A Vertically Resolved Canopy Improves Chemical Transport Model Predictions of Ozone Deposition to North Temperate Forests

Abstract

Dry deposition is the second largest tropospheric ozone (O₃) sink and occurs through stomatal and nonstomatal pathways. Current O₃ uptake predictions are limited by the simplistic big-leaf schemes commonly used in chemical transport models (CTMs) to parameterize deposition. Such schemes fail to reproduce observed O₃ fluxes over terrestrial ecosystems, highlighting the need for more realistic treatment of surface-atmosphere exchange in CTMs. We address this need by linking a resolved canopy model (1D Multi-Layer Canopy CHemistry and Exchange Model, MLC-CHEM) to the GEOS-Chem CTM and use this new framework to simulate O₃ fluxes over three north temperate forests. We compare results with in situ measurements from four field studies and with standalone, observationally constrained MLC-CHEM runs to test current knowledge of O₃ deposition and its drivers. We show that GEOS-Chem overpredicts observed O₃ fluxes across all four studies by up to 2×, whereas the resolved-canopy models capture observed diel profiles of O₃ deposition and in-canopy concentrations to within 10%. Relative humidity and solar irradiance are strong O₃ flux drivers over these forests, and uncertainties in those fields provide the largest remaining source of model deposition biases. Flux partitioning analysis shows that: (a) nonstomatal loss accounts for 60% of O₃ deposition on average; (b) in-canopy chemistry makes only a small contribution to total O₃ fluxes; and (c) the CTM big-leaf treatment overestimates O₃-driven stomatal loss and plant phytotoxicity in these temperate forests by up to 7×. Results motivate the application of fully online vertically explicit canopy schemes in CTMs for improved O₃ predictions.