Evaluation of effective quantum yields of photosystem II for CO 2 leakage monitoring in carbon capture and storage sites

PeerJ

article

Wenmei He¹  Gayoung Yoo¹  Youngryel Ryu² 

[1] Department of Applied Environmental Science, Kyunghee University;Department of Landscape Architecture and Rural System Engineering, Seoul National University

关键词: Carbon capture and storage;    CO2 leakage;    Chlorophyll fluorescence;    Hyperspectral sensing;    Index evaluation score;   

DOI  :  10.7717/peerj.10652

学科分类：社会科学、人文和艺术（综合）

来源: Inra

【 摘 要 】

Vegetation monitoring can be used to detect CO2 leakage in carbon capture and storage (CCS) sites because it can monitor a large area at a relatively low cost. However, a rapidly responsive, sensitive, and cost-effective plant parameters must be suggested for vegetation monitoring to be practically utilized as a CCS management strategy. To screen the proper plant parameters for leakage monitoring, a greenhouse experiment was conducted by exposing kale (Brassica oleracea var. viridis), a sensitive plant, to 10%, 20%, and 40% soil CO2 concentrations. Water and water with CO2 stress treatments were also introduced to examine the parameters differentiating CO2 stress from water stresses. We tested the hypothesis that chlorophyl fluorescence parameters would be early and sensitive indicator to detect CO2 leakage. The results showed that the fluorescence parameters of effective quantum yield of photosystem II (Y(II)), detected the difference between CO2 treatments and control earlier than any other parameters, such as chlorophyl content, hyperspectral vegetation indices, and biomass. For systematic comparison among many parameters, we proposed an indicator evaluation score (IES) method based on four categories: CO2 specificity, early detection, field applicability, and cost. The IES results showed that fluorescence parameters (Y(II)) had the highest IES scores, and the parameters from spectral sensors (380–800 nm wavelength) had the second highest values. We suggest the IES system as a useful tool for evaluating new parameters in vegetation monitoring.

【 授权许可】

CC BY