The contribution of NOx emissions and background O3 to the sources and partitioning of the oxidants [OX (= O3 + NO2)] at the Marylebone Road site in London during the 2000s and 2010s has been investigated to see the impact of the control measures or technology changes inline with the London Mayor's Air Quality Strategy. The abatement of the pollution emissions has an impact on the trends of local and background oxidants, [OX]L and [OX]B, decreasing by 1.4% per year and 0.4% per year, respectively from 2000 to 2019. We also extend our study to three roadside sites (Din Daeng, Thonburi and Chokchai) in another megacity, Bangkok, to compare [OX]L and [OX]B and their behavioural changes with respect to the Marylebone Road site. [OX]L and [OX]B at the Marylebone Road site (0.21[NOx] and 32 ppbv) are comparable with the roadside sites of Thailand (0.12[NOx] to 0.26[NOx] and 29 to 32 ppbv). The seasonal variation of [OX]B levels displays a spring maximum for London, which is due to the higher northern hemispheric ozone baseline, but a maximum during the dry season is found for Bangkok which is likely due to regional-scale long-range transport from the Asian continent. The diurnal variations of [OX]L for both London and Bangkok roadside sites confirm the dominance of the oxidants from road transport emissions, which are found to be higher throughout the daytime. WRF-Chem-CRI model simulations of the distribution of [OX] showed that the model performed well for London background sites when predicting [OX] levels compared with the measured [OX] levels suggesting that the model is treating the chemistry of the oxidants correctly. However, there are large discrepancies for the model-measurement [OX] levels at the traffic site because of the difficulties in the modelling of [OX] at large road networks in megacities for the complex sub grid-scale dynamics that are taking place, both in terms of atmospheric processes and time-varying sources, such as traffic volumes. For roadside sites in Bangkok, the trend in changes of [OX] is predicted by the model correctly but overestimated in absolute magnitude. We suggest that this large deviation is likely to be due to discrepancies in the EDGAR emission inventory (emission overestimates) beyond the resolution of the model.