A new three-band spectral and metal element index for estimating soil arsenic content around the mining area
| Autor: | Wei Zhang, Yu Cui, Guobiao Yao, Feisheng Feng, Pingjie Fu, Keming Yang, Fei Meng |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Spectral index
Environmental Engineering Materials science Correlation coefficient General Chemical Engineering Analytical chemistry chemistry.chemical_element Derivative Spectral line VNIR Metal chemistry Aluminium visual_art visual_art.visual_art_medium Environmental Chemistry Safety Risk Reliability and Quality Arsenic |
| Zdroj: | Process Safety and Environmental Protection. 157:27-36 |
| ISSN: | 0957-5820 |
| DOI: | 10.1016/j.psep.2021.10.028 |
| Popis: | Owing to the advantages of fast and non-destructive measurement, visible and near-infrared reflectance (VNIR) spectra have been widely used in the study of heavy metal pollution. However, few studies have focused on the estimation of soil heavy metal concentration by the enhanced joint architecture of spectral indices and metal elements enriched in clay minerals. In this work, a new composite index, namely Three-band Spectral and Metal Element Index (TSMEI), is proposed to retrieve arsenic (As) in soil by utilizing the multi-view spectral information. Based on obtained data, including spectra and the concentration of iron (Fe), potassium (K), aluminum (Al), magnesium (Mg) and arsenic (As) of the soil around the open-pit coal mine area, the three-band spectral index (TBSI) for As, K, Fe, Mg and Al were calculated from four types of spectral data, that is, raw reflectance (R), the first-order derivative of the spectrum (FD), spectral continuum removal (CR) and spectral reciprocal logarithmic (RL). Then, the metal element index (MEI) for As concentration were constructed via estimated content of K, Fe, Mg and Al based on their TBSIs. Finally, the optimized TBSIs and MEIs were used to construct TSMEI, and it was combined with random forest to invert the As concentration. The following conclusions are drawn: TBSIs is significantly better than that dual-band spectral index and single-band spectrum for estimating As content, and the correlations between the TBSIs based on the FD and the As concentration perform best (r ≥ 0.7684). In addition, two/three element MEIs show higher correlation coefficients with As concentration compared to individual metal element. Furthermore, the proposed TSMEI allow high-precision estimation of As content, which acquired highest correlation coefficient and lowest RMSE (r=0.9732, RMSE=0.0703). The results confirm that the TSMEI is significantly effective in estimating soil As content. |
| Databáze: | OpenAIRE |
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