Modelling the dynamic chemical interactions of atmospheric ammonia with leaf surface wetness in a managed grassland canopy

Ammonia exchange fluxes between grassland and the atmosphere were modelled on the basis of stomatal compensation points and leaf surface chemistry, and compared with measured fluxes during the GRAMINAE intensive measurement campaign in spring 2000 near Braunschweig, Germany. Leaf wetness and dew chemistry in grassland were measured together with ammonia fluxes and apoplastic NH4+ and H+ concentration, and the data were used to apply, validate and further develop an existing model of leaf surface chemistry and ammonia exchange. Foliar leaf wetness which is known to affect ammonia fluxes may be persistent after the end of rainfall, or sustained by recondensation of water vapour originating from the ground or leaf transpiration, so measured leaf wetness values were included in the model. pH and ammonium concentrations of dew samples collected from grass were compared to modelled values.The measurement period was divided into three phases: a relatively wet phase followed by a dry phase in the first week before the grass was cut, and a second drier week after the cut. While the first two phases were mainly characterised by ammonia deposition and occasional short emission events, regular events of strong ammonia emissions were observed during the post-cut period. A single-layer resistance model including dynamic cuticular and stomatal exchange could describe the fluxes well before the cut, but after the cut the stomatal compensation points needed to numerically match measured fluxes were much higher than the ones measured by bioassays, suggesting another source of ammonia fluxes. Considerably better agreement both in the direction and the size range of fluxes were obtained when a second layer was introduced into the model, to account for the large additional ammonia source inherent in the leaf litter at the bottom of the grass canopy. Therefore, this was found to be a useful extension of the mechanistic dynamic chemistry model by keeping the advantage of requiring relatively little site-specific information.