Source, environmental behavior and potential health risk of rare earth elements in Beijing urban park soils

Uncovering rare earth and precious metal in landfill-mined soil-like-fractions: distribution prediction, ecological risk and resource potential

The introduction of rare earth elements (REEs) and precious metals (PMs) containing wastes in aged landfills leads to a significant pollutant and resource potential. Against this backdrop, the accumulation of REEs and PMs in soil-like-fractions (SLF) remains uncertain. This study pioneers a comprehensive analysis of the REE/PM speciation, ecological risks of REEs and economic potential of PMs in SLF. Concentrations of REEs and PMs varied from 146.14 to 464.28 mg/kg and 4.20-111.86 mg/kg, respectively, with a particular enrichment in the upper SLF. REEs and PMs were immobilized by SLF and stabilized into organic- and mineral-bound fractions. A dataset linking urban development and landfill conditions to REE/PM concentrations was created, and the Support Vector Regression (SVR) model was utilized to achieve high-precision prediction of REEs and PMs content (R2 > 0.9). The Shapley Additive Explanations (SHAP) algorithm revealed development of electronics industry as the primary driver of REE/PM enrichment, followed by organic matter content in SLF. The potential ecological risk index (PERI) showed limited risks of REEs, but the bioavailable REEs posed long-term accumulation and chronic toxicity in terrestrial organisms, emphasizing the detoxification before SLF reusage. The economic potential of PMs reached 871.82 USD per ton of SLF, higher than primary minerals. These findings provide new insights into valuable resources during landfill mining and suggest potential areas for applying modern techniques, such as machine learning, to landfill management.

Health risks of rare earth elements exposure: Impact on mitochondrial DNA copy number and micronucleus frequency

Toxic effects in terms of mitochondria and hereditary substances have been characterized in vitro for individual rare earth elements, while, the joint effects of mixed elements exposure in the population remain ambiguous. Based on the Occupational Chromate Exposure Dynamic Cohort of China, this study investigated the relationship between 15 blood rare earth elements (cerium, dysprosium, erbium, europium, gadolinium, holmium, lanthanum, lutetium, neodymium, praseodymium, samarium, terbium, thulium, yttrium, and ytterbium) and mitochondrial DNA copy number (MtDNACN) as well as peripheral blood lymphocyte micronucleus frequency (MNF). The elastic net was used to select elements highly correlated with effect indicators, whose dose-response relationships were further illustrated by restricted cubic splines. Bayesian kernel regression was employed to explore the combined effects of elements and the contributions of single element. The results showed that most rare earth elements were positively correlated with effect indicators, with yttrium showing the strongest association (β (95% CI): 0.139 (0.1089 - 0.189) for MtDNACN, 0.937 (0.345 - 1.684) for MNF). In the mixed exposure model, with the exposure level fixed at the 50th percentile as the reference, the effect estimates on MtDNACN and MNF increased by 0.228 and 0.598 units, respectively, at the 75th percentile. The single effect analysis implied that yttrium, lanthanum and terbium contributed the most to the elevation of MtDNACN, while yttrium posed the highest risk for genetic damage, accordingly, we provided recommendations to prioritize these elements of concern. In addition, we observed a chief mediating effect of MtDNACN on the elevation of MNF caused by lanthanum, whereas further mechanistic exploration is required to confirm this finding.

Sex disparities in the association between rare earth elements exposure and genetic mutation frequencies in lung cancer patients

The ubiquitous use of rare earth elements (REEs) in modern living environments raised concern about their impact on human health. With the detrimental and beneficial effects of REEs reported by different studies, the genuine role of REEs in the human body remains a mystery. This study explored the association between REEs and genetic mutations in patients with lung adenocarcinoma (LUAD). A cohort of 53 LUAD patients underwent tumor DNA sequencing (1123 cancer-related genes) and plasma REE (lanthanum (La), cerium (Ce), praseodymium (Pr), neodymium (Nd), and yttrium (Y)) quantification. We found divergent relationships between plasma REE levels and mutation load between sexes. Specifically, Ce levels and mutation load were positively correlated in males but negatively correlated in females, while La exposure exhibited opposite associations in the two sexes. This observation was validated using the Bayesian Kernel Machine Regression (BKMR) model. Additionally, plasma REE levels was associated with specific mutation types and variant allele frequencies (VAFs) of particular genes in a sex-dependent manner. Mutational signature analysis revealed sex-specific associations of La with indel signatures. These findings highlight the intricate interplay between plasma REE levels and genetic mutations in LUAD, emphasizing the need for a personalized, sex-oriented approach to understand and treat this disease.

Evaluating the bioavailability of rare earth elements in paddy soils and their uptake in rice grains for human health risk

Rare earth elements (REEs) are a critical global focus due to their increasing use, raising concerns about their environmental distribution and human exposure, both vital to food safety and human health. Surface soil (0-30 cm) and corresponding rice grain samples (n = 85) were collected from paddy fields in Taiwan. This study investigated the total REE contents in soil through aqua regia digestion, as well as their labile forms extracted using 0.05 M ethylenediaminetetraacetic acid (EDTA), 0.10 M hydrogen chloride (HCl), and 0.01 M calcium chloride (CaCl2). The REE concentrations in the rice grains (Oryza sativa L.) were also analyzed. The estimated daily intake (EDI) of REEs through rice consumption for males was 1.3 times higher than that for females. Children under 12 years of age, regardless of gender, had the highest EDI of REEs compared to other age groups. High rice consumption and a high proportion of children are potentially at higher risk for elevated REE exposure. The transport of REEs from soil to rice demonstrated their shift of fractionation by the lower ratio of light REEs and heavy REEs in rice grain compared to soil and their upper continental crust (UCC)-normalized patterns. Empirical equations were developed to estimate the concentrations of REEs in rice grains based on soil pH, clay content, organic carbon, cation exchange capacity, dithionite-citrate-bicarbonate extractable iron, and labile REEs. This study provides critical insights into the health risks of REEs, clarifying their human exposure and the bioavailability from paddy soil to rice.

Comprehensive assessment of pollution status, health risks and source apportionment of heavy metals in surface wetland soils of Yellow River Delta using Monte Carlo simulation and positive matrix factorization

Excessive heavy metals (HMs) exposure in surface soils may cause non-negligible health risks to human beings; however, the potential health risk assessment of HMs in Yellow River Delta wetland (YRDW) soils has rarely been evaluated. In this study, we sampled surface wetland soils from ten typical functional areas in YRDW, assessed the HMs pollution status, evaluated their potential health risks, stimulated their probabilistic distributions of health risks and analyzed their potential source apportionment using Positive matrix factorization and Monte Carlo simulation. Enrichment factor (EF) and geo-accumulation index (Igeo) indicated significant anthropogenic impacts, particularly in oil-contaminated sites, while Sediment Quality Guidelines (SQGs) comparison results suggested potential ecological risks, especially for As and Ni, which were occasionally above threshold effect levels. The potential health risks based on Monte Carlo simulations revealed no non-carcinogenic health risks to all populations, but highlighted potential carcinogenic risks within the acceptable range (1E-06 to 1E-04), especially for children. Positive Matrix Factorization (PMF) identified primary HMs sources as industrial emissions, agricultural activities and local geochemical background. This study underscores the need for continuous monitoring and remediation to mitigate health and ecological risks in the YRDW soils.

Urine is better for rare earth elements bimonitoring in long-term exposed population: An exposure-response relationship study

With the soaring use of rare earth elements (REEs) worldwidely in high-technology and clean energy industries, there were growing concerns for adverse health effect from the REEs exposure. However, there is a lack of biomonitoring research concerning both urine and blood in population with definite exposure. We performed a biomonitoring study that involved 103 REEs exposed males and 110 males as non-REEs exposed controls. We measured the levels of REEs in environment and urine and blood samples from participants, and explored the exposure-response relationship between REEs in environment and body fluids. The effects of exposure duration and smoking status on the internal exposure level of REEs were also investigated. The results showed environmental REEs level of exposure group was significantly higher than that of control group (range of geometric mean of exposure vs. control: 1.08-4.07 × 104 ng/m3 vs. Collapse

Key Words

• Biological monitoring
• Exposure-response relationship
• Rare earth

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MESH Headings

• Humans
• Male
• Metals, Rare Earth/urine
• Metals, Rare Earth/blood
• Biological Monitoring/methods
• Adult
• Environmental Exposure/analysis
• Middle Aged
• Environmental Monitoring/methods
• Environmental Pollutants/urine
• Environmental Pollutants/blood

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Affiliation(s)

Zhizhou He State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China; Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Li Liu Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Ting Wang State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Cailan Zhou State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Xuewei Zhang State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Nan Wu State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Mengmeng Xu State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China
Jianqiong Gao Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Bin Li Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Yonglan Wang Baotou Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
Qiang Zhi Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Chenguang Zhang Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Yaochun Fan Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China
Jiqiang Dai Baotou Center for Disease Control and Prevention, Baotou, Inner Mongolia, China
Sheng Gao Inner Mongolia Autonomous Regin Center for Disease Control and Prevention, Hohhot, Inner Mongolia, China.
Huawei Duan State Key Laboratory of Trauma and Chemical Poisoning, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China; Key Laboratory of Chemical Safety and Health, National Institute for Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing, China.

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Determining the priority control sources of heavy metals in the roadside soils in a typical industrial city of North China

Heavy metals (HMs) in roadside soils (RS) are closely related to urban ecosystem and human health, but priority control sources and eco-health risks of HMs remain unclear. We explored pollution sources of HMs using positive matrix factorization (PMF), scanning electron microscopy with energy dispersive spectroscopy (SEM-EDS), and random forest (RF), and assessed their source-specific eco-health risks. The combination of PMF, SEM-EDS and RF indicated that pollution sources of HMs were coal combustion (27.99 %), construction materials (30.15 %), and traffic emissions (41.86 %). SEM-EDS revealed RS particles were identified by a combination of physical (spherical, porous rounded, crustal flake, crustal rounded and irregular particles) and elemental surface characteristics (O, C, Si, Al, Fe, Ca, Mg, K, Zn, Cu, and Mn). RF highlighted road network density, residential density, and industrial density had significant importance influence on pollution sources. Approximately 72.35 % of soil samples were at a low ecological risk with traffic emissions being the major contributor. Non-carcinogenic risks had a minimal effect, but carcinogenic risks were at a cautionary level with coal combustion being the highest contributor. Overall, coal combustion and traffic emissions were regarded as priority control sources of HMs. These findings provided effective guidance for soil pollution prevention and risk control.

In-use dissipation of technology-critical elements from vehicles and renewable energy technologies in Vienna, Austria: A public health matter?

The rollout of electric vehicles and photovoltaic panels is essential to mitigate climate change. However, they depend on technology-critical elements (TCEs), which can be harmful to human health and whose use is rapidly expanding, while recycling is lacking. While mining has received substantial attention, in-use dissipation in urban areas has so far not been assessed, for example, corrosion and abrasion of vehicle components and weather-related effects affecting thin-film photovoltaic panels. Therefore, the question arises to which extent TCEs dissipate during use and which potential non-occupational human health impacts could occur. We assessed the available information on urban in-use dissipation and human health concerns and conducted exploratory modeling of in-use technology stocks, in- and outflows, and in-use dissipation of neodymium, dysprosium, lanthanum, praseodymium, cerium, gallium, germanium, and tellurium contained in 21 vehicle and renewable energy technologies, for Vienna, Austria. In prospective scenarios, TCE dynamics in a trend-continuation vis à vis official city policy plans and a more ambitious transition scenario were then assessed. We find that electrifying the vehicle fleet without demand-reduction is the main driver of TCE consumption, effectively doubling cumulative end-of-life outflows to 3,073 [2,452-3,966] t and cumulative in-use dissipation to 9.3 [5.2-15.7] t by the year 2060. Sufficiency-based measures could reduce demand and in-use dissipation well below levels with continued trends, thus highlighting the need to combine decarbonization with demand-reducing measures. These results help assess potential future in-use dissipation dynamics and inform discussions about potential public health hazards associated with exposure to TCEs accumulating in the urban environment.

Sources and health risks of heavy metals in kindergarten dust: The role of particle size

Particle size effects significantly impact the concentration and toxicity of heavy metals (HMs) in dust. Nevertheless, the differences in concentrations, sources, and risks of HMs in dust with different particle sizes are unclear. Therefore, guided by the definition of atmospheric particulate matter, dust samples with particle sizes under 1000 μm (DT1000), 100 μm (DT100), and 63 μm (DT63) from Beijing kindergartens were collected. The concentrations of HMs (e.g., Cd, Pb, Zn, Ni, Cr, Ba, Cu, V, Mn, Co, and Ti) in dust samples with different particle sizes were measured. Besides, the differences in HM concentrations, contamination levels, sources, and source-oriented health risks in dust samples of different particle sizes were systematically explored. The results show that the concentrations of Mn, V, Zn, and Cd gradually increase with decreasing dust particle sizes, the concentrations of Ba and Pb show a decreasing trend, and the concentrations of Cr, Cu, Ni, and Co display an increasing and then decreasing trend. The degree of contamination of HMs in dust of different particle sizes varies, with Cd being the most dominant contaminant. Compared with DT1000 and DT63, DT100 is the most polluted. In addition, the sources of HMs in DT1000, DT100, and DT63 become more single with decreasing particle size, which may be mainly due to the particle-size effect inducing the redistribution of HMs in different sources. Notably, the potential health risk is higher in DT100 than in DT1000 and DT63. The highest contribution of industrial sources to the health risk is found in DT100, which is mainly caused by highly toxic chromium (Cr). This work emphasizes the importance of considering particle size in risk assessment and pollution control, which can provide a theoretical basis for precise management of HMs pollution in dust.

Advancing source apportionment of soil potentially toxic elements using a hybrid model: a case study in urban parks, Beijing, China

Identifying the source-specific health risks of potentially toxic elements (PTE) in urban park soils is essential for human health protection. However, previous studies have mostly focused on the deterministic source-specific health risks, ignoring the health risk assessment from a probabilistic perspective. To fill this gap, we developed a hybrid model that incorporated machine learning (ML) interpretability into positive matrix factorization (PMF) and probability health risk assessment (PHRA) based on the Monte Carlo simulation. The results indicated that concentrations of soil PTEs except for Mn and Sb were significantly higher than their corresponding background values. Random forest (RF) was regarded as the best ML model to identify key drivers for As, Cd, Cr, Cu, Ni, Pb, and Zn, with R2 > 0.60, but was less effective for other soil PTEs (R2 < 0.49). Specifically, the contributions of the four potential pollution sources were mixed sources, traffic emission, fuel combustion, and building materials, with contribution rate of 24.88%, 30.56%, 28.99%, and 15.56%, respectively. Fuel combustion contributed the most to non-carcinogenic for children (39.45%), male (43.84%), and female (43.76%), and the non-carcinogenic risk could be considered negligible for human. However, building materials was the major contributor to carcinogenic risk for children (36.1%), male (44.9%), and female (43.2%). The integration of the RF model with PMF and PHRA improved the accuracy of the results by identifying and quantifying the specific sources of each soil PTE using the relative importance analysis from the RF model. The results of this study assisted in providing efficient strategies for risk management and control of soil PTEs in Beijing parks.

Hazard profiles, distribution trends, and sources tracing of rare earth elements in dust of kindergartens in Beijing

Children, the most vulnerable group in urban populations, are susceptible to the effects of pollution in urban environments. It is significant to evaluate the influence of rare earth elements (REEs) from kindergartens dust (KD) in Beijing on children's health. This study collected surface dust from 73 kindergartens in 16 districts of the mega-city of Beijing, and the concentrations of 14 REEs in KD, including La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu, were detected. The contamination levels, source apportionment, and health exposure risk of REEs were comprehensively investigated. The results indicate that the contamination levels of 14 REEs are within the acceptable range. Nevertheless, Eu, Ce, La, Pr, Nd, Gd, and Sm show high enrichment due to anthropogenic influence. Besides, KD is rich in light rare earth elements (LREEs) (90.97 mg kg-1) compared to heavy rare earth elements (HREEs) (8.65 mg kg-1). The distribution parameter patterns of REEs suggest that complicated anthropogenic sources influence the enrichment of REEs in KD. The main sources of REEs in KD include natural sources (40.64%), mixed high-tech industries and construction (33.89%), and mixed coal-fired, historical industrial, and transportation sources (26.47%). The primary pathway for daily intake of REEs in children is through ingestion, which presents a low but not negligible health risk. This study provides guidance for the effective risk management of REEs in KD.

Fate and potential ecological risk of rare earth elements in 3000-year reclaimed soil chronosequences

The introduction of anthropogenic inputs into natural systems may lead to enduring alterations in the innate characteristics of Rare Earth Elements (REEs). Against this backdrop, the evolutionary processes and environmental drivers of REEs in soil remain uncertain. A 3000-year soil chronosequence with uniform parent material was established in reclaimed farmland along the Yangtze River, reconstructing, for the first time, the dynamic processes of REE accumulation and fractionation over a long-time scale. Analysis of 122 soil samples showed REE concentrations ranging from 146.00 to 216.56 μg/g. Based on reclamation duration, three significant stages of REE evolution were identified: natural leaching, rapid accumulation, and stable accumulation with differentiation. Reclaimed soil after 3000 years exhibited a 14.1 % increase in REE concentrations compared to fresh sediments, attributed to anthro -pedogenic processes. Moreover, Heavy Rare Earth Elements (HREEs) accumulated faster than Light Rare Earth Elements (LREEs), particularly in deeper soils (60-100 cm), where HREE concentrations rose by 34.3 %, mainly due to acidic environments promoting HREE fixation. Additionally, the potential ecological risk posed by REEs heightened with reclamation duration, with HREEs exhibiting a sensitivity of 83 % to 94 %. Our findings stress the urgency of carefully monitoring exogenous REEs introduced through anthropogenic activities, particularly HREEs.

Assessment of rare earth elements variations in five water systems in Beijing: Distribution, geochemical features, and fractionation patterns

This study investigates the distribution of rare earth elements (REEs) within the Beijing water system, specifically examining the Yongding, Chaobai, Beiyun, Jiyun, and Daqing rivers. Results indicate that the Beiyun River exhibits the highest REE concentrations, ranging from 35.95 to 59.78 μg/mL, while the Daqing River shows the lowest concentrations, ranging from 15.79 to 17.48 μg/mL. LREEs (La to Nd) predominate with a total concentration of 23.501 μg/mL, leading to a notable LREE/HREE ratio of 7.901. Positive Ce anomalies (0.70-1.11) and strong positive Eu anomalies (1.38-2.49) were observed. The study suggests that the Beijing water system's REEs may originate from geological and anthropogenic sources, such as mining and industrial activities in neighboring regions, including Inner Mongolia. These findings underscore the importance of ongoing monitoring and effective water management strategies to address REE-related environmental concerns.

Rare earth elements reveal the human health and environmental concerns in the largest tributary of the Mekong river, Northeastern Thailand

The widespread application of rare earth elements (REEs) in contemporary industries and agriculture, has caused emerging contaminant accumulation in aquatic environments. However, there is a limited scope of risk assessments, particularly in relation to human health associated with REEs. This study investigated the provenance, and contamination levels of REEs, further evaluating their environmental and human health risks in river sediments from an agricultural basin. The concentrations of REEs ranged from 30.5 to 347.7 mg/kg, with showing an upward trend from headwater to downstream. The positive matrix factorization (PMF) model identified natural and anthropogenic input, especially from agricultural activities, as the primary source of REEs in Mun River sediments. The contamination assessment by the geoaccumulation index (I-geo) and pollution load index (PLI) confirmed that almost individual REEs in the samples were slightly to moderately polluted. The potential ecological risk index (PERI) showed mild to moderate risks in Mun River sediment. Regular fertilization poses pollution and ecological risks to agricultural areas, manifesting as an enrichment of light REEs in river sediments. Nevertheless, Monte Carlo simulations estimated the average daily doses of total REEs from sediments to be 0.24 μg/kg/day for adults and 0.95 μg/kg/day for children, comfortably below established human health thresholds. However, the risk of REE exposure appears to be higher in children, and sensitivity analyses suggested that REE concentration contributed more to health risks, whether the adults or children. Thus, concerns regarding REE contamination and risks should be raised considering the wide distribution of agricultural regions, and further attention is warranted to assess the health risks associated with other routes of REE exposure.

Urban environmental monitoring and health risk assessment introducing a fuzzy intelligent computing model

Introduction

To enhance the precision of evaluating the impact of urban environments on resident health, this study introduces a novel fuzzy intelligent computing model designed to address health risk concerns using multi-media environmental monitoring data.

Methods

Three cities were selected for the study: Beijing (B City), Kunming (K City), and Wuxi (W City), representing high, low, and moderate pollution levels, respectively. The study employs a Fuzzy Inference System (FIS) as the chosen fuzzy intelligent computing model, synthesizing multi-media environmental monitoring data for the purpose of urban health risk assessment.

Results

(1) The model reliably estimates health risks across diverse cities and environmental conditions. (2) There is a positive correlation between PM2.5 concentrations and health risks, though the impact of noise levels varies by city. In cities B, K, and W, the respective correlation coefficients are 0.65, 0.55, and 0.7. (3) The Root Mean Square Error (RMSE) values for cities B, K, and W, are 0.0132, 0.0125, and 0.0118, respectively, indicating that the model has high accuracy. The R2 values for the three cities are 0.8963, 0.9127, and 0.9254, respectively, demonstrating the model's high explanatory power. The residual values for the three cities are 0.0087, 0.0075, and 0.0069, respectively, indicating small residuals and demonstrating robustness and adaptability. (4) The model's p-values for the Indoor Air Quality Index (IAQI), Thermal Comfort Index (TCI), and Noise Pollution Index (NPI) all satisfy p < 0.05 for the three cities, affirming the model's credibility in estimating health risks under varied urban environments.

Discussion

These results showcase the model's ability to adapt to diverse geographical conditions and aid in the accurate assessment of existing risks in urban settings. This study significantly advances environmental health risk assessment by integrating multidimensional data, enhancing the formulation of comprehensive environmental protection and health management strategies, and providing scientific support for sustainable urban planning.

Artisanal mining of monazite and cassiterite in the Amazon: Potential risks of rare earth elements for the environment and human health

Artisanal mining is intensely carried out in developing countries, including Brazil and especially in the Amazon. This method of mineral exploration generally does not employ mitigation techniques for potential damages and can lead to various environmental problems and risks to human health. The objectives of this study were to quantify the concentrations of rare earth elements (REEs) and estimate the environmental and human health risks in cassiterite and monazite artisanal mining areas in the southeastern Amazon, as well as to understand the dynamics of this risk over time after exploitation. A total of 35 samples of wastes classified as overburden and tailings in active areas, as well as in areas deactivated for one and ten years were collected. Samples were also collected in a forest area considered as a reference site. The concentrations of REEs were quantified using alkaline fusion and ICP-MS. The results were used to calculate pollution indices and environmental and human health risks. REEs showed higher concentrations in anthropized areas. Pollution and environmental risk levels were higher in areas deactivated for one year, with considerable contamination factors for Gd and Sm and significant to extreme enrichment factors for Sc. Human health risks were low (< 1) in all studied areas. The results indicate that artisanal mining of cassiterite and monazite has the potential to promote contamination and enrichment by REEs.

Remarkable contamination characteristics, potential hazards and source apportionment of heavy metals in surface dust of kindergartens in a northern megacity of China

It is essential to understand the impact of heavy metals (HMs) present in the surface dust (SD) of kindergartens on children, who are highly sensitive to contaminated dust in cities in their growth stage. A study was conducted on 11 types of HMs present in the SD of 73 kindergartens in Beijing. This study aims to assess the pollution levels and sources of eleven HMs in Beijing's kindergartens surface dust (KSD), and estimate the potential health risks in different populations and sources. The results indicate that Cd has the highest contamination in the KSD, followed by Pb, Zn, Ni, Ba, Cr, and Cu. The sources of these pollutants are identified as industrial sources (23.7%), natural sources (22.1%), traffic sources (30.4%), and construction sources (23.9%). Cancer risk is higher in children (4.02E-06) than in adults (8.93E-06). Notably, Cr is the priority pollutant in the KSD, and industrial and construction activities are the main sources of pollution that need to be controlled. The pollution in the central and surrounding areas is primarily caused by historical legacy industrial sites, transportation, urban development, and climate conditions. This work provides guidance to manage the pollution caused by HMs in the KSD of Beijing. ENVIRONMENTAL IMPLICATION: Children within urban populations are particularly sensitive to pollutants present in SD. Prolonged exposure to contaminated SD significantly heightens the likelihood of childhood illnesses. The pollution status and potential health risks of HMs within SD from urban kindergartens are comprehensively investigated. Additionally, the contributions from four primary sources are identified and quantified. Furthermore, a pollution-source-oriented assessment is adopted to clearly distinguish the diverse impacts of different sources on health risks, and the priority pollutants and sources are determined. This work holds pivotal importance for risk management, decision-making, and environmental control concerning HMs in KSD.

Rare earth elements interaction with iron-organic matter colloids as a control of the REE environmental dissemination

Rare earth elements (REE) are highly sought after for advanced technology, in response concerns about their environmental impact have arisen. The mobility and transport of REEs are influenced by their binding to solid surfaces, particularly colloids. With the widespread occurrence of REEs and their potential increase due to climate change, there is growing interest in understanding colloids composed of organic matter (OM) and iron (Fe). The reactivity of these colloids depends on their structural organization and the availability of Fe phase and OM binding sites. The effect of pH on the binding and mobility of REEs in these colloids in response to structural modification of Fe-OM colloids was investigated. REEs are primarily bind to the OM component of Fe-OM colloids, and their mobility is controlled by the response of OM colloids and molecules to pH conditions. At pH 6, the solubilization of small organic colloids (<3 kDa) control the REE pattern and subsequent speciation and mobility. In contrast, at pH 4, Fe-OM colloids bind less amount of REE but aggregate to form a large network. While most REEs remain soluble, those bound to Fe-OM colloids are expected to be immobilized through settlement or trapping in soil and sediment pores. This study supports the idea that colloids control the REE speciation and subsequent dissemination. The findings are particularly relevant for assessing the fate and ecotoxicology of REE in response to changing environmental conditions and increasing REE concentration in natural systems.

Ecological and Health Risks Attributed to Rare Earth Elements in Coal Fly Ash

The occurrence and distribution of yttrium and rare earth elements (REYs), along with major elements and heavy metal(loid)s (HMs) in coal fly ash (CFA) from five coal-fired power plants (CFPPs), were analyzed, and the REY-associated ecological and health risks were assessed. The individual REYs in CFA were abundant in the following order: Ce > La > Nd > Y > Pr > Gd > Sm > Dy > Er > Yb > Eu > Ho > Tb > Tm > Lu. The total REY content ranged from 135 to 362 mg/kg, averaging 302 mg/kg. The mean light-to-heavy REY ratio was 4.1, indicating prevalent light REY enrichment in CFA. Significantly positive correlations between the REYs suggested that they coexist and share similar origins in CFA. REYs were estimated to pose low to moderate ecological risks, with risk index (RI) values ranging from 66 to 245. The hazard index (HI) and target cancer risk (TCR) of REYs from CFA, estimated to be higher for children (HIc = 0.15, TCRc = 8.4 × 10-16) than for adults (HIa = 0.017, TCRa = 3.6 × 10-16), were well below the safety limits (HI = 1, TCR = 1.0 × 10-6). However, the danger to human health posed by HMs in the same CFA samples (HIc = 5.74, TCRc = 2.6 × 10-4, TCRa = 1.1 × 10-4) exceeded the safe thresholds (excl. HIa = 0.63). The mean RI and HI attributed to REYs in CFA were 14% and 2.6%, respectively, of the total risks that include HMs.

Spatial Variability of Rare Earth Elements in Groundwater in the Vicinity of a Coal-Fired Power Plant and Associated Health Risk

This study investigated the occurrence and distribution of rare earth elements (REEs), including 14 lanthanoids, scandium (Sc), and yttrium (Y), in groundwater around a large coal-fired thermal power plant (TPP). The ICP-MS technique was used to analyze 16 REEs in groundwater samples collected from monitoring wells. REE concentrations ranged from 59.9 to 758 ng/L, with an average of 290 ng/L. The most abundant was Sc, followed by La, accounting for 54.2% and 21.4% of the total REE concentration, respectively. Geospatial analysis revealed the REE enrichment at several hotspots near the TPP. The highest REE concentrations were observed near the TPP and ash landfill, decreasing with the distance from the plant and the landfill. REE fractionation ratios and anomalies suggested the Light REE dominance, comprising over 78% of the total REEs. Correlation and principal component analyses indicated similar behavior and sources for most REEs. Health risk assessment found hazard indices (HI) of 1.36 × 10-3 and 1.98 × 10-3 for adults and children, respectively, which are far below the permissible limit (HI = 1). Likewise, incremental lifetime cancer risks (ILCR) were all below 1 × 10-6. Nevertheless, ongoing ash disposal and potential accumulation in the environment could elevate the REE exposure over time.

Accumulation, translocation, and fractionation of rare earth elements (REEs) in fern species of hyperaccumulators and non-hyperaccumulators growing in urban areas

The issue of ion-adsorption type rare earth deposits (IADs) in urban areas of South China has garnered significant attention due to its environmental implications. Hyperaccumulator-based phytoremediation is a potentially effective solution for reducing the environmental impact of IADs in urban areas, particularly using ferns as they are known to be REE hyperaccumulators. However, the ability of different fern species to accumulate REEs in urban areas remains unknown. In this study, four fern species, including known hyperaccumulators (Dicranopteris linearis and Blechnum orientale) and other ferns (Pteris ensiformis and Cibotium barometz), were studied to investigate their REE accumulation abilities in the Guangzhou urban area. The aboveground parts of Dicranopteris linearis (848.7 μg g-1) and Blechum orientale (1046.8 μg g-1) have been found to accumulate high concentrations of REEs, demonstrating they probably can be applied for phytoremediation in the natural environments. Despite having lower REE concentrations than REE hyperaccumulators, Pteris ensiformis and Cibotium barometz still probably have the function as phytostabilizers in urban areas, as REEs can be enriched in their roots beyond the normal levels of plants. The enrichment of REEs in ferns is influenced by the availability of various nutrients (K, Ca, Fe, and P), which probably can be associated with different growth processes. The four fern species show LREE enrichment, moderate Eu anomalies and different Ce anomalies. It is difficult to absorb and transfer Ce to the aboveground parts of Blechnum orientale and Cibotium barometz. The study also identified selective enrichment of Ce in Pteris ensiformis, which has potential for comprehensive extraction of REEs when combined with other REE hyperaccumulators. REE fractionations are probably determined by the specific characteristics of different fern parts. Overall, these findings provide insights for addressing potential environmental problems related to IADs and offer guidelines for phytoremediation technology in addressing high REE levels in urban areas.

Spatial Distribution and Risk Assessment of Heavy Metal(oid)s Contamination in Topsoil around a Lead and Zinc Smelter in Henan Province, Central China

A total of 137 farmland soil samples were collected around a lead/zinc smelter within 64 km². The concentration, spatial distribution, and potential source of nine heavy metal(oid)s (As, Cd, Co, Cr, Cu, Ni, Pb, V, and Zn) in soils and their potential ecological risk were investigated in detail. The results showed that the average concentrations of Cd, Pb, Cr and Zn in these soils were higher than their background value in Henan Province, and the average content of Cd was 2.83 times of the risk screening values in the national standard of China (GB 15618-2018). According to the distribution of different heavy metal(oid)s in soils, Cd and Pb in soil decrease gradually with the increase of distance from the smelter to the surrounding area. This indicates that the Pb and Cd originate from smelters via airborne practices according to the typical air pollution diffusion model. The distribution of Zn, Cu, and As were similar to Cd and Pb. However, Ni, V, Cr, and Co were mainly affected by soil parent materials. The potential ecological risk of Cd was higher than those of other elements, and the risk grade of the other eight elements was mainly low. The polluted soils with significantly high and high potential ecological risk covered 93.84% of all the studied regions. This should be of serious concern to government. The results of a principal component analysis (PCA) and cluster analysis (CA) show that Pb, Cd, Zn, Cu, and As were the elements mainly stemmed from smelter and other types of plants, with a contribution rate of 60.08%, while Co, Cr, Ni, and V are mainly caused by nature, with a contribution rate of 26.26%.