A meta-analysis of the greenhouse gas abatement of bioenergy factoring in land use changes.

A meta-analysis of the greenhouse gas abatement of bioenergy factoring in land use changes.
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DOI:
10.1038/s41598-018-26712-x
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发表时间:
2018-06-04
期刊:
影响因子:
4.6
通讯作者:
Makowski D
Makowski D
中科院分区:
综合性期刊3区
文献类型:
--
作者:
El Akkari M;Réchauchère O;Bispo A;Gabrielle B;Makowski D

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非食品生物质生产正在迅速发展,为生物能源行业提供燃料并替代日益减少的化石资源,这可能会影响全球土地利用模式。最近的出版物试图将这种影响纳入生物能源链的气候缓解潜力中,但根据其范围、数据来源或方法得出了广泛不同的结论。在这里,我们首次对有关该主题的科学文献进行了系统回顾,并通过荟萃分析得出了定量趋势。我们表明,第二代生物燃料和生物电比第一代生物燃料具有更大的温室气体 (GHG) 减排潜力,并且与化石燃料相比,最有可能(80% 至 90% 的概率范围)实现 50% 的减排。相反,直接转变森林生态系统来生产生物能源原料似乎是最坏的情况,系统性地导致温室气体减排量为负。另一方面,与化石能源相比,转变草地似乎是一个更好的选择,并且有 60% 的机会将温室气体排放量减少一半。由于大多数气候缓解方案假设节约量更大,因此更好地了解土地利用变化的影响至关重要,以便对与生物能源相关的缓解潜力提供更现实的估计。
Non-food biomass production is developing rapidly to fuel the bioenergy sector and substitute dwindling fossil resources, which is likely to impact land-use patterns worldwide. Recent publications attempting to factor this effect into the climate mitigation potential of bioenergy chains have come to widely variable conclusions depending on their scope, data sources or methodology. Here, we conducted a first of its kind, systematic review of scientific literature on this topic and derived quantitative trends through a meta-analysis. We showed that second-generation biofuels and bioelectricity have a larger greenhouse gas (GHG) abatement potential than first generation biofuels, and stand the best chances (with a 80 to 90% probability range) of achieving a 50% reduction compared to fossil fuels. Conversely, directly converting forest ecosystems to produce bioenergy feedstock appeared as the worst-case scenario, systematically leading to negative GHG savings. On the other hand, converting grassland appeared to be a better option and entailed a 60% chance of halving GHG emissions compared to fossil energy sources. Since most climate mitigation scenarios assume still larger savings, it is critical to gain better insight into land-use change effects to provide a more realistic estimate of the mitigation potential associated with bioenergy.
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