The document discusses farm scale modeling of greenhouse gas emissions and mitigation strategies at Aarhus University, focusing on organic farming and intensive livestock systems. It highlights the challenges of accurately defining farm boundaries, managing complex interactions, and estimating emissions from various farm components, such as crops and livestock. The need for simplified models, good data, and a flexible approach to emissions accounting is emphasized to enhance understanding and management of carbon and nitrogen flows.

1. TATION
AARHUS
UNIVERSITY
Farm scale modelling of greenhouse gas emissions and mitigation
Professor Jørgen E. Olesen
1

2. AARHUS
UNIVERSITY
Activities
›DK projects: farm scale modelling of mitigation potentials for organic farmers, farm scale modelling of mitigation in intensive livestock and crop farms
›AnimalChange: farm scale modelling in Europe and developing countries of emissions, mitigation and adaptation
›South China (Kaiping): Carbon and nitrogen cycling in different traditional farming systems to estimate enviromental (and GHG) load
›Vietnam (completed): Emissions of greenhouse gases from various types of smallholder farmers (different ethnic groups)

3. AARHUS
UNIVERSITY
Carbon and nitrogen flows on farms
Feed
Livestock
Soil/crops
Manure Import (CO2, N2O)
Export in meat/milk
Treatment
(bioenergy, composting)
Emissions
(CH4, NH3, NO3, N2O)
Emissions
(CO2, NH3, NO3, N2O)
Fertiliser
(CO2, N2O) Emissions (CH4)
Agroecology
Feeding strategy and additives
Manure treatment
Landscape design

4. AARHUS
UNIVERSITY
The FarmGHG model (originally designed for European dairy farms)

5. AARHUS
UNIVERSITY
Data needed for modelling farm GHGs
›Imports of goods (and energy) to the farm (and to the household)
›Farm land allocations (permanent crops, arable crops, ponds, non- utilised area)
›Farm livestock (stocks and flows of animals)
›Crop management (crop type, timing of sowing/harvesting, fertilisation, crop protection)
›Livestock management (feeding, breeding, milking, slaughtering, timing)
›Crop and livestock production (yield) – if not modelled by the model

6. AARHUS
UNIVERSITY
Challenges of complex systems
Wide range of environmental
conditions giving a widely
different biogeochemical reactions
Defining system boundaries

7. AARHUS
UNIVERSITY
Challenges of complex systems
Wide range of crops and
livestock
Many inter-linkages on farm
in time and space

8. AARHUS
UNIVERSITY
Challenges of complex systems
Changing systems
structures and
boundaries

9. AARHUS
UNIVERSITY
Need for simplification
›Properly define farm (system) boundaries (e.g. by land, structures, buildings)
›Define main structures on the farm (crops, livestock, manure storages, ponds) and their interlinkages
›Get good data for imports and exports to/from the farm
›Focus on the main crops and animals on the farm and get data on their extent and management

10. AARHUS
UNIVERSITY
Estimating emissions
›Modelling flows of carbon and nitrogen
›Nitrogen inputs in fertilisers, manure and biological fixation
›Plant productivity
›Animal efficiency
›Animal waste management
›Modelling emissions of methane and nitrous oxide
›IPCC emission factor approach
›Biogeochemical models
›Modelling (changes in) carbon stocks
›Vegetation models
›Soil models (simple or complex)

11. AARHUS
UNIVERSITY
Data sources
›Remote sensing
›Land allocation
›Vegetation duration and development
›Farm surveys
›Trade in and out of the farm
›Crop area and management
›Livestock numbers and management
›Manure managment
›Monitoring
›Production at regional scale
›C and N flows at the landscape (rivers, non-agricultural land)
›Literature and controlled experiments

12. AARHUS
UNIVERSITY
Challenges and gaps
›Define farm system boundary (allow for changing boundaries)
›Develop flexible and modular tool for linking farm C and N flows
›Design simple protocol for quantifying stocks and flows of C and N between main farm components and the outside (standard, actual)
›Incorporate emission modelling (flexible tier) with C+N flows – sensitive to enviroment and management
›Allow for assessment of mitigation (and adaptation) options
›Issues:
›Accounting and verification of activity data in complex systems
›Uncertainty assessments
›We do not scientifically understand many of these complex systems