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Analysis of visible and near infrared spectral reflectance for assessing metals in soil

机译:可见和近红外光谱反射率分析,以评估土壤中的金属

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Visible and near infrared reflectance (VNIR; 350-2500 nm) spectroscopy has greatly been used in soils, especially for studying variability in spectrally active soil components (e.g., organic carbon, clays, and Fe/Al oxides) based on their diagnostic spectral features. In recent years, this technique has also been applied to assess soil metallic ions. In this research, the feasibility of VNIR spectroscopy for determination of soil metals was investigated with two soil data sets: (i) artificially metal-spiked and (ii) in situ metal-contaminated soils. Results showed that reflectance spectra of neither metal-spiked soils with Cd, As, and Pb even at their higher concentrations of 20, 900, and 1200 mg kg(-1), respectively, nor in situ metal-contaminated soils (with concentrations of 30 mg Cd, 3019 mg As, and 5725 mg Pb kg-1 soil) showed any recognized absorption peaks that correspond to soil metal concentrations. We observed variations in reflectance intensity for in situ metal-contaminated soils only, showing higher reflectance across the entire spectrum for strongly and lower for less metal-contaminated soils. A significant correlation was found between surface soil metals' concentrations and continuum removed spectra, while soil metals were also found significantly associated with soil organic matter and total Fe. A partial least square regression with cross-validation approach produced an acceptable prediction of metals (R-2 = 0.58-0.94) for both soil data sets, metal-spiked and in situ metal-contaminated soils. However, high values of root mean square error ruled out practical application of the achieved prediction models.
机译:可见光和近红外反射率(VNIR; 350-2500 nm)光谱已在土壤中大量使用,尤其是根据其诊断光谱特征研究光谱活性土壤成分(例如有机碳,粘土和Fe / Al氧化物)的变异性。近年来,该技术也已应用于评估土壤金属离子。在这项研究中,通过两个土壤数据集研究了VNIR光谱法测定土壤金属的可行性:(i)人工掺金属和(ii)原位金属污染的土壤。结果表明,即使分别在20、900和1200 mg kg(-1)的较高浓度下,无论是Cd,As和Pb的金属掺加土壤,还是在原位金属污染的土壤(浓度分别为20、900和1200 mg kg(-1) 30 mg Cd,3019 mg As和5725 mg Pb kg-1土壤)显示出任何与土壤金属浓度相对应的吸收峰。我们仅观察到原位金属污染土壤的反射强度变化,强烈反射显示整个光谱范围内的反射率较高,金属污染较少的土壤则显示较低的反射强度。地表土壤金属的浓度与连续去除光谱之间存在显着相关性,而土壤金属也与土壤有机质和总铁显着相关。使用交叉验证方法进行的偏最小二乘回归可以为土壤数据集(金属加标和原位金属污染的土壤)产生可接受的金属预测(R-2 = 0.58-0.94)。然而,均方根误差的高值排除了所获得的预测模型的实际应用。

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