A combined Lagrangian stochastic model with micro mixing and chemical sub-models is used to investigate a reactive
plume of nitrogen oxides (NOx) released into a turbulent grid flow doped with ozone (O3). Sensitivities to the model input
parameters are explored for high NOx model scenarios. A wind tunnel experiment is used to provide the simulation conditions for
the first case study where photolysis reactions are not included and the main uncertainties occur in the parameters defining the
turbulence scales, the source size and the reaction rate of NO (nitric oxide) with O3. Using nominal values of the parameters from
previous studies, the model gives a good representation of the radial profile of the conserved scalar [NOx] compared to the
experiments, although the width of the simulated profile is slightly smaller, especially at longer distances from the source. For this
scenario, the Lagrangian velocity structure function coefficient has the largest impact on simulated [NOx] profiles. At the next stage
photolysis reactions are included in a chemical scheme consisting of eight reactions between species NO, O, O3 and NO2. The high
dimensional model representation (HMDR) method is used to investigate the effects of uncertainties in the various model inputs
resulting from the parameterisation of important physical and chemical processes in the reactive plume model, on the simulation of
primary and secondary chemical species concentrations. Both independent and interactive effects of the parameters are studied. In
total 22 parameters are assumed to be uncertain, among them the turbulence parameters, temperature dependant rate parameters,
photolysis rates, temperature, fraction of NO in total NOx at the source and background concentration of O3. Only uncertainties in
the mixing time scale coefficient and the structure function coefficient are responsible for the variance in the [NOx] radial profile.
On the other hand, the variance in the [O3] profile is caused by parameters describing both physical and chemical processes
