Carbon Capture and Storage (CCS) is a potential significant mitigation strategy to combat climate change and ocean acidification. The technology is well understood but its current implementation must be scaled up nearly by a hundredfold to become an effective tool that helps meet mitigation targets. Regulations require monitoring and verification at storage sites, and reliable monitoring strategies for detection and quantification of seepage of the stored carbon need to be developed. The C_seep method was developed for reliable determination of CO₂ seepage signal in seawater by estimating and filtering out natural variations in dissolved inorganic carbon (C). In this work, we analysed data from the first-ever subsea CO₂ release experiment performed in the north-western North Sea by the EU STEMM−CCS project. We successfully demonstrated the ability of the C_seep method to (i) predict natural C variations around the Goldeneye site over seasonal to interannual time scales; (ii) establish a process-based baseline C concentration with minimal variability; (iii) determine CO₂ seepage detection threshold (DT) to reliably differentiate released−CO₂ signal from natural variability and quantify released−CO₂ dissolved in the sampled seawater. DT values were around 20 % of the natural C variations indicating high sensitivity of the method. Moreover, with the availability of DT value, the identification of released−CO₂ required no pre-knowledge of seepage occurrence, but we used additional available information to assess the confidence of the results. Overall, the C_seep method features high sensitivity, automation suitability, and represents a powerful future monitoring tool both for large and confined marine areas.

碳捕集与封存（CCS）是一种潜在的重要减缓战略，可应对气候变化和海洋酸化。该技术已广为人知，但其当前实施必须扩大近百倍，才能成为有助于实现缓解目标的有效工具。法规要求在存储地点进行监视和验证，并且需要制定可靠的监视策略以检测和量化存储的碳的渗漏。通过估计和滤出溶解的无机碳（C）的自然变化，开发了C_渗漏法，用于可靠地确定海水中CO ₂渗漏信号。在这项工作中，我们分析了有史以来第一次海底CO _2的数据欧盟STEMM-CCS项目在西北西北海地区进行的释放实验。我们成功地证明了C_渗漏法能够（i）预测从季节性到年际的时间尺度上白点周围自然C的变化；（ii）建立基于过程的基线C浓度，且变化最小；（iii）确定CO ₂渗漏检测阈值（DT）以可靠地将释放的CO ₂信号与自然变化区分开，并量化溶解在采样海水中的释放的CO ₂。DT值约为自然C变化的20％，表明该方法具有很高的灵敏度。此外，借助DT值，可以识别释放的CO ₂无需事先了解渗漏的发生，但我们使用了其他可用信息来评估结果的可信度。总体而言，C _seep方法具有高灵敏度，自动化适用性的特点，并且代表了未来针对大型和受限海洋区域的强大监视工具。