RAINS review 2004

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RAINS review 2004
The RAINS model Vegetation impacts of ozone
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Main issues

• Methodology for vegetation impact assessment
• Choice of impact indicator

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Concentration-based critical levels for
ozoneSource Mapping manual
Receptor Time period Critical level AOT30, ppm.h(only for IAM) Critical level AOT40, ppm.h
Agricultural crops 3 months 4 3
Horticultural crops 4 months - 5
Forest trees Growing season (6 months) 9 5
Semi-natural vegetation 3 months - 3
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Flux-based critical levels for ozoneSource
Mapping manual
Receptor Time period Critical level (AFst6)
Wheat 900 C days starting 200 C days before anthesis (flowering) 1 mmol/m2 projected sunlit leaf area
Potato 1130 C days starting at plant emergence 5 mmol/m2 projected sunlit leaf area
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Considerations for RAINS

• Critical levels for forests are most sensitive
• Use flux-based assessment for ex-post scenario
  analysis, concentrations-based CL for
  optimisation
• For trees, mapping manuals leaves a choice
  between AOT40 and AOT30
• Further analysis of advantages and disadvantages
  necessary

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Statistical indicators for AOT-based CLSource
Mapping manual
  Linear regression for birch and beech Linear regression for birch and beech Linear regression for birch and beech Linear regression for birch and beech Linear regression for birch and beech
r2 r2 p for the slope p for the slope p for the intercept slope
AOT30 AOT30 0.61 0.61 0.61 0.61 lt0.01 0.63 - 0.494
AOT40 AOT40 0.62 0.62 0.62 0.62 lt0.01 0.31 - 0.732
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Performance of Euro-Delta models AOT30 vs. AOT40
Ensemble model
EMEP model
r0.57
r0.65
r0.61
r0.48
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O3 changes calculated by Euro-Delta
modelsCLE-MFR, 9 German stations selected
AOT30
AOT40
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Response of ozone due to ?NOxfrom German
emissions
AOT30
AOT40
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Response of ozone due to ?NOxfrom German
emissions
AOT30
AOT40
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Response of ozone due to ?VOCfrom German
emissions
AOT30
AOT40
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Response of ozone due to ?VOCfrom German
emissions
AOT30
AOT40
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Summary of model performances
AOT30 AOT40
r2 of critical level estimates
for birch, beech 0.61 0.62
Correlation coefficient of ensemble dispersion models 0.65 0.61
Correlation coefficient of the EMEP model 0.57 0.48
Variability of model results for emission control scenarios ? ??
Linearity between CLE and MFR ? ??
???
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Further work

• Decide on metric for analysis
• Develop regional source-receptor (S-R)
  relationships for O3
• Investigate inter-annual meteorological
  variability
• Quantify uncertainties, explore use of
  ensemble-model
• Conduct uncertainty analysis for impact analysis