Investigation on pretreatment method for the determination of rare earth elements in polymetallic mineral samples in Pan-Xi region by ICP-MS.

The polymetallic mineral samples in Pan-Xi region are rich in rare earth resources, and exploring an efficient and accurate analysis method is of great significance for their comprehensive utilization. In this study, the samples were decomposed by three methods, namely closed acid dissolution, open acid dissolution with five acid and alkali fusion with sodium peroxide, and the 15 REE were determined by inductively coupled plasma mass spectrometry (ICP-MS) with Rh and Re as internal standard correction elements. The comparative experiments were conducted using standard substances, and the results showed: (1) The detection limit of closed acid dissolution method was low with relative standard deviation (RSD) ranging from 2.51% to 9.56% and the accuracy of method (ΔlgC) ranging from 0.006 to 0.073, while the sample processing was long, and the results of some REE were low. (2) The RSD of open acid dissolution with five acid method ranged from 1.93% to 7.96%, and ΔlgC ranged from 0.004 to 0.045 with low results of the determination results of REE. (3) The alkali fusion with sodium peroxide method eliminated the influence of matrix effects by selecting instrument optimization, sample dilution, appropriate internal standard elements, etc. The RSD ranged from 1.24% to 6.49%, and ΔlgC ranged from 0.001 to 0.032. In conclusion, alkali fusion with sodium peroxide method has a fast analysis process, complete sample dissolution, and the accuracy and precision of test results can meet the requirements of specification (DZ/T0011-2015), which is most suitable for the analysis of REE in polymetallic mineral samples from Pan-Xi region.

Ecological risk and spatial distribution, sources of heavy metals in typical purple soils, southwest China.

The identification and quantification of the ecological risks, sources and distribution of heavy metals in purple soils are essential for regional pollution control and management. In this study, geo-accumulation index (Igeo), enrichment factor (EF), pollution index (PI), potential ecological risk index (RI), principal component analysis (PCA) model and geographical detector (GD) were combined to evaluate the status, ecological risk, and sources of heavy metals (HMs) in soils from a typical purple soil areas of Sichuan province. The results showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn in purple soil were 7.77, 0.19, 69.5, 27.9, 0.077, 30.9, 26.5 mg/kg and 76.8 mg/kg, and the Igeo, EF and RI of topsoil Hg and Cd in designated area was the highest, and the average contents of Hg and Cd in topsoil were obviously greater than respective soil background value in Sichuan province and purple soil. The hot spots for the spatial distribution of 8 HMs were mainly focused in the southwest and northeast of the designated area, and there were also significant differences for 8 HMs distribution characteristics in the profile soil. Cu comes from both anthropogenic and natural sources, Zn, Ni and Cr mainly come from natural sources, but As, Pb, Hg and Cd mainly derived from human activities. GD results showed that soil texture (X18), altitude (X4), total nitrogen (TN), clay content (X3), sand content (X2) and silt content (X1) had the greatest explanatory power to 8 HMs spatial differentiation.This study provides a reference for understanding the status and influencing factors of HM pollution in typical purple soil, and lays a theoretical foundation for the environmental treatment of purple soil in China.

Source identification and driving factor apportionment for soil potentially toxic elements via combining APCS-MLR, UNMIX, PMF and GDM.

The contamination and quantification of soil potentially toxic elements (PTEs) contamination sources and the determination of driving factors are the premise of soil contamination control. In our study, 788 soil samples from the National Agricultural Park in Chengdu, Sichuan Province were used to evaluate the contamination degree of soil PTEs by pollution factors and pollution load index. The source identification of soil PTEs was performed using positive matrix decomposition (PMF), edge analysis (UNMIX) and absolute principal component score-multiple line regression (APCS-MLR). The geo-detector method (GDM) was used to analysis drivers of soil PTEs pollution sources to help interpret pollution sources derived from receptor models. Result shows that soil Cu, Pb, Zn, Cr, Ni, Cd, As and Hg average content were 35.2, 32.3, 108.9, 91.9, 37.1, 0.22, 9.76 and 0.15 mg/kg in this study area. Except for As, all are higher than the corresponding soil background values in Sichuan Province. The best performance of APCS-MLR was determined by comparison, and APCS-MLR was considered as the preferred receptor model for soil PTEs source distribution in the study area. ACPS-MLR results showed that 82.70% of Cu, 61.6% of Pb, 75.3% of Zn, 91.9% of Cr and 89.4% of Ni came from traffic-industrial emission sources, 60.9% of Hg came from domestic-transportation emission sources, 57.7% of Cd came from agricultural sources, and 89.5% of As came from natural sources. The GDM results showed that distance from first grade highway, population, land utilization and total potassium (TK) content were the main driving factors affecting these four sources, with q values of 0.064, 0.048, 0.069 and 0.058, respectively. The results can provide reference for reducing PTEs contamination in farmland soil.

Spatial distribution characteristics of soil heavy metals in Sabao Chaqu watershed of Tuotuo river, Qinghai-Tibet Plateau based on geographic detector.

The Qinghai-Tibet Plateau belongs to the area of extremely fragile environment and sensitive to human activities. In recent years, more and more human interference has been detected in this area. In this study, 128 surface soil samples were collected from the Sabao Chaqu watershed of the Tuotuo river at the source of the Yangtze River on the Qinghai-Tibet Plateau. The soil pollution status and spatial distribution characteristics of Cd, Hg, As, Cu, Pb, Cr, Zn and Ni were evaluated by soil accumulation index, enrichment factor, pollution index and geographical detector. The results showed that the average contents of As, Cd, Pb and Zn in the study area were 1.2-3.64 times higher than soil background values of Tibet, while the contents of Hg, Cr, Cu and Ni were lower than the background values, while the average content of As was higher than the soil pollution risk screening value (GB15618-2018), and the pollution index showed that As was in a low pollution state, while the other 7 heavy metals were in a safe state. There were significant differences in the spatial distribution of 8 heavy metals and there was a significant correlation with soil properties and distance factors. Factor detection showed that natural factors had the strongest explanatory power to the contents of As, Cd, Cr, Cu and Ni, distance from the lake and soil Sc content had the strongest explanatory power to Hg content, and anthropogenic factors had the strongest explanatory power to Pb content. Interaction detection revealed that the q values of the strongest interaction explanatory power for As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn were 2.81, 4.30, 1.26, 2.47, 2.33, 1.59, 6.37, and 5.08 times higher than their strongest factor detection explanatory power, respectively. The interaction between anthropogenic factors and other factors has an important influence on the spatial differentiation of heavy metals in the study area. Risk detection showed that the average contents of As, Cd, Cr, Cu, Hg, Ni, Pb and Zn were the highest in the subregions of MgO, TS, Sc, X6, X13, MgO, TN and X4, respectively. Comprehensive study shows that the spatial differentiation of As, Cd, Cr, Cu, Ni and Zn is mainly affected by natural factors, but there are also some anthropogenic factors, the spatial differentiation of Hg is affected by both natural factors and atmospheric deposition, and the spatial distribution characteristics of Pb are mainly affected by anthropogenic factors.

Spatial differentiation of soil nutrients and their ecological chemometrics based on geographic detector in National Agricultural Park of Tangchang, Southwest China.

In order to analyze the spatial variability of soil nutrients and their ecological chemometrics in Tangchang Town, National Agricultural Park, 20 influencing factors were selected: soil pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni, Se, elevation, slope, aspect, land use type, distance from industrial land, distance from commercial land, distance from railway, distance from residential area, distance from highway and distance from river. The effects of various influencing factors on the spatial variability of total organic carbon (TOC), total nitrogen (N), total phosphorus (P), total potassium (K) and ecological stoichiometry were analyzed by means of geographic detector. The results showed that average contents of soil TOC, N, P and K in the study area are 10.24 g kg-1, 1.33 g kg-1, 1.14 g kg-1 and 23.60 g kg-1, respectively, and there were significant differences in the spatial distribution of soil nutrients and their eco-stoichiometry in the study area, and TOC, N, P, K, C/N, C/P, C/K, N/P, N/K and P/K has a significant correlation with each other and most correlation coefficients are above 0.5 or below -0.5. Factor detection showed that soil properties, distance from railway and distance from residential area had the most significant explanatory power to the spatial heterogeneity of soil nutrients and eco-stoichiometry. Interaction detection showed that the interaction between soil properties with other factors was the most important factor affecting the spatial differentiation of soil nutrients and their ecological chemometrics, and elevation, distance from railway and distance from residential area were also important factors. Risk detection showed that the differences of soil nutrients and their ecological stoichiometry were most significant in the subregions of soil properties (pH, Cd, Hg, As, Cu, Pb, Cr, Zn, Ni and Se).

[Research Progress on Spatial Differentiation and Influencing Factors of Soil Heavy Metals Based on Geographical Detector].

The geographical detector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. It can not only reveal the influence of a single factor on dependent variables but also evaluate the influence of two-factor interactions and does not need to consider linearity, while also avoiding the influence of multivariate collinearity. Without strong model assumptions, it solves the limitations of traditional methods in analyzing category variables. The research on the spatial differentiation of heavy metals in soil is increasingly widely used. This study collected 40 research reports on the spatial differentiation of soil heavy metals via geographical detector, combed the discrete methods of independent variables, research scale, dependent variables and types of independent variables, factor detection, exchange detection, risk detection, and ecological detection and put forward the problems that need to be clarified in the future application of this research. It is expected to provide support for the deep application of geo-detector in the field of spatial differentiation of soil heavy metals.

Spatial distribution characteristics of heavy metal(loid)s health risk in soil at scale on town level.

In order to reveal the Spatial distribution characteristics of heavy metal(loid)s health risk in soil on the town-scale, 788 topsoil samples were collected from a town in the hinterland of Chengdu Plain, with 5 subordinate communities and 17 administrative villages as the research sub regions. The USEPA health risk assessment model was used to assess the health risks of heavy metal(loid)s Cd, Hg, As, Cu, Pb, Cr, Zn and Ni in the soil, the health risk analysis method system based on the geographic detector and the optimized rank-size theory model are used to clarify the spatial differentiation and risk level difference of health risk in the study area. The results showed that the average values of Cd, Hg, As, Pb, Cr, Cu, Ni and Zn in the soil of the study area were 0.221, 0.155, 9.76, 32.2, 91.9, 35.2, 37.1 and 108.8 mg/kg, respectively. The health risks of heavy metal(loid)s in soil to adults and children are generally within the acceptable range, but the maximum hazard index of children and the maximum non-carcinogenic risk value of Cr to children are 2.653303 and 1.213098 respectively, which were exceeding the acceptable range. The carcinogenic risk of Cr and As to adults and children and the carcinogenic risk of Cd to children are at 1 × 10-4 to 1 × 10-6, exceeding the 10-6 health threshold. The q-value range of heavy metal(loid)s health risk spatial differentiation of soil in the study area is 0.016-0.425. The spatial differentiation of non-carcinogenic risk of Hg, As, Ni, Pb, Cd and Cr and the spatial differentiation of carcinogenic risk of Cr and As are larger, which needs further attention. The strictly controlled area of heavy metal(loid)s health risk in the soil of the study area (R ≥ 1.1) is mainly concentrated in the central, western and northeast sub regions, and most sub regions belong to the safe utilization area (0.9 < R < 1.1). The health risk assessment of heavy metal(loid)s in soil on a town scale is of positive significance for enriching health risk research methods, measuring health risk levels at different scales, and formulating refined risk management and control strategies.

[Spatial Differentiation and Influencing Factor Analysis of Soil Heavy Metal Content at Town Level Based on Geographic Detector].

Geographic detectors can quickly detect spatial stratified heterogeneity and quantitatively reveal the intensity of driving factors of heavy metal content, which is of great significance for the prevention, control, and remediation of soil heavy metal pollution. In order to reveal the spatial differentiation and influencing factors of soil heavy metal content on the town-scale, 788 topsoil samples were collected from a town in the hinterland of Chengdu Plain. Soil heavy metal (Cd, Hg, As, Cu, Pb, Cr, Zn, and Ni) pollution risk assessments were carried out by using the geo-accumulation index method. Additionally, based on the geographic detector model, 15 factors such as soil properties, topography, soil forming factors, and distance were taken as independent variables, and the contents of each heavy metal element were taken as dependent variables to explore the spatial differentiation and influencing factors of heavy metal content in soils. The results showed that:the average contents of Hg, As, Pb, Cr, Cu, Ni, and Zn in the study area were 1.06-1.93 times the background value of Chengdu, and the content of Cd was lower than the background value; among them, Hg reached the light pollution level, and the other seven heavy metals were at the non-pollution level. The spatial distribution of eight heavy metals was significantly different, the correlation among the elements was significant, and a significant correlation was found between most heavy meals with soil properties; however, the correlation with distance factor and topographic factor was relatively weak. The factor detection showed that TP, TK, pH, TOC, elevation, and distance from the railway had the most significant explanatory power for the heavy metal contents. Interaction detection showed that the interaction between soil properties and other factors was the dominant factor for the spatial variation in heavy metals, and elevation, distance from residential area, distance from railways, and distance from industrial areas were also important factors. Risk detection showed that Hg had the most significant difference in the subregion of elevation and distance from railway, whereas the other seven heavy metals had the most significant difference in the sub-regions of influencing factors of soil properties. The spatial distribution of heavy metals varied significantly in soil at the town-scale, which was closely related to soil properties, topography, and human activities in the study area.

Ecological and human health risk assessment of heavy metal(loid)s in agricultural soil in hotbed chives hometown of Tangchang, Southwest China.

To determine the heavy metal(loid)s (HMs) contamination of agricultural soil in hotbed chives hometown of Tangchang, 788 topsoil samples were collected and analyzed for their heavy metal(loid)s concentration. The index of geo-accumulation (Igeo), pollution index (PI) and potential ecological risk index (EIi) were used to assess the degree of pollution. Correlation analysis and principal component analysis (PCA) were used to determine the sources of soil HMs. Human health risks estimated with hazard index (HI) and carcinogenic risk (CR) indices based on ingestion, inhalation and dermal exposure pathways for adults and children. The mean values of Cd, Hg, As, Pb, Cr, Cu, Ni and Zn were 0.221, 0.155, 9.76, 32.2, 91.9, 35.2, 37.1 and 108.8 mg kg-1, respectively, which did not exceed the threshold values of the risk screening value for soil contamination. The potential ecological risk of soil heavy metal(loid)s was low level and there was no significant human health risk. Based on PCA, Pb and Hg may originate from transportation and atmospheric deposition, Zn, Cr and Ni may originate from natural sources and industrial activities, and Cu and Cd may originate from agricultural activities. Overall, from the perspective of HMs content, the soil quality in this study area was at a clean level. This study provides a reference and a basis for formulating effective measures to prevent and control HMs enrichment in agricultural soils.

[Distribution characteristics and environmental significance of heavy metals in soil particle size fractions from tropical forests in China].

Three tropical forest soils were collected from Haikou, Qionghai and Tunchang in Hainan Island. Soil particle size fractionations were conducted using the standard dry-sieving procedure. Distribution of heavy metals in bulk samples and particle size fractions was determined by ICP-MS. The distribution characteristics and the response to organic carbon and iron were discussed. The results showed that the distribution of heavy metals was highly associated with the particle size fractions and variable patterns were found, which decreased with the increasing size. The accumulation of Cr, Ni, Cu, Zn, Cd and Cd was predominantly contributed by the particles finer than < 53 microm in diameter, whereas As mainly accumulated in particle size of 53-1 000 microm. Generally, the microaggregate (< 250 microm) contributed 14.38%-65.04% of heavy metals to the contents in bulk soil and the silt-clay aggregates (< 53 microm) contributed 2.61% -32.01%. The content of heavy metals except for As and Cd and Pb in Haikou soil in these different size fractions were controlled by the organic carbon and iron contents, which increased with the decreasing particle size.