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How can land-use modelling tools inform bioenergy policies?

pmid: 22482028
pmc: PMC3262264
Targets for bioenergy have been set worldwide to mitigate climate change. Although feedstock sources are often ambiguous, pledges in European nations, the United States and Brazil amount to more than 100 Mtoe of biorenewable fuel production by 2020. As a consequence, the biofuel sector is developing rapidly, and it is increasingly important to distinguish bioenergy options that can address energy security and greenhouse gas mitigation from those that cannot. This paper evaluates how bioenergy production affects land-use change (LUC), and to what extent land-use modelling can inform sound decision-making. We identified local and global internalities and externalities of biofuel development scenarios, reviewed relevant data sources and modelling approaches, identified sources of controversy about indirect LUC (iLUC) and then suggested a framework for comprehensive assessments of bioenergy. Ultimately, plant biomass must be managed to produce energy in a way that is consistent with the management of food, feed, fibre, timber and environmental services. Bioenergy production provides opportunities for improved energy security, climate mitigation and rural development, but the environmental and social consequences depend on feedstock choices and geographical location. The most desirable solutions for bioenergy production will include policies that incentivize regionally integrated management of diverse resources with low inputs, high yields, co-products, multiple benefits and minimal risks of iLUC. Many integrated assessment models include energy resources, trade, technological development and regional environmental conditions, but do not account for biodiversity and lack detailed data on the location of degraded and underproductive lands that would be ideal for bioenergy production. Specific practices that would maximize the benefits of bioenergy production regionally need to be identified before a global analysis of bioenergy-related LUC can be accomplished.
- University of Bristol (UoB) United Kingdom
- University of Bristol (UoB) United Kingdom
- Département Sciences sociales, agriculture et alimentation, espace et environnement France
- Agricultural & Applied Economics Association United States
- Institut National de la recherche agronomique France
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, MISCANTHUS, 330, 550, AGRICULTURE, 333, ENERGY, ORGANIC-CARBON, BENEFITS, feedstocks, SWITCHGRASS, indirect land-use change, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, GREENHOUSE-GAS EMISSIONS, CLIMATE-CHANGE, biofuels, NITROGEN, greenhouse gas, [SDV.SA] Life Sciences/Agricultural sciences, BIOFUEL FEEDSTOCK, environmental economics, ecosystem services
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences, MISCANTHUS, 330, 550, AGRICULTURE, 333, ENERGY, ORGANIC-CARBON, BENEFITS, feedstocks, SWITCHGRASS, indirect land-use change, [SDV.SA] Life Sciences [q-bio]/Agricultural sciences, GREENHOUSE-GAS EMISSIONS, CLIMATE-CHANGE, biofuels, NITROGEN, greenhouse gas, [SDV.SA] Life Sciences/Agricultural sciences, BIOFUEL FEEDSTOCK, environmental economics, ecosystem services
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).23 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
