We analyzed chemical composition, mineralogy, and spectral characteristics of the tailings of a hydrothermal gold mine in South Korea. We measured spectral responses of tailings to arsenic (As) and lead (Pb) concentration and developed and validated a prediction model for As and Pb in the tailings. The tailing was heavily contaminated with heavy metal elements and composed of rock forming minerals, gangue minerals and hydrothermal alteration minerals. The spectral features of the tailing were closely related to hydrothermal alteration minerals. The spectral responses associated with As and Pb concentrations were detected in shortwave infrared (SWIR) region at absorption positions of the hydrothermal alteration minerals. The prediction models were constructed using spectral bands of absorption features of the hydrothermal alteration minerals and were statistically significant. We found distinctive differences in spectral characteristics and spectral response to heavy metal contamination between the tailings and soils in the mining area. While the spectral signals to heavy metal concentration of tailings were associated with the hydrothermal alteration minerals, those of soils in mining area were manifested by clay minerals originated from weathering processes. This infers that geological processes associated with formation of soils and tailings are the major controlling factors of spectral responses to heavy metal contamination. This study provides a rare reference for the estimation of As and Pb concentration in the tailings with similar types of ore deposit and host rock.

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The spectral response to arsenic (As) stress of pine needles (Pinus densiflora Siebold and Zucc.) from an abandoned lead (Pb)–zinc (Zn) mine was investigated based on chemical and spectroscopic analyses. The correlation analysis between the content of As in needle samples and that of soils and spectral parameters of the needle samples were conducted. The results showed very high correlation between As content in pine needles and soils. The major spectral response of pine needles to the As stress were characterized by the increase in the green and red color reflectance, the decrease in the first derivatives at 1648 nm, and the shrink in the red absorption feature. These changes were caused by the pigment content loss and the structural changes of phenolic compounds in the pine needles due to the As content. The linear regression analysis with the stepwise method showed the first derivatives at 668 nm and 1648 nm were the most useful variables in the regression model for As content prediction in pine needles. The As index of pine needles could be used to detect As content in soils associated with As and heavy metals contamination and/or mineralization in coniferous forests.

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