Spectroscopic response of soil organic matter in mining area to Pb/Cd heavy metal interaction: A mirror of coherent structural variation

2020 ◽  
Vol 393 ◽  
pp. 122425 ◽  
Author(s):  
Wei Chen ◽  
Li Peng ◽  
Keren Hu ◽  
Zhang Zhang ◽  
Changhong Peng ◽  
...  
2013 ◽  
Vol 9 (3) ◽  
pp. 201-206 ◽  

The hydrological basin of Keritis in Chania, Greece is mainly an agricultural area where various agrochemicals are used. In topsoils, the total and available forms of Cu, Zn, Pb and Cr were determined after their extraction with boiling Aqua Regia and DTPA respectively. Although the total heavy metal concentrations in Keritis soils were similar to the total concentrations in other agricultural areas, the studied soils can not be described as heavily polluted. The bioavailable concentrations of Cu, Zn, Pb and Cr were low. The relative availability and comparative mobility followed the order of Cu>Pb>Zn>Cr and was closely related to the soil organic matter.


Sensors ◽  
2020 ◽  
Vol 20 (6) ◽  
pp. 1795 ◽  
Author(s):  
Chuanmei Zhu ◽  
Zipeng Zhang ◽  
Hongwei Wang ◽  
Jingzhe Wang ◽  
Shengtian Yang

Soil organic matter (SOM) is a crucial indicator for evaluating soil quality and an important component of soil carbon pools, which play a vital role in terrestrial ecosystems. Rapid, non-destructive and accurate monitoring of SOM content is of great significance for the environmental management and ecological restoration of mining areas. Visible-near-infrared (Vis-NIR) spectroscopy has proven its applicability in estimating SOM over the years. In this study, 168 soil samples were collected from the Zhundong coal field of Xinjiang Province, Northwest China. The SOM content (g kg−1) was determined by the potassium dichromate external heating method and the soil reflectance spectra were measured by the spectrometer. Two spectral feature extraction strategies, namely, principal component analysis (PCA) and the optimal band combination algorithm, were introduced to choose spectral variables. Linear models and random forests (RF) were used for predictive models. The coefficient of determination (R2), root mean square error (RMSE), and the ratio of the performance to the interquartile distance (RPIQ) were used to evaluate the predictive performance of the model. The results indicated that the variables (2DI and 3DI) derived from the optimal band combination algorithm outperformed the PCA variables (1DV) regardless of whether linear or RF models were used. An inherent gap exists between 2DI and 3DI, and the performance of 2DI is significantly poorer than that of 3DI. The accuracy of the prediction model increases with the increasing number of spectral variable dimensions (in the following order: 1DV < 2DI < 3DI). This study proves that the 3DI is the first choice for the optimal band combination algorithm to derive sensitive parameters related to SOM in the coal mining area. Furthermore, the optimal band combination algorithm can be applied to hyperspectral or multispectral images and to convert the spectral response into image pixels, which may be helpful for a soil property spatial distribution map.


2021 ◽  
Vol 232 (5) ◽  
Author(s):  
Dawid Kupka ◽  
Mateusz Kania ◽  
Marcin Pietrzykowski ◽  
Adam Łukasik ◽  
Piotr Gruba

AbstractIntensified vehicular traffic causes increased heavy metal contamination of the environment. We investigated the heavy metal chemistry of soils located under silver fir stands in the vicinity of Poland’s S7 roadway. Three sampling sites were located in fir stands in central Poland. Fieldwork included soil sampling of the organic (O) horizon and mineral (A) topsoil. We analyzed the soil pH, carbon (C) and nitrogen (N) concentration, and the HCl-extractable forms of sodium (Na) and heavy metals: copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn). The stoichiometric ratios Cu:C, Ni:C, Pb:C, and Zn:C were also calculated. In all sites, a higher Na concentration was found in the 0–10 m from the forest edge. This zone was characterized by increased pH in the O horizon, increased Zn and Ni in the A horizon, and a decreased Pb in the O horizon. There was no clear pattern for the Cu concentration. The Ni:C and Zn:C ratios were correlated with pH, while Pb:C and Cu:C ratios were correlated with the clay minerals. HCl-extractable Ni and Zn concentrations in A horizon were greater near the roadway, revealing strong pH dependency. The roadway affects the geochemical background of the topsoil in the nearby fir stands. Mechanistically, we suggest that Na increases the soil pH and therefore enhances the ability of soil organic matter to bind Ni and Zn by releasing hydrogen from soil organic matter functional groups into the soil solution. A depleted Pb near the road was likely owing to the strong competition from Na.


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