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Multivariate Regression-Based Dynamic Simulation Modeling of Cumulative Carbon Emissions from Fields

Author

Listed:
  • Jianqin Ma

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Xiaolong Xu

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Bifeng Cui

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
    Henan Key Laboratory of Water Pollution Control and Rehabilitation Technology, Henan University of Urban Construction, Pingdingshan 467036, China)

  • Xiuping Hao

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Jiangshan Yang

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Shuoguo Yang

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

  • Lansong Liu

    (School of Water Conservaney, North China University of Water Resources and Electric Power, Zhengzhou 450046, China)

Abstract

Determining the influencing factors of winter wheat field carbon emissions and their dynamic trends is of great significance to study the carbon emission mechanism of winter wheat, reduce greenhouse gas emissions from agricultural fields, and promote the sustainable development of agriculture. The aim of this study is to analyze the relationship between different influencing factors and CO 2 emission fluxes in winter wheat fields and to construct a dynamic simulation model of field carbon emission so as to provide a basis for accurate and convenient calculation of CO 2 emission from wheat fields in the Henan region. This study comprehensively considered the effects of the dynamic changes in meteorological, soil, hydrological, and other factors over time on the field carbon emission during the growth process of the crop and carried out a dynamic simulation study of the field carbon emission in the experimental field with six sets of experiments, using the multiple regression method. Six groups of experiments were set up, and a multi-parameter field carbon emission dynamic model was constructed by the multiple regression method to simulate the optimal calculation model. The results showed that the simulated values of field CO 2 emissions were consistent with the trend of the measured values, and the total cumulative CO 2 emissions in fields A1, A2, and A3 were 8624.2 kg/hm 2 , 7924.3 kg/hm 2 , and 7531.4 kg/hm 2 , respectively, while the model-simulated values were 9399.2 kg/hm 2 , 8935.2 kg/hm 2 , and 8371.1 kg/hm 2 . The errors between the simulated and actual emissions were 7.9%, 12.8%, and 11.1%, respectively, indicating a high accuracy in the simulation results. The model developed in this study comprehensively accounts for the dynamic impacts of meteorological, soil, and hydraulic factors on CO 2 emissions, effectively reflecting the dynamic changes in field carbon emissions and achieving high calculation accuracy.

Suggested Citation

  • Jianqin Ma & Xiaolong Xu & Bifeng Cui & Xiuping Hao & Jiangshan Yang & Shuoguo Yang & Lansong Liu, 2024. "Multivariate Regression-Based Dynamic Simulation Modeling of Cumulative Carbon Emissions from Fields," Sustainability, MDPI, vol. 16(22), pages 1-13, November.
    • Handle: RePEc:gam:jsusta:v:16:y:2024:i:22:p:9700-:d:1516028
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    References listed on IDEAS

    as
    1. Jianqin Ma & Lansong Liu & Bifeng Cui & Xiuping Hao & Qinxue He & Jiangshan Yang & Xiaolong Xu, 2024. "Research on the Coupling Effect of Water and Fertilizer on Maize under Multi-Objective Conditions and Its Application Scenarios," Sustainability, MDPI, vol. 16(13), pages 1-15, June.
    2. 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.
    3. Jianqin Ma & Jiangshan Yang & Xiuping Hao & Bifeng Cui & Shuoguo Yang, 2023. "Dynamic Simulation Model of Channel Leakage Based on Multiple Regression," Sustainability, MDPI, vol. 15(20), pages 1-13, October.
    Full references (including those not matched with items on IDEAS)

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