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

Thank You