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.