Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling
To achieve the precise quantification and real-time monitoring of CO<sub>2</sub> emissions from stationary sources, this study developed a Gaussian plume model-based dispersion framework incorporating emission characteristics. Critical factors affecting CO<sub>2</sub> dispers...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-05-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/11/2827 |
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| author | Yang Wei Yufei Teng Xueyuan Liu Yumin Chen Jie Zhang Shijie Deng Zhengyang Liu Qian Li |
| author_facet | Yang Wei Yufei Teng Xueyuan Liu Yumin Chen Jie Zhang Shijie Deng Zhengyang Liu Qian Li |
| author_sort | Yang Wei |
| collection | DOAJ |
| description | To achieve the precise quantification and real-time monitoring of CO<sub>2</sub> emissions from stationary sources, this study developed a Gaussian plume model-based dispersion framework incorporating emission characteristics. Critical factors affecting CO<sub>2</sub> 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<sub>2</sub> 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<sub>2</sub> emissions. |
| format | Article |
| id | doaj-art-2cebfc09fa6040a8b7f17fb5ea97173d |
| institution | OA Journals |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-05-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-2cebfc09fa6040a8b7f17fb5ea97173d2025-08-20T02:32:37ZengMDPI AGEnergies1996-10732025-05-011811282710.3390/en18112827Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume ModelingYang Wei0Yufei Teng1Xueyuan Liu2Yumin Chen3Jie Zhang4Shijie Deng5Zhengyang Liu6Qian Li7Power System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, ChinaPower System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, ChinaPower System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, ChinaPower System Security and Operation Key Laboratory of Sichuan Province, Chengdu 611731, ChinaState Grid Sichuan Electric Power Company, Chengdu 610041, ChinaSchool of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, ChinaSchool of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, ChinaSchool of Electrical Engineering and Information, Southwest Petroleum University, Chengdu 610500, ChinaTo achieve the precise quantification and real-time monitoring of CO<sub>2</sub> emissions from stationary sources, this study developed a Gaussian plume model-based dispersion framework incorporating emission characteristics. Critical factors affecting CO<sub>2</sub> 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<sub>2</sub> 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<sub>2</sub> emissions.https://www.mdpi.com/1996-1073/18/11/2827stationary sourcescarbon dioxideatmospheric dispersionGaussian plume model |
| spellingShingle | Yang Wei Yufei Teng Xueyuan Liu Yumin Chen Jie Zhang Shijie Deng Zhengyang Liu Qian Li Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling Energies stationary sources carbon dioxide atmospheric dispersion Gaussian plume model |
| title | Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling |
| title_full | Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling |
| title_fullStr | Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling |
| title_full_unstemmed | Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling |
| title_short | Diffusion Modeling of Carbon Dioxide Concentration from Stationary Sources with Improved Gaussian Plume Modeling |
| title_sort | diffusion modeling of carbon dioxide concentration from stationary sources with improved gaussian plume modeling |
| topic | stationary sources carbon dioxide atmospheric dispersion Gaussian plume model |
| url | https://www.mdpi.com/1996-1073/18/11/2827 |
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