随着全球气候变暖, 减少温室气体排放成为全世界所关注的问题, 而碳捕捉与储存(carbon capture and storage, CCS)技术可以减少温室气体CO2排放量, 但储存在地下的CO2有泄漏的风险。 本工作的目的是通过野外模拟实验, 研究地表植被(甜菜)在CO2轻微泄漏胁迫下其叶片叶绿素含量、 水分含量及光谱变化特征, 结果表明CO2泄漏胁迫的甜菜叶绿素与叶片含水量明显降低, 叶片反射率在550 nm减小, 而在680 nm增大。 设计了比值指数R550/R680进行识别CO2泄漏胁迫的甜菜, 发现该指数能够在胁迫发生7天后识别出胁迫的甜菜, 且该指数具有较强的敏感性、 稳健性及识别能力。 研究结果对于未来CCS项目选址、 地表生态监测评估、 遥感监测CO2泄漏点等都具有重要的现实意义与应用价值。

With the global climate warming, reducing greenhouse gas emissions becomes a focused problem for the world. The carbon capture and storage (CCS) techniques could mitigate CO2 into atmosphere, but there is a risk in case that the CO2 leaks from underground. The objective of this paper is to study the chlorophyll contents (SPAD value), relative water contents (RWC) and leaf spectra changing features of beetroot under CO2 leakage stress through field experiment. The result shows that the chlorophyll contents and RWC of beetroot under CO2 leakage stress become lower than the control beetroot’, and the leaf reflectance increases in the 550 nm region and decreases in the 680nm region. A new vegetation index (R550/R680) was designed for identifying beetroot under CO2 leakage stress, and the result indicates that the vegetation index R550/R680 could identify the beetroots after CO2 leakage for 7 days. The index has strong sensitivity, stability and identification for monitoring the beetroots under CO2 stress. The result of this paper has very important meaning and application values for selecting spots of CCS project, monitoring and evaluating land-surface ecology under CO2 stress and monitoring the leakage spots by using remote sensing.