Urban soil contamination by potentially toxic elements (PTEs) is a recognized health concern in densely populated urban environments. Through a systematic meta-analysis of 91 peer-reviewed studies (2000–2025) reporting 12,174 sampling sites in capital and core cities, we characterized regional patterns in the spatiotemporal dynamics and health risks of eight PTEs across two well-represented continental subsets (Asia, k = 18–36 per element; Europe, k = 11–23 per element) with comparative reference to the Americas, Africa, and Oceania. Given the uneven geographic distribution of qualifying primary studies, continental comparisons should be interpreted as hypothesis-generating: Asia (k = 18–36 per element) and Europe (k = 11–23 per element) provide the statistically robust core of the synthesis, while results for the Americas (k = 3–7 for several elements), Africa (k = 4–15), and Oceania (k = 2) are presented as illustrative rather than statistically representative. Pooled concentrations followed Zn (138.59) > Pb (56.97) > Cr (54.26) > Cu (47.00) > Ni (31.94) > As (8.56) > Hg (3.13) > Cd (1.23) mg·kg−1. Within the well-represented Asian and European subsets, Asian cities showed the most severe enrichment of As, Cd, Cr, and Hg (Igeo > 4 in hotspots such as Kathmandu Igeo (Cd) = 7.06 and Jinan Igeo (Hg) = 5.27), whereas European centres exhibited substantial legacy Pb accumulation (pooled mean 87.69 mg·kg−1). A reproducible pollution gradient was identified across functional zones: industrial > transportation ≥ residential > commercial > agricultural > urban green areas. The deterministic non-carcinogenic Hazard Index (HI = 1.49) for children in Asia exceeded the safe threshold (HI > 1), driven primarily by As and Cr exposure via incidental soil-and-dust ingestion. Monte Carlo probabilistic assessment (N = 10,000) confirmed elevated cumulative non-carcinogenic risk at the median of the exposure distribution for children in the data-rich Asian (P50 = 1.55; P(HI > 1) = 81.9%) and European (P50 = 1.28; P(HI > 1) = 69.8%) subsets, with adults in both subsets remaining well below the safety threshold (P(HI > 1) = 0.0%). Temporal analysis revealed a decoupling between economic growth and PTE accumulation in long-established cities, together with an inverse Ni–population correlation indicative of strategic resource allocation. For Asian capital and core cities, where the evidence base is strongest (k = 18–36 per element), the present synthesis supports further investigation of risk-based, child-centric soil management as a public-health priority. For European cities (k = 11–23 per element), the same direction of risk is indicated but should be confirmed in regionally focused syntheses. Policy considerations for under-represented regions should await expansion of the primary monitoring base.

Lithium (Li) geochemical background concentrations exhibit pronounced lithological dependence, challenging reliable resource prospecting in heterogeneous terrains. Accurate, spatially resolved background estimation is essential for robust anomaly detection. This study applies partial least squares regression (PLSR) to a 1:200,000-scale stream sediment dataset from northeastern Hunan, China, developing a site-specific Li background model. Nine lithologically sensitive elements (Al2O3, Fe2O3, MgO, CaO, K2O, Sr, Ti, V, Y) were selected as predictors based on geochemical coherence with Li and rock-type responsiveness. Leave-one-out cross-validation (LOOCV) was used for component selection and sample-wise cross-validation, and spatial block cross-validation was further conducted to assess model applicability. The resulting regression equation in clr-transformed space is: Li(background)=3.83750-0.17707×Sr-0.35090×Ti-0.17547×V-0.32998×Y+0.49467×Al2O3-0.08215×CaO-0.30069×Fe2O3+0.10333×K2O+0.25553×MgO. Using this model, Li background values were computed for all samples in clr-transformed space. Li anomalies were identified by comparing observed clr-transformed Li values with the upper prediction limit of the PLSR-derived background estimate, yielding 115 anomalous samples and enabling spatial delineation of geochemical anomalies. Performance was evaluated against two benchmarks: a deep autoencoder and the conventional [mean + 2 standard deviations] criterion. Results demonstrate that PLSR effectively decouples anomalous signals from lithological background trends. These sample-level estimates substantially reduce false anomalies in high-background zones and enhance sensitivity to weak mineralization in low-background settings. Notably, in areas with significant background variation, the PLSR method produces Li anomalies that are more geologically consistent than those identified by the DAE and the [mean + 2 standard deviations] method. This work establishes a reproducible, interpretable, and geologically grounded framework for Li exploration in lithologically complex regions, applicable to other pathfinder elements under strong lithological control.

Background: Rare earth elements (REEs) are present in agricultural ecosystems, but their baseline soil–plant transfer dynamics require systematic understanding. This study investigated the ‘source-to-sink’ biogeochemical distribution of REEs in soybean under background soil conditions. Methods: We characterized REE concentrations and fractionation patterns in the composite surface soil samples and analyzed two soybean cultivars (‘Jiyu 201’ (JY) and ‘Ping’an 16’ (PA)). A seven-stage sampling scheme (20–80 days post-sowing) using whole-plant samples was employed to evaluate temporal concentration dynamics, followed by discrete organ-level analysis at maturity. Results: The composite surface soil samples exhibited a light REE (LREE)-enriched signature with negative cerium (Ce) and europium (Eu) anomalies. While plants consistently mirrored the soil’s negative Eu anomaly, an observable shift toward a positive Ce anomaly was detected in plant tissues during the 45–65 days post-sowing window. REE concentrations were markedly higher in roots than in aerial tissues, indicating strong root-associated retention and limited acropetal translocation; however, the root values include both internalized and surface-associated fractions. Acropetal transport was accompanied by preferential LREE enrichment. Final organ-level partitioning was highly genotype-dependent: the indeterminate cultivar PA accumulated higher REEs in beans, whereas the sub-determinate cultivar JY retained them primarily in vegetative stems. Conclusions: Under background soil conditions, REE uptake and partitioning in soybean exhibit dynamic and genotype-dependent patterns. The observed shift in the Ce anomaly presents a notable biogeochemical phenomenon. Establishing these baseline dynamics is vital for evaluating crop elemental homeostasis and utilizing REEs as biogeochemical tracers.

The problem of elemental background variation greatly influences anomaly recognition and has not been effectively addressed. Taking the 1 : 200 000 scale geochemical data of stream sediments from Leiyang, SE China, as an example, we established a Random Forests model to determine Sn anomalies, focusing on the application effect of this method. Al2O3, CaO, K2O, MgO, Na2O, SiO2, Ba, Be, Li, and Y were selected as model indicators, and 40 background and 40 anomalous samples were chosen to train the Random Forests model, which was then used to estimate the probability (0 to 1) of Sn mineralization. According to the identification rate of known Sn deposits in the study area, the high, medium, and low Sn mineralization probability thresholds were determined to be 1, 0.98, and 0.96, respectively, and thus, strong, medium, and weak Sn anomalies were delineated. Compared to the Sn anomalies identified using the [mean ± k standard deviation] method and the partitioning method, those determined by Random Forests exhibit greater accuracy. Random Forests eliminated some spurious anomalies that are easily misidentified in high-background areas and better recognized some subtle anomalies that are challenging to detect in low-background areas, suggesting that it can largely remove the background influence on the identification of geochemical anomalies.

In recent years, the attention paid to the viscoacoustic wave equation with decoupled fractional Laplacian (DFL) operators has increased remarkably. This is due to the equation's unique decoupling property and its ability to accurately characterize the quality factor. The DFL viscoacoustic equation is typically computed numerically employing the finite difference (FD) and Fourier pseudo-spectral (PS) methods with respect to the derivatives of time and space, respectively. Although the FD-PS method provides spectral accuracy in the spatial domain, its time accuracy is limited to second order. In scenarios with a larger time sampling interval, the FD-PS method might encounter significant time dispersion. Although reducing the time sampling interval can alleviate this dispersion, it significantly boosts computational cost. To correct the time error introduced by time dispersion, we propose a hybrid rapid expansion method (HREM) to rectify the time error in DFL viscoacoustic equation. This method mitigates the time error by compensating for the dispersion-dominated term that exerts a considerable influence on the time error. HREM has been validated to effectively correct the time error through theoretical analysis and numerical experiments. Compared to the traditional FD-PS method, the stability condition of HREM is looser, thereby conferring enhanced flexibility in the selection of sampling parameters. Furthermore, HREM allows for the accurate estimation of the wavefield with larger time steps. The application of a three-dimensional overthrust model illustrates its effectiveness for large-scale seismic modelling.

Most currently available methods for identifying geochemical anomalies using machine/deep learning algorithms ignore the issue of elemental background variation. This study exemplifies the identification of Pb anomalies in regional stream sediments from Shaoshan, central China, by utilizing a deep autoencoder (DAE). The focus is on applying this algorithm to detect geochemical anomalies in areas with varying geochemical background of elements. Firstly, we grouped the stream sediment samples into seven clusters using the Expectation-Maximization (EM) clustering algorithm, effectively minimizing the influence of elemental background variation. Subsequently, elements associated with Pb mineralization in groups one to seven were determined through robust principal component analysis (RPCA): Bi-Li-Sn-Pb, Li-Pb-MgO, As-Nb-Pb, Nb-Pb-Zn-Al2O3, Li-Pb-Al2O3-Fe2O3, Ag-Pb-CaO, and Ag-Bi-Li-Pb-Sb-SiO2. The elemental data for each group were then input into the DAE respectively to calculate the reconstruction error, with a threshold value of 0.24 established to delineate Pb anomalies. The identified anomalies corresponded to the known Pb deposits with an accuracy of 89%. In comparison to the DAE method, the combined approach offers a more effective means of identifying geochemical anomalies. This is primarily evident in its ability to eliminate false anomalies in areas with high background while also detecting weak anomalies in regions with low background. The integration of the EM clustering algorithm with machine/deep learning techniques for anomaly detection can significantly enhance the accuracy of geochemical anomaly identification.

The black soil in northeast China plays an important role in coping with global climate change. However, long-term predatory production methods and the excessive application of pesticides and fertilizers to respond to the growing demand resulted in a severe contamination of the black soil with Cd, leading to a decrease in the properties of black soil. In this study, we propose the preparation of bio-adsorbents including a natural bio-adsorbent (AW), a modified bio-adsorbent (AM), biochar cracking at 300, 500, and 700 °C (C300, C500, C700), modified biochar (CM), and a magnetic bio-adsorbent particle (MBP) using the waste of black soil autotrophic specialty crop multiplier onion (Allium cepa var. aggregatum) to investigate the adsorption and immobilization of Cd in contaminated soil. The results show that the application of bio-adsorbents resulted in a 17.29–35.67% and 18.24–30.76% decrease in effective and total Cd content in soil after dry–wet–freeze circulation. Exchangeable Cd in soil decreased and gradually transformed to more stable fractions, with a reduction in Cd bioavailability after remediation. Interestingly, an increase in plant uptake of Cd was observed in the biochar-treated group for a short period, causing a 93.72% increase in Cd concentration in plants after the application of C700, which can be applied concomitantly with hyperaccumulator plants harvested multiple times annually by encouraging higher Cd uptake by plants. Additionally, the rich content of humic acid (HA) in black soil was capable of promoting the immobilization of Cd in soil, enhancing the Cd resistance of black soil. Bio-adsorbents derived from Allium cepa var. aggregatum waste can be applied as a new type of green and effective material for the long-term remediation of Cd in the soil at a lower cost.

In order to identify the nutrient level and environmental quality of paddy fields in Wanchang area, and to provide scientific basis and technical support for planting rice in Wanchang area, the soil geochemical survey was carried out, 30 samples were collected from paddy soil in Wanchang area, and 20 elements (indicators) were analyzed. The characterization of the elemental content of soils in the study area was carried out, and the geochemical level for soil nutrients, the geochemical level for the soil environment, and the comprehensive geochemical level of soil quality were evaluated. The results showed that the average values of K content and pH of the soil in the study area were smaller than the background values of Jilin Province, and the average values of 18 elements including N, P, Ca, S, Pb, Zn etc. were bigger than the background values of Jilin Province. The results of the evaluation of soil single element nutrient in the study area showed that the available state nutrient levels of Mn, Zn, Cu, and K increased compared with the total amounts of nutrients level, with Cu increasing the most; the available state nutrient level of N, P, B, and Mo decreased compared with the total amounts of nutrients level, with Mo decreasing the most. The comprehensive level of soil nutrients geochemistry in paddy fields was mainly Level Ⅲ (medium), accounting for 53.33%, and the low abundance level was caused by the lack of P element; the comprehensive level of soil environmental geochemistry was mainly Level Ⅰ (clean), accounting for 96.67%, with only slight pollution caused by Cd. The comprehensive geochemical level of soil quality was mainly Level Ⅱ, accounting for 66.67%. Suggestions were put forward for the rational utilization of soil resources in paddy fields in the study area.

In order to validate the applicability of pXRF for rapid in situ detection of heavy metals in urban soils and to accurately obtain an assessment of soil quality in Changchun, a city in northeast China, 164 soil samples from within the main urban area of Changchun were collected for pXRF analysis. The main stable elements Si and Ti were used to establish a matrix effect correction model, and the values of Cr (64.2 mg⋅kg−1), Cu (43.8 mg⋅kg−1), Zn (96.2 mg⋅kg−1), As (20.9 mg⋅kg−1), and Pb (57.4 mg⋅kg−1) were predicted. The empirical findings indicate that the quality of soil data from the pXRF was improved to different degrees under the correction model, and it became a relatively reliable dataset; the order of improvement was Cu > Pb > Cr > Zn > As. A comprehensive assessment indicated that Changchun City is primarily contaminated by the heavy metals As, Pb, and Cu, with the main sources being automobile manufacturing and pharmaceutical chemical production. These findings align with previous studies and have produced favorable outcomes in practical applications. This rapid, non-destructive and economical detection method is very applicable and economical for the sustainable monitoring and control of heavy metals in large cities. This study provides a basis for rapid large-scale prediction of urban soil safety and protection of local human health.

Combined electrokinetic remediation employing reducing agents represents an extensively utilized approach for the remediation of hexavalent chromium (Cr(VI))-contaminated soil. In this investigation, electrokinetic remediation of artificially contaminated kaolin was conducted utilizing a separate circulation system for the anolyte, with a 0.5M solution of acetic acid (HAc) as the electrolyte and foamed iron serving as the anode. The experimental outcomes demonstrated that employing HAc as the electrolyte enhances the electromigration of Cr(VI) and establishes an acidic milieu conducive to the reduction of Cr(VI) by foamed iron, thereby facilitating the rapid reduction of Cr(VI) accumulated in the anolyte through electrokinetic remediation. In the self-prepared contaminated kaolin, the initial concentration of Cr(VI) was 820.26 mg/L. Following the remediation process under optimal experimental conditions, the concentration was significantly reduced to 11.6 mg/L, achieving a removal efficiency of Cr(VI) in the soil of 98.59

As an important capital city of intensive urbanization and industrialization in Northeast China, Changchun has experienced extremely rapid development, with diverse sectors such as automobile manufacturing, equipment manufacturing, optoelectronics, and pharmaceutical decoration. However, data on the levels and profiles of perfluoroalkyl substances (PFASs) in urban soils of Changchun is limited. This study investigated 17 PFASs across various functional zones within the main urban area of Changchun. Sigma PFAS concentrations in the soils ranged from 0.236 to 6.483 ng/g, averaging 1.820 ng/g. Perfluorocarboxylic acids (PFCAs) were more prevalent than perfluorosulfonic acids (PFSAs), and short-chain PFASs (C <= 6) were the predominant residues. PFAS concentrations varied across functional zones, with commercial markets exhibiting the highest levels, followed by industrial areas, residential areas, suburban zones, and transportation areas. Molecular diagnostic ratio and PCA-MLR analysis identified industrial production processes of consumer goods and wastewater treatment plants as the primary sources of soil PFAS contamination. There were no obvious health risks of soil & sum;PFASs, while soil PFOS and PFHxS may have an impact on the richness and diversity of soil microbial communities in some certain locations. This study provides new data on PFAS residues in soils influenced by diverse contamination sources within a key industrial city in Northeast China, offering valuable insights for prioritizing remediation and restoration efforts.

The inversion of the relative content and spatial distribution characteristics of radioactive elements on the lunar surface, as inferred from gamma-ray spectrometer data, holds substantial importance for forecasting lunar surface compositions. During the inversion process of gamma-ray spectrometer data, galactic cosmic rays (GCRs) have engendered disruptive “stripe noise” in the distribution map of radioactive elements. This phenomenon significantly hampers the interpretation of data and the extraction of lunar surface information. The proposed approach adeptly separates the influence of GCR from the counting rate distribution map of the lunar surface by employing the empirical mode decomposition method. It achieves the deduction of GCR background from the Chang’e-2 gamma-ray spectrometer data with precision. Compared to conventional GCR background deduction methods employed by predecessors, this model does not need to process a large amount of original data repeatedly. Moreover, it achieves an accurate deduction of the GCR background without intricate formulaic derivations. The procedural simplicity and reduced time investment make this approach significantly superior.

The "background" is an essential index for identifying anthropogenic inputs and potential ecological risks of soil heavy metals. However, the lithology of bedrock can cause significant spatial variation in the natural background of soil elements, posing considerable difficulties in estimating background values. In this study, an attempt was made to calculate the natural background through regression analysis of soil chemical composition, and reasonably evaluate the impact of lithology. A total of 1771 surface soil samples were collected from the Songhua River Basin, China, for chemical composition analysis, and the partial least square regression (PLSR) method was employed to establish the relationship between heavy metals (As, Hg, Cr, Cd, Pb, Cu, Zn, and Ni) and soil chemical composition/environmental parameters (SiO2, Al2O3, TFe2O3, MgO, CaO, K2O, Na2O, La, Y, Zr, V, Sc, Sr, Li and pH). The result shows that As, Cr, Pb, Cu, Zn, and Ni have significant linear relationships with soil chemical composition. Each of these six heavy metals obtained 1771 regression background values; some were higher than the uniform background value obtained from the boxplot, while others were lower. The regression background values recognized not only subtle anthropogenic inputs and potential ecological risks in low-background regions but also spurious contamination in high-background areas. All these indicate that the PLSR method can effectively improve the determination accuracy of the natural background of soil heavy metals. More attention should be paid to the serious anthropogenic inputs appearing in some places of the study area.

Identifying saline soils is of great importance for protecting land resources and for the sustainable development of agriculture. Total soil salinity (TSS) is the most commonly used indicator for determining soil salinization, but the application of soil geochemical data is rarely reported. In general, there is a significant relationship between TSS and the content of soil-soluble Na, which can be estimated by the difference between the bulk-soil Na2O content and its background value. In this study, the partial least squares regression (PLSR) method was employed to calculate the Na2O background value via a regression model between Na2O and SiO2, Al2O3, TFe2O3, Cr, Nb, and P in a 1:250,000 scale regional geochemical data set of soils in Jilin Province, NE China. We defined δNa as the difference between the bulk-soil Na2O value and the regression background value, which can be used as a geochemical indicator to identify saline soils. One hundred and five samples with known TSS contents in the study area were selected to test the capability of the indicator δNa. The result shows that the identification accuracy can be up to 75%, indicating that the indicator can provide a new means for saline soil identification.

胶东地区一直是金矿研究的热点,但大部分研究集中在胶西北和牟乳成矿区,而蓬莱—栖霞成矿区研究较少.笏山金矿床位于蓬莱—栖霞成矿带的南部,受北东向台前—陡崖断裂控制.笏山金矿床主要载金矿物为黄铁矿,根据黄铁矿结构、形态特征,成矿阶段可分为早成矿阶段和晚成矿阶段.通过采用LA-ICP-MS对笏山金矿床不同成矿阶段的黄铁矿进行原位微区成分分析,结果显示:黄铁矿中w(Co)最大值为502.57×10-6,平均值为137.56×10-6,指示其属于中低温型黄铁矿.早成矿阶段w(Co)/w(Ni)值要大于晚成矿阶段,说明成矿过程中温度逐渐降低.笏山金矿床中金元素主要以可见金的形式存在,显微镜下可观察到大量可见金颗粒.元素含量关系图显示:Au含量均在Au最大溶解度曲线以下,说明黄铁矿中不可见金主要以晶格金的形式存在.Au与As呈正向相关,暗示Au富集受As影响.早成矿阶段As对黄铁矿晶胞中S的替代,为Au富集提供了便利条件.到了晚成矿阶段,成矿热液从相对还原态向相对氧化态过渡,成矿流体减压使成矿热液中的金沉淀下来,最终形成可见金颗粒.

The propagation of Rayleigh waves is usually accompanied by dispersion, which becomes more complex with inherent attenuation. The accurate simulation of Rayleigh waves in attenuation media is crucial for understanding wave mechanisms, layer thickness identification, and parameter inversion. Although the vacuum formalism or stress image method (SIM) combined with the generalized standard linear solid (GSLS) is widely used to implement the numerical simulation of Rayleigh waves in attenuation media, this type of method still has its limitations. First, the GSLS model cannot split the velocity dispersion and amplitude attenuation term, thus limiting its application in the Q-compensated reverse time migration/full waveform inversion. In addition, GSLS-model-based wave equation is usually numerically solved using staggered-grid finite-difference (SGFD) method, which may result in the numerical dispersion due to the harsh stability condition and poses complexity and computational burden. To overcome these issues, we propose a high-accuracy Rayleigh-waves simulation scheme that involves the integration of the fractional viscoelastic wave equation and vacuum formalism. The proposed scheme not only decouples the amplitude attenuation and velocity dispersion but also significantly suppresses the numerical dispersion of Rayleigh waves under the same grid sizes. We first use a homogeneous elastic model to demonstrate the accuracy in comparison with the analytical solutions, and the correctness for a viscoelastic half-space model is verified by comparing the phase velocities with the dispersive images generated by the phase shift transformation. We then simulate several two-dimensional synthetic models to analyze the effectiveness and applicability of the proposed method. The results show that the proposed method uses twice as many spatial step sizes and takes 0.6 times that of the GSLS method (solved by the SGFD method) when achieved at 95% accuracy.

Gold mining is the most important anthropogenic source of heavy metal emissions into the environment. Re-searchers have been aware of the environmental impacts of gold mining activities and have conducted studies in recent years, but they have only selected one gold mining site and collected soil samples in its vicinity for analysis, which does not reflect the combined impact of all gold mining activities on the concentration of potentially toxic trace elements (PTES) in nearby soils at a global scale. In this study, 77 research papers from 24 countries were collected from 2001 to 2022, and a new dataset was developed to provide a comprehensive study of the distribution characteristics, contamination characteristics, and risk assessment of 10 PTEs (As, Cd, Cr, Co, Cu, Hg, Mn, Ni, Pb, and Zn) in soils near the deposits. The results show that the average levels of all 10 elements are higher than the global background values and are at different levels of contamination, with As, Cd, and Hg at strong contamination levels and serious ecological risks. As and Hg contribute to a greater non-carcinogenic risk to both children and adults in the vicinity of the gold mine, and the carcinogenic risks of As, Cd, and Cu are beyond the acceptable range. Gold mining on a global scale has already caused serious impacts on nearby soils and should be given adequate attention. Timely heavy metal treatment and landscape restoration of extracted gold mines and environmentally friendly approaches such as bio-mining of unexplored gold mines where adequate protection is available are of great significance.

Eighteen organochlorine pesticides (OCPs) in soil samples from the Changchun central urban area, Northeast China were analyzed using accelerated solvent extraction combined with gas chromatography/mass spectrometry (ASE-GC/MS) for the purpose of elucidating their contamination status, distribution characteristics, influencing factors, and feasible dangers in this city region. The complete concentrations of OCPs ranged from 15.63 to 92.79 ng/g, with a geomean of 36.46 ng/g. Hexachlorocyclohexane(HCHs), dichlorodiphenyltrichoroethane (DDTs), and chlordanes were the most dominant OCPs, with γ-HCH and p,p′-DDT being the predominant isomers. Higher concentrations of OCPs often centered to the northeast and southwest of the Changchun metropolis, and these artificial influences contributed to the destiny of OCPs in the soils. The residues of OCPs were derived from the historic utility of the technological DDT, dicofol, and lindane. A Pearson’s correlation evaluation indicated that TOC was once a key factor controlling OCP accumulation. The ecological risk evaluation based on the soil quality guidelines (SQGs) advises that the presence of DDTs, lindane, and heptachlor may additionally pose a poisonous ecological danger to soil organisms. The contrast outcomes of the incremental lifetime cancer risk (ILCR) confirmed that the highest cancer risk of OCPs to the posed populace was once low, whilst some unique areas with excessive OCP residues ought to be given attention. The research results provide basic information for evaluating the extent of OCP pollution in the soil of major cities in Northeast China and can help authorities establish environmental protection regulations and soil remediation techniques.