The increased production and price of rare earth elements(REEs) are indicative of their importance and of growing global attention. More accurate and practical exploration procedures are needed for REEs, and for other...The increased production and price of rare earth elements(REEs) are indicative of their importance and of growing global attention. More accurate and practical exploration procedures are needed for REEs, and for other geochemical resources. One such procedure is a multivariate approach. In this study, five classifiers, including multilayer perceptron(MLP), Bayesian, k-Nearest Neighbors(KNN), Parzen, and support vector machine(SVM),were applied in supervised pattern classification of bulk geochemical samples based on REEs, P, and Fe in the Kiruna type magnetite-apatite deposit of Se-Chahun,Central Iran. This deposit is composed of four rock types:(1) High anomaly(phosphorus iron ore),(2) Low anomaly(metasomatized tuff),(3) Low anomaly(iron ore), and(4)Background(iron ore and others). The proposed methods help to predict the proper classes for new samples from the study area without the need for costly and time-consuming additional studies. In addition, this paper provides a performance comparison of the five models. Results show that all five classifiers have appropriate and acceptable performance. Therefore, pattern classification can be used for evaluation of REE distribution. However, MLP and KNN classifiers show the same results and have the highest CCRs in comparison to Bayesian, Parzen, and SVM classifiers. MLP is more generalizable than KNN and seems to be an applicable approach for classification and predictionof the classes. We hope the predictability of the proposed methods will encourage geochemists to expand the use of numerical models in future work.展开更多
A total of 24 soil samples were collected from areas around Artisanal Gold and associated Pb-Zn-Cu sulfide mining and mineral processing sites in the Anka mining district of Zamfara State, NW Nigeria. The samples were...A total of 24 soil samples were collected from areas around Artisanal Gold and associated Pb-Zn-Cu sulfide mining and mineral processing sites in the Anka mining district of Zamfara State, NW Nigeria. The samples were geochemically analyzed with the main objective of assessing the degree of Pb and Hg pollution in the environment resulting from the mining and mineral ore processing activities in the mining district and to consider the effect on human health. The assessment of the degree of pollution or toxicity was based on the Igeo （index of geoaccummulation） and EF （enrichment factor） where the former gives a quantitative pollution class with respect to the quality of the medium analyzed, while the latter differentiates between metals originating from anthropogenic activities and those from natural processes. The geochemical results show that the concentrations of Pb and Hg especially at the mineral processing sites significantly exceed the established thresholds （4,152 ppm and 12.92 ppm respectively）. The calculated EF values for both Pb and Hg revealed that the soils from the entire mining district are extremely enriched in these elements, essentially originating from the anthropogenic activities （EF= 〉〉 40）. Lead and Mercury are toxic heavy metals with documented long-lasting adverse human health effects. These calls for efficient bioremediation measures for the removal of Pb and Hg from the contaminated soils that take into account the geochemical peculiarities of the mining district.展开更多
Changping Plain, located in the northwest of Beijing, has become an important groundwater recharge area for the Beijing Plain and an important source for the urban water supply. In this study, groundwater samples were...Changping Plain, located in the northwest of Beijing, has become an important groundwater recharge area for the Beijing Plain and an important source for the urban water supply. In this study, groundwater samples were collected during the dry and wet seasons in 2015 from 24 monitoring wells distributed in Changping Plain. A Piper-Tri-linear diagram, a Schoeller diagram, a Gibbs diagram, and the isotope technique were used to investigate the temporal and spatial variations in the concentrations of groundwater hydrochemicals and the sources of groundwater recharge. The results indicated： 1） seasonal variations in the concentrations of HCO3^–, Ca^2＋, and Na^＋ were significant; the spatial variations of these ions were more dramatic in the dry season than in the wet season due to the dilution effect of precipitation; 2） Most groundwater samples had a HCO3-Ca-Mg based hydrochemical type and a few had a HCO3-Na-K based hydrochemical type; the hydrochemical type tended to evolve from HCO3-Ca-Mg based to HCO3-Na-K based in some monitoring wells that showed distinct seasonal variation; 3） the groundwater in the study area originated mainly from atmospheric precipitation, and it is affected by evaporation and concentration processes.展开更多
文摘The increased production and price of rare earth elements(REEs) are indicative of their importance and of growing global attention. More accurate and practical exploration procedures are needed for REEs, and for other geochemical resources. One such procedure is a multivariate approach. In this study, five classifiers, including multilayer perceptron(MLP), Bayesian, k-Nearest Neighbors(KNN), Parzen, and support vector machine(SVM),were applied in supervised pattern classification of bulk geochemical samples based on REEs, P, and Fe in the Kiruna type magnetite-apatite deposit of Se-Chahun,Central Iran. This deposit is composed of four rock types:(1) High anomaly(phosphorus iron ore),(2) Low anomaly(metasomatized tuff),(3) Low anomaly(iron ore), and(4)Background(iron ore and others). The proposed methods help to predict the proper classes for new samples from the study area without the need for costly and time-consuming additional studies. In addition, this paper provides a performance comparison of the five models. Results show that all five classifiers have appropriate and acceptable performance. Therefore, pattern classification can be used for evaluation of REE distribution. However, MLP and KNN classifiers show the same results and have the highest CCRs in comparison to Bayesian, Parzen, and SVM classifiers. MLP is more generalizable than KNN and seems to be an applicable approach for classification and predictionof the classes. We hope the predictability of the proposed methods will encourage geochemists to expand the use of numerical models in future work.
文摘A total of 24 soil samples were collected from areas around Artisanal Gold and associated Pb-Zn-Cu sulfide mining and mineral processing sites in the Anka mining district of Zamfara State, NW Nigeria. The samples were geochemically analyzed with the main objective of assessing the degree of Pb and Hg pollution in the environment resulting from the mining and mineral ore processing activities in the mining district and to consider the effect on human health. The assessment of the degree of pollution or toxicity was based on the Igeo （index of geoaccummulation） and EF （enrichment factor） where the former gives a quantitative pollution class with respect to the quality of the medium analyzed, while the latter differentiates between metals originating from anthropogenic activities and those from natural processes. The geochemical results show that the concentrations of Pb and Hg especially at the mineral processing sites significantly exceed the established thresholds （4,152 ppm and 12.92 ppm respectively）. The calculated EF values for both Pb and Hg revealed that the soils from the entire mining district are extremely enriched in these elements, essentially originating from the anthropogenic activities （EF= 〉〉 40）. Lead and Mercury are toxic heavy metals with documented long-lasting adverse human health effects. These calls for efficient bioremediation measures for the removal of Pb and Hg from the contaminated soils that take into account the geochemical peculiarities of the mining district.
基金National Natural Science Foundation of China(41572240)
文摘Changping Plain, located in the northwest of Beijing, has become an important groundwater recharge area for the Beijing Plain and an important source for the urban water supply. In this study, groundwater samples were collected during the dry and wet seasons in 2015 from 24 monitoring wells distributed in Changping Plain. A Piper-Tri-linear diagram, a Schoeller diagram, a Gibbs diagram, and the isotope technique were used to investigate the temporal and spatial variations in the concentrations of groundwater hydrochemicals and the sources of groundwater recharge. The results indicated： 1） seasonal variations in the concentrations of HCO3^–, Ca^2＋, and Na^＋ were significant; the spatial variations of these ions were more dramatic in the dry season than in the wet season due to the dilution effect of precipitation; 2） Most groundwater samples had a HCO3-Ca-Mg based hydrochemical type and a few had a HCO3-Na-K based hydrochemical type; the hydrochemical type tended to evolve from HCO3-Ca-Mg based to HCO3-Na-K based in some monitoring wells that showed distinct seasonal variation; 3） the groundwater in the study area originated mainly from atmospheric precipitation, and it is affected by evaporation and concentration processes.
