Following the Paris Agreement of 2015, most countries have agreed to reduce their carbon dioxide (CO₂) emissions according to individually set Nationally Determined Contributions. However, national CO₂ emissions are reported by individual countries and cannot be directly measured or verified by third parties. Inherent weaknesses in the reporting methodology may misrepresent, typically an under-reporting of, the total national emissions. This paper applies the theory of sequential testing to design a statistical monitoring procedure that can be used to detect systematic under-reportings of CO₂ emissions. Using simulations, we investigate how the proposed sequential testing procedure can be expected to work in practice. We find that, if emissions are reported faithfully, the test is correctly sized, while, if emissions are under-reported, detection time can be sufficiently fast to help inform the 5 yearly global “stocktake” of the Paris Agreement. We recommend the monitoring procedure be applied going forward as part of a larger portfolio of methods designed to verify future global CO₂ emissions.

根据 2015 年的《巴黎协定》，大多数国家都同意根据各自设定的国家自主贡献减少其二氧化碳 (CO ₂ ) 排放量。但是，国家 CO ₂排放量由个别国家报告，无法由第三方直接测量或验证。报告方法的固有缺陷可能会歪曲国家排放总量，通常是少报。本文应用顺序测试理论设计了一个统计监测程序，该程序可用于检测 CO _{2 的}系统性漏报排放。使用模拟，我们研究了所提出的顺序测试程序如何在实践中发挥作用。我们发现，如果如实报告排放量，则测试的规模是正确的，而如果排放量报告不足，则检测时间可以足够快，以帮助为《巴黎协定》的 5 年度全球“盘点”提供信息。我们建议将监测程序应用于未来，作为旨在验证未来全球 CO ₂排放量的更大方法组合的一部分。