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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, - PowerPoint PPT Presentation
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TFIAM meeting27 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 6Introduction
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
PRIMES
Economy
AEA-T model
CH4, N2O, HFC, PFC, SF6 (Europe)
CO2 (Europe)
Transport Agriculture
Regional concen-tration:SO2, NO, NH3, PM, O3
POLES
IMAGE
TIMER FAIR
WaterGap
Energy Price
CO2 Permit Price
CO2, CH4, N2O, HFC, PFC, SF6
Sinks
EMEPOFIS
AQ impacts
Urban conc. PM, NO2, O3
Emissions
OPSM
Street increments
CC impacts
GEM-E3, PROMETHEUS
RAINS
MERLIN
COPERT III, TREMOVE, TREND
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
300
500
700
900
1100
1300
1990 2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
year
CO
2eq
conc
(pp
mv)
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 SEP SEP-LEAssumed permit price at EU-level1 Assumed global
permit priceYear
Euro (2000)/ton CO2
Low medium High2010 6 12 18 12 6 5 22015 8 16 24 20 6 6 12020 10 20 30 30 20 25 152025 10 20 30 50 40 45 352030 10 20 30 65 55 60 502040 - - - 105 802050 - - - 115 952075 - - - 165 1052100 - - - 190 105
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
0
500
1000
1500
2000
2500
3000
Bil
lion
(19
95)
$
fossil modern biofuels electricity savings
Global energy investments baseline 2000-2050
0
500
1000
1500
2000
2500
3000
2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050
Inve
stm
ent
bill
ion
$(19
95)
fossil modern biofuels electricity savings
Past and projected prices of fossil fuels and
electricity 1970-2050
OECD End-use costs (including tax) 1971-2050
0
5
10
15
20
25
30
35
40
45
1970 1980 1990 2000 2010 2020 2030 2040 2050Year
$(1995
)/Gj
Coal-industrial
Oil-transport
Electricity-residential
LCEP
Baseline
0
8
16
24
32
40
48
1970 1980 1990 2000 2010 2020 2030 2040 2050year
$(1999
)/bar
rel start of ye
ar
0
1
2
3
4
5
6
7
8
Prices $(199
9)/G
J
Baseline
Oil
Coal
Gas
Baseline
Baseline
LCEP
Fossil prices prices baseline and LCEP 1970-2050Left axis oil prices per barrel, right axis gas and coal prices per GJ
GREENHOUSE GAS EMISSIONS
0
1000
2000
3000
4000
5000
6000
1990 2000 2010 2020 2030 2040 2050
CO
2eq
(Mto
n)
all numbers compared to 1990 (%) Result LGEP climate policy scenario EU-25 EU-25 PRIMES FAIR Range share Year Baseline Commitment domestic domestic domestic 2020 +4% -20% -10% -8% 50-60%2030 +8% -40% -16% -26% 50-70%2040 +9% -57% -48% 85%2050 +7% -64% -61% 95%
Baseline
Commitment in LGEP
Domestic action
non-domestic (trade)
LGEP (FAIR)
LGEP (PRIMES)
Uncertainty range
Kyoto
Kyoto:FAIR: 6 Euro/ton CO2eq
PRIMES: 12 Euro/ton CO2eq
Avoided CO2 emissions
0
500
1000
1500
2000
2500
3000
3500
4000
4500
2000 2005 2010 2015 2020 2025 2030
Pro
ject
ed
en
erg
y-re
late
d C
O2
emis
sio
ns
(Mt)
Transport
Services
Households
Industry
Energy Branch
Electricity and Steamproduction
Emissions LCEP
Avoidable "baseline" emissions by sector:
Changes in the fuel mix of EU-25 gross inland energy consumption compared to the baseline in 2030
-100% -75% -50% -25% 0% 25% 50% 75% 100% 125% 150%
Solids
Oil
Natural gas
Nuclear
Renewable energy forms
Change in gross inland energy consumption compared to baseline (in 2030)
LCEP nuclear phase out
LCEP nuclear accelerated
LCEP renewables
LCEP
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
0
500
1000
1500
2000
2500
3000
3500
4000
4500
1990 2000 2030 -baseline
2030 - SEP 2030 - SEPincr.
Renewables
2030 -nuclear
phase-out
2030 - incr.nuclear
MtC
O2
Transport
Services
Households
Industry
Energy branch
Electricity & Steamproduction
Change in air pollutants emissions in developed and developing regions under the baseline and LGEP scenarios
relative to year 2000
Developed regions
0
50
100
150
200
250
300
baseline LGEP NOx
baseline LGEP SO2
baseline LGEP NMVOC
Ind
ex (
year
200
0 =
100
)
2000 2010 baseline 2020 baseline 2030 baseline 2050 baseline
2010 LGEP 2020 LGEP 2030 LGEP 2050 LGEP
Developing regions
0
50
100
150
200
250
300
baseline LGEP NOx
baseline LGEP SO2
baseline LGEP NMVOC
Ind
ex (
year
200
0 =
100
)
0
20
40
60
80
100
NOx SO2 NMVOC NH3 PM10
Ind
ex (
year
200
0 =
100)
2000 2020 CAFE 2030 baseline 2030 LGEP 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
CLE MFR B-CLE LE-CLE B-MFR
Finland 0.7 0.7 0.2 0.7 0.7 0.2
Sweden 14.9 10.5 5.2 10.9 10.5 5.1
UK 8.1 3.7 1.3 3.8 3.5 0.8
Norway 28.6 19.3 9.1 19.9 19.6 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: Baseline 2030 LGEP LGEP-MFR
NOx -47% - 52 % -75% NMVOC -45% - 45 % -62% SO2 -67% - 73 % -87% NH3 - 6% - 5 % -43% PM10 - 38% - 45 % -67% PM2.5 - 46% - 51 % -73%
2030: LGEP LGEP-MFR • Loss of statistical life expectancy: - 44% - 78% • Premature mortality due to ozone: - 16 % - 51% • Forest area at risk of acidification: - 56% - 88% • Ecosystems’ area endangered by eutrophication - 15 % - 82%
Table 8: Air pollutant emissions; baseline compared to CP and LGEP
EU25 emissions kton % change LREM-E 2030, LGEP 2030, LGEP
air pollutant 2000 2030 B-CLE LE-CLE SER-CLE B-MFR B-CLE LE-CLE SER-CLE B-MFRSO2 8736 2851 2371 2150 2342 1130 -16,8 -24,6 -17,9 -60,4NOx 11581 6125 5524 4972 5550 2849 -9,8 -18,8 -9,4 -53,5VOC 10654 5863 5877 5701 5912 4101 0,2 -2,8 0,8 -30,1NH3 3824 3597 3582 3573 3584 2174 -0,4 -0,7 -0,4 -39,6PM10 2455 1512 1357 1258 1344 817 -10,3 -16,8 -11,1 -46,0PM2.5 1748 937 860 790 857 468 -8,2 -15,7 -8,5 -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.
2010 2020 2030
Pollutant 1990 2000 SHIP-BAU
SHIP-BAU
SHIP-MFR
SHIP-BAU
SHIP-MFR
NOx 2743 3501 4265 5207 595 6530 769 NMVOC 101 131 170 219 219 284 284 SO2 1874 2418 2652 3415 752 4406 972 PM10 171 222 270 348 298 450 385 PM2.5 162 210 255 330 282 426 364
Emission control costs EU-25 billion Euro/year
Climate change benefit
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 Reference run 42.64 42.4 42.14 41.66 41.12
Best practice 42.64 37.77 35.04 31.44 28.05
Potassium Reference run 31.44 29.54 29.12 28.52 28.01
Best practice 31.44 19.92 16.27 12.26 8.81
Phosphate Reference run 15.89 14.44 14.02 13.42 12.8
Best practice 15.89 9.4 7.05 4.04 1.03
Ammonium Reference run 19.45 19.68 19.87 20.04 20.21
Best practice 19.45 14.28 12.3 9.8 7.32
Methane Reference run 48.82 47.52 47.78 48 48.31
Best practice 48.82 47.52 47.78 48 48.31
Nitrous oxide 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
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA PARI PRAG ROME STUT THES
0
10
20
30
40
50
60
70
80
observations
OFIS
EMEP
Results for NO2 annual average
R2 = 0.58
0
10
20
30
40
50
60
70
80
0 10 20 30 40 50 60 70 80
Observed (μg/m 3)
OF
IS m
od
el r
esu
lts
(μg
/m3)
Comparison EMEP/OFIS results NO2 annual average 2000
0
10
20
30
40
50
60
70
80
90
100
0 10 20 30 40 50 60 70 80 90 100
Observed (μg/m3)
OF
IS m
od
el (
μg
/m3)
PRAG
BERL
COPE
MARS
GDAN
LISB
HELS
ROME
BRUS
ANTW
GRAZ
THES
BUDA
LOND
MILA
ATHE
KATO
PARI
STUT
BARC
Trend NO2 European cities 2000-2030
0
10
20
30
40
50
60
Gra
z
Gdan
sk
Thessa
lonik
i
Mars
eille
Copen
hagen
Stutg
art
Hels
inki
Lisbon
Prague
Barcelo
na
Berlin
Budapes
t
Athen
s
Rome
Antwer
p
Bruss
elPar
is
Kat
owice
London
Mila
n
NO
2 (u
g/m
3)2000 2030-CC 2030-CC-MFR
Annual average ozone concentration (ug/m3)
Trend somo-35 in European cities 2000-2030
0
1000
2000
3000
4000
5000
6000
7000
8000
9000
Londo
n
Helsin
ki
Copenha
gen
Antwer
p
Brusse
l
Katowice
Lisbon
Gdansk
Berlin
Paris
Pragu
e
Budapes
t
Athen
sRome
Graz
Thess
aloniki
Stutga
rt
Barce
lona
Mars
eille
Mila
n
som
o-35
(pp
b.da
ys)
2000 2030-CC 2030-CC-MFR Coverage:55 Million inhabitants 2030
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA PARI PRAG ROME STUT THES
0
10
20
30
40
50
observations
OFIS
EMEP
PM10 annual mean values
Summary results 20 cities, 55 million inhabitants (2030)
Population weighted average NO2 PM10 O3 (SOMO35)
Scenario 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
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
Average yearly wind speed considered per city
Specific wind directions for each cityWind direction Frequency for THES
0
2
4
6
8
10
12N
NNE
NE
ENE
E
ESE
SE
SSE
S
SSW
SW
WSW
W
WNW
NW
NNW
Wind direction Frequency for STUT
0
5
10
15N
NNE
NE
ENE
E
ESE
SE
SSE
S
SSW
SW
WSW
W
WNW
NW
NNW
Wind direction Frequency for ROME
0
2
4
6
8
10N
NNE
NE
ENE
E
ESE
SE
SSE
S
SSW
SW
WSW
W
WNW
NW
NNW
Wind direction Frequency for LISB
0
5
10
15
20
25N
NNE
NE
ENE
E
ESE
SE
SSE
S
SSW
SW
WSW
W
WNW
NW
NNW
0
5
10
15
20
25
30
35
40
45
50
55
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA PARI PRAG ROME STUT THES
Con
cent
ratio
n (μ
g/m
3)
measured modelled
Mean annual NO2 street increments (μg/m3) in 20 European cities: OSPM model results compared with observations
0
2
4
6
8
10
12
14
16
18
20
22
24
26
28
30
32
ANTW ATHE BARC BERL BRUS BUDA COPE GDAN GRAZ HELS KATO LISB LOND MARS MILA PARI PRAG ROME STUT THES
Con
cent
ratio
n (μ
g/m
3 )
measured modelled
Mean annual PM10 street increments (μg/m3) in 20 European cities: OSPM model results compared with observations.
• PM10: range modelled street increment 5-16 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
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. PC - LDV Gasoline PC - LDV Diesel HDV Package 1 - -20% -50% Package 2 - -20% -85% Package 3 - -40% -85% Package 4 -40% -20% -85% Package 5 -40% -40% -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 PC - LDV Diesel HDV Package 1 -50% -0% Package 2 - DPF -0% Package 3 DPF (GDI) DPF DPF
basis reduction: discussions on Euro V and Euro VI held at EU level (European Commission, 2004)
Development of NOx emission factor (%) for the two scenarios in Germany (reference year: 2000)
2010 2015 2020 2025 2030 NOx emissonfactor (%) CLE MFR CLE MFR CLE MFR CLE MFR CLE MFR
PC Gasoline 36 36 22 20 17 13 16 12 17 12
PC Diesel 108 108 105 78 102 54 98 38 100 30
LDV 81 81 74 58 74 45 79 42 83 42
HDV 67 67 46 42 34 25 32 15 36 11
Buses 70 70 44 42 26 21 22 12 21 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 69 69 69 44 70 26 69 15 70 11
LDV 58 58 47 34 42 20 45 15 47 15
HDV 54 54 30 29 17 13 12 6 13 5
Buses 64 64 35 34 16 13 10 6 9 5
COPERT III,TRENDS and input traffic activity data originating from TREMOVE (version 2.23 ).
SCENARIOS FOR SOEOR2005: CONCLUSIONS (II)
• SEP does initiate changes, but does not yet (2030) requires afundamental “transition” in the European energy system.
• A sustainability transition meeting all EU’s climate and energytargets appears to be feasible, but at significant costs (400Euro/household/year in 2030); there is not one optimal solution -> SEP variants.
• Integrated CC&AP policies can result in cost savings, avoidanceof trade-offs, and effective abatement of air pollutant and GHGemissions.
• A sustainability transition in Europe has to be viewed in a globalcontext.
• The costs for medium term GHG emissions reductions aresignificant dependent on the assumed economic growth, asshown by a lower economic growth variant.
LGEP
LGEP
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