraints placed on these sources should help to improve predictions of how climate change will affect wet-land emissions of methane.

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Crossref · 10.1126/science.1175176

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Metadata

Authors
Bloom, A. A., Palmer, P. I., Fraser, A., Reay, D. S., & Frankenberg, C.
Venue
Science
Published
2010-01-15
Volume
327
Issue
5963
Pages
322-325
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2040858974
Cited by
340
References
24
FWCI
27.15
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Large-Scale Controls of Methanogenesis Inferred from Methane and Gravity Spaceborne Data. https://app.cochat.ai/papers/10.1126/science.1175176
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Bloom, A. A., Palmer, P. I., Fraser, A., Reay, D. S., & Frankenberg, C. (2010). Large-Scale Controls of Methanogenesis Inferred from Methane and Gravity Spaceborne Data. Science. https://doi.org/10.1126/science.1175176

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.