Lake George as a Sink for Contaminants Derived from the Kilembe Copper Mining Area, Western Uganda

2005 ◽  
Vol 24 (3) ◽  
pp. 114-123 ◽  
Author(s):  
Tina Hartwig ◽  
Michael Owor ◽  
Andrew Muwanga ◽  
Dieter Zachmann ◽  
Walter Pohl
Keyword(s):  
Mining Area ◽  
Copper Mining ◽  
Western Uganda ◽  
Lake George

scholarly journals Joint MT and Gravity Inversion Using Structural Constraints: A Case Study from the Linjiang Copper Mining Area, Jilin, China

Minerals ◽  
2019 ◽  
Vol 9 (7) ◽  
pp. 407 ◽  
Author(s):  
Rongzhe Zhang ◽  
Tonglin Li ◽  
Shuai Zhou ◽  
Xinhui Deng
Keyword(s):  
Mining Area ◽  
Elastic Net ◽  
Gravity Inversion ◽  
Copper Mining ◽  
Structural Constraints ◽  
L1 Norm ◽  
Elastic Net Regularization ◽  
Gradient Constraints ◽  
Anomalous Bodies ◽  
Best Fit

We present a joint 2D inversion approach for magnetotelluric (MT) and gravity data with elastic-net regularization and cross-gradient constraints. We describe the main features of the approach and verify the inversion results against a synthetic model. The results indicate that the best fit solution using the L2 is overly smooth, while the best fit solution for the L1 norm is too sparse. However, the elastic-net regularization method, a convex combination term of L2 norm and L1 norm, can not only enforce the stability to preserve local smoothness, but can also enforce the sparsity to preserve sharp boundaries. Cross-gradient constraints lead to models with close structural resemblance and improve the estimates of the resistivity and density of the synthetic dataset. We apply the novel approach to field datasets from a copper mining area in the northeast of China. Our results show that the method can generate much more detail and a sharper boundary as well as better depth resolution. Relative to the existing solution, the large area divergence phenomenon under the anomalous bodies is eliminated, and the fine anomalous bodies boundary appeared in the smooth region. This method can provide important technical support for detecting deep concealed deposits.

Impact of tailings from the Kilembe copper mining district on Lake George, Uganda

2006 ◽  
Vol 51 (6) ◽  
pp. 1065-1075 ◽  
Author(s):  
Michael Owor ◽  
Tina Hartwig ◽  
Andrew Muwanga ◽  
Dieter Zachmann ◽  
Walter Pohl
Keyword(s):  
Copper Mining ◽  
Mining District ◽  
Lake George

Spatial Variability Analysis of Cu Content

2017 ◽  
Vol 8 (1) ◽  
pp. 81-93 ◽  
Author(s):  
Huy A. Hoang ◽  
Tuyen D. Vu ◽  
Thanh T. Nguyen
Keyword(s):  
Spatial Variability ◽  
Spatial Correlation ◽  
Data Distribution ◽  
Mining Area ◽  
Geochemical Data ◽  
Copper Mining ◽  
Sediment Samples ◽  
Variability Analysis ◽  
Cu Content ◽  
Robust Estimates

Conventional variogram has been widely applied to study spatial variability of geochemical data. In case of data is not normally distributed, the conventional estimator is biased. In this study, Cressie variogram and Moran correlogram were used to identify the degree of spatial variabilty of Cu content using 1341 stream sediment samples in Jiurui copper mining area. Cressie variogram was applied to reduce the influences of high values in identifying spatial variability in different directions. Moran correlogram was employed to study spatial correlation at different distances and the influences of data distribution on the results in quantitative ways. It was found that Cressie variogram yields stable robust estimates of the variogram with the maximum spatial variability of 12km for all directions; Moran correlogram provided more information, directly viewed and stable than variogram. Moran correlogram identified a strong positive spatial correlation at distances below 6km for the raw data and a strong positive spatial correlation at distances below 11km for Box-Cox transformed data.

scholarly journals Pollution Assessment of Trace Elements in Agricultural Soils around Copper Mining Area

2018 ◽  
Vol 10 (12) ◽  
pp. 4533 ◽  
Author(s):  
Xianfeng Cheng ◽  
Jarmila Drozdova ◽  
Tomas Danek ◽  
Qianrui Huang ◽  
Wufu Qi ◽  
...  
Keyword(s):  
Trace Elements ◽  
Agricultural Soils ◽  
Pollution Assessment ◽  
Mining Area ◽  
Potential Ecological Risk ◽  
Environmental Risks ◽  
National Standards ◽  
Copper Mining ◽  
Sources Of Pollution ◽  
Mining And Smelting Activities

Agricultural soils from Dongchuan copper mining area were sampled and analyzed to determine the concentrations of selected trace elements, namely As, Cd, Cr, Cu, Hg, Ni, Pb and Zn. The main objectives of this study were: (1) To determine the levels of trace elements and their spatial distribution in soils; (2) to evaluate the potential ecological risk; and (3) to identify the main sources of risk element pollution. The environmental risks were assessed using five different contamination and pollution indexes. Descriptive and exploratory statistical analyses were performed to identify the relations among the trace elements in soils and possible sources of pollution. Although the values of As, Cu and Zn in the soils were significantly higher than Yunnan background values and exceeded the limits of the Chinese national standards in several sampling points, the most serious threat for the ecosystem and human health was represented by Cd. The main sources of Cu and As were identified mining activities, airborne particulates from smelters and the weathering of tailings, and partly also agricultural fertilizers. The major source of Cd was agricultural fertilizers and partly sources associated with mining and smelting activities.

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