CO₂ capture and storage (CCS) is an important technical strategy to reduce global CO₂ emission from heavy industries. However, the risk of CO₂ leakage in CCS-related projects cannot be ignored and it is crucial to identify and monitor CO₂ leakage in CCS project areas in a timely and effective manner. So here we investigate the biological characteristics (plant height, leaf length, leaf width and SPAD value) and leaf spectral characteristics of maize under soil CO₂ concentration of 10, 30, and 50%, with normal soil condition as control (CK). By analysing the original spectrum and first derivative spectrum of maize leaves, spectral parameters relatively sensitive to soil CO₂ stress were extracted. Further, eight composite spectral characteristic indexes that are expected to identify CO₂ leakages were constructed and analyzed. Besides, the normalized pigment chlorophyll index (NPCI) and modified chlorophyll absorption in reflectance index (MCARI) were also investigated for the indication role in CO₂ leakage. The results showed that maize morphological traits had a significant hysteresis effect for the indication of CO₂ leakage; the SPAD value was difficult to indicate the lower concentration of soil CO₂ early. But it was found that three spectral characteristic indexes REP-BEP, RGP/RRV and RGP-RRV/RGP+RRV can effectively identify CO₂ leakage, and three spectral characteristic indexes (RVP-GPP, REP-BEP and MCARI) can be used for quantitative inversion of soil CO₂ concentration. Especially, REP-BEP index could both indicate CO₂ leakage and quantitatively inverse soil CO₂ concentration. In sum, the spectral characteristic indexes of maize leaves can be used as effective indicators to quickly and effectively identify CO₂ leakage and quantitatively invert the CO₂ concentration in soil.

CO ₂捕获和封存（CCS）是减少全球重工业CO ₂排放的重要技术策略。然而，CCS相关项目的CO ₂泄漏风险不容忽视，及时有效地识别和监测CCS项目区的CO ₂泄漏至关重要。因此，这里我们以正常土壤条件为对照（CK），研究了土壤CO ₂浓度分别为10%、30%和50%时玉米的生物学特性（株高、叶长、叶宽和SPAD值）和叶片光谱特性。通过分析玉米叶片的原始光谱和一阶导数光谱，光谱参数对土壤CO ₂相对敏感应力被提取。此外，构建和分析了八种有望识别CO ₂泄漏的复合光谱特征指标。此外，还研究了归一化色素叶绿素指数（NPCI）和修正叶绿素吸收反射指数（MCARI）对CO ₂泄漏的指示作用。结果表明，玉米形态性状对CO ₂泄漏的指示具有显着的滞后效应；SPAD 值难以早期表明土壤CO ₂浓度较低。但发现REP-BEP、RGP/RRV和RGP-RRV/RGP+RRV三个光谱特征指标可以有效识别CO ₂3 个光谱特征指标（RVP-GPP、REP-BEP 和 MCARI）可用于土壤 CO ₂浓度的定量反演。特别是REP-BEP指数既可以指示CO ₂泄漏，也可以定量反演土壤CO ₂浓度。综上所述，玉米叶片光谱特征指标可作为快速有效识别CO ₂泄漏和定量反演土壤中CO ₂浓度的有效指标。