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Dynamic NH 3 model

Dynamic NH 3 model. EMEP atmospheric dispersion model. Deposition estimates used in policymaking Needs emission estimates Europe-wide (50 x 50 km grid). High temporal resolution (3 hours). Work in progress. Animal. Animal housing. Storage. Field. The model. Sources: Housing.

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Dynamic NH 3 model

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  1. Dynamic NH3 model EMEP atmospheric dispersion model. Deposition estimates used in policymaking Needs emission estimates Europe-wide (50 x 50 km grid). High temporal resolution (3 hours). Work in progress.

  2. Animal Animal housing Storage Field The model • Sources: • Housing. • Storage. • Field. • Mass flow model: • Ammoniacal N. • Organic N. • Dry matter. • Water. • Hourly timestep

  3. NH3 H2O Animal housing Manure storage NH4+ Organic-N H2O Manure

  4. NH3 H2O Field application NH4+ Organic-N H2O Manure Soil NH4+ H2O

  5. Area of manure * Amount of NH4+ * Henry-factor Amount of water * Transport resistance NH3 emission

  6. Area of manure * Amount of NH4+ * Henry-factor. Amount of water * Transport resistance Animal house emission Number of animals Floor area per animal Number of animals Urea-N per animal Temperature Manure pH Number of animals Volume per animal Ventilation rate Housing factor

  7. Area of manure * Amount of NH4+ * Henry-factor. Amount of water * Transport resistance Animal house emission Number of animals Floor area per animal Number of animals Urea-N per animal Temperature Manure pH Number of animals Volume per animal Ventilation rate Housing factor = parameter

  8. Parameterisation & testing • Lots of data. • Lots of time. • (see presentation on later today). • Temporary parameterisation using Dk emissions. • Synthetic weather data.

  9. Ammonia emission (kg/day) 10 000 finishing pigs per 50 x 50km

  10. Inputs  • Meteorological e.g. • Daily temperature, rainfall, wind speed etc. • Structural (vary with location) e.g. • Number of animals. • Type of animal housing. • Operational (vary with time & location) e.g. • Housing dates and ventilation rates. • Manure application dates.  

  11. Structural input examples • For each animal type: • Animal numbers. • Ammoniacal-N and organic N excreted per animal. • Housing/storage type. • Dairy cattle.

  12. Animal numbers • EUROSTAT Farm Structural Survey: • Animal numbers by type. • Regularly updated. • Some data missing. • NitroEurope project

  13. Dairy cattle

  14. Nitrogen excretion • Use IPCC methodology: • Feed intake, faecal dry matter production. • Data: • Milk production per cow (FSS). • Assumptions: • Diet quality, growth, weight.

  15. Manure type • Housing type depends on farm size? • Small volumes – solid manure cheapest. • Large volumes – slurry cheapest. • Relate probability of slurry to farm size. • Use farm size (FSS) to estimate slurry/solid. • Example from Denmark

  16. Operational example - ventilation • Simple dynamic model. • Estimate livestock heat production. • CIGAR (2002) • Calculate ventilation necessary to maintain: • A target inside temperature (forced ventilation). • Maximum and minimum ventilation rates. • Heating. • Inside temperature 4C above ambient (free).

  17. Forced ventilation

  18. Conclusions (1) • Lack harmonised data at European scale. • But may be available at country scale. • Operational management affected by legislation. • Modelling • How accurate? • Useful for scenarios.

  19. Conclusions (2) • Data required for many purposes. • Ammonia, Greenhouse gasses, Nitrate leaching, Erosion. • Secondary PM formation. • EU project. • Data collection. • Modelling.

  20. Parameters - storage • Depth of storage. • Manure pH and temperature. • Organic N degradation coefficient. • Transport resistance.

  21. Parameters - field • Start/stop date for applications • Maximum application capacity. • Application rate. • Transport resistance constant. • Infiltration rate. • Duration of emission.

  22. Animal housing • Dirty floor area per animal. • Manure pH and temperature. • Transport resistance.

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