1. Agriculture: Links between water and air IEAs
Martin Adams
Judith Bates
AEA Technology Environment
European Topic Centre on Air and Climate Change (ETC/ACC)

2. Introduction
Framework for agricultural baseline scenario development and modelling
Existing datagaps & main additional information sources
Links/relevance of IA for ETC-WTR assessment
Common definition of agricultural sector for water and air?
Immediate drivers/uses of ETC-ACC IA:
CAFÉ (EU15 + AC+ Switz. for 2010, 2015, 2020)
EEA State of the Environment report 2004
projection for the EU monitoring mechanism (2010 & 2020)

3. IA: Agricultural sector
Agriculture is important driving force for pressures on air and water pollution.
Main emissions (non-energy) comprise NH3, CH4 and N2O.
Main driving forces:
increases in fertiliser use & livestock numbers /density
Leading to:
higher manure loadings and ammonia emissions;
nutrient surpluses, NO3- leaching and higher atmospheric N deposition.
Policy drivers:
general level of agricultural activity
CAP reform: trend toward better nutrient budgets
Nitrate directive - trend towards driving fertiliser use down

4. Base-line scenario development
Two part approach used:
Part A: Determine agricultural activity data; (incorporates scenario runs e.g. CAP reform).
Part B: Application of data in emissions models
IIASA RAINS model for NH3
AEAT model for CH4 and N2O
Unable to find current single model with adequate:
geographical scope
temporal scope
resolution (detail)
Two part approach:
1) models - influence of transitions
2) apply e.f’s (IPCC etc)

5. Part A: Future activity data - CAPRI
Common Agricultural Policy Regional Impact
activity-level based (ca. 50), farm & market balances, unit value prices, policy variables (regional and EU-level: tariffs, quotas etc).
Detailed: Includes all agric. inputs and outputs according to national accounts definition.
Allows modelling of agri-environment policy measures.
Developed under 4th framework programme (led by Uni of Bonn)
Allows analysis of regional impacts of CAP on prodn, income, markets and the environment
Currently being updated and improved under CAP-STRAT project.
First stage of model calculated nutrient balances and certain emission sources. Emission sources not to be included in update

6. CAPRI continued.
Reference run and strategic scenarios due in 2004 (future CAP scenarios - DG AGRI).
Regarded as future (EU15) model of choice:
Disaggregated output: analysis broken down from EU to national and to regional levels by activity.
Short timescale available (10 yr horizon)
Coverage of AC not included
Updated baseline output not yet available    

7. Part B: Emissions modelling - RAINS
Regional Air Pollution INformation and Simulation
Reduction strategies & costs for SO2, NOx, VOCs and NH3 emissions and impacts on acidification and eutrophication.
NH3 module source data:
based on historical national stats (FAOSTAT & IFA),
projection forecasts compiled by IIASA based on ECAM and EFMA data
IFA - International Fertiliser Org)
ECAM - European Community Agric Model)
EFMA - European Fertiliser Manufacturers Association
Original Scenarios reviewed during UNECE Gothenburg Protocol negotiations

8. Part B: Emissions modelling - AEAT
CH4 & N2O emissions for EU15: 1990 and 2010.
Emissions based on IPCC inventory guidelines using national activity data and emission factors.
Source data:
livestock numbers from EUROSTAT and DG AGRI ‘Prospects for Agricultural Markets’
N fertiliser use: FAOSTAT and EFMA
crop production from FAOSTAT, forecasts from EFMA

9. Data Gaps & Issues
CAPRI: no activity data on % inorganic N fertiliser use which is urea (EFMA, IFA, FAOSTAT)
CAPRI reference base-line includes exogenous variables: e.g. GDP/capita, population. Should be consistent with other IA work.
Coverage:
CAPRI: EU15 + NO to 2010 only
IIASA Rains: All countries to 2010 (extension to 2020)
AEAT: EU15 to 2010 (extension to CEE/NIS & 2020)
Average N loss from urea estimated to be significantly higher than for other fertilisers. Main coutnbries Itals, Hungary, Spain, Eastern Europe   

10. Issues continued ETC/ACC: Secondary IA: need data from several models:
initial IA for EU15 to 2010
secondary IA for EU15 + AC & 2010 to 2020
Secondary IA: need data from several models:
major inconsistencies in assumptions and policy drivers (involve CAPRI team)
large regional models (e.g. IMAGE) lack resolution & data on country trading etc.
Current ETC/ACC work often driven by what data is available and when.

11. Common ground for ETC/ACC and WTR?
Regard use of same agricultural scenarios (i.e. at least Part A) as sensible:
consistency
transparency
CAPRI output reviewed to assess usefulness for ETC/WTR?
Investigate potential links to RAINS and AEAT models (both ‘nutrient surplus’ based).