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?