地质封存CO2泄漏玉米光谱差异特征分析
Spectral difference analysis of maize to CO2 leakage from geological storage
薛璐 1马俊杰 2王浩璠 2马劲风2
作者信息
- 1. 榆林学院生命科学学院,陕西 榆林 719000;西北大学碳中和学院(榆林),陕西 西安 710069;二氧化碳捕集与封存国家与地方工程研究中心,陕西 西安 710127;陕西省碳中和技术重点实验室,陕西 西安 710069
- 2. 西北大学碳中和学院(榆林),陕西 西安 710069;二氧化碳捕集与封存国家与地方工程研究中心,陕西 西安 710127;陕西省碳中和技术重点实验室,陕西 西安 710069
- 折叠
摘要
构建CO2泄漏模拟平台,利用玉米叶片原始光谱分析、一阶导数光谱分析及相关性分析、差异性分析与回归分析,提取对土壤CO2泄漏敏感的玉米光谱特征参量.结果表明:土壤CO2泄漏条件下的玉米绿峰(Rg)、红谷(Rr)、蓝边幅值(Db)和红边幅值(Dr)四个特征参量变化明显,且Rg和Rr与土壤CO2有更高的相关性(R2≥0.869).在泄漏10,20和30 d,土壤CO2体积分数为10%,30%和50%下的Rr均与对照组呈显著性差异;泄漏20和30 d时,土壤CO2体积分数为10%,30%和50%下的Rg均与CK呈显著性差异,但泄漏10 d、土壤CO2体积分数仅为30%和50%时,Rg与CK呈显著性差异.泄漏10 d时,Rg仅可识别土壤CO2体积分数为30%以上的泄漏;泄漏20和30 d时,Rr和Rg均可有效识别土壤CO2体积分数为10%,30%和50%的泄漏.同时,Rg与Rr与土壤CO2呈较强的线性关系(R2≥0.751 5),可利用Rg和Rr与CO2的线性回归方程定量反演土壤CO2可能泄漏的体积分数.
Abstract
By constructing a CO2 leakage simulation platform,the spectral characteristic parameters of maize that are sensitive to soil CO2 leakage were extracted by means of original spectral analysis of maize leaves,first-order derivative spectral analysis,correlation analysis,difference analysis and regression analysis,providing a basis for CO2 leakage monitoring in the CO2 capture and storage(CCS)project area.The results show that Rg,Rr,Db and Dr change significantly under CO2 leakage conditions,and Rg and Rr have a higher correlation with soil CO2(R2≥0.869).At 10,20 and 30 days of leakage,Rr was significantly different from CK at soil CO2 concentration of 10%,30%and 50%.At 20 and 30 days of leakage,Rg at soil CO2 concentration of 10%,30%and 50%showed significant differences with CK.However,at the 10 days of leakage,Rg showed significant differences with CK only at soil CO2 concentration of 30%and 50%.At 10 days of leakage,Rg can only identify leakage with soil CO2 above 30%,and at 20 and 30 days of leakage,both Rr and Rg can effectively identify leakage with soil CO2 of 10%,30%and 50%.Furthermore,Rg and Rr show a good linear relationship with soil CO2(R2≥0.751 5),and the possible leakage concentration of soil CO2 can be quantitatively retrieved using the linear regression equation of Rg and Rr.
关键词
植物高光谱/光谱特征参量/CO2泄漏/CO2地质封存/泄漏监测Key words
plant hyperspectrum/spectral characteristic parameter/CO2 leakage/CO2 capture and storage(CCS)/Leakage monitoring引用本文复制引用
出版年
2025
国家科技期刊平台
NSTL
万方数据