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TFIAM meeting
27 May 2005 Berlin
EEA scenario 2005 project :
Low greenhouse gas emission pathways
Presentation by Hans Eerens
EEA Topic Centre Air and Climate Change
Netherlands Environmental Assessment Agency (MNP)
It is not most important to predict the future,
but to be prepared for it
Perikles (about 500-429 b. Chr.)
1. Introduction, methodology
2. Energy and GHG projections
3. Regional air quality, emission trend and
costs 2030
4. Urban background trend (PM10, NO2,
SOMO-35)
5. Street increment (PM10, NO2)
ETC/ACC partners and others involved:
• RIVM: IMAGE/TIMER/FAIR/EUROMOVE models, global
scenarios, climate effects, coordination
• NTUA: PRIMES/GEM-E3/PROMETHEUS models, European
energy system
• IIASA: RAINS model, European air quality
• DNMI: EMEP model
• AEAT: non-CO2 GHGs and non-energy CO2 emissions
• IPTS: POLES model, technology variants
• AUTH: OFIS, OSPM model, transport & urban Air Quality
• NILU: Air Pollution State & policies
• CCE: Air pollution effects on ecosystems/critical loads
• EEA: project guidance, links with issues other than air and
climate change
ETC/ACC SoEOR2005 subreport 6
Introduction
Objectives:
•Explore air pollution and climate change
trends and projections using 3 scenarios:
–Long-Range Energy Modelling (LREM)
–Low greenhouse gas Emission Pathways (LGEP)
–Plus variants
•Target assessment on possible use for EU’s
post-2012 debate
SoEOR2005: flow chart of models used
M
Economy
GEM-E3, PROMETHEUS
PRIMES
Transport
Agriculture
AEA-T
model
COPERT III,
TREMOVE,
TREND
RAINS
Emissions
CO2
(Europe)
CH4, N2O,
HFC, PFC,
MERLIN
SF6 (Europe)
CO2 Permit
EMEP
OFIS
Price
OPSM
POLES
TIMER
FAIR
Sinks
CO2, CH4,
N2O, HFC,
Regional concentration:SO2, NO,
NH3, PM, O3
Urban conc.
PM, NO2, O3
PFC, SF6
Energy Price
CC impacts
IMAGE
WaterGap
AQ impacts
Street
increments
Focus air pollution assessment:
• Emission/effects/costs change between 2020
and 2030 assuming:
–
–
–
–
–
No climate change policies
Increased climate change policies
Different economic growth path
High renewable/biomass ambition
Increase/decrease use of nuclear energy
Emission/activity due to various agricultural scenario’s:
– CAP reform
– Animlib (reduced border protection for pig & poultry,
dairy liberalization)
– Best environmental practice
Data availability and dissemination
•
•
•
•
•
SoEOR2005 report
SoEOR2005 sub reports
SoEOR2005 technical papers
Articles
SoEOR2005 Scenario information platform
(web-based application, indicator based
country specific information) including
maps
• presentations
LREM and LGEP emissions compared to SRES
scenarios
CO2eq conc (ppmv)
1300
1100
900
700
500
300
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
year
baseline
550mitigation
A1B
A2
B1
B2
Global development in energy use 1980-2100:
hydropower, non-thermal electricity, traditional biofuels, modern biofuels,
natural gas, oil and coal. Left baseline (1170 EJ by 2100), right LGEP (730
EJ by 2100)
Permit prices assumed
CAFE-KR
SEP
SEP-LE
Assumed permit price at EU-level1
Year
SEP
SEP-LE
Assumed global
permit price
Euro (2000)/ton CO2
2010
2015
2020
2025
2030
2040
2050
2075
2100
Low
6
8
10
10
10
medium
12
16
20
20
20
-
High
18
24
30
30
30
12
20
30
50
65
-
6
6
20
40
55
-
5
6
25
45
60
105
115
165
190
2
1
15
35
50
80
95
105
105
Projected global energy investment 2000-2050 Investments in
respectively energy savings, electricity, modern biofuels and fossil fuel.
Left baseline (4400 thousand million €/year by 2100), right LGEP (4600
thousand million €/year by 2100
Global energy investments LGEP 1990-2050
3000
3000
2500
2500
Billion (1995) $
2000
1500
1000
500
2000
1500
1000
500
0
0
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
fossil
modern biofuels
electricity
savings
19
90
19
94
19
98
20
02
20
06
20
10
20
14
20
18
20
22
20
26
20
30
20
34
20
38
20
42
20
46
20
50
Investment billion $(1995)
Global energy investments baseline 2000-2050
fossil
modern biofuels
electricity
savings
Past and projected prices of fossil fuels and
electricity 1970-2050
Fossil prices prices baseline and LCEP 1970-2050
Left axis oil prices per barrel, right axis gas and coal prices per GJ
48
8
45
7
40
Electricity-residential
Baseline
35
32
5
Baseline
24
4
Oil
3
16
Gas
Baseline
30
25
Coal
0
1980
1990
2000
year
2010
2020
2030
2040
15
10
1
5
0
0
1970
2050
Oil-transport
20
LCEP
8
1970
2
$(1995)/Gj
6
Prices $(1999)/GJ
$(1999)/barrel start of year
40
OECD End-use costs (including tax) 1971-2050
LCEP
Coal-industrial
Baseline
1980
1990
2000
2010
Year
2020
2030
2040
2050
GREENHOUSE GAS EMISSIONS
Kyoto:
FAIR: 6 Euro/ton CO2eq
PRIMES: 12 Euro/ton CO2eq
6000
Baseline
Kyoto
5000
LGEP (FAIR)
Domestic
action
LGEP (PRIMES)
Uncertainty range
CO2eq (Mton)
4000
non-domestic (trade)
3000
Commitment in LGEP
2000
Result LGEP climate policy scenario
EU-25
PRIMES FAIR
Range share
Commitment domestic domestic domestic
-20%
-10%
-8%
50-60%
-40%
-16%
-26%
50-70%
-57%
-48%
85%
-64%
-61%
95%
all numbers compared to 1990 (%)
1000
Year
2020
2030
2040
2050
0
1990
EU-25
Baseline
+4%
+8%
+9%
+7%
2000
2010
2020
2030
2040
2050
Avoided CO2 emissions
4500
Projected energy-related CO2 emissions (Mt)
4000
Avoidable "baseline"
emissions by sector:
3500
Transport
Services
3000
Households
2500
Industry
Energy Branch
2000
Electricity and Steam
production
Emissions LCEP
1500
1000
500
0
2000
2005
2010
2015
2020
2025
2030
Changes in the fuel mix of EU-25 gross inland energy
consumption compared to the baseline in 2030
Renewable energy forms
Nuclear
Natural gas
Oil
LCEP nuclear phase out
LCEP nuclear accelerated
Solids
LCEP renewables
LCEP
-100%
-75%
-50%
-25%
0%
25%
50%
75%
100%
Change in gross inland energy consumption compared to baseline (in 2030)
125%
150%
Further CO2 reductions are possible through enhanced
renewable deployment (meeting targets), while phasing out
nuclear risks increasing emissions if these plants are
replaced by fossil fuels
4500
4000
Transport
3500
Services
3000
MtCO2
Households
2500
Industry
2000
1500
Energy branch
1000
Electricity & Steam
production
500
0
1990
2000
2030 baseline
2030 - SEP
2030 - SEP
incr.
Renewables
2030 nuclear
phase-out
2030 - incr.
nuclear
300
300
Developed regions
Developing regions
250
Index (year 2000 = 100)
Index (year 2000 = 100)
250
200
200
150
150
100
100
50
50
0
0
baseline LGEP baseline LGEP baseline LGEP
NOx
SO2
NMVOC
2000
baseline LGEP
NOx
baseline LGEP baseline LGEP
SO2
NMVOC
2010 baseline
2020 baseline
2030 baseline
2050 baseline
2010 LGEP
2020 LGEP
2030 LGEP
2050 LGEP
Change in air pollutants emissions in developed and
developing regions under the baseline and LGEP scenarios
relative to year 2000
100
Index (year 2000 =100)
80
60
40
20
0
NOx
2000
SO2
2020 CAFE
NMVOC
2030 baseline
NH3
2030 LGEP
PM10
2030 LGEP-MFR
Change in emissions of air pollutants in the EU 25 region
relative to 2000
Identified anthropogenic contribution to modelled grid-average PM2.5
concentrations (annual mean, µg/m3) , 2000, 2020-CAFÉ, 2030-CC, 2030-CC-MFR
Percentage of total ecosystems area receiving nitrogen deposition above the critical
loads for the emissions of the year 2000 (top left panel), the current legislation for 2020
(top right), the LGEP in 2030 and the maximum feasible reduction case for 2030
(LGEP-B-MFR – bottom right panel).
Percentage of forest area receiving acid deposition above the critical
loads for the emissions of the year 2000 (top left panel), CAFE 2020 (top
right), LGEP (bottom left) and LGEP-MFR (bottom right panel).
1.Regional air quality and impacts
Loss in statistical life expectancy that can be attributed to the identified
anthropogenic contributions to PM2.5 (in months) for the emissions of
the year 2000 (top left panel), ‘CAFE 2020’ (top right), the “LGEP”
(bottom left) and the LGEP-MFR (bottom right) panel).
1.Regional air quality and impacts
Grid-average ozone concentrations in ppb.days expressed as SOMO35 for
the emissions of the year 2000 (top left panel), CAFE 2020 (top right), LGEP
(bottom left) and LGEP-MFR (bottom right panel).
Provisional estimates of premature mortality attributable to ozone
(cases of premature deaths per million inhabitants per year)
Percentage of total ecosystems area receiving nitrogen deposition
above the critical loads for eutrophication by country group and scenario
Country
2000
2020, CP
2030, SEP
Finland
Sweden
UK
Norway
0.7
14.9
8.1
28.6
CLE
0.7
10.5
3.7
19.3
MFR
0.2
5.2
1.3
9.1
B-CLE
0.7
10.9
3.8
19.9
LE-CLE
0.7
10.5
3.5
19.6
B-MFR
0.2
5.1
0.8
6.9
Switzerland
79.8
56.9
18.2
53.2
52.7
9.7
Average
22.6
15.4
7.3
15.8
15.5
5.9
Percentage of freshwater ecosystems area receiving acid deposition above the
critical loads for by scenario and country. Calculation results for the
meteorological conditions of 1997, using grid-average deposition. Critical loads
data base of 2004.
 Reductions in emissions compared with 2000:
NOx
NMVOC
SO2
NH3
PM10
PM2.5
Baseline 2030
-47%
-45%
-67%
- 6%
- 38%
- 46%
LGEP
- 52 %
- 45 %
- 73 %
-5%
- 45 %
- 51 %
LGEP-MFR
-75%
-62%
-87%
-43%
-67%
-73%
 2030:
• Loss of statistical life expectancy:
• Premature mortality due to ozone:
• Forest area at risk of acidification:
• Ecosystems’ area endangered by eutrophication
LGEP
- 44%
- 16 %
- 56%
- 15 %
LGEP-MFR
- 78%
- 51%
- 88%
- 82%
Table 8: Air pollutant emissions; baseline compared to CP and LGEP
EU25 emissions
air pollutant
SO2
NOx
VOC
NH3
PM10
PM2.5
kton
2000
8736
11581
10654
3824
2455
1748
LREM-E
2030
2851
6125
5863
3597
1512
937
2030, LGEP
B-CLE
LE-CLE SER-CLE
2371
2150
2342
5524
4972
5550
5877
5701
5912
3582
3573
3584
1357
1258
1344
860
790
857
B-MFR
1130
2849
4101
2174
817
468
% change
2030, LGEP
B-CLE
LE-CLE SER-CLE
-16,8
-24,6
-17,9
-9,8
-18,8
-9,4
0,2
-2,8
0,8
-0,4
-0,7
-0,4
-10,3
-16,8
-11,1
-8,2
-15,7
-8,5
B-MFR
-60,4
-53,5
-30,1
-39,6
-46,0
-50,1
Table Error! No text of specified style in document.-1: Total annual emissions (Kton) of
air pollutants from international shipping for the European sea region.
Pollutant
NOx
NMVOC
SO2
PM10
PM2.5
1990
2743
101
1874
171
162
2000
3501
131
2418
222
210
2010
SHIPBAU
4265
170
2652
270
255
2020
SHIPBAU
5207
219
3415
348
330
SHIPMFR
595
219
752
298
282
2030
SHIP- SHIPBAU MFR
6530
769
284
284
4406
972
450
385
426
364
Climate
change benefit
Emission control costs EU-25 billion Euro/year
The trend engine:
What is included?
• About 50 crop and animal products/activities, covering
agriculture according to the definition of Economic
Accounts
• Plus some major derived products (dairy, oils and cakes)
• Areas/herd sizes, yields, market balances, producer and
consumer prices, feed requirements …
• Time series from 1985 onwards, projected till 2030
• EU25 (minus Cyprus und Malta)
Table 4: Environmental indicators in the “best practice” scenario compared to the baseline run
in EU 23
Region : European Union
2001
2011
2015
2020
2025
Item : Environmental indicator per ha
(kg/ha)
Nitrogen
Potassium
Phosphate
Ammonium
Methane
Nitrous oxide
Reference run
42.64
42.4
42.14
41.66
41.12
Best practice
42.64
37.77
35.04
31.44
28.05
Reference run
31.44
29.54
29.12
28.52
28.01
Best practice
31.44
19.92
16.27
12.26
8.81
Reference run
15.89
14.44
14.02
13.42
12.8
Best practice
15.89
9.4
7.05
4.04
1.03
Reference run
19.45
19.68
19.87
20.04
20.21
Best practice
19.45
14.28
12.3
9.8
7.32
Reference run
48.82
47.52
47.78
48
48.31
Best practice
48.82
47.52
47.78
48
48.31
Reference run
2.98
3.07
3.11
3.16
3.21
Best practice
2.98
2.88
2.83
2.77
2.72
80% organic farming, full covered storage facilities, improved manure
handling in the stable. Better application techniques as injections are
assumed to reduce ammonia losses during application to 5% No changes
are assumed regarding the grazing practice
Urban background:
• 20 Cities (MERLIN project), 53 million
inhabitants
• EMEP regional background (1997)
• OFIS model urban background
• City specific fleet composition data
Results for NO2 annual average
80
observations
OFIS
EMEP
70
60
50
40
30
20
10
0
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO
LISB
LOND MARS MILA
PARI PRAG ROME STUT THES
Comparison EMEP/OFIS results NO2 annual average 2000
PRAG
80
100
2
R = 0.58
70
COPE
90
MARS
GDAN
80
60
LISB
HELS
70
50
OFIS model (μg/m3)
OFIS model results (μg/m 3)
BERL
40
30
ROME
60
BRUS
ANTW
50
GRAZ
THES
40
BUDA
30
LOND
20
MILA
20
10
ATHE
KATO
10
PARI
0
0
0
10
20
30
40
Observed (μg/m 3)
50
60
70
80
STUT
0
10
20
30
40
50
60
Observed (μg/m 3)
70
80
90
100
BARC
ra
z
nt
w
e
er
p
om
2000
Pa
ri
s
K
at
ow
ic
e
Lo
nd
on
M
il a
n
Br
us
se
l
A
R
G
Th dan
sk
es
sa
lo
ni
ki
M
ar
s
C
op eille
en
ha
ge
n
St
ut
ga
rt
H
el
sin
ki
Li
sb
on
Pr
ag
ue
Ba
rc
el
on
a
Be
rl
in
Bu
da
pe
st
A
th
en
s
G
NO2 (ug/m3)
Trend NO2 European cities 2000-2030
2030-CC
2030-CC-MFR
60
50
40
30
20
10
0
Annual average ozone concentration (ug/m3)
2030-CC-MFR
ila
n
2030-CC
M
2000
G
Th
ra
es
z
sa
lo
ni
ki
St
ut
ga
rt
Ba
rc
el
on
a
M
ar
se
i ll
e
Lo
nd
on
H
el
Co sin k
i
pe
nh
ag
en
A
nt
we
rp
Br
us
se
K
l
at
ow
ic
e
Li
sb
on
G
da
ns
k
Be
rli
n
Pa
ris
Pr
ag
u
Bu e
da
pe
st
A
th
en
s
Ro
m
e
somo-35 (ppb.days)
Trend somo-35 in European cities 2000-2030
Coverage:55 Million inhabitants 2030
9000
8000
7000
6000
5000
4000
3000
2000
1000
0
PM10 annual mean values
50
observations
OFIS
EMEP
40
30
20
10
0
ANTW ATHE BARC
BERL BRUS BUDA COPE GDAN GRAZ
HELS KATO
LISB
LOND MARS
MILA
PARI
PRAG ROME STUT
THES
Summary results 20 cities, 55
million inhabitants (2030)
NO2
Scenario
Population weighted average
PM10
O3 (SOMO35)
MIN AVE MAX EXC* MIN AVE MAX MIN AVE MAX
Reference year (2000)
13
37
51
5
8.2
16
30
1300 4890 8000
LGEP
7.7
24
32
0
5.3
10
16
2000 4950 7400
LGEPMFR
4.5
15
23
0
2.5
6
10
1500 4480 6600
two hypothetical street canyon configurations:
street 1:narrow canyon with a traffic volume of 20,000
vehicles per day
street 2:wide canyon with a traffic volume of 60,000 vehicles
per day
Orientation: East to West , centrally located, specific fleet
composition, average vehicle speed of 26 km/h
Average yearly wind speed considered per city
City
Wind speed (m/s)
City
Wind speed (m/s)
ANTW
3.10
KATO
2.62
ATHE
3.07
LISB
3.13
BARC
2.29
LOND
3.74
BERL
2.83
MARS
2.70
BRUS
3.06
MILA
1.66
BUDA
2.27
PARI
2.88
COPE
3.68
PRAG
2.63
GDAN
3.44
ROME
2.50
GRAZ
2.67
STUT
2.48
HELS
3.15
THES
1.90
Specific wind directions for each city
Wind direction Frequency for THES
Wind direction Frequency for STUT
N
NNW
12
N
NNE
NNW
15
NNE
10
NW
NE
8
NW
NE
10
6
WNW
4
ENE
WNW
E
W
ESE
WSW
ENE
5
2
W
0
WSW
SW
0
ESE
SW
SE
SSW
SE
SSW
SSE
SSE
S
S
Wind direction Frequency for ROME
Wind direction Frequency for LISB
N
NNW
10
N
NNW
NNE
8
NW
NE
NNE
NE
15
4
ENE
WNW
10
2
W
25
20
NW
6
WNW
E
ENE
5
0
WSW
SW
SE
SSW
SSE
S
E
W
ESE
WSW
0
E
ESE
SW
SE
SSW
SSE
S
55
measured
modelled
50
Concentration (μg/m 3)
45
40
35
30
25
20
15
10
5
0
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA
PARI PRAG ROME STUT THES
Mean annual NO2 street increments (μg/m3) in 20 European cities: OSPM
model results compared with observations
32
measured
30
modelled
28
Concentration (μg/m 3)
26
24
22
20
18
16
14
12
10
8
6
4
2
0
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA
PARI PRAG ROME STUT THES
Mean annual PM10 street increments (μg/m3) in 20 European cities:
OSPM model results compared with observations.
• PM10: range modelled street increment 516 μg/m3,(average10.3μg/m3).
• PM10: Average measured street
increment 11.1 μg/m3, (not including
exceptionally large street increment for
Lisbon).
• PM10, 16 station background-street pairs
(< 1km distance) from airbase: 6.9 μg/m3
• HDV% and average vehicle speed per day
most sensitive assumptions for street
emission calculations
basis reduction: discussions on Euro V and Euro VI held at EU level (European
Commission, 2004)
Reduction percentage of NOx emissions with respect to Euro IV (for PC and LDV) and to Euro V
(for HDV) for Euro V (for PC and LDV) and Euro VI (for HDV) compliant vehicles, according to the
four scenarios.
Package 1
Package 2
Package 3
Package 4
Package 5
PC - LDV Gasoline
-40%
-40%
PC - LDV Diesel
-20%
-20%
-40%
-20%
-40%
HDV
-50%
-85%
-85%
-85%
-85%
Reduction percentage of PM emissions with respect to Euro IV (for PC and LDV) and to
Euro V (for HDV) for Euro V (for PC and LDV) and Euro VI (for HDV) compliant vehicles,
according to the four scenarios.
PC - LDV Gasoline
Package 1
Package 2
Package 3
DPF (GDI)
PC - LDV Diesel
-50%
DPF
DPF
HDV
-0%
-0%
DPF
COPERT III,TRENDS and input traffic activity data originating from TREMOVE
(version 2.23 ).
Development of NOx emission factor (%) for the two scenarios in Germany (reference year:
2000)
NOx
emissonfactor
(%)
PC Gasoline
PC Diesel
LDV
HDV
Buses
2010
CLE
36
108
81
67
70
2015
MFR
36
108
81
67
70
CLE
22
105
74
46
44
2020
MFR
20
78
58
42
42
CLE
17
102
74
34
26
2025
MFR
13
54
45
25
21
CLE
16
98
79
32
22
2030
MFR
12
38
42
15
12
CLE
17
100
83
36
21
MFR
12
30
42
11
10
Development of PM emission factor (%) for the two scenarios in Germany (reference year:
2000)
2010
2015
2020
2025
2030
PM emission
factor (%)
CLE
MFR
CLE
MFR
CLE
MFR
CLE
MFR
CLE
MFR
PC Diesel
LDV
HDV
Buses
69
58
54
64
69
58
54
64
69
47
30
35
44
34
29
34
70
42
17
16
26
20
13
13
69
45
12
10
15
15
6
6
70
47
13
9
11
15
5
5
SCENARIOS FOR SOEOR2005:
CONCLUSIONS (II)
• LGEP
SEP does initiate changes, but does not yet (2030) requires a
fundamental “transition” in the European energy system.
• A sustainability transition meeting all EU’s climate and energy
targets appears to be feasible, but at significant costs (400
Euro/household/year in 2030); there is not one optimal solution > LGEP
SEP variants.
• Integrated CC&AP policies can result in cost savings, avoidance
of trade-offs, and effective abatement of air pollutant and GHG
emissions.
• A sustainability transition in Europe has to be viewed in a global
context.
• The costs for medium term GHG emissions reductions are
significant dependent on the assumed economic growth, as
shown by a lower economic growth variant.
While a transition such as LGEP can bring
enormous benefits, it also presents substantial
challenges
• Benefits
 Decoupling of CO2 emissions from economic growth and reduced European
contribution to global climate change
 Reduced emissions of air pollutants
 Reduced energy import dependency (-20%)
 Employment in industrial and agricultural sectors selling biofuels and clean
and low energy technologies to Europe and the world
• Challenges
 Large changes required in the energy sector
 Difficult choices over controversial technologies such as nuclear power and
carbon capture and storage
 Potential for energy efficiency is well-known, but achieving energy reductions
in practice will require new policy approaches
 Costs may be small in relation to GDP, but are nevertheless large in real
terms