Risk assessment of the economic impacts of climate change on the implementation of mandatory biodiesel blending programs: A fuzzy inoperability input-output modeling (IIM) approach
Many countries have implemented biofuel programs designed to address pressing concerns such as climate change, energy security and rural development. However, recent works suggest that biofuel resources may be at risk due to climate-induced disruptions such as changes in precipitation levels, pest i...
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Main Authors: | , , , , , |
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Format: | text |
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Animo Repository
2015
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Subjects: | |
Online Access: | https://animorepository.dlsu.edu.ph/faculty_research/2239 https://animorepository.dlsu.edu.ph/context/faculty_research/article/3238/type/native/viewcontent |
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Institution: | De La Salle University |
Summary: | Many countries have implemented biofuel programs designed to address pressing concerns such as climate change, energy security and rural development. However, recent works suggest that biofuel resources may be at risk due to climate-induced disruptions such as changes in precipitation levels, pest infestation, or increased frequency of extreme weather events. The incidence of such disruptions not only affects biofuel producers, but also energy-dependent economic sectors, resulting in "ripple effects" that further increase economic losses. A variant of the inoperability input-output model (IIM) is used to assess the economic effects of implementing mandatory biodiesel blending programs in the Philippines. This approach is an extension of input-output analysis that quantifies risk through the dimensionless inoperability metric, whose value ranges from 0 to 1 depending on the degree of failure. Using the IIM, we estimate the resulting crop losses using the storm damage and pest infestation scenarios at the proposed blending rate of 5% currently being considered in the Philippines. Uncertainties within the modeling framework are captured using fuzzy numbers. Different ranking strategies are then evaluated to determine sector vulnerability using inoperability levels and economic losses. The effect of uncertainties is also taken into account through fuzzy ranking of the sectors. © 2015 Elsevier Ltd. |
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