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Tropospheric Ozone (O-3) is both an air pollutant and a greenhouse gas. Predicting changes to O-3 is therefore important for both air quality and near-term climate forcing. It is computationally expensive to predict changes in tropospheric O-3 from every possible future scenario in composition climate models like those used in the 6th Coupled Model Intercomparison Project (CMIP6). Here we apply the different emission pathways used in CMIP6 with a model based on source-receptor relationships for tropospheric O-3 to predict historical and future changes in O-3 and its radiative forcing over a 300 year period (1750-2050). Changes in regional precursor emissions (nitrogen oxides, carbon monoxide and volatile organic compounds) and global methane abundance are used to quantify the impact on tropospheric O-3 globally and across 16 regions, neglecting any impact from changes in climate. We predict large increases in global surface O-3 ( + 8 ppbv) and O-3 radiative forcing ( + 0.3 W m(-2)) over the industrial period. Nine different Shared Socio-economic Pathways are used to assess future changes in O-3. Scenarios involving weak air pollutant controls and climate mitigation are inadequate in limiting the future degradation of surface O-3 air quality and enhancement of near-term climate warming over all regions. Middle-ofthe-road and strong mitigation scenarios reduce both surface O-3 concentrations and O-3 radiative forcing by up to 5 ppbv and 0.17 W m(-2) globally, providing benefits to future air quality and near-term climate forcing. Sensitivity experiments show that targeting mitigation measures towards reducing global methane abundances could yield additional benefits for both surface O-3 air quality and near-term climate forcing. The parameterisation provides a valuable tool for rapidly assessing a large range of future emission pathways that involve differing degrees of air pollutant and climate mitigation. The calculated range of possible responses in tropospheric O-3 from these scenarios can be used to inform other modelling studies in CMIP6.