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Evaluation of effective quantum yields of photosystem II for CO.sub.2 leakage monitoring in carbon capture and storage sites
Vegetation monitoring can be used to detect CO.sub.2 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 practic...
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Published in: | PeerJ (San Francisco, CA) CA), 2021-01, Vol.9, p.e10652 |
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Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Online Access: | Get full text |
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Summary: | Vegetation monitoring can be used to detect CO.sub.2 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 CO.sub.2 concentrations. Water and water with CO.sub.2 stress treatments were also introduced to examine the parameters differentiating CO.sub.2 stress from water stresses. We tested the hypothesis that chlorophyl fluorescence parameters would be early and sensitive indicator to detect CO.sub.2 leakage. The results showed that the fluorescence parameters of effective quantum yield of photosystem II (Y(II)), detected the difference between CO.sub.2 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: CO.sub.2 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. |
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ISSN: | 2167-8359 2167-8359 |
DOI: | 10.7717/peerj.10652 |