Current approaches for capturing the effect of diet management on - - PowerPoint PPT Presentation

CEDERS 2017-2020

1 Cecile de Klein, Arjan Jonker, Tony van der Weerden, Ronaldo Vibart; 2 André

Bannink, Leon Sebek; 3 Alireza Bayat, Jouni Nousiainen; 4 Les Crompton; 5 Maguy Eugène, Katja Klump, Etienne Mathias, Anais Durand; 6 Steen Gyldenkærne, Peter Lund; 7 Dieter Haenel, Björn Kuhla; 8 Pekka Huhtanen, Johanna Wallsten;

9 Dominika Krol, Bernard Hyde, Gary Lanigan; 10 Francisco Salazar, Marta Alfaro

Current approaches for capturing the effect of diet management on GHG emissions from ruminant systems

1New Zealand, AgResearch Limited; 2The Netherlands, Wageningen University & Research; 3Finland,

Natural Resources Institute; 4UK, University of Reading; 5France, French National Institute for Agricultural Research and CITEPA, 6Denmark, Aarhus University; 7Germany, Leibniz Institute for Farm Animal Biology and Thünen Institute of Climate-Smart Agriculture; 8Sweden, Swedish University of Agricultural Sciences; 9Ireland, Teagasc and Environmental Protection Agency; 10Chile, INIA

CEDERS 2017-2020

Expected outcomes of work package 4

National GHG inventory models and on-farm accounting tools have been updated to better capture the effect of diet management on GHG emission from ruminant systems

• Updated relationships between diet characteristics and GHGs
• New approaches adopted (from other countries or other models)

First step: understand how these models currently capture diet effects

CEDERS 2017-2020

Approach

Review of inventory models from all partner countries Review of a range of on-farm accounting tools Key assessment criteria:

• Activity data requirements (animal and feed characteristics)
• How animal energy requirements and intake are assessed
• How emissions from manure and excreta are calculated
• Which diet characteristics are captured

CEDERS 2017-2020

Partner countries

Sweden Finland Ireland UK Nether- lands Germany France Denmark Chile New Zealand

CEDERS 2017-2020

Results – Three generic approaches

Three generic approaches for estimating methane and nitrous oxide emissions from livestock systems: 1. Per animal:

• Methane emission factors per head of animal
• Nitrous oxide emission factors per head of animal

Feed characteristic captured: not applicable

CEDERS 2017-2020

2. Based on animal population characteristics and production: Estimates energy requirements, dry matter intake and N excretion

• Methane emission per unit of dry matter intake
• Nitrous oxide emission per unit of N excreted

Key feed characteristic: energy and nitrogen contents of diet

CEDERS 2017-2020

Animal population characteristics (by animal class) Milk and meat production (by animal class) Metabolisable energy (ME) requirements (MJ) (by animal class) Metabolisable energy (ME) content in the diet MJ ME/kg DM CH4 emission factor (by animal class)

X

Enteric CH4 emissions (by animal class)

X

Nitrogen (N) content in dry matter Total N intake N in products

Using methodology based on Australian feeding standard X X X Direct N2O emissions from animal excreta N2O emission factorurine N2O emission factordung Nin urine Nin dung Nin effluent /manure N2O emission Factorseffluent/manure

Total N excretion Total dry matter intake (by animal class)

EXAMPLE: New Zealand inventory model

CEDERS 2017-2020

3. Mechanistic approach to estimate net H+ production

• Methane
• Nitrous oxide emissions generally estimated as approach 2,

but feed digestibility is used for estimating N in urine and dung Feed characteristics: energy, sugar, starch, NDF, CP, NH3, fat, ash and nitrogen content and feed digestibility

H+ sources H+ sinks Excess H+ Methane out Feed in Rumen

CEDERS 2017-2020

Country Animal Population Animal production and population Mechanistic approach

Chile Other livestock Cattle

n/a

Denmark

n/a

Cattle

n/a

Finland Other livestock Cattle, sheep and reindeer

n/a

France Other livestock Cattle

n/a

Germany Sheep, goats, horses Other cattle and swine Dairy cows Ireland Other livestock Cattle

n/a

Netherlands Sheep, goats All other cattle Lactating cows New Zealand Goats, swine, horses Cattle, Sheep, Deer

n/a

Sweden Other livestock Cattle

n/a

UK Other livestock

n/a

Cattle, sheep

n/a = not applicable

Summary of Inventory approaches for enteric CH4

CEDERS 2017-2020

Cool Farm Tool Farm Carbon Calculator

On-farm accounting models – early results

Farm Carbon Footprint Calculator DairyWise OMINEA SYKE FASSET FarmAC RothC / RR Landscape model The CLA CALM Calculator The Carbon Navigator BEEFGEM UP-Green-LCA

CEDERS 2017-2020

Country Animal Population Animal production and population Mechanistic approach

Denmark Fasset France FarmSIM Ireland C navigator BEEFGEM Netherlands Dairywise COWPOLL New Zealand Farm C-footprint calculator Overseer Whole farm model UK Cool farm tool SIMS dairy

On-farm accounting models – early results

CEDERS 2017-2020

In summary,

Energy and N content and digestibility are the feed characteristics most commonly captured The more detailed approach captures additional feed characteristics e.g. sugar, starch, NDF, CP, NH3, fat and ash content Opportunities for improvement of models:

• Moving towards more detailed approach
• Better relationships between feed characteristics and CH4

Results could help inform the data-base analysis

CEDERS 2017-2020

Acknowledgements

International funding bodies:

Denmark: Innovationsfonden Finland: Ministry of Agriculture and Forestry France: Agence National de la Recherche Germany: Bundesministerium für Ernährung und Landwirtschaft Ireland: TEAGASC and Department of Agriculture, food and the Marine Netherlands: Nederlandse Organisatie voor Wetenschappelijk Onderzoek New Zealand: Ministry for Primary Industries (also supporting Chile) Sweden: Forskningsrådet för Miljö, Areella Näringar och Samhällsbyggande United Kingdom: The Secretary of State for Environment, Food and Rural Affairs

This project is funded in the frame of the ERA-NET FACCE ERA-GAS. FACCE ERA-GAS has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 696356.