Break out session: Impact assessment of policies and actions

Asia Pacific and Eastern Europe Regional Workshop on Nationally Appropriate

Mitigation Actions

12-14 June 2015, Derag Livinghotel Kanzler, Bonn

Marion Vieweg-Mersmann, Programme Officer, International Consultation and Analysis Support Unit, Non-Annex I Support Sub-programme, Mitigation, Data and Analysis Programme

Outline

• The WRI Policy and Action Standard in more detail (20 min)

• Exercise: Cookstove initiative in Ethiopia (30 min)

• Report back from exercise and discussion (20 min)

• Quantification of the cookstove initiative: next steps and limitations (20 min)

Identifying effects and mapping the causal chain

Understanding inputs and activities is a means to understanding which effects are expected to occur

Inputs, activities, and effects

• Inputs: Resources that go into implementing a policy or action, such as

financing

• Activities: Activities involved in implementing the policy or action (undertaken by

the authority or entity that implements the policy or action), such as permitting,

licensing, procurement, or compliance and enforcement

• Intermediate effects: Changes in behavior, technology, processes, or practices

that result from the policy or action

• GHG effects: Changes in GHG emissions by sources and removals by sinks that

result from the intermediate effects of the policy or action

• Non-GHG effects: Changes in relevant environmental, social, or economic

conditions other than GHG emissions or climate change mitigation that result from

the policy or action

Types of effects

• Different types of effects can be described, based on the point of view taken:

a) By geopolitical boundary: in-jurisdiction/out-of-jurisdiction

b) By time frame: short- and long term

c) By objectives: intended and unintended

d) By probability: likely, possible, and unlikely

e) By sign of expected GHG effect: GHG increasing / decreasing

• Individual effects usually fall into more than one of these categories

Suggestion on how to identify effects by type

Indicator types Short-term Long-term

Intended effects

Unintended effects (Including rebound effects)

Out-of-jurisdiction effects (Leakage and spillover effects)

Example: Types of effects

Indicator types Short-term Long-term

Intended effects

• Reduced emissions from private transport due to shift to public transport

• Increased emissions from public transport due to higher use

• Reduced emissions from densification of urban areas close to the BRT corridors

Unintended effects (Including rebound effects)

• Increased emissions from construction

• Increased emissions from manufacturing construction materials

• Increased emissions from congestion during construction

• Reduced emissions from private transport due to reduced congestion

• Increased emissions (rebound) caused by the reduction in congestion which incentivizes people to change back to private transport

Out-of-jurisdiction effects (Leakage and spillover effects)

• Increased emissions from manufacturing construction materials

The causal chain concept

• A causal chain is a conceptual diagram tracing the process by which the policy or action

leads to GHG effects through a series of interlinked logical and sequential stages of

cause-and-effect relationships.

• Mapping the causal chain can help identify additional effects not previously identified.

• It helps to structure and understand cause-effect relationships.

• Developing and reporting the causal chain is required to be in conformance with the

standard.

Two ways to get to first stage effects

Including inputs and activities Directly from the policy

Two main direct effects:

• Increased installation of insulation

• Increased production of insulation material

Example for a causal chain: Home insulation subsidy

Intended intermediate effect

Unintended intermediate effect

Unintended GHG effect

Example for a causal chain: Home insulation subsidy

Intended intermediate effect

Intended GHG effect

Unintended intermediate effect

Example for a causal chain: Home insulation subsidy

Example for a causal chain: Home insulation subsidy

Determine significance of effects

Based on the assessment of likelihood and magnitude the significance of effects can be

determined, following the guidance shown in the table below

MagnitudeLikelihood

Minor Moderate Major

Very likely

May be excludedShould be includedLikely

Possible

Unlikely

Very unlikely May be excluded

Example of assessing each effect by gas

Define the assessment period

• The timeframe for the baseline scenario refers to the period over which emissions are

projected.

• The start year can depend on:

a) Availability of data

b) Objective of the assessment

c) Starting point of implemented or planned mitigation activities

• The end year can depend on:

a) The time frame set for a goal

b) The time frame set for mitigation actions

c) Political cycles

d) Internationally relevant points in time

e) Availability of reliable data projections for key assumptions

Exercise

• Split into groups of 4-5

• Nominate a facilitator (also responsible for time keeping!)

• Nominate a rapporteur

• 30 minutes for group work

• 20 minutes for report back and discussion

Typical steps for estimating GHG effects

• Some steps may also be carried out in reversed order or in parallel rather than in

sequence

• Whatever the sequence of steps is chosen, each step should be completed and

separately reported

Drivers and parameters

• Parameters, i.e. variables in the calculation, are affected by drivers: Socioeconomic or

other conditions or other policies that influence the level of emissions or removals.

• Drivers that affect emissions activities are divided into two types:

a) Policies; and

b) Non-policy drivers.

• For the baseline all policy and non-policy drivers should be considered that are significant

and to the extent that they are not related to the mitigation actions that are proposed.

Relationship between sources/sinks, methods and parameters

• Emission estimation methods for different types of sources may differ

• Each method contains a number of relevant parameters for calculation

• Policy and non-policy drivers influence parameter values

• GHG effects/sources to be estimated (from previous example):

• Task: Estimate baseline scenario emissions for each of the three GHG effects/sources

Estimating baseline emissions

Step 1: Method

• Step 1: Define an emissions estimation method and all parameters to calculate baseline emissions for each source or sink

 Baseline emissions for cooking with inefficient wood stoves in 2020 (t

CO2e) =

baseline fuel wood use (t) x baseline emission factor (t CO2e/t)

Step 2: Baseline values

• Step 2: Determine baseline values for each parameter by identifying policy and non-policy drivers and assumptions for each driver

• Baseline fuel wood use in 2020: 1,000,000 t

– E.g. based on current fuel wood use per capita and population projections

• Baseline emission factor: 1.513 t CO2 / t

– E.g. based on FAO data, data from regional studies, country specific data

Step 3: Estimating baseline emissions

 Baseline emissions for cooking with inefficient wood stoves in 2020 =

1,000,000 t x 1.513 t CO2/t

= 1,513,000 t CO2

Identifying affected parameters for ex-ante analysis

• For GHG sources or sinks not affected by the policy or action:

a) Use baseline values

• For GHG sources or sinks that are affected by the policy or action, estimate policy

scenario values based on:

a) Historical trends in relevant parameters

b) How implementation of the policy or action is expected to change during the GHG

assessment period

c) Interactions with implemented or adopted policies included in the baseline

scenario

d) Barriers to policy effectiveness

e) Sensitivity of parameters to assumptions

Estimating policy scenario values for parameters

Estimating policy scenario parameter values

• In our example only one parameter changes: Fuel wood use in 2020

• Policy scenario fuel wood use in 2020: 600,000 t

– E.g. based on literature, pilot studies, in-country studies

Estimating policy scenario emissions

Policy scenario emissions for cooking with inefficient wood stoves in 2020

=

600,000 t x 1.513 t CO2/t

= 907,800 t CO2

Estimating emission reductions

Baseline emissions - policy scenario emissions =

1,513,000 t CO2 - 907,800 t CO2

= 605,200 t CO2