Calculating greenhouse gas (GHG) emissions reductions from projects requires construction of a hypothetical baseline that approximates emissions levels without the project. Such baselines can be project-specific, multi-project, or a hybrid of the two (Ellis and Bosi, 1999). Project-specific baselines are determined on a project-by-project basis using specific measurements or assumptions. Multi-project baselines use existing or estimated emissions levels from a defined set of actual or projected projects to derive a baseline level. The hybrid approach combines project-specific and standardized parameters to derive a baseline (Ellis and Bosi, 1999).

This paper describes a standardized multi-project baseline methodology for industrial energy-efficiency and electric power projects. For the purposes of this paper, we assume that the proposed projects have already passed an additionality test and have been accepted as qualified projects. Additionality tests are designed to ensure that a proposed project will result in actual GHG emissions reductions that would not have occurred in the absence of the project. The multi-project baselines described in this paper are then used for estimating the number of carbon emission reduction (CER) units that is earned from a project. The multi-project baseline methodology is illustrated with four case studies. Two case studies, for Brazil and China, focus on energy-efficiency projects in the cement sector. The other two case studies focus on electric power sector projects in India and South Africa.

Rationale for Use of Multi-Project Baselines

The rationale for exploring the use of multi-project baselines as an alternative to project-specific baselines is to seek a balance between ensuring environmental integrity and minimizing transaction costs while encouraging emissions reduction projects. Project-by-project baselines may have higher transaction costs than multi-project baselines, reducing the number of projects that attract investment.

Experience with other project evaluations has shown that construction of project-specific baselines is time-consuming, costly, and can be highly uncertain. Thus, the concept of standardized baselines across many projects, for particular sectors or given technologies, has emerged. These multi-project baselines can be used as an alternative to project-specific baselines depending upon the preference of the developer and/or the host country government. The aim of this paper is to explore alternative options for multi-project baselines.

Project-specific baselines can be static or dynamic. Static baselines are set at the time of project approval and remain unchanged for the duration of the project, while dynamic baselines may be revised during the course of the project should new information about the baseline conditions require a re-examination of the original baseline. Multi-project baselines too could be adjusted in a similar manner if the original baseline were to undergo an unexpected change.

Establishing a baseline for a particular activity, sector and/or region potentially simplifies the calculation of emissions reductions. Baselines need to be simple enough to be practical in developing countries.

Three key decisions are required to calculate multi-project baselines:

Choosing Baseline Plants: The first decision is which set of plants to include in the multi-project baseline. For each plant, the essential data are the fuel input (in GJ per year) and the product output (in tonnes/year for industrial projects) or electrical output (in TWh/year for power projects). Combining this information with the calorific value of the fuel and its carbon content, we can calculate the carbon (C) intensity. The carbon intensity is measured in mass of carbon per unit of product output or energy produced, e.g. in units of kg C/tonne or kg C/kWh. This carbon intensity value is the key element for constructing the emissions baselines. Once the multi-project baselines are constructed using the calculated carbon intensity levels, project CERs are determined by multiplying the difference between the project's carbon intensity level and that of the chosen baseline level by the project's annual production.

One approach for constructing multi-project baselines is to use carbon intensity values for recently-constructed plants to calculate the baseline, assuming that these represent the best available technology. An advantage of this approach is that the data for such plants are observable. Another approach is to use a forward-looking baseline that includes near-future plants, making assumptions about which plants would most likely be built. A forward-looking baseline has the advantage that it can consider new, more efficient technologies. Arguably this type of baseline is more realistic regarding what new technologies are likely to be used. In this sense, a forward-looking baseline is likely to be methodologically more accurate while one based on recently-constructed units is likely to have more accurate data.

A concern is that forward-looking baselines are open to gaming in which countries have an incentive to choose a baseline with high carbon intensity, so that projects will be able to earn more credits. Gaming can be avoided to some extent by including factors that are difficult to change, for example requiring the projection to be based on published government or utility plans. Setting regional baselines also makes gaming more difficult, as would a system of international review (Meyers, 2000). To the extent that gaming cannot be avoided, there is a trade-off between this risk and the risk of free riders against a backward-looking baseline that does not promote the best available technology.

Fuel-switching is a complicating issue regarding the choice of either recently-built or forward-looking baselines. If lower-carbon fuels are available and have not yet been fully utilized, then a baseline using recently-built, more carbon-intensive, plants or a forward-looking baseline that captures this opportunity could provide larger emissions credits for lower carbon projects. Also, if the current trend in the country is to fuel-switch away from lower carbon fuels and future plans reflect this trend, then a recently-built baseline could also be the best choice in terms of providing larger credits for lower-carbon projects.

Choosing Baseline Breadth: The second issue is which set of plants should be used for comparison to the proposed project. For example, does a proposed gas plant need to perform better than the average power station in the whole sector, the average fossil-fueled plant or better than other gas-fired plants? Obviously, the fuel-specific comparison only works if there is at least one plant or unit in the baseline using the same fuel as the project. The decision whether to compare the proposed project to other plants using the same fuel (fuel-specific), to all fossil fuel-fired plants (all fossil), or to the entire sector (sector-wide) will need to be made based on country-specific conditions. The choice of an appropriate baseline may also be technology specific. Thus for a proposed coal project one might use a mix of baseload plants, while a mix of peaking units (plants that are only operated during peak demand periods) might be a more appropriate multi-project baseline for a solar PV unit.

Choosing Baseline Stringency: The third decision to make when constructing multi-project baselines is whether to compare potential projects against average, better-than-average or best plants. Once the carbon intensity of the baseline plants is calculated, increasingly stringent benchmarks can be constructed: average, weighted average, 25th percentile, 10th percentile, or best plant. The choice of stringency level will determine the amount of CERs a project will earn by comparing the actual performance of the project to the chosen multi-project baseline level. The choice of this stringency level will need to balance the desire to encourage GHG emissions reduction projects with the desire ensure that CERs are only granted for additional emissions reductions.

In addition to being used to determine CERs, multi-project baselines can also be used to test for additionality. Additionality raises the question of whether a proposed project would have been undertaken as part of the baseline activity anyway. Institutional, financial, and technological additionality tests in order to check for environmental additionality have been proposed. A financial test would check to see whether a proposed project meets investment criteria when carbon benefits are included, but not otherwise. Institutional additionality requires the establishment of new institutions. Technological additionality is the demonstration of new technology that is specific to the proposed project. Multi-project baselines can also provide an indication of whether a project appears to be additional by comparing the proposed project to one of the more stringent benchmarks, such as best plant or the 10th percentile level. Projects that perform better than these stringent levels could be assumed to result in GHG emissions reductions that would not have otherwise occurred.

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Publications

• Multi-Project Baselines for Evaluation of Industrial Energy-Efficiency and Electric Power Projects
• Energy Use and Carbon Dioxide Emissions in the Steel Sector in Key Developing Countries
• Multi-project baselines for potential Clean Development Mechanism projects in the electricity sector in South Africa
• Multi-project Baselines for Evaluation of Electric Power Projects