Preprints
https://doi.org/10.5194/egusphere-2025-6470
https://doi.org/10.5194/egusphere-2025-6470
25 Feb 2026
 | 25 Feb 2026
Status: this preprint is open for discussion and under review for Atmospheric Chemistry and Physics (ACP).

Elucidating CO2 accumulation and dispersion in a semi-enclosed bay industrial park using Lidar and WRF-GHG modelling

Daihao Yu, Qiuwei Xia, Saifen Yu, Yixiang Chen, Keyi Xu, Haobin Han, Jianjun Guo, Kexin Guo, Jiadong Hu, Zhen Zhang, Jing Cai, Yuanjian Yang, and Haiyun Xia

Abstract. Industrial parks represent critical nodes in the global carbon cycle and thus require accurate monitoring and modelling to support effective carbon management. Although satellite observations, ground-based measurements, and numerical modelling frameworks have been widely utilized, these approaches inherently struggle to simultaneously achieve high temporal and spatial resolution. In this study, high-resolution Lidar is integrated with the Weather Research and Forecasting model coupled with greenhouse gas fluxes (WRF-GHG) modelling to comprehensively diagnose the CO2 accumulation–dispersion dynamics and their driving mechanisms within the Luoyuan Bay industrial park. The comprehensive analysis reveals a distinctive diurnal pattern of CO2, characterized by nighttime accumulation and daytime dispersion. Lidar observations indicate that stable atmospheric conditions and valley terrain synergistically cause CO2 to accumulate in low-lying areas at night, with concentrations exceeding 700 ppm. During daytime, strengthened southeasterly sea breezes and intensified turbulence promote its dispersion to the northwest and vertical uplift, reducing concentrations to 500-550 ppm. A significantly negative correlation between CO2 concentration and wind speed is also confirmed. While the WRF-GHG model reproduces the overall temporal variation, it systematically underestimates CO2 levels (420–460 ppm). The discrepancy is attributed to the limited spatial resolution of the emission inventory and the model’s inherent constraints in capturing terrain–wind field interactions within the bay. This study highlights the unique capabilities of coherent differential absorption Lidar, elucidates the key limitations of current modelling approaches, and provides a robust scientific basis for refining carbon verification systems and enhancing the performance of regional carbon models.

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Daihao Yu, Qiuwei Xia, Saifen Yu, Yixiang Chen, Keyi Xu, Haobin Han, Jianjun Guo, Kexin Guo, Jiadong Hu, Zhen Zhang, Jing Cai, Yuanjian Yang, and Haiyun Xia

Status: open (until 08 Apr 2026)

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Daihao Yu, Qiuwei Xia, Saifen Yu, Yixiang Chen, Keyi Xu, Haobin Han, Jianjun Guo, Kexin Guo, Jiadong Hu, Zhen Zhang, Jing Cai, Yuanjian Yang, and Haiyun Xia
Daihao Yu, Qiuwei Xia, Saifen Yu, Yixiang Chen, Keyi Xu, Haobin Han, Jianjun Guo, Kexin Guo, Jiadong Hu, Zhen Zhang, Jing Cai, Yuanjian Yang, and Haiyun Xia
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Short summary
Industrial parks are critical nodes in the global carbon cycle. This study combines high-resolution lidar observations and the WRF-GHG model to examine CO2 accumulation and dispersion in a semi-enclosed bay. Distinct diurnal patterns emerge: nighttime accumulation and daytime dispersion driven by terrain, atmospheric stability and sea breezes. WRF-GHG captures temporal trends, but it underestimates CO2 levels, indicating limitations in emission inventories and terrain-wind interactions.
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