Nitric oxide formation in lean, methane-air stagnation flames at supra-atmospheric pressures

Abstract Increasingly stringent regulations are imposed on nitric oxide (NO) due to its numerous, direct and indirect, deleterious effects on human health and the environment. A better control of the post-flame temperature field to contain the thermal (Zel’dovich) route resulted in significant reductions of engine emissions. An improved knowledge of the chemistry and rate of the secondary prompt, NNH, and N 2 O pathways is now required to decrease nitric oxide emissions further. For this effort, NO laser-induced fluorescence (LIF) measurements are presented for lean ( ϕ = 0.7 ), jet-wall, stagnation, premixed flames at pressures of 2, 4, and 8 atm. For all cases, the NO-LIF signal increases rapidly through the flame front, and relatively slowly in the post-flame region where the temperature is too low to sustain the thermal pathway. Nitric oxide mole fractions are inferred from the measurements and show that the pressure has a very weak, monotonic, adverse effect on NO formation. Reaction pathway analyses are applied to flame simulations performed with a thermochemical model capturing the general trends of the data to assess the contribution of each NO formation route. For all cases, the N 2 O pathway, which proceeds mostly in the flame front region, dominates. This route produces slightly larger amounts of NO at higher pressures, but the variation appears very limited when considering the termolecular nature of its initiation reaction. The thermal route is predicted to progress slowly in the post-flame region, which causes a shallow increase in the NO mole fraction. The NNH and prompt pathways generate small amounts of NO, and their contributions reduce with the pressure. Overall, the thermochemical model predicts that the formation of NO is relatively unaffected by the pressure, which is consistent with the experiments. The experimental dataset reported in this work is made available for the development of thermochemical models.