Articles | Volume 16, issue 5
https://doi.org/10.5194/essd-16-2465-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/essd-16-2465-2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Data description paper
| 
24 May 2024
Data description paper |
| 24 May 2024
| 24 May 2024
National forest carbon harvesting and allocation dataset for the period 2003 to 2018
Daju Wang
School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong 510245, China
Peiyang Ren
School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong 510245, China
Xiaosheng Xia
School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong 510245, China
Chongqing Jinfo Mountain Karst Ecosystem National Observation and Research Station, School of Geographical Sciences, Southwest University, Chongqing 400715, China
Zhangcai Qin
School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong 510245, China
Xiuzhi Chen
School of Atmospheric Sciences, Guangdong Province Data Center of Terrestrial and Marine Ecosystems Carbon Cycle, Sun Yat-sen University, Zhuhai, Guangdong 510245, China
Wenping Yuan
CORRESPONDING AUTHOR
Institute of Carbon Neutrality, Sino-French Institute for Earth System Science, College of Urban and Environmental Sciences, Peking University, Beijing 100091, China
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Sylvain Schmitt, Fabian J. Fischer, James G. C. Ball, Nicolas Barbier, Marion Boisseaux, Damien Bonal, Benoit Burban, Xiuzhi Chen, Géraldine Derroire, Jeremy W. Lichstein, Daniela Nemetschek, Natalia Restrepo-Coupe, Scott Saleska, Giacomo Sellan, Philippe Verley, Grégoire Vincent, Camille Ziegler, Jérôme Chave, and Isabelle Maréchaux
Geosci. Model Dev., 18, 5205–5243, https://doi.org/10.5194/gmd-18-5205-2025, https://doi.org/10.5194/gmd-18-5205-2025, 2025
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We evaluate the capability of TROLL 4.0, a simulator of forest dynamics, to represent tropical forest structure, diversity, dynamics, and functioning in two Amazonian forests. Evaluation data include forest inventories, carbon and water fluxes between the forest and the atmosphere, and leaf area and canopy height from remote sensing products. The model realistically predicts the structure and composition as well as the seasonality of carbon and water fluxes at both sites.
Rubaya Pervin, Scott Robeson, Mallory Barnes, Stephen Sitch, Anthony Walker, Ben Poulter, Fabienne Maignan, Qing Sun, Thomas Colligan, Sönke Zaehle, Kashif Mahmud, Peter Anthoni, Almut Arneth, Vivek Arora, Vladislav Bastrikov, Liam Bogucki, Bertrand Decharme, Christine Delire, Stefanie Falk, Akihiko Ito, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Michael O’Sullivan, Wenping Yuan, and Natasha MacBean
EGUsphere, https://doi.org/10.5194/egusphere-2025-2841, https://doi.org/10.5194/egusphere-2025-2841, 2025
This preprint is open for discussion and under review for Biogeosciences (BG).
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Drylands contribute more than a third of the global vegetation productivity. Yet, these regions are not well represented in global vegetation models. Here, we tested how well 15 global models capture annual changes in dryland vegetation productivity. Models that didn’t have vegetation change over time or fire have lower variability in vegetation productivity. Models need better representation of grass cover types and their coverage. Our work highlights where and how these models need to improve.
Xueqin Yang, Qingling Sun, Liusheng Han, Jie Tian, Wenping Yuan, Liyang Liu, Wei Zheng, Mei Wang, Yunpeng Wang, and Xiuzhi Chen
Earth Syst. Sci. Data, 17, 3293–3314, https://doi.org/10.5194/essd-17-3293-2025, https://doi.org/10.5194/essd-17-3293-2025, 2025
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Understanding how leaves absorb carbon from the atmosphere is essential for predicting changes in global forests. Young leaves play a key role in this process, but their efficiency has been difficult to measure at large scales. Using satellite data, we developed a new method to track the seasonal patterns of young leaves’ photosynthetic capacity from 2001 to 2018. Our dataset helps scientists better understand forest growth and how ecosystems respond to climate change.
Die Hu, Yuan Wang, Han Jing, Linwei Yue, Qiang Zhang, Lei Fan, Qiangqiang Yuan, Huanfeng Shen, and Liangpei Zhang
Earth Syst. Sci. Data, 17, 2849–2872, https://doi.org/10.5194/essd-17-2849-2025, https://doi.org/10.5194/essd-17-2849-2025, 2025
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Existing L-band vegetation optical depth (L-VOD) products suffer from data gaps and coarse resolution of historical data. Therefore, it is necessary to integrate multi-temporal and multisource L-VOD products. Our study begins with the reconstruction of missing data and then develops a spatiotemporal fusion model to generate global daily seamless 9 km L-VOD products from 2010 to 2021, which are crucial for understanding the global carbon cycle.
Ruoque Shen, Qiongyan Peng, Xiangqian Li, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data, 17, 2193–2216, https://doi.org/10.5194/essd-17-2193-2025, https://doi.org/10.5194/essd-17-2193-2025, 2025
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Rice is a vital staple crop that plays a crucial role in food security in China. However, long-term high-resolution rice distribution maps in China are lacking. This study developed a new rice-mapping method, mitigating the impact of cloud contamination and missing data in optical remote sensing observations on rice mapping. The resulting dataset, CCD-Rice (China Crop Dataset-Rice), achieved high accuracy and showed a strong correlation with statistical data.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Hongmei Li, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Carla F. Berghoff, Henry C. Bittig, Laurent Bopp, Patricia Cadule, Katie Campbell, Matthew A. Chamberlain, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Thomas Colligan, Jeanne Decayeux, Laique M. Djeutchouang, Xinyu Dou, Carolina Duran Rojas, Kazutaka Enyo, Wiley Evans, Amanda R. Fay, Richard A. Feely, Daniel J. Ford, Adrianna Foster, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul K. Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Etsushi Kato, Ralph F. Keeling, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Xin Lan, Siv K. Lauvset, Nathalie Lefèvre, Zhu Liu, Junjie Liu, Lei Ma, Shamil Maksyutov, Gregg Marland, Nicolas Mayot, Patrick C. McGuire, Nicolas Metzl, Natalie M. Monacci, Eric J. Morgan, Shin-Ichiro Nakaoka, Craig Neill, Yosuke Niwa, Tobias Nützel, Lea Olivier, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Zhangcai Qin, Laure Resplandy, Alizée Roobaert, Thais M. Rosan, Christian Rödenbeck, Jörg Schwinger, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Roland Séférian, Shintaro Takao, Hiroaki Tatebe, Hanqin Tian, Bronte Tilbrook, Olivier Torres, Etienne Tourigny, Hiroyuki Tsujino, Francesco Tubiello, Guido van der Werf, Rik Wanninkhof, Xuhui Wang, Dongxu Yang, Xiaojuan Yang, Zhen Yu, Wenping Yuan, Xu Yue, Sönke Zaehle, Ning Zeng, and Jiye Zeng
Earth Syst. Sci. Data, 17, 965–1039, https://doi.org/10.5194/essd-17-965-2025, https://doi.org/10.5194/essd-17-965-2025, 2025
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The Global Carbon Budget 2024 describes the methodology, main results, and datasets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2024). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yangyang Fu, Xiuzhi Chen, Chaoqing Song, Xiaojuan Huang, Jie Dong, Qiongyan Peng, and Wenping Yuan
Earth Syst. Sci. Data, 17, 95–115, https://doi.org/10.5194/essd-17-95-2025, https://doi.org/10.5194/essd-17-95-2025, 2025
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This study proposed the Winter-Triticeae Crops Index (WTCI), which had great performance and stable spatiotemporal transferability in identifying winter-triticeae crops in 66 countries worldwide, with an overall accuracy of 87.7 %. The first global 30 m resolution distribution maps of winter-triticeae crops from 2017 to 2022 were further produced based on the WTCI method. The product can serve as an important basis for agricultural applications.
Zhen Zhang, Benjamin Poulter, Joe R. Melton, William J. Riley, George H. Allen, David J. Beerling, Philippe Bousquet, Josep G. Canadell, Etienne Fluet-Chouinard, Philippe Ciais, Nicola Gedney, Peter O. Hopcroft, Akihiko Ito, Robert B. Jackson, Atul K. Jain, Katherine Jensen, Fortunat Joos, Thomas Kleinen, Sara H. Knox, Tingting Li, Xin Li, Xiangyu Liu, Kyle McDonald, Gavin McNicol, Paul A. Miller, Jurek Müller, Prabir K. Patra, Changhui Peng, Shushi Peng, Zhangcai Qin, Ryan M. Riggs, Marielle Saunois, Qing Sun, Hanqin Tian, Xiaoming Xu, Yuanzhi Yao, Yi Xi, Wenxin Zhang, Qing Zhu, Qiuan Zhu, and Qianlai Zhuang
Biogeosciences, 22, 305–321, https://doi.org/10.5194/bg-22-305-2025, https://doi.org/10.5194/bg-22-305-2025, 2025
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This study assesses global methane emissions from wetlands between 2000 and 2020 using multiple models. We found that wetland emissions increased by 6–7 Tg CH4 yr-1 in the 2010s compared to the 2000s. Rising temperatures primarily drove this increase, while changes in precipitation and CO2 levels also played roles. Our findings highlight the importance of wetlands in the global methane budget and the need for continuous monitoring to understand their impact on climate change.
Ruoque Shen, Qiongyan Peng, Xiangqian Li, Xiuzhi Chen, and Wenping Yuan
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2024-147, https://doi.org/10.5194/essd-2024-147, 2024
Manuscript not accepted for further review
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Rice is a vital staple crop that plays a crucial role in food security in China. However, long-term high-resolution rice distribution maps in China are lacking. This study developed a new rice mapping method using to address the challenges of cloud contamination and missing data in optical remote sensing observations. The resulting dataset, CCD-Rice (China Crop Dataset-Rice), achieved high accuracy and showed strong correlation with statistical data.
Kai Yan, Jingrui Wang, Rui Peng, Kai Yang, Xiuzhi Chen, Gaofei Yin, Jinwei Dong, Marie Weiss, Jiabin Pu, and Ranga B. Myneni
Earth Syst. Sci. Data, 16, 1601–1622, https://doi.org/10.5194/essd-16-1601-2024, https://doi.org/10.5194/essd-16-1601-2024, 2024
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Variations in observational conditions have led to poor spatiotemporal consistency in leaf area index (LAI) time series. Using prior knowledge, we leveraged high-quality observations and spatiotemporal correlation to reprocess MODIS LAI, thereby generating HiQ-LAI, a product that exhibits fewer abnormal fluctuations in time series. Reprocessing was done on Google Earth Engine, providing users with convenient access to this value-added data and facilitating large-scale research and applications.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Peter Landschützer, Corinne Le Quéré, Ingrid T. Luijkx, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Peter Anthoni, Leticia Barbero, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Bertrand Decharme, Laurent Bopp, Ida Bagus Mandhara Brasika, Patricia Cadule, Matthew A. Chamberlain, Naveen Chandra, Thi-Tuyet-Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Xinyu Dou, Kazutaka Enyo, Wiley Evans, Stefanie Falk, Richard A. Feely, Liang Feng, Daniel J. Ford, Thomas Gasser, Josefine Ghattas, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Jens Heinke, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Andrew R. Jacobson, Atul Jain, Tereza Jarníková, Annika Jersild, Fei Jiang, Zhe Jin, Fortunat Joos, Etsushi Kato, Ralph F. Keeling, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Xin Lan, Nathalie Lefèvre, Hongmei Li, Junjie Liu, Zhiqiang Liu, Lei Ma, Greg Marland, Nicolas Mayot, Patrick C. McGuire, Galen A. McKinley, Gesa Meyer, Eric J. Morgan, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin M. O'Brien, Are Olsen, Abdirahman M. Omar, Tsuneo Ono, Melf Paulsen, Denis Pierrot, Katie Pocock, Benjamin Poulter, Carter M. Powis, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Roland Séférian, T. Luke Smallman, Stephen M. Smith, Reinel Sospedra-Alfonso, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Erik van Ooijen, Rik Wanninkhof, Michio Watanabe, Cathy Wimart-Rousseau, Dongxu Yang, Xiaojuan Yang, Wenping Yuan, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 15, 5301–5369, https://doi.org/10.5194/essd-15-5301-2023, https://doi.org/10.5194/essd-15-5301-2023, 2023
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The Global Carbon Budget 2023 describes the methodology, main results, and data sets used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, land ecosystems, and the ocean over the historical period (1750–2023). These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Ruoque Shen, Baihong Pan, Qiongyan Peng, Jie Dong, Xuebing Chen, Xi Zhang, Tao Ye, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 15, 3203–3222, https://doi.org/10.5194/essd-15-3203-2023, https://doi.org/10.5194/essd-15-3203-2023, 2023
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Paddy rice is the second-largest grain crop in China and plays an important role in ensuring global food security. This study developed a new rice-mapping method and produced distribution maps of single-season rice in 21 provincial administrative regions of China from 2017 to 2022 at a 10 or 20 m resolution. The accuracy was examined using 108 195 survey samples and county-level statistical data, and we found that the distribution maps have good accuracy.
Xueqin Yang, Xiuzhi Chen, Jiashun Ren, Wenping Yuan, Liyang Liu, Juxiu Liu, Dexiang Chen, Yihua Xiao, Qinghai Song, Yanjun Du, Shengbiao Wu, Lei Fan, Xiaoai Dai, Yunpeng Wang, and Yongxian Su
Earth Syst. Sci. Data, 15, 2601–2622, https://doi.org/10.5194/essd-15-2601-2023, https://doi.org/10.5194/essd-15-2601-2023, 2023
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We developed the first time-mapped, continental-scale gridded dataset of monthly leaf area index (LAI) in three leaf age cohorts (i.e., young, mature, and old) from 2001–2018 data (referred to as Lad-LAI). The seasonality of three LAI cohorts from the new Lad-LAI product agrees well at eight sites with very fine-scale collections of monthly LAI. The proposed satellite-based approaches can provide references for mapping finer spatiotemporal-resolution LAI products with different leaf age cohorts.
Yuchan Chen, Xiuzhi Chen, Meimei Xue, Chuanxun Yang, Wei Zheng, Jun Cao, Wenting Yan, and Wenping Yuan
Hydrol. Earth Syst. Sci., 27, 1929–1943, https://doi.org/10.5194/hess-27-1929-2023, https://doi.org/10.5194/hess-27-1929-2023, 2023
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This study addresses the quantification and estimation of the watershed-characteristic-related parameter (Pw) in the Budyko framework with the principle of hydrologically similar groups. The results show that Pw is closely related to soil moisture and fractional vegetation cover, and the relationship varies across specific hydrologic similarity groups. The overall satisfactory performance of the Pw estimation model improves the applicability of the Budyko framework for global runoff estimation.
Giacomo Grassi, Clemens Schwingshackl, Thomas Gasser, Richard A. Houghton, Stephen Sitch, Josep G. Canadell, Alessandro Cescatti, Philippe Ciais, Sandro Federici, Pierre Friedlingstein, Werner A. Kurz, Maria J. Sanz Sanchez, Raúl Abad Viñas, Ramdane Alkama, Selma Bultan, Guido Ceccherini, Stefanie Falk, Etsushi Kato, Daniel Kennedy, Jürgen Knauer, Anu Korosuo, Joana Melo, Matthew J. McGrath, Julia E. M. S. Nabel, Benjamin Poulter, Anna A. Romanovskaya, Simone Rossi, Hanqin Tian, Anthony P. Walker, Wenping Yuan, Xu Yue, and Julia Pongratz
Earth Syst. Sci. Data, 15, 1093–1114, https://doi.org/10.5194/essd-15-1093-2023, https://doi.org/10.5194/essd-15-1093-2023, 2023
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Striking differences exist in estimates of land-use CO2 fluxes between the national greenhouse gas inventories and the IPCC assessment reports. These differences hamper an accurate assessment of the collective progress under the Paris Agreement. By implementing an approach that conceptually reconciles land-use CO2 flux from national inventories and the global models used by the IPCC, our study is an important step forward for increasing confidence in land-use CO2 flux estimates.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Luke Gregor, Judith Hauck, Corinne Le Quéré, Ingrid T. Luijkx, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Clemens Schwingshackl, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone R. Alin, Ramdane Alkama, Almut Arneth, Vivek K. Arora, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Henry C. Bittig, Laurent Bopp, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Wiley Evans, Stefanie Falk, Richard A. Feely, Thomas Gasser, Marion Gehlen, Thanos Gkritzalis, Lucas Gloege, Giacomo Grassi, Nicolas Gruber, Özgür Gürses, Ian Harris, Matthew Hefner, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Atul K. Jain, Annika Jersild, Koji Kadono, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Keith Lindsay, Junjie Liu, Zhu Liu, Gregg Marland, Nicolas Mayot, Matthew J. McGrath, Nicolas Metzl, Natalie M. Monacci, David R. Munro, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Naiqing Pan, Denis Pierrot, Katie Pocock, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Carmen Rodriguez, Thais M. Rosan, Jörg Schwinger, Roland Séférian, Jamie D. Shutler, Ingunn Skjelvan, Tobias Steinhoff, Qing Sun, Adrienne J. Sutton, Colm Sweeney, Shintaro Takao, Toste Tanhua, Pieter P. Tans, Xiangjun Tian, Hanqin Tian, Bronte Tilbrook, Hiroyuki Tsujino, Francesco Tubiello, Guido R. van der Werf, Anthony P. Walker, Rik Wanninkhof, Chris Whitehead, Anna Willstrand Wranne, Rebecca Wright, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, Jiye Zeng, and Bo Zheng
Earth Syst. Sci. Data, 14, 4811–4900, https://doi.org/10.5194/essd-14-4811-2022, https://doi.org/10.5194/essd-14-4811-2022, 2022
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The Global Carbon Budget 2022 describes the datasets and methodology used to quantify the anthropogenic emissions of carbon dioxide (CO2) and their partitioning among the atmosphere, the land ecosystems, and the ocean. These living datasets are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Haicheng Zhang, Ronny Lauerwald, Pierre Regnier, Philippe Ciais, Kristof Van Oost, Victoria Naipal, Bertrand Guenet, and Wenping Yuan
Earth Syst. Dynam., 13, 1119–1144, https://doi.org/10.5194/esd-13-1119-2022, https://doi.org/10.5194/esd-13-1119-2022, 2022
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We present a land surface model which can simulate the complete lateral transfer of sediment and carbon from land to ocean through rivers. Our model captures the water, sediment, and organic carbon discharges in European rivers well. Application of our model in Europe indicates that lateral carbon transfer can strongly change regional land carbon budgets by affecting organic carbon distribution and soil moisture.
Ziqi Lin, Yongjiu Dai, Umakant Mishra, Guocheng Wang, Wei Shangguan, Wen Zhang, and Zhangcai Qin
Earth Syst. Sci. Data Discuss., https://doi.org/10.5194/essd-2022-232, https://doi.org/10.5194/essd-2022-232, 2022
Manuscript not accepted for further review
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Spatial soil organic carbon (SOC) data is critical for predictions in carbon climate feedbacks and future climate trends, but no conclusion has yet been reached on which dataset to be used for specific purposes. We evaluated the SOC estimates from five widely used global soil datasets and a regional permafrost dataset, and identify uncertainties of SOC estimates by region, biome, and data sources, hoping to help improve SOC/soil data in the future.
Quandi Niu, Xuecao Li, Jianxi Huang, Hai Huang, Xianda Huang, Wei Su, and Wenping Yuan
Earth Syst. Sci. Data, 14, 2851–2864, https://doi.org/10.5194/essd-14-2851-2022, https://doi.org/10.5194/essd-14-2851-2022, 2022
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In this paper we generated the first national maize phenology product with a fine spatial resolution (30 m) and a long temporal span (1985–2020) in China, using Landsat images. The derived phenological indicators agree with in situ observations and provide more spatial details than moderate resolution phenology products. The extracted maize phenology dataset can support precise yield estimation and deepen our understanding of the response of agroecosystem to global warming in the future.
Pierre Friedlingstein, Matthew W. Jones, Michael O'Sullivan, Robbie M. Andrew, Dorothee C. E. Bakker, Judith Hauck, Corinne Le Quéré, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Josep G. Canadell, Philippe Ciais, Rob B. Jackson, Simone R. Alin, Peter Anthoni, Nicholas R. Bates, Meike Becker, Nicolas Bellouin, Laurent Bopp, Thi Tuyet Trang Chau, Frédéric Chevallier, Louise P. Chini, Margot Cronin, Kim I. Currie, Bertrand Decharme, Laique M. Djeutchouang, Xinyu Dou, Wiley Evans, Richard A. Feely, Liang Feng, Thomas Gasser, Dennis Gilfillan, Thanos Gkritzalis, Giacomo Grassi, Luke Gregor, Nicolas Gruber, Özgür Gürses, Ian Harris, Richard A. Houghton, George C. Hurtt, Yosuke Iida, Tatiana Ilyina, Ingrid T. Luijkx, Atul Jain, Steve D. Jones, Etsushi Kato, Daniel Kennedy, Kees Klein Goldewijk, Jürgen Knauer, Jan Ivar Korsbakken, Arne Körtzinger, Peter Landschützer, Siv K. Lauvset, Nathalie Lefèvre, Sebastian Lienert, Junjie Liu, Gregg Marland, Patrick C. McGuire, Joe R. Melton, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Tsuneo Ono, Denis Pierrot, Benjamin Poulter, Gregor Rehder, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Thais M. Rosan, Jörg Schwinger, Clemens Schwingshackl, Roland Séférian, Adrienne J. Sutton, Colm Sweeney, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Francesco Tubiello, Guido R. van der Werf, Nicolas Vuichard, Chisato Wada, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Chao Yue, Xu Yue, Sönke Zaehle, and Jiye Zeng
Earth Syst. Sci. Data, 14, 1917–2005, https://doi.org/10.5194/essd-14-1917-2022, https://doi.org/10.5194/essd-14-1917-2022, 2022
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The Global Carbon Budget 2021 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Yidi Xu, Philippe Ciais, Le Yu, Wei Li, Xiuzhi Chen, Haicheng Zhang, Chao Yue, Kasturi Kanniah, Arthur P. Cracknell, and Peng Gong
Geosci. Model Dev., 14, 4573–4592, https://doi.org/10.5194/gmd-14-4573-2021, https://doi.org/10.5194/gmd-14-4573-2021, 2021
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In this study, we implemented the specific morphology, phenology and harvest process of oil palm in the global land surface model ORCHIDEE-MICT. The improved model generally reproduces the same leaf area index, biomass density and life cycle fruit yield as observations. This explicit representation of oil palm in a global land surface model offers a useful tool for understanding the ecological processes of oil palm growth and assessing the environmental impacts of oil palm plantations.
Pierre Friedlingstein, Michael O'Sullivan, Matthew W. Jones, Robbie M. Andrew, Judith Hauck, Are Olsen, Glen P. Peters, Wouter Peters, Julia Pongratz, Stephen Sitch, Corinne Le Quéré, Josep G. Canadell, Philippe Ciais, Robert B. Jackson, Simone Alin, Luiz E. O. C. Aragão, Almut Arneth, Vivek Arora, Nicholas R. Bates, Meike Becker, Alice Benoit-Cattin, Henry C. Bittig, Laurent Bopp, Selma Bultan, Naveen Chandra, Frédéric Chevallier, Louise P. Chini, Wiley Evans, Liesbeth Florentie, Piers M. Forster, Thomas Gasser, Marion Gehlen, Dennis Gilfillan, Thanos Gkritzalis, Luke Gregor, Nicolas Gruber, Ian Harris, Kerstin Hartung, Vanessa Haverd, Richard A. Houghton, Tatiana Ilyina, Atul K. Jain, Emilie Joetzjer, Koji Kadono, Etsushi Kato, Vassilis Kitidis, Jan Ivar Korsbakken, Peter Landschützer, Nathalie Lefèvre, Andrew Lenton, Sebastian Lienert, Zhu Liu, Danica Lombardozzi, Gregg Marland, Nicolas Metzl, David R. Munro, Julia E. M. S. Nabel, Shin-Ichiro Nakaoka, Yosuke Niwa, Kevin O'Brien, Tsuneo Ono, Paul I. Palmer, Denis Pierrot, Benjamin Poulter, Laure Resplandy, Eddy Robertson, Christian Rödenbeck, Jörg Schwinger, Roland Séférian, Ingunn Skjelvan, Adam J. P. Smith, Adrienne J. Sutton, Toste Tanhua, Pieter P. Tans, Hanqin Tian, Bronte Tilbrook, Guido van der Werf, Nicolas Vuichard, Anthony P. Walker, Rik Wanninkhof, Andrew J. Watson, David Willis, Andrew J. Wiltshire, Wenping Yuan, Xu Yue, and Sönke Zaehle
Earth Syst. Sci. Data, 12, 3269–3340, https://doi.org/10.5194/essd-12-3269-2020, https://doi.org/10.5194/essd-12-3269-2020, 2020
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The Global Carbon Budget 2020 describes the data sets and methodology used to quantify the emissions of carbon dioxide and their partitioning among the atmosphere, land, and ocean. These living data are updated every year to provide the highest transparency and traceability in the reporting of CO2, the key driver of climate change.
Jie Dong, Yangyang Fu, Jingjing Wang, Haifeng Tian, Shan Fu, Zheng Niu, Wei Han, Yi Zheng, Jianxi Huang, and Wenping Yuan
Earth Syst. Sci. Data, 12, 3081–3095, https://doi.org/10.5194/essd-12-3081-2020, https://doi.org/10.5194/essd-12-3081-2020, 2020
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For the first time, we produced a 30 m winter wheat distribution map in China for 3 years during 2016–2018. Validated with 33 776 survey samples, the map had perfect performance with an overall accuracy of 89.88 %. Moreover, the method can identify planting areas of winter wheat 3 months prior to harvest; that is valuable information for production predictions and is urgently necessary for policymakers to reduce economic loss and assess food security.
Yuan Zhang, Ana Bastos, Fabienne Maignan, Daniel Goll, Olivier Boucher, Laurent Li, Alessandro Cescatti, Nicolas Vuichard, Xiuzhi Chen, Christof Ammann, M. Altaf Arain, T. Andrew Black, Bogdan Chojnicki, Tomomichi Kato, Ivan Mammarella, Leonardo Montagnani, Olivier Roupsard, Maria J. Sanz, Lukas Siebicke, Marek Urbaniak, Francesco Primo Vaccari, Georg Wohlfahrt, Will Woodgate, and Philippe Ciais
Geosci. Model Dev., 13, 5401–5423, https://doi.org/10.5194/gmd-13-5401-2020, https://doi.org/10.5194/gmd-13-5401-2020, 2020
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We improved the ORCHIDEE LSM by distinguishing diffuse and direct light in canopy and evaluated the new model with observations from 159 sites. Compared with the old model, the new model has better sunny GPP and reproduced the diffuse light fertilization effect observed at flux sites. Our simulations also indicate different mechanisms causing the observed GPP enhancement under cloudy conditions at different times. The new model has the potential to study large-scale impacts of aerosol changes.
Cited articles
Asner, G. P., Knapp, D. E., Broadbent, E. N., Oliveira, P. J. C., Keller, M., and Silva, J. N.: Selective logging in the Brazilian Amazon, Science, 310, 480–482, https://doi.org/10.1126/science.1118051, 2005.
Brunet-Navarro, P., Jochheim, H., and Muys, B.: Modelling carbon stocks and fluxes in the wood product sector: a comparative review, Glob. Change Biol., 22, 2555–2569, https://doi.org/10.1111/gcb.13235, 2016.
Brunet-Navarro, P., Jochheim, H., and Muys, B.: The effect of increasing lifespan and recycling rate on carbon storage in wood products from theoretical model to application for the European wood sector, Mitig. Adapt. Strateg. Glob. Change, 22, 1193–1205, https://doi.org/10.1007/s11027-016-9722-z, 2017.
Cai, B., Lou, Z., Wang, J., Geng, Y., Sarkis, J., Liu, J., and Gao, Q.: CH4 mitigation potentials from China landfills and related environmental co-benefits, Sci. Adv., 4, eaar8400, https://doi.org/10.1126/sciadv.aar8400, 2018.
Chang, Z., Fan, L., Wigneron, J.-P., Wang, Y.-P., Ciais, P., Chave, J., Fensholt, R., Chen, J. M., Yuan, W., Ju, W., Li, X., Jiang, F., Wu, M., Chen, X., Qin, Y., Frappart, F., Li, X., Wang, M., Liu, X., Tang, X., Hobeichi, S., Yu, M., Ma, M., Wen, J., Xiao, Q., Shi, W., Liu, D., and Yan, J.: Estimating aboveground carbon dynamic of China using optical and microwave remote sensing datasets from 2013 to 2019, J. Remote Sens., 3, 0005, https://doi.org/10.34133/remotesensing.0005, 2023.
Chen, C., Park, T., Wang, X., Piao, S., Xu, B., Chaturvedi, R. K., Fuchs, R., Brovkin, V., Ciais, P., Fensholt, R., Tømmervik, H., Bala, G., Zhu, Z., Nemani, R. R., and Myneni, R. B.: China and India lead in greening of the world through land-use management, Nat. Sustain., 2, 122–129, https://doi.org/10.1038/s41893-019-0220-7, 2019.
Chen, Y., Shen, H., Zhong, Q., Chen, H., Huang, T., Liu, J., Cheng, H., Zeng, E. Y., Smith, K. R., and Tao, S.: Transition of household cookfuels in China from 2010 to 2012, Appl. Energ., 184, 800–809, https://doi.org/10.1016/j.apenergy.2016.07.136, 2016.
Churkina, G., Organschi, A., Reyer, C. P. O., Ruff, A., Vinke, K., Liu, Z., Reck, B. K., Graedel, T. E., and Schellnhuber, H. J.: Buildings as a global carbon sink, Nat. Sustain., 3, 269–276, https://doi.org/10.1038/s41893-019-0462-4, 2020.
Costanza, R., d'Arge, R., de Groot, R., Farberl, S., Grasso, M., Hannon, B., Limburg, K., Naeem, S., O'Neil, R. V., Paruelo, J., Raskin, R. G., Suttonl, P., and van den Belt, M.: The value of the world's ecosystem services and natural capital, Nature, 387, 253–260, https://doi.org/10.1016/S0921-8009(98)00020-2, 1997.
Curtis, P. G., Slay, C. M., Harris, N. L., Tyukavina, A., and Hansen, M. C.: Classifying drivers of global forest loss, Science, 361, 1108–1111, https://doi.org/10.1126/science.aau3445, 2018.
Deal, R. L. and White, R.: Integrating forest products with ecosystem services: A global perspective, For. Policy Econ., 17, 1–2, https://doi.org/10.1016/j.forpol.2012.02.014, 2012.
Dixon, R. K., Solomon, A. M., Brown, S., Houghton, R. A., Trexier, M. C., and Wisniewski, J.: Carbon pools and flux of global forest ecosystems, Science, 263, 185–190, https://doi.org/10.1126/science.263.5144.185, 1994.
Dong, J., Zhou, Y., and You, N.: A 30 m annual maximum NDVI dataset for China from 2000 to 2020 [DB/OL], National Ecosystem Science Data Center [data set], https://doi.org/10.12199/nesdc.ecodb.rs.2021.012, 2021.
FAO: Forestry data, FAOSTAT Database, Food and Agriculture Organization of the United Nations, Rome, Italy, https://www.fao.org/faostat/en/#data/FO (last access: 25 June 2023), 2020.
Fisher, B., Edwards, D. P., and Wilcove, D. S.: Logging and conservation: Economic impacts of the stocking rates and prices of commercial timber species, For. Policy Econ., 38, 65–71, https://doi.org/10.1016/j.forpol.2013.05.006, 2014.
Fortin, M., Ningre, F., Robert, N., and Mothe, F.: Quantifying the impact of forest management on the carbon balance of the forest-wood product chain: A case study applied to even-aged oak stands in France, Forest Ecol. Manag., 279, 176–188, https://doi.org/10.1016/j.foreco.2012.05.031, 2012.
Hansen, M. C., Potapov, P. V., Moore, R., Hancher, M., Turubanova, S. A., Tyukavina, A., Thau, D., Stehman, S. V., Goetz, S. J., Loveland, T. R., Kommareddy, A., Egorov, A., Chini, L., Justice, C. O., and Townshend, J. R. G.: High-resolution global maps of 21st-century forest cover change, Science, 342, 850–853, https://doi.org/10.1126/science.1244693, 2013.
Harper, A. B., Powell, T., Cox, P. M., House, J., Huntingford, C., Lenton, T. M., Sitch, S., Burke, E., Chadburn, S. E., Collins, W. J., Comyn-Platt, E., Daioglou, V., Doelman, J. C., Hayman, G., Robertson, E., Van Vuuren, D., Wiltshire, A., Webber, C. P., Bastos, A., Boysen, L., Ciais, P., Devaraju, N., Jain, A. K., Krause, A., Poulter, B., and Shu, S.: Land-use emissions play a critical role in landbased mitigation for Paris climate targets, Nat. Commun., 9, 2938, https://doi.org/10.1038/s41467-018-05340-z, 2018.
Harris, N. L., Gibbs, D. A., Baccini, A., Birdsey, R. A., De Bruin, S., Farina, M., Fatoyinbo, L., Hansen, M. C., Herold, M., Houghton, R. A., Potapov, P. V., Suarez, D. R., Roman-Cuesta, R. M., Saatchi, S. S., Slay, C. M., Turubanova, S. A., and Tyukavina, A.: Global maps of twenty-first century forest carbon fluxes, Nat. Clim. Change, 11, 234–240, https://doi.org/10.1038/s41558-020-00976-6, 2021.
Hethcoat, M. G., Edwards, D. P., Carreiras, J. M. B., Bryant, R. G., França, F. M., and Quegan, S.: A machine learning approach to map tropical selective logging, Remote Sens. Environ., 221, 569–582, https://doi.org/10.1016/j.rse.2018.11.044, 2019.
Huete, A., Didan, K., Miura, T., Rodriguez, E. P., Gao, X., and Ferreira, L. G.: Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195–213, https://doi.org/10.1016/S0034-4257(02)00096-2, 2002.
Hurtt, G. C., Chini, L. P., Frolking, S., Betts, R. A., Feddema, J., Fischer, G., Fisk, J. P., Hibbard, K., Houghton, R. A., Janetos, A., Jones, C. D., Kindermann, G., Kinoshita, T., Klein Goldewijk, K., Riahi, K., Shevliakova, E., Smith, S., Stehfest, E., Thomson, A., Thornton, P., Van Vuuren, D. P., and Wang, Y. P.: Harmonization of land-use scenarios for the period 1500–2100: 600 years of global gridded annual land-use transitions, wood harvest, and resulting secondary lands, Climatic Change, 109, 117–161, https://doi.org/10.1007/s10584-011-0153-2, 2011.
Hurtt, G. C., Chini, L., Sahajpal, R., Frolking, S., Bodirsky, B. L., Calvin, K., Doelman, J. C., Fisk, J., Fujimori, S., Klein Goldewijk, K., Hasegawa, T., Havlik, P., Heinimann, A., Humpenöder, F., Jungclaus, J., Kaplan, J. O., Kennedy, J., Krisztin, T., Lawrence, D., Lawrence, P., Ma, L., Mertz, O., Pongratz, J., Popp, A., Poulter, B., Riahi, K., Shevliakova, E., Stehfest, E., Thornton, P., Tubiello, F. N., van Vuuren, D. P., and Zhang, X.: Harmonization of global land use change and management for the period 850–2100 (LUH2) for CMIP6, Geosci. Model Dev., 13, 5425–5464, https://doi.org/10.5194/gmd-13-5425-2020, 2020.
IPCC: 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry and Other Land Use, Chap. 12: Harvested Wood Products, https://www.ipcc-nggip.iges.or.jp/support/Primer_2006GLs.pdf (last access: 25 June 2023), 2006a.
IPCC: 2006 IPCC Guidelines for National Greenhouse Gas Inventories, Volume 4: Agriculture, Forestry and Other Land Use, Chap. 4: Forest Land, https://www.ipcc-nggip.iges.or.jp/public/2006gl/pdf/4_Volume4/V4_04_Ch4_Forest_Land.pdf (last access: 27 December 2023), 2006b.
IPCC: 2013 revised supplementary methods and good practice guidance arising from the Kyoto Protocol, Intergovernmental Panel on Climate Change, Geneva, Switzerland, https://www.ipcc-nggip.iges.or.jp/public/kpsg/pdf/KP_Supplement_Entire_Report.pdf (last access: 24 June 2023), 2014.
IPCC: Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Volume 5: Waste, Chap. 3: Solid Waste Disposal, https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/5_Volume5/19R_V5_3_Ch03_SWDS.pdf (last access: 25 June 2023), 2019a.
IPCC: Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. Volume 4: Agriculture, Forestry and Other Land Use, Chap. 12: Harvested Wood Products, https://www.ipcc-nggip.iges.or.jp/public/2019rf/pdf/4_Volume4/19R_V4_Ch12_HarvestedWoodProducts.pdf (last access: 27 December 2023), 2019b.
IPCC: Climate Change 2021 – The Physical Science Basis: Working Group I Contribution to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, 1st Edn., Cambridge University Press, https://doi.org/10.1017/9781009157896, 2023.
Jian, X., Zhang, X., Liu, Y., Liu, X., Chen, K., Wang, L., Li, J., Zhao, Y., Luo, J., Zhugu, R., and Ma, J.: The response of radiative forcing to high spatiotemporally resolved land-use change and transition from 1982 to 2010 in China, Geophys. Res. Lett., 49, e2022GL099003, https://doi.org/10.1029/2022GL099003, 2022.
Jiang, X., Li, K., and Jiang, B.: Analysis on influencing factors of wood products blank outturn rate, Sci. Technol. Eng., 22, 10930–10938, 2022.
Johnston, C. M. T. and Radeloff, V. C.: Global mitigation potential of carbon stored in harvested wood products, P. Natl. Acad. Sci. USA, 116, 14526–14531, https://doi.org/10.1073/pnas.1904231116, 2019.
Kowalski, A. S., Loustau, D., Berbigier, P., Manca, G., Tedeschi, V., Borghetti, M., Valentini, R., Kolari, P., Berninger, F., Rannik, Ü., Hari, P., Rayment, M., Mencuccini, M., Moncrieff, J., and Grace, J.: Paired comparisons of carbon exchange between undisturbed and regenerating stands in four managed forests in Europe: Carbon exchange in mature and regenerating forest, Glob. Change Biol., 10, 1707–1723, https://doi.org/10.1111/j.1365-2486.2004.00846.x, 2004.
Lal, R., Lorenz, K., Hüttl, R. F., Schneider, B. U., and Von Braun, J. (Eds.): Ecosystem services and the global carbon cycle, in: Ecosystem services and carbon sequestration in the biosphere, Springer Netherlands, Dordrecht, 151–181, https://doi.org/10.1007/978-94-007-6455-2, 2013.
Li, F., He, B., and Yang, Z.: Progress of research on tree felling root treatment and application technology, Pract. For. Technol., 8, 9–11, https://doi.org/10.13456/j.cnki.lykt.2012.08.017, 2012.
Lippke, B., Oneil, E., Harrison, R., Skog, K., Gustavsson, L., and Sathre, R.: Life cycle impacts of forest management and wood utilization on carbon mitigation: knowns and unknowns, Carbon Manag., 2, 303–333, https://doi.org/10.4155/cmt.11.24, 2011.
Liu, D., Chen, Y., Cai, W., Dong, W., Xiao, J., Chen, J., Zhang, H., Xia, J., and Yuan, W.: The contribution of China's Grain to Green Program to carbon sequestration, Landsc. Ecol., 29, 1675–1688, https://doi.org/10.1007/s10980-014-0081-4, 2014.
Liu, S., Bond-Lamberty, B., Hicke, J. A., Vargas, R., Zhao, S., Chen, J., Edburg, S. L., Hu, Y., Liu, J., McGuire, A. D., Xiao, J., Keane, R., Yuan, W., Tang, J., Luo, Y., Potter, C., and Oeding, J.: Simulating the impacts of disturbances on forest carbon cycling in North America: Processes, data, models, and challenges, J. Geophys. Res., 116, G00K08, https://doi.org/10.1029/2010JG001585, 2011.
Masek, J. G., Cohen, W. B., Leckie, D., Wulder, M. A., Vargas, R., De Jong, B., Healey, S., Law, B., Birdsey, R., Houghton, R. A., Mildrexler, D., Goward, S., and Smith, W. B.: Recent rates of forest harvest and conversion in North America, J. Geophys. Res., 116, G00K03, https://doi.org/10.1029/2010JG001471, 2011.
Matricardi, E. A. T., Skole, D. L., Pedlowski, M. A., Chomentowski, W., and Fernandes, L. C.: Assessment of tropical forest degradation by selective logging and fire using Landsat imagery, Remote Sens. Environ., 114, 1117–1129, https://doi.org/10.1016/j.rse.2010.01.001, 2010.
Matsumoto, R., Kayo, C., Kita, S., Nakamura, K., Lauk, C., and Funada, R.: Estimation of carbon stocks in wood products for private building companies, Sci. Rep., 12, 18112, https://doi.org/10.1038/s41598-022-23112-0, 2022.
Nabuurs, G.-J., Verweij, P., Van Eupen, M., Pérez-Soba, M., Pülzl, H., and Hendriks, K.: Next-generation information to support a sustainable course for European forests, Nat. Sustain., 2, 815–818, https://doi.org/10.1038/s41893-019-0374-3, 2019.
National Forestry Administration: The definition of China forestry statistic indicators, China Forestry Press, Beijing, 117–137, https://www.stats.gov.cn/zt_18555/ztsj/hjtjzl/2013/202303/t20230302_1920915.html (last access: 12 January 2024), 2000.
National Forestry and Grassland Administration: China Forest Resources Report in 2014–2018, China Forestry Publishing, ISBN 978-7-5038-9982-9, 2019.
Nepstad, D. C., Nobre, C., Lima, E., Lefebvre, P., Schlesinger, P., Potter, C., Mendoza, E., Cochrane, M., and Brooks, V.: Large-scale impoverishment of Amazonian forests by logging and fire, 398, 505–508, https://doi.org/10.1038/19066, 1999.
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., Phillips, O. L., Shvidenko, A., Lewis, S. L., Canadell, J. G., Ciais, P., Jackson, R. B., Pacala, S. W., McGuire, A. D., Piao, S., Rautiainen, A., Sitch, S., and Hayes, D.: A large and persistent carbon sink in the world's forests, Science, 333, 988–993, https://doi.org/10.1126/science.1201609, 2011.
Pennock, D. J. and Van Kessel, C.: Clear-cut forest harvest impacts on soil quality indicators in the mixedwood forest of Saskatchewan, Canada, Geoderma, 75, 13–32, https://doi.org/10.1016/S0016-7061(96)00075-4, 1997.
Pingoud, K. and Wagner, F.: Methane emissions from landfills and carbon dynamics of harvested wood products: The First-Order Decay revisited, Mitig. Adapt. Strateg. Glob. Change, 11, 961–978, https://doi.org/10.1007/s11027-006-9029-6, 2006.
Profft, I., Mund, M., Weber, G.-E., Weller, E., and Schulze, E.-D.: Forest management and carbon sequestration in wood products, Eur. J. For. Res., 128, 399–413, https://doi.org/10.1007/s10342-009-0283-5, 2009.
Research and Market: Research report on timber import in China, 2019–2023, China Research & Intelligence, https://www.researchandmarkets.com/reports/4744796 (last access: 27 July 2023), 2019.
Skog, K. E.: Sequestration of carbon in harvested wood products for the United States, For. Prod. J., 58, 56–72, 2008.
Skog, K. E., Pingoud, K., and Smith, J. E.: A method countries can use to estimate changes in carbon stored in harvested wood products and the uncertainty of such estimates, Environ. Manage., 33, https://doi.org/10.1007/s00267-003-9118-1, 2004.
Smyth, C. E., Stinson, G., Neilson, E., Lemprière, T. C., Hafer, M., Rampley, G. J., and Kurz, W. A.: Quantifying the biophysical climate change mitigation potential of Canada's forest sector, Biogeosciences, 11, 3515–3529, https://doi.org/10.5194/bg-11-3515-2014, 2014.
Stockmann, K. D., Anderson, N. M., Skog, K. E., Healey, S. P., Loeffler, D. R., Jones, G., and Morrison, J. F.: Estimates of carbon stored in harvested wood products from the United States forest service northern region, 1906–2010, Carbon Balance Manag., 7, 1, https://doi.org/10.1186/1750-0680-7-1, 2012.
Tao, S., Ru, M. Y., Du, W., Zhu, X., Zhong, Q. R., Li, B. G., Shen, G. F., Pan, X. L., Meng, W. J., Chen, Y. L., Shen, H. Z., Lin, N., Su, S., Zhuo, S. J., Huang, T. B., Xu, Y., Yun, X., Liu, J. F., Wang, X. L., Liu, W. X., Cheng, H. F., and Zhu, D. Q.: Quantifying the rural residential energy transition in China from 1992 to 2012 through a representative national survey, Nat. Energy, 3, 567–573, https://doi.org/10.1038/s41560-018-0158-4, 2018.
Van Ewijk, S., Stegemann, J. A., and Ekins, P.: Limited climate benefits of global recycling of pulp and paper, Nat. Sustain., 4, 180–187, https://doi.org/10.1038/s41893-020-00624-z, 2020.
Wang, D., Ren, P., Xia, X., Fan, L., Qin, Z., Chen, X., and Yuan, W.: National forest carbon harvesting and allocation dataset for the period 2003 to 2018. figshare [data set], https://doi.org/10.6084/m9.figshare.23641164.v2, 2023.
Wei, X., Zhao, J., Hayes, D. J., Daigneault, A., and Zhu, H.: A life cycle and product type based estimator for quantifying the carbon stored in wood products, Carbon Balance Manag., 18, 1, https://doi.org/10.1186/s13021-022-00220-y, 2023.
Werner, F., Taverna, R., Hofer, P., Thürig, E., and Kaufmann, E.: National and global greenhouse gas dynamics of different forest management and wood use scenarios: a model-based assessment, Environ. Sci. Policy, 13, 72–85, https://doi.org/10.1016/j.envsci.2009.10.004, 2010.
White, M. K., Gower, S. T., and Ahl, D. E.: Life cycle inventories of roundwood production in northern Wisconsin: Inputs into an industrial forest carbon budget, Forest Ecol. Manag., 219, 13–28, https://doi.org/10.1016/j.foreco.2005.08.039, 2005.
Winjum, J. K., Brown, S., and Schlamadinger, B.: Forest harvests and wood products: Sources and sinks of atmospheric carbon dioxide, For. Sci., 44, 272–284, https://doi.org/10.1093/forestscience/44.2.272, 1998.
Xia, X., Xia, J., Chen, X., Fan, L., Liu, S., Qin, Y., Qin, Z., Xiao, X., Xu, W., Yue, C., Yue, X., and Yuan, W.: Reconstructing long-term forest cover in China by fusing national forest inventory and 20 land use and land cover data sets, J. Geophys. Res.-Biogeo., 128, e2022JG007101, https://doi.org/10.1029/2022JG007101, 2023.
Yu, Z., Zhao, H., Liu, S., Zhou, G., Fang, J., Yu, G., Tang, X., Wang, W., Yan, J., Wang, G., Ma, K., Li, S., Du, S., Han, S., Ma, Y., Zhang, D., Liu, J., Liu, S., Chu, G., Zhang, Q., and Li, Y.: Mapping forest type and age in China's plantations, Sci. Total Environ., 744, 140790, https://doi.org/10.1016/j.scitotenv.2020.140790, 2020.
Yu, Z., Ciais, P., Piao, S., Houghton, R. A., Lu, C., Tian, H., Agathokleous, E., Kattel, G. R., Sitch, S., Goll, D., Yue, X., Walker, A., Friedlingstein, P., Jain, A. K., Liu, S., and Zhou, G.: Forest expansion dominates China's land carbon sink since 1980, Nat. Commun., 13, 5374, https://doi.org/10.1038/s41467-022-32961-2, 2022.
Yuan, W., Li, X., Liang, S., Cui, X., Dong, W., Liu, S., Xia, J., Chen, Y., Liu, D., and Zhu, W.: Characterization of locations and extents of afforestation from the Grain for Green Project in China, Remote Sens. Lett., 5, 221–229, https://doi.org/10.1080/2150704X.2014.894655, 2014.
Yuan, W., Zheng, Y., Piao, S., Ciais, P., Lombardozzi, D., Wang, Y., Ryu, Y., Chen, G., Dong, W., Hu, Z., Jain, A. K., Jiang, C., Kato, E., Li, S., Lienert, S., Liu, S., Nabel, J. E. M. S., Qin, Z., Quine, T., Sitch, S., Smith, W. K., Wang, F., Wu, C., Xiao, Z., and Yang, S.: Increased atmospheric vapor pressure deficit reduces global vegetation growth, Sci. Adv., 5, eaax1396, https://doi.org/10.1126/sciadv.aax1396, 2019.
Zhang, L., Sun, Y., Song, T., and Xu, J.: Harvested wood products as a carbon sink in China, 1900–2016, Int. J. Environ. Res. Pub. He., 16, 445, https://doi.org/10.3390/ijerph16030445, 2019.
Zhang, X., Yang, H., and Chen, J.: Life-cycle carbon budget of China's harvested wood products in 1900–2015, For. Policy Econ., 92, 181–192, https://doi.org/10.1016/j.forpol.2018.05.005, 2018.
Short summary
This study generated a high-precision dataset, locating forest harvested carbon and quantifying post-harvest wood emissions for various uses. It enhances our understanding of forest harvesting and post-harvest carbon dynamics in China, providing essential data for estimating the forest ecosystem carbon budget and emphasizing wood utilization's impact on carbon emissions.
This study generated a high-precision dataset, locating forest harvested carbon and quantifying...
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