input_allocation
Differences
This shows you the differences between two versions of the page.
Both sides previous revisionPrevious revisionNext revision | Previous revisionLast revisionBoth sides next revision | ||
input_allocation [2020/02/25 09:57] – [Input allocation for labour] matsz | input_allocation [2020/03/31 08:24] – [Input allocation for young animals and the herd flow model] matsz | ||
---|---|---|---|
Line 43: | Line 43: | ||
**Figure 5: The cattle chain** | **Figure 5: The cattle chain** | ||
- | {{: | + | {{: |
Accordingly, | Accordingly, | ||
Line 105: | Line 105: | ||
|GROFYCOW| Numer of heifers raised to young cows| 235, | |GROFYCOW| Numer of heifers raised to young cows| 235, | ||
|HEIRLEVL| Activity level of the heifers raising process |235, | |HEIRLEVL| Activity level of the heifers raising process |235, | ||
+ | \\ Source: CAPRI Modelling System | ||
Line 115: | Line 116: | ||
|Bull fattening (BULF) |BULL: | |Bull fattening (BULF) |BULL: | ||
|Heifers fattening (HEIF)| HEIL: | |Heifers fattening (HEIF)| HEIL: | ||
+ | \\ Source: CAPRI Modelling System | ||
====Input allocation for feed==== | ====Input allocation for feed==== | ||
Line 146: | Line 148: | ||
Wide supports for the Gross Value Added of the fodder activities mirror the problem of finding good internal prices but also the dubious data quality both of fodder output as reported in statistics and the value attached to it in the EAA. The wide supports allow for negative Gross Value Added, which may certainly occur in certain years depending on realised yields. In order to exclude such estimation outcomes as far as possible an additional constraint is introduced: | Wide supports for the Gross Value Added of the fodder activities mirror the problem of finding good internal prices but also the dubious data quality both of fodder output as reported in statistics and the value attached to it in the EAA. The wide supports allow for negative Gross Value Added, which may certainly occur in certain years depending on realised yields. In order to exclude such estimation outcomes as far as possible an additional constraint is introduced: | ||
- | |||
- | FIXME | ||
\begin{equation} | \begin{equation} | ||
Line 190: | Line 190: | ||
| |FEDAGGR_ |aggregate to roughage, concentarte feed, etc|Defines feed aggregates from single bulks FEED| | | |FEDAGGR_ |aggregate to roughage, concentarte feed, etc|Defines feed aggregates from single bulks FEED| | ||
| |FeedAggrShare_ |Calculate share of feed aggregates (roughage, concentrates, | | |FeedAggrShare_ |Calculate share of feed aggregates (roughage, concentrates, | ||
- | | |MeanFeedTotal_ |Calculates total feed intake in DM per animal|Part of revised objective function| | + | | |MeanFeedTotal_ |Calculates total feed intake in DM per animal|Part of revised objective function| |
The four additional equations developed in the new feed allocation procedure are described in more detail in the following. | The four additional equations developed in the new feed allocation procedure are described in more detail in the following. | ||
Line 211: | Line 211: | ||
^FeedCons| | | | | | | | X | X | X | X | | | ^FeedCons| | | | | | | | X | X | X | X | | | ||
^FeedOth| | | | | X | X | X | | | | | X | | ^FeedOth| | | | | X | X | X | | | | | X | | ||
- | ^FeedTotal| | + | ^FeedTotal| |
__ FeedAggrShare_ __ | __ FeedAggrShare_ __ | ||
Line 235: | Line 235: | ||
{{: | {{: | ||
- | This part of the objective functions tries to minimize the difference between the requirements calculated from the feed input coefficients (v_animReq) and the expected (mean) requirements (p_animReq) coming from literature. Due to the weighting with number of animals (v_actLevl) and expected requirements (p_animReq) the optimal solution tends to distribute over or under supply of nutrients relatively even over all activities and regions. It has been decided to attach an exponent smaller one to these weights which strongly pulls them towards unity (see: [...] FIXME (doppelstern) | + | This part of the objective functions tries to minimize the difference between the requirements calculated from the feed input coefficients (v_animReq) and the expected (mean) requirements (p_animReq) coming from literature. Due to the weighting with number of animals (v_actLevl) and expected requirements (p_animReq) the optimal solution tends to distribute over or under supply of nutrients relatively even over all activities and regions. It has been decided to attach an exponent smaller one to these weights which strongly pulls them towards unity (see: [...] FIXME (section? |
__Deviation of sub regional total feed intake from regional average__ | __Deviation of sub regional total feed intake from regional average__ | ||
Line 273: | Line 273: | ||
^ SHGF | 6.3 | 5.8 | 7 | 0.155 | 0.14 | 0.17 | | ^ SHGF | 6.3 | 5.8 | 7 | 0.155 | 0.14 | 0.17 | | ||
^ HENS | 8 | 7.8 | 8.2 | 0.18 | 0.14 | ^ HENS | 8 | 7.8 | 8.2 | 0.18 | 0.14 | ||
- | ^ POUF | 8 | 7.8 | 8.2 | 0.18 | 0.14 | 0.2 | | + | ^ POUF | 8 | 7.8 | 8.2 | 0.18 | 0.14 | 0.2 | \\ |
__Shares of feed aggregates in total feed intake in DRMA __ | __Shares of feed aggregates in total feed intake in DRMA __ | ||
Line 301: | Line 301: | ||
^ SHGF | | 0.3 | | 0.05 | | ^ SHGF | | 0.3 | | 0.05 | | ||
^ HENS | | | | 0.99 | | ^ HENS | | | | 0.99 | | ||
- | ^ POUF | | | | 0.99 | | + | ^ POUF | | | | 0.99 | \\ Source: own compilation |
For „other feed“ there are no lower bounds but rather low upper bounds: 10% for adult cattle, 5% for calves and sheep, 1% for pigs and 1E-6 (so near zero) for poultry. | For „other feed“ there are no lower bounds but rather low upper bounds: 10% for adult cattle, 5% for calves and sheep, 1% for pigs and 1E-6 (so near zero) for poultry. | ||
Line 376: | Line 376: | ||
| | | |Nitrogen in ammonia, NOx, N2O and runoff losses from mineral fertiliser| | | | | |Nitrogen in ammonia, NOx, N2O and runoff losses from mineral fertiliser| | ||
| **TOTAL INPUT** | | **TOTAL INPUT** | ||
- | | | | | **Nutrient losses at soil level (SURPLUS)** | + | | | | | **Nutrient losses at soil level (SURPLUS)** |
The difference between nutrient inputs and outputs corresponds to the soil surplus. For nitrates the leaching is calculated as a fraction of the soil surplus, which is based on estimates from the MITERRA project, and depends on the soil type, the land use (grassland or cropland), the precipitation surplus, the average temperature and the carbon content in soils. For details see Velthof et al. 2007 “Development and application of the integrated nitrogen model MITERRA-EUROPE”. Alternatively, | The difference between nutrient inputs and outputs corresponds to the soil surplus. For nitrates the leaching is calculated as a fraction of the soil surplus, which is based on estimates from the MITERRA project, and depends on the soil type, the land use (grassland or cropland), the precipitation surplus, the average temperature and the carbon content in soils. For details see Velthof et al. 2007 “Development and application of the integrated nitrogen model MITERRA-EUROPE”. Alternatively, | ||
Line 389: | Line 389: | ||
|**Cattle**| | |**Cattle**| | ||
|**Swine**| | |**Swine**| | ||
- | |**Poultry**| | + | |**Poultry**| |
- | Source:Lufa von Weser-Ems, Stand April 1990, Naehrstoffanfall. | + | |
These data are converted into typical pure nutrient emission at tail per day and kg live weight in order to apply them for the different type of animals. For cattle, it is assumed that one live stock unit (=500 kg) produces 18 m³ manure per year, so that the numbers in the table above are multiplied with 18 m³ and divided by (500 kg *365 days). | These data are converted into typical pure nutrient emission at tail per day and kg live weight in order to apply them for the different type of animals. For cattle, it is assumed that one live stock unit (=500 kg) produces 18 m³ manure per year, so that the numbers in the table above are multiplied with 18 m³ and divided by (500 kg *365 days). | ||
Line 409: | Line 408: | ||
|N|0.0084| | |N|0.0084| | ||
|P|0.004| | |P|0.004| | ||
- | |K|0.0047| | + | |K|0.0047| |
- | Source: RAUMIS Model [[http:// | + | FIXME |
The factors shown above for pigs are converted into a per day and live weight factor for sows by assuming a production of 5 m³ of manure per sow (200 kg sow) and 15 piglets at 10 kg over a period of 42 days. Consequently, | The factors shown above for pigs are converted into a per day and live weight factor for sows by assuming a production of 5 m³ of manure per sow (200 kg sow) and 15 piglets at 10 kg over a period of 42 days. Consequently, | ||
Line 493: | Line 492: | ||
**Figure 6. Ex-post calibration of NPK balances and the ammonia module** | **Figure 6. Ex-post calibration of NPK balances and the ammonia module** | ||
- | {{:: | + | {{:: |
The following equations comprise together the cross-entropy estimator for the NPK (Fnut=N, P or K) balancing problem. Firstly, the purchases (NETTRD) of anorganic fertiliser for the regions must add up to the given inorganic fertiliser purchases at Member State level: | The following equations comprise together the cross-entropy estimator for the NPK (Fnut=N, P or K) balancing problem. Firstly, the purchases (NETTRD) of anorganic fertiliser for the regions must add up to the given inorganic fertiliser purchases at Member State level: | ||
Line 607: | Line 606: | ||
**Figure 8: Carbon flows in the agricultural production process** | **Figure 8: Carbon flows in the agricultural production process** | ||
- | {{: | + | {{: |
- | Source: Weiss and Leip (2016) | + | |
In the following, we briefly describe the general methodology for the quantification of the carbon flows that are taken into account in the CAPRI approach. | In the following, we briefly describe the general methodology for the quantification of the carbon flows that are taken into account in the CAPRI approach. |
input_allocation.txt · Last modified: 2022/11/07 10:23 by 127.0.0.1