Title: Riku Suutari, Markus Amann, Janusz Cofala, Zbigniew Klimont Wolfgang Sch
1Riku Suutari, Markus Amann, Janusz Cofala,
Zbigniew Klimont Wolfgang Schöpp
A methodology to propagate uncertainties through
the RAINS scenario calculations A study
funded by the UK Department of Environment, Food
and Rural Affairs
2Uncertainty analysis through error propagation
Emission model
Dispersion model
Critical load model
Transfer matrices
Regional emissions
Critical load functions
Protection isolines
Deposition estimate
Environmental impact
3Assumed uncertainties in input parametersCoeffici
ents of variation
SO2 NOx NH3
Activity rates 1990 2010 0.06-0.200.12-0.30 0.06-0.200.12-0.30 0.05-0.50 0.10-1.00
Emission factors 0.05-0.10 0.075-0.15 0.15-0.40
Removal efficiencies 0.005-0.05 0.015-0.10 0.05-0.15
Atmospheric transfer coefficients 0.10-0.15
Critical loads CLmax 0.22 0.12 0.12
4Uncertainties of intermediate results95
confidence intervals
SO2 NOx NH3
Emissions 13 13 15
Deposition 14-17
Critical loads excess(area of protected ecosystems) -5 - 2.5 -5 - 2.5 -5 - 2.5
5Probability for protecting ecosystems Gothenburg
Protocol 2010
6Conclusions General
- A methodology for uncertainty treatment is now
available, but conclusions are still incomplete
and preliminary - Quantifications of uncertainties are the most
uncertain elements in uncertainty analyses - Correlations and distributions difficult to
quantify - Uncertainties only for specific model output, but
not for general model
7Conclusions Uncertainties in the RAINS model
chain
- The potential for error compensation determines
uncertainties of emission and deposition
estimates - Spread of ecosystems sensitivity determines
uncertainties in ecosystems protection - Uncertainties in ecosystems protection are
smaller than many uncertainties of input
parameters - Uncertainties are determined by data availability
and can be influenced by model design - Overall largest uncertainties due to sub-grid
deposition and limited data about critical loads
8ConclusionsUncertainty results in a policy
context
- Do these type of conclusions (quantified
uncertainties) help the decision makers? - Implications for target setting! Is a new
approach required? - Error propagation useful for scenario analysis
- For optimization different approach (robustness!)
necessary