测量重金属化合物氯化铬（CrCl3）、 氯化铜（CuCl2）、 氯化锌（ZnCl2）的可见-近红外反射光谱（VNIRS）, 将重金属反射光谱与重金属元素的核外电子排布式联系起来, 观察重金属化合物的反射光谱特征; 结合晶体场理论分析重金属的特征反射峰出现的波段位置和原因。 以湖北大冶地区土壤样品为例, 向土样中添加不同浓度梯度的CrCl3, CuCl2和ZnCl2并测定其可见-近红外反射光谱, 研究不同种类不同浓度的重金属对土壤反射光谱的影响。 对样本的反射光谱进行不同光谱预处理, 探究重金属浓度与土壤反射光谱之间的线性相关关系及显著相关（p<0.05）波段出现的位置和潜在机理。 结果表明, 重金属化合物CrCl3, CuCl2和ZnCl2在可见光-短波近红外波段范围内的反射光谱特征与重金属元素3d轨道上的电子填充状态有关。 添加入土壤中的重金属化合物影响了土壤的可见-近红外反射光谱, 其浓度与土壤反射光谱之间整体呈负相关, 最大负相关系数分别为-0.788, -0.880和-0.824。 样品反射光谱经不同预处理后, 重金属浓度与土壤反射光谱之间的线性相关关系有所变化, 显著相关波段信息更加丰富。 研究表明, 重金属的可见-近红外反射光谱与重金属的电子结构紧密相关, 可见-近红外反射光谱技术可以检测到土壤中较高浓度重金属的存在, 该技术在快速高效、 无损低耗地预测土壤重金属元素含量方面拥有巨大潜力。 基于部分重金属化合物的可见-近红外反射光谱特征, 结合晶体场理论为土壤重金属的定性和定量反射光谱分析提供了理论依据和实验参考。

In this paper, the reflectance spectral features of chromium(CrCl3), copper chloride(CuCl2) and zinc chloride (ZnCl2) were measured by using visible and near-infrared reflectance spectroscopy (VNIRS). Thus, the spectra features integrating with the state of electrons arranged of heavy metal elements, and combined with the Crystal Field Theory were used to analyze where and why the wavebands of spectral features occurred. With the soil samples collected from Daye City, CrCl3, CuCl2 and ZnCl2 were added to them with different concentrations, and measured their VNIRS to study the impacts of different concentrations of heavy metals on soil reflectance spectra. Besides, the spectral data were transformed via different spectra pre-processing methods to explore the linear correlations between heavy metal concentrations and the reflectance spectra of the soil samples, and to study on where and why the Pearson’s significantly correlated wavebands (p<0.05) appeared and its potential mechanism. The results showed that the reflectance spectra in the range of visible and shortwave near-infrared of heavy metal compounds are related to the whether the 3d orbits of heavy metal elements filled by electron or not. The reflectance spectra of soil samples have been affected by the heavy metal compounds which were added, and negative correlations were revealed between the reflectance spectra data and the heavy metal concentrations. The maximum of the negative values of Pearson correlation coefficient were -0.788, -0.880, -0.824, respectively. There were some changes with the linear correlation between the heavy metal concentrations and the reflectance spectra, and the information of Pearson’s significantly correlated wavebands (p<0.05) became richer and more obvious after the reflectance spectra being pre-processed. This research indicated that the VNIRS of heavy metals are closely related to their electronic structure; the high concentrations of heavy metals in soils could be detected by the VNIRS technique, which has great potential in predicting soil heavy metal contents with rapid and efficient, non-destructive and cost-effective. Based on the VNIRS characteristics of some heavy metals, this paper integrated with the Crystal Field Theory to provide a theoretical basis and experimental reference for qualitative and quantitative analysis of reflectance spectroscopy of soil heavy metals.