1 / 35

A collation of ammonia research

A collation of ammonia research. Identifying significant gaps and uncertainties in UK ammonia EF. J Webb (ADAS), TH Misselbrook (IGER), Prof. U. D ä mmgen, B Eurich-Menden (FAL), D. Starmans (WUR), RW Sneath (SRI) and R Harrison (Ex-ADAS, now Lincoln University, NZ). Background.

magnar
Download Presentation

A collation of ammonia research

An Image/Link below is provided (as is) to download presentation Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author. Content is provided to you AS IS for your information and personal use only. Download presentation by click this link. While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server. During download, if you can't get a presentation, the file might be deleted by the publisher.

E N D

Presentation Transcript


  1. A collation of ammonia research Identifying significant gaps and uncertainties in UK ammonia EF J Webb (ADAS), TH Misselbrook (IGER), Prof. U. Dämmgen, B Eurich-Menden (FAL), D. Starmans (WUR), RW Sneath (SRI) and R Harrison (Ex-ADAS, now Lincoln University, NZ).

  2. Background • To develop effective policies to reduce gaseous emissions, it is essential to prepare accurate inventories of emission sources and their size • two major sources of UK NH3 are livestock buildings and following land spreading of manures, which each account for c. 35% of livestock emissions

  3. Background • However, while emissions following land spreading of slurry were characterized by c. 25 datasets, there were no data from emissions from some types of housing, e.g. beef suckler cows • therefore a need to identify and review gaps in emissions data used to compile the UKAEI and NARSES

  4. Background • Data needed for all significant sources • obtained over the full range of activity of each source • taken under a representative range of environmental conditions • abatement techniques need to have been tested under the range of conditions over which they may be applied.

  5. Objectives • Identify sources for which we have no data • assess the accuracy of our estimate of NH3 emissions from all sources • assess whether data obtained in other European countries can be used to fill gaps • estimate the likely cost of any further studies

  6. 1 Itemize inventory sources • Data used to calculate EFs for both UKAEI and NARSES identified and itemised • NARSES housing emissions calculated for each livestock class in the June Census (22) • for only 10 of these categories have NH3 emissions been measured • for others an EF was derived from a similar class of livestock

  7. UK census data

  8. 1 Itemize inventory sources

  9. 2 Collate data used to create EF for each source • The emission derived from each UKAEI EF was totaled • for each EF derived from more than 1 value, a standard deviation, coefficient of variation (CV), and standard error (SE) were derived. • the SE was expressed as a percentage of the mean for standardized comparison

  10. 2 Collate data used to create EF for each source

  11. 3 Identify gaps where no data exist • These NARSES categories, each estimated to emit > 2.0 x 103 t NH3-N per year: • Buildings housing beef suckler cows and heifers on straw (5.41 x 103 t) • Spreading sheep FYM (2.34 x 103 t) • Buildings housing male turkeys (2.22 x 103 t; 3.40 x 103 t including female turkeys) • Upland sheep grazing (2.05 x 103 t)

  12. 3 Assess significance of gaps in EFs - prioritise filling those gaps • Record range and SE of data and hence range of emissions • Estimate data needed for an emission estimate of ±20% • Prioritise areas of either new or additional research

  13. Generating confidence intervals for EFs Largest 10 sources:

  14. Generating confidence intervals for EFs Worst 5 CI as % mean:

  15. 4 Prioritise areas of either new or additional research • Expressing the CI as a % of the mean emission may be misleading when attempting to assess priorities • may over-emphasize importance of small sources • simple ‘uncertainty’ ranking (UR) was used based on the size of emission, % SE and % CI

  16. 4 Uncertainty ranking

  17. 4 Greatest uncertainties • Fattening pigs housed on straw (45) • dairy slurry lagoons (32) • beef cattle grazing (24) • lowland sheep grazing (18) • beef slurry lagoons (16) • dairy slurry storage in tanks (16) • dairy cows and heifers housed on straw (12) • upland sheep grazing (12)

  18. 5 Priorities for research • Based on uncertainties in EFs and gaps in data these are: • buildings housing fattening pigs and dairy cows and heifers on straw • cattle slurry lagoons • a project is due to report measurements of these • grazing by beef cattle, upland and lowland sheep

  19. 6 Assess usefulness of data obtained in other countries • 6.1 Examine the EU IPPC Reference (BREF) Notes for information on emissions for the pig and poultry sector • 6.2 Collate non-UK data available in English-language publications

  20. Usefulness of BREF documentation • Large list of pig/poultry housing types with EF or expected reductions • No indication of robustness of EFs • References cited difficult to follow/obtain • EF for ‘reference’ systems differ from UK EFs (kg per bird place per year): • BREF UK • layers in cages deep-pit 0.386 0.290 • layer in cages, belt removal 0.035 0.117 • broilers, deep litter 0.080 0.043 • Therefore, difficult to ‘read-across’ for alternative housing systems • Source data most likely covered in review in this project (Appendix 3) • Useful source of potential abatement strategies for scenario testing, but would want to use UK-specific data

  21. 6 Collate non-UK data available in English-language publications • Most data are for sources for which the UK EFs are reasonably robust • in most cases little information available on the environmental or management conditions • difficult to assess the transferability to UK conditions

  22. 6 Collate non-UK data available in English-language publications • Little or no work from outside the UK on the priorities • straw-based housing systems, pastures grazed by beef cattle or sheep or from slurry lagoons • results were available of assessment of the abatement potential of reduced-emissions slurry applicators and rapid incorporation of slurries to arable land

  23. 7 Assess usefulness of data obtained in other countries • Collate non-UK data available in German and Dutch. • record farming practices and environmental conditions under which data collected. • filter out data not applicable to UK. • evaluate usefulness of remainder

  24. 7 Collate non-UK data available in German and Dutch • Again, little information on most areas of uncertainty • data from Germany on pigs housed on FYM • very little background information with respect to • N excretion by the livestock, animal age or weight, temperature or time of year when the measurements were made or of the litter characteristics

  25. 7 Collate non-UK data - comparison of Inventory EFs • EFs for buildings housing livestock on slurry similar • unlike UK, the EF for cattle housed on straw is the same or greater than that for cattle on slurry • some big differences in storage EFs • especially for FYM, which we may be underestimating • UK and German EFs following manure spreading are similar

  26. 8 Abatement • Among the most cost-effective abatement techniques identified for UK conditions are application of slurry by reduced-emission applicators • trailing hose (TH) • trailing shoe (TS) • open-slot injection (SlI)

  27. Trailing hose - % abatement

  28. Trailing shoe - % abatement

  29. Slot Injection - % abatement

  30. Rapid incorporation of slurry into arable land by tillage • Very little UK data • work from NL • only one result for ploughing (more for disc and tine) • only March, April and September • Around 22% of cattle and 54% of pig slurry are applied to arable land, mainly in late summer to stubbles prior to cultivation

  31. Priorities for work • Abatement % appear robust for TH and TS • work needed at field-scale for slot injection • rapid incorporation of slurries into arable land a potentially cost-effective means of reducing NH3 emissions. • data needed from experiments comparing several incorporation techniques in the UK

  32. Generating confidence intervals for EFs Propagate range in raw data? @RISK simulations – Latin hypercube sampling Probability Monte Carlo sampling EF value

  33. Generating confidence intervals for EFs Latin hypercube sampling Cumulative probability EF value 3,000 iterations

  34. Manure management stage Total emission t x 103 CI as % mean NARSES UK_Inv Buildings 70.4 70.2 71 Hard standings 18.9 20.3 52 Storage 11.6 11.9 82 Spreading 85.6 81.4 81 Grazing/outdoor 23.3 22.4 92 TOTAL 209.8 206.2 41 Uncertainties within inventory total (NARSES) (excluding fertilizers) 2001 activity data

More Related