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      Evaluating climate geoengineering proposals in the context of the Paris Agreement temperature goals

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          Abstract

          Current mitigation efforts and existing future commitments are inadequate to accomplish the Paris Agreement temperature goals. In light of this, research and debate are intensifying on the possibilities of additionally employing proposed climate geoengineering technologies, either through atmospheric carbon dioxide removal or farther-reaching interventions altering the Earth’s radiative energy budget. Although research indicates that several techniques may eventually have the physical potential to contribute to limiting climate change, all are in early stages of development, involve substantial uncertainties and risks, and raise ethical and governance dilemmas. Based on present knowledge, climate geoengineering techniques cannot be relied on to significantly contribute to meeting the Paris Agreement temperature goals.

          Abstract

          Research and debate are intensifying on complementing CO 2 emissions reductions with hypothetical climate geoengineering techniques. Here, the authors assess their potentials, uncertainties and risks, and show that they cannot yet be relied on to significantly contribute to meeting the Paris Agreement temperature goals.

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          Quantifying uncertainties in global and regional temperature change using an ensemble of observational estimates: The HadCRUT4 data set

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            Global Carbon Budget 2017

            Accurate assessment of anthropogenic carbon dioxide (CO 2 ) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the global carbon budget – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. CO 2 emissions from fossil fuels and industry ( E FF ) are based on energy statistics and cement production data, respectively, while emissions from land-use change ( E LUC ), mainly deforestation, are based on land-cover change data and bookkeeping models. The global atmospheric CO 2 concentration is measured directly and its rate of growth ( G ATM ) is computed from the annual changes in concentration. The ocean CO 2 sink ( S OCEAN ) and terrestrial CO 2 sink ( S LAND ) are estimated with global process models constrained by observations. The resulting carbon budget imbalance ( B IM ), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1 σ . For the last decade available (2007–2016), E FF was 9.4 ± 0.5 GtC yr −1 , E LUC 1.3 ± 0.7 GtC yr −1 , G ATM 4.7 ± 0.1 GtC yr −1 , S OCEAN 2.4 ± 0.5 GtC yr −1 , and S LAND 3.0 ± 0.8 GtC yr −1 , with a budget imbalance B IM of 0.6 GtC yr −1 indicating overestimated emissions and/or underestimated sinks. For year 2016 alone, the growth in E FF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr −1 . Also for 2016, E LUC was 1.3 ± 0.7 GtC yr −1 , G ATM was 6.1 ± 0.2 GtC yr −1 , S OCEAN was 2.6 ± 0.5 GtC yr −1 , and S LAND was 2.7 ± 1.0 GtC yr −1 , with a small B IM of −0.3 GtC. G ATM continued to be higher in 2016 compared to the past decade (2007–2016), reflecting in part the high fossil emissions and the small S LAND consistent with El Niño conditions. The global atmospheric CO 2 concentration reached 402.8 ± 0.1 ppm averaged over 2016. For 2017, preliminary data for the first 6–9 months indicate a renewed growth in E FF of +2.0 % (range of 0.8 to 3.0 %) based on national emissions projections for China, USA, and India, and projections of gross domestic product (GDP) corrected for recent changes in the carbon intensity of the economy for the rest of the world. This living data update documents changes in the methods and data sets used in this new global carbon budget compared with previous publications of this data set (Le Quéré et al., 2016, 2015b, a, 2014, 2013). All results presented here can be downloaded from https://doi.org/10.18160/GCP-2017 (GCP, 2017).
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              Soil carbon 4 per mille

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                Author and article information

                Contributors
                mark.lawrence@iass-potsdam.de
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                13 September 2018
                13 September 2018
                2018
                : 9
                : 3734
                Affiliations
                [1 ]ISNI 0000 0004 0409 4235, GRID grid.464582.9, Institute for Advanced Sustainability Studies (IASS), ; Potsdam, Germany
                [2 ]ISNI 0000 0001 0942 1117, GRID grid.11348.3f, University of Potsdam, ; Potsdam, Germany
                [3 ]ISNI 0000 0004 1936 8948, GRID grid.4991.5, Institute for Science, Innovation and Society, , University of Oxford, ; Oxford, UK
                [4 ]ISNI 0000 0004 1936 8921, GRID grid.5510.1, University of Oslo, ; Oslo, Norway
                [5 ]ISNI 0000 0001 1516 2393, GRID grid.5947.f, Norwegian University of Science and Technology, ; Trondheim, Norway
                [6 ]ISNI 0000 0004 1936 7988, GRID grid.4305.2, University of Edinburgh, ; Edinburgh, UK
                [7 ]ISNI 0000 0000 9056 9663, GRID grid.15649.3f, GEOMAR, ; Kiel, Germany
                [8 ]ISNI 0000 0001 1092 7967, GRID grid.8273.e, University of East Anglia, ; Norwich, UK
                [9 ]ISNI 0000 0001 2308 1657, GRID grid.462844.8, Institut Pierre-Simon Laplace, , CNRS / Sorbonne Université, ; Paris, France
                [10 ]ISNI 0000 0001 0721 4552, GRID grid.450268.d, Max Planck Institute for Meteorology, ; Hamburg, Germany
                [11 ]ISNI 0000 0004 1936 8024, GRID grid.8391.3, University of Exeter, ; Exeter, UK
                [12 ]ISNI 0000000405133830, GRID grid.17100.37, Met Office Hadley Centre, ; Exeter, UK
                [13 ]ISNI 0000 0001 2287 2617, GRID grid.9026.d, University of Hamburg, ; Hamburg, Germany
                Author information
                http://orcid.org/0000-0002-2178-4903
                http://orcid.org/0000-0002-4446-2069
                http://orcid.org/0000-0003-4738-493X
                http://orcid.org/0000-0002-4599-194X
                http://orcid.org/0000-0002-8295-4013
                http://orcid.org/0000-0002-4532-2084
                http://orcid.org/0000-0003-2328-5769
                http://orcid.org/0000-0001-7977-5041
                http://orcid.org/0000-0002-2143-6634
                http://orcid.org/0000-0002-7171-3062
                Article
                5938
                10.1038/s41467-018-05938-3
                6137062
                30213930
                20576911-b8b6-4e18-af3c-dd8fdd71fddb
                © The Author(s) 2018

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 1 November 2017
                : 7 August 2018
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