The FARMnor Model Environmental assessment of Norwegian agriculture

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Section 1 : Identification sheet

Transcription:

The FARMnor Model Environmental assessment of Norwegian agriculture Thünen-Institute for Organic Farming Seite Molde 0

Aims of the modeling Calculate 20 Norwegian dairy farms Consistent calculation for Energy Greenhouse gases Nutrients (Nitrogen, Phosphorous, Potassium) Based on practical data Produce information for farmers & scientists Adapt calculation to needs of the project Seite 1

FARM model The model FARM (Flow Analysis and Resource Management) has been developed at the Thünen-Institute of Organic Farming. The model is based on the LCA and material flow analysis software Umberto 5.6 developed by ifu Hamburg GmbH. The focus of the modelling are on material flows on farm. Supply chains of products are modelled using datasets from ecoinvent 2.2 within the same modelling environment. The model is structured hierarchically. The entire life cycle from cradle to gate is the highest level. Each farm section builds one module in the second level which itself is further divided into sub-modules. Data entries are realized through MS Excel files containing parameters for the calculation. By changing parameters in the Excel file the calculation of material flows is controlled allowing for easy preparation of data. Seite 2

The dairy system a black box? Input Output -Energy -Fuel -Water -Fertilizer -Land -Seed -Cover foil -CO 2 Feed Production Feed Storage Animal Husbandry -Milk -Surplus calves -Animals for slaughter -Emissions (NH3, CH 4, N 2 O, CO 2 ) -Waste for disposal Seite 3

FARM Flow Analysis and Resource Management Seite 4

Cradle-to-gate Feed production Feed processing Animal husbandry Crop rotation element 1 Crop rotation element 2 Crop rotation element 3 Crop rotation element 4 Crop rotation element 5 Crop rotation element 6 Pasture Ensiling Drying Milling Calves Heifers Lactating cows Dry cows 1 n 1 n 1 n 1 n 1 n 1 n 1 n Feedi ng Milki ng Clean ing Seite 5

Mass flows in roughage production Feed Production Fertilizer Application - Fertilizer - Slurry BNF Products - Grazed grass - Roughage Volatile emissions Increase/ decrease of nutrients in soil Feed Slurry Seite 6

Feed Production Application - Fertilizer - Slurry BNF Products - Grazed grass - Roughage Volatile emissions Increase/ decrease of nutrients in soil IPCC factors Norwegian statistics Assumptions Seite 7

Seite 8

Seite 9

More questions (in between) Emissions from roughage production calculated from real flows. How do we get the data in? How do we know the nutrients content of the slurry? Can IPCC be used for individual farms? How do we get the data out? Seite 10

Getting farm data in Seite 11

Getting emission factors in Seite 12

Getting data out Seite 13

Seite 14

Methodological challenges Temporal system boundary Allocation Seite 15

Temporal system boundary Using the average of input data for 3 years Slurry Seite 16

Allocation options 100% Based on: 90% - Financial earnings 80% - N yield 70% - Energy yield 60% Excess feed - Mass yield 50% 40% 30% Metabolism Milk production Meat production Based - on: - hours/ machine hours 20% - Fodder costs 10% 0% Earnings Costs - Energy content in feed - DM content feed Seite 17 -

Advantage of allocation by costs Supports subdivision (Electricity for the milking machine) Seite 18

Allocation by FEm (3 FEm per kg liv. Increase) 100.00% 90.00% 17.3% 80.00% 70.00% 60.00% 50.00% 40.00% 82.7% 61.5% 77.8% 100.0% 55.0% 90.0% Rest Meat production 30.00% 20.00% 10.00% 0.00% 45.0% 38.5% 22.2% 0.0% 10.0% Suckling calves Youngstock Heifers Cows Bulls Total Seite 19

Conclusions Basing the GHG emission calculation / nutrient efficiency calculation on (the same) real flows allows for plausibility checks. Practical data as input data leads to realistic scenarios in sensitivity analysis. Special consideration has been made to facilitate result visualization. Seite 20

Discussion Based on this data set, what scenarios should we calculate? Individualized emission factors for each farm Numerical parameter variation for sensitivity analysis (Monte Carlo, Morris method) Reduction of concentrate in ration Seite 21