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Most projects developed under the AIJ Pilot Phase have used project-specific, bottom-up baselines determined by project developers (Moura-Costa et al., 2000; see also Table 5-4). The attractions of this approach are that analysis focuses on specific areas and activities relating to the project and that developers may have a better knowledge of local conditions. Because land-use practices and change processes are often spatially and temporally variable, a detailed project-specific study arguably is likely to yield a more accurate prediction of emissions than a broader regional or sectoral assessment. Giving project developers the task of developing baselines also introduces the risk, however, that they may choose scenarios that maximize their perceived benefits (Tipper and de Jong, 1998). Moreover, ensuring consistency between assessments may be difficult if different teams develop many baselines. Allowing ad hoc project baselines could lead to inconsistent approaches among similar projects and increase the risk that project baselines would be set strategically to maximize the potential to generate credits.
Generic methods that have been proposed but not yet tested include benchmarking models similar to those being assessed for the industrial and energy sectors (Center for Clean Air Policy, 1998; Hargrave et al., 1998; Baumert, 1999; Ellis and Bosi, 1999; Friedman, 1999; Jepma, 1999; Michaelowa, 1999). For example, certain practices could be considered "standard management practice," and baselines might be set to reflect the level of carbon sequestration or emissions avoidance that would occur if these practices were universally applied. Credit would then be available only to the extent that a project improved on the results that would be obtained by simply applying these standard practices. Because the development of credible baseline scenarios represents a significant capital cost, the use of generic baselines for sectors, technologies, or regions could provide economies of scale (Baumert, 1999). If such baselines were set by an organization independent from project developers, they could also provide transparency and reduce the potential for discrepancies between projects. The applicability of this approach to the LULUCF sector is unclear; no project to date has used a benchmarking approach. Generic baselines set by a coordinating body have been used in a few cases (e.g., the Protected Areas Project in Costa Rica, SGS, 1998; the Profafor project in Ecuador, FACE Foundation, 1998).
Another proposed approach involves minimum performance benchmarks (Brown, 1998). Minimum baselines or benchmarks could help to avoid rewarding countries or investors with poor practices or policies by paying for improvements over an exceedingly low baseline (Brown, 1998). If countries hosting LULUCF projects have policies that encourage carbon-emitting activities, such as subsidies for deforestation, LULUCF projects may only be mitigating the impact of poor policies. For instance, if project baselines are influenced by the threat that a particular area will be deforested in the absence of the project, this situation could create an incentive to "demonstrate" the threat of deforestation-by building roads through isolated areas, for example.
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