M. Amann, W. Asman, I. Bertok, J. Cofala, C. Heyes,
Z. Klimont, W. Schöpp, F. Wagner
Recent methodological changes
in the GAINS model
Meeting of the Task Force on Integrated Assessment Modelling
Prague, May 2-4, 2007
Recent methodological changes
• Update to the City-delta methodology
• RAINS cost curve-based optimization replaced by
GAINS measured-based optimization
• 5-years meteorological conditions
• EC4MACS work plan
Changes to the City-delta methodology
Changes since December 2006
• New population and city-domain data
(“compact” city shapes including ~70% of population)
• Target metric: population-weighted PM2.5 concentration for
health impact assessment
• Refined results from the three urban models
• Revised functional relationship
• Multi-year meteorology
• Modified assumptions on urban emissions
“Compact urban shape” for which the urban
increment is computed – Prague
Compact urban shapes for which the urban
increments are computed
Paris
London
Lisbon
Krakow
Milan
Berlin
Urban increments computed by the three models for
the 5*5 km center grid cell and population-weighted
12
Increment (microgram/m3)
10
8
6
4
2
0
Berlin
Krakow
Lisbon
5 km * 5 km
London
Milan
Population-weighted
Paris
Prague
Urban increments computed by Chimere, CAMx,
RCG, compared with the City-delta regression
14
12
microgram/m3
10
8
6
4
2
0
Berlin
Krakow
Lisbon
Chimere
London
CAMx
RCG
Milan
City-delta
Paris
Prague
Hypothesis of the City-delta functional relationship
D
D
d
c   
Q   
Q
U
U
365
Δc
… concentration increment computed with the 3 models
α. β … regression coefficients
D
… city diameter
U
… wind speed
Δq … change in emission fluxes
d
… number of winter days with low wind speed
ie
n
So
fia
Br
H no
el
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nk
i
Li
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l
e
Va To
le ul
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i
M enn
on e
tp s
el
Av lier
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g
M
ue non
n
N ch
ue en
rn
W be
up rg
pe
Bi rta
el l
e
C fel
he d
m
ni
Ka tz
ss
el
H
D al
or le
tm
un
M d
ila
G no
en
o
Ve va
Am ne
st zia
er
da
Le m
id
K en
By rak
dg ow
os
zc
z
C Por
on to
st
a
Lj nta
ub
l
Za jan
ra a
go
C za
or
St do
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kh
o
G lm
M en
an ev
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c
N hes
ot
t
e
tin
r
P gh
St orts am
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e- ou
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t
Ki So n-T h
ng ut
r
e
st ha nt
on m
up pto
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H
ul
l
W
kg PM2.5/person/yr
Urban per-capita emissions by SNAP sector
3.0
2.5
2.0
1.5
1.0
0.5
0.0
SNAP 2 (Domestic)
SNAP 3 (Idustry)
Snap 7 (Traffic)
SNAP 8 (Other mobile sources)
0
Urban increment (microgram PM2.5/m3)
Emission density (t/km2)
Kingston upon Hull
Southampton
Stoke-on-Trent
Portsmouth
Nottingham
Manchester
Geneve
Stockholm
Cordoba
Zaragoza
Ljubljana
Constanta
Porto
Bydgoszcz
Krakow
Leiden
Amsterdam
Venezia
Genova
Milano
Dortmund
Halle
Kassel
Chemnitz
Bielefeld
Wuppertal
Nuernberg
Muenchen
Avignon
Montpellier
Valenciennes
Toulon
Lille
Helsinki
Brno
Sofia
Wien
Emission densities (red) and
computed urban increments (blue)
30
25
20
15
10
5
Contribution of long-range transport (blue) and
local primary PM emissions (red) to urban PM2.5
35
30
AT
BE
Bulgaria
FI
France
20
15
10
5
Assumed mineral and sea salt
Urban increment
Brest
Angers
Dijon
Avignon
Bethune
Rennes
Saint-Etienne
Metz
Valenciennes
Grenoble
Lens
Nantes
Toulouse
Lille
Marseille
Turku
Helsinki
Arhus
Ostrava
Praha
Varna
Sofia
Gent
Bruxelles
Linz
0
Wien
microgram PM2.5/m3
25
Regional background
AIRBASE monitoring data for urban background 2004
Assumed mineral and sea salt
Urban increment
Porto
Lisboa
Netherlands NO Poland
Torun
Kielce
Radom
Czestochowa
Gdynia
Bialystok
Lublin
Bydgoszcz
Szczecin
Gdansk
Poznan
Wroclaw
Krakow
Lodz
Warszawa
Katowice
Bergen
Oslo
Groningen
Heerlen
Tilburg
Dordrecht
Leiden
Eindhoven
Utrecht
Gravenhage
Rotterdam
Amsterdam
Italy
Kaunas
Vilnius
Riga
Trieste
Padova
Messina
Verona
Venezia
Catania
Bari
Firenze
Bologna
Genova
Palermo
Torino
Napoli
Roma
Milano
microgram PM2.5/m3
Contribution of long-range transport (blue) and
local primary PM emissions (red) to urban PM2.5
35
PT
30
25
20
15
10
5
0
Regional background
AIRBASE monitoring data for urban background 2004
Contribution of long-range transport (blue) and
local primary PM emissions (red) to urban PM2.5
35
Germany
GR HU
30
20
15
10
5
Assumed mineral and sea salt
Urban increment
Debrecen
Thessaloniki
Dortmund
Wuerzburg
Zwickau
Magdeburg
Muenster
Halle
Osnabrueck
Kiel
Braunschweig
Reutlingen
Chemnitz
Moenchengladbach
Leipzig
Karlsruhe
Dresden
Wuppertal
Bonn
Hannover
Duesseldorf
Koeln
Muenchen
Stuttgart
0
Essen
microgram PM2.5/m3
25
Regional background
AIRBASE monitoring data for urban background 2004
Assumed mineral and sea salt
Urban increment
Plymouth
Kingston upon Hull
Barnsley
Gillingham
Luton
Derby
Aldershot
Blackpool
Preston
Southend-on-Sea
Swansea
Southampton
Birkenhead
Cardiff
Coventry
Belfast
Stoke-on-Trent
Middlesbrough
Reading
Bournemouth
Leicester
Portsmouth
Edinburgh
Brighton
Bristol
Sheffield
Nottingham
Liverpool
Newcastle-upon-Tyne
Glasgow
Leeds
Manchester
Birmingham
London
microgram PM2.5/m3
Contribution of long-range transport (blue) and
local primary PM emissions (red) to urban PM2.5
35
30
United Kingdom
25
20
15
10
5
0
Regional background
AIRBASE monitoring data for urban background 2004
Sectoral contributions to background concentrations
of primary PM2.5 components from urban sources
18
16
AT
BE
Bulgaria
FI
France
14
10
8
6
4
2
Domestic (SNAP 2)
Industry (SNAP3)
Traffic (SNAP7)
Non-road mobile (SNAP 8)
Brest
Angers
Dijon
Avignon
Bethune
Rennes
Saint-Etienne
Metz
Valenciennes
Grenoble
Lens
Nantes
Toulouse
Lille
Marseille
Turku
Helsinki
Arhus
Ostrava
Praha
Varna
Sofia
Gent
Bruxelles
Linz
0
Wien
microgram PM2.5/m3
12
Domestic (SNAP 2)
Industry (SNAP3)
Traffic (SNAP7)
Non-road mobile (SNAP 8)
Plymouth
Kingston upon Hull
Barnsley
Gillingham
Luton
Derby
Aldershot
Blackpool
Preston
Southend-on-Sea
Swansea
Southampton
Birkenhead
Cardiff
Coventry
Belfast
Stoke-on-Trent
Middlesbrough
Reading
Bournemouth
Leicester
16
Portsmouth
Edinburgh
Brighton
Bristol
Sheffield
Nottingham
Liverpool
Newcastle-upon-Tyne
Glasgow
Leeds
Manchester
Birmingham
London
microgram PM2.5/m3
Sectoral contributions to background concentrations
of primary PM2.5 components from urban sources
18
United Kingdom
14
12
10
8
6
4
2
0
Summary
• Substantial revisions of methodology and input data
• Health impact assessment based on population-weighted
increments – conservative assumption?
• Largest uncertainties associated with quality of urban
emission estimates. Large discrepancies cannot be readily
explained
• More plausible on emissions assumptions improve
estimates
• Validation hampered by lack of quality-controlled
monitoring data
• Sensitivity analysis explored implications on optimization
results
Mathematical formulation of the GAINS optimization
Comparison of cost curves
Examples for Germany and Greece
Germany, SO2, NEC_NAT,2020
800
1000
800
600
400
200
costs-RAINS
costs-GAINS
700
Total cost MEur/yr
costs-RAINS
costs-GAINS
1200
Total cost MEur/yr
600
500
400
300
200
100
340
390
0
660
440
Remaining Emissions kt/yr
1000
800
600
400
200
760
810
860
75
910
Greece, SO2, NEC_NAT,2020
Greece, NOx, NEC_NAT,2020
60
40
20
90
95
100
250
160
Total cost MEur/yr
80
85
Greece, PM2.5, NEC_NAT,2020
180
costs-RAINS
costs-GAINS
80
Remaining Emissions kt/yr
Remaining Emissions kt/yr
120
100
costs-RAINS
costs-GAINS
1200
0
710
costs-RAINS
costs-GAINS
140
Total cost MEur/yr
Total cost MEur/yr
1400
900
0
290
Total cost MEur/yr
Germany, PM2.5, NEC_NAT,2020
Germany, NOx, NEC_NAT,2020
1400
120
100
80
60
40
costs-RAINS
costs-GAINS
200
150
100
50
20
0
40
50
60
70
80
Remaining Emissions kt/yr
90
0
140
0
150
160
170
180
190
Remaining Emissions kt/yr
200
210
16
21
26
Remaining Emissions kt/yr
31
Multi-year meteorology
Multi-year meteorology
• Atmospheric dispersion based on meteorological conditions
of 1996, 1997, 1998, 2000, 2003
• Sensitivity analysis with 2003
5-yrs mean
2003
1997
Switzerland
Norway
Croatia
EU-25
EU-27
UK
Sweden
Spain
Slovenia
Slovakia
Romania
Portugal
Poland
Netherlands
Malta
Luxembourg
Lithuania
Latvia
Italy
Ireland
Hungary
Greece
Germany
France
Finland
Estonia
Denmark
Czech Rep.
Cyprus
Bulgaria
Belgium
Austria
Months
Loss in statistical life expectancy computed with different
meteorological conditions (for 2000)
14
12
10
8
6
4
2
0
5-yrs mean
2003
1997
Switzerland
Norway
Turkey
Croatia
EU-27
UK
Sweden
Spain
Slovenia
Slovakia
Romania
Portugal
Poland
Netherlands
Malta
Luxembourg
Lithuania
Latvia
Italy
Ireland
Hungary
Greece
Germany
France
Finland
Estonia
Denmark
Czech Rep.
Cyprus
Bulgaria
Belgium
Austria
Mortality cases in relation to 5-yrs mean
Estimates of mortality from ozone for year 2000 emissions for
different meteorological conditions
140%
130%
120%
110%
100%
90%
80%
70%
5-yrs mean
2003
1997
Switzerland
Norway
Turkey
Croatia
EU-25
EU-27
UK
Sweden
Spain
Slovenia
Slovakia
Romania
Portugal
Poland
Netherlands
Malta
Luxembourg
Lithuania
Latvia
Italy
Ireland
Hungary
Greece
Germany
France
Finland
Estonia
Denmark
Czech Rep.
Cyprus
Bulgaria
Belgium
Austria
km2 of ecosystems with acid deposition above critical loads
in relation to 1997
Estimates of unprotected forest area for year 2000 emissions
for different meteorological conditions
130%
120%
110%
100%
90%
80%
70%
60%
50%
5-yrs mean
2003
1997
Switzerland
Norway
Turkey
Croatia
EU-27
UK
Sweden
Spain
Slovenia
Slovakia
Romania
Portugal
Poland
Netherlands
Malta
Luxembourg
Lithuania
Latvia
Italy
Ireland
Hungary
Greece
Germany
France
Finland
Estonia
Denmark
Czech Rep.
Cyprus
Bulgaria
Belgium
Austria
km2 of ecosystems with nitrogen deposition above critical
loads in relation to 1997
Estimates of ecosystem area with excess nitrogen deposition
for year 2000 emissions for different meteorological conditions
120%
110%
100%
90%
80%
70%
60%
50%
Summary
• For EU-27, PM and ozone impacts from 5-yrs meteorology
very similar to 1997. Acidification ~10% higher,
eutrophication ~5% higher
• But different trends in different regions across Europe
• Implications on meaures
• 2003 produces higher health impacts for PM and ozone
EC4MACS
European Consortium for Modelling of Air
Pollution and Climate Strategies
Overview of the 5 years work plan
The EC4MACS model system
Global/
hemispheric
boundary
conditions
Agriculture
Atmosphere
Ecosystems
Costeffectiveness
Impacts
CAPRI
GEM-E3
Transport
Energy
European
policy drivers
TREMOVE
POLES
PRIMES
TM5
EMEP
CCE-IMPACTS
GAINS
BENEFITS
FASOM
General work plan
• 2007:
– Methodological improvements
• 2008:
– Data collection
– Feedbacks on methodological improvements
• 2009
– Interim assessment
– Methodology workshop
• 2010
– Uncertainty assessment
– Bilateral consultations on input data
• 2011
– Final assessment