Chemical mechanism reduction is common practice in combustion research for accelerating numerical simulations, however there have been limited applications in atmospheric chemistry. In this study, we employ a powerful reduction method in order to produce a skeletal mechanism of an atmospheric chemistry code that is commonly used in air quality and climate modelling. The skeletal mechanism is developed using input data from a model scenario, and its performance is evaluated both a priori against the model scenario results, but also posteriori by implementing the skeletal mechanism in a chemistry-transport model namely the Weather Research and Forecasting code with Chemistry. Preliminary results, indicate a substantial increase in computational speedup for both cases, with a minimal loss of accuracy with regards to the spatio-temporal mixing ratio of the target species, which was selected to be ozone.