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The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

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Page 1: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

The robustness of the source receptor relationships used in GAINS

Hilde Fagerli, EMEP/MSC-W

EMEP/MSC-W

Page 2: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Outline

• Where do the uncertainties in S-R relationships come from and can they be validated?

• What main changes in the EMEP model have been done?

• How do these changes influence S-R relationships?

Page 3: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Where do the uncertainties in the S-R relationships come from ?

• Input data; Meteorology, Emissions (land and ship)

• Meteorological variability• Uncertainties in the chemical

transport model itself (chemical processes, dry and wet removal, transport).

Page 4: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

EMEP/MSC-W

• Very small effect of scale in meteorology

• Larger effect of redistribution of emissions

-in this case the lack of oil installations in the north sea in the TNO data

Page 5: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Where do the uncertainties in the S-R relationships come from ?

• Input data; Meteorology, Emissions (land and ship)

• Meteorological variability• Uncertainties in the chemical

transport model itself (chemical processes, dry and wet removal, transport).

Page 6: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

The S-R relationships themselves cannot be validated, but the model results can (in many cases)

• Validation of air concentrations and wet depositions

• Validation of trends (response to changes in the chemical climate)

• Some processes more uncertain than others:– E.g. dry deposition– Vertical mixing– Gas-particle partitioning, e.g. for nitrate-nitric

acid– SOA (not included)

Page 7: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Comparison of the EMEP model and other models – response to emission changes (EuroDelta II)

Spain: Potency of Spanish emission reductions of different compounds to population weighted PM2.5 in EU-25

0,00

0,05

0,10

0,15

0,20

0,25

Model 1 Model 2 Model 3 Model 4 Model 5

Po

p W

eig

hte

d n

gP

M2.

5/m

3/kt

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

NOx All: EU-25 SO2 All: EU-25 NH3: EU25 PPM All (RHS): EU-25

Comparison of the potency of emission reductions of NOx, SO2, NH3 and PPM from Spain, as calculated by the different models (Model 3=EMEP). Potency averaged over EU-25

Page 8: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

What changes have been done in the EMEP model (since the S-R used in GAINS) ?

• Nitrate chemistry• Meteorological driver• But there are other changes

coming..

..since the model is continuously improved!

Page 9: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Change 1. Update of the N2O5 hydrolysis

• Result: Less conversion of N2O5 to HNO3 and consequently less formation of nitrate aerosols (more NO2)

• Largest effect for countries with high NOx and NH3 emissions

Difference in total nitrate betweenversion with and without upgradednitrate formation, new- old (%)

Page 10: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Consequence for S-R matrices

• Consequence for S-R matrices:

More NO2, less HNO3, NO3

-. Somewhat more long-range transport of oxidized nitrogen

• PROBLEM: Nitrate is difficult!

16.213.8SE

2.32.3NL

1.10.7DK

17.515.4DE

3.22.7BE

OLD model (%)

NEW model (%)

Percentage of emissions from the country that is deposited within the country itself (OXN), 2005

Page 11: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Change 2. Change of meteorological driverfrom PARLAM-PS to HIRLAM

• Why? – More updated science in new HIRLAM

version– Increased model domain to include

EECCA countries

• Better performance in terms of spatial and temporal correlations, but more negative bias for SIA

Page 12: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Pollution export,example: export of SOx from GB

• Large terms rather robust• Transport over sea (e.g. UK to NO or SE) more

sensitive• ‘NWP Variability’ smaller or similar to met.

variability

Page 13: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Pollution import,example: import to Germany and Norway (PPM2.5)

The results are normalized to H50-2006

Germany Norway

Page 14: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Summary, change of NWP

• No systematic changes• For large countries the ‘NWP uncertainty’

is smaller than for small countries (met. average out changes)

• The relative uncertainty is larger for small contributions, whilst the results for large contributions are relatively robust

• In general; uncertainty smaller or comparable to met variability

Page 15: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Conclusions

• The 'accuracy' of the S-R relationship depends on both input data (e.g. emissions, meteorology) and the chemical transport model

• The most important changes in the EMEP model is the updated nitrate formation and the meteorological driver

• The update of the N2O5 hydrolysis has led to somewhat more long range transport of OXN

• The change of meteorological driver: Non-systematic. The large terms are relatively robust, but smaller terms are more uncertain

Page 16: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

The end

Page 17: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

To what extent can we trust the S-R relationships?

• Changes made in the EMEP model the last year

• How these changes influence S-R relationships

• Whether the EMEP workplan has influenced the SR matrices in use

Page 18: The robustness of the source receptor relationships used in GAINS Hilde Fagerli, EMEP/MSC-W EMEP/MSC-W

Norwegian Meteorological Institute met.no

Potency of Spanish emission reductions of different compounds in population weighted PM2.5 Concentrations in Spain

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0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

1,80

Model 1 Model 2 Model 3 Model 4 Model 5

Po

p W

eig

hte

d n

gP

M2.

5/m

3/kt

0,0

2,0

4,0

6,0

8,0

10,0

12,0

14,0

16,0

18,0

NOx All: Spain SO2 All: Spain NH3: Spain PPM All: Spain (RHS)

Same as above but with potencies averaged over Spain, the emitter country. Note that secondary y-axis refers to Primary Particulate Matter.