Comment on egusphere-2025-485

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Abstract
The presence of dense forest canopies significantly alters the near-field dynamical, physical, and chemical environment, with implications for atmospheric composition and air quality variables such as boundary layer ozone (O₃). Observations show profound vertical gradients in O3 concentration beneath forest canopies; however, most chemical transport models (CTMs) used in the operational and research community, such as the Community Multiscale Air Quality (CMAQ) model, cannot account for such effects due to inadequate canopy representation and lack of sub-canopy processes. To address this knowledge gap, we implemented detailed forest canopy processes—including in-canopy photolysis attenuation and turbulence—into the CMAQv5.3.1 model, driven by the Global Forecast System and enhanced with high-resolution vegetation datasets. Simulations were conducted for August 2019 over the contiguous U.S. The canopy-aware model shows substantial improvement, with mean O₃ bias reduced from +0.70 ppb (Base) to −0.10 ppb (Canopy), and fractional bias from +9.71% to +6.37%. Monthly mean O₃ in the lowest model layer (~0–40 m) decreased by up to 9 ppb in dense forests, especially in the East. Process analysis reveals a 75.2% drop in first-layer O₃, with daily surface production declining from 673 to 167 ppb d⁻¹, driven by suppressed photolysis and vertical mixing. This enhances NOₓ titration and reduces O₃ formation under darker, stable conditions. The results highlight the critical role of canopy processes in atmospheric chemistry and demonstrate the importance of incorporating realistic vegetation-atmosphere interactions in CTMs to improve air quality forecasts and health-relevant exposure assessments.

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