地下储存CO2 泄漏胁迫下地表植被光谱变化特征及识别研究

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。

Research on the Spectral Feature and Identification of the Surface Vegetation Stressed by Stored CO2 Underground Leakage

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.