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Huang Y, Song X, Wang YP, Canadell JG, Luo Y, Ciais P, Chen A, Hong S, Wang Y, Tao F, Li W, Xu Y, Mirzaeitalarposhti R, Elbasiouny H, Savin I, Shchepashchenko D, Rossel RAV, Goll DS, Chang J, Houlton BZ, Wu H, Yang F, Feng X, Chen Y, Liu Y, Niu S, Zhang GL. Size, distribution, and vulnerability of the global soil inorganic carbon. Science 2024; 384:233-239. [PMID: 38603490 DOI: 10.1126/science.adi7918] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2023] [Accepted: 03/07/2024] [Indexed: 04/13/2024]
Abstract
Global estimates of the size, distribution, and vulnerability of soil inorganic carbon (SIC) remain largely unquantified. By compiling 223,593 field-based measurements and developing machine-learning models, we report that global soils store 2305 ± 636 (±1 SD) billion tonnes of carbon as SIC over the top 2-meter depth. Under future scenarios, soil acidification associated with nitrogen additions to terrestrial ecosystems will reduce global SIC (0.3 meters) up to 23 billion tonnes of carbon over the next 30 years, with India and China being the most affected. Our synthesis of present-day land-water carbon inventories and inland-water carbonate chemistry reveals that at least 1.13 ± 0.33 billion tonnes of inorganic carbon is lost to inland-waters through soils annually, resulting in large but overlooked impacts on atmospheric and hydrospheric carbon dynamics.
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Affiliation(s)
- Yuanyuan Huang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Xiaodong Song
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Ying-Ping Wang
- CSIRO Environment, Private Bag 10, Clayton South VIC 3169, Australia
| | | | - Yiqi Luo
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca NY 14853, USA
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91990, France
| | - Anping Chen
- Department of Biology and Graduate Degree Program in Ecology, Colorado State University, Fort Collins, CO 80523, USA
| | - Songbai Hong
- School of Urban Planning and Design, Shenzhen Graduate School, Peking University, Shenzhen 518055, China
| | - Yugang Wang
- State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi, Xinjiang 830011, China
| | - Feng Tao
- Department of Ecology and Evolutionary Biology and Department of Global Development, Cornell University, Ithaca, New York 14853, USA
| | - Wei Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing 100084, China
| | - Yiming Xu
- School of Grassland Science, Beijing Forestry University, Beijing 100083, China
| | - Reza Mirzaeitalarposhti
- Institute of Crop Science (340i), University of Hohenheim, Fruwirthstraße 20, 70599 Stuttgart, Germany
| | - Heba Elbasiouny
- Agriculture Faculty (Girls), Al-Azhar University, Cairo 11651, Egypt
| | - Igor Savin
- V.V. Dokuchaev Soil Science Institute, Moscow 119017, Russia
- Institute of Environmental Engineering of RUDN University, Moscow 117198, Russia
| | - Dmitry Shchepashchenko
- International Institute for Applied Systems Analysis (IIASA) Schlossplatz 1, 2361 Laxenburg, Austria
- Center for Forest Ecology and Productivity of the Russian Academy of Sciences, Moscow 117997, Russia
- Institute of Ecology and Geography, Siberian Federal University, 79 Svobodny Prospect, 660041 Krasnoyarsk, Russia
| | - Raphael A Viscarra Rossel
- Soil and Landscape Science School of Molecular and Life Sciences, Faculty of Science and Engineering, Curtin University, GPO Box U1987, Perth WA 6845, Australia
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91990, France
| | - Jinfeng Chang
- International Institute for Applied Systems Analysis (IIASA) Schlossplatz 1, 2361 Laxenburg, Austria
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou 310058, China
| | - Benjamin Z Houlton
- Department of Ecology and Evolutionary Biology and Department of Global Development, Cornell University, Ithaca, New York 14853, USA
| | - Huayong Wu
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Fei Yang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
| | - Xiaoming Feng
- Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
| | - Yongzhe Chen
- Department of Geography, The University of Hong Kong, Hong Kong 999077, China
| | - Yu Liu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Gan-Lin Zhang
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing 210008, China
- College of Advanced Agronomy, University of Chinese Academy of Sciences, Beijing 100049, China
- Nanjing Institute of Geography and Limnology, Chinese Academy of Sciences, Nanjing 210008, China
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Khairoun A, Mouillot F, Chen W, Ciais P, Chuvieco E. Coarse-resolution burned area datasets severely underestimate fire-related forest loss. Sci Total Environ 2024; 920:170599. [PMID: 38309343 DOI: 10.1016/j.scitotenv.2024.170599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2023] [Revised: 01/28/2024] [Accepted: 01/29/2024] [Indexed: 02/05/2024]
Abstract
Global coarse-resolution (≥250 m) burned area (BA) products have been used to estimate fire related forest loss, but we hypothesised that a significant part of fire impacts might be undetected because of the underestimation of small fires (<100 ha), especially in the tropics. In this paper, we analysed fire-related forest cover loss in sub-Saharan Africa (SSA) for 2016 and 2019 based on a BA product generated from Sentinel-2 data (20 m), which was observed to have significantly lower omission errors than the coarse-resolution BA products. Using these higher resolution BA datasets, we found that fires contribute to >46 % of total forest losses over SSA, more than twice the estimates from coarse-resolution BA products. In addition, burned forest areas showed more than twofold likelihood of subsequent loss compared to unburned ones. In moist tropical forests, the most fire-vulnerable biome, burning had even six times more chance to precede forest loss than unburned areas. We also found that fire-related characteristics, such as fire size and season, and forest fragmentation play a major role in the determination of tree cover fate. Our results reveal that medium-resolution BA detects more fires in late fire season, which tend to have higher impact on forests than early season ones. On the other hand, small fires represented the major driver of forest loss after fires and the vast majority of these losses occur in fragmented landscapes near forest edge (<260 m). Therefore medium-resolution BA products are required to obtain a more accurate evaluation of fire impacts in tropical ecosystems.
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Affiliation(s)
- Amin Khairoun
- Universidad de Alcalá, Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Colegios 2, 28801 Alcalá de Henares, Spain
| | - Florent Mouillot
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE, UMR 5175, CNRS, Université de Montpellier, Université Paul-Valéry Montpellier, EPHE, IRD, 1919 Route de Mende, 34293 Montpellier Cedex 5, France
| | - Wentao Chen
- Centre d'Ecologie Fonctionnelle et Evolutive CEFE, UMR 5175, CNRS, Université de Montpellier, Université Paul-Valéry Montpellier, EPHE, IRD, 1919 Route de Mende, 34293 Montpellier Cedex 5, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Emilio Chuvieco
- Universidad de Alcalá, Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, Colegios 2, 28801 Alcalá de Henares, Spain.
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Mittakola RT, Ciais P, Schubert JE, Makowski D, Zhou C, Bazzi H, Sun T, Liu Z, Davis SJ. Drivers of natural gas use in U.S. residential buildings. Sci Adv 2024; 10:eadh5543. [PMID: 38569031 PMCID: PMC10990266 DOI: 10.1126/sciadv.adh5543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Accepted: 02/28/2024] [Indexed: 04/05/2024]
Abstract
Natural gas is the primary fuel used in U.S. residences, yet little is known about its consumption patterns and drivers. We use daily county-level gas consumption data to assess the spatial patterns of the relationships and the sensitivities of gas consumption to outdoor air temperature across U.S. households. We fitted linear-plus-plateau functions to daily gas consumption data in 1000 counties, and derived two key coefficients: the heating temperature threshold (Tcrit) and the gas consumption rate change per 1°C temperature drop (Slope). We identified the main predictors of Tcrit and Slope (like income, employment rate, and building type) using interpretable machine learning models built on census data. Finally, we estimated a potential 2.47 million MtCO2 annual emission reduction in U.S. residences by gas savings due to household insulation improvements and hypothetical behavioral change toward reduced consumption by adopting a 1°C lower Tcrit than the current value.
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Affiliation(s)
- Rohith Teja Mittakola
- Laboratoire des Sciences du Climat et de l’Environnement, IPSL CEA CNRS UVSQ, Gif-sur-Yvette, France
- Atos France, Technical Services, 80 Quai Voltaire, 95870 Bezons, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, IPSL CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Jochen E. Schubert
- Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA, USA
| | - David Makowski
- UMR MIA 518, AgroParisTech, INRAE, Université Paris-Saclay, Palaiseau, France
| | - Chuanlong Zhou
- Laboratoire des Sciences du Climat et de l’Environnement, IPSL CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Hassan Bazzi
- Laboratoire des Sciences du Climat et de l’Environnement, IPSL CEA CNRS UVSQ, Gif-sur-Yvette, France
- Atos France, Technical Services, 80 Quai Voltaire, 95870 Bezons, France
- UMR MIA 518, AgroParisTech, INRAE, Université Paris-Saclay, Palaiseau, France
| | - Taochun Sun
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Zhu Liu
- Department of Earth System Science, Tsinghua University, Beijing, China
- DInstitute for Climate and Carbon Neutrality and Department of Geography, University of Hong Kong
| | - Steven J. Davis
- Department of Earth System Science, University of California, Irvine, Irvine, CA, USA
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4
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Abs E, Chase AB, Manzoni S, Ciais P, Allison SD. Microbial evolution-An under-appreciated driver of soil carbon cycling. Glob Chang Biol 2024; 30:e17268. [PMID: 38562029 DOI: 10.1111/gcb.17268] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/20/2023] [Revised: 03/18/2024] [Accepted: 03/18/2024] [Indexed: 04/04/2024]
Abstract
Although substantial advances in predicting the ecological impacts of global change have been made, predictions of the evolutionary impacts have lagged behind. In soil ecosystems, microbes act as the primary energetic drivers of carbon cycling; however, microbes are also capable of evolving on timescales comparable to rates of global change. Given the importance of soil ecosystems in global carbon cycling, we assess the potential impact of microbial evolution on carbon-climate feedbacks in this system. We begin by reviewing the current state of knowledge concerning microbial evolution in response to global change and its specific effect on soil carbon dynamics. Through this integration, we synthesize a roadmap detailing how to integrate microbial evolution into ecosystem biogeochemical models. Specifically, we highlight the importance of microscale mechanistic soil carbon models, including choosing an appropriate evolutionary model (e.g., adaptive dynamics, quantitative genetics), validating model predictions with 'omics' and experimental data, scaling microbial adaptations to ecosystem level processes, and validating with ecosystem-scale measurements. The proposed steps will require significant investment of scientific resources and might require 10-20 years to be fully implemented. However, through the application of multi-scale integrated approaches, we will advance the integration of microbial evolution into predictive understanding of ecosystems, providing clarity on its role and impact within the broader context of environmental change.
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Affiliation(s)
- Elsa Abs
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, California, USA
- Laboratoire Des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Alexander B Chase
- Department of Earth Sciences, Southern Methodist University, Dallas, Texas, USA
| | - Stefano Manzoni
- Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
| | - Philippe Ciais
- Laboratoire Des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Steven D Allison
- Department of Ecology and Evolutionary Biology, University of California, Irvine, Irvine, California, USA
- Department of Earth System Science, University of California, Irvine, Irvine, California, USA
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5
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Fendrich AN, Ciais P, Panagos P, Martin P, Carozzi M, Guenet B, Lugato E. Including land management in a European carbon model with lateral transfer to the oceans. Environ Res 2024; 245:118014. [PMID: 38151146 DOI: 10.1016/j.envres.2023.118014] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/25/2023] [Revised: 11/11/2023] [Accepted: 12/21/2023] [Indexed: 12/29/2023]
Abstract
The use of cover crops (CCs) is a promising cropland management practice with multiple benefits, notably in reducing soil erosion and increasing soil organic carbon (SOC) storage. However, the current ability to represent these factors in land surface models remains limited to small scales or simplified and lumped approaches due to the lack of a sediment-carbon erosion displacement scheme. This precludes a thorough understanding of the consequences of introducing a CC into agricultural systems. In this work, this problem was addressed in two steps with the spatially distributed CE-DYNAM model. First, the historical effect of soil erosion, transport, and deposition on the soil carbon budget at a continental scale in Europe was characterized since the early industrial era, using reconstructed climate and land use forcings. Then, the impact of two distinct policy-oriented scenarios for the introduction of CCs were evaluated, covering the European cropping systems where surface erosion rates or nitrate susceptibility are critical. The evaluation focused on the increase in SOC storage and the export of particulate organic carbon (POC) to the oceans, compiling a continental-scale carbon budget. The results indicated that Europe exported 1.95 TgC/year of POC to the oceans in the last decade, and that CCs can contribute to reducing this amount while increasing SOC storage. Compared to the simulation without CCs, the additional rate of SOC storage induced by CCs peaked after 10 years of their adoption, followed by a decrease, and the cumulative POC export reduction stabilized after around 13 years. The findings indicate that the impacts of CCs on SOC and reduced POC export are persistent regardless of their spatial allocation adopted in the scenarios. Together, the results highlight the importance of taking the temporal aspect of CC adoption into account and indicate that CCs alone are not sufficient to meet the targets of the 4‰ initiative. Despite some known model limitations, which include the lack of feedback of erosion on the net primary productivity and the representation of carbon fluxes with an emulator, the current work constitutes the first approach to successfully couple a distributed routing scheme of eroded carbon to a land carbon model emulator at a reasonably high resolution and continental scale. SHORT ABSTRACT: A spatially distributed model coupling erosion, transport, and deposition to the carbon cycle was developed. Then, it was used to simulate the impact of cover crops on both erosion and carbon, to show that cover crops can simultaneously increase organic carbon storage and reduce particulate organic carbon export to the oceans. The results seemed persistent regardless of the spatial distribution of cover crops.
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Affiliation(s)
- Arthur N Fendrich
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy; Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSACLAY, 91190, Gif sur Yvette, France; Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France.
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSACLAY, 91190, Gif sur Yvette, France
| | - Panos Panagos
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy
| | - Philippe Martin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France
| | - Marco Carozzi
- Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France
| | - Bertrand Guenet
- LG-ENS (Laboratoire de géologie) - CNRS UMR 8538 - École normale supérieure, PSL University - IPSL, Paris, France
| | - Emanuele Lugato
- European Commission, Joint Research Centre (JRC), Ispra, VA, Italy.
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Tao F, Houlton BZ, Frey SD, Lehmann J, Manzoni S, Huang Y, Jiang L, Mishra U, Hungate BA, Schmidt MWI, Reichstein M, Carvalhais N, Ciais P, Wang YP, Ahrens B, Hugelius G, Hocking TD, Lu X, Shi Z, Viatkin K, Vargas R, Yigini Y, Omuto C, Malik AA, Peralta G, Cuevas-Corona R, Di Paolo LE, Luotto I, Liao C, Liang YS, Saynes VS, Huang X, Luo Y. Reply to: Model uncertainty obscures major driver of soil carbon. Nature 2024; 627:E4-E6. [PMID: 38448699 DOI: 10.1038/s41586-023-07000-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 12/19/2023] [Indexed: 03/08/2024]
Affiliation(s)
- Feng Tao
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Benjamin Z Houlton
- Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA
- Department of Global Development, Cornell University, Ithaca, NY, USA
| | - Serita D Frey
- Center for Soil Biogeochemistry and Microbial Ecology, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA
| | - Johannes Lehmann
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Stefano Manzoni
- Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
| | - Yuanyuan Huang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Lifen Jiang
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Umakant Mishra
- Computational Biology & Biophysics, Sandia National Laboratories, Livermore, CA, USA
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA
| | - Bruce A Hungate
- Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA
| | | | | | - Nuno Carvalhais
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | | | | | - Gustaf Hugelius
- Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
| | - Toby D Hocking
- School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA
| | - Xingjie Lu
- School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
| | - Zheng Shi
- Institute for Environmental Genomics, University of Oklahoma, Norman, OK, USA
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
| | - Kostiantyn Viatkin
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Ronald Vargas
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Yusuf Yigini
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Christian Omuto
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Ashish A Malik
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | - Guillermo Peralta
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | | | | | - Isabel Luotto
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Cuijuan Liao
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Yi-Shuang Liang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Vinisa S Saynes
- Food and Agriculture Organization of the United Nations, Rome, Italy
| | - Xiaomeng Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
| | - Yiqi Luo
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA.
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7
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Liu W, Li M, Huang Y, Makowski D, Su Y, Bai Y, Schauberger B, Du T, Abbaspour KC, Yang K, Yang H, Ciais P. Mitigating nitrogen losses with almost no crop yield penalty during extremely wet years. Sci Adv 2024; 10:eadi9325. [PMID: 38416832 PMCID: PMC10901370 DOI: 10.1126/sciadv.adi9325] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/29/2023] [Accepted: 01/25/2024] [Indexed: 03/01/2024]
Abstract
Climate change-induced precipitation anomalies during extremely wet years (EWYs) result in substantial nitrogen losses to aquatic ecosystems (Nw). Still, the extent and drivers of these losses, and effective mitigation strategies have remained unclear. By integrating global datasets with well-established crop modeling and machine learning techniques, we reveal notable increases in Nw, ranging from 22 to 56%, during historical EWYs. These pulses are projected to amplify under the SSP126 (SSP370) scenario to 29 to 80% (61 to 120%) due to the projected increases in EWYs and higher nitrogen input. We identify the relative precipitation difference between two consecutive years (diffPr) as the primary driver of extreme Nw. This finding forms the basis of the CLimate Extreme Adaptive Nitrogen Strategy (CLEANS), which scales down nitrogen input adaptively to diffPr, leading to a substantial reduction in extreme Nw with nearly zero yield penalty. Our results have important implications for global environmental sustainability and while safeguarding food security.
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Affiliation(s)
- Wenfeng Liu
- State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Beijing 100083, China
- National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733000, China
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
| | - Mengxue Li
- State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Beijing 100083, China
- National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733000, China
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
| | - Yuanyuan Huang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - David Makowski
- UMR Applied Mathematics and Computer Science (MIA518), INRAE AgroParisTech, Université Paris-Saclay, Palaiseau, France
| | - Yang Su
- UMR ECOSYS, INRAE UVSQ, Université Paris-Saclay, 91190 Gif-sur-Yvette, France
- Département d'Informatique, École Normale Supérieure - PSL, 75005 Paris, France
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Yawei Bai
- State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Beijing 100083, China
- National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733000, China
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
| | - Bernhard Schauberger
- University of Applied Sciences Weihenstephan-Triesdorf, Department of Sustainable Agriculture and Energy Systems, Am Staudengarten 1, 85354 Freising, Germany
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, 14473 Potsdam, Germany
| | - Taisheng Du
- State Key Laboratory of Efficient Utilization of Agricultural Water Resources, Beijing 100083, China
- National Field Scientific Observation and Research Station on Efficient Water Use of Oasis Agriculture in Wuwei of Gansu Province, Wuwei 733000, China
- Center for Agricultural Water Research in China, College of Water Resources and Civil Engineering, China Agricultural University, Beijing 100083, China
| | - Karim C. Abbaspour
- 2w2e Environmental Consulting GmbH, Mettlenweg 3, Dübendorf, 8600 Zürich, Switzerland
| | - Kun Yang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
- National Tibetan Plateau Data Center, State Key Laboratory of Tibetan Plateau Earth System and Resource Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Hong Yang
- 2w2e Environmental Consulting GmbH, Mettlenweg 3, Dübendorf, 8600 Zürich, Switzerland
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
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8
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Yue C, Jian J, Ciais P, Ren X, Jiao J, An S, Li Y, Wu J, Zhang P, Bond-Lamberty B. Field experiments show no consistent reductions in soil microbial carbon in response to warming. Nat Commun 2024; 15:1731. [PMID: 38413557 PMCID: PMC10899254 DOI: 10.1038/s41467-024-45508-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2023] [Accepted: 01/25/2024] [Indexed: 02/29/2024] Open
Affiliation(s)
- Chao Yue
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China
- College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi, China
| | - Jinshi Jian
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China.
- College of Grassland Agriculture, Northwest A&F University, Yangling, Shaanxi, China.
- Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resource, Yangling, Shaanxi, China.
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Xiaohua Ren
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China
| | - Juying Jiao
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China.
- Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resource, Yangling, Shaanxi, China.
| | - Shaoshan An
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Institute of Soil and Water Conservation, Northwest A & F University, Yangling, China
- Institute of Soil and Water Conservation, Chinese Academy of Sciences and Ministry of Water Resource, Yangling, Shaanxi, China
| | - Yu Li
- College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi, China
| | - Jie Wu
- College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi, China
| | - Pengyi Zhang
- College of Natural Resources and Environment, Northwest A & F University, Yangling, Shaanxi, China
| | - Ben Bond-Lamberty
- Pacific Northwest National Laboratory, Joint Global Change Research Institute at the University of Maryland-College Park, College Park, MD, USA
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9
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Liang L, Ziegler AD, Chen D, Ciais P, Li LZX, Liang S, Wang D, Xu R, Zeng Z. Changing footprint of the Pacific Decadal Oscillation on global land surface air temperature. Sci Bull (Beijing) 2024; 69:445-448. [PMID: 38103950 DOI: 10.1016/j.scib.2023.12.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/17/2023] [Revised: 10/26/2023] [Accepted: 10/28/2023] [Indexed: 12/19/2023]
Affiliation(s)
- Lili Liang
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China; SUSTech Energy Institute for Carbon Neutrality, Southern University of Science and Technology, Shenzhen 518055, China
| | - Alan D Ziegler
- Faculty of Fisheries Technology and Aquatic Resources, Mae Jo University, Chiang Mai 50000, Thailand
| | - Deliang Chen
- Regional Climate Group, Department of Earth Sciences, University of Gothenburg, Gothenburg 40530, Sweden
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Laurent Z X Li
- Laboratoire de Météorologie Dynamique, Centre national de la recherche scientifique, Sorbonne Université, École Normale Supérieure, École Polytechnique, Paris 75000, France
| | - Shijing Liang
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Dashan Wang
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Rongrong Xu
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Zhenzhong Zeng
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China; SUSTech Energy Institute for Carbon Neutrality, Southern University of Science and Technology, Shenzhen 518055, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China.
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10
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Yu K, Chen HYH, Gessler A, Pugh TAM, Searle EB, Allen RB, Pretzsch H, Ciais P, Phillips OL, Brienen RJW, Chu C, Xie S, Ballantyne AP. Forest demography and biomass accumulation rates are associated with transient mean tree size vs. density scaling relations. PNAS Nexus 2024; 3:pgae008. [PMID: 38390215 PMCID: PMC10883769 DOI: 10.1093/pnasnexus/pgae008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 12/27/2023] [Indexed: 02/24/2024]
Abstract
Linking individual and stand-level dynamics during forest development reveals a scaling relationship between mean tree size and tree density in forest stands, which integrates forest structure and function. However, the nature of this so-called scaling law and its variation across broad spatial scales remain unquantified, and its linkage with forest demographic processes and carbon dynamics remains elusive. In this study, we develop a theoretical framework and compile a broad-scale dataset of long-term sample forest stands (n = 1,433) from largely undisturbed forests to examine the association of temporal mean tree size vs. density scaling trajectories (slopes) with biomass accumulation rates and the sensitivity of scaling slopes to environmental and demographic drivers. The results empirically demonstrate a large variation of scaling slopes, ranging from -4 to -0.2, across forest stands in tropical, temperate, and boreal forest biomes. Steeper scaling slopes are associated with higher rates of biomass accumulation, resulting from a lower offset of forest growth by biomass loss from mortality. In North America, scaling slopes are positively correlated with forest stand age and rainfall seasonality, thus suggesting a higher rate of biomass accumulation in younger forests with lower rainfall seasonality. These results demonstrate the strong association of the transient mean tree size vs. density scaling trajectories with forest demography and biomass accumulation rates, thus highlighting the potential of leveraging forest structure properties to predict forest demography, carbon fluxes, and dynamics at broad spatial scales.
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Affiliation(s)
- Kailiang Yu
- High Meadows Environmental Institute, Princeton University, Princeton, NJ 08544, USA
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59801, USA
| | - Han Y H Chen
- Faculty of Natural Resources Management, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
| | - Arthur Gessler
- Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Birmensdorf CH-8903, Switzerland
| | - Thomas A M Pugh
- Department of Physical Geography and Ecosystem Science, Lund University, Lund S-223 62, Sweden
- School of Geography, Earth and Environmental Sciences, University of Birmingham, Birmingham B15 2TT, UK
- Birmingham Institute of Forest Research, University of Birmingham, Birmingham B15 2TT, UK
| | - Eric B Searle
- Faculty of Natural Resources Management, Lakehead University, Thunder Bay, ON P7B 5E1, Canada
| | | | - Hans Pretzsch
- Chair for Forest Growth and Yield Science, Center of Life and Food Sciences Weihenstephan, Technical University of Munich, Freising 85354, Germany
- Sustainable Forest Management Research Institute iuFOR, University Valladolid, Valladolid 47002, Spain
| | - Philippe Ciais
- Le Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCECEA/CNRS/UVSQ Saclay, Gif-sur-Yvette 91191, France
| | | | | | - Chengjin Chu
- State Key Laboratory of Biocontrol, School of Ecology, Shenzhen Campus of Sun Yat-sen University, Shenzhen 518000, China
| | - Shubin Xie
- State Key Laboratory of Grassland Agro-Ecosystem, School of Life Sciences, Lanzhou University, Lanzhou 730000, China
| | - Ashley P Ballantyne
- Department of Ecosystem and Conservation Sciences, WA Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59801, USA
- Le Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCECEA/CNRS/UVSQ Saclay, Gif-sur-Yvette 91191, France
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11
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Abdallah C, Lauvaux T, Lian J, Bréon FM, Ramonet M, Laurent O, Ciais P, Denier van der Gon HAC, Dellaert S, Perrussel O, Baudic A, Utard H, Gros V. A Gradient-Descent Optimization of CO 2-CO-NO x Emissions over the Paris Megacity─The Case of the First SARS-CoV-2 Lockdown. Environ Sci Technol 2024; 58:302-314. [PMID: 38114451 DOI: 10.1021/acs.est.3c00566] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/21/2023]
Abstract
Urban greenhouse gas emissions monitoring is essential to assessing the impact of climate mitigation actions. Using atmospheric continuous measurements of air quality and carbon dioxide (CO2), we developed a gradient-descent optimization system to estimate emissions of the city of Paris. We evaluated our joint CO2-CO-NOx optimization over the first SARS-CoV-2 related lockdown period, resulting in a decrease in emissions by 40% for NOx and 30% for CO2, in agreement with preliminary estimates using bottom-up activity data yet lower than the decrease estimates from Bayesian atmospheric inversions (50%). Before evaluating the model, we first provide an in-depth analysis of three emission data sets. A general agreement in the totals is observed over the region surrounding Paris (known as Île-de-France) since all the data sets are constrained by the reported national and regional totals. However, the data sets show disagreements in their sector distributions as well as in the interspecies ratios. The seasonality also shows disagreements among emission products related to nonindustrial stationary combustion (residential and tertiary combustion). The results presented in this paper show that a multispecies approach has the potential to provide sectoral information to monitor CO2 emissions over urban areas enabled by the deployment of collocated atmospheric greenhouse gases and air quality monitoring stations.
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Affiliation(s)
- Charbel Abdallah
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Groupe de Spectrométrie Moléculaire et Atmosphérique GSMA, Université de Reims-Champagne Ardenne, UMR CNRS 7331, Moulin de la Housse, BP 1039, 51687 Reims 2, France
| | - Thomas Lauvaux
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Groupe de Spectrométrie Moléculaire et Atmosphérique GSMA, Université de Reims-Champagne Ardenne, UMR CNRS 7331, Moulin de la Housse, BP 1039, 51687 Reims 2, France
| | - Jinghui Lian
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
- Origins.earth, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense Cedex 6, France
| | - François-Marie Bréon
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Michel Ramonet
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Olivier Laurent
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
| | | | - Stijn Dellaert
- Department of Climate, Air and Sustainability, TNO, P.O. Box 80015, 3508 TA Utrecht, The Netherlands
| | - Olivier Perrussel
- Association de Surveillance de la Qualité de l'Air en Île-de-France (AIRPARIF), 75004 Paris, France
| | - Alexia Baudic
- Association de Surveillance de la Qualité de l'Air en Île-de-France (AIRPARIF), 75004 Paris, France
| | - Hervé Utard
- Origins.earth, Suez Group, Tour CB21, 16 Place de l'Iris, 92040 Paris La Défense Cedex 6, France
| | - Valérie Gros
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, UMR CNRS-CEA-UVSQ, IPSL, Gif-sur-Yvette, 91191 Île-de-France, France
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12
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Chen B, Fang J, Piao S, Ciais P, Black TA, Wang F, Niu S, Zeng Z, Luo Y. A meta-analysis highlights globally widespread potassium limitation in terrestrial ecosystems. New Phytol 2024; 241:154-165. [PMID: 37804058 DOI: 10.1111/nph.19294] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Accepted: 09/08/2023] [Indexed: 10/08/2023]
Abstract
Potassium (K+ ) is the most abundant inorganic cation in plant cells, playing a critical role in various plant functions. However, the impacts of K on natural terrestrial ecosystems have been less studied compared with nitrogen (N) and phosphorus (P). Here, we present a global meta-analysis aimed at quantifying the response of aboveground production to K addition. This analysis is based on 144 field K fertilization experiments. We also investigate the influences of climate, soil properties, ecosystem types, and fertilizer regimes on the responses of aboveground production. We find that: K addition significantly increases aboveground production by 12.3% (95% CI: 7.4-17.5%), suggesting a widespread occurrence of K limitation across terrestrial ecosystems; K limitation is more prominent in regions with humid climates, acidic soils, or weathered soils; the effect size of K addition varies among climate zones/regions, and is influenced by multiple factors; and previous N : K and K : P thresholds utilized to detect K limitation in wetlands cannot be applied to other biomes. Our findings emphasize the role of K in limiting terrestrial productivity, which should be integrated into future terrestrial ecosystems models.
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Affiliation(s)
- Baozhang Chen
- State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing, 100101, China
- University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing, 100049, China
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, Jiangsu, China
| | - Jingchun Fang
- State Key Laboratory of Resources and Environment Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 11A, Datun Road, Chaoyang District, Beijing, 100101, China
- University of Chinese Academy of Sciences, No. 19A, Yuquan Road, Beijing, 100049, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, 91191, France
| | - Thomas Andrew Black
- Faculty of Land and Food Systems, University of British Columbia, Vancouver, V6T 1Z4, Canada
| | - Fei Wang
- Institute of Agricultural Information and Economics, Shandong Academy of Agricultural Sciences, Jinan, 250100, China
| | - Shuli Niu
- Key Laboratory of Ecosystem Network Observation and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Zhenzhong Zeng
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, 518055, China
| | - Yiqi Luo
- School of Integrative Plant Science, Cornell University, Ithaca, NY, 14853, USA
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13
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Shen X, Shen M, Wu C, Peñuelas J, Ciais P, Zhang J, Freeman C, Palmer PI, Liu B, Henderson M, Song Z, Sun S, Lu X, Jiang M. Critical role of water conditions in the responses of autumn phenology of marsh wetlands to climate change on the Tibetan Plateau. Glob Chang Biol 2024; 30:e17097. [PMID: 38273510 DOI: 10.1111/gcb.17097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Revised: 11/24/2023] [Accepted: 11/29/2023] [Indexed: 01/27/2024]
Abstract
The Tibetan Plateau, housing 20% of China's wetlands, plays a vital role in the regional carbon cycle. Examining the phenological dynamics of wetland vegetation in response to climate change is crucial for understanding its impact on the ecosystem. Despite this importance, the specific effects of climate change on wetland vegetation phenology in this region remain uncertain. In this study, we investigated the influence of climate change on the end of the growing season (EOS) of marsh wetland vegetation across the Tibetan Plateau, utilizing satellite-derived Normalized Difference Vegetation Index (NDVI) data and observational climate data. We observed that the regionally averaged EOS of marsh vegetation across the Tibetan Plateau was significantly (p < .05) delayed by 4.10 days/decade from 2001 to 2020. Warming preseason temperatures were found to be the primary driver behind the delay in the EOS of marsh vegetation, whereas preseason cumulative precipitation showed no significant impact. Interestingly, the responses of EOS to climate change varied spatially across the plateau, indicating a regulatory role for hydrological conditions in marsh phenology. In the humid and cold central regions, preseason daytime warming significantly delayed the EOS. However, areas with lower soil moisture exhibited a weaker or reversed delay effect, suggesting complex interplays between temperature, soil moisture, and EOS. Notably, in the arid southwestern regions of the plateau, increased preseason rainfall directly delayed the EOS, while higher daytime temperatures advanced it. Our results emphasize the critical role of hydrological conditions, specifically soil moisture, in shaping marsh EOS responses in different regions. Our findings underscore the need to incorporate hydrological factors into terrestrial ecosystem models, particularly in cold and dry regions, for accurate predictions of marsh vegetation phenological responses to climate change. This understanding is vital for informed conservation and management strategies in the face of current and future climate challenges.
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Affiliation(s)
- Xiangjin Shen
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Miaogen Shen
- State Key Laboratory of Earth Surface Processes and Resource Ecology, Faculty of Geographical Science, Beijing Normal University, Beijing, China
| | - Chaoyang Wu
- Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Josep Peñuelas
- CREAF, Cerdanyola del Vallès, Barcelona, Spain
- CSIC, Global Ecology Unit CREAF-CSIC- UAB, Barcelona, Spain
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Jiaqi Zhang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Chris Freeman
- School of Natural Sciences, Bangor University, Bangor, UK
| | - Paul I Palmer
- School of GeoSciences, University of Edinburgh, Edinburgh, UK
- National Centre for Earth Observation, University of Edinburgh, Edinburgh, UK
| | - Binhui Liu
- College of Forestry, Northeast Forestry University, Harbin, China
| | - Mark Henderson
- Mills College, Northeastern University, Oakland, California, USA
| | - Zhaoliang Song
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin, China
| | - Shaobo Sun
- Institute of Surface-Earth System Science, School of Earth System Science, Tianjin University, Tianjin, China
| | - Xianguo Lu
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
| | - Ming Jiang
- Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun, China
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14
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Wang H, Ciais P, Sitch S, Green JK, Tao S, Fu Z, Albergel C, Bastos A, Wang M, Fawcett D, Frappart F, Li X, Liu X, Li S, Wigneron JP. Anthropogenic disturbance exacerbates resilience loss in the Amazon rainforests. Glob Chang Biol 2024; 30:e17006. [PMID: 37909670 DOI: 10.1111/gcb.17006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 09/03/2023] [Accepted: 10/10/2023] [Indexed: 11/03/2023]
Abstract
Uncovering the mechanisms that lead to Amazon forest resilience variations is crucial to predict the impact of future climatic and anthropogenic disturbances. Here, we apply a previously used empirical resilience metrics, lag-1 month temporal autocorrelation (TAC), to vegetation optical depth data in C-band (a good proxy of the whole canopy water content) in order to explore how forest resilience variations are impacted by human disturbances and environmental drivers in the Brazilian Amazon. We found that human disturbances significantly increase the risk of critical transitions, and that the median TAC value is ~2.4 times higher in human-disturbed forests than that in intact forests, suggesting a much lower resilience in disturbed forests. Additionally, human-disturbed forests are less resilient to land surface heat stress and atmospheric water stress than intact forests. Among human-disturbed forests, forests with a more closed and thicker canopy structure, which is linked to a higher forest cover and a lower disturbance fraction, are comparably more resilient. These results further emphasize the urgent need to limit deforestation and degradation through policy intervention to maintain the resilience of the Amazon rainforests.
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Affiliation(s)
- Huan Wang
- College of Urban and Environmental Sciences, Peking University, Beijing, China
- INRAE, UMR1391 ISPA, Université de Bordeaux, Villenave d'Ornon, France
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Julia K Green
- Department of Environmental Science, The University of Arizona, Tucson, Arizona, USA
| | - Shengli Tao
- College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Zheng Fu
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | | | - Ana Bastos
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Mengjia Wang
- School of Geoscience and Technology, Zhengzhou University, Zhengzhou, China
| | - Dominic Fawcett
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
- Swiss Federal Institute for Forest Snow and Landscape Research WSL, Birmensdorf, Switzerland
| | - Frédéric Frappart
- INRAE, UMR1391 ISPA, Université de Bordeaux, Villenave d'Ornon, France
| | - Xiaojun Li
- INRAE, UMR1391 ISPA, Université de Bordeaux, Villenave d'Ornon, France
| | - Xiangzhuo Liu
- INRAE, UMR1391 ISPA, Université de Bordeaux, Villenave d'Ornon, France
| | - Shuangcheng Li
- College of Urban and Environmental Sciences, Peking University, Beijing, China
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15
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Zhu D, Wang Y, Ciais P, Chevallier F, Peng S, Zhang Y, Wang X. Temperature dependence of spring carbon uptake in northern high latitudes during the past four decades. Glob Chang Biol 2024; 30:e17043. [PMID: 37988234 DOI: 10.1111/gcb.17043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/09/2023] [Revised: 10/16/2023] [Accepted: 10/24/2023] [Indexed: 11/23/2023]
Abstract
In the northern high latitudes, warmer spring temperatures generally lead to earlier leaf onsets, higher vegetation production, and enhanced spring carbon uptake. Yet, whether this positive linkage has diminished under climate change remains debated. Here, we used atmospheric CO2 measurements at Barrow (Alaska) during 1979-2020 to investigate the strength of temperature dependence of spring carbon uptake reflected by two indicators, spring zero-crossing date (SZC) and CO2 drawdown (SCC). We found a fall and rise in the interannual correlation of temperature with SZC and SCC (RSZC-T and RSCC-T ), showing a recent reversal of the previously reported weakening trend of RSZC-T and RSCC-T . We used a terrestrial biosphere model coupled with an atmospheric transport model to reproduce this fall and rise phenomenon and conducted factorial simulations to explore its potential causes. We found that a strong-weak-strong spatial synchrony of spring temperature anomalies per se has contributed to the fall and rise trend in RSZC-T and RSCC-T , despite an overall unbroken temperature control on net ecosystem CO2 fluxes at local scale. Our results provide an alternative explanation for the apparent drop of RSZC-T and RSCC-T during the late 1990s and 2000s, and suggest a continued positive linkage between spring carbon uptake and temperature during the past four decades. We thus caution the interpretation of apparent climate sensitivities of carbon cycle retrieved from spatially aggregated signals.
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Affiliation(s)
- Dan Zhu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Yilong Wang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Frédéric Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Shushi Peng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Yao Zhang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Xuhui Wang
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
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16
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Peng S, Giron C, Liu G, d’Aspremont A, Benoit A, Lauvaux T, Lin X, de Almeida Rodrigues H, Saunois M, Ciais P. High-resolution assessment of coal mining methane emissions by satellite in Shanxi, China. iScience 2023; 26:108375. [PMID: 38025773 PMCID: PMC10679808 DOI: 10.1016/j.isci.2023.108375] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 07/25/2023] [Accepted: 10/27/2023] [Indexed: 12/01/2023] Open
Abstract
Accurate assessment of coal mine methane (CMM) emissions is a prerequisite for defining baselines and assessing the effectiveness of mitigation measures. Such an endeavor is jeopardized, however, by large uncertainties in current CMM estimates. Here, we assimilated atmospheric methane column concentrations observed by the TROPOMI space borne instrument in a high-resolution regional inversion to estimate CMM emissions in Shanxi, a province representing 15% of the global coal production. The emissions are estimated to be 8.5 ± 0.6 and 8.6 ± 0.6 Tg CH4 yr-1 in 2019 and 2020, respectively, close to upper bound of current bottom-up estimates. Data from more than a thousand of individual mines indicate that our estimated emission factors increase significantly with coal mining depth at prefecture level, suggesting that ongoing deeper mining will increase CMM emission intensity. Our results show robustness of estimating CMM emissions utilizing TROPOMI images and highlight potential of monitoring methane leakages and emissions from satellites.
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Affiliation(s)
- Shushi Peng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China
| | | | - Gang Liu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China
| | - Alexandre d’Aspremont
- Kayrros, 33 rue Lafayette, 75009 Paris, France
- CNRS & DI, Ecole Normale Supérieure, Paris, France
| | | | - Thomas Lauvaux
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Xin Lin
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | | | - Marielle Saunois
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191 Gif-sur-Yvette, France
- The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus
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17
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Deng X, Huang Y, Yuan W, Zhang W, Ciais P, Dong W, Smith P, Qin Z. Building soil to reduce climate change impacts on global crop yield. Sci Total Environ 2023; 903:166711. [PMID: 37652390 DOI: 10.1016/j.scitotenv.2023.166711] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 08/24/2023] [Accepted: 08/28/2023] [Indexed: 09/02/2023]
Abstract
Improving soil health and resilience is fundamental for sustainable food production, however the role of soil in maintaining or improving global crop productivity under climate warming is not well identified and quantified. Here, we examined the impact of soil on yield response to climate warming for four major crops (i.e., maize, wheat, rice and soybean), using global-scale datasets and random forest method. We found that each °C of warming reduced global yields of maize by 3.4%, wheat by 2.4%, rice by 0.3% and soybean by 5.0%, which were spatially heterogeneous with possible positive impacts. The random forest modeling analyses further showed that soil organic carbon (SOC), as an indicator of soil quality, dominantly explained the spatial heterogeneity of yield responses to warming and would regulate the negative warming responses. Improving SOC under the medium SOC sequestration scenario would reduce the warming-induced yield loss of maize, wheat, rice and soybean to 0.1% °C-1, 2.7% °C-1, 3.4% °C-1 and - 0.6% °C-1, respectively, avoiding an average of 3%-5% °C-1 of global yield loss. These yield benefits would occur on 53.2%, 67.8%, 51.8% and 71.6% of maize, wheat, rice and soybean planting areas, respectively, with particularly pronounced benefits in the regions with negative warming responses. With improved soil carbon, food systems are predicted to provide additional 20 to over 130 million tonnes of food that would otherwise lose due to future warming. Our findings highlight the critical role of soil in alleviating negative warming impacts on food security, especially for developing regions, given that sustainable actions on soil improvement could be taken broadly.
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Affiliation(s)
- Xi Deng
- School of Atmospheric Sciences, Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-Sen University, Zhuhai 519000, China
| | - Yao Huang
- State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing 100093, China; State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Wenping Yuan
- School of Atmospheric Sciences, Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-Sen University, Zhuhai 519000, China
| | - Wen Zhang
- State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing 100029, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette 91191, France
| | - Wenjie Dong
- School of Atmospheric Sciences, Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-Sen University, Zhuhai 519000, China
| | - Pete Smith
- Institute of Biological and Environmental Sciences, School of Biological Sciences, University of Aberdeen, Aberdeen AB24 3UU, UK
| | - Zhangcai Qin
- School of Atmospheric Sciences, Key Laboratory of Tropical Atmosphere-Ocean System (Ministry of Education), Southern Marine Science and Engineering Guangdong Laboratory (Zhuhai), Sun Yat-Sen University, Zhuhai 519000, China.
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18
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Gurriaran L, Tanaka K, Takahashi K, Ciais P. How climate change may shift power demand in Japan: Insights from data-driven analysis. J Environ Manage 2023; 345:118799. [PMID: 37690242 DOI: 10.1016/j.jenvman.2023.118799] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/25/2023] [Revised: 08/07/2023] [Accepted: 08/09/2023] [Indexed: 09/12/2023]
Abstract
The impact of climate change on power demand in Japan and its related CO2 emissions is a matter of concern for the Japanese authorities and power companies as it may have consequences on the power grid, but is also of global importance as Japan is a significant contributor to global greenhouse gas emissions. In this study, we trained random forest models against daily power data in ten Japanese regions and for different types of power generation to project changes in future power production and its carbon intensity. We used climate variables, heat stress indices, and one variable for the level of human activities. We then used the models trained from the present-day period to estimate the future power demand, carbon intensity, and pertaining CO2 emissions over the period 2020-2100 under three Shared Socioeconomic Pathways (SSPs) scenarios (SSP126, SSP370, and SSP585). The impact of climate change on CO2 emissions via power generation shows seasonal and regional disparities. In cold regions, a decrease in power demand during winter under future warming leads to an overall decrease in power demand over the year. In contrast, the decrease in winter power demand in hot regions can be overcompensated by an increase in summer power demand due to more frequent hot days, resulting in an overall annual increase. From our regional models, power demand is projected to increase the most in most Japanese regions in May, June, September, and October rather than in the middle of summer, as found in previous studies. This increase could result in regular power outages during those months as the power grid could become particularly tense. Overall, we observed that power demand in regions with extreme climates is more sensitive to global warming than in temperate regions. The impact of climate change on power demand induces a net annual decrease in CO2 emissions in all regions except for Okinawa, in which power demand strongly increases during the summer, resulting in a net annual increase in CO2 emissions. However, climate change's impact on carbon intensity may reverse the trend in some regions (Shikoku, Tohoku). Additionally, we assessed the relative impacts of socioeconomic factors such as population, GDP, and environmental policies on CO2 emissions. When combined with these factors, we found that the climate change effect is more important than when considered individually and significantly impacts total CO2 emissions under SSP585. The contrasting results observed in the warm and cold regions of Japan can offer valuable insight into the potential future variations in energy demand and resulting CO2 emissions on a global scale.
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Affiliation(s)
- Léna Gurriaran
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France; ATOS, River Ouest, Bezons, Cedex, 95877, France.
| | - Katsumasa Tanaka
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France; Earth System Division, National Institute for Environmental Studies (NIES), Tsukuba, Japan.
| | - Kiyoshi Takahashi
- Social Systems Division, National Institute for Environmental Studies (NIES), Tsukuba, Japan
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
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19
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van der Woude AM, Peters W, Joetzjer E, Lafont S, Koren G, Ciais P, Ramonet M, Xu Y, Bastos A, Botía S, Sitch S, de Kok R, Kneuer T, Kubistin D, Jacotot A, Loubet B, Herig-Coimbra PH, Loustau D, Luijkx IT. Author Correction: Temperature extremes of 2022 reduced carbon uptake by forests in Europe. Nat Commun 2023; 14:6976. [PMID: 37914728 PMCID: PMC10620409 DOI: 10.1038/s41467-023-42798-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/03/2023] Open
Affiliation(s)
- Auke M van der Woude
- University of Groningen, Centre for Isotope Research, Groningen, 8481 NG, The Netherlands
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
| | - Wouter Peters
- University of Groningen, Centre for Isotope Research, Groningen, 8481 NG, The Netherlands.
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands.
| | - Emilie Joetzjer
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, 54000, Nancy, France
| | - Sébastien Lafont
- Functional Ecology and Environmental Physics, Ephyse, INRA, Villenave d'Ornon, France
| | - Gerbrand Koren
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands
| | - Philippe Ciais
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Michel Ramonet
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Yidi Xu
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Ana Bastos
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | | | - Stephen Sitch
- Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
| | - Remco de Kok
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
- ICOS ERIC, Carbon Portal, Geocentrum II, Sölvegatan 12, SE-22362, Lund, Sweden
| | - Tobias Kneuer
- Deutscher Wetterdienst, Hohenpeissenberg Meteorological Observatory, Hohenpeissenberg, Germany
| | - Dagmar Kubistin
- Deutscher Wetterdienst, Hohenpeissenberg Meteorological Observatory, Hohenpeissenberg, Germany
| | - Adrien Jacotot
- Sol, Agro et hydrosystèmes, Spatialisation (SAS), UMR 1069, INRAE, Institut Agro, Rennes, France
| | - Benjamin Loubet
- Université Paris Saclay, AgroParisTech, INRAE, UMR 1402 ECOSYS, 91120, Palaiseau, France
| | | | - Denis Loustau
- ISPA, Bordeaux Sciences Agro, INRAE, F-33140, Villenave d'Ornon, France
| | - Ingrid T Luijkx
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
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20
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van der Woude AM, Peters W, Joetzjer E, Lafont S, Koren G, Ciais P, Ramonet M, Xu Y, Bastos A, Botía S, Sitch S, de Kok R, Kneuer T, Kubistin D, Jacotot A, Loubet B, Herig-Coimbra PH, Loustau D, Luijkx IT. Temperature extremes of 2022 reduced carbon uptake by forests in Europe. Nat Commun 2023; 14:6218. [PMID: 37803032 PMCID: PMC10558467 DOI: 10.1038/s41467-023-41851-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 08/30/2023] [Indexed: 10/08/2023] Open
Abstract
The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km2) of the European continent was under severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe's developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests.
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Affiliation(s)
- Auke M van der Woude
- University of Groningen, Centre for Isotope Research, Groningen, 8481 NG, The Netherlands
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
| | - Wouter Peters
- University of Groningen, Centre for Isotope Research, Groningen, 8481 NG, The Netherlands.
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands.
| | - Emilie Joetzjer
- Université de Lorraine, AgroParisTech, INRAE, UMR Silva, 54000, Nancy, France
| | - Sébastien Lafont
- Functional Ecology and Environmental Physics, Ephyse, INRA, Villenave d'Ornon, France
| | - Gerbrand Koren
- Copernicus Institute of Sustainable Development, Utrecht University, Utrecht, The Netherlands
| | - Philippe Ciais
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Michel Ramonet
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Yidi Xu
- UMR CEA-CNRS-UVSQ, Laboratoire des Sciences du Climat et de l'Environnement, Gif sur Yvette, France
| | - Ana Bastos
- Max Planck Institute for Biogeochemistry, Jena, Germany
| | | | - Stephen Sitch
- Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
| | - Remco de Kok
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
- ICOS ERIC, Carbon Portal, Geocentrum II, Sölvegatan 12, SE-22362, Lund, Sweden
| | - Tobias Kneuer
- Deutscher Wetterdienst, Hohenpeissenberg Meteorological Observatory, Hohenpeissenberg, Germany
| | - Dagmar Kubistin
- Deutscher Wetterdienst, Hohenpeissenberg Meteorological Observatory, Hohenpeissenberg, Germany
| | - Adrien Jacotot
- Sol, Agro et hydrosystèmes, Spatialisation (SAS), UMR 1069, INRAE, Institut Agro, Rennes, France
| | - Benjamin Loubet
- Université Paris Saclay, AgroParisTech, INRAE, UMR 1402 ECOSYS, 91120, Palaiseau, France
| | | | - Denis Loustau
- ISPA, Bordeaux Sciences Agro, INRAE, F-33140, Villenave d'Ornon, France
| | - Ingrid T Luijkx
- Wageningen University, Meteorology & Air Quality Dept, Wageningen, 6700 AA, The Netherlands
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21
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Liu S, Brandt M, Nord-Larsen T, Chave J, Reiner F, Lang N, Tong X, Ciais P, Igel C, Pascual A, Guerra-Hernandez J, Li S, Mugabowindekwe M, Saatchi S, Yue Y, Chen Z, Fensholt R. The overlooked contribution of trees outside forests to tree cover and woody biomass across Europe. Sci Adv 2023; 9:eadh4097. [PMID: 37713489 PMCID: PMC10881069 DOI: 10.1126/sciadv.adh4097] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 08/15/2023] [Indexed: 09/17/2023]
Abstract
Trees are an integral part in European landscapes, but only forest resources are systematically assessed by national inventories. The contribution of urban and agricultural trees to national-level carbon stocks remains largely unknown. Here we produced canopy cover, height and above-ground biomass maps from 3-meter resolution nanosatellite imagery across Europe. Our biomass estimates have a systematic bias of 7.6% (overestimation; R = 0.98) compared to national inventories of 30 countries, and our dataset is sufficiently highly resolved spatially to support the inclusion of tree biomass outside forests, which we quantify to 0.8 petagrams. Although this represents only 2% of the total tree biomass, large variations between countries are found (10% for UK) and trees in urban areas contribute substantially to national carbon stocks (8% for the Netherlands). The agreement with national inventory data, the scalability, and spatial details across landscapes, including trees outside forests, make our approach attractive for operational implementation to support national carbon stock inventory schemes.
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Affiliation(s)
- Siyu Liu
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Thomas Nord-Larsen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Jerome Chave
- Laboratoire Evolution et Diversité Biologique, CNRS, UPS, IRD, Université Paul Sabatier, Toulouse, France
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Nico Lang
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Xiaoye Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | - Christian Igel
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Adrian Pascual
- Department of Geographical Sciences, University of Maryland, College Park, MD, USA
| | - Juan Guerra-Hernandez
- Forest Research Center, School of Agriculture, University of Lisbon, Lisbon, Portugal
| | - Sizhuo Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Maurice Mugabowindekwe
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Sassan Saatchi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Yuemin Yue
- Key Laboratory for Agro-ecological Processes in Subtropical Region, Institute of Subtropical Agriculture, Chinese Academy of Sciences, Changsha, China
| | - Zhengchao Chen
- Airborne Remote Sensing Center, Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing, China
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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22
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Albarus I, Fleischmann G, Aigner P, Ciais P, Denier van der Gon H, Droge R, Lian J, Narvaez Rincon MA, Utard H, Lauvaux T. From political pledges to quantitative mapping of climate mitigation plans: Comparison of two European cities. Carbon Balance Manag 2023; 18:18. [PMID: 37672136 PMCID: PMC10481584 DOI: 10.1186/s13021-023-00236-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Accepted: 08/20/2023] [Indexed: 09/07/2023]
Abstract
BACKGROUND Urban agglomerates play a crucial role in reaching global climate objectives. Many cities have committed to reducing their greenhouse gas emissions, but current emission trends remain unverifiable. Atmospheric monitoring of greenhouse gases offers an independent and transparent strategy to measure urban emissions. However, careful design of the monitoring network is crucial to be able to monitor the most important sectors as well as adjust to rapidly changing urban landscapes. RESULTS Our study of Paris and Munich demonstrates how climate action plans, carbon emission inventories, and urban development plans can help design optimal atmospheric monitoring networks. We show that these two European cities display widely different trajectories in space and time, reflecting different emission reduction strategies and constraints due to administrative boundaries. The projected carbon emissions rely on future actions, hence uncertain, and we demonstrate how emission reductions vary significantly at the sub-city level. CONCLUSIONS We conclude that quantified individual cities' climate actions are essential to construct more robust emissions trajectories at the city scale. Also, harmonization and compatibility of plans from various cities are necessary to make inter-comparisons of city climate targets possible. Furthermore, dense atmospheric networks extending beyond the city limits are needed to track emission trends over the coming decades.
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Affiliation(s)
- Ivonne Albarus
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif sur Yvette Cedex, France.
- Origins.earth, Suez Group, 92040, Paris La Défense, France.
| | | | - Patrick Aigner
- Environmental Sensing and Modeling, Technical University of Munich (TUM), Munich, Germany
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif sur Yvette Cedex, France
| | | | - Rianne Droge
- Department of Climate, Air and Sustainability, TNO, Utrecht, The Netherlands
| | - Jinghui Lian
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif sur Yvette Cedex, France
- Origins.earth, Suez Group, 92040, Paris La Défense, France
| | | | - Hervé Utard
- Origins.earth, Suez Group, 92040, Paris La Défense, France
| | - Thomas Lauvaux
- GSMA, UMR 7331, University of Reims Champagne Ardenne, Reims, France
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23
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He L, Wang J, Ciais P, Ballantyne A, Yu K, Zhang W, Xiao J, Ritter F, Liu Z, Wang X, Li X, Peng S, Ma C, Zhou C, Li ZL, Xie Y, Ye JS. Non-symmetric responses of leaf onset date to natural warming and cooling in northern ecosystems. PNAS Nexus 2023; 2:pgad308. [PMID: 37780232 PMCID: PMC10538477 DOI: 10.1093/pnasnexus/pgad308] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 09/11/2023] [Indexed: 10/03/2023]
Abstract
The northern hemisphere has experienced regional cooling, especially during the global warming hiatus (1998-2012) due to ocean energy redistribution. However, the lack of studies about the natural cooling effects hampers our understanding of vegetation responses to climate change. Using 15,125 ground phenological time series at 3,620 sites since the 1950s and 31-year satellite greenness observations (1982-2012) covering the warming hiatus period, we show a stronger response of leaf onset date (LOD) to natural cooling than to warming, i.e. the delay of LOD caused by 1°C cooling is larger than the advance of LOD with 1°C warming. This might be because cooling leads to larger chilling accumulation and heating requirements for leaf onset, but this non-symmetric LOD response is partially offset by warming-related drying. Moreover, spring greening magnitude, in terms of satellite-based greenness and productivity, is more sensitive to LOD changes in the warming area than in the cooling. These results highlight the importance of considering non-symmetric responses of spring greening to warming and cooling when predicting vegetation-climate feedbacks.
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Affiliation(s)
- Lei He
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
- State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Jian Wang
- Department of Geography, The Ohio State University, Columbus, OH 43210, USA
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l′Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91191, France
| | - Ashley Ballantyne
- Laboratoire des Sciences du Climat et de l′Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91191, France
- Department of Ecosystem and Conservation Sciences, University of Montana, Missoula, MT 59801, USA
| | - Kailiang Yu
- Laboratoire des Sciences du Climat et de l′Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91191, France
- Department of Ecology & Evolutionary Biology, Princeton University, Princeton, NJ 08544, USA
| | - Wenxin Zhang
- Department of Physical Geography and Ecosystem Science, Lund University, Lund 22362, Sweden
| | - Jingfeng Xiao
- Earth Systems Research Center, Institute for the Study of Earth, Oceans, and Space, University of New Hampshire, Durham, NH 03824, USA
| | - François Ritter
- Laboratoire des Sciences du Climat et de l′Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette 91191, France
| | - Zhihua Liu
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China
| | - Xufeng Wang
- Key Laboratory of Remote Sensing of Gansu Province, Heihe Remote Sensing Experimental Research Station, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
| | - Xiaojun Li
- INRAE, UMR1391 ISPA, Université de Bordeaux, Villenave d′Ornon 33140, France
| | - Shouzhang Peng
- State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Northwest A&F University, Yangling 712100, China
| | - Changhui Ma
- State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Chenghu Zhou
- Center for Ocean Remote Sensing of Southern Marine Science and Engineering Guangdong Laboratory (Guangzhou), Guangzhou Institute of Geography, Guangdong Academy of Sciences, Guangzhou 510070, China
| | - Zhao-Liang Li
- State Key Laboratory of Efficient Utilization of Arid and Semi-arid Arable Land in Northern China, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing 100081, China
- State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
| | - Yaowen Xie
- College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China
- Key Laboratory of Western China's Environmental Systems (Ministry of Education), Lanzhou University, Lanzhou 730000, China
| | - Jian-Sheng Ye
- State Key Laboratory of Herbage Improvement and Grassland Agro-Ecosystems, College of Ecology, Lanzhou University, Lanzhou 730000, China
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24
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Yan Y, Lauerwald R, Wang X, Regnier P, Ciais P, Ran L, Gao Y, Huang L, Zhang Y, Duan Z, Papa F, Yu B, Piao S. Increasing riverine export of dissolved organic carbon from China. Glob Chang Biol 2023; 29:5014-5032. [PMID: 37332159 DOI: 10.1111/gcb.16819] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 05/23/2023] [Accepted: 05/23/2023] [Indexed: 06/20/2023]
Abstract
River transport of dissolved organic carbon (DOC) to the ocean is a crucial but poorly quantified regional carbon cycle component. Large uncertainties remaining on the riverine DOC export from China, as well as its trend and drivers of change, have challenged the reconciliation between atmosphere-based and land-based estimates of China's land carbon sink. Here, we harmonized a large database of riverine in-situ measurements and applied a random forest model, to quantify riverine DOC fluxes (FDOC ) and DOC concentrations (CDOC ) in rivers across China. This study proposes the first DOC modeling effort capable of reproducing well the magnitude of riverine CDOC and FDOC , as well as its trends, on a monthly scale and with a much wider spatial distribution over China compared to previous studies that mainly focused on annual-scale estimates and large rivers. Results show that over the period 2001-2015, the average CDOC was 2.25 ± 0.45 mg/L and average FDOC was 4.04 ± 1.02 Tg/year. Simultaneously, we found a significant increase in FDOC (+0.044 Tg/year2 , p = .01), but little change in CDOC (-0.001 mg/L/year, p > .10). Although the trend in CDOC is not significant at the country scale, it is significantly increasing in the Yangtze River Basin and Huaihe River Basin (0.005 and 0.013 mg/L/year, p < .05) while significantly decreasing in the Yellow River Basin and Southwest Rivers Basin (-0.043 and -0.014 mg/L/year, p = .01). Changes in hydrology, play a stronger role than direct impacts of anthropogenic activities in determining the spatio-temporal variability of FDOC and CDOC across China. However, and in contrast with other basins, the significant increase in CDOC in the Yangtze River Basin and Huaihe River Basin is attributable to direct anthropogenic activities. Given the dominance of hydrology in driving FDOC , the increase in FDOC is likely to continue under the projected increase in river discharge over China resulting from a future wetter climate.
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Affiliation(s)
- Yanzi Yan
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ronny Lauerwald
- Université Paris-Saclay, INRAE, AgroParisTech, UMR ECOSYS, Thiverval-Grignon, France
- Department Geoscience, Environment & Society-BGEOSYS, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Xuhui Wang
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Pierre Regnier
- Department Geoscience, Environment & Society-BGEOSYS, Université Libre de Bruxelles, Bruxelles, Belgium
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, IPSL-LSCE CEA/CNRS/UVSQ, Orme des Merisiers, Gif sur Yvette, France
| | - Lishan Ran
- Department of Geography, The University of Hong Kong, Hong Kong, China
| | - Yuanyi Gao
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Ling Huang
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yao Zhang
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Zheng Duan
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Fabrice Papa
- University of Toulouse, LEGOS (IRD/CNES/CNRS/UPS), Toulouse, France
- Universidade de Brasília (UnB), IRD, Instituto de Geociências, Brasília, Brazil
| | - Bing Yu
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Shilong Piao
- Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing, China
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
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25
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Graf A, Wohlfahrt G, Aranda-Barranco S, Arriga N, Brümmer C, Ceschia E, Ciais P, Desai AR, Di Lonardo S, Gharun M, Grünwald T, Hörtnagl L, Kasak K, Klosterhalfen A, Knohl A, Kowalska N, Leuchner M, Lindroth A, Mauder M, Migliavacca M, Morel AC, Pfennig A, Poorter H, Terán CP, Reitz O, Rebmann C, Sanchez-Azofeifa A, Schmidt M, Šigut L, Tomelleri E, Yu K, Varlagin A, Vereecken H. Joint optimization of land carbon uptake and albedo can help achieve moderate instantaneous and long-term cooling effects. Commun Earth Environ 2023; 4:298. [PMID: 38665193 PMCID: PMC11041785 DOI: 10.1038/s43247-023-00958-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Accepted: 08/07/2023] [Indexed: 04/28/2024]
Abstract
Both carbon dioxide uptake and albedo of the land surface affect global climate. However, climate change mitigation by increasing carbon uptake can cause a warming trade-off by decreasing albedo, with most research focusing on afforestation and its interaction with snow. Here, we present carbon uptake and albedo observations from 176 globally distributed flux stations. We demonstrate a gradual decline in maximum achievable annual albedo as carbon uptake increases, even within subgroups of non-forest and snow-free ecosystems. Based on a paired-site permutation approach, we quantify the likely impact of land use on carbon uptake and albedo. Shifting to the maximum attainable carbon uptake at each site would likely cause moderate net global warming for the first approximately 20 years, followed by a strong cooling effect. A balanced policy co-optimizing carbon uptake and albedo is possible that avoids warming on any timescale, but results in a weaker long-term cooling effect.
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Affiliation(s)
- Alexander Graf
- Institute of Bio- and Geosciences: Agrosphere (IBG-3), Research Centre Jülich, Jülich, Germany
| | - Georg Wohlfahrt
- Universität Innsbruck, Institut für Ökologie, Innsbruck, Austria
| | - Sergio Aranda-Barranco
- Andalusian Institute for Earth System Research (IISTA-CEAMA), 18071 Granada, Spain
- Departament of Ecology, University of Granada, 18071 Granada, Spain
| | - Nicola Arriga
- European Commission, Joint Research Centre (JRC), Ispra, Italy
| | - Christian Brümmer
- Thünen Institute of Climate-Smart Agriculture, Braunschweig, Germany
| | - Eric Ceschia
- CESBIO, Université de Toulouse, CNES/CNRS/INRA/IRD/UPS, Toulouse, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191 France
| | - Ankur R. Desai
- Department of Atmospheric and Oceanic Sciences, University of Wisconsin-Madison, Madison, WI USA
| | - Sara Di Lonardo
- Research Institute on Terrestrial Ecosystems-National Research Council (IRET-CNR), Sesto Fiorentino, Italy
| | - Mana Gharun
- Institute of Landscape Ecology, University of Münster, Münster, Germany
| | - Thomas Grünwald
- Technische Universität Dresden, Institute of Hydrology and Meteorology, Dresden, Germany
| | - Lukas Hörtnagl
- Department of Environmental Systems Science, ETH Zürich, Universitätstrasse 2, Zürich, 8092 Switzerland
| | - Kuno Kasak
- Department of Geography, University of Tartu, Tartu, Estonia
| | | | | | - Natalia Kowalska
- Global Change Research Institute CAS, Bělidla 986/4a, CZ-60300 Brno, Czech Republic
| | - Michael Leuchner
- Physical Geography and Climatology, Institute of Geography, RWTH Aachen University, Aachen, Germany
| | - Anders Lindroth
- Department of Physical Geography and Ecosystem Science, Lund University, Lund, Sweden
| | - Matthias Mauder
- Technische Universität Dresden, Institute of Hydrology and Meteorology, Dresden, Germany
| | | | - Alexandra C. Morel
- Division of Energy, Environment and Society, University of Dundee, Dundee, UK
| | - Andreas Pfennig
- Department of Chemical Engineering, University of Liège, Liège, Belgium
| | - Hendrik Poorter
- Institute of Bio- and Geosciences: Plant Sciences (IBG-2), Research Centre Jülich, Jülich, Germany
- Department of Natural Sciences, Macquarie University, North Ryde, NSW 2109 Australia
| | - Christian Poppe Terán
- Institute of Bio- and Geosciences: Agrosphere (IBG-3), Research Centre Jülich, Jülich, Germany
| | - Oliver Reitz
- Physical Geography and Climatology, Institute of Geography, RWTH Aachen University, Aachen, Germany
| | - Corinna Rebmann
- Department Computational Hydrosystems, Helmholtz Centre for Environmental Research (UFZ), Permoserstr. 15, 04318 Leipzig, Germany
| | - Arturo Sanchez-Azofeifa
- Earth and Atmospheric Sciences Department, Centre for Earth Observation Sciences (CEOS), Edmonton, AB Canada
| | - Marius Schmidt
- Institute of Bio- and Geosciences: Agrosphere (IBG-3), Research Centre Jülich, Jülich, Germany
| | - Ladislav Šigut
- Global Change Research Institute CAS, Bělidla 986/4a, CZ-60300 Brno, Czech Republic
| | - Enrico Tomelleri
- Faculty of Agricultural, Environmental and Food Sciences, Free University of Bolzano, Piazza Università 5, 39100 Bolzano, Italy
| | - Ke Yu
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, 91191 France
| | - Andrej Varlagin
- A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, 119071 Leninsky pr.33, Moscow, Russia
| | - Harry Vereecken
- Institute of Bio- and Geosciences: Agrosphere (IBG-3), Research Centre Jülich, Jülich, Germany
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26
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Li H, Zheng B, Ciais P, Boersma KF, Riess TCVW, Martin RV, Broquet G, van der A R, Li H, Hong C, Lei Y, Kong Y, Zhang Q, He K. Satellite reveals a steep decline in China's CO 2 emissions in early 2022. Sci Adv 2023; 9:eadg7429. [PMID: 37478188 PMCID: PMC10361590 DOI: 10.1126/sciadv.adg7429] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 06/16/2023] [Indexed: 07/23/2023]
Abstract
Response actions to the coronavirus disease 2019 perturbed economies and carbon dioxide (CO2) emissions. The Omicron variant that emerged in 2022 caused more substantial infections than in 2020 and 2021 but it has not yet been ascertained whether Omicron interrupted the temporary post-2021 rebound of CO2 emissions. Here, using satellite nitrogen dioxide observations combined with atmospheric inversion, we show a larger decline in China's CO2 emissions between January and April 2022 than in those months during the first wave of 2020. China's CO2 emissions are estimated to have decreased by 15% (equivalent to -244.3 million metric tons of CO2) during the 2022 lockdown, greater than the 9% reduction during the 2020 lockdown. Omicron affected most of the populated and industrial provinces in 2022, hindering China's CO2 emissions rebound starting from 2021. China's emission variations agreed with downstream CO2 concentration changes, indicating a potential to monitor CO2 emissions by integrating satellite and ground measurements.
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Affiliation(s)
- Hui Li
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Bo Zheng
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Philippe Ciais
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - K. Folkert Boersma
- Department of Meteorology and Air Quality, Wageningen University, Wageningen, Netherlands
- Climate Observations Department, Royal Netherlands Meteorological Institute, De Bilt, Netherlands
| | | | - Randall V. Martin
- Department of Energy, Environmental and Chemical Engineering, Washington University, St. Louis, MO, USA
- Department of Physics and Atmospheric Science, Dalhousie University, Halifax, NS, Canada
| | - Gregoire Broquet
- Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Ronald van der A
- R&D Satellite Observations, Royal Netherlands Meteorological Institute (KNMI), De Bilt, Netherlands
| | - Haiyan Li
- School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China
| | - Chaopeng Hong
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yu Lei
- Chinese Academy of Environmental Planning, Beijing 100012, China
| | - Yawen Kong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
- State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
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27
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Li Z, Ciais P, Wright JS, Wang Y, Liu S, Wang J, Li LZX, Lu H, Huang X, Zhu L, Goll DS, Li W. Increased precipitation over land due to climate feedback of large-scale bioenergy cultivation. Nat Commun 2023; 14:4096. [PMID: 37433799 DOI: 10.1038/s41467-023-39803-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 06/27/2023] [Indexed: 07/13/2023] Open
Abstract
Bioenergy with carbon capture and storage (BECCS) is considered to be a key technology for removing carbon dioxide from the atmosphere. However, large-scale bioenergy crop cultivation results in land cover changes and activates biophysical effects on climate, with earth's water recycling altered and energy budget re-adjusted. Here, we use a coupled atmosphere-land model with explicit representations of high-transpiration woody (i.e., eucalypt) and low-transpiration herbaceous (i.e., switchgrass) bioenergy crops to investigate the range of impact of large-scale rainfed bioenergy crop cultivation on the global water cycle and atmospheric water recycling. We find that global land precipitation increases under BECCS scenarios, due to enhanced evapotranspiration and inland moisture advection. Despite enhanced evapotranspiration, soil moisture decreases only slightly, due to increased precipitation and reduced runoff. Our results indicate that, at the global scale, the water consumption by bioenergy crop growth would be partially compensated by atmospheric feedbacks. Thus, to support more effective climate mitigation policies, a more comprehensive assessment, including the biophysical effects of bioenergy cultivation, is highly recommended.
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Affiliation(s)
- Zhao Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Jonathon S Wright
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Yong Wang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Shu Liu
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Jingmeng Wang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Laurent Z X Li
- Laboratoire de Météorologie Dynamique, Centre National de la Recherche Scientifique, Sorbonne Université, Ecole Normale Supérieure, Ecole Polytechnique, 75252, Paris, France
| | - Hui Lu
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Xiaomeng Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Lei Zhu
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China
| | - Daniel S Goll
- Université Paris Saclay, CEA-CNRS-UVSQ, LSCE/IPSL, Gif sur Yvette, France
| | - Wei Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, 100084, Beijing, China.
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, 100084, Beijing, China.
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28
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Wang Y, Wang R, Tanaka K, Ciais P, Penuelas J, Balkanski Y, Sardans J, Hauglustaine D, Liu W, Xing X, Li J, Xu S, Xiong Y, Yang R, Cao J, Chen J, Wang L, Tang X, Zhang R. Accelerating the energy transition towards photovoltaic and wind in China. Nature 2023; 619:761-767. [PMID: 37495878 PMCID: PMC10371865 DOI: 10.1038/s41586-023-06180-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2022] [Accepted: 05/09/2023] [Indexed: 07/28/2023]
Abstract
China's goal to achieve carbon (C) neutrality by 2060 requires scaling up photovoltaic (PV) and wind power from 1 to 10-15 PWh year-1 (refs. 1-5). Following the historical rates of renewable installation1, a recent high-resolution energy-system model6 and forecasts based on China's 14th Five-year Energy Development (CFED)7, however, only indicate that the capacity will reach 5-9.5 PWh year-1 by 2060. Here we show that, by individually optimizing the deployment of 3,844 new utility-scale PV and wind power plants coordinated with ultra-high-voltage (UHV) transmission and energy storage and accounting for power-load flexibility and learning dynamics, the capacity of PV and wind power can be increased from 9 PWh year-1 (corresponding to the CFED path) to 15 PWh year-1, accompanied by a reduction in the average abatement cost from US$97 to US$6 per tonne of carbon dioxide (tCO2). To achieve this, annualized investment in PV and wind power should ramp up from US$77 billion in 2020 (current level) to US$127 billion in the 2020s and further to US$426 billion year-1 in the 2050s. The large-scale deployment of PV and wind power increases income for residents in the poorest regions as co-benefits. Our results highlight the importance of upgrading power systems by building energy storage, expanding transmission capacity and adjusting power load at the demand side to reduce the economic cost of deploying PV and wind power to achieve carbon neutrality in China.
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Affiliation(s)
- Yijing Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Rong Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China.
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China.
- Institute of Atmospheric Sciences, Fudan University, Shanghai, China.
- Shanghai Frontiers Science Center of Atmosphere-Ocean Interaction, Shanghai, China.
- MOE Laboratory for National Development and Intelligent Governance, Fudan University, Shanghai, China.
- Institute of Eco-Chongming (IEC), Shanghai, China.
- National Observations and Research Station for Wetland Ecosystems of the Yangtze Estuary, Fudan University, Shanghai, China.
| | - Katsumasa Tanaka
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- Earth System Division, National Institute for Environmental Studies (NIES), Tsukuba, Japan
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Josep Penuelas
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Spain
- CREAF, Cerdanyola del Vallès, Spain
| | - Yves Balkanski
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Jordi Sardans
- CSIC, Global Ecology Unit CREAF-CSIC-UAB, Bellaterra, Spain
- CREAF, Cerdanyola del Vallès, Spain
| | - Didier Hauglustaine
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), CEA/CNRS/UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Wang Liu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Xiaofan Xing
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Jiarong Li
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Siqing Xu
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Yuankang Xiong
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Ruipu Yang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Junji Cao
- Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Jianmin Chen
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Lin Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention (LAP3), Department of Environmental Science and Engineering, Fudan University, Shanghai, China
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Xu Tang
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- Institute of Atmospheric Sciences, Fudan University, Shanghai, China
| | - Renhe Zhang
- IRDR International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, China
- Institute of Atmospheric Sciences, Fudan University, Shanghai, China
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29
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Ke P, Deng Z, Zhu B, Zheng B, Wang Y, Boucher O, Arous SB, Zhou C, Andrew RM, Dou X, Sun T, Song X, Li Z, Yan F, Cui D, Hu Y, Huo D, Chang JP, Engelen R, Davis SJ, Ciais P, Liu Z. Carbon Monitor Europe near-real-time daily CO 2 emissions for 27 EU countries and the United Kingdom. Sci Data 2023; 10:374. [PMID: 37291162 DOI: 10.1038/s41597-023-02284-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2023] [Accepted: 05/31/2023] [Indexed: 06/10/2023] Open
Abstract
With the urgent need to implement the EU countries pledges and to monitor the effectiveness of Green Deal plan, Monitoring Reporting and Verification tools are needed to track how emissions are changing for all the sectors. Current official inventories only provide annual estimates of national CO2 emissions with a lag of 1+ year which do not capture the variations of emissions due to recent shocks including COVID lockdowns and economic rebounds, war in Ukraine. Here we present a near-real-time country-level dataset of daily fossil fuel and cement emissions from January 2019 through December 2021 for 27 EU countries and UK, which called Carbon Monitor Europe. The data are calculated separately for six sectors: power, industry, ground transportation, domestic aviation, international aviation and residential. Daily CO2 emissions are estimated from a large set of activity data compiled from different sources. The goal of this dataset is to improve the timeliness and temporal resolution of emissions for European countries, to inform the public and decision makers about current emissions changes in Europe.
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Affiliation(s)
- Piyu Ke
- Department of Earth System Science, Tsinghua University, Beijing, China
- Department of Mathematics and Statistics, Faculty of Environment, Science and Economy, University of Exeter, Exeter, UK
| | - Zhu Deng
- Department of Earth System Science, Tsinghua University, Beijing, China
- Alibaba Cloud, Hangzhou, China
| | - Biqing Zhu
- Department of Earth System Science, Tsinghua University, Beijing, China
- Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France
| | - Bo Zheng
- Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen, 518055, China
| | - Yilong Wang
- Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China
| | - Olivier Boucher
- Institute Pierre-Simon Laplace, Sorbonne Université/CNRS, Paris, France
| | | | - Chuanlong Zhou
- Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France
| | - Robbie M Andrew
- CICERO Center for International Climate Research, Oslo, 0349, Norway
| | - Xinyu Dou
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Taochun Sun
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Xuanren Song
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Zhao Li
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Feifan Yan
- Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ministry of Education, Ocean University of China, Qingdao, 266100, China
| | - Duo Cui
- Department of Earth System Science, Tsinghua University, Beijing, China
| | - Yifan Hu
- Key Laboratory of Sustainable Forest Ecosystem Management, Northeast Forestry University, Harbin, 150040, China
| | - Da Huo
- Department of Earth System Science, Tsinghua University, Beijing, China
- Department of Civil & Mineral Engineering, University of Toronto, Toronto, ON, M5S 1A4, Canada
| | | | - Richard Engelen
- European Centre for Medium-Range Weather Forecasts, Reading, RG2 9AX, UK
| | - Steven J Davis
- Department of Earth System Science, University of California, Irvine, 3232 Croul Hall, Irvine, CA, 92697-3100, USA
| | - Philippe Ciais
- Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France.
- Climate and Atmosphere Research Center (CARE-C) The Cyprus Institute 20 Konstantinou Kavafi Street, 2121, Nicosia, Cyprus.
| | - Zhu Liu
- Department of Earth System Science, Tsinghua University, Beijing, China.
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Tao F, Huang Y, Hungate BA, Manzoni S, Frey SD, Schmidt MWI, Reichstein M, Carvalhais N, Ciais P, Jiang L, Lehmann J, Wang YP, Houlton BZ, Ahrens B, Mishra U, Hugelius G, Hocking TD, Lu X, Shi Z, Viatkin K, Vargas R, Yigini Y, Omuto C, Malik AA, Peralta G, Cuevas-Corona R, Di Paolo LE, Luotto I, Liao C, Liang YS, Saynes VS, Huang X, Luo Y. Microbial carbon use efficiency promotes global soil carbon storage. Nature 2023; 618:981-985. [PMID: 37225998 PMCID: PMC10307633 DOI: 10.1038/s41586-023-06042-3] [Citation(s) in RCA: 35] [Impact Index Per Article: 35.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/16/2021] [Accepted: 04/03/2023] [Indexed: 05/26/2023]
Abstract
Soils store more carbon than other terrestrial ecosystems1,2. How soil organic carbon (SOC) forms and persists remains uncertain1,3, which makes it challenging to understand how it will respond to climatic change3,4. It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss5-7. Although microorganisms affect the accumulation and loss of soil organic matter through many pathways4,6,8-11, microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes12,13. Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved7,14,15. Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate.
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Affiliation(s)
- Feng Tao
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Yuanyuan Huang
- Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, China
| | - Bruce A Hungate
- Center for Ecosystem Science and Society, Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA
| | - Stefano Manzoni
- Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
| | - Serita D Frey
- Center for Soil Biogeochemistry and Microbial Ecology, Department of Natural Resources and the Environment, University of New Hampshire, Durham, NH, USA
| | | | | | - Nuno Carvalhais
- Max Planck Institute for Biogeochemistry, Jena, Germany
- Departamento de Ciências e Engenharia do Ambiente, DCEA, Faculdade de Ciências e Tecnologia, FCT, Universidade Nova de Lisboa, Caparica, Portugal
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Lifen Jiang
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Johannes Lehmann
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | | | - Benjamin Z Houlton
- Department of Ecology and Evolutionary Biology and Department of Global Development, Cornell University, Ithaca, NY, USA
| | | | - Umakant Mishra
- Computational Biology and Biophysics, Sandia National Laboratories, Livermore, CA, USA
- Joint BioEnergy Institute, Lawrence Berkeley National Laboratory, Emeryville, CA, USA
| | - Gustaf Hugelius
- Department of Physical Geography and Bolin Centre for Climate Research, Stockholm University, Stockholm, Sweden
| | - Toby D Hocking
- School of Informatics, Computing and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA
| | - Xingjie Lu
- School of Atmospheric Sciences, Sun Yat-sen University, Guangzhou, China
| | - Zheng Shi
- Institute for Environmental Genomics and Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
| | - Kostiantyn Viatkin
- Food and Agricultural Organization of the United Nations, Rome, Italy
- Soil and Crop Sciences Section, School of Integrative Plant Science, Cornell University, Ithaca, NY, USA
| | - Ronald Vargas
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Yusuf Yigini
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Christian Omuto
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Ashish A Malik
- School of Biological Sciences, University of Aberdeen, Aberdeen, UK
| | - Guillermo Peralta
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | | | | | - Isabel Luotto
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Cuijuan Liao
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Yi-Shuang Liang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China
| | - Vinisa S Saynes
- Food and Agricultural Organization of the United Nations, Rome, Italy
| | - Xiaomeng Huang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modelling, Institute for Global Change Studies, Tsinghua University, Beijing, China.
| | - Yiqi Luo
- School of Integrative Plant Science, Cornell University, Ithaca, NY, USA.
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Sun Y, Goll DS, Huang Y, Ciais P, Wang YP, Bastrikov V, Wang Y. Machine learning for accelerating process-based computation of land biogeochemical cycles. Glob Chang Biol 2023; 29:3221-3234. [PMID: 36762511 DOI: 10.1111/gcb.16623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/05/2022] [Accepted: 01/02/2023] [Indexed: 05/03/2023]
Abstract
Global change ecology nowadays embraces ever-growing large observational datasets (big-data) and complex mathematical models that track hundreds of ecological processes (big-model). The rapid advancement of the big-data-big-model has reached its bottleneck: high computational requirements prevent further development of models that need to be integrated over long time-scales to simulate the distribution of ecosystems carbon and nutrient pools and fluxes. Here, we introduce a machine-learning acceleration (MLA) tool to tackle this grand challenge. We focus on the most resource-consuming step in terrestrial biosphere models (TBMs): the equilibration of biogeochemical cycles (spin-up), a prerequisite that can take up to 98% of the computational time. Through three members of the ORCHIDEE TBM family part of the IPSL Earth System Model, including versions that describe the complex interactions between nitrogen, phosphorus and carbon that do not have any analytical solution for the spin-up, we show that an unoptimized MLA reduced the computation demand by 77%-80% for global studies via interpolating the equilibrated state of biogeochemical variables for a subset of model pixels. Despite small biases in the MLA-derived equilibrium, the resulting impact on the predicted regional carbon balance over recent decades is minor. We expect a one-order of magnitude lower computation demand by optimizing the choices of machine learning algorithms, their settings, and balancing the trade-off between quality of MLA predictions and need for TBM simulations for training data generation and bias reduction. Our tool is agnostic to gridded models (beyond TBMs), compatible with existing spin-up acceleration procedures, and opens the door to a wide variety of future applications, with complex non-linear models benefit most from the computational efficiency.
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Affiliation(s)
- Yan Sun
- College of Marine Life Sciences, Ocean University of China, Qingdao, China
- Laboratoire des Sciences du Climat et de 1'Environnement, CEA-CNRS-UVSQ, Gif sur Yvette, France
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de 1'Environnement, CEA-CNRS-UVSQ, Gif sur Yvette, France
| | | | - Philippe Ciais
- Laboratoire des Sciences du Climat et de 1'Environnement, CEA-CNRS-UVSQ, Gif sur Yvette, France
| | | | | | - Yilong Wang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment (TPESRE), Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
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Chen B, Kayiranga A, Ge M, Ciais P, Zhang H, Black A, Xiao X, Yuan W, Zeng Z, Piao S. Anthropogenic activities dominated tropical forest carbon balance in two contrary ways over the Greater Mekong Subregion in the 21st century. Glob Chang Biol 2023; 29:3421-3432. [PMID: 36949006 DOI: 10.1111/gcb.16688] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/14/2022] [Accepted: 02/11/2023] [Indexed: 05/16/2023]
Abstract
The tropical forest carbon (C) balance threatened by extensive socio-economic development in the Greater Mekong Subregion (GMS) in Asia is a notable data gap and remains contentious. Here we generated a long-term spatially quantified assessment of changes in forests and C stocks from 1999 to 2019 at a spatial resolution of 30 m, based on multiple streams of state-of-the-art high-resolution satellite imagery and in situ observations. Our results show that (i) about 0.54 million square kilometers (21.0% of the region) experienced forest cover transitions with a net increase in forest cover by 4.3% (0.11 million square kilometers, equivalent to 0.31 petagram of C [Pg C] stocks); (ii) forest losses mainly in Cambodia, Thailand, and in the south of Vietnam, were also counteracted by forest gains in China due mainly to afforestation; and (iii) at the national level during the study period an increase in both C stocks and C sequestration (net C gain of 0.087 Pg C) in China from new plantation, offset anthropogenetic emissions (net C loss of 0.074 Pg C) mainly in Cambodia and Thailand from deforestation. Political, social, and economic factors significantly influenced forest cover change and C sequestration in the GMS, positively in China while negatively in other countries, especially in Cambodia and Thailand. These findings have implications on national strategies for climate change mitigation and adaptation in other hotspots of tropical forests.
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Affiliation(s)
- Baozhang Chen
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, 210044, Nanjing, China
- State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
- University of Chinese Academy of Sciences, 100190, Beijing, China
- Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, 210023, Nanjing, China
| | - Alphonse Kayiranga
- State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
- University of Chinese Academy of Sciences, 100190, Beijing, China
| | - Mengyu Ge
- School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, 210044, Nanjing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Huifang Zhang
- State Key Laboratory of Resource and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, 100101, Beijing, China
| | - Andy Black
- Faculty of Land and Food Systems, University of British Columbia, British Columbia, Vancouver, Canada
| | - Xiangming Xiao
- Department of Microbiology and Plant Biology, Center for Earth Observation and Modeling, University of Oklahoma, Oklahoma, Norman, USA
| | - Wenping Yuan
- School of Atmospheric Sciences, Guangdong Province Key Laboratory for Climate Change and Natural Disaster Studies, Zhuhai Key Laboratory of Dynamics Urban Climate and Ecology, Sun Yat-sen University, 510245, Guangdong, Zhuhai, China
| | - Zhenzhong Zeng
- State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Shilong Piao
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, 100871, Beijing, China
- Key Laboratory of Alpine Ecology and Biodiversity, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, 100085, Beijing, China
- Center for Excellence in Tibetan Plateau Earth Sciences, Chinese Academy of Sciences, 100085, Beijing, China
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Liu L, Ciais P, Wu M, Padrón RS, Friedlingstein P, Schwaab J, Gudmundsson L, Seneviratne SI. Increasingly negative tropical water-interannual CO 2 growth rate coupling. Nature 2023; 618:755-760. [PMID: 37258674 PMCID: PMC10284699 DOI: 10.1038/s41586-023-06056-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2022] [Accepted: 04/05/2023] [Indexed: 06/02/2023]
Abstract
Terrestrial ecosystems have taken up about 32% of the total anthropogenic CO2 emissions in the past six decades1. Large uncertainties in terrestrial carbon-climate feedbacks, however, make it difficult to predict how the land carbon sink will respond to future climate change2. Interannual variations in the atmospheric CO2 growth rate (CGR) are dominated by land-atmosphere carbon fluxes in the tropics, providing an opportunity to explore land carbon-climate interactions3-6. It is thought that variations in CGR are largely controlled by temperature7-10 but there is also evidence for a tight coupling between water availability and CGR11. Here, we use a record of global atmospheric CO2, terrestrial water storage and precipitation data to investigate changes in the interannual relationship between tropical land climate conditions and CGR under a changing climate. We find that the interannual relationship between tropical water availability and CGR became increasingly negative during 1989-2018 compared to 1960-1989. This could be related to spatiotemporal changes in tropical water availability anomalies driven by shifts in El Niño/Southern Oscillation teleconnections, including declining spatial compensatory water effects9. We also demonstrate that most state-of-the-art coupled Earth System and Land Surface models do not reproduce the intensifying water-carbon coupling. Our results indicate that tropical water availability is increasingly controlling the interannual variability of the terrestrial carbon cycle and modulating tropical terrestrial carbon-climate feedbacks.
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Affiliation(s)
- Laibao Liu
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland.
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Université Paris Saclay, Gif-sur-Yvette, France
| | - Mengxi Wu
- Joint Institute for Regional Earth System Science and Engineering (JIFRESSE), University of California, Los Angeles, Los Angeles, CA, USA
| | - Ryan S Padrón
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Pierre Friedlingstein
- College of Engineering, Mathematics and Physical Sciences, University of Exeter, Exeter, UK
| | - Jonas Schwaab
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Lukas Gudmundsson
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
| | - Sonia I Seneviratne
- Institute for Atmospheric and Climate Science, ETH Zurich, Zurich, Switzerland
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Liu X, Sun G, Fu Z, Ciais P, Feng X, Li J, Fu B. Compound droughts slow down the greening of the Earth. Glob Chang Biol 2023; 29:3072-3084. [PMID: 36854491 DOI: 10.1111/gcb.16657] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Revised: 01/23/2023] [Accepted: 02/24/2023] [Indexed: 05/03/2023]
Abstract
Vegetation response to soil and atmospheric drought has raised extensively controversy, however, the relative contributions of soil drought, atmospheric drought, and their compound droughts on global vegetation growth remain unclear. Combining the changes in soil moisture (SM), vapor pressure deficit (VPD), and vegetation growth (normalized difference vegetation index [NDVI]) during 1982-2015, here we evaluated the trends of these three drought types and quantified their impacts on global NDVI. We found that global VPD has increased 0.22 ± 0.05 kPa·decade-1 during 1982-2015, and this trend was doubled after 1996 (0.32 ± 0.16 kPa·decade-1 ) than before 1996 (0.16 ± 0.15 kPa·decade-1 ). Regions with large increase in VPD trend generally accompanied with decreasing trend in SM, leading to a widespread increasing trend in compound droughts across 37.62% land areas. We further found compound droughts dominated the vegetation browning since late 1990s, contributing to a declined NDVI of 64.56%. Earth system models agree with the dominant role of compound droughts on vegetation growth, but their negative magnitudes are considerably underestimated, with half of the observed results (34.48%). Our results provided the evidence of compound droughts-induced global vegetation browning, highlighting the importance of correctly simulating the ecosystem-scale response to the under-appreciated exposure to compound droughts as it will increase with climate change.
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Affiliation(s)
- Xianfeng Liu
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, China
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Gaopeng Sun
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, China
| | - Zheng Fu
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, Gif-sur-Yvette, France
| | - Xiaoming Feng
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
| | - Jing Li
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, China
| | - Bojie Fu
- School of Geography and Tourism, Shaanxi Normal University, Xi'an, China
- State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, China
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35
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Feng M, Peng S, Wang Y, Ciais P, Goll DS, Chang J, Fang Y, Houlton BZ, Liu G, Sun Y, Xi Y. Overestimated nitrogen loss from denitrification for natural terrestrial ecosystems in CMIP6 Earth System Models. Nat Commun 2023; 14:3065. [PMID: 37244896 DOI: 10.1038/s41467-023-38803-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/10/2022] [Accepted: 05/12/2023] [Indexed: 05/29/2023] Open
Abstract
Denitrification and leaching nitrogen (N) losses are poorly constrained in Earth System Models (ESMs). Here, we produce a global map of natural soil 15N abundance and quantify soil denitrification N loss for global natural ecosystems using an isotope-benchmarking method. We show an overestimation of denitrification by almost two times in the 13 ESMs of the Sixth Phase Coupled Model Intercomparison Project (CMIP6, 73 ± 31 Tg N yr-1), compared with our estimate of 38 ± 11 Tg N yr-1, which is rooted in isotope mass balance. Moreover, we find a negative correlation between the sensitivity of plant production to rising carbon dioxide (CO2) concentration and denitrification in boreal regions, revealing that overestimated denitrification in ESMs would translate to an exaggeration of N limitation on the responses of plant growth to elevated CO2. Our study highlights the need of improving the representation of the denitrification in ESMs and better assessing the effects of terrestrial ecosystems on CO2 mitigation.
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Affiliation(s)
- Maoyuan Feng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Shushi Peng
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China.
- Institute of Carbon Neutrality, Peking University, Beijing, China.
| | - Yilong Wang
- State Key Laboratory of Tibetan Plateau Earth System, Resources and Environment, Institute of Tibetan Plateau Research, Chinese Academy of Sciences, Beijing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
- The Cyprus Institute 20 Konstantinou Kavafi Street, 2121, Nicosia, Cyprus
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Jinfeng Chang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou, China
| | - Yunting Fang
- CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang, China
| | - Benjamin Z Houlton
- Department of Ecology and Evolutionary Biology and Department of Global Development, CALS, Cornell University, Ithaca, NY, USA
| | - Gang Liu
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China
- Institute of Carbon Neutrality, Peking University, Beijing, China
| | - Yan Sun
- College of Marine Life Sciences, Ocean University of China, Qingdao, China
| | - Yi Xi
- Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, and Laboratory for Earth Surface Processes, Peking University, Beijing, China
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
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36
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Fendrich AN, Matthews F, Van Eynde E, Carozzi M, Li Z, d'Andrimont R, Lugato E, Martin P, Ciais P, Panagos P. From regional to parcel scale: A high-resolution map of cover crops across Europe combining satellite data with statistical surveys. Sci Total Environ 2023; 873:162300. [PMID: 36828062 DOI: 10.1016/j.scitotenv.2023.162300] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2022] [Revised: 01/12/2023] [Accepted: 02/13/2023] [Indexed: 06/18/2023]
Abstract
The reformed Common Agricultural Policy of 2023-2027 aims to promote a more sustainable and fair agricultural system in the European Union. Among the proposed measures, the incentivized adoption of cover crops to cover the soil during winter provides numerous benefits such as improved soil structure and reduced nutrient leaching and erosion. Despite this recognized importance, the availability of spatial data on cover crops is scarce. The increasing availability of field parcel declarations in the European Union has not yet filled this data gap due to its insufficient information content, limited public availability and a lack of standardization at continental scale. At present, the best information available is regionally aggregated survey data, which although indicative, hinders the development of spatially accurate studies. In this work, we propose a statistical model relating Sentinel-1 data to the existence of cover crops at the 100-m spatial resolution over the entirety of the European Union and United Kingdom and estimate its parameters using the spatially aggregated survey data. To validate the method in a spatially-explicit way, predictions were compared against farmers' registered declarations in France, where the adoption of cover crops is widespread. The results indicate a good agreement between predictions and parcel-level data. When interpreted as a binary classifier, the model yielded an Area Under the Curve (AUC) of 0.74 for the whole country. When the country was divided into five regions for the evaluation of regional biases, the AUC values were 0.77, 0.75, 0.74, 0.70, and 0.65 for the North, Center, West, East, and South regions respectively. Despite limitations such as the lack of data for validation outside France, and the non-standardized nomenclature for cover crops among Member States, this work constitutes the first effort to obtain a relevant cover crop map at a European scale for researchers and practitioners.
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Affiliation(s)
- Arthur Nicolaus Fendrich
- European Commission, Joint Research Centre (JRC), Ispra 21027, Italy; Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSACLAY, Gif sur Yvette 91190, France; Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France.
| | - Francis Matthews
- European Commission, Joint Research Centre (JRC), Ispra 21027, Italy; KU Leuven, Unit of Geography and Tourism, Celestijnenlaan 200e, Leuven 3001, Belgium
| | - Elise Van Eynde
- European Commission, Joint Research Centre (JRC), Ispra 21027, Italy
| | - Marco Carozzi
- Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France
| | - Zheyuan Li
- School of Mathematics and Statistics, Henan University, Kaifeng 475001, China; Department of Statistics and Actuarial Science, Simon Fraser University, University Dr W, 8888, Burnaby, BC V5A 1S6, Canada
| | | | - Emanuele Lugato
- European Commission, Joint Research Centre (JRC), Ispra 21027, Italy
| | - Philippe Martin
- Université Paris-Saclay, INRAE, AgroParisTech, UMR SAD-APT, 91120, Palaiseau, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ-UPSACLAY, Gif sur Yvette 91190, France
| | - Panos Panagos
- European Commission, Joint Research Centre (JRC), Ispra 21027, Italy
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37
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Fu J, Jian Y, Wang X, Li L, Ciais P, Zscheischler J, Wang Y, Tang Y, Müller C, Webber H, Yang B, Wu Y, Wang Q, Cui X, Huang W, Liu Y, Zhao P, Piao S, Zhou F. Extreme rainfall reduces one-twelfth of China's rice yield over the last two decades. Nat Food 2023; 4:416-426. [PMID: 37142747 DOI: 10.1038/s43016-023-00753-6] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/24/2022] [Accepted: 04/11/2023] [Indexed: 05/06/2023]
Abstract
Extreme climate events constitute a major risk to global food production. Among these, extreme rainfall is often dismissed from historical analyses and future projections, the impacts and mechanisms of which remain poorly understood. Here we used long-term nationwide observations and multi-level rainfall manipulative experiments to explore the magnitude and mechanisms of extreme rainfall impacts on rice yield in China. We find that rice yield reductions due to extreme rainfall were comparable to those induced by extreme heat over the last two decades, reaching 7.6 ± 0.9% (one standard error) according to nationwide observations and 8.1 ± 1.1% according to the crop model incorporating the mechanisms revealed from manipulative experiments. Extreme rainfall reduces rice yield mainly by limiting nitrogen availability for tillering that lowers per-area effective panicles and by exerting physical disturbance on pollination that declines per-panicle filled grains. Considering these mechanisms, we projected ~8% additional yield reduction due to extreme rainfall under warmer climate by the end of the century. These findings demonstrate that it is critical to account for extreme rainfall in food security assessments.
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Affiliation(s)
- Jin Fu
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yiwei Jian
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xuhui Wang
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Laurent Li
- Laboratoire de Météorologie Dynamique, CNRS, Sorbonne Université, Paris, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE, Gif sur Yvette, France
- Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, Nicosia, Cyprus
| | - Jakob Zscheischler
- Department of Computational Hydrosystems, Helmholtz Centre for Environmental Research-UFZ, Leipzig, Germany
| | - Yin Wang
- Institute of Ecology, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yanhong Tang
- Institute of Ecology, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Christoph Müller
- Potsdam Institute for Climate Impact Research (PIK), Member of the Leibniz Association, Potsdam, Germany
| | - Heidi Webber
- Leibniz Centre for Agricultural Landscape Research, Müncheberg, Germany
| | - Bo Yang
- Key Laboratory of Nonpoint Source Pollution Control, Institute of Agricultural Resources and Regional Planning, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yali Wu
- National Engineering Laboratory for Lake Pollution Control and Ecological Restoration, Chinese Research Academy of Environmental Sciences, Beijing, China
| | - Qihui Wang
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xiaoqing Cui
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Weichen Huang
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yongqiang Liu
- State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China
| | - Pengjun Zhao
- School of Urban Planning and Design, Peking University Shenzhen Graduate School, Shenzhen, China
| | - Shilong Piao
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Feng Zhou
- Institute of Carbon Neutrality, Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China.
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38
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Reiner F, Brandt M, Tong X, Skole D, Kariryaa A, Ciais P, Davies A, Hiernaux P, Chave J, Mugabowindekwe M, Igel C, Oehmcke S, Gieseke F, Li S, Liu S, Saatchi S, Boucher P, Singh J, Taugourdeau S, Dendoncker M, Song XP, Mertz O, Tucker CJ, Fensholt R. More than one quarter of Africa's tree cover is found outside areas previously classified as forest. Nat Commun 2023; 14:2258. [PMID: 37130845 PMCID: PMC10154416 DOI: 10.1038/s41467-023-37880-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/06/2022] [Accepted: 03/29/2023] [Indexed: 05/04/2023] Open
Abstract
The consistent monitoring of trees both inside and outside of forests is key to sustainable land management. Current monitoring systems either ignore trees outside forests or are too expensive to be applied consistently across countries on a repeated basis. Here we use the PlanetScope nanosatellite constellation, which delivers global very high-resolution daily imagery, to map both forest and non-forest tree cover for continental Africa using images from a single year. Our prototype map of 2019 (RMSE = 9.57%, bias = -6.9%). demonstrates that a precise assessment of all tree-based ecosystems is possible at continental scale, and reveals that 29% of tree cover is found outside areas previously classified as tree cover in state-of-the-art maps, such as in croplands and grassland. Such accurate mapping of tree cover down to the level of individual trees and consistent among countries has the potential to redefine land use impacts in non-forest landscapes, move beyond the need for forest definitions, and build the basis for natural climate solutions and tree-related studies.
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Affiliation(s)
- Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | - Martin Brandt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | - Xiaoye Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - David Skole
- Global Observatory for Ecosystem Services, Department of Forestry, Michigan State University, East Lansing, MI, 48823, USA
| | - Ankit Kariryaa
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA/CNRS/UVSQ/Université Paris Saclay, Gif-sur-Yvette, France
| | - Andrew Davies
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | | | - Jérôme Chave
- Laboratoire Evolution et Diversité Biologique, CNRS, UPS, IRD, Université Paul Sabatier, Toulouse, France
| | - Maurice Mugabowindekwe
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Christian Igel
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Stefan Oehmcke
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Fabian Gieseke
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
- Department of Information Systems, University of Münster, Münster, Germany
| | - Sizhuo Li
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Université Paris Saclay, Gif-sur-Yvette, France
| | - Siyu Liu
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Sassan Saatchi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, 91109, USA
| | - Peter Boucher
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | - Jenia Singh
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02138, USA
| | | | - Morgane Dendoncker
- Earth and Life Institute, Environmental Sciences, Université catholique de Louvain, Louvain-la-Neuve, Belgium
| | - Xiao-Peng Song
- Department of Geographical Sciences, University of Maryland, College Park, MD, 20740, USA
| | - Ole Mertz
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Compton J Tucker
- Earth Sciences Division, NASA Goddard Space Flight Center, Greenbelt, MD, 20771, USA
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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39
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Wang J, Ciais P, Smith P, Yan X, Kuzyakov Y, Liu S, Li T, Zou J. The role of rice cultivation in changes in atmospheric methane concentration and the Global Methane Pledge. Glob Chang Biol 2023; 29:2776-2789. [PMID: 36752684 DOI: 10.1111/gcb.16631] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2022] [Accepted: 02/03/2023] [Indexed: 05/31/2023]
Abstract
Resumption of the increase in atmospheric methane (CH4 ) concentrations since 2007 is of global concern and may partly have resulted from emissions from rice cultivation. Estimates of CH4 emissions from rice fields and abatement potential are essential to assess the contribution of improved rice management in achieving the targets of the Global Methane Pledge agreed upon by over 100 countries at COP26. However, the contribution of CH4 emissions from rice fields to the resumed CH4 growth and the global abatement potential remains unclear. In this study, we estimated the global CH4 emissions from rice fields to be 27 ± 6 Tg CH4 year-1 in the recent decade (2008-2017) based on the 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. The trend of CH4 emissions from rice cultivation showed an increase followed by no significant change and then, a stabilization over 1990-2020. Consequently, the contribution of CH4 emissions from rice fields to the renewed increase in atmospheric CH4 concentrations since 2007 was minor. We summarized the existing low-cost measures and showed that improved water and straw management could reduce one-third of global CH4 emissions from rice fields. Straw returned as biochar could reduce CH4 emissions by 12 Tg CH4 year-1 , equivalent to 10% of the total reduction of all anthropogenic emissions. We conclude that other sectors than rice cultivation must have contributed to the renewed increase in atmospheric CH4 concentrations, and that optimizing multiple mitigation measures in rice fields could contribute significantly to the abatement goal outlined in the Global Methane Pledge.
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Affiliation(s)
- Jinyang Wang
- Key Laboratory of Green and Low-carbon Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
- Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement (LSCE), Institut Pierre Simon Laplace, CEA/CNRS/Université de Versailles Saint-Quentin-en-Yvelines/Université de Paris Saclay, Gif-sur-Yvette, France
| | - Pete Smith
- Institute of Biological and Environmental Sciences, University of Aberdeen, Aberdeen, UK
| | - Xiaoyuan Yan
- State Key Laboratory of Soil and Sustainable Agriculture, Institute of Soil Science, Chinese Academy of Sciences, Nanjing, China
| | - Yakov Kuzyakov
- Department of Soil Science of Temperate Ecosystems, University of Gottingen, Gottingen, Germany
- Peoples Friendship University of Russia (RUDN University), Moscow, Russia
| | - Shuwei Liu
- Key Laboratory of Green and Low-carbon Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
- Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing, China
| | - Tingting Li
- LAPC, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, China
| | - Jianwen Zou
- Key Laboratory of Green and Low-carbon Agriculture in Southeastern China, Ministry of Agriculture and Rural Affairs, College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing, China
- Jiangsu Key Laboratory of Low Carbon Agriculture and GHGs Mitigation, Jiangsu Collaborative Innovation Center for Solid Organic Waste Resource Utilization, Nanjing, China
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40
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Chappell A, Webb NP, Hennen M, Schepanski K, Ciais P, Balkanski Y, Zender CS, Tegen I, Zeng Z, Tong D, Baker B, Ekström M, Baddock M, Eckardt FD, Kandakji T, Lee JA, Nobakht M, von Holdt J, Leys JF. Satellites reveal Earth's seasonally shifting dust emission sources. Sci Total Environ 2023; 883:163452. [PMID: 37088383 DOI: 10.1016/j.scitotenv.2023.163452] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Revised: 03/31/2023] [Accepted: 04/07/2023] [Indexed: 05/03/2023]
Abstract
Establishing mineral dust impacts on Earth's systems requires numerical models of the dust cycle. Differences between dust optical depth (DOD) measurements and modelling the cycle of dust emission, atmospheric transport, and deposition of dust indicate large model uncertainty due partially to unrealistic model assumptions about dust emission frequency. Calibrating dust cycle models to DOD measurements typically in North Africa, are routinely used to reduce dust model magnitude. This calibration forces modelled dust emissions to match atmospheric DOD but may hide the correct magnitude and frequency of dust emission events at source, compensating biases in other modelled processes of the dust cycle. Therefore, it is essential to improve physically based dust emission modules. Here we use a global collation of satellite observations from previous studies of dust emission point source (DPS) dichotomous frequency data. We show that these DPS data have little-to-no relation with MODIS DOD frequency. We calibrate the albedo-based dust emission model using the frequency distribution of those DPS data. The global dust emission uncertainty constrained by DPS data (±3.8 kg m-2 y-1) provides a benchmark for dust emission model development. Our calibrated model results reveal much less global dust emission (29.1 ± 14.9 Tg y-1) than previous estimates, and show seasonally shifting dust emission predominance within and between hemispheres, as opposed to a persistent North African dust emission primacy widely interpreted from DOD measurements. Earth's largest dust emissions, proceed seasonally from East Asian deserts in boreal spring, to Middle Eastern and North African deserts in boreal summer and then Australian shrublands in boreal autumn-winter. This new analysis of dust emissions, from global sources of varying geochemical properties, have far-reaching implications for current and future dust-climate effects. For more reliable coupled representation of dust-climate projections, our findings suggest the need to re-evaluate dust cycle modelling and benefit from the albedo-based parameterisation.
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Affiliation(s)
- Adrian Chappell
- School of Earth and Environmental Science, Cardiff University, Cardiff, UK.
| | | | - Mark Hennen
- School of Earth and Environmental Science, Cardiff University, Cardiff, UK
| | | | - Philippe Ciais
- Laboratoire des Sciences du Climat eipcct de l'Environnement, CEA CNRS UPSACLAY, Gif-sur-Yvette, France; Climate and Atmosphere Research Center (CARE-C), The Cyprus Institute, 20 Konstantinou Kavafi Street, 2121 Nicosia, Cyprus
| | - Yves Balkanski
- Laboratoire des Sciences du Climat eipcct de l'Environnement, CEA CNRS UPSACLAY, Gif-sur-Yvette, France
| | - Charles S Zender
- Department of Earth System Science, University of California, Irvine, USA
| | - Ina Tegen
- Leibniz Institute for Tropospheric Research, Leipzig, Germany
| | - Zhenzhong Zeng
- School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen 518055, China
| | - Daniel Tong
- Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA 22030, USA
| | - Barry Baker
- Department of Atmospheric, Oceanic and Earth Sciences, George Mason University, Fairfax, VA 22030, USA
| | - Marie Ekström
- School of Earth and Environmental Science, Cardiff University, Cardiff, UK
| | - Matt Baddock
- Geography and Environment, Loughborough University, Loughborough, UK
| | - Frank D Eckardt
- Department of Environmental and Geographical Science, University of Cape Town, Rondebosch 7701, South Africa
| | | | | | - Mohamad Nobakht
- Telespazio UK Ltd, Capability Green, Luton LU1 3LU, Bedfordshire, UK
| | - Johanna von Holdt
- Department of Environmental and Geographical Science, University of Cape Town, Rondebosch 7701, South Africa
| | - John F Leys
- Science Division, Department of Planning, Industry and Environment, Gunnedah, Australia; Fenner School of Environment and Society, Australian National University, Canberra, Australia
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41
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Zhang X, Ciais P, Jian X, Liu X, Wang R, Chen K, Huang Y, Huang T, Gao H, Zhao Y, Ma J. The carbon footprint response to projected base stations of China's 5G mobile network. Sci Total Environ 2023; 870:161906. [PMID: 36731564 DOI: 10.1016/j.scitotenv.2023.161906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/11/2022] [Revised: 01/19/2023] [Accepted: 01/26/2023] [Indexed: 06/18/2023]
Abstract
While the rapid expansion of China's 5G mobile network helps to speed up the nation's economic and social development, it tends to release more CO2 due to the 5G's significant energy demand, hampering sustainable development of the 5G network. Previous assessments of CO2 emissions from China's 5G development were based on a projected 5G network ranging from six to fifteen million base stations with the absent of a convincing business model in 5G's application. Under the scenario of business-estimated six million base stations in 2030, the share of electricity consumed by China's 5G networks in 2030 could reach 8.4 % of the national total power generation, causing 0.44 GtCO2/yr CO2 emissions. We collected 5G base station numbers in 2020 and 2021 in 31 provinces and province-level municipalities (PLM), the period with the rapid growth of the 5G base stations in China. We linked these provincial base stations with provincial Gross Domestic Product (GDP), population (POP), and big data development level (BDDL) and established a statistical model to predict 5G base stations by 2030. The model predicted 2-5 million 5G base stations by 2030, considerably lower than the business-projected base station number. Under the model predicted 5G base stations, China's 5G network could yield 0.15-0.29 GtCO2/yr emissions subject to the nation's BDDL from 40 to 80 % by 2030. Both 5G base stations and CO2 emissions are significantly lower than the previous estimates. We decomposed the CO2 footprint of China's 5G networks and assessed the contribution of the number of 5G base stations and mobile data traffic to 5G-induced CO2 emissions. We find that increasing the application of clean energy and promoting energy efficiency can reduce CO2 emissions in the 5G network. To more accurately estimate 5G's climate effect, we propose that it urgently needs to improve vivid 5G business models.
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Affiliation(s)
- Xiaodong Zhang
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA CNRS UVSQ, Gif-sur-Yvette, France
| | - Xiaohu Jian
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Xinrui Liu
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Rong Wang
- Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Department of Environmental Science and Engineering, Fudan University, Shanghai, China
| | - Kaijie Chen
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Yufei Huang
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China
| | - Tao Huang
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Hong Gao
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Yuan Zhao
- Key Laboratory for Environmental Pollution Prediction and Control, College of Earth and Environmental Sciences, Lanzhou University, Lanzhou, China
| | - Jianmin Ma
- Laboratory for Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, China.
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42
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Zhu B, Deng Z, Song X, Zhao W, Huo D, Sun T, Ke P, Cui D, Lu C, Zhong H, Hong C, Qiu J, Davis SJ, Gentine P, Ciais P, Liu Z. CarbonMonitor-Power near-real-time monitoring of global power generation on hourly to daily scales. Sci Data 2023; 10:217. [PMID: 37069166 PMCID: PMC10108797 DOI: 10.1038/s41597-023-02094-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2022] [Accepted: 03/20/2023] [Indexed: 04/19/2023] Open
Abstract
We constructed a frequently updated, near-real-time global power generation dataset: CarbonMonitor-Power since January, 2016 at national levels with near-global coverage and hourly-to-daily time resolution. The data presented here are collected from 37 countries across all continents for eight source groups, including three types of fossil sources (coal, gas, and oil), nuclear energy and four groups of renewable energy sources (solar energy, wind energy, hydro energy and other renewables including biomass, geothermal, etc.). The global near-real-time power dataset shows the dynamics of the global power system, including its hourly, daily, weekly and seasonal patterns as influenced by daily periodical activities, weekends, seasonal cycles, regular and irregular events (i.e., holidays) and extreme events (i.e., the COVID-19 pandemic). The CarbonMonitor-Power dataset reveals that the COVID-19 pandemic caused strong disruptions in some countries (i.e., China and India), leading to a temporary or long-lasting shift to low carbon intensity, while it had only little impact in some other countries (i.e., Australia). This dataset offers a large range of opportunities for power-related scientific research and policy-making.
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Affiliation(s)
- Biqing Zhu
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France
| | - Zhu Deng
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- Product and Solution & Website Business Unit, Alibaba Cloud, Hangzhou, Zhejiang, 311121, China
| | - Xuanren Song
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Wenli Zhao
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
- Department Biogeochemical Integration, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Da Huo
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
- Department of Civil & Mineral Engineering, University of Toronto, Toronto, ON, M5S 1A1, Canada
| | - Taochun Sun
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Piyu Ke
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Duo Cui
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Chenxi Lu
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China
| | - Haiwang Zhong
- Department of Electrical Engineering, Sichuan Energy Internet Research Institute, Tsinghua University, Beijing, 100084, China
| | - Chaopeng Hong
- Institute of Environment and Ecology, Shenzhen International Graduate School, Tsinghua University, Shenzhen, China
| | - Jian Qiu
- Product and Solution & Website Business Unit, Alibaba Cloud, Hangzhou, Zhejiang, 311121, China
| | - Steven J Davis
- Department of Earth System Science, University of California, Irvine, 3232 Croul Hall, Irvine, CA, 92697-3100, USA
| | - Pierre Gentine
- Department of Earth and Environmental Engineering, Columbia University, New York, NY, USA
| | - Philippe Ciais
- Laboratoire des Sciences du Climate et de l'Environnement LSCE, Orme de Merisiers, 91191, Gif-sur-Yvette, France.
| | - Zhu Liu
- Department of Earth System Science, Tsinghua University, Beijing, 100084, China.
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43
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Bell SM, Raymond SJ, Yin H, Jiao W, Goll DS, Ciais P, Olivetti E, Leshyk VO, Terrer C. Quantifying the recarbonization of post-agricultural landscapes. Nat Commun 2023; 14:2139. [PMID: 37059844 PMCID: PMC10104816 DOI: 10.1038/s41467-023-37907-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2022] [Accepted: 04/05/2023] [Indexed: 04/16/2023] Open
Affiliation(s)
- Stephen M Bell
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-sur-Yvette, France.
- Institute of Environmental Science and Technology, Universitat Autònoma de Barcelona, 08193, Bellaterra, Spain.
| | - Samuel J Raymond
- MIT Climate and Sustainability Consortium, Cambridge, MA, 02139, USA
| | - He Yin
- Department of Geography, Kent State University, 325 S. Lincoln Street, Kent, OH, 44242, USA
| | - Wenzhe Jiao
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- MIT Climate and Sustainability Consortium, Cambridge, MA, 02139, USA
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, 91191, Gif-sur-Yvette, France
| | - Elsa Olivetti
- MIT Climate and Sustainability Consortium, Cambridge, MA, 02139, USA
- Department of Materials Science and Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Victor O Leshyk
- Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, 86011, USA
| | - César Terrer
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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44
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Li S, Brandt M, Fensholt R, Kariryaa A, Igel C, Gieseke F, Nord-Larsen T, Oehmcke S, Carlsen AH, Junttila S, Tong X, d’Aspremont A, Ciais P. Deep learning enables image-based tree counting, crown segmentation, and height prediction at national scale. PNAS Nexus 2023; 2:pgad076. [PMID: 37065619 PMCID: PMC10096914 DOI: 10.1093/pnasnexus/pgad076] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Revised: 01/28/2023] [Accepted: 02/27/2023] [Indexed: 04/18/2023]
Abstract
Sustainable tree resource management is the key to mitigating climate warming, fostering a green economy, and protecting valuable habitats. Detailed knowledge about tree resources is a prerequisite for such management but is conventionally based on plot-scale data, which often neglects trees outside forests. Here, we present a deep learning-based framework that provides location, crown area, and height for individual overstory trees from aerial images at country scale. We apply the framework on data covering Denmark and show that large trees (stem diameter >10 cm) can be identified with a low bias (12.5%) and that trees outside forests contribute to 30% of the total tree cover, which is typically unrecognized in national inventories. The bias is high (46.6%) when our results are evaluated against all trees taller than 1.3 m, which involve undetectable small or understory trees. Furthermore, we demonstrate that only marginal effort is needed to transfer our framework to data from Finland, despite markedly dissimilar data sources. Our work lays the foundation for digitalized national databases, where large trees are spatially traceable and manageable.
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Affiliation(s)
- Sizhuo Li
- To whom correspondence should be addressed: ;
| | | | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| | - Ankit Kariryaa
- Department of Computer Science, University of Copenhagen, Copenhagen 2100, Denmark
| | - Christian Igel
- Department of Computer Science, University of Copenhagen, Copenhagen 2100, Denmark
| | - Fabian Gieseke
- Department of Computer Science, University of Copenhagen, Copenhagen 2100, Denmark
- Department of Information Systems, University of Münster, Münster 48149, Germany
| | - Thomas Nord-Larsen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
| | - Stefan Oehmcke
- Department of Computer Science, University of Copenhagen, Copenhagen 2100, Denmark
| | - Ask Holm Carlsen
- Department of Earth Observations, The Danish Agency for Data Supply and Infrastructure, Copenhagen 2400, Denmark
| | - Samuli Junttila
- Department of Forest Sciences, University of Eastern Finland, Joensuu 80101, Finland
| | - Xiaoye Tong
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen 1350, Denmark
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45
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Zheng B, Ciais P, Chevallier F, Yang H, Canadell JG, Chen Y, van der Velde IR, Aben I, Chuvieco E, Davis SJ, Deeter M, Hong C, Kong Y, Li H, Li H, Lin X, He K, Zhang Q. Record-high CO 2 emissions from boreal fires in 2021. Science 2023. [PMID: 36862792 DOI: 10.1126/science.ade0805] [Citation(s) in RCA: 9] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/04/2023]
Abstract
Extreme wildfires are becoming more common and increasingly affecting Earth's climate. Wildfires in boreal forests have attracted much less attention than those in tropical forests, although boreal forests are one of the most extensive biomes on Earth and are experiencing the fastest warming. We used a satellite-based atmospheric inversion system to monitor fire emissions in boreal forests. Wildfires are rapidly expanding into boreal forests with emerging warmer and drier fire seasons. Boreal fires, typically accounting for 10% of global fire carbon dioxide emissions, contributed 23% (0.48 billion metric tons of carbon) in 2021, by far the highest fraction since 2000. 2021 was an abnormal year because North American and Eurasian boreal forests synchronously experienced their greatest water deficit. Increasing numbers of extreme boreal fires and stronger climate-fire feedbacks challenge climate mitigation efforts.
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Affiliation(s)
- Bo Zheng
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.,State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Philippe Ciais
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.,Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France.,The Cyprus Institute, Nicosia 2121, Cyprus
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Hui Yang
- Department of Biogeochemical Integration, Max Planck Institute for Biogeochemistry, 07745 Jena, Germany
| | | | - Yang Chen
- Department of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA
| | - Ivar R van der Velde
- SRON Netherlands Institute for Space Research, Utrecht, Netherlands.,Department of Earth Sciences, Vrije Universiteit, Amsterdam, Netherlands
| | - Ilse Aben
- SRON Netherlands Institute for Space Research, Utrecht, Netherlands.,Department of Physics and Astronomy, Vrije Universiteit, Amsterdam, Netherlands
| | - Emilio Chuvieco
- Universidad de Alcalá, Environmental Remote Sensing Research Group, Department of Geology, Geography and the Environment, 28801 Alcalá de Henares, Spain
| | - Steven J Davis
- Department of Earth System Science, University of California, Irvine, Irvine, CA 92697, USA.,Department of Civil and Environmental Engineering, University of California, Irvine, Irvine, CA 92697, USA
| | - Merritt Deeter
- Atmospheric Chemistry Observations and Modeling Laboratory, National Center for Atmospheric Research, Boulder, CO 80307 USA
| | - Chaopeng Hong
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China.,State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China
| | - Yawen Kong
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
| | - Haiyan Li
- School of Civil and Environmental Engineering, Harbin Institute of Technology, Shenzhen 518055, China
| | - Hui Li
- Shenzhen Key Laboratory of Ecological Remediation and Carbon Sequestration, Institute of Environment and Ecology, Tsinghua Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
| | - Xin Lin
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Kebin He
- State Environmental Protection Key Laboratory of Sources and Control of Air Pollution Complex, Beijing 100084, China.,State Key Joint Laboratory of Environment Simulation and Pollution Control, School of Environment, Tsinghua University, Beijing 100084, China
| | - Qiang Zhang
- Ministry of Education Key Laboratory for Earth System Modeling, Department of Earth System Science, Tsinghua University, Beijing 100084, China
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46
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Goll DS, Bauters M, Zhang H, Ciais P, Balkanski Y, Wang R, Verbeeck H. Atmospheric phosphorus deposition amplifies carbon sinks in simulations of a tropical forest in Central Africa. New Phytol 2023; 237:2054-2068. [PMID: 36226674 DOI: 10.1111/nph.18535] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 09/18/2022] [Indexed: 06/16/2023]
Abstract
Spatial redistribution of nutrients by atmospheric transport and deposition could theoretically act as a continental-scale mechanism which counteracts declines in soil fertility caused by nutrient lock-up in accumulating biomass in tropical forests in Central Africa. However, to what extent it affects carbon sinks in forests remains elusive. Here we use a terrestrial biosphere model to quantify the impact of changes in atmospheric nitrogen and phosphorus deposition on plant nutrition and biomass carbon sink at a typical lowland forest site in Central Africa. We find that the increase in nutrient deposition since the 1980s could have contributed to the carbon sink over the past four decades up to an extent which is similar to that from the combined effects of increasing atmospheric carbon dioxide and climate change. Furthermore, we find that the modelled carbon sink responds to changes in phosphorus deposition, but less so to nitrogen deposition. The pronounced response of ecosystem productivity to changes in nutrient deposition illustrates a potential mechanism that could control carbon sinks in Central Africa. Monitoring the quantity and quality of nutrient deposition is needed in this region, given the changes in nutrient deposition due to human land use.
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Affiliation(s)
- Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CNRS, Université de Versailles Saint-Quentin, Université Paris Saclay, Gif-sur-Yvette, 91190, France
| | - Marijn Bauters
- Isotope Bioscience Laboratory-ISOFYS, Ghent University, Ghent, 9000, Belgium
- Department of Environment, Computational and Applied Vegetation Ecology - CAVElab, Ghent University, Ghent, 9000, Belgium
| | - Haicheng Zhang
- Department Geoscience, Environment & Society, Université Libre de Bruxelles, Bruxelles, 1050, Belgium
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CNRS, Université de Versailles Saint-Quentin, Université Paris Saclay, Gif-sur-Yvette, 91190, France
| | - Yves Balkanski
- Laboratoire des Sciences du Climat et de l'Environnement, Commissariat à l'Énergie Atomique et aux Énergies Alternatives, CNRS, Université de Versailles Saint-Quentin, Université Paris Saclay, Gif-sur-Yvette, 91190, France
| | - Rong Wang
- Department of Environmental Science and Engineering, Shanghai Key Laboratory of Atmospheric Particle Pollution and Prevention, Fudan University, Shanghai, 200438, China
- Integrated Research on Disaster Risk International Center of Excellence on Risk Interconnectivity and Governance on Weather/Climate Extremes Impact and Public Health, Fudan University, Shanghai, 200438, China
- Department of Atmospheric and Oceanic Sciences, Institute of Atmospheric Sciences, Fudan University, Shanghai, 200438, China
- Center for Urban Eco-Planning & Design, Fudan University, Shanghai, 200438, China
- Big Data Institute for Carbon Emission and Environmental Pollution, Fudan University, Shanghai, 200438, China
- Shanghai Institute of Pollution Control and Ecological Security, Shanghai, 200092, China
| | - Hans Verbeeck
- Department of Environment, Computational and Applied Vegetation Ecology - CAVElab, Ghent University, Ghent, 9000, Belgium
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47
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Fernández-Martínez M, Peñuelas J, Chevallier F, Ciais P, Obersteiner M, Rödenbeck C, Sardans J, Vicca S, Yang H, Sitch S, Friedlingstein P, Arora VK, Goll DS, Jain AK, Lombardozzi DL, McGuire PC, Janssens IA. Diagnosing destabilization risk in global land carbon sinks. Nature 2023; 615:848-853. [PMID: 36813960 DOI: 10.1038/s41586-023-05725-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2021] [Accepted: 01/11/2023] [Indexed: 02/24/2023]
Abstract
Global net land carbon uptake or net biome production (NBP) has increased during recent decades1. Whether its temporal variability and autocorrelation have changed during this period, however, remains elusive, even though an increase in both could indicate an increased potential for a destabilized carbon sink2,3. Here, we investigate the trends and controls of net terrestrial carbon uptake and its temporal variability and autocorrelation from 1981 to 2018 using two atmospheric-inversion models, the amplitude of the seasonal cycle of atmospheric CO2 concentration derived from nine monitoring stations distributed across the Pacific Ocean and dynamic global vegetation models. We find that annual NBP and its interdecadal variability increased globally whereas temporal autocorrelation decreased. We observe a separation of regions characterized by increasingly variable NBP, associated with warm regions and increasingly variable temperatures, lower and weaker positive trends in NBP and regions where NBP became stronger and less variable. Plant species richness presented a concave-down parabolic spatial relationship with NBP and its variability at the global scale whereas nitrogen deposition generally increased NBP. Increasing temperature and its increasing variability appear as the most important drivers of declining and increasingly variable NBP. Our results show increasing variability of NBP regionally that can be mostly attributed to climate change and that may point to destabilization of the coupled carbon-climate system.
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Affiliation(s)
- Marcos Fernández-Martínez
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium.
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain.
- BEECA-UB, Department of Evolutionary Biology, Ecology and Environmental Sciences, University of Barcelona, Barcelona, Spain.
| | - Josep Peñuelas
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain
- CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Barcelona, Spain
| | - Frederic Chevallier
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Michael Obersteiner
- International Institute for Applied Systems Analysis (IIASA), Laxenburg, Austria
- School of Geography and the Environment, University of Oxford, Oxford, UK
| | - Christian Rödenbeck
- Department of Biogeochmical Systems, Max Planck Institute for Biogeochemistry, Jena, Germany
| | - Jordi Sardans
- CREAF, Campus de Bellaterra (UAB), Cerdanyola del Vallès, Spain
- CSIC, Global Ecology Unit, CREAF-CSIC-UAB, Bellaterra, Barcelona, Spain
| | - Sara Vicca
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
| | - Hui Yang
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Stephen Sitch
- College of Life and Environmental Sciences, University of Exeter, Exeter, UK
| | - Pierre Friedlingstein
- College of Engineering, Mathematics, and Physical Sciences, University of Exeter, Exeter, UK
| | - Vivek K Arora
- Canadian Centre for Climate Modelling and Analysis, Climate Research Division, Environment and Climate Change Canada, Victoria, BC, Canada
| | - Daniel S Goll
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette, France
| | - Atul K Jain
- Department of Atmospheric Sciences, University of Illinois, Urbana, IL, USA
| | - Danica L Lombardozzi
- Climate and Global Dynamics Laboratory, National Center for Atmospheric Research, Boulder, CO, USA
| | - Patrick C McGuire
- Department of Meteorology, Department of Geography & Environmental Science, National Centre for Atmospheric Science, University of Reading, Reading, UK
| | - Ivan A Janssens
- PLECO (Plants and Ecosystems), Department of Biology, University of Antwerp, Wilrijk, Belgium
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48
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Lin F, Li X, Jia N, Feng F, Huang H, Huang J, Fan S, Ciais P, Song XP. The impact of Russia-Ukraine conflict on global food security. Global Food Security 2023. [DOI: 10.1016/j.gfs.2022.100661] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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49
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Tucker C, Brandt M, Hiernaux P, Kariryaa A, Rasmussen K, Small J, Igel C, Reiner F, Melocik K, Meyer J, Sinno S, Romero E, Glennie E, Fitts Y, Morin A, Pinzon J, McClain D, Morin P, Porter C, Loeffler S, Kergoat L, Issoufou BA, Savadogo P, Wigneron JP, Poulter B, Ciais P, Kaufmann R, Myneni R, Saatchi S, Fensholt R. Sub-continental-scale carbon stocks of individual trees in African drylands. Nature 2023; 615:80-86. [PMID: 36859581 PMCID: PMC9977681 DOI: 10.1038/s41586-022-05653-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Accepted: 12/13/2022] [Indexed: 03/03/2023]
Abstract
The distribution of dryland trees and their density, cover, size, mass and carbon content are not well known at sub-continental to continental scales1-14. This information is important for ecological protection, carbon accounting, climate mitigation and restoration efforts of dryland ecosystems15-18. We assessed more than 9.9 billion trees derived from more than 300,000 satellite images, covering semi-arid sub-Saharan Africa north of the Equator. We attributed wood, foliage and root carbon to every tree in the 0-1,000 mm year-1 rainfall zone by coupling field data19, machine learning20-22, satellite data and high-performance computing. Average carbon stocks of individual trees ranged from 0.54 Mg C ha-1 and 63 kg C tree-1 in the arid zone to 3.7 Mg C ha-1 and 98 kg tree-1 in the sub-humid zone. Overall, we estimated the total carbon for our study area to be 0.84 (±19.8%) Pg C. Comparisons with 14 previous TRENDY numerical simulation studies23 for our area found that the density and carbon stocks of scattered trees have been underestimated by three models and overestimated by 11 models, respectively. This benchmarking can help understand the carbon cycle and address concerns about land degradation24-29. We make available a linked database of wood mass, foliage mass, root mass and carbon stock of each tree for scientists, policymakers, dryland-restoration practitioners and farmers, who can use it to estimate farmland tree carbon stocks from tablets or laptops.
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Affiliation(s)
- Compton Tucker
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA.
| | - Martin Brandt
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA.
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark.
| | - Pierre Hiernaux
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA.
- Pastoralisme Conseil, Caylus, France.
| | - Ankit Kariryaa
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Kjeld Rasmussen
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Jennifer Small
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Christian Igel
- Department of Computer Science, University of Copenhagen, Copenhagen, Denmark
| | - Florian Reiner
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
| | - Katherine Melocik
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Jesse Meyer
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Scott Sinno
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Eric Romero
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Erin Glennie
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Yasmin Fitts
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - August Morin
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Jorge Pinzon
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Devin McClain
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
- Science Systems and Applications, Inc., NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Paul Morin
- Learning and Environmental Sciences, University of Minnesota, Saint Paul, MN, USA
| | - Claire Porter
- Learning and Environmental Sciences, University of Minnesota, Saint Paul, MN, USA
| | - Shane Loeffler
- Learning and Environmental Sciences, University of Minnesota, Saint Paul, MN, USA
| | - Laurent Kergoat
- Géosciences Environnement Toulouse, Observatoire Midi-Pyrénées, UMR 5563 (CNRS/UPS/IRD/CNES), Toulouse, France
| | | | | | | | - Benjamin Poulter
- Earth Science Division, NASA Goddard Space Flight Center, Greenbelt, MD, USA
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, CEA-CNRS-UVSQ, CE Orme des Merisiers, Gif sur Yvette, France
| | - Robert Kaufmann
- Department of Earth & Environment, Boston University, Boston, MA, USA
| | - Ranga Myneni
- Department of Earth & Environment, Boston University, Boston, MA, USA
| | - Sassan Saatchi
- Jet Propulsion Laboratory, California Institute of Technology, Pasadena, CA, USA
| | - Rasmus Fensholt
- Department of Geosciences and Natural Resource Management, University of Copenhagen, Copenhagen, Denmark
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50
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Wang J, Ciais P, Gasser T, Chang J, Tian H, Zhao Z, Zhu L, Li Z, Li W. Temperature Changes Induced by Biogeochemical and Biophysical Effects of Bioenergy Crop Cultivation. Environ Sci Technol 2023; 57:2474-2483. [PMID: 36723918 DOI: 10.1021/acs.est.2c05253] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/18/2023]
Abstract
The production of bioenergy with carbon capture and storage (BECCS) is a pivotal negative emission technology. The cultivation of dedicated crops for BECCS impacts the temperature through two processes: net CO2 removal (CDR) from the atmosphere (biogeochemical cooling) and changes in the local energy balance (biophysical warming or cooling). Here, we compare the magnitude of these two processes for key grass and tree species envisioned for large-scale bioenergy crop cultivation, following economically plausible scenarios using Earth System Models. By the end of this century, the cumulative CDR from the cultivation of eucalypt (72-112 Pg C) is larger than that of switchgrass (34-83 Pg C) because of contrasting contributions of land use change carbon emissions. The combined biogeochemical and biophysical effects are cooling (-0.26 to -0.04 °C) at the global scale, but 13-28% of land areas still have net warming signals, mainly due to the spatial heterogeneity of the biophysical effects. Our study shows that the deployment of bioenergy crop cultivation should not only be guided by the principles of maximizing yield and CDR but should also take an integrated perspective that includes all relevant Earth system feedbacks.
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Affiliation(s)
- Jingmeng Wang
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Beijing100084, China
| | - Philippe Ciais
- Laboratoire des Sciences du Climat et de l'Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Université Paris-Saclay, Gif-sur-Yvette91191, France
| | - Thomas Gasser
- International Institute for Applied Systems Analysis (IIASA), Laxenburg2361, Austria
| | - Jinfeng Chang
- College of Environmental and Resource Sciences, Zhejiang University, Hangzhou310058, China
| | - Hanqin Tian
- Schiller Institute for Integrated Science and Society, Department of Earth and Environmental Sciences, Boston College, Chestnut Hill, Massachusetts02467, United States
| | - Zhe Zhao
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
| | - Lei Zhu
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
| | - Zhao Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
| | - Wei Li
- Department of Earth System Science, Ministry of Education Key Laboratory for Earth System Modeling, Institute for Global Change Studies, Tsinghua University, Beijing100084, China
- Ministry of Education Ecological Field Station for East Asian Migratory Birds, Beijing100084, China
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