JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Uncertainty in agriculture
Adrian Leip
Joint Research Centre, Institute for Environment
and Sustainability, Climate Change Unit
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Quantitative Tier 1 uncertainty estimates
CATEGORYCOUNTRY Year TOTAL
4ACH4
4B CH4
4BN2O
4DN2O
4D1N2O
4D2N2O
4D3N2O
Austria 2003 5.5 0.3 0.7 0.6 0.7 0 0 0
Belgium 2003 8.1 1.2 0 0 7.2 0 0 0
Denmark 2003 6.8 0.5 1.3 0.8 1.6 0 0 0
Finland 2003 15.9 0.7 0.1 0.6 0 8.8 0 2.9
France 2002 22.1 2.3 1.4 0.3 20.9 0 0 0
Greece 2003 10.8 0.6 0.2 0.2 0 5.1 2.9 1.2
Ireland 2003 12.2 2.8 1.2 1 11.5 0 0 0
Italy 2001 2.5 0.7 0.4 0.8 0 0.5 0.4 0.7
Spain 2002 15.8 0.8 4.4 0.8 0 8 0.9 11.8
Sweden 2003 7.2 1.2 0.3 0.5 6.1 0 0 0
Netherlands 2003 6 0.5 0 0.3 0 1.3 0 3.1
UK 2002 17.9 0.5 0.1 0.9 17.6 0 0 0
% of total emissions
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
TOTAL 4A-CH4 4B-CH4 4B-N2O 4D-N2O
United Kingdom 17.9 103% 100% 100% 19%
France 22.1 105% 102% 101% 36%
Ireland 12.2 113% 102% 101% 38%
Spain 15.8 104% 98% 100% 38%
Sweden 6.9 103% 101% 101% 56%
Belgium 8.1 102% 101% 100% 59%
Netherlands 6 103% 100% 100% 86%
Greece 10.8 102% 100% 100% 89%
Finland 15.9 102% 100% 101% 94%
Italy 2.5 98% 99% 95% 96%
Austria 5.5 103% 100% 100% 102%
Denmark 6.8 104% 99% 100% 105%
xtot
xxtottotxtot EE
EUEUU
22
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
EC uncertainty in agriculture
Overall uncertainty estimates 5 % to 8 %.
Source category
Gas Emissions 2003
Share of EC emissions used
EC uncertainty
4A CH4 130748 99% 12%
4B CH4 61967 98% 17%
4C CH4 2205 75% 38%
4D CH4 -521 102% 127%
4F CH4 107 39% 54%
4B N2O 21873 78% 93%
4D N2O 197455 98% 84% - 195%
4F N2O 369 4% 54%
Total agriculture
all 414427 97% 44 – 83%
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Contribution of emission estimated with country-specific information to the total EC emission estimates for key sources in the agriculture sector.
CategoryEmissions
[Gg CO2-eq]Percentage
estimated with country-specific
approach
4.A.1: Cattle (CH4) 109814 58%
4.A.3: Sheep (CH4) 14665 73%
4.B.1: Cattle (CH4) 28982 19%
4.B.8: Swine (CH4) 30066 42%
4.B.12: Solid storage and dry lot (N2O) 20364 13%
4.D.1: Direct soil emissions (N2O) 100401 8%
4.D.2: Animal production (N2O) 28566 1%
4.D.3: Indirect emissions (N2O) 64473 53%
TOTAL 397332 34%
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
EU-uncertainty for agricultural soils[% of emissions, combined AD-EF]
total direct animal indirect
Austria 24
Belgium 252
Denmark 21 25-54 32 51-54
Finland 227 334
France 200
Germany 16 77 16
Greece 401 112 54
Ireland 105
Italy 32 102 54
Netherlands 61 206
Spain 380 112 906
Sweden 87
United Kingdom 424
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Uncertainty for N2O emissions from soils
→ How can bias be estimated (representativeness)
→ How does temporal variability translate into uncertainty?
→ How large is the impact of correlations
AD uncertainty
small compared with EF uncertainty
EF uncertainty: Spatial variability
high, driven by
climate, soil and morphological variations
cropping patterns, fertilizer mixEF uncertainty: Temporal variability
high, driven by
weather conditions
fluctuations in management, fertilizer mix, cropping changes
bias
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Jungkunst 2005
Reducing uncertainty:
STRATIFICATION
• Climate regions (freeze-thaw events/rewetting of dry soils)
• Effect of soil type (organic carbon, wetness)• Effect of type of N applied (mineral / organic)• Effect of crop type (classes)
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Mulligan, 2005: DNDC-Italy
… mean emission factor for mineral N fertiliser derived from the linear regression of the emission estimates plotted against non-volatilised N fertiliser: 0.83%
applied manure emission factor: 1%
Butterbach- Bahl and Werner, 2005: DNDC-Germany
… Fertilizer induced emissions, were only approx. 50% of total N2O emissions. If the latter figure is used, our estimates are approx. 1/3 lower than estimates based on the IPCC approach for Germany
Brown et al., 2002, 2005: DNDC-UK
DNDC-UK IPCC
Fertiliser 1 1.25
FYM 0.6 1.25
Slurry 1.7 1.25
Grazing 0.5 2
PROCESS-BASED MODELS
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
ADDITIVITY of fertilizers
→ in 40% of the cases the synchronous addition of
synthetic fertilizer and animal wastes lead to higher N2O
emissions by >10% than the sum of single EFs would
suggest
→ in 10% of the cases
the effect is >40%
→ only 12% of the cases
lead to an over-
estimation of N2O
emissions by >10%
CALCULATION OF N2O EMISSIONS FROM SEPARATE EFs FOR SYNTHETIC
FERTILIZER AND ANIMAL WASTES
CALCULATION OF N2O EMISSIONS FROM SEPARATE EFs FOR SYNTHETIC
FERTILIZER AND ANIMAL WASTES
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
FAO / IFA, 2001; Bouwman et al., 2002:
Global estimates of gaseous emissions of
NH3, NO and N2O from agricultural land
Factor class value for fertilizer type
• Ammonium bicarbonate, ammonium chloride, ammonium sulphate 0.6
• Calcium nitrate, potassium nitrate, sodium nitrate 2.6
• Calcium ammonium nitrate and combinations of AN and CaCO3 2.3
• Ammonium nitrate 3.0
• Urea and urine 1.9
• Urea-ammonium phosphate 3.2
• Mix of various fertilizers 3.4
• Ammonium phosphate and other NP fertilizers 3.8
• Anhydrous ammonia including aqueous ammonia 4.4
• Organic fertilizers 4.7
• Combinations of organic and synthetic fertilizers 5.9
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Correlations
dependencies, even if they exist, may not be important to
the assessment of uncertainties
When dependencies among inputs are judged to be of importance
(i) modelling the dependence explicitly;
(ii) stratifying or aggregating the source categories;
(iii) simulating correlation using restricted pairing methods;
(iv) use of resampling techniques in cases where multivariate datasets are
available;
(v) considering bounding or sensitivity cases.
ADs are regarded as generally uncorrelated in
time
EFs are regarded as generally correlated in
time
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Correlation: Disaggregation
→ The compensation effect reduces uncertainty when
adding source categories / countries of similar magnitude
SUM OF CATEGORIES
EF1 assumed correlated - lack of evidence to provide different default
values for various forms of N input does not imply that the error is the same for
all nitrogen input!
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Correlation in time
→ In time uncorrelated
sources result in highly
uncertain trends
If higher-Tier approaches (models) are used:- How should temporal
variability be treated?- Use response to ‘climate’
rather than ‘weather’ for process-based models
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
Spatial variability
FAO / IFA, 2001; Bouwman et al., 2002:
“… emissions induced by fertilizers amount to 0.9 Mt or approximately 0.8 % of current nitrogen fertilizer input.”
Reported total emissions relative to
fertilizer input. Organic soils are adjusted by 8 kg
N2O-N ha-1
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
lognormalmean
# of estimates
included
Range* ratio high/low
Global 0.9% 643 0.04% .... 15.43% 379
Regions of the world
America 1.2% 186 0.07% ... 15.93% 239
Europe 0.9% 352 0.04% ... 17.85% 505
Asia 0.3% 69 0.02% ... 3.16% 130
Other 1.3% 34 0.26% ... 7.38% 28
Individual countries
Germany 1.5% 147 0.05% ... 26.03% 537
UK 0.6% 130 0.02% ... 14.64% 844
Canada 2.1% 27 0.29% ... 19.08% 66
* based on log-normal distribution; ±2 SD
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
HYPOTHESIS 1:
Is the compensation effect in the uncertainty assessment
appropriately considered?
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
HYPOTHESIS 2:
As measurements programs alone will not
suffice to obtain stratified emission factors, future
N2O inventories must rely on models to reduce level
uncertainty.
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
HYPOTHESIS 3:
Temporal variability of N2O emissions from soils
leads to high trend uncertainty.
Care must be taken how to treat it.
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
HYPOTHESIS 4:
Direct EFs for emissions from synthetic fertilizer, manure, crop residues should be treated as uncorrelated in the
uncertainty assessment.
JRC/AL – Uncertainty Workshop, Helsinki 06/09/2005
THANK YOU FOR YOUR
ATTENTION !