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Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling

Author

Listed:
  • Yang Wei

    (Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, China
    State Grid Sichuan Electric Power Research Institute, Chengdu 610041, China)

  • Yufei Teng

    (Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, China
    State Grid Sichuan Electric Power Research Institute, Chengdu 610041, China)

  • Xueyuan Liu

    (Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, China
    State Grid Sichuan Electric Power Research Institute, Chengdu 610041, China)

  • Yumin Chen

    (Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, China
    State Grid Sichuan Electric Power Research Institute, Chengdu 610041, China)

  • Jie Zhang

    (State Grid Sichuan Electric Power Company, Chengdu 610041, China)

  • Shijie Deng

    (School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, China)

  • Zhengyang Liu

    (School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, China)

  • Qian Li

    (School of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, China)

Abstract

To achieve the precise quantification and real-time monitoring of CO 2 emissions from stationary sources, this study developed a Gaussian plume model-based dispersion framework incorporating emission characteristics. Critical factors affecting CO 2 dispersion were systematically analyzed, with model optimization conducted through plume rise height adjustments and reflection coefficient calibrations. MATLAB-based simulations on an industrial park case study demonstrated that wind speed, atmospheric stability, and effective release height constituted pivotal determinants for enhancing CO 2 dispersion modeling accuracy. Furthermore, the inverse estimation of source strength at emission terminals was implemented via particle swarm optimization, establishing both theoretical foundations and methodological frameworks for the precision monitoring and predictive dispersion analysis of stationary-source CO 2 emissions.

Suggested Citation

  • Yang Wei & Yufei Teng & Xueyuan Liu & Yumin Chen & Jie Zhang & Shijie Deng & Zhengyang Liu & Qian Li, 2025. "Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling," Energies, MDPI, vol. 18(11), pages 1-24, May.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:11:p:2827-:d:1667163
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