Identifying the spectral responses of several plant species under CO2 leakage and waterlogging stresses

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Carbon capture and storage (CCS) is one of the potential options for mitigating global climate warming. This process can capture the CO2 released during industrial processes and store it deep in geological sites. However, there is a possible risk that the CO2 might leak from underground. Therefore, detecting sites of CO2 leakage is important for the safety and success of CCS projects. The remote sensing of plants offers the potential to identify locations of CO2 leakage from the spectral responses of the plants growing on the surface of sequestration fields. A field experiment was performed at the Sutton Bonington campus of University of Nottingham (52.8N, 1.2W) that aimed to study the spectral characteristics of maize (Zea mays L.), beetroot (Beta vulgaris L.), cabbage (Brassica oleracea L.), lettuce (Lactuca sativa L.) and bean (Phaseolus vulgaris L.) under CO2 leakage and waterlogging stress conditions, to develop a new method for distinguishing between species growing under CO2 leakage and waterlogging stresses, and to determine which plant was most sensitive to CO2 leakage stress.Leaf spectra were measured and processed using smoothing, continuum removal and first-derivative methods. For maize, cabbage, lettuce and bean, as the severity of CO2 leakage stress increased, the areas of the 510–545nm regions of the first-derivative spectral curves increased, and those of the 690–750nm regions decreased compared with the controls. However, for beetroot, the area of the 510–545nm region of the first-derivative spectral curve decreased, and that of the 690–750nm region increased compared with the control. When exposed to waterlogging stress, the areas of both the 510–545nm and the 690–750nm regions of the first-derivative spectral curves decreased compared with the controls for all 5 species examined. The areas of the 510–545nm and 690–750nm regions of the first-derivative spectral curves were named the AREAgreen and AREAred, respectively. Furthermore, the AREAred/AREAgreen ratio was able to effectively identify the species exposed to CO2 leakage stress, and the product of AREAred×AREAgreen accurately identified the species under waterlogging stress.These results suggest that the spectral responses of plants to CO2 leakage and waterlogging stresses are different and that the AREAred/AREAgreen and AREAred×AREAgreen indices can effectively distinguish the treated plants and the control plants, respectively. Cabbage is the most sensitive of the examined species to the CO2 leakage stress, followed by maize, beetroot and lettuce, and then bean, the least sensitive plant species. This experiment suggests that leaf reflectance can be adopted to detect plants that grow in regions of high soil CO2 leakage; moreover, the species’ responses to CO2 leakage stress and waterlogging stress can be differentiated. Nevertheless, to accurately detect locations of CO2 leakage in fields and determining whether the models are suitable for airborne or satellite data, large-scale field experiments must also be performed in the near future.