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Moving from reactive to proactive modelling of agriculturalgreenhouse gas mitigation

机译:从无功到农业休闲室内减缓的主动建模

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Greenhouse gas (GHG) emissions from agriculture, land use, land use change and forestry (ALULUCF) are a significant percentage of UK emissions. This means that as the UK and devolved administrations set ambitious emissions reductions targets, the ALULUCF sectors will come under increasing scrutiny and pressure to reduce emissions. In order to address this, the Committee on Climate Change (CCC) commissioned a project developing marginal abatement cost curves (MACCs) for greenhouse gas mitigation in the ALULUCF sectors. As with many policy-relevant questions, the project constraints led to a largely reactive process with numerous enforced shortcuts in the integration process. On reflection, it is easy to identify areas where the analysis could be improved. However, accuracy comes at a cost, and a more challenging task is to identify the optimal level of analysis.
机译:农业,土地利用,土地利用变化和林业(Alulucf)的温室气体(GHG)排放量是英国排放量的显着比例。这意味着随着英国和Dovolved主管部门设定雄心勃勃的排放减少目标,亚利桑那州部门将在增加审查和压力下降低排放。为了解决这一问题,气候变化委员会(CCC)委托一个项目开发亚利桑那州股市温室气体缓解边缘减排成本曲线(MACCS)。与许多政策相关的问题一样,项目限制导致了在集成过程中具有许多强制捷径的反应性过程。在反射上,很容易识别可以改善分析的区域。但是,准确性以成本为本,并且更具挑战性的任务是识别最佳分析水平。

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