The oxidative capacity of the troposphere – primarily characterized by the burden of the most abundant and reactive of oxidants, the hydroxyl radical (OH) – determines the lifetime of many trace gases of importance to climate and human health, including air pollutants and the greenhouse gas methane. In the upper troposphere, there is large uncertainty in the oxidative capacity associated with the lightning NOx production, for which reported results range from 16-700 mol NO flash-1. I implemented a lightning parameterization which significantly improves the representation of lightning in one chemical transport and and showed that this parameterization should be more effective in any model. I combined the model simulations configured with this new lightning parameterization with the satellite observations of NO2 column to yield a better estimate of lightning NOx production over the continental US. In cities, urban OH controls the removal rate of primary pollutants and triggers the production of ozone. Interannual trends of OH in urban areas are not well documented or understood due to the short lifetime and high spatial heterogeneity of OH and of OH precursors. Here I synthesized a machine learning technique, satellite observations and simulations from a state-of-art chemical transport model to estimate OH trends between 2005 and 2014 in 49 North American cities. I described trends in the summertime OH with wide variation among different cities. The variation of OH is explained by the shift in chemical regime from one where additional NOx slows chemistry to one where additional NOx speeds chemistry over the years. The identification of chemical regime, in turn, sheds light on the effective policy for controlling ozone.