1. Monte Carlo Simulation Applied to Finnish Inventory Uncertainty
September 5, 2005
Helsinki

2. The model Suvi Monni is the principal developer of current approach
Now used and developed by Statistics Finland
Extensive documentation is available
Monni, Syri & Savolainen (2004) in Environmental Science and Policy 7(2), 87-99
Monni (2004) VTT Working Papers 5
Monni & Syri (2003) VTT Research Notes 2209
Reports available at
Teemu Oinonen

3. How the model “works” Transformation of random quantities
(emission factors, activity data, etc.)
(emission trend, level, etc.)
y = gi (x) x1 y1 x2 y2 : : . . xJ yK
Approximate mean and covariance can be calculated by analytic methods, but things get
complicated for large number of xj’s, especially when dependencies exist between them
Teemu Oinonen

4. Complexity of the input Random quantities xj and their correlations
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5. The Monte Carlo approach Approximate mean and covariance via random sampling
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6. Uncertainty of the emissions level
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7. 2003 level sensitivity - top 5 factors
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8. 2003 level sensitivity The effect of fixing the value of carbon stock change (5A1)
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9. Trend sensitivity - top 5 factors
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10. Trend sensitivity Scatter plot of carbon stock change in 1990 (5A1) vs
Trend sensitivity Scatter plot of carbon stock change in 1990 (5A1) vs. trend
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11. Conclusions
Model developed by VTT is now used and maintained by Statistics Finland
Further development is done as needed, e.g. to incorporate changes in inventory preparation
Uncertainties are quantified for every submission
Sensitivity analysis is used to guide inventory improvement
Teemu Oinonen