The application of THz-TDS in the characterization of Bayan Obo magnetite ore composition.

The application of terahertz time-domain spectroscopy (THz-TDS) in the quantitative analysis of major minerals in Bayan Obo magnetite ore was explored. The positive correlation between the optical parameters of the original ore and its iron content is confirmed. The detections of three main iron containing minerals, including magnetite, pyrite, and hematite, were simulated using corresponding reagents. The random forest algorithm is used for quantitative analysis, and FeS2 is detected with precision of R2 = 0.7686 and MAE = 0.6307% in ternary mixtures. The experimental results demonstrate that THz-TDS can distinguish specific iron containing minerals and reveal the potential application value of this testing method in exploration and mineral processing fields.

Three-stage niobium mineralization at Bayan Obo, China.

The Chinese Bayan Obo deposit is a world-class rare earth element (REE) deposit with considerable niobium (Nb) and iron (Fe) resources. A complete genetic understanding on all metals is fundamental for establishing genetic models at Bayan Obo. With extensive research being focused on REE enrichment, the timing and controls of Nb enrichment remain unresolved at Bayan Obo, which is mainly due to the challenges in dating, i.e. multistage thermal events, fine-grained minerals with complex textures and the rare occurrence of uranium-enriched minerals with mature dating methods. Based on robust geological and petrographic frameworks, here we conducted ion probe uranium-lead (U-Pb) dating of ferrocolumbite to unravel the timing, hence the genesis of Nb mineralization. Three types of hydrothermal ferrocolumbites-key Nb-bearing minerals-are identified based on their textures and mineral assemblages. They yield U-Pb ages of 1312 ± 47 Ma (n = 99), 438 ± 7 Ma (n = 93), and 268 ± 5 Ma (n = 19), respectively. In line with deposit geology, we tentatively link the first, second and third stage Nb mineralization to Mesoproterozoic carbonatite magmatism, ubiquitous early Paleozoic hydrothermal activity, and Permian granitic magmatism, respectively. While quantifying the contribution of metal endowment from each stage requires further investigation, our new dates highlight that multi-stage mineralization is critical for Nb enrichment at Bayan Obo, which may also have implications for the enrichment mechanism of Nb in REE deposits in general.

A human health risk assessment of rare earth elements through daily diet consumption from Bayan Obo Mining Area, China.

Rare earth elements (REEs) have been broad application in a range of industries, including the electronics industry, advanced materials, and medicine. However, health risks associated with REEs received increasing attention. 31 residents (16 males and 15 females) from Bayan Obo mining in Inner Mongolia, China, were enrolled in this study. In total, 677 food samples, the major human exposure matrices (drinking water and duplicate diets), and bio-samples (urine and blood) of 31 participants were obtained. The concentrations of REEs were measured to characterize their external and internal exposures, and the potential health risk of exposure to REE through the ingestion route was analyzed. The results revealed that the detection rate in blood samples (100%) is higher than in urine (32.86%), and only a few REEs were detected in water samples (8.06%), the urine concentrations were considerably lower than in blood. Exposure to REEs through drinking water was considered negligible compared to food intake. Lanthanum and cerium were the most concentrated REEs in food samples. Health risks were calculated based on a dose-response model, the total hazard quotients (THQ) values for all food groups were within normal levels, and the Monte Carlo simulation results show that the 5th, the 50th, and the 95th percentile values of HI were found as 1.45 × 10-2, 3.52 × 10-2, and 9.13 × 10-2, respectively, neither exceeds the threshold, indicating low health risks associated with food intake exposure for this area. The sensitivity results suggest that underweight people are at higher risk, cerium, lanthanum, and yttrium concentrations, and food intake contributes more to health risks. The use of probability distribution methods can improve the accuracy of the results. The cumulative health risk through food intake is negligible, and further attention should be paid to the health risk induced by other routes of exposure to REEs by the local residents.

Exploring rare earth mineral recovery through characterization of riebeckite type ore in Bayan Obo.

The aim of this study was to characterize the riebeckite type rare earth ore found in the Bayan Obo deposit, in order to identify the distribution and occurrence of both rare earths and gangue species within the ore. Several analytical techniques were utilized to accomplish this, such as chemical analysis, quantitative XRD, a single polarizing microscope, and a mineral automatic analysis system. The analysis revealed that the primary rare earth minerals (REMs) in the ore were bastnaesite and monazite, with huanghoite, parisite, aeschynite, and fergusonite identified as secondary rare earth minerals. The main gangue species was magnetite, accompanied by smaller quantities of riebeckite and dolomite. The ore was rich in rare earth oxides, with a 3.81 wt% grade. The screen analysis of the pulverized ore indicates that the 43-100 µm fraction is the dominant size, while the finer size fractions below 43 µm contain the bastnaesite and monazite, as well as huanghoite, parisite, aeschynite, and fergusonite. Microstructural characterization showed that the REMs were both coarse-grained and fine-grained, occurring as granular aggregates and fine disseminations within the gangue. Bastnaesite and monazite were the major REMs, with dominant amounts of cerium, lanthanum, praseodymium, and neodymium, while parasite was identified as an impurity. Huanghoite and parisite contained barium and calcium as impurities, respectively. Aeschynite and fergusonite were REMs that included niobium in their composition. Bastnaesite and monazite were found to contain a much higher rare earth content than huanghoite, parisite, aeschynite, and fergusonite. Potential methods for recovering rare earths from this ore, such as magnetic separation and froth flotation, have been identified and may be applicable to similar ferruginous rare earth-bearing ores.

Selection of optimal models for predicting growth stress in Artemisia desertorum by comparison of linear regression and multiple neural networks: Take the construction of a green mine in the Bayan Obo mine as an example.

In recent years, more and more countries are focusing on the control of mining sites and the surrounding ecological environment, and the new environmental concept of green mines has been proposed. By investigating the ecological background of a mine site, pollution and ecological imbalances in the mine can be predicted, managed or transformed. This study investigated the effects of rare earth elements on plant growth in the Baotou Bayan Obo Rare Earth Mine and evaluated soil contamination and subsequent remediation through the measured plant height. Using linear regression, BP(Back Propagation) neural networks, GA-BP(Genetic Algorithm- Back Propagation) neural networks, ELM(Extreme Learning Machine) and GA-ELM(Genetic Algorithm- Extreme Learning Machine) model prediction instruments, the different rare earth solution concentrations were set as input values and the heights of Artemisia desertorum, which as the model plant, were set as output values in the prediction. The results showed that the linear regression predicted the standard error of single La(III), Ce(III) solution and compound La(III) + Ce(III) solution for Artemisia desertorum growth stress was on the high side, 7.02%- 8.92%; the efficiency range of each group of models under BP neural network, GA-BP neural network and ELM neural network were 1.15%- 2.53%, 0.85%- 1.28%, 1.76%- 3.53%; while the efficiency range under GA-ELM neural network was 0.59%- 0.68%, with average error values and predicted values close to the true values. Among them, the MAPE of GA-ELM neural network are significantly lower than other models, and the error decreases with increasing concentration of the compound solution. So GA-ELM neural network can be used as an efficient, fast and reasonable optimal model for predicting the growth stress of Artemisia desertorum in Bayan Obo mining area. The experimental results can provide a theoretical basis for assessing the risk of soil rare earth contamination in the area, evaluating the expectation of later remediation, and provide a degree of new ideas for the construction of green mines.

Life Cycle Assessment studies of rare earths production - Findings from a systematic review.

Rare earth elements (REEs) are one of the most important elements used for transformation of the fossil era into a decarbonized future. REEs are essential for wind, electric and hybrid vehicles, and low-energy lighting. However, there is a general understanding that REEs come along with multiple environmental problems during their extraction and processing. Life cycle assessment (LCA) is a well-established method for a holistic evaluation of environmental effects of a product system considering the entire life cycle. This paper reviews LCA studies for determining the environmental impacts of rare earth oxide (REO) production from Bayan Obo and ion adsorption clays (IAC) in China, and shows why some studies lead to over- and underestimated results. We found out that current LCA studies of REE production provide a good overall understanding of the underlying process chains, which are mainly located in China. However, life cycle inventories (LCI) appear often not complete. Several lack accuracy, consistency, or transparency. Hence, resulting environmental impacts are subject to great uncertainty. This applies in particular to radioactivity and the handling of wastewater and slurry in tailing ponds, which have often been neglected. This article reviews 35 studies to identify suitable LCAs for comparison. The assessment covers the world's largest REO production facility, located in Bayan Obo, as well as in-situ leaching of IACs in the Southern Provinces of China. A total of 12 studies are selected, 8 for Bayan Obo and IACs each. The LCIs of these studies are reviewed in detail. The effects of over- and underestimated LCIs on the life cycle impact assessment (LCIA) are investigated. The partly controversial results of existing LCAs are analyzed thoroughly and discussed. Our results show that an increased consistency in LCA studies on REO production is needed.

Anomalous abundance and redistribution patterns of rare earth elements in soils of a mining area in Inner Mongolia, China.

The Bayan Obo Mine, the largest rare earth element (REE) deposit ever found in the world, has been mined for nearly 60 years for iron and rare earth elements. To assess the influences of mining activities on geochemical behavior of REEs in soils, 27 surface soil samples and three soil profile samples were collected from different directions in the vicinity of the mine area. The total concentrations of REEs in surface soils varied from 149.75 to 18,891.81 mg kg(-1) with an average value of 1906.12 mg kg(-1), which was apparently higher than the average values in China (181 mg kg(-1)). The order of the average concentrations of individual REEs in surface soils was similar to that in Bayan Obo ores, which confirmed that the concentration and distribution of REEs in the soils was influenced by the mining activities. The concentrations of single REE in the soil profiles showed a similar trend with depth with an increase at 0-25 cm section, then decreased and remained relatively stable in the deep part. The normalized curves inclined to the right side, showing the conspicuous fractionation between the light and heavy REEs, which supported by the North American Shale Composite (NASC) and Post-Archean Australian Shale (PAAS) normalized concentration ratios calculated for selected elements (La N /Yb N , La N /Sm N , Gd N /Yb N ). Slight positive Ce anomaly and negative Eu anomaly were also observed.

In-situ gamma-ray survey of rare-earth tailings dams--A case study in Baotou and Bayan Obo Districts, China.

An in-situ gamma-ray spectrometer survey with a scintillation detector of NaI(Tl) (Φ75 mm × 75 mm) was carried out in the Baotou and Bayan Obo Districts in order to estimate the levels of natural radionuclides near rare-earth (RE) tailings dams. In the RE tailings dam of Baotou, the mean concentrations of (238)U and (232)Th were 3.0 ± 1.0 mg/kg (range: 1.9-4.6 mg/kg) and 321 ± 31 mg/kg (range: 294-355 mg/kg), respectively. In the Bayan Obo tailings dam, the mean concentrations of (238)U and (232)Th were 5.7 ± 0.5 mg/kg (range: 5.3-6.1 mg/kg) and 276 ± 0.5 mg/kg (range: 275.5-276.3 mg/kg), respectively. The average (232)Th concentrations in the mining areas of the Bayan Obo Mine and the living areas of the Bayan Obo Town were 18.7 ± 7.5 and 26.2 ± 9.1 mg/kg, respectively. The (232)Th concentration recorded in the tailings dams was much higher than the global average (7.44 mg/kg). Our investigation shows that the (232)Th concentration in the tailings in the Baotou dam was 34.6 times greater than that in the local soil (in Guyang County); the average concentrations of (232)Th in the soil in the Baotou District and Bayan Obo Districts were about 1.35 and 2.82 times greater, respectively, than that in the soil in Guyang County. Based on our results, the highest estimated effective dose due to gamma irradiation was 1.15 mSv per year, estimated from the data observed in the Baotou tailings dams. The results of this preliminary study indicate the potential importance of radioactivity in RE tailings dams and that remedial measures may be required.

Hydrogeochemical signatures and evolution of groundwater impacted by the Bayan Obo tailing pond in northwest China.

Uncontrolled leakage from mine tailing ponds can pose a serious environmental threat. Groundwater quality in a semi-arid region with extensive worries about the leakage from one of world's largest tailing ponds is studied herein through an integrated hydrogeochemical analysis and multivariate statistical analysis. Results show that elevated concentrations of NO2(-), B, Mn, NH4(+), F(-), and SO4(2-) in groundwater were probably caused by leakage from the tailing pond and transported with the regional groundwater flow towards downstream Yellow River. While NO2(-) contamination is only limited to areas close to the pond, high B concentrations persist within the contaminated plume originating from the tailing pond. Our current study shows that there is no geochemical evidence for U and Th contamination in groundwater due to leakage from the Bayan Obo tailing pond. Combining effects which includes regional variations, pond leaking and downstream mixing, mineral precipitation and dissolution, redox processes, ion exchange processes and agricultural activities, controlled groundwater hydrogeochemical signatures in the studied area. This study demonstrate that an increase in knowledge of evolution of groundwater quality by integrating field hydrochemical data and multivariate statistical analysis will help understand major water-rock interactions and provide a scientific basis for protection and rational utilization of groundwater resources in this and other tailing-impacted areas.

Rare earth element components in atmospheric particulates in the Bayan Obo mine region.

The Bayan Obo mine, located in Inner Mongolia, China, is the largest light rare earth body ever found in the world. The research for rare earth elements (REEs) enrichment in atmospheric particulates caused by mining and ore processing is fairly limited so far. In this paper, atmospheric particulates including total suspended particulate (TSP) matter and particles with an equivalent aerodynamic diameter less than 10 µm (PM10) were collected around the Bayan Obo mine region, in August 2012 and March 2013, to analyze the levels and distributions of REEs in particles. The total concentrations of REEs for TSP were 149.8 and 239.6 ng/m(3), and those for PM10 were 42.8 and 68.9 ng/m(3), in August 2012 and March 2013, respectively. Enrichment factor was calculated for all 14 REEs in the TSP and PM10 and the results indicated that REEs enrichment in atmosphere particulates was caused by anthropogenic sources and influenced by the strong wind in springtime. The spatial distribution of REEs in TSP showed a strong gradient concentration in the prevailing wind direction. REE chondrite normalized patterns of TSP and PM10 were similar and the normalized curves inclined to the right side, showing the conspicuous fractionation between the light REEs and heavy REE, which supported by the chondrite normalized concentration ratios calculated for selected elements (La(N)/Yb(N), La(N)/Sm(N), Gd(N)/Yb(N)).