Ozone deposition impact assessments for forest canopies require accurate ozone flux partitioning on diurnal timescales

Dry deposition is an important sink of tropospheric ozone that affects surface concentrations and impacts crop yields, the land carbon sink, and the terrestrial water cycle. Dry deposition pathways include plant uptake via stomata and non-stomatal removal by soils, leaf surfaces, and chemical reactions. Observational studies indicate that ozone deposition exhibits substantial temporal variability that is not reproduced by atmospheric chemistry models due to a simplified representation of vegetation uptake processes in these models. In this study, we explore the importance of stomatal and non-stomatal uptake processes in driving ozone dry deposition variability on diurnal to seasonal timescales. Specifically, we compare two land surface ozone uptake parameterizations - a commonly applied big leaf parameterization (W89; Wesely, 1989) and a multi-layer model (MLC-CHEM) constrained with observations - to multi-year ozone flux observations at two European measurement sites (Ispra, Italy, and Hyytiala, Finland). We find that W89 cannot reproduce the diurnal cycle in ozone deposition due to a misrepresentation of stomatal and non-stomatal sinks at our two study sites, while MLC-CHEM accurately reproduces the different sink pathways. Evaluation of non-stomatal uptake further corroborates the previously found important roles of wet leaf uptake in the morning under humid conditions and soil uptake during warm conditions. The misrepresentation of stomatal versus non-stomatal uptake in W89 results in an overestimation of growing season cumulative ozone uptake (CUO), a metric for assessments of vegetation ozone damage, by 18 % (Ispra) and 28 % (Hyytiala), while MLC-CHEM reproduces CUO within 7 % of the observation-inferred values. Our results indicate the need to accurately describe the partitioning of the ozone atmosphere-biosphere flux over the in-canopy stomatal and non-stomatal loss pathways to provide more confidence in atmospheric chemistry model simulations of surface ozone mixing ratios and deposition fluxes for large-scale vegetation ozone impact assessments.