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Long-term monitoring stations for atmospheric pollutants are often equipped with low-resolution concentration samplers. In this study, we analyse the errors associated with using monthly average ammonia concentrations as input variables for bidirectional biosphere-atmosphere exchange models, which are commonly used to estimate dry deposition fluxes. Previous studies often failed to account for a potential correlation between ammonia exchange velocities and ambient concentrations. We formally derive the exact magnitude of these errors from statistical considerations and propose a correction scheme based on parallel measurements using high-frequency analysers. In case studies using both modelled and measured ammonia concentrations and micrometeorological drivers from sites with varying pollution levels, we were able to substantially reduce bias in the predicted ammonia fluxes. Neglecting to account for these errors can, in some cases, lead to significantly biased deposition estimates compared to using high-frequency instrumentation or corrected averaging strategies. Our study presents a first step towards a unified correction scheme for data from nation-wide air pollutant monitoring networks to be used in chemical transport and air quality models.

The hidden cost of using low-resolution concentration data in the estimation of NH3 dry deposition fluxes