Algorithm for estimating the crop height effect on ammonia emission from slurry applied to cereal fields and grassland

Ammonia (NH$_{3})$ emission following the application of livestock slurry to agricultural land is a significant source of atmospheric NH$_{3}$, and not only poses a risk to the environment through eutrophication and acidification of sensitive ecosystems, but may also result in a loss of plant-available nitrogen (N). The band-spread slurry application technologies of trailing hose and trailing shoe have been shown to reduce NH$_{3}$ emissions and consequently to increase plant uptake of slurry-applied N. There is a need to improve the precision in calculating the reduction in NH$_{3}$ emission nationally and at farm level, and this may be achieved through the development of algorithms that more accurately estimate NH$_{3}$ emission and also support the assessment of fertilizer efficiency of slurry that is band-applied to crops. Therefore, this study reviewed studies of NH$_{3}$ emission from slurry band applied with a trailing hose or shoe with the objective of developing an algorithm for calculating the reduction efficiency of the band application technique in relation to crop height. The developed algorithm predicted that for slurry applications to cereal crops, the reduction efficiency would increase by slightly less than 1% for every 1 cm increase in crop height. For slurry application to grassland, the reduction efficiency was predicted to increase by approximately 5% for every 1 cm increase in sward height. The developed algorithm was used in combination with the ALFAM model, which predicts NH$_{3}$ emission from slurry applications to bare soil, to provide monthly coefficients for estimating NH$_{3}$ emission from slurry applied to bare soil, cereal crops and grassland for Denmark and Southern England. Inclusion of the crop height algorithm in the emission factor derivation predicted, for example, a decrease in the emission factor for cattle slurry application by trailing hose to winter wheat from c. 25% to c. 15% of applied ammoniacal N for applications in January and May, respectively. While the algorithm developed in this study would benefit from wider validation, should more published data become available, the present paper demonstrates its potential value as an educational tool for farmers and advisers in developing more sustainable manure management strategies and for inclusion in emission factor calculations for national inventories to both improve the temporal distribution of emissions from slurry application and to better reflect improved management practices of farmers