IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i4p781-d1109909.html
   My bibliography  Save this article

Estimates of Dust Emissions and Organic Carbon Losses Induced by Wind Erosion in Farmland Worldwide from 2017 to 2021

Author

Listed:
  • Yongxiang Liu

    (Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China
    Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

  • Hongmei Zhao

    (Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

  • Guangying Zhao

    (Heilongjiang Province Key Laboratory of Geographical Environment Monitoring and Spatial Information Service in Cold Regions, School of Geographical Sciences, Harbin Normal University, Harbin 150025, China)

  • Xinyuan Cao

    (School of Energy and Environment, Shenyang Aerospace University, Shenyang 110136, China)

  • Xuelei Zhang

    (Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

  • Aijun Xiu

    (Key Laboratory of Wetland Ecology and Environment, Northeast Institute of Geography and Agroecology, Chinese Academy of Sciences, Changchun 130102, China)

Abstract

Wind erosion can cause high dust emissions from agricultural land and can lead to a significant loss of carbon and nutrients from the soil. The carbon balance of farmland soil is an integral part of the carbon cycle, especially under the current drive to develop carbon-neutral practices. However, the amount of global carbon lost due to the wind erosion of farmland is unknown. In this study, global farmland dust emissions were estimated from a dust emission inventory (0.1° × 0.1°, daily) built using the improved Community Multiscale Air Quality Modeling System–FENGSHA (CMAQ-FENGSHA), and global farmland organic carbon losses were estimated by combining this with global soil organic carbon concentration data. The average global annual dust emissions from agricultural land from 2017 to 2021 were 1.75 × 10 9 g/s. Global dust emissions from agricultural land are concentrated in the UK, Ukraine, and Russia in Europe; in southern Canada and the central US in North America; in the area around Buenos Aires, the capital of Argentina, in South America; and in northeast China in Asia. The global average annual organic carbon loss from agricultural land was 2970 Gg for 2017–2021. The spatial distribution of emissions is roughly consistent with that of dust emissions, which are mainly concentrated in the world’s four major black soil regions. These estimates of dust and organic carbon losses from agricultural land are essential references that can inform the global responses to the carbon cycle, dust emissions, and black soil conservation.

Suggested Citation

  • Yongxiang Liu & Hongmei Zhao & Guangying Zhao & Xinyuan Cao & Xuelei Zhang & Aijun Xiu, 2023. "Estimates of Dust Emissions and Organic Carbon Losses Induced by Wind Erosion in Farmland Worldwide from 2017 to 2021," Agriculture, MDPI, vol. 13(4), pages 1-15, March.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:4:p:781-:d:1109909
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/4/781/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/4/781/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Christian Otto & Franziska Piontek & Matthias Kalkuhl & Katja Frieler, 2020. "Event-based models to understand the scale of the impact of extremes," Nature Energy, Nature, vol. 5(2), pages 111-114, February.
    2. Weixiao Chen & Huan Meng & Hongquan Song & Hui Zheng, 2022. "Progress in Dust Modelling, Global Dust Budgets, and Soil Organic Carbon Dynamics," Land, MDPI, vol. 11(2), pages 1-19, January.
    3. Mugizi, Francisco M.P. & Matsumoto, Tomoya, 2020. "Population pressure and soil quality in Sub-Saharan Africa: Panel evidence from Kenya," Land Use Policy, Elsevier, vol. 94(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yongxiang Liu & Hongmei Zhao & Guangying Zhao & Xuelei Zhang & Aijun Xiu, 2024. "Carbon Emission Characteristics of Cropland in Northeast China and Monitoring Means," Agriculture, MDPI, vol. 14(3), pages 1-13, February.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nikas, A. & Gambhir, A. & Trutnevyte, E. & Koasidis, K. & Lund, H. & Thellufsen, J.Z. & Mayer, D. & Zachmann, G. & Miguel, L.J. & Ferreras-Alonso, N. & Sognnaes, I. & Peters, G.P. & Colombo, E. & Howe, 2021. "Perspective of comprehensive and comprehensible multi-model energy and climate science in Europe," Energy, Elsevier, vol. 215(PA).
    2. Mugizi, Francisco M.P. & Matsumoto, Tomoya, 2021. "A curse or a blessing? Population pressure and soil quality in Sub-Saharan Africa: Evidence from rural Uganda," Ecological Economics, Elsevier, vol. 179(C).
    3. Mengyao Zhu & Dandan Liu & Weichao Tang & Qian Chi & Xiao Zhao & Siqi Xu & Siyu Ye & Yaobin Wang & Yaoping Cui & Shenghui Zhou, 2022. "Exploring the Ecological Climate Effects Based on Five Land Use Types: A Case Study of the Huang-Huai-Hai River Basin in China," Land, MDPI, vol. 11(2), pages 1-18, February.
    4. Arnaud Mignan & Matteo Spada & Peter Burgherr & Ziqi Wang & Didier Sornette, 2022. "Dynamics of severe accidents in the oil & gas energy sector derived from the authoritative ENergy-related severe accident database," PLOS ONE, Public Library of Science, vol. 17(2), pages 1-14, February.
    5. Xinhai Lu & Yanwei Zhang & Chaoran Lin & Feng Wu, 2021. "Evolutionary Overview and Prediction of Themes in the Field of Land Degradation," Land, MDPI, vol. 10(3), pages 1-23, March.
    6. Ling Yang & Qiang Ren & Shiji Ge & Zhiqiang Jiao & Wenhao Zhan & Runxiao Hou & Xinling Ruan & Yanfang Pan & Yangyang Wang, 2022. "Metal(loid)s Spatial Distribution, Accumulation, and Potential Health Risk Assessment in Soil-Wheat Systems near a Pb/Zn Smelter in Henan Province, Central China," IJERPH, MDPI, vol. 19(5), pages 1-12, February.
    7. Xiao Zhao & Mengyao Zhu & Dandan Liu & Siqi Xu & Siyu Ye & Shuang Wang & Yaoping Cui & Shenghui Zhou, 2022. "Exploring the Ecological Climate Effects of Different Land Use Changes in the Yangtze River Basin from 2000 to 2020," Land, MDPI, vol. 11(10), pages 1-16, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:4:p:781-:d:1109909. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.