Abstract
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.
Highlights
Gaseous ammonia (NH3) plays an important role in the atmosphere as part of the natural and anthropogenic N cycle and contributes to a number of adverse effects on the environment and public health[1]
If they are properly validated against flux measurements in different ecosystems, they can be applied for regional estimates of NH3 dry deposition using only concentration measurements and a small number of meteorological variables as input data[6,7,8,9,10]
These models are usually ran on a 30 minute basis, in accordance with the typical temporal resolution of flux measurements, or on an hourly basis within some large-scale chemistry transport models (CTM), such as LOTOS-EUROS11,12
Summary
Gaseous ammonia (NH3) plays an important role in the atmosphere as part of the natural and anthropogenic N cycle and contributes to a number of adverse effects on the environment and public health[1]. Recent developments allow the direct quantification of NH3 dry deposition and emission fluxes via the eddy-covariance method[2,3,4]; the necessary instrumentation is costly, long-term continuous studies are yet to be published, and the method is not trivially applicable in every environment Alternative methods, such as the aerodynamic gradient technique, are even more labour-intensive, usually require expensive wet-chemical analyses, and are prone to errors in non-ideal conditions[5]. If they are properly validated against flux measurements in different ecosystems, they can be applied for regional estimates of NH3 dry deposition using only concentration measurements and a small number of (micro-) meteorological variables as input data[6,7,8,9,10] These models are usually ran on a 30 minute basis, in accordance with the typical temporal resolution of flux measurements, or on an hourly basis within some large-scale chemistry transport models (CTM), such as LOTOS-EUROS11,12. Our study lays the groundwork for the characterisation of errors and estimation of site-specific correction functions when using NH3 dry deposition models with low-resolution input data
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