ALBERT

Description: © The Author(s), 2016. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Earth System Science Data 8 (2016): 605-649, doi:10.5194/essd-8-605-2016.

Description: Accurate assessment of anthropogenic carbon dioxide (CO2) 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 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. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO2 emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respectively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO2 concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO2 sink (SOCEAN) is based on observations from the 1990s, while the annual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO2 measurements. The global residual terrestrial CO2 sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ±1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3 ± 0.5 GtC yr−1, ELUC 1.0 ± 0.5 GtC yr−1, GATM 4.5 ± 0.1 GtC yr−1, SOCEAN 2.6 ± 0.5 GtC yr−1, and SLAND 3.1 ± 0.9 GtC yr−1. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9 ± 0.5 GtC yr−1, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr−1 that took place during 2006–2015. Also, for 2015, ELUC was 1.3 ± 0.5 GtC yr−1, GATM was 6.3 ± 0.2 GtC yr−1, SOCEAN was 3.0 ± 0.5 GtC yr−1, and SLAND was 1.9 ± 0.9 GtC yr−1. GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO2 concentration reached 399.4 ± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to +1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO2 concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO2 will reach 565 ± 55 GtC (2075 ± 205 GtCO2) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013). All observations presented here can be downloaded from the Carbon Dioxide Information Analysis Center (doi:10.3334/CDIAC/GCP_2016).

Description: Australia, Integrated Marine Observing System and Antarctic Climate and Ecosystems CRC BT; European Commission (EC) Copernicus Atmosphere Monitoring Service, European Centre for Medium-Range Weather Forecasts (ECMWF) FC; EC H2020 (AtlantOS; grant no. 633211) NL, AO; EC H2020 (CRESCENDO; grant no. 641816) CD, RS, OA, PF; EC H2020 European Research Council (ERC) (QUINCY; grant no. 647204). SZ; EC H2020 ERC Synergy grant (IMBALANCE-P; grant no. ERC-2013-SyG-610028) PC; France, BNP Paribas Foundation grant to support the Global Carbon Atlas PC; French Institut National des Sciences de l’Univers (INSU) and Institut Paul Emile Victor (IPEV) for OISO cruises NM; French Institut de recherche pour le développement (IRD) NL; German Federal Ministry of Education and Research (grant no. 01LK1224I ICOS-D) MH; German Research Foundation’s Emmy Noether Programme (grant no. PO1751/1-1) JN; German Max Planck Society CR, SZ; Germany, Federal Ministry of Education and Research (BMBF) AK; Germany, Helmholtz Postdoc Programme (Initiative and Networking Fund of the Helmholtz Association) JH; Japan Ministry of Agriculture, Forestry and Fisheries (MAFF) OT; Japan Ministry of Environment SN; Japan Ministry of Environment (grant no. ERTDF S-10) EK; NASA LCLUC programme (grant no. NASA NNX14AD94G) AJ; New Zealand National Institute of Water and Atmospheric Research (NIWA) Core Funding KC; Norway Research Council (grant no. 229752) AMO; Norway Research Council (grant no. 569980) GPP, RMA, JIK; Norway Research Council (project EVA; grant no. 229771) JS; Norwegian Environment Agency (grant no. 16078007) IS; Research Fund – Flanders (FWO; formerly Hercules Foundation) TG; South Africa Council for Scientific and Industrial Research (CSIR) PMSM; UK Natural Environment Research Council (RAGANRAoCC; grant no. NE/K002473/1) US; UK Newton Fund through the Met Office Climate Science for Service Partnership Brazil (CSSP Brazil) AJW; US Department of Agriculture, National Institute of Food and Agriculture (grant no. 2015-67003- 23485) DL; US Department of Energy (grant no. DE-FC03-97ER62402/A010) DL; US Department of Energy, Biological and Environmental Research Program, Office of Science (grant no. DE-AC05-00OR22725) APW; US Department of Commerce, NOAA’s Climate Observation Division of the Climate Program Office SRA, AJS; US Department of Energy, Office of Science and BER programme (grant no. DOE DE-SC0016323) AJ; US National Science Foundation (grant no. AGS-1048827) SD; US National Science Foundation (grant no. AOAS-1543457) DRM; US National Science Foundation (grant no. AOAS-1341647) DRM; US NOAA’s Climate Observation Division of the Climate Program Office (grant no. N8R1SE3P00); US NOAA’s Ocean Acidification Program (grant no. N8R3CEAP00) DP, LB; US National Science Foundation (grant no. NSF AGS 12-43071)

Description: Particle fluxes at the Cape Verde Ocean Observatory (CVOO) in the eastern tropical North Atlantic for the period December 2009 until May 2011 are discussed based on bathypelagic sediment trap time-series data collected at 1290 and 3439 m water depth. The typically oligotrophic particle flux pattern with weak seasonality is modified by the appearance of a highly productive and low oxygen (minimum concentration below 2 µmol kg**-1 at 40 m depth) anticyclonic modewater eddy (ACME) in winter 2010. The eddy passage was accompanied by unusually high mass fluxes of up to 151 mg m**-2 d**-1, lasting from December 2009 to May 2010. Distinct biogenic silica (BSi) and organic carbon flux peaks of ~15 and 13.3 mg m**-2 d**-1, respectively, were observed in February-March 2010 when the eddy approached the CVOO. The flux of the lithogenic component, mostly mineral dust, was well correlated with that of organic carbon, in particular in the deep trap samples, suggesting a tight coupling. The lithogenic ballasting obviously resulted in high particle settling rates and, thus, a fast transfer of epi-/meso-pelagic signatures to the bathypelagic traps. We suspect that the two- to three-fold increase in particle fluxes with depth as well as the tight coupling of mineral dust and organic carbon in the deep trap samples might be explained by particle focusing processes within the deeper part of the eddy. Molar C : N ratios of organic matter during the ACME passage were around 18 and 25 for the upper and lower trap samples, respectively. This suggests that some productivity under nutrient (nitrate) limitation occurred in the euphotic zone of the eddy in the beginning of 2010 or that a local nitrogen recycling took place. The d15N record showed a decrease from 5.21 to 3.11 per mil from January to March 2010, while the organic carbon and nitrogen fluxes increased. The causes of enhanced sedimentation from the eddy in February/March 2010 remain elusive, but nutrient depletion and/or an increased availability of dust as a ballast mineral for organic-rich aggregates might have contributed. Rapid remineralisation of sinking organic-rich particles could have contributed to oxygen depletion at shallow depth. Although the eddy formed in the West African coastal area in summer 2009, no indications of coastal flux signatures (e.g. from diatoms) were found in the sediment trap samples, confirming the assumption that the suboxia developed within the eddy en route. However, we could not detect biomarkers indicative of the presence of anammox (anaerobic ammonia oxidation) bacteria or green sulfur bacteria thriving in photic zone suboxia/hypoxia, i.e. ladderane fatty acids and isorenieratene derivatives, respectively. This could indicate that suboxic conditions in the eddy had recently developed and/or the respective bacterial stocks had not yet reached detection thresholds. Another explanation is that the fast-sinking organic-rich particles produced in the surface layer did not interact with bacteria from the suboxic zone below. Carbonate fluxes dropped from -52 to 21.4 mg m**-2 d**-1 from January to February 2010, respectively, mainly due to reduced contribution of shallow-dwelling planktonic foraminifera and pteropods. The deep-dwelling foraminifera Globorotalia menardii, however, showed a major flux peak in February 2010, most probably due to the suboxia/hypoxia. The low oxygen conditions forced at least some zooplankton to reduce diel vertical migration. Reduced "flux feeding" by zooplankton in the epipelagic could have contributed to the enhanced fluxes of organic materials to the bathypelagic traps during the eddy passage. Further studies are required on eddy-induced particle production and preservation processes and particle focusing.