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CENTRO EURO-MEDITERRANEO PER I CAMBIAMENTI CLIMATICI
1
Dottorato
Climate Change and Policy Modelling Assessment:
Adaptation in (CGE) Modelling
Francesco Bosello
2CENTRO EURO-MEDITERRANEO PER I CAMBIAMENTI CLIMATICI
Defining adaptation (1)
“Adjustment in ecological, social, or economic systems in response to actual or expected climatic stimuli, and their effects or impacts. […] refers to changes in processes, practices or structures to moderate or offset potential damages or to take advantages of opportunities associated with changes in climate” (IPCC TAR, 2001)
“Process by which strategies to moderate, cope with and take advantage of the consequences of climate events are enhanced, developed and implemented” (UNDP, APF, 2005).
“Policies, practices, and projects with the effect of moderating damages and/or realising opportunities associated with climate change” (EEA, 2005)
“Institutional definitions”
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Defining adaptation (2)
“Process through which people reduce the adverse effects of climate on their health and well-being, and take advantage of the opportunities that their climatic environment provides” (Burton, 1992)
“Any adjustment, whether passive, reactive or anticipatory, that is proposed as a means for ameliorating the anticipated adverse consequences associated with climate change (Stakhiv, 1993)
“Changes in a system in response to some force or perturbation, in our case related to climate” (Smithers and Smit, 1997)
“Definitions from the science”
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Defining adaptation (3)
There are some key concepts
Systemic process or transformation
Through space and time
Reducing(increasing) negative(positive) impacts if successful viceversa if unsuccessful (maladaptation)
Triggered by a climatic pressure
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Classifying adaptation (1)
The subject of adaptation: Who or what adapts Ecological, social and/or economic systems. These changes can be the result of natural responses and in this case they usually involve organisms or species, or of socio-economic or institutional reactions in which case they are undertaken by individual or collective actors, private or public agents.
The object of adaptation: What they adapt to Adaptive responses can be induced either by changes in average conditions or by changes in variability of extreme events. While in the first case the change is slow and usually falls within the “coping range” of systems, in the second case changes are abrupt and outside this coping range (Smit and Pilifosova, 2001).
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Classifying adaptation (2)
How Adaptation Occurs Several criteria can be used to identify the different adaptation processes (see e.g. Smit et al. 1999; Klein and Tol, 1997; Fankhauser et al., 1999; IPCC, 2001).
Concept or Attribute
Purposefulness Autonomous → Planned
Timing Anticipatory → Responsive
Temporal Scope Short term → Long term
Spatial Scope Localised → Widespread
Function/Effects Retreat – accommodate – protect – prevent
Form Structural – legal – institutional
Valuation of performance Effectiveness-efficiency-equity
Source: adapted from Smit et al. 1999
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Classifying adaptation (3)
Autonomous Adaptation: natural automatic response to a “shock”. Also socio-economic systems react partly autonomously. There are substitution possibilities triggered by price (scarcity) signals.
Planned Adaptation: strategies apt to alleviating the damage once it is (or will be) materialized via proper modifications of the impacted socio-economic-environmental system. Undertaken by public agencies – agents.
Objectives of planned adaptation (Klein and Tol, 1997): increasing the robustness of infrastructural design and long term
investment, increasing the flexibility of vulnerable managed system, enhancing the adaptability of vulnerable natural systems, reversing trends that increase vulnerability (“maladaptation”), improving societal awareness and preparedness.
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A short history of adaptation (1)
Art. 2 objectives "...achieve [stabilization of greenhouse gas concentrations] within a time frame to allow ecosystems to adapt naturally to climate change, to ensure that food production is not threatened and to enable economic development to proceed in a sustainable manner.” (UN, 1992).
Art. 3.3: “The Parties should take precautionary measures to anticipate, prevent or minimise the causes of climate change and mitigate its adverse effects”.
UNFCCC (Rio Earth Summit 1992)
not a new issue indeed…
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A short history of adaptation (2)
Article 4.1(b): parties are committed to “formulate, implement, publish and regularly update national and, where appropriate, regional programmes containing […] measures to facilitate adequate adaptation to climate change”.
Article 4.1(e): all parties should “cooperate in preparing for adaptation to the impacts of climate change” and to “develop and elaborate appropriate and integrated plans for coastal zone management, water resources and agriculture, and for the protection and rehabilitation of areas, particularly in Africa, affected by drought and desertification, as well as floods”.
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A short history of adaptation (3)
Kyoto Protocol (1997)
Art. 10: “All parties […] shall […] formulate, implement, publish and regularly update national and, where appropriate, regional programmes containing measures to […] facilitate adequate adaptation to climate change”
Article 12.8: “The Conference of the Parties […] shall ensure that a share of the proceeds from certified project activities is used to […] assist developing country Parties that are particularly vulnerable to the adverse effect of climate change to meet the cost of adaptation”
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A short history of adaptation (4)
However until the end of ’90s main policy & research focus was on mitigation (e.g.
see 1995 IPCC SAR)
Prudential and “politically correct”
Mitigation “easy” to investigate
Then
Awareness of climate inertias
Difficulty of effective implementation of mitigation policies (Kyoto)
Interest on adaptation (2001 TAR, 2007 FAR)
Standard tools for economic policy (command and control and/or market based mech.s) & standard analysis could be applied to mitigation
More of an issue for “developing countries”
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Where do we stand now (1)
IPCC TAR (2001) [p. 779] “…Adaptation to climate change has the potential to substantively reduce many of the adverse impacts of climate
change and enhance beneficial impacts - though neither without cost nor without leaving residual damages…”
An increasing number of researches, but still far from conclusive, highlights a strong potential for adaptation to reduce climate change adverse effects see e.g. the vast literature on coastal protection or on agriculture
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Where do we stand now (2)
“…Current knowledge of adaptation and adaptive capacity is insufficient for reliable predictions of adaptations; it also is insufficient for rigorous evaluation of planned adaptation options, measures and policies of governments” (IPCC 2001, TAR)
Nevertheless it is recognised that:
“…more quantitative information on the costs and benefits of economy-wide adaptation is required…” (the Stern review, 2006)
“Only a few credible estimates are now available of the cost of adaptation (in the Developing countries) …and… highly speculative” (the Stern Review 2006)
“At a global or international level, defining a socially, economically and environmentally justifiable mix of mitigation, adaptation and development remains difficult and a research need” (IPCC 2007, FAR)
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Adaptation in modelling
Exhogenous adaptation: the Hope’s PAGE (2002) model
Select a mitigation and adaptation policySelect a mitigation and adaptation policy
Global and regional
temperature
Global and regional
temperature
Costs ofmitigationCosts of
mitigationCosts of
adaptationCosts of
adaptation
Impacts Impacts CostsCosts
Source: Hope (2006)
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Adaptation in modelling
0
0.5
1
1.5
2
2.5
3
3.5
4
4.5
2000 2020 2040 2060 2080 2100
ATL AD GRT ATL1
Tolerability Plateau
Slope
Damage Reduction
Source: Hope (2006)
Adaptation can achieve an increase in the tolerable t increase (plateau + slope effect) and a reduction in damage
°C
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Adaptation in modelling
251.2520000non-econLDC
251.2520000non-econOECD
502.520000econLDC
904.5200020.12000econOECD
%%/yeardegCdegC/yearSectorRegion
PlateauSlopeStart datePlateauSlopeStart date
Reduction in impactsTolerable temperature rise
251.2520000non-econLDC
251.2520000non-econOECD
502.520000econLDC
904.5200020.12000econOECD
%%/yeardegCdegC/yearSectorRegion
PlateauSlopeStart datePlateauSlopeStart date
Reduction in impactsTolerable temperature rise
Source: Hope (2006)
Default adaptation strategy in PAGE2002
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Adaptation in modelling
Source: Hope (2006)
Costs of default adaptation strategy in economic sector, PAGE 2002
min mode max
1 °C rise in
tolerable temp
3 12 25
10% reduction in
impact
0.4 1.6 3.2
$US (2000) billion/year2000 - 2200
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Adaptation in modelling
Endogenous adaptation as a flow, DeBruin et al. (2007)
D = CC damageRD = residual damageGD = gross damagePC = adaptation costP = adaptation rateY = GDPTE = temperature
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Adaptation in modelling
Restrictions:
0.3 < P(t=2130) < 0.8
0.1% of GDP < PC(t=2130) < 0.5% of GDP
and
7% of TD < PC(t=2130) < 25% of TD
To be estimated
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Adaptation in modelling
Endogenous adaptation as a stock. Bosello (2006)
N
n
T
t
t
tnC tnL
tnCtnLn
1 1
)1(
),( ),(
),(log),()1()(max
]),(),([),(),(),( )1( tnLtnKtnKtnAtnQ R
),(),()1()1,( tnItnKtnK K “Productive” capitalaccumulation
Gross production
Obj. Funct.
),(),()1()1,( tnIAtnADStnADS SAD
),(&),()1()1,( tnDRtnKtnK RKR R “Knowledge stock”
accumulation
“Adaptation” capitalaccumulation
),()),(1]()),()(exp(
)(),([),( tnQtn
tnKn
ntntnE
R
Emissions
The “double” role of knowledge: productivity increasing and emission intensity decreasing
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Adaptation in modelling
),(&),(),(),(),( tnDRtnIAtnItnCtnY Ususal output allocation function
“Link” gross – net output
Net (of CC damage and environmentalPolicies) output
2
2
1,
1,
1 ( , )( , )
11 ( ) / 2,5
exp( ( , ))
bn
n
b n tn t
T tSAD n t
),(),(),( tnQtntnY
Abatement costs (as forgone GDP) depending (+) on abatement rates
Climate change damages (as forgone GDP) depending (+) on temperature and (-) on adaptation “capital”
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Adaptation: compendium of results. (Hope, 2006)
At given assumptions aggressive adaptation policies could be easily justified as well: for instance, at a 5% discount rate, the mean cost of US $ 0.5 trillion implied by an ambitious adaptation strategy implemented between 1990 and 2100, were outweighed by the US $ 17.5 trillion benefits from the reduction in economic impacts.
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Adaptation: compendium of results. (De Bruin et al., 2006)
Climate change damages
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Adaptation: compendium of results. (Bosello, 2006)
Abatement Rates
0
2
4
6
8
10
12
142000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Ab
ate
men
t in
%
M
M+A
M+A+R
CO2 Emissions
0
50
100
150
200
250
300
350
400
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Millio
n T
on
s C
O2
M
M+A
M+A+R
Cumulated Disc. Environmental Damage
0
200
400
600
800
1000
1200
1990
2000
2010
2020
2030
2040
2050
2060
2070
2080
2090
2100
Billio
ns U
S $
M
M+A
M+A+R
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Adaptation: compendium of results. (Bosello, 2006)
0
1
2
3
4
5
6
7
2000 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100
% o
f to
tal c
apit
al s
tock
0
2
4
6
8
10
12
14
% o
f ab
ated
em
issi
on
s
Abatement Adaptation stock Knowedge stock
Mitigation and R&D investment start at the beginning, adaptation later
Mitigation, R&D investment and adaptation (M+A+R)
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Autonomous adaptation: CGE modelling
It can “intrinsically” highlight the role of autonomous adaptation (i.e. economic substitution possibilities) as long as the difference between direct and indirect costs can be shown.
Extreme care in the interpretation (and communication) of results.
The big issues here:
The geographical scale effect: large aggregations conceal “hot spots”
Stock vs flows (do not compare pears with apples)!
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Autonomous adaptation: CGE modelling
Sometimes it is “embedded” in the model. It is nothing else than the very functioning of the general equilibrium structure of the model with all its interconnected adjustments (see SLR example)
In some other cases also autonomous adaptation need to be modelled.
This is the case of climate change impacts on health or tourism flows (but is this really adaptation or impact?) when endogenous (in this case demand) variables have to be modified
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Autonomous adaptation: CGE modelling
Example: Bosello et al. (2007), “Economy wide estimations of climate change impacts Sea level rise”
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Autonomous adaptation: CGE modelling, SLR
Inputs to the CGE model Outputs from the CGE model
ml $as % of
GDP Land Labour CapitalUSA -0.052 121 0.0002 -0.0013 -0.016 0.015 0.684 -0.034 -0.034
CAN -0.002 72 0.0017 -0.0004 0.029 0.032 0.822 -0.013 -0.009
WEU -0.029 298 0.0005 -0.0019 -0.005 0.016 0.608 -0.035 -0.036
JPK -0.141 146 0.0004 -0.0018 0.006 0.011 1.132 -0.034 -0.035
ANZ -0.010 237 0.0075 -0.0008 0.081 0.010 0.967 -0.022 -0.028
EEU -0.041 45 0.0016 -0.0047 -0.001 -0.037 0.629 -0.074 -0.079
FSU 0.000 0 0.0000 -0.0007 -0.005 0.010 0.613 -0.038 -0.040
MDE -0.007 75 0.0011 -0.0045 0.000 -0.001 0.998 -0.035 -0.044
CAM -0.120 182 0.0049 -0.0098 0.052 -0.023 0.806 -0.053 -0.059
SAM -0.041 647 0.0043 -0.0007 0.102 0.020 0.742 0.005 0.007
SAS -0.396 6000 0.1180 -0.0649 0.078 -0.212 1.420 -0.285 -0.292
SEA -0.839 14913 0.1475 -0.1092 -0.032 -0.357 2.372 -0.468 -0.504
CHI -0.091 579 0.0063 -0.0303 -0.060 -0.236 0.521 -0.235 -0.260
NAF -0.039 1120 0.0548 -0.0036 0.012 0.039 0.795 -0.002 0.016
SSA -0.130 8869 0.2359 -0.0094 0.100 -0.029 1.034 -0.055 -0.062
SIS -0.167 188 0.0220 -0.0189 -0.020 -0.086 0.885 -0.162 -0.169
Terms of Trade
Invest. flows
Factor PricesLand loss
Direct costs: value of land lost
GDP
Reference Year 2050: % changes wrt baselineland loss ranking
direct cost
ranking
gdp loss ranking
USA 8 15 12CAN 15 10 16WEU 12 13 10JPK 4 14 11ANZ 13 6 13EEU 9 11 7FSU 16 16 14MDE 14 12 8CAM 6 8 5SAM 10 9 15SAS 2 3 2SEA 1 2 1CHI 7 7 3NAF 11 4 9SSA 5 1 6SIS 3 5 4
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Autonomous adaptation: CGE modelling, SLR
0.1475
0.0063
0.0548
0.2359
0.0220
0.0649
0.1092
0.0303
0.0036 0.00940.0189
0.1180
0
2000
4000
6000
8000
10000
12000
14000
16000
SAS SEA CHI NAF SSA SIS
Mill
ion
s $
0.00
0.05
0.10
0.15
0.20
0.25
2050
GD
P %
DC abs GEC abs DC %GDP GEC % GDP
0.00
02 0.00
17
0.00
05
0.00
04
0.00
75
0.00
16
0.00
00 0.00
11
0.00
49
0.00
43
0
100
200
300
400
500
600
700
800
USA CAN WEU JPK ANZ EEU FSU MDE CAM SAM
Mill
ion
s $
0.000
0.002
0.004
0.006
0.008
0.010
0.012
2050
GD
P %
DC abs GEC abs DC %GDP GEC % GDP
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Planned adaptation and CGE modelling.
The typical approach is the “if then” one.
That is: a scenario with climate change impacts and without adaptation is compared with a scenario with adaptation. Adaptation is one (or more) specific planned adaptation strategy ad hoc modelled and a lower climate change impact is imposed.
Thus we return to the shortcoming of not having an endogenously defined optimal level of adaptation
In addition, when stock and flow variables at a time are concerned by climate change and adaptation, results are difficult to interpret.
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Planned adaptation and CGE modelling.
Bosello, F., Roson, R. and Tol, R.S.J. (2007), “Economy wide estimates of the implications of climate change: sea level rise”, Environmental and Resource Economics, 37.
Example
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Modelling coastal protection
The amount of savings by regional households adjusts endogenously. In each region regional savings increase uniformly to meet the increased investment demand.
This additional investment increases (exogenously) regional investment. (Cost of coastal protections from Nicholls)
Given that income is allocated between savings, private and public expenditure, more savings => less consumption. The sum of the three “shares” cannot exceed 1.
The idea: coastal protection implies additional investment need.
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CGE modelling and planned adaptation: SLR
Equation(linear)RORGLOBAL# global supply of cap. goods, or global rental rate on investment (HT 59)# (all,r,REG)
qcgds(r)= investment(r);
(8) New exhogenous variables(8) Endogenous variables deleted (equations for cgds)
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CGE modelling and planned adaptation: SLREQUATION (Linear) DEVSAVE1 (all,r,USA1) (all,i,EU1) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE2 (all,r,EU1) (all,i,JPN1) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE3 (all,r,JPN1) (all,i,EEFSU1) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE4 (all,r,EEFSU1) (all,i,CHIND1) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE5 (all,r,CHIND1) (all,i,EEx1) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE6 (all,r,EEX1) (all,i,RoA11) qsave(r)=qsave(i);
EQUATION (Linear) DEVSAVE7 (all,r,RoA11) (all,i,RoW1)qsave(r)=qsave(i);
(7 ??) New endogenous variables
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CGE modelling and planned adaptation: SLR
Equation DISTPARSUM #sum of the distribution parameters# (all,r,REG)
DPARSUM(r)*dpsum(r)=DPARPRIV(r)*dppriv(r)+DPARGOV(r)*dpgov(r)+ DPARSAVE(r)*dpsave(r);
From exogenous to endogenous
From endogenous to endogenous
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CGE modelling and planned adaptation: SLR
Full Protection: Selected Results
Inputs Outputs
USA 0.01 0.151 0.001 -0.189 -0.206 -0.069EU 0.025 0.302 -0.022 -0.262 -0.296 -0.16EEFSU 0.332 3.179 0.049 -0.143 0.033 -0.133JPN 0.032 0.242 -0.009 -0.569 -0.605 -0.344RoA1 0.799 9.422 0.103 -0.315 -0.009 -0.13EEx 0.185 2.235 0.015 -0.274 -0.223 -0.069CHIND 0.106 1.254 0.003 -0.961 -0.889 -0.116RoW 0.148 1.817 0.009 -0.355 -0.31 -0.115
Household utility
index (% change
w.r.t. baseline)
CO2
Emissions (% change
w.r.t. baseline)
Coastal protection
expenditure (% of GDP)
Private expenditure (% change
w.r.t. baseline)
Investment induced by
coastal protection (% change
w.r.t. baseline)
GDP (% change
w.r.t. baseline)
= highest (absolute) values
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CGE modelling and planned adaptation: SLR
GDP: No Protection vs Full Protection (2050)
-0.04
-0.02
0
0.02
0.04
0.06
0.08
0.1
0.12
USA EU EEFSU JPN RoA1 EEX CHIND RoW
% o
f G
DP
No Protection
Full Protection
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CGE modelling and planned adaptation: SLR
Utility: No Protection vs Full Protection
-0.1
-0.08
-0.06
-0.04
-0.02
0
0.02
USA EU EEFSU JPN RoA1 EEx CHIND RoW
% c
han
ge
in u
tili
ty
-1
-0.8
-0.6
-0.4
-0.2
0
0.2
% c
han
ge
in u
tili
ty
No Protection
Full Protection
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SLR, optimal adaptation (the PESETA project 2007)
0
20
40
60
80
100
120
Austri
a
Belgiu
m
Denm
ark
Finlan
d
Franc
e
Ger
man
y
UKingd
om
Gre
ece
Irelan
dIta
ly
Luxe
mbo
urg
Nethe
rland
s
Portu
gal
Spain
Sweden
Cypru
s
Czech
Rep
Eston
ia
Hunga
ry
Latv
ia
Lith
uani
aM
alta
Polan
d
Slova
kia
Slove
nia
0
2
4
6
8
10
12
14
16
% of land at risk protected % of protected land
A2 2085 high SLR scenario: optimal protection levels for the EU from the DIVA model
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SLR, optimal adaptation (the PESETA project 2007)
-0.8
-0.6
-0.4
-0.2
0
0.2
0.4
0.6
0.8
1
Austria
Belgiu
m
Denm
ark
Finla
nd
France
Ger
man
y
UKingd
om
Gre
ece
Irela
nd Italy
Luxem
bourg
Nether
lands
Portugal
Spain
Swed
en
Cypru
s
Czech
Rep
Estonia
Hungar
y
Latvi
a
Lithuan
ia
Mal
ta
Poland
Slova
kia
Slove
nia
-0.11
-0.06
-0.01
0.04
0.09
0.14
GDP Opt AD
GDP No AD
A2 2085 high SLR scenario: GDP no adaptation vs optimal adaptaton
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CGE modelling and planned adaptation: SLR
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CGE modelling and planned adaptation: SLR
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CGE modelling and planned adaptation: SLR
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