Folie 1 - UNFCCC

Report
CDM baseline standardization
– key policy questions
Axel Michaelowa
Center for Comparative and International Studies (CIS),
University of Zurich and ETH Zurich; Perspectives
[email protected], [email protected]
Joint Workshop, Bonn, March 13, 2011
Harnessing emissions
reduction potential
CDM
CDM
CDM



CDM

CDM
CDM


CDM

Source: IPCC (2007)
Potential 2030, bottom-up studies
Preventing
emissions take-off
0.95
0.9
China
Critical 0.85
level
0.8
of HDI
Korea
Singapore
Malaysia
Hong Kong
Ireland
0.75
Israel
HDI
Portugal
0.7
Spain
0.65
Source: Michaelowa and Michaelowa (2009)
0.6
0
2
4
6
8
10 t CO2/capita
What can be standardized?
• Use of pre-defined values / parameters
applicable to many projects at once
•
•
•
Baseline setting
Additionality determination
Criteria, emission factors, calculation methods,
equations, models feeding into baseline
methodologies
• Across project types
•
E.g. all electricity related projects
• Within individual project types
•
E.g. benchmark for N2O from adipic acid
Why standardization?
• Administrative improvements to the CDM:
•
•
•
•
Increased efficiency of registration process
Greater objectivity, consistency and predictability
Reduced transaction costs
Increased project flow
• Broader systemic improvements:
•
•
Guaranteeing and improving environmental
integrity
Improved distribution across host countries and
project types
•Trade-offs between these goals??
•
Careful implementation and regulatory oversight !
Potential risks
• Subjectivity is not really eliminated, but shifted
from project registration process to the baseline
setting stage
•
•
One off decision, difficult to reverse
Gaming with standard setting can lock in too
lenient baselines / non-conservative parameters
• High costs for public administrations,
especially if frequent updating
• Aggregation level is crucial
•
•
Too high: risk for environmental integrity, and of
reaching all mitigation potential
Too low: data confidentiality issues
Types of standards
• Emissions intensity benchmarks (add. /bl.)
• X t CO2 / amount of product or service
• Homogeneous products, large number of entities,
normal performance distribution
• Technology / practice standards (add./bl.)
•
•
•
Average of top X % performance
Reference technology that is common practice
Project technology that is highly innovative
• Market penetration rates (add.)
•
•
X percentage of installed capacity
Economies of scale and learning are important
• Model (add/bl)
Types of standards II
• Deemed savings defaults (emission reduction)
• X t CO2 reduced per installation and year
• Requires good understanding of usage patterns
• Utilization defaults (add.)
•
•
X % plant load factor / x hours average daily use
Limited variability of parameters influencing plant
load factor
• Positive lists (add.)
•
•
Technology
Applicable if no other revenues than CERs or if
technology clearly faces a cost gap to alternative
technologies providing the same service
Key issues for benchmarks
Type of
benchmark
Aggregation
level
Stringency
level
Updating
frequency
e.g tCO2 / t
output
Process?
Average?
Product or
service?
Best 20%?
Fixed
improvement
factor?
Vintage?
Geographic
area?
Best used?
Best available?
According to
data?
Decision on stringency
Emission intensity
(tCO2 / t output)
Plants
A
C
B
D
CERs
Baseline
benchmark
Additionality
benchmark




Greenfield vs brownfield
New plants
Share
Existing plants
Efficiency
Vintages count!
Share
40 year-old plants
5 year-old plants
Efficiency
Technology shifts
Benchmark development
Initial feasibility study for the CDM benchmarking:



How large is the expected emission reduction potential for a benchmarking-based
CDM?
What is the level of complexity expected?
Which efforts are needed regarding the data collection?
Decision on whether to develop a benchmarking based CDM for the sector/product
Development of the benchmarking approach
Data collection
(1) Definition of the system boundary
Choice of MRV procedures
(2) Identification of key performance indicator
(3) Selection of peers for comparison
(Choice on the aggregation level)
Data collection
(Monitoring, Reporting,
Verification)
(3) Selection of peers for comparison
(Choice on the aggregation level)
(Monitoring, Reporting,
Verification)
Benchmark development II
Selection of the stringency level
(1) Preliminary choice on stringency level
(2) Evaluation of the impact
(3) Decision on stringency levels
Approval of the CDM benchmarking:

Approval of benchmarking approach


Approval of the data adequacy
Approval of selected stringency level
Policy questions
• Which sectors and project types should be
prioritized for standardization?
•
•
Highly homogeneous, large-scale industries?
Small, dispersed emissions sources?
• How
stringent
should
standardized
approaches be to guarantee a sufficiently high
environmental integrity?
•
•
More stringent than project-based approaches?
Role of experts?
• What lessons can be drawn from existing use
of standardization in offset programmes?
•
US programmes (CAR, RGGI, CCX)
Policy questions
• Who
should
administer
standardized methodologies?
•
•
•
and
develop
CDM EB?
Project developers?
Should there be a Baseline Standard rulebook?
• How can we prioritize countries and regions?
•
•
Underrepresented regions?
Regions with highest potential?
• How can DNAs be enabled to decide whether
to apply standardized baselines?
•
•
Capacity building required
Can distortions be prevented?

similar documents