Plants have a strong influence on climate by controlling the transfer of carbon dioxide and water between the biosphere and atmosphere during the processes of photosynthesis and transpiration. Chronic exposure to surface ozone (Oâ) differentially affects photosynthesis and transpiration because it damages stomatal conductance, the common link that controls both processes, in addition to the leaf biochemistry that only affects photosynthesis. Because of the integral role of Oâ in altering plant interactions with the atmosphere, there is a strong motivation to incorporate the influence of Oâ into regional and global models. However, there are currently no analyses documenting both photosynthesis and stomatal conductance responses to Oâ exposure through time using a standardized Oâ parameter that can be easily incorporated into models. Therefore, models often rely on photosynthesis data derived from the responses of one or a few plant species that exhibit strong negative correlations with Oâ exposure to drive both rates of photosynthesis and transpiration, neglecting potential divergence between the two fluxes. Using data from the peer-reviewed literature, we have compiled photosynthetic and stomatal responses to chronic Oâ exposure for all plant types with data available in the peer-reviewed literature as a standardized function of cumulative uptake of Oâ (CUO), which integrates Oâ flux into leaves through time. These data suggest that stomatal conductance decreases â¼11% after chronic Oâ exposure, while photosynthesis independently decreases â¼21%. Despite the overall decrease in both variables, high variance masked any correlations between the decline in photosynthesis or stomatal conductance with increases in CUO. Though correlations with CUO are not easily generalized, existing correlations demonstrate that photosynthesis tends to be weakly but negatively correlated with CUO while stomatal conductance is more often positively correlated with CUO. Results suggest that large-scale models using data with strong negative correlations that only affect photosynthesis need to reconsider the generality of their response. Data from this analysis are now available to the scientific community and can be incorporated into global models to improve estimates of photosynthesis, global land-carbon sinks, hydrology, and indirect radiative forcing that are influenced by chronic Oâ exposure.