Assessing the Climate Effects of Biofuels Using Integrated Assessment Models, Part I: Methodological Considerations
In: Journal of Industrial Ecology, Band 21, Heft 6, S. 1478-1487
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In: Journal of Industrial Ecology, Band 21, Heft 6, S. 1478-1487
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Many national and regional governments have been promoted biofuels as a strategy to mitigate the climate change effects of the existing petroleum-based transportation system. New performance-based policies such as the California Low-Carbon Fuel Standard and the US Renewable Fuel Standard use Life Cycle Assessment (LCA) to estimate greenhouse gas (GHG) emissions to determine the life cycle global warming effects of each fuel production pathway. However, the current generation of policies have largely ignored the highly uncertain and often subjective nature of LCA assessments. Considering these uncertainties raises questions about the appropriateness of using an LCA-based estimate as a performance metric in public policy. The objective of this dissertation is to characterize--qualitatively and quantitatively--the many data, parameter, model, and decision uncertainties inherent to estimates of the life cycle climate effects of transportation fuels, and to critically examine the robustness of these policies to these uncertainties. As demonstrated herein, LCA-based fuel regulations may accomplish much less than expected, and have the potential to cause more climate change than a business-as-usual scenario absent biofuels. Alternative policies that acknowledge uncertainty and respect the limitations of LCA--and thus of our understanding of the benefits of LCA-based policies--can be more robust in achieving GHG reductions.
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In: Journal of Industrial Ecology, Band 18, Heft 1, S. 73-83
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In: Goldman School of Public Policy Working Paper No. GSPP10-007
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Working paper
Bioenergy deployment offers significant potential for climate change mitigation, but also carries considerable risks. In this review, we bring together perspectives of various communities involved in the research and regulation of bioenergy deployment in the context of climate change mitigation: Land-use and energy experts, landuse and integrated assessment modelers, human geographers, ecosystem researchers, climate scientists and two different strands of life-cycle assessment experts. We summarize technological options, outline the state-of-theart knowledge on various climate effects, provide an update on estimates of technical resource potential and comprehensively identify sustainability effects. Cellulosic feedstocks, increased end-use efficiency, improved land carbon-stock management and residue use, and, when fully developed, BECCS appear as the most promising options, depending on development costs, implementation, learning, and risk management. Combined heat and power, efficient biomass cookstoves and small-scale power generation for rural areas can help to promote energy access and sustainable development, along with reduced emissions. We estimate the sustainable technical potential as up to 100 EJ: high agreement; 100–300 EJ: medium agreement; above 300 EJ: low agreement. Stabilization scenarios indicate that bioenergy may supply from 10 to 245 EJ yr 1 to global primary energy supply by 2050. Models indicate that, if technological and governance preconditions are met, large-scale deployment (>200 EJ), together with BECCS, could help to keep global warming below 2° degrees of preindustrial levels; but such high deployment of land-intensive bioenergy feedstocks could also lead to detrimental climate effects, negatively impact ecosystems, biodiversity and livelihoods. The integration of bioenergy systems into agriculture and forest landscapes can improve land and water use efficiency and help address concerns about environmental impacts. We conclude that the high variability in pathways, uncertainties in technological development and ambiguity in political decision render forecasts on deployment levels and climate effects very difficult. However, uncertainty about projections should not preclude pursuing beneficial bioenergy options. ; publishedVersion ; © 2015. This is the authors' accepted and refereed manuscript to the article. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ DOI:10.1111/gcbb.12205
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