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Excretion factors Task 2: In-depth analysis of methodologies for calculation and presentation Léon Šebek, 28 March 2014.

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Presentation on theme: "Excretion factors Task 2: In-depth analysis of methodologies for calculation and presentation Léon Šebek, 28 March 2014."— Presentation transcript:

1 Excretion factors Task 2: In-depth analysis of methodologies for calculation and presentation Léon Šebek, 28 March 2014

2 Aim of Task 2 For 10 selected EU-27 countries
Identify and analyse differences in methodologies Point out accuracy and reliability of the excretion coefficients in use Compare excretion coefficients

3 Countries under consideration
Denmark, Estonia, France, Germany, Ireland, Italy, The Netherlands, Poland, Spain and the United Kingdom

4 Different methodologies Methods for quantifying excretion coefficients for livestock
Direct measurements of manure in storage Direct excretion measurements with livestock Metabolic and mechanistic models Input-output measurements (balance method)

5 Accuracy and reliability
Balance method building blocks for N and P excretion coefficients (kg per animal per year) Level 1 Level 2 Level 3 Output Input Data origin Accuracy and reliability

6 Accuracy and reliability of excretion coefficients
Method used Measurements, models, defaults or expert judgement? Aggregation level: animal or country? Building block level? Data origin Statistical reference Update interval Comparing quality

7 Accuracy and reliability Quality of data origin
Statistical reference Update interval in years Over-all 1 2-5 5-10 >10 score Yes No 1 Measurements input-output Animal x 1Y1 Farm 1Y2 Region 1Y3 Country 1Y4 2 Modelling approach 2Y1 2Y2 X 2N1 2N2 3 Measurements manure animal category 3N1 animal species 3N2 3N3 3N4 4 Defaults 4Y2 4Y3 common literature 4N2 country specific information 4N3 5 Expert judgement 5Y3 5Y4 5N3

8 Accuracy and reliability building blocks of balance method
Data origin

9 Accuracy and reliability Quality of data origin
Building block Country DK Fr Ger Irl It NL UK Esp P Est N intake 1Y1 2Y1 2Y2 2Y3 5N4 5N1 N deposition 5N3 Feed intake 1Y3 4N3 5Y1 Feed composition Animal production 3Y1 Animal composition 4Y1 4Y2 Method used B SFOM1 IPCC 1) SFOM: A tool for simulating quantity and quality of organic fertilizers produced at the farm. Jadczyszyn, e.a., 2000. Building block Country DK Fr Ger Irl It NL UK Esp P Est N intake +++ ++ + --- - N deposition -- Feed intake +/- Feed composition Animal production Animal composition Total Method used B SFOM IPCC

10 Conclusions methods, accuracy and reliability Estimating N and P excretion coefficients at national level Best method available: balance method Accuracy and reliability is strongly affected by quality of data origin Data preferably from well documented origin, regular updates and with respect to all building blocks of the balance method For the 8 out of 10 selected countries: sufficient accuracy and reliability to make direct comparisons

11 Comparing excretion coefficients Animal categorization
National total N and P excretions animal numbers x average excretion per animal (kg/year) Different species and different animal categories Large differences in categorization between countries Categorization based on husbandry systems Data collection based on local categorization Uniform categorization Farm System Survey or Livestock registers Possible loss of quality of data origin

12 N excretion coefficients cattle for some selected countries (kg/animal/year)
Category France2 Germany2 Netherlands2 Poland1 Dairy Milk (kg/yr) weight (kg) 136.7 >5000 105.6 86.7 6000 114.5 7000 125.2 119.3 8000 133.0 9000 144.9 >10.000 160.4 Beef 0-440 29.0 30-640 37.3 32.3 22.8 45-625 35.3 45-700 40.1 1) Not balance method, but system based on mineral excretion by manure. 2) Different excretion coefficients related to well defined different diets

13 N excretion coefficients pigs for some selected countries (kg/animal/year)
Category Denmark France3 Germany4 Ireland Spain Average present sow incl. piglets to weaning 26.41 20.4 – 24.6 20.1 20.44 Average present sow incl. piglets up to the grower period 34.9–37.3 26.22 Weaned piglets 0.532 0.56–0.622 3.3 – 3.4 6.5 1.71 Growing–finishing pig 3.12 3.8–4.62 10.96 7.69 1) Based on a performance level of 26.0 weaned piglets (7.3 kg) per sow per year. 2) Animal basis 3) First value is based on a 2-phase feeding system; the second value is based on a standard feeding system. 4) Based on a performance level of 22.0 weaned piglets (28 kg) per sow per year. The first value is based on N/P low diets, the second value is based on standard diets. 5) Based on growth rate of 800 g/d. 6) Range of 25 – 100 kg BW.

14 N excretion coefficients poultry for some selected countries (kg/animal/year)
Category Denmark France Germany1 Italy UK Broiler chickens, 30 days 0.317 Broiler chickens, 32 days 0.346 Broiler chickens, 35 days 0.395 Broiler chickens, 40 days 0.478 0.36 0.429 Broiler chickens, 45 days 0.563 0.0512 Barn-reared chickens, 56 days1 0.351 0.0682 Broiler chickens organic, 81 days1 0.508 0.1252 Laying hens, free-range 0.875 0.703 0.830 Laying hens, organic 1.010 0.718 Laying hens, barn-reared 0.864 Laying hens, cages 0.684 0.713 0.754 0.720 1) The first value is based on N/P low diets, the second value is based on standard diets. 2) On an animal basis. 3) Variation due to different strains.

15 Conclusions comparison of countries Estimating N and P excretion coefficients at national level
Observed differences between countries largely due to regional differences Animal husbandry systems Animal categorization Uniform animal categorization Clarity in what is compared Possible negative effect on data quality when uniform categorization differs significantly from local categorization

16 National N and P excretion proposal for a common method for EU-27
Uniform animal categories Country specific defaults per uniform animal category Based on calculations with balance method for regional animal categories Translate regional category defaults to uniform category defaults Check national excretion Update of defaults in short intervals (1-3 years)

17 Thank you for your attention!
Discussion


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