decision making analysis for climate change actions dd ... resili… · objectives &...
TRANSCRIPT
DD / MM / YY
Decision Making Analysis for
Climate Change Actions
Climate change action planning process
and its key components
Source: UNFCC (2011)
ASSESSMENT
PLANNINGMONITORING AND
EVALUATION
IMPLEMENTATION
EX-ANTE
EX-POST
Climate Change Planning Cycle
Assessment
Decision Support and
Assessment Tools for
Climate Change
• Cost Benefit Analysis (CBA)
• Cost Effectiveness Analysis (CEA)
• Multiple Criteria Analysis (MCA)
Cost Benefit Analysis (CBA)
CBA: Background
• Economics
• Finance
• Project appraisal
CBA: Main Steps
Define project(s),
policy(ies)
Identify likely impacts
Quantify likely impacts
Monetize impacts –
express in Costs and Benefits
Compare
Costs and Benefits
• Economics of climate change
• Climate policy modeling
• Mitigation
• Adaptation
CBA: Climate Related
Issues
CBA: 4 structural elements
• benefit schedule
• cost schedule
• time horizon
• discount rate
1 Euro today is worth more than 1 Euro tomorrow
Present Value (of money)
Today Tomorrow
WHY?
• Uncertainty
• Inflation
• Investment opportunities
• Consumption today vs future consumption
Present Value Concept
Discounting: = process to obtain the present value of future Euro amounts
0 ttime
present value future value
Euro
Present Value Concept
PV = present value, FV = future value, r = discount rate, and t is the number of
periods into the future.
1*
1t
PV FV wherer
CBA criteria
• Net Present Value (NPV)
• Benefit-Cost Ratio (BCR)
Choice of discount rate
time horizon in years
Discount rate 25 50 100 200
2 60.95 37.15 13.80 1.91
4 37.51 14.07 1.98 0.04
6 23.30 5.43 0.29 0.0009
8 14.60 2.13 0.05 0.00002
The Present Values of 100 Euros
CBA strengths
• Proven, widely used
• Project, policy specific
• Good on quantitative comparisons
CBA Limitations
• Resource intensive
• Non market C-B
• Discount rate
• “Objective”
• Distribution of C-B
Cost Effectiveness
Analysis (CEA)
CEA: Background
• Economics
• Health research
• Energy research
CEA: Main
Characteristics
• Target oriented
• Two criteria
• Costs in monetary terms
• Benefits quantified but not monetized
CEA: Climate Related
Issues
• Marginal abatement cost curves (MACs) –
Mitigation
• Marginal Adaptation Cost curves
CEA: Main steps
Define Objective -Target
Identify measures
Estimate effectiveness
Estimate Costs
Rank measures
Adaptation Cost Curve
CEA: Strengths
• Consideration of budget
constraints
• Benefits in other metric than
monetary
CEA: Strengths
• Resource intensive
• Only two criteria (parameters)
• Extensive data collection
Multiple Criteria Analysis (MCA)
MCA: Background
• Decision analysis
• Management science
Structural elements
of MCA
• Multiple Alternatives (at least two)
• Multiple – and often conflicting- Criteria
• Policy makers or multiple stakeholders
MCA: Climate related
issues
• NAPAs and NAMAs
• TNAs
• Adaptation benefits
• Assessment of climate abatement
technologies
MCA:
Main steps
Define Alternatives
Define criteria/objectives
Quantify impacts or
assign scores
Normalize scores
Weight evaluation criteria
Rank options
Define alternatives and evaluation criteria
Alternative A Alternative B Alternative C Alternative D
Criterion 1
Criterion 2
Criterion 3
Criterion 4
Criterion 5
Criterion 6
ObjectiveRank
Cost
Safety
Comfort
2
Alternative
#2
Alterntive
#1
$13,000 $10,000
2 6
Low- 2.5ft leg room
- 5.5ft head
room
- hard seats
Moderate- 3ft leg room
- 6ft head room
- hard seats
Alternative
#3
Alternative
#4
$12,000 $11,000
6 6
High- 3.5ft leg room
- 6ft head room
- hard seats
Low- 2.5ft leg room
- 5.5ft head
room
- hard seats
($)
(# of
airbags)1
(Index)
2
3
0
1
Is it worth $1,000
for ½ ft of leg room?
This is the Framework
Objectives & decision-making
• Establishes the structure
• Ask: What is important?
• Separates people from the problem,
issues from emotions
• Categorize (Environment, Economic &
Social)
Action 2
•Actions
•Alternatives
•Options
Indicator
• Predictive
• Specific
• Understandable
• Practical (available resources)
Action 1 Action 3
Multi Criteria Analysis evaluation
Area of
concern
Criteria Indicators highway 2 lane
road
train
Economic
effects
Cost Total cost (mln. $) 200 250 500
Accessibility Travel time (---
/+++)
+++ ++ +
Capacity Passengers
(mln/km/yr)
30 20 40
Environmental
impacts
Climate
Change
CO2 emissions
(tons/yr)
1000 750 100
Landscape Visual intrusion (---
/+++)
--- -- -
Train
2lanes
High.
Impact
assessment
Normalization: translating different units to one
common scale
1
0maxmin
0.6
benefitcosts
Facts
Valuation
of facts
Value functions
Weighting of criteria
• How more important is x criterion than the y criterion? (pairwise)
• Assign 100 points to criteria based on their relative importance (direct)
Aggregation:
Weighted summation
)()( pvwpV j
j
j
Aggregation to ranking of alternatives with
weighted summation
Rank concern weight
1 Capacity 0.36
CO2 0.36
2 Cost 0.16
3 Travel time 0.06
Landscape 0.06
concern highway 2 lane Train
Capacity 0.5 0 1
CO2 0 0.28 1
Cost 1 0.83 0
Travel time 1 0.67 0.33
Landscape 0 0.33 0.67
Weights Value functions
concern weight x stand.
score
Total
Capacity 0.36 x 0.5 0.18
CO2 0.36 x 0 0
Cost 0.16 x 1 0.16
Travel time 0.06 x 1 0.06
Landscape 0.06 x 0 0
WEIGHTED SUM highway 0.4
0.78
0.4
0.29
TR
AIN
HIG
HW
AY
2 L
AN
E
RANKING
Opportunities
• Allows multiple perspectives – views
• Incorporates different measurement
scales
• Provides transparency and structure
• Triggers discussion between
stakeholders and knowledge generation
Challenges
• High degree of subjectivity
• Difficult to reach consensus on weights
of criteria
• Risk of double counting
Adaptation Decision Matrix
Combination of MCA and CEA
Result
Options
Benefit
1
Benefit
2
Benefit
3
Benefit Index
Costs
A
B
C
D
E
F
Choice?Alternatives
Costs and benefits
monetized?
YES
CBA
NO
Costs monetized,
benefits quantified?
YES
CEA
NO
Impacts not monetized
but quantified?
YES
MCA
Tools Technical
Capacity
Data Needs Time Cost $ Participant
Requirements
CBA
CEA
MCA
= Low Requirements ; = Medium Requirements
= High Requirements; = Very High Requirements
Comparison of Tools Requirements
Source: UN-HABITAT
Source: UN-Habitat (2014)
Applications
CBA CEA MCA
High Income
Mitigation
Adaptation
Mid - Low Income
Mitigation
Adaptation
Selection of cases
Studies characteristics
Year Author Country Assessment
Method
Level Sectoral
coverage
Scope
1 2009
Environment
Agency (UK) in
UNFCC United Kingdom CBA Local
Flood
management Urban
2 2011
Practical Action
in UNFCC Nepal CBA Local
Disaster
management Rural
3 2006
Kouwenhoven P.,
Cheatham, C (in
UNFCC) Pacific Islands CEA Local
Water
management Rural
4 2010 ECA Group South Florida
CEA (partial
CBA) Local
Hurricane/Sea
Level Rise Urban
5 2011 Haque et al Bangladesh MCA Local
Flood
management Urban
6 2008
Chowdury and
Rahman Bangladesh MCA Local
Flood
management Urban
Cases Method Adaptation Process Level Funding Source
Environment Agency; UK (Redcar)
CBA Ex-Ante LOCAL (CITY) NATIONAL(Environmental Agency)
Practical Action;Nepal (group of communities)
CBA Ex-Post LOCAL (COMMUNITY)
INTERNATIONAL DONOR(DFID)
Kouwenhoven P., Cheatham, C; Pacific Islands(several islands)
CEA Ex-Post LOCAL (COMMUNITY)
INTERNATIONAL DONOR(CIDA)
ECA Group; SouthFlorida (several cities)
CEA Ex-Ante LOCAL (REGIONAL) PRIVATEINTERNATIONAL DONORS , BANKS
Haque at al;Bangladesh (Dhaka)
MCA Ex-Ante LOCAL (CITY) RESEARCH FUND, National Government
Chowdury and Rahman;Bangladesh/Sylhet
MCA Ex-Ante LOCAL (CITY) RESEARCH FUND, Local Government
Further Characteristics
Sources & Literature
• United Nations Framework Convention on Climate Change (UNFCCC) (2002), A Guide to the Climate Change Convention and its Kyoto Protocol.
• UNFCCC (2012), Assessing the costs and benefits of adaptation options: An overview of approaches, http://unfccc.int/files/adaptation/nairobi_work_programme/knowledge_resources_and_publications/application/pdf/2011_nwp_costs_benefits_adaptation.pdf
• ECA (2011), Shaping climate resilient development, http://www.clintonglobalinitiative.org/media/Shaping_Climate_Resilent_Development.pdf
• Stern, N., (2007), The Economics of Climate Change: The Stern review, Cambridge, UK
• Haque, A., Grafakos, S., and Huijsman, M., (2011), Assessment of adaptation measures against flooding in the city of Dhaka, Bangladesh, Environment and Urbanization Vol. 24 (1),1:17
• Grafakos, S. and Olivotto, V., (2012), Choosing the right adaptation assessment method, ICLEI resilient cities congress, http://resilient-cities.iclei.org/fileadmin/sites/resilient-cities/files/Resilient_Cities_2012/Program_Updates/Grafakos_and_Olivotto.pdf
• Siemens, (2010), Sustainable urban infrastructure: A London edition - a view to 2025
• Siemens, (2007), Sustainable Urban Infrastructure, http://www.siemens.com/responsibility/pool/stakeholder/sustainable_cities_nur_e.pdf
Additional sources – (MCA)
• www.mca4climate.info : Multi-Criteria Analysis for climate change: developing guidance for sound climate policy planning (UNEP)
• http://unfccc.int/ttclear/pdf/TNA%20HB%20version%2028May2010.pdf: Technology needs assessment for climate change
• Yahaya, Sani, Ahmad, Noordin. and Abdalla, Rania Fadlallah (2009), “Multi criteria analysis for flood vulnerable areas in Hadejia- Jama’ Are river basin, Nigeria”, European Journal of Scientific Research, Vol42, No. 1, pages 71- 83.
• Bell, M., Hobbs, B. and Ellis, H. (2003), “The use of multi-criteria decision-making methods in the integrated assessment of climate change: implications for IA practitioners”, Socio-Economic Planning Sciences, Vol. 37, pp. 289-316.
• Shackley, S. and McLahlan, C. (2006), “Trade-offs in assessing different energy futures: a regional multi-criteria assessment of the role of carbon dioxide capture and storage”, Environmental Science and Policy, Vol. 9, pp. 376-91.
• Sutter, C. (2003), “Sustainability check – up for CDM: how to assess the sustainability of international projects under the Kyoto Protocol”, PhD thesis, Swiss Federal Institute of Technology, Zurich
• Kubal, C., Haase, D., Meyer, V. and Scheuer S. (2009), “Integrated urban flood risk assessment –adapting a multicriteria approach to a city”, Natural Hazards and Earth System Sciences, Vol 9, November, pages 1881-189
• Grafakos, S., Flamos, A., Oikonomou V., Zevgolis, D. (2010). Multi Criteria Analysis weighting methodology to incorporate stakeholders’ preferences in energy and climate policy interactions, International Journal of Energy Sector Management, Vol. 4 No. 3, pp. 434-461
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