The Experts below are selected from a list of 237 Experts worldwide ranked by ideXlab platform
Yongcun Zhao - One of the best experts on this subject based on the ideXlab platform.
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effects of subsetting by Parent Materials on prediction of Soil organic matter content in a hilly area using vis nir spectroscopy
PLOS ONE, 2016Co-Authors: Xuezheng Shi, Meiyan Wang, Yongcun ZhaoAbstract:Assessment and monitoring of Soil organic matter (SOM) quality are important for understanding SOM dynamics and developing management practices that will enhance and maintain the productivity of agricultural Soils. Visible and near-infrared (Vis–NIR) diffuse reflectance spectroscopy (350–2500 nm) has received increasing attention over the recent decades as a promising technique for SOM analysis. While heterogeneity of sample sets is one critical factor that complicates the prediction of Soil properties from Vis–NIR spectra, a spectral library representing the local Soil diversity needs to be constructed. The study area, covering a surface of 927 km2 and located in Yujiang County of Jiangsu Province, is characterized by a hilly area with different Soil Parent Materials (e.g., red sandstone, shale, Quaternary red clay, and river alluvium). In total, 232 topSoil (0–20 cm) samples were collected for SOM analysis and scanned with a Vis–NIR spectrometer in the laboratory. Reflectance data were related to surface SOM content by means of a partial least square regression (PLSR) method and several data pre-processing techniques, such as first and second derivatives with a smoothing filter. The performance of the PLSR model was tested under different combinations of calibration/validation sets (global and local calibrations stratified according to Parent Materials). The results showed that the models based on the global calibrations can only make approximate predictions for SOM content (RMSE (root mean squared error) = 4.23–4.69 g kg−1; R2 (coefficient of determination) = 0.80–0.84; RPD (ratio of standard deviation to RMSE) = 2.19–2.44; RPIQ (ratio of performance to inter-quartile distance) = 2.88–3.08). Under the local calibrations, the individual PLSR models for each Parent material improved SOM predictions (RMSE = 2.55–3.49 g kg−1; R2 = 0.87–0.93; RPD = 2.67–3.12; RPIQ = 3.15–4.02). Among the four different Parent Materials, the largest R2 and the smallest RMSE were observed for the shale Soils, which had the lowest coefficient of variation (CV) values for clay (18.95%), free iron oxides (15.93%), and pH (1.04%). This demonstrates the importance of a practical subsetting strategy for the continued improvement of SOM prediction with Vis–NIR spectroscopy.
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sources of heavy metal pollution in agricultural Soils of a rapidly industrializing area in the yangtze delta of china
Ecotoxicology and Environmental Safety, 2014Co-Authors: Yongcun Zhao, Xiaoyan Zhao, Yudong Wang, Wenjing DengAbstract:The rapid industrialization and urbanization in developing countries have increased pollution by heavy metals, which is a concern for human health and the environment. In this study, 230 surface Soil samples (0-20cm) were collected from agricultural areas of Jiaxing, a rapidly industrializing area in the Yangtze Delta of China. Sequential Gaussian simulation (SGS) and multivariate factorial kriging analysis (FKA) were used to identify and explore the sources of heavy metal pollution for eight metals (Cu, Zn, Pb, Cr, Ni, Cd, Hg and As). Localized hot-spots of pollution were identified for Cu, Zn, Pb, Cr, Ni and Cd with area percentages of 0.48 percent, 0.58 percent, 2.84 percent, 2.41 percent, 0.74 percent, and 0.68 percent, respectively. The areas with Hg pollution covered approximately 38 percent whereas no potential pollution risk was found for As. The Soil Parent material and point sources of pollution had significant influences on Cr, Ni, Cu, Zn and Cd levels, except for the influence of agricultural management practices also accounted for micro-scale variations (nugget effect) for Cu and Zn pollution. Short-range (4km) diffusion processes had a significant influence on Cu levels, although they did not appear to be the dominant sources of Zn and Cd variation. The short-range diffusion pollution arising from current and historic industrial emissions and urbanization, and long-range (33km) variations in Soil Parent Materials and/or diffusion jointly determined the current concentrations of Soil Pb. The sources of Hg pollution risk may be attributed to the atmosphere deposition of industrial emission and historical use of Hg-containing pesticides.
Annamaria Lima - One of the best experts on this subject based on the ideXlab platform.
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u th signatures of agricultural Soil at the european continental scale gemas distribution weathering patterns and processes controlling their concentrations
Science of The Total Environment, 2018Co-Authors: Philippe Negrel, Benedetto De Vivo, Clemens Reimann, Anna Ladenberger, Domenico Cicchella, Stefano Albanese, Manfred Birke, Walter De Vos, Enrico Dinelli, Annamaria LimaAbstract:Abstract Agricultural Soil (Ap-horizon, 0–20 cm) samples were collected in Europe (33 countries, 5.6 million km2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) Soil-mapping project. The GEMAS survey area includes diverse groups of Soil Parent Materials with varying geological history, a wide range of climate zones, and landscapes. The Soil data have been used to provide a general view of U and Th mobility at the continental scale, using aqua regia and MMI® extractions. The U-Th distribution pattern is closely related to the compositional variation of the geological bedrock on which the Soil is developed and human impact on the environment has not concealed these genuine geochemical features. Results from both extraction methods (aqua regia and MMI®) used in this study support this general picture. Ternary plots of several Soil parameters have been used to evaluate chemical weathering trends. In the aqua regia extraction, some relative Th enrichment-U loss is related to the influence of alkaline and schist bedrocks, due to weathering processes. Whereas U enrichment-Th loss characterizes Soils developed on alkaline and mafic bedrock end-members on one hand and calcareous rock, with a concomitant Sc depletion (used as proxy for mafic lithologies), on the other hand. This reflects weathering processes sensu latu, and their role in U retention in related Soils. Contrary to that, the large U enrichment relative to Th in the MMI® extraction and the absence of end-member Parent material influence explaining the enrichment indicates that lithology is not the cause of such enrichment. Comparison of U and Th to the Soil geological Parent material evidenced i) higher capability of U to be weathered in Soils and higher resistance of Th to weathering processes and its enrichment in Soils; and, ii) the MMI® extraction results show a greater affinity of U than Th for the bearing phases like clays and organic matter. The comparison of geological units with U anomalies in agricultural Soil at the country scale (France) enables better understanding of U sources in the surficial environment and can be a useful tool in risk assessments.
Ruiqing Zhang - One of the best experts on this subject based on the ideXlab platform.
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spatial distribution and pollution assessment of heavy metals in urban Soils from southwest china
Journal of Environmental Sciences-china, 2012Co-Authors: Fengchang Wu, Ruiqing ZhangAbstract:Abstract To identify the concentrations and sources of heavy metals, and to assess Soil environmental quality, 63 Soil samples were collected in Yibin City, Sichuan Province, China. Mean concentrations of As, Pb, Zn, and Cu were 10.55, 61.23, 138.88 and 56.35 mg/kg, respectively. As concentrations were comparable to background values, while Pb, Zn, and Cu concentrations were higher than their corresponding background values. Industrial areas exhibited the highest concentrations of As, Pb, Zn, and Cu, while the lowest concentrations occurred in parks. Statistical analysis was performed and two cluster groups of metals were identified with Pb, Zn, and Cu in one group and As in the other. Spatial distribution maps indicated that Pb, Zn, and Cu were mainly controlled by anthropogenic activities, whereas As could be mainly accounted for by Soil Parent Materials. Pollution index values of As, Pb, Zn, and Cu varied in the range of 0.24–1.93, 0.66–7.24, 0.42–4.19, and 0.62–5.25, with mean values of 0.86, 1.98, 1.61, and 1.78, respectively. The integrated pollution index (IPI) values of these metals varied from 0.82 to 3.54, with a mean of 1.6 and more than 90% of Soil samples were moderately or highly contaminated with heavy metals. The spatial distribution of IPI showed that newer urban areas displayed relatively lower heavy metal contamination in comparison with older urban areas.
Philippe Negrel - One of the best experts on this subject based on the ideXlab platform.
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u th signatures of agricultural Soil at the european continental scale gemas distribution weathering patterns and processes controlling their concentrations
Science of The Total Environment, 2018Co-Authors: Philippe Negrel, Benedetto De Vivo, Clemens Reimann, Anna Ladenberger, Domenico Cicchella, Stefano Albanese, Manfred Birke, Walter De Vos, Enrico Dinelli, Annamaria LimaAbstract:Abstract Agricultural Soil (Ap-horizon, 0–20 cm) samples were collected in Europe (33 countries, 5.6 million km2) as part of the GEMAS (GEochemical Mapping of Agricultural and grazing land Soil) Soil-mapping project. The GEMAS survey area includes diverse groups of Soil Parent Materials with varying geological history, a wide range of climate zones, and landscapes. The Soil data have been used to provide a general view of U and Th mobility at the continental scale, using aqua regia and MMI® extractions. The U-Th distribution pattern is closely related to the compositional variation of the geological bedrock on which the Soil is developed and human impact on the environment has not concealed these genuine geochemical features. Results from both extraction methods (aqua regia and MMI®) used in this study support this general picture. Ternary plots of several Soil parameters have been used to evaluate chemical weathering trends. In the aqua regia extraction, some relative Th enrichment-U loss is related to the influence of alkaline and schist bedrocks, due to weathering processes. Whereas U enrichment-Th loss characterizes Soils developed on alkaline and mafic bedrock end-members on one hand and calcareous rock, with a concomitant Sc depletion (used as proxy for mafic lithologies), on the other hand. This reflects weathering processes sensu latu, and their role in U retention in related Soils. Contrary to that, the large U enrichment relative to Th in the MMI® extraction and the absence of end-member Parent material influence explaining the enrichment indicates that lithology is not the cause of such enrichment. Comparison of U and Th to the Soil geological Parent material evidenced i) higher capability of U to be weathered in Soils and higher resistance of Th to weathering processes and its enrichment in Soils; and, ii) the MMI® extraction results show a greater affinity of U than Th for the bearing phases like clays and organic matter. The comparison of geological units with U anomalies in agricultural Soil at the country scale (France) enables better understanding of U sources in the surficial environment and can be a useful tool in risk assessments.
Gafur Gozukara - One of the best experts on this subject based on the ideXlab platform.
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using vis nir and pxrf data to distinguish Soil Parent Materials an example using 136 pedons from wisconsin usa
Geoderma, 2021Co-Authors: Gafur Gozukara, Yakun Zhang, Alfred E HarteminkAbstract:Abstract Many Soils have two or more Parent Materials. It is not always possible to distinguish these Materials in a Soil pit or in the field. Here we present a study in the Driftless Area of Wisconsin, where Soils were developed in loess covering the weathered impurities of dolostone, termed terra rossa. We evaluated the geochemical signature of 136 pedons with loess (A and Bt) and/or terra rossa (2Bt) horizons and developed decision tree models to distinguish the Bt and 2Bt horizons from different geochemical indicators. In total 409 samples were collected from A, Bt, and 2Bt horizons and the samples were scanned using vis-NIR and pXRF spectrometers to obtain the color information, elemental data, and to calculate weathering indices. The Munsell color, texture, total carbon (TC), total nitrogen (TN), and pH were measured in the laboratory. Twenty one types of input data were compared in decision tree models. It was found that the 2Bt horizons had higher clay, pH, Mg, Al, Fe, Ca, Mn, Zn, Rb, CTR, and Ti/Zr than the loess A and Bt horizons. The Ruxten index (R), clay, horizon thickness (HT), CaO/TiO2 (CTR), and Ti/Zr were robust variables to distinguish loess Bt and terra rossa 2Bt using a decision tree model. However, similarities in the values of some elements and weathering indices compromised the characterizations of Bt and 2Bt horizons, which is the result of mixing of Parent Materials through bioturbation over time. It can be concluded that pXRF and vis-NIR spectra can be used to distinguish Parent Materials in Soil profiles, and pXRF spectra had slightly better overall accuracy than vis-NIR spectra.