Integrating Ozone–vegetation Damage Schemes into SSiB4/TRIFFID: Evaluation of Six Parameterizations and Refinement of Ozone Decay Process Across Plant Functional Types

Abstract. Tropospheric ozone (O₃) is a major air pollutant that threatens vegetation productivity and terrestrial ecosystems. Quantifying O₃-induced impacts on photosynthesis and stomatal conductance is crucial for understanding biosphere-atmosphere interactions at regional and global scales. In recent decades, several parameterization schemes have been developed to describe the photosynthetic and stomatal responses to O₃ exposure. However, substantial discrepancies remain when applying different schemes in various model frameworks. In this study, we integrated six flux-based O₃-vegetation damage parameterizations into SSiB4/TRIFFID, a well-established dynamic global vegetation model, to assess the impacts of O₃ pollution on vegetation photosynthesis in China during the 2010s. Our results indicate that O₃ pollution led to approximately a 20 % reduction in GPP during the 2010s, with discrepancies ranging from 15 % to 31 % across different schemes. Comparison of the O₃ damage schemes revealed substantial differences in plant O₃ sensitivity across schemes and plant functional types (PFTs). When evaluated against observations, the newly developed L2024 parameterization—which features non‑linear response formulations—and the trait‑informed approaches based on leaf mass per area (LMA) both reproduce observed O₃ sensitivity more closely, as reflected in their consistently smaller biases. This improved performance can be attributed to the inclusion of a broader range of observational and experimental data, as well as key physiological parameters (e.g., LMA) to better capture O₃ sensitivity. Furthermore, we found that the L2024 scheme exhibited strong inhibition of photosynthesis in the late growing season due to cumulative O₃ exposure. By refining the "decay" process of O₃ accumulation using leaf lifespan parameters and applying the "decay" and "healing" processes across all PFTs, we improved the spatial and temporal distribution of gross primary productivity (GPP) simulations. This study highlights the importance of observations and physiological insights in developing O₃-vegetation damage parameterizations. Future efforts should focus on expanding observational and experimental data on O₃ responses in China’s natural ecosystems to enhance O₃ damage assessment and model development.