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Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle

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  • Xiao Chen

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China
    Institute of Smart Agriculture, Jilin Agricultural University, Changchun 130118, China)

  • Tao Tao

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China)

  • Jiaxin Zhou

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China)

  • Helong Yu

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China
    Institute of Smart Agriculture, Jilin Agricultural University, Changchun 130118, China)

  • Hongliang Guo

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China
    Institute of Smart Agriculture, Jilin Agricultural University, Changchun 130118, China)

  • Hongbing Chen

    (College of Information Technology, Jilin Agricultural University, Changchun 130118, China
    Institute of Smart Agriculture, Jilin Agricultural University, Changchun 130118, China)

Abstract

Greenhouse gas emission is a key issue in the sustainable development of agriculture. To effectively predict the greenhouse gas emissions of beef cattle, a model is proposed based on system dynamics and greenhouse gas emission calculation methods, and a scenario is set as a ‘Straw to Beef’ project in Jilin Province. The model was built on a baseline emission scenario (feed precision: 60%, breeding environment: dry fattening farm, corn straw utilization: burning straw), with single- and comprehensive emission reduction scenarios considered, predicting trends and reduction potentials in greenhouse gas emissions from cattle breeding and straw burning in Jilin Province from 2013 to 2028, measured in CO 2 -eq (CO 2 equivalent). The model also explored the impact of 11 controllable variables on greenhouse gas emissions. Results showed that (1) From 2013 to 2022, greenhouse gas emissions from straw burning and cattle breeding in Jilin Province increased significantly and had an annual growth rate of 6.51% in 2020. (2) Single emission reduction scenarios showed an increasing trend in greenhouse gas emissions, while comprehensive emission reduction scenarios showed a decreasing trend. Among them, the S2.2.1 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: burning straw) had the strongest emission reduction ability in the single reduction scenario, the S3.2.2 scenario (feed precision: 80%, breeding environment: livestock barn manure pit, corn straw utilization: Feed-processing straw) had the strongest emission reduction ability in the comprehensive reduction scenario, reducing emissions by 5.10% and 69.24%, respectively, compared to the baseline scenario. This suggests that the comprehensive emission reduction scenarios which utilized straw resources reasonably can greatly reduce agricultural greenhouse gas emissions. (3) The optimal emission reduction scenario indicated that the higher the proportion of digestible energy in beef cattle’s total energy intake, the more perfect the fecal treatment process, and the higher the utilization rate of straw feed, the lower the greenhouse gas emissions. Therefore, to effectively reduce greenhouse gas emissions from cattle breeding and straw burning in Jilin Province, it is important to implement comprehensive emission reduction scenarios prioritizing the efficient utilization of straw resources and improving beef cattle management practices.

Suggested Citation

  • Xiao Chen & Tao Tao & Jiaxin Zhou & Helong Yu & Hongliang Guo & Hongbing Chen, 2023. "Simulation and Prediction of Greenhouse Gas Emissions from Beef Cattle," Sustainability, MDPI, vol. 15(15), pages 1-14, August.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:15:p:11994-:d:1210426
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    References listed on IDEAS

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