A deep dive into the modelling assumptions for biomass with carbon capture and storage (BECCS): a transparency exercise
A deep dive into the modelling assumptions for biomass with carbon capture and storage (BECCS): a transparency exercise
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深入探讨碳捕获和封存生物质 (BECCS) 的建模假设：透明度练习
DOI：
10.1088/1748-9326/ab5c3e
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发表时间：
2020
影响因子：
6.7
通讯作者：
Butnar I
中科院分区：
文献类型：
--
作者：
Butnar I
具有碳捕获和封存的生物能源(BECCS)被设想为符合《巴黎协定》的大多数深度脱碳途径的关键要素。这种变革性的升级-到2050年达到每年3-7Gt二氧化碳-需要前所未有的技术、经济、社会文化和政治努力，以及至关重要的是，所有利益攸关方之间的透明沟通。作为政府间气候变化专门委员会评估的1.5C情景的基础的综合评估模型(IAM)在构建和评估深度脱碳叙事方面发挥了关键作用。然而，它们的高级别聚合及其复杂性可能会导致IAM社区以外的利益相关者认为它们不透明。本文通过对IAM中使用的BECCS假设进行全面评估来弥合这一差距，以便向更广泛的受众开放它们。我们侧重于支撑BECCS的五个方面的关键假设：生物质可用性、BECCS技术、二氧化碳运输和存储基础设施、BECCS成本，以及有利于BECCS部署的更广泛的系统条件。通过结构化审查，我们发现所有IAM都透明地传达更广泛的系统假设和主要成本假设。然而，随着我们更深入地挖掘模型细节，这种质量会逐渐消失。对于二氧化碳运输和储存基础设施等一系列技术要素来说，情况尤其如此，我们发现这些要素的假设最不透明。我们还发现，政府间管理机构对我们所调查的环境、环境和气候变化问题五个方面的处理不够透明，在纳入和处理可行性的社会文化和体制监管方面也不透明，而这些都是气专委所建议的环境、环境、环境和气候变化问题的关键要素。最后，我们围绕如何提高IAM透明度进行了实际讨论，以此作为这个社区与来自其他学科的利益相关者、决策者、金融家和公众之间的桥梁。
Bioenergy with carbon capture and storage (BECCS) is envisaged as a critical element of most deep decarbonisation pathways compatible with the Paris Agreement. Such a transformational upscaling—to 3–7 Gt CO 2/yr by 2050—requires an unprecedented technological, economic, socio-cultural and political effort, along with, crucially, transparent communication between all stakeholders. Integrated Assessment Models (IAMs) that underpin the 1.5 C scenarios assessed by IPCC have played a critical role in building and assessing deep decarbonisation narratives. However, their high-level aggregation and their complexity can cause them to be perceived as non-transparent by stakeholders outside of the IAM community. This paper bridges this gap by offering a comprehensive assessment of BECCS assumptions as used in IAMs so as to open them to a wider audience. We focus on key assumptions that underpin five aspects of BECCS: biomass availability, BECCS technologies, CO 2 transport and storage infrastructure, BECCS costs, and wider system conditions which favour the deployment of BECCS. Through a structured review, we find that all IAMs communicate wider system assumptions and major cost assumptions transparently. This quality however fades as we dig deeper into modelling details. This is particularly true for sets of technological elements such as CO 2 transport and storage infrastructure, for which we found the least transparent assumptions. We also found that IAMs are less transparent on the completeness of their treatment of the five BECCS aspects we investigated, and not transparent regarding the inclusion and treatment of socio-cultural and institutional-regulatory dimensions of feasibility which are key BECCS elements as suggested by the IPCC. We conclude with a practical discussion around ways of increasing IAM transparency as a bridge between this community and stakeholders from other disciplines, policy decision makers, financiers, and the public.
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