Modelling Seasonal Dynamics from Temporal Variation in Agricultural Practices in the UK Ammonia Emission Inventory |
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Authors: | S Hellsten U Dragosits C J Place T H Misselbrook Y S Tang M A Sutton |
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Institution: | (1) Centre for Ecology and Hydrology Edinburgh, Bush Estate, Edinburgh, Scotland, EH26 0QB, UK;(2) Institute of Geography, The University of Edinburgh, Drummond Street, Edinburgh, EH8 9XP, UK;(3) IVL Swedish Environmental Research Institute Ltd, P.O. Box 5302, 400 14 Gothenburg, Sweden;(4) Institute of Grassland and Environmental Research, North Wyke, Okehampton, Exeter, EX 2SB, UK |
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Abstract: | Most ammonia (NH3) emission inventories have been calculated on an annual basis and do not take into account the seasonal variability of emissions
that occur as a consequence of climate and agricultural practices that change throughout the year. When used as input to atmospheric
transport models to simulate concentration fields, these models therefore fail to capture seasonal variations in ammonia concentration
and dry and wet deposition. In this study, seasonal NH3 emissions from agriculture were modelled on a monthly basis for the year 2000, by incorporating temporal aspects of farming
practice. These monthly emissions were then spatially distributed using the AENEID model (Atmospheric Emissions for National
Environmental Impacts Determination). The monthly model took the temporal variation in the magnitude of the ammonia emissions,
as well as the fine scale (1-km) spatial variation of those temporal changes into account to provide improved outputs at 5-km
resolution. The resulting NH3 emission maps showed a strong seasonal emission pattern, with the highest emissions during springtime (March and April) and
the lowest emissions during summer (May to July). This emission pattern was mainly influenced by whether cattle were outside
grazing or housed and by the application of manures and fertilizers to the land. When the modelled emissions were compared
with measured NH3 concentrations, the comparison suggested that the modelled emission trend corresponds fairly well with the seasonal trend
in the measurements. The remaining discrepancies point to the need to develop functional parametrisations of the interactions
with climatic seasonal variation. |
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Keywords: | ammonia emissions GIS modelling seasonal dynamics temporal resolution |
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