Transcript Folie 1 - UNFCCC
CDM baseline standardization – key policy questions
Axel Michaelowa Center for Comparative and International Studies (CIS), University of Zurich and ETH Zurich; Perspectives
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
Critical
0.85
level
0.8
of HDI
0.75
HDI 0.7
0.65
0.6
0 2 Source: Michaelowa and Michaelowa (2009) 4 6 8 10 t CO2/capita China Korea Singapore Malaysia Hong Kong Ireland Israel Portugal Spain
What can be standardized?
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Use of pre-defined applicable to values / many projects at once
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Baseline setting Additionality determination parameters Criteria, emission factors, calculation methods, equations, models feeding into baseline methodologies
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Across
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project types E.g. all electricity related projects
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Within individual project types
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E.g. benchmark for N 2 O from adipic acid
Why standardization?
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Administrative improvements
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to the CDM: Increased efficiency of registration process
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Greater objectivity , consistency and predictability Reduced transaction costs Increased project flow
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Broader systemic
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Guaranteeing integrity improvements: and improving
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Improved distribution project types environmental across host countries and
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Trade-offs between these goals??
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Careful implementation and regulatory oversight !
Potential risks
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Subjectivity is not really eliminated, but shifted from project registration process to the baseline setting stage
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One off decision , difficult to reverse Gaming with standard setting can lock in too lenient baselines / non-conservative parameters
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High costs for public especially if frequent updating
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Aggregation level
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is crucial Too high: risk for environmental integrity, and of reaching all mitigation potential
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administrations Too low: data confidentiality issues ,
Types of standards
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Emissions intensity
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benchmarks (add. /bl.) X t CO 2 / amount of product or service Homogeneous products, large number of entities, normal performance distribution
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Technology /
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practice standards Average of top X % performance Reference technology that is Project technology that is (add./bl.) common practice highly innovative
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Market penetration
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rates (add.) X percentage of installed capacity Economies of scale and learning are important
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Model (add/bl)
Types of standards II
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Deemed savings
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defaults (emission reduction) X t CO 2 reduced per installation and year Requires good understanding of usage patterns
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Utilization
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defaults (add.) X % plant load factor / x hours average daily use Limited variability of parameters load factor influencing plant
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Positive lists
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Technology (add.) 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 e.g tCO 2 output / t Aggregation level Stringency level Updating frequency Process?
Product or service?
Vintage?
Geographic area?
Average?
Best 20%?
Best used?
Best available?
Fixed improvement factor?
According to data?
Decision on stringency
Emission intensity (tCO 2 / t output) A Plants B C D CERs Baseline benchmark Additionality benchmark
Greenfield vs brownfield
Share New plants Existing plants Efficiency
Share
Vintages count!
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 (1) Definition of the system boundary (2) Identification of key performance indicator (3) Selection of peers for comparison (Choice on the aggregation level) Data collection Choice of MRV procedures Data collection (Monitoring, Reporting, Verification) 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
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 (1) Definition of the system boundary Data collection Choice of MRV procedures (2) Identification of key performance indicator (3) Selection of peers for comparison (Choice on the aggregation level)
Benchmark development II
Data collection (Monitoring, Reporting, Verification) 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
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Which sectors and project types should be prioritized for standardization?
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Highly homogeneous , large-scale industries?
Small, dispersed emissions sources?
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How stringent should standardized approaches be to guarantee a sufficiently high environmental integrity?
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More stringent than project-based approaches?
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What lessons can be drawn from of standardization existing use in offset programmes?
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Role of experts?
US programmes (CAR, RGGI, CCX)
Policy questions
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Who should administer standardized methodologies?
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CDM EB?
Project developers?
and develop Should there be a Baseline Standard rulebook ?
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How can we
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prioritize countries and regions?
Underrepresented regions?
Regions with highest potential?
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How can DNAs be enabled to decide whether to apply standardized baselines?
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Capacity building required Can distortions be prevented?