Download The Challenge of Adapting to Climate in a Changing World

Developing Baseline Socioeconomic
Scenarios for V&A Assessments
Consultative Group of Experts on National Communications from Parties not
Included in Annex I to the UNFCCC (CGE)
Hands-on Training Workshop on Vulnerability and Adaptation for Asia and
Pacific Countries
20~24 March 2006
Jakarta, Indonesia
Xianfu Lu
National Communications Support Programme (NCSP), UNDP-UNEP-GEF
[email protected]
1A.1
In the next 45 minutes or so…
• Introduction: what are baseline socio-economic
scenarios and why do we need them?
• Procedures for developing socio-economic
scenarios: how to develop socioeconomic scenarios?
• Guidance documents, and data sources
• Examples
1A.2
Introduction:
what are baseline socio-economic scenarios?
• Socio-economic scenarios are plausible, and often
simplified, representation of future state of socioeconomic parameters, i.e., they are neither
predictions nor forecasts;
• Baseline socio-economic scenarios are scenarios
that do not account for the effects of climate
change.
1A.3
Introduction:
why do we need baseline socio-economic
scenarios?
Increasing demand for policy relevant
information has led to the growing consideration
of multiple stressors and drivers in V&A
assessments.
1A.4
Introduction:
why do we need baseline socio-economic
scenarios? (continued)
V&A assessments suffer from serious weakness if
by default they assume that the projected
climates will take place in a world with a society
and economy similar to today.
1A.5
Introduction:
why do we need baseline socio-economic
scenarios? (continued)
Features about the socio-economic future that have
a bearing on our response to climate change. They
affect:
• Availability of resources to cope with climate change
• The administrative quality of future governments
• Ability of special interest groups to influence the
public agenda
1A.6
Introduction:
why do we need baseline socio-economic
scenarios? (continued)
Interactions between society/economy
and climate impacts and adaptation is
that socio-economic developments can
make the world more or less vulnerable
to the impacts of climate change.
1A.7
Introduction:
why do we need baseline socio-economic
scenarios? (continued)
• Flooding events may be worse if there is a larger population
living on the flood plain as a result of planning decisions.
• The effect of climate change on crop yields will depend on
how many farmers have planted the crops, whether their
farm income is dependent on that crop, in turn depending
on agricultural subsidies, access to technology and so on.
• Some technological developments, such as improvement of
weather forecasting, may better enable precautions to be
taken to diminish vulnerability to extreme weather events.
1A.8
Introduction:
why do we need baseline socio-economic
scenarios? (continued)
• Flooding events may be worse if there is a larger population
living on the flood plain as a result of planning decisions.
• The effect of climate change on crop yields will depend on
how many farmers have planted the crops, whether their
farm income is dependent on that crop, in turn depending
on agricultural subsidies, access to technology and so on.
• Some technological developments, such as improvement of
weather forecasting, may better enable precautions to be
taken to diminish vulnerability to extreme weather events.
1A.9
Procedures for developing socioeconomic scenarios
If you think the task of developing climate scenarios
is difficult, the job of generating socio-economic
scenarios is even more complex.
Due to the fast changing, and poorly understood
interactions of factors operating within socioeconomic systems, it is not possible to construct
socio-economic scenarios on the same long-term
time-scales as climate scenarios.
1A.10
Procedures for developing socioeconomic scenarios – general approach
NOT every scenario exercise has to go through all the steps.
Efforts could be saved by making use of existing elements of
scenarios.
1A.11
Procedures for developing socio-economic
scenarios: identify drivers
• Key factors that define impacts, vulnerability and
adaptive capacity;
• Often not directly measurable (e.g., social
wellbeing, quality of governance, etc.)
• Wide stakeholder participation required
1A.12
Procedures for developing socio-economic
scenarios: develop narrative storylines
• Qualitative and holistic portraits of the general
structure and values of society;
• Conditions resulting from economic and social
policies, human reproduction, occupations, and use
of energy and technology;
• Major national and regional development policy and
plans to be consulted;
• Stakeholders to be widely engaged
1A.13
Procedures for developing socio-economic scenarios:
identify indicators
• Most relevant measurements of the key factors
that define impacts, vulnerability and adaptive
capacity;
• Indicators to be quantifiable;
• Wide stakeholder participation required
1A.14
Procedures for developing socio-economic
scenarios: develop narrative storylines
• Qualitative and holistic portraits of the general
structure and values of society;
• Conditions resulting from economic and social
policies, human reproduction, occupations, and use
of energy and technology;
• Major national and regional development policy and
plans to be consulted;
• Stakeholders to be widely engaged
1A.15
Procedures for developing socio-economic
scenarios: project indicators/parametres
• Model simulation (e.g., SRES);
• Analogues;
• Expert judgement
1A.16
Baselines for Bangladesh
“Best Guess” Macro Projections for Bangladesh
Population (millions)
1998
2020
2050
124
168
218
a
GDP (billions)
$28.6
$72.2
$180.0
GDP/capita
$220
$430
$825
a. 1995 value.
Source for 1998 data: WRI, 1998.
Optimistic Macro Projections for Bangladesh
1998
2020
2050
124
165
165
GDP (billions)
$28.6a
$206.3
$1,485.0
GDP/capita
$220
$1,250
$9,000
Population (millions)
a. 1995 value.
Source for 1998 data: WRI, 1998.
1A.17
Vulnerability Indicators
Vulnerability Indicators for 2020
1998
Bangladesh
Analogue Country
2020 Best Guess
for Bangladesh
2020 Optimistic
for Bangladesh
Pakistan
Kazakhstan
GDP/Capita
$240
$460
$1330
% of Economy in Agriculture
30%
25%
12%
58
64
68
% Pop. with Access to Health Care
45%
55%
Not available
Literacy
38%
39%
98%
Life Expectancy in Years (1995-2000)
Sources: WRI, 1998; literacy rates from CIA, 1998.
Vulnerability Indicators for 2050
1998
Bangladesh
Analogue Country
2050 Best Guess
for Bangladesh
2050 Optimistic
for Bangladesh
Bolivia
South Korea
GDP/Capita
$240
$800
$9,700
% of Economy in Agriculture
30%
17%
8%
Life Expectancy (1995-2000)
58
62
73
% Pop. with Access to Health Care
45%
67%
100%
Literacy
38%
83%
98%
Sources: WRI, 1998; literacy rates from CIA, 1998.
1A.18
Procedures for developing socio-economic
scenarios: criteria
• Relevance - applicable to public and private
sector decision-making
• Consistency- based on coherent assumptions;
• Credibility - not over-estimating the rate of
change;
• Transparency – explicit account of assumptions
1A.19
Example:
the IPCC SRES Scenarios
• IPCC Special Report on Emission Scenarios (SRES)
•
•
•
•
makes projections about emissions of GHGs and aerosols
up to 2100 for the purpose of modelling climate change;
The world divided into four macro-regions (ALM, ASIA,
REF, OECD90);
Six modelling teams (6 modelling teams: AIM, ASF,
IMAGE, MARIA, MESSAGE, MiniCAM)
Open process;
“Storyline-and-Simulation” approach
1A.20
Example:
the IPCC SRES Scenarios – the process
•
•
•
•
•
Scoping and planning;
Identify drivers;
Formulate narrative storylines;
Quantify storylines using models;
“Open” review process
1A.21
Example:
the IPCC SRES Scenarios – guiding principles
•
•
•
•
No ‘business as usual’ scenario
No probabilities ascribed
No climate policy assumed
No adaptation assumed
1A.22
Example:
the IPCC SRES Scenarios – principal drivers
•
•
•
•
Population growth
GDP growth
Energy and technological change
Land-use change
1A.23
Example:
the IPCC SRES Scenarios – the storylines
Four quadrants along
two axes
• Governance
•
(autonomy vs
interdependence);
Aspiration/value
(consumerism vs.
community)
1A.24
Example:
the IPCC SRES Scenarios – the storylines
Four distinctive future worlds depicted
by the four storylines…
1A.25
Example:
the IPCC SRES Scenarios – the storylines
A1: rapid economic growth, low population growth,
rapid adoption of new technologies, convergence
of regions, capacity building, increased social
interaction, reduced region differences in per
capita income;
A2: heterogenous world, self-reliance and local
identities preserved, high population growth,
regionally-specific economic growth, fragmented
economic and technological development
1A.26
Example:
the IPCC SRES Scenarios – the storylines
B1: convergent world with low population growth,
transition to service and info economy, resource
productivity improvements, clean technology
towards global solutions
B2: Divergent world with emphasis on local solutions
to economic, social and environmental
sustainability, moderate population growth,
intermediate levels of economic growth, less rapid
technological change
1A.27
Example:
the IPCC SRES Scenarios – the scenarios
1A.28
Example:
the IPCC SRES Scenarios – the scenarios
1A.29
Example:
Developing socio-economic scenarios for V&A assessment
in water resource sector (Indonesia)
• Key drivers: level of water demand in the 21st Century
• Storylines: SRES A2 and B2
• Indicators:
o population change rate;
o GDP growth rate
o level of development of domestic water resources
o Water withdrawal per capita
1A.30
Example:
Developing socio-economic scenarios for V&A assessment
in water resource sector (Indonesia)
Step 1: Derive estimates of population and GDP
changes from SRES (or other sources) in relation to
base year (1990)
2010
2020
2030
2040
2050
Population change
36
54
72
90
106
Population change
32
47
59
69
77
GDP change
121
292
521
828
1207
GDP change
121
335
635
1150
1750
1A.31
Example:
Developing socio-economic scenarios for V&A assessment
in water resource sector (Indonesia)
Step 2: Estimate level of development of domestic
water resources
2010
2020
2030
2040
2050
Level of development of
domestic water resources
2.90
5.57
6.07
7.13
17.4
Level of development of
domestic water resources
2.90
5.39
5.77
6.54
23.20
L
Withdrawal
Re sources
L1990  2.9
Lt  L1990  ( L2050  L1990 )  (GDPr , 2050  GDPr ,1990 )
1A.32
Example:
Developing socio-economic scenarios for V&A assessment
in water resource sector (Indonesia)
Step 3: Estimate annual water withdrawal
2010
2020
2030
2040
2050
Annual water withdrawal
158.09
172.25
202.28
299.46
493.81
Annual water withdrawal
153.03
163.73
185.64
274.34
658.42
Withdrawal  L * resources
(Re sources1990  2838km )
3
1A.33
Example:
Developing socio-economic scenarios for V&A assessment
in water resource sector (Indonesia)
Step 4: Estimate per capita water withdrawal
2010
2020
2030
2040
2050
water withdrawal per capital
563.45
542.17
570.05
763.98
1161.97
water withdrawal per capital
561.97
539.90
565.95
786.87
1803.13
Withdrawal percapita  Withdrawal 109  Population
( Population2000  206.3  10 6 )
1A.34
Guidance documents
1.
Guidelines on the use of scenario data for climate impact and adaptation
assessment (http://ipcc-ddc.cru.uea.ac.uk/guidelines/ggm_no1_v1_12-1999.pdf)
2.
Developing Socio-Economic Scenarios for Use in Vulnerability and Adaptation
Assessments
(http://www.undp.org/cc/pdf/publications%20and%20flyers/SES_draft.pdf)
3.
Socio-economic scenarios for climate change impact assessment: a guide to their
use in the UK
(http://www.ukcip.org.uk/resources/publications/pub_dets.asp?ID=34)
4.
Special Report on Emissions Scenarios: A Special Report of Working Group III of
the Intergovernmental Panel on Climate Change
(http://www.grida.no/climate/ipcc/emission/index.htm)
1A.35
Data Sources: The World Bank
1A.36
Data Sources: The World Bank
1A.37
Data Sources: UNDP (Human Development Report)
1A.38
Data Sources: IPCC Data Distribution Centre
1A.39
A Few Concluding Thoughts
•
Remember that creating baseline scenarios is NOT an end
in itself; So,
•
•
Do NOT get consumed by them;
•
Try to focus on the socioeconomic variables to which the
vulnerability of interest is most sensitive.
Perhaps a simple comparison exercise between constant
socioeconomic conditions and a changing socioeconomic
future can provide much insight;
1A.40