Use of remote sensing to assess vegetative stress as a proxy for soil contamination
Use of remote sensing to assess vegetative stress as a proxy for soil contamination
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DOI：
10.1039/d3em00480e
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发表时间：
2023-11-23
影响因子：
5.5
通讯作者：
Perry，Justin J.
中科院分区：
文献类型：
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作者：
Dean，John R.;Ahmed，Shara;Perry，Justin J.
我们报告，第一次，目前的原油后处理和储存地点的多模式调查，以评估其对环境的影响后，50年的连续运行。我们采用双重方法调查潜在的土壤污染。第一种方法使用传统的分析技术，即能量色散X射线荧光（ED-XRF）进行金属分析，并使用亲水性液相相互作用色谱高分辨率质谱（HILIC-MS）进行互补代谢组学研究。第二，部署一架带有多光谱图像照相机的无人驾驶飞行器，用于遥感植被压力，作为次表层土壤污染的代用指标。结果发现，后处理场地存在高浓度的钡（平均值为21 017 ± 5950 μg g−1，n = 36）以及来自原油（多环芳烃）、清洁过程（表面活性剂）和其他有机污染物（例如农药、增塑剂和药品）的代谢物。 然后将这些数据与飞行后数据分析得出的植被指数（归一化植被指数、全球植被指数、SAVI和Cl绿色VI）相关联，以评估由于植被压力而确定土壤污染的可能性。结果发现，土壤污染水平与地面植被之间存在很强的相关性（平均R2>0.68）。利用航空遥感技术对疑似受污染的土地进行初步调查，为决策提供信息，这种可能性具有全球影响。
We report, for the first time, a multimodal investigation of current crude oil reprocessing and storage sites to assess their impact on the environment after 50 years of continuous operation. We have adopted a dual approach to investigate potential soil contamination. The first approach uses conventional analytical techniques i.e. energy dispersive X-ray fluorescence (ED-XRF) for metal analysis, and a complementary metabolomic investigation using hydrophilic liquid interaction chromatography hi-resolution mass spectrometry (HILIC-MS) for organic contaminants. Secondly, the deployment of an unmanned aerial vehicle (UAV) with a multispectral image (MSI) camera, for the remote sensing of vegetation stress, as a proxy for sub-surface soil contamination. The results identified high concentrations of barium (mean 21 017 ± 5950 μg g−1, n = 36) as well as metabolites derived from crude oil (polycyclic aromatic hydrocarbons), cleaning processes (surfactants) and other organic pollutants (e.g. pesticides, plasticizers and pharmaceuticals) in the reprocessing site. This data has then been correlated, with post-flight data analysis derived vegetation indices (NDVI, GNDVI, SAVI and Cl green VI), to assess the potential to identify soil contamination because of vegetation stress. It was found that strong correlations exist (an average R2 of >0.68) between the level of soil contamination and the ground cover vegetation. The potential to deploy aerial remote sensing techniques to provide an initial survey, to inform decision-making, on suspected contaminated land sites can have global implications.