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Institut Pierre-Simon Laplace

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About: Institut Pierre-Simon Laplace is a facility organization based out in . It is known for research contribution in the topics: Environmental science & Geology. The organization has 29 authors who have published 132 publications receiving 530 citations.

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Journal ArticleDOI
University of Exeter1, Max Planck Institute for Biogeochemistry2, Tyndall Centre3, Atlantic Oceanographic and Meteorological Laboratory4, Bjerknes Centre for Climate Research5, University of Maryland, College Park6, CICERO Center for International Climate Research7, Leibniz Institute for Baltic Sea Research8, University of Reading9, Leibniz Institute of Marine Sciences10, Goddard Space Flight Center11, Flanders Marine Institute12, Food and Agriculture Organization13, Alfred Wegener Institute for Polar and Marine Research14, National Oceanic and Atmospheric Administration15, University of East Anglia16, Japan Meteorological Agency17, ETH Zurich18, National Institute for Environmental Studies19, Karlsruhe Institute of Technology20, Laboratoire des Sciences du Climat et de l'Environnement21, Tula Foundation22, Hertie Institute for Clinical Brain Research23, Nanjing University of Information Science and Technology24, Wageningen University and Research Centre25, Tsinghua University26, University of Western Sydney27, Cooperative Institute for Research in Environmental Sciences28, University of Florida29, Center for Neuroscience and Regenerative Medicine30, Woods Hole Research Center31, Michigan State University32, Tianjin University33, Auburn University34, Jilin Medical University35, Max Planck Institute for Meteorology36, Imperial College London37, Centre National de Recherches Météorologiques38, University of Groningen39, Tohoku University40, Ludwig Maximilian University of Munich41, Bank for International Settlements42, Institut Pierre-Simon Laplace43, Environment Canada44, North West Agriculture and Forestry University45, Northwest A&F University46, Pacific Marine Environmental Laboratory47, Stanford University48, Utrecht University49
TL;DR: Friedlingstein et al. as mentioned in this paper presented and synthesized datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties, including fossil CO2 emissions, land use and land-use change data and bookkeeping models.
Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize datasets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), 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 ±1σ. For the first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gas inventories, supporting the assessment of collective countries' climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1, and SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021 suggest a rebound in EFOS relative to 2020 of +4.8 % (4.2 % to 5.4 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and datasets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this dataset (Friedlingstein et al., 2020, 2019; Le Quéré et al., 2018b, a, 2016, 2015b, a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

343 citations

Journal ArticleDOI
Pierre Friedlingstein1, Sönke Zaehle2, Corinne Le Quéré3, Christian Rödenbeck2, Bronte Tilbrook, Henry C. Bittig4, Denis Pierrot5, Louise Chini6, Jan Ivar Korsbakken7, Nicolas Bellouin8, Toste Tanhua9, Benjamin Poulter10, Peter Landschützer11, Francesco N. Tubiello12, Judith Hauck13, Are Olsen14, Vivek K. Arora15, Colm Sweeney16, Almut Arneth17, Marion Gehlen18, Hiroyuki Tsujino19, Daniel P. Kennedy20, Yosuke Iida19, Luke Gregor21, Jiye Zeng22, George C. Hurtt6, Nicolas Mayot23, Giacomo Grassi24, Shin-Ichiro Nakaoka22, Frédéric Chevallier18, Clemens Schwingshackl7, Wiley Evans25, Meike Becker26, Thomas Gasser27, Xu Yue28, Katie Pocock25, Stephanie Falk29, Thanos Gkritzalis11, Naiqing Pan30, Ingrid T. van der Laan-Luijkx31, Fraser Holding32, Carlos Gustavo Halaburda, Guanghong Zhou33, Peter Angele34, Jianling Chen1, e6gehqc68135, Carlos Muñoz Pérez23, Hiroshi Niinami36, Zongwe Binesikwe Crystal Hardy, Samuel Bourne37, Ralf Wüsthofen38, Paulo Brito, Christian Liguori39, Juan A. Martin-Ramos, Rattan Lal, kensetyrdhhtml2mdcom40, Staffan Furusten, Luca Miceli41, Eric Horster16, V. Miranda Chase, Field Palaeobiology Lab30, Living Tree Cbd Gummies, Lifeng Qin34, Yong Tang42, Annie Phillips43, Nathalie Fenouil26, mark, Karina Querne de Carvalho44, Satya Wydya Yenny, Maja Bak Herrie, Silvia Ravelli45, Andreas Gerster46, Denise Hottmann47, Wui-Lee Chang, Andreas Lutz48, Olga D. Vorob'eva49, Pallavi Banerjee1, Verónica Undurraga50, Jovan Babić, Michele D. Wallace9, Mònica Ginés-Blasi, 에볼루션카지노51, James Kelvin29, Christos Kontzinos1, Охунова Дилафруз Муминовна, Isabell Diekmann, Emily Burgoyne16, Vilemina Čenić52, Naomi Gikonyo26, CHAO LUAN21, Benjamin Pfluger53, Benjamin Pfluger54, A. J. Shields, Kobzos, Laszlo55, Adrian Langer56, Stuart L. Weinstein55, Abdullah ÖZÇELİK57, Yi Chen58, Anzhelika Solodka59, Valery Vasil'evich Kozlov60, Н.С. Рыжук, Roshan Vasant Shinde, Dr Sandeep Haribhau Wankhade, Dr Nitin Gajanan Shekapure, Mr Sachin Shrikant …61, Mylene Charon7, David Seibt62, Kobi Peled, None Rahmi52 
University of Exeter1, Max Planck Institute for Biogeochemistry2, Tyndall Centre3, Leibniz Institute for Baltic Sea Research4, Atlantic Oceanographic and Meteorological Laboratory5, University of Maryland, College Park6, CICERO Center for International Climate Research7, University of Reading8, Leibniz Institute of Marine Sciences9, Goddard Space Flight Center10, Flanders Marine Institute11, Food and Agriculture Organization12, Alfred Wegener Institute for Polar and Marine Research13, Geophysical Institute14, University of Victoria15, National Oceanic and Atmospheric Administration16, Karlsruhe Institute of Technology17, Laboratoire des Sciences du Climat et de l'Environnement18, Japan Meteorological Agency19, Indiana University20, ETH Zurich21, National Institute for Environmental Studies22, University of East Anglia23, European Commission24, Tula Foundation25, Bjerknes Centre for Climate Research26, Hertie Institute for Clinical Brain Research27, Nanjing University of Information Science and Technology28, Ludwig Maximilian University of Munich29, Auburn University30, Wageningen University and Research Centre31, University of Western Sydney32, Cooperative Institute for Research in Environmental Sciences33, Tsinghua University34, University of Florida35, Center for Neuroscience and Regenerative Medicine36, Woods Hole Research Center37, University of Alaska Fairbanks38, Princeton University39, Michigan State University40, University of Washington41, Appalachian State University42, Sun Yat-sen University43, Imperial College London44, University of Groningen45, University of Tennessee46, Washington University in St. Louis47, Jilin Medical University48, Tohoku University49, Rutgers University50, Centre for Research on Ecology and Forestry Applications51, Institut Pierre-Simon Laplace52, North West Agriculture and Forestry University53, Northwest A&F University54, Pacific Marine Environmental Laboratory55, Xi'an Jiaotong University56, Stanford University57, National Center for Atmospheric Research58, University of Edinburgh59, Max Planck Institute for Meteorology60, Utrecht University61, Oak Ridge National Laboratory62
TL;DR: Friedlingstein et al. as mentioned in this paper presented and synthesized data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties, including fossil CO2 emissions, land use and land-use change data and bookkeeping models.
Abstract: Abstract. Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodologies to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), 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 ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr−1 (9.9 ± 0.5 GtC yr−1 when the cement carbonation sink is included), and ELUC was 1.1 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission (including the cement carbonation sink) of 10.9 ± 0.8 GtC yr−1 (40.0 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr−1 (2.5 ± 0.1 ppm yr−1), SOCEAN was 2.9 ± 0.4 GtC yr−1, and SLAND was 3.5 ± 0.9 GtC yr−1, with a BIM of −0.6 GtC yr−1 (i.e. the total estimated sources were too low or sinks were too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022 suggest an increase in EFOS relative to 2021 of +1.0 % (0.1 % to 1.9 %) globally and atmospheric CO2 concentration reaching 417.2 ppm, more than 50 % above pre-industrial levels (around 278 ppm). Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows (1) a persistent large uncertainty in the estimate of land-use change emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extratropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set. The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

98 citations

Journal ArticleDOI
TL;DR: Deng et al. as mentioned in this paper presented a comprehensive framework to process the results of an ensemble of atmospheric inversions in order to make their net ecosystem exchange (NEE) carbon dioxide (CO2) flux suitable for evaluating national greenhouse gas inventories (NGHGIs) submitted by countries to the United Nations Framework Convention on Climate Change (UNFCCC).
Abstract: Abstract. In support of the global stocktake of the Paris Agreement on climate change, this study presents a comprehensive framework to process the results of an ensemble of atmospheric inversions in order to make their net ecosystem exchange (NEE) carbon dioxide (CO2) flux suitable for evaluating national greenhouse gas inventories (NGHGIs) submitted by countries to the United Nations Framework Convention on Climate Change (UNFCCC). From inversions we also deduced anthropogenic methane (CH4) emissions regrouped into fossil and agriculture and waste emissions, as well as anthropogenic nitrous oxide (N2O) emissions. To compare inversion results with national reports, we compiled a new global harmonized database of emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by non-Annex I countries, given by national communications and biennial update reports. No gap filling was applied. The method to reconcile inversions with inventories is applied to selected large countries covering ∼90 % of the global land carbon uptake for CO2 and top emitters of CH4 and N2O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO2 fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products and the role of carbon uptake in unmanaged lands, both not accounted for by NGHGIs. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH4, we find good consistency between the inversions assimilating only data from the global in situ network and those using satellite CH4 retrievals and a tendency for inversions to diagnose higher CH4 emission estimates than reported by NGHGIs. In particular, oil- and gas-extracting countries in central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N2O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to a lack of reporting indirect N2O emissions from atmospheric deposition and from leaching to rivers, to the existence of natural sources intertwined with managed lands, or to an underestimation of N2O emission factors for direct agricultural soil emissions. Inversions provide insights into seasonal and interannual greenhouse gas fluxes anomalies, e.g., during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports (e.g., NGHGIs) could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges. The dataset constructed by this study is publicly available at https://doi.org/10.5281/zenodo.5089799 (Deng et al., 2021).

28 citations

Journal ArticleDOI
TL;DR: In this article , the authors provide an update to regional carbon budgets over the last two decades based on observations for 10 regions covering the globe with a better harmonization than the precursor project, and define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region.
Abstract: Abstract. Regional land carbon budgets provide insights into the spatial distribution of the land uptake of atmospheric carbon dioxide and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields, or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions due to different definitions and component fluxes being reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers that connect CO2 uptake in one area with its release in another also requires better definitions and protocols to reach harmonized regional budgets that can be summed up to a globe scale and compared with the atmospheric CO2 growth rate and inversion results. In this study, using the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims to be an update to regional carbon budgets over the last 2 decades based on observations for 10 regions covering the globe with a better harmonization than the precursor project, we provide recommendations for using atmospheric inversion results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes, and land use fluxes.

17 citations

Journal ArticleDOI
TL;DR: In this article , the authors used the land surface model (LSM) ORCHILEAK to simulate the terrestrial C budget, including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe.
Abstract: Abstract. Leaching of dissolved organic carbon (DOC) from soils into the river network is an important component of the land carbon (C) budget. At regional to global scales, its significance has been estimated through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as a proxy of DOC leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a systematic underestimation of the leaching flux because of the decay of DOC during fluvial transport. Moreover, this procedure does not allow for revealing spatiotemporal variability in DOC leaching from soils, which is vital to better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the land surface model (LSM) ORCHILEAK to simulate the terrestrial C budget, including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe. The model performance is evaluated not only against the sparse observations of the soil DOC leaching rate, but also against the more abundant observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated DOC fluxes are realistic. The model is then used to simulate the spatiotemporal patterns of DOC leaching across Europe over the period 1972–2012, quantifying both the environmental drivers of these patterns and the impact of DOC leaching on the land C budget. Over the simulation period, we find that, on average, 14.3 Tg C yr−1 of DOC is leached from land into European rivers, which is about 0.6 % of the terrestrial net primary production (NPP), a fraction significantly lower than that reported for tropical river networks. On average, 12.3 Tg C yr−1 of the leached DOC is finally exported to the coast via the river network, and the rest is respired during transit. DOC leaching presents a large seasonal variability, with the maximum occurring in winter and the minimum in summer, except for most parts of northern Europe, where the maximum occurs in spring due to snowmelt. The DOC leaching rate is generally low in warm and dry regions, and high in the cold and wet regions of Europe. Furthermore, runoff and the ratio between runoff from shallower flow paths on one hand and deep drainage and groundwater flow on the other hand are the main drivers of the spatiotemporal variation of DOC leaching. Temperature, as a major control of DOC production and decomposition rates in the soils, plays only a secondary role.

8 citations


Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202349
202283