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Context: Diffusion of species on the dust surface is a key process fordetermining the chemical composition of interstellar ices. On the dust surface,adsorbed species diffuse from one potential well to another and react withother adsorbed reactants, resulting in the formation of simple and complexmolecules. Aims: We study the impact on the abundances of the species simulatedby the chemical codes by considering the uncertainties in the diffusion energyof adsorbed species. We aim to limit the uncertainties in the abundances ascalculated by chemical codes by identifying the surface species that result ina larger error because of the uncertainties in their diffusion energy. Methods:We ran various cases with 2000 to 10000 simulations in each case and varied thediffusion energies of some or all surface species randomly. We calculatedPearson correlation coefficients between the abundances and the ratio ofdiffusion to binding energy of adsorbed species. We identified the species thatintroduce maximum uncertainty in the ice and gas-phase abundances. With thesespecies we ran three sets, with 2000 simulations in each, to quantify theuncertainties they introduce. Results: We present the abundances of variousmolecules in the gas phase and also on the dust surface at different timeintervals during the simulation. We show which species produce a largeuncertainty in the abundances. We sorted species into different groups inaccordance with their importance in propagating uncertainty in the chemicalnetwork. Conclusions: We show that CO, H$_2$, O, N, and CH$_3$ are the keyspecies for uncertainties in the abundances, while CH$_2$, HCO, S and O$_2$come next, followed by NO, HS, and CH. We also show that by limiting theuncertainties in the ratio of diffusion to binding energy of these species, wecan eliminate the uncertainties in the gas-phase abundances of almost all thespecies.

Statistical study of uncertainties in the diffusion rate of species on interstellar ice and its impact on chemical model predictions