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Adrienne J. Sutton

Researcher at Pacific Marine Environmental Laboratory

Publications -  79
Citations -  8455

Adrienne J. Sutton is an academic researcher from Pacific Marine Environmental Laboratory. The author has contributed to research in topics: Ocean acidification & Carbon cycle. The author has an hindex of 28, co-authored 69 publications receiving 5138 citations. Previous affiliations of Adrienne J. Sutton include Oregon State University & University of Maryland Center for Environmental Science.

Papers
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Global Carbon Budget 2020

Pierre Friedlingstein, +95 more
TL;DR: In this paper, the authors describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
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Global Carbon Budget 2018

Corinne Le Quéré, +84 more
TL;DR: In this article, the authors describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including emissions from land use and land-use change data and bookkeeping models.
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Global Carbon Budget 2016

Corinne Le Quéré, +71 more
TL;DR: In this article, the authors quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community.
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Global Carbon Budget 2015

C. Le Quéré, +76 more
TL;DR: In this article, the authors presented a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community.
Journal ArticleDOI

Global carbon budget 2014

C. Le Quéré, +69 more
TL;DR: In this paper, the authors present a methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community.