Processes controlling the exchange of ammonia between grassland and the atmosphere (GRAMINAE) Editor(s): K. Pilegaard, J. K. Schjoerring, and M. A. Sutton ; Deposition of atmospheric ammonia (NH3) to semi-natural ecosystems leads to serious adverse effects, such as acidification and eutrophication. A step in quantifying such effects is the measurement of NH3 fluxes over semi-natural and agricultural land. However, measurement of NH3 fluxes over vegetation in the vicinity of strong NH3 sources is challenging, since NH3 emissions are highly heterogeneous. Indeed, under such conditions, local advection errors may alter the measured fluxes. In this study, local advection errors (?Fz,adv) were estimated over a 14 ha grassland field, which was successively cut and fertilised, as part of the GRAMINAE integrated Braunschweig experiment. The magnitude of ?Fz,adv was determined up to 810 m downwind from farm buildings emitting between 6.2 and 9.9 kg NH3 day-1. The GRAMINAE experiment provided a unique opportunity to compare two methods of estimating ?Fz,adv: one inference method based on measurements of horizontal concentration gradients, and one based on inverse dispersion modelling with a two-dimensional model. Two sources of local advection were clearly identified: the farm NH3 emissions leading to positive ?Fz,adv ("bias towards emissions") and field NH3 emissions, which led to a negative ?Fz,adv ("bias towards deposition"). The local advection flux from the farm was in the range 0 to 27 ng NH3 m-2 s-1 at 610 m from the farm, whereas ?Fz,adv due to field emission was proportional to the local flux, and ranged between -209 and 13 ng NH3 m-2 s-1. The local advection flux ?Fz,adv was either positive or negative depending on the magnitude of these two contributions. The modelled and inferred advection errors agreed well. The inferred advection errors, relative to the vertical flux at 1 m height, were 52% on average, before the field was cut, and less than 2.1% when the field was fertilised. The variability of the advection errors in response to changes in micrometeorological conditions is also studied. The limits of the 2-D modelling approach are discussed.