用VNIR-SWIR光谱学预测沿着一个AMD (酸性矿井排水) 污染的溪流排水一座煤矿的微金属含量
Jamie-Leigh Robin Abrahams1, Emmanuel John M Carranza2
1Department of Geology, Faculty of Natural and Agricultural Sciences, University of the Free State, 205 Nelson Mandela Drive, Park West, Bloemfontein, 9301, South Africa. jrobinabrahams@gmail.com.
Environmental monitoring and assessment
|October 2, 2023
概括
可见/近红外到短波红外 (VNIR-SWIR) 光谱学有效地预测了沉积物中的微量金属,使用与石和高石相关的光谱吸收特征参数 (SAFP). 这种方法为大规模评估提供了传统地质化学分析的有价值的替代方案.
科学领域:
- 地质化学 地质化学
- 遥感 遥感 遥感 遥感
- 环境科学 环境科学
背景情况:
- 分析沉积物中的微量金属度的传统地质化学方法往往耗时且对大规模研究具有挑战性.
- 可见/近红外到短波红外 (VNIR-SWIR) 光谱学提供了一个潜在的非破坏性和快速的分析技术.
- 了解光谱特性和矿物成分之间的关系对于将VNIR-SWIR光谱学应用于地质化学分析至关重要.
研究的目的:
- 调查VNIR-SWIR光谱法在预测海上沉积物中微量金属 (Pb,Cd,As,Cu) 度方面的有效性.
- 导出光谱吸收特征参数 (SAFP) 并将其与微量金属含量相关联.
- 构建和评估回归模型,以使用SAFPs预测微量金属度.
主要方法:
- 从研究地点收集了上岸沉积物样本.
- 使用VNIR-SWIR光谱学 (400-2500纳米) 测量地面光谱.
- 衍生出与高和高相关的SAFP,并构建了单变量回归模型来预测微量金属度.
主要成果:
- 发现了与石 (深度433b,Asym433b,宽度433b) 和石 (深度1366b,Asym1366b,宽度1366b,深度2208b,Asym2208b,宽度2208b) 相关的SAFPs.
- 与石相关的SAFPs的相关性最强,而Pb,As和Cu与石和高石相关的SAFPs有很强的相关性.
- 最好的预测模型实现了Cu和Pb的R2值为0.73,对于As (R2=0.46) 和Cd (R2=0.17) 的模型较弱.
结论:
- VNIR-SWIR光谱,通过SAFP与石和高石相关,可以间接预测海岸沉积物中的微量金属度.
- 这种光谱方法提供了一个有价值的,大规模的替代传统地质化学分析的微量金属评估.
- 进一步的研究可以完善这些模型,以便在环境监测中更准确,更广泛地应用.
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