Technical monitoring considerations for advancing CCS Projects under the California Low Carbon Fuel Standard in relation to other global regulatory regimes

Technical monitoring considerations for advancing CCS Projects under the California Low Carbon Fuel Standard in relation to other global regulatory regimes
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与其他全球监管制度相关的加州低碳燃料标准下推进 CCS 项目的技术监测考虑因素

DOI:
10.2139/ssrn.3811985
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发表时间:
2021
期刊:
Social Science Research Network
影响因子:
--
通讯作者:
T. Dixon
T. Dixon
中科院分区:
--
文献类型:
--
作者:
K. Romanak;T. Dixon

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加州空气资源委员会低碳燃料标准(LCFS)旨在减少与加州使用的运输燃料相关的温室气体排放,包括在该州以外生产和进口使用的燃料。LCFS承认通过碳捕获、利用和地质储存(CCU)实现的减排,并使这些措施能够产生LCFS信用额度,前提是这些信用额度符合LCFS CCS议定书(CCSP)中规定的监管要求和指导方针。这些准则侧重于展示“永久储存”和环境完整性,其中包括整个储存综合体,但主要集中在近地表和表层。我们对CCSP的分析表明,该法规存在几个技术挑战,包括1)规范性监测技术的要求,2)不可谈判的100年注射后现场护理期(PISC),3)在项目获得认证之前需要有意义的数据收集,以及4)根据一年的环境基线数据可以预测100多个监测期内的环境变化。我们讨论了这些要求的技术分支,并讨论了根据环境监测中的新知识,如何最好地使用普通和低成本的近地表监测技术来满足这些要求。
The California Air Resources Board Low Carbon Fuel Standard (LCFS) seeks to reduce GHG emissions associated with transport fuels used in California, including those produced outside the state and imported for use. The LCFS recognises emissions reductions through carbon capture, utilisation and geologic storage (CCUS) and enables these to generate LCFS credits provided that regulatory requirements and guidelines set forth within the LCFS CCS Protocol (CCSP) are met. These guidelines are focused on demonstration of “permanent storage” and environmental integrity which includes the entire storage complex but predominantly focuses in the near-surface and surface. Our analysis of the CCSP indicates several technical challenges with the regulation as written including 1) the requirement of prescriptive monitoring technologies, 2) a non-negotiable 100-year post injection site care period (PISC), 3) the need for meaningful data collection before a project can be certified, and 4) the expectation that environmental variations over the 100+ monitoring period can be predicted from a year of environmental baseline data. We discuss the technical ramifications of these requirements and discuss the ways in which common and low-cost near surface monitoring techniques can best be used to satisfy the requirements in light of new learning in environmental monitoring.
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