A market mechanism for
adaptation to climate
change
EU Centre at RMIT
Melbourne, 2 April 2012
Axel Michaelowa
University of Zurich, [email protected]
Perspectives, [email protected]
www.perspectives.cc · [email protected]
Topics
 Experiences with market mechanisms in
mitigation
 The funding challenge for adaptation
 Common metrics for adaptation
 Design of an Adaptation Market Mechanism
 Questions and discussion
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Expectations for the
mitigation mechanisms
 Two project-based mechanism (CDM and JI)
 One government-government trade based
IET
mechanism (IET)
JI
CDM
 Expectations 1990s:
 IET dominates numerically due to high supply of hot air
and low transaction costs
 JI will be attractive, especially in countries in transition
 CDM will fail as its rules are much too cumbersome and
the investment climate in developing countries is
dismal
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Lessons from the
mitigation mechanisms
 Results 2011
 CDM overwhelming numerical success - 6000 projects,
billions of CERs, but some sectors sidelined
 IET stalled due to mistrust of buyers in government
sellers. First transactions tainted with corruption
 JI latecomer due to late institutional decisionmaking
and governmental ERU transfers
 Reason: Clear incentives for
the private sector and limited
government interference
determine success
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CDM
IET
JI
How will adaptation funding be distributed?
Financial
sources
CDM
Donors: International financial pledges 2010-2012: 30 billion USD
~ 30% - 50% in adaptation projects
Denmark,
EU 56 mio $,
Spain 59 mio $,
Germany 10 mio $
Financial
resources
~ 8.6 mio.
CERs =
~ 115 mio.
USD
Channeling
institutions
Adaptation Fund
(UN legitimation)
~ 40%
US: 1.8 bn USD
EU27: 4 bn USD
Multilateral Channeling Institutions:
e.g. ICCAI, PPCR, GCCA, WB-CIFs, etc.
Standardized,
Semi-transparent
Distribution
criterias
~ 60%
US: 1.2 bn USD
EU27: 6 bn USD
Bilateral Funding
Individual,
Totally intransparent
Adaptation projects in developing countries
Source: World Resources Institute; UNFCCC
 Lack of performance linked standards and indicators may lead to
monetary flows which only rarely lead to long-lasting benefits
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5
Adaptation evaluation
Status Quo
 On international level many initiatives to tackle evaluation of
adaptation projects/programmes, highly differing approaches
 Common understanding
 Adaptation does not lend itself to a straightforward metric
 Several indicators/criteria needed
 Common challenges
 Uncertainty about climate change projections and impacts
 Differentiation between natural variability and climate change
 “Soft measures“ dominate current activities and are more
difficult to assess
 How to deal with adaptive deficit in baseline determination?
 Timescales much longer than project lifetime
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Challenges in monitoring of adaptation projects
Overview of results levels
Source: Scheyde et Wagner, 2008, p.7
GIZ approach
Indicator definition
 Objective of project is
usually split up in several
indicators
 Depending on the result
levels either process or
objective indicators are used
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Indicator value definition
The indicator value acts as
the monitoring unit which
enables evaluation of the
indicator (and finally of the
objective of the project).
Evaluation of adaptation projects
Introduction of new indicators
Perspectives proposal
Attribution gap
 Step 1) Below attribution gap: Free definition of process and outcome
indicators (preferably in quantitative manner)
 Step 2) Beyond attribution gap: Definition of common set of
effectiveness indicators:
- Saved Wealth (SW)
- Saved Health (SH)
- (Environmental Benefits (EB))
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New indicators for measuring adaptation effectiveness
 Developing of a new approach to assess adaptive benefit of
project/programme by definition of indicators:
- Saved Wealth (SW)
- Saved Health (SH)
- (Environmental Benefit (EB))
 These indicators build the framework to assess the total benefit /
value of a project/programme:
TVadapt  SWp  SH p
 Note: + is not meant to allow for summing the values of SW and SH.
It rather indicates that the total adaptation benefits consists of
different indicators
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9
1. Indicator: Saved Wealth (SW) I
 General measurement of wealth restricted to economic assets in €
Purchasing Power Parity (PPP)
 Four possible concepts with advantages and disadvantages:
Concept
Description
Advantages
Disadvantages
Absolute wealth
(in €)
Wealth benefit in €
Easy to measure
Benefits richer countries, not
close to vulnerability
Relative wealth
saved
(assessed on an
aggregate level)
Wealth benefit relative to
overall assets of a nation
(or region, city, community)
, multiplied with population
Allocates (adaptation)
funds to poorest
countries (or regions,
cities, communities)
Benefits not necessarily
poorest or most vulnerable
persons within a country (or
region, city, community)
Relative wealth
saved
(assessed on an
individual level)
Wealth % saved per person
/(or city, region) (multiplied
with population of city);
individual percentages are
summed up
Close to vulnerability
Data access difficult in case of
individualized approach
Wealth below
the subsistence
level (in €)
The subsistence level (or
another critical value) is
defined, e.g. 2000 € per
person. Only savings below
the benchmark are counted
Accounts for the issue
that poorer
communities are
more vulnerable
Subsistence level definition is
difficult & critical.
When using aggregate data,
the concept loses power, while
detailed data may be missing.
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10
1. Indicator: Saved Wealth (SW) II
 We recommend a Mixed Index for Saved Wealth (MISW):
- Consisting of absoulte wealth saved (AWS) and relative wealth
saved (RWS)
SWp  MISWp  AWS p  RWS p
 Combines advantages of both concepts:
- Vulnerable regions are adequately reflected while
- High absolute numbers of wealth in developed regions are not
neglected
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11
1. Indicator: Saved Wealth (SW) III
 MISW may be applied to:
- Public infrastructure
- Private property
 Natural resources and services (cropland, graze land, forests, fishing
ground, carbon uptake, built-up land) are included in public property
 Development of wealth over time based on expected economic growth is
considered
 Discounting of wealth based on regional discount rates is considered:
€
Autonomous
development of wealth
in region over time
(undiscounted)
Discounted
development of wealth
in region over time
€
Damage per event
Time
 SW will be adjusted to the frequency of climate change
driven extreme events
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12
Frequency
Example Saved Wealth I
 A seawall project in a medium developed region, populated by
500,000 people. The example shows how SW is accounted
 First step: Calculation of dam
specification for 100yr flood as well
as flood frequency and damage
potential
 Second step: Calculation of wealth
losses (private and public property)
Wealth loss per flood (% of wealth )
Total value (Mn €); average
over lifetime; already
51-100 yr 11-50 yr 6-10 yr
Type of wealth
deflated)
floods
floods
floods
Public infrastructure
200
30%
10%
3%
Private property, rich
150
3%
1.5%
1.00%
Private property, middle class
90
30%
10%
3%
Private property, poor
40
50%
20%
10%
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13
1-5yr
floods
1%
0.5%
1%
4%
Wealth per
person
(€/person)
400
30000
600
116
Example Saved Wealth II
 Third step: Calculating the annual expected wealth losses
Average wealth loss per year (Mn Euros)
Total value (Mn €); average 51-100 yr 11-50 yr 6-10 yr
1-5yr
Type of wealth
over lifetime; deflated)
floods
floods
floods
floods
Public infrastructure
200
0.80
0.67
0.80
0.80
Private property, rich
150
0.06
0.08
0.20
0.30
Private property, middle class
90
0.36
0.30
0.36
0.36
Private property, poor
40
0.27
0.27
0.53
0.64
Total wealth
480
Total
3.07
0.64
1.38
1.71
6.79
 Fourth step: Calculating the MISW, assuming a project lifetime of 50
years and 500,000 inhabitants
SWp  MISWp  AWS p  RWS p  120Mn.€
6.79 Mn. € * 50 years
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6.79 Mn. € / 480 Mn. € *
500,000 inhabitants * 50 years
14
2. Indicator: Saved Health (SH) I


Basic concept: Independent indicator for human life and wellbeing without
monetary valuation avoids ethical challanges
New approach based on WHO-standard Disability Adjusted Life Years
Saved (DALYs)
Enhancement of DALYs to avoid discounting and age weighting


New indicator Saved Health is defined as: DALYscc
Calculation:

DALYcc = YLL
+
YLL = N x L
YLD = I x DW x L
YLL: years of life lost due to premature
mortality
N = number of deaths
L = standard life expactancy at age of death
(in years)
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YLD
YLD: years lived with disability
I = number of incident cases
DW = disability weight
L = average duration of disability (years)
15
2. Indicator: Saved Health (SH) II
 Data base for years lived
with disability: WHO
information
May need to be enhanced
for adaptation purposes
Source: Extract from WHO (2010)
 Data base for Life
expactancy: UN information
Increase of life expactancy
over time will be considered
 Health damage distribution is adjusted to the frequency of climate
change driven extreme events (according to Saved Wealth calculation)
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16
Example Saved Health I
 We assume the seawall example in the same region as before,
standard life expectancy in region: 70 years
 First step: Calculation of dam
specification for 100yr flood as well
as flood frequency and health
damage potential
 Second step: Calculation of health
loss according to categories and
disability weights (e.g. average
duration of fractures is two months)
Average health loss
(% of population affected)
Deaths
Fractures
Malaria
Diarrhoea
....
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51-100 yr
floods
1%
10%
8%
20%
17
11-50 yr
floods
0,3%
8%
2%
12%
6-10 yr
floods
0,15%
5%
1%
8%
1-5yr
floods
0,1%
4%
1%
5%
Example Saved Health II
 Third step: Calculating people affected per category
Number of people affected
Deaths
Fractures
Malaria
Diarrhoea
....
51-100 yr
floods
67
667
533
1.333
11-50 yr
floods
50
1.333
333
2.000
6-10 yr
floods
100
3.333
667
5.333
1-5yr
floods
200
8.000
2.000
10.000
 Fourth step: Calculating the DALYsCC
DALYcc = YLL
No. of deaths * standard life
expectancy at age of death:
417 * 30 = 12,500 DALYsCC
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+ YLD
= 13,100 DALYcc /a
Summing up the YLDs
(e.g. YLD Fractures = 3,600 *
0.27 * 0.176 = 600 DALYsCC )
18
Total
417
13.333
3.533
18.667
-
Basics of adaptation
market mechanism
 Trading of quotas for a public good requires
scarcity defined by policymakers
 Public bad: politically palatable maximum
 Public good: desired quantity
 Trading generates the more benefits, the higher
the cost differentials of providing the public
good
 Cost differentials of adaptation projects are
substantial
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Cost differentials
Hurricane adaptation in Florida
Source:
ECA
(2009)
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Key concepts contd.
 Universally accepted trading unit
 Saved wealth and saved health could be generally
acceptable
 Third-party verification is required
 Non-compliance needs to be prevented by
enforcement of penalties
 Two principal forms
 Allocation – trade
 Baseline - credit
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Principles of Adaptation
Market Mechanism
 An adaptation commitment is specified by
government in two trading units (“adaptation
units”)
 Property protected from climate change impacts
 Human health impacts prevented (in DALYs)
 The commitment is allocated to entities that
Mexico
have to fulfil it, preferably in annual tranches
 Preferably proportional to greenhouse
 Honours polluter pays principle
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Accord
gas2010?
emissions
Principles of Adaptation
Market Mechanism II
 Covered entities have different options to
comply with their adaptation commitment
 directly investing in adaptation projects that generate
adaptation units
 acquiring adaptation units from dedicated adaptation
project developers
 acquiring adaptation units from covered companies
Mexico
with a surplus of such units
Accord
2010?
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General concept of an Adaptation Market Mechanism
Climate
Change
Adaptation
project dev. I
Adaptation
project dev. II
Identify,
invest,
implement
Politics
Defines,
validates,
verifies
Agriculture,
Forests
Private
property
Regulator
Sets
Adaptation
target
Activities 2
Tradable units
Public
infrastructure
Health,
etc.
Demand
Activities 1
 Adaptation market mechanism
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An example of use of the AMM
EU
Sets Target (hypothetical):
 5 billion € Saved Wealth annually
 10,000 DALYs annually

Emitter 1:
10 % of EU-ETS GHG 
emissions lead to
- 1,000 DALYs/a
- 500 million € SW/a
SW, SH
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Emitter 2:
1 % of EU-ETS GHG
emissions lead to
- 100 DALYs/a
- 50 million € SW/a

Emitter 3:
5 % of EU-ETS GHG
emissions lead to
- 500 DALYs/a
- 250 million € SW/a
The regional scope
 Global scope would mobilize the most efficient
activities
 Flows to developing countries could be counted
as part of the Copenhagen/Cancun pledges
 If adaptation benefit for EU is to be maximized,
scope should be restricted to the EU
 Increases costs to covered units
 Compromise: Maximum import threshold
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Audit requirements
 Independent auditors
 Validation of project documentation regarding
assumptions
 Politically agreed climate models
 Projection of autonomous development of property
value
 Regionally appropriate discount rates
 Verification at least every 5 years on the basis of
standardized monitoring reports
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Challenges for an Adaptation
Market Mechanism
 Allocating targets might be a highly political process
without precise knowledge about future impacts of
climate change
 Under uncertain climate change projections, a
consistent estimate of the level of adaptation units
across adaptation projects of strongly differing design
and lifetime is difficult -> might lead to inefficient
spending
 Assessment of the prevention of climate impacts
through technological intervention may be difficult
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More food for thought…
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Thank you!
Perspectives GmbH
University of Zurich
Axel Michaelowa
[email protected]
[email protected]
www.perspectives.cc · [email protected]