Identification of factors driving the spatial distribution of molybdenum (Mo) in topsoil in the Longitudinal Range-Gorge Region of Southwestern China using the Geodetector model.

As a key component of plant nitrogen-fixing enzymes and a variety of human coenzyme factors, molybdenum (Mo) plays an essential role in supporting both plant growth and human health. Soil is a key medium for the cycling of Mo in the biosphere. However, the driving anthropogenic and natural factors governing the spatial distribution of Mo in soil and their interactions are not well understood. To determine the factors that affect the spatial patterns of Mo in topsoil, 6980 samples were collected from the Longitudinal Range-Gorge Region (Linshui County, Sichuan Province, China). In this area, tall mountains are adjacent to deep valleys. Topsoil with enriched Mo is mostly distributed in mountainous areas. The most important factors influencing Mo in topsoil are soil parent materials (q = 0.482), altitude (q = 0.256), and soil type (q = 0.259). There are synergistic effects among the various driving factors [q(X1 âˆ© X2) > Max[q(X1), q(X2)]]. The Geodetector model was used to validate the magnitude of the interaction effects. The contribution to interacting factors is nonlinearly enhanced when the contribution of a single factor was low (any two factors of aspect, road distance, land use type, and S). The contribution to interacting factors is enhanced bidirectionally when the contribution of a single factor was high (any two factors of altitude, soil type, soil parent material, OM, and TFe2O3). When the contribution of one factor is high and the other is low, the contributing to interacting factors is mostly enhanced bidirectionally and a few are nonlinearly enhanced.

Linking health to geology-a new assessment and zoning model based on the frame of medical geology.

With the growing concerns about the Earth's environment and human health, there has been a surge in research focused on the intersection of health and geology. This study quantitatively assesses the relationship between human health and geological factors using a new framework. The framework considers four key geological environment indicators related to health: soil, water, geological landform, and atmosphere. Results indicate that the atmospheric and water resource indicators in the study area were generally favorable, while the scores of geological landforms varied based on topography. The study also found that the selenium content in the soil greatly exceeded the local background value. Our research underscores the importance of geological factors on human health, establishes a new health-geological assessment model, and provides a scientific foundation for local spatial planning, water resource development, and land resource management. However, due to varying geological conditions worldwide, the framework and indicators for health geology may need to be adjusted accordingly.

Study on safe usage of agricultural land in karst and non-karst areas based on soil Cd and prediction of Cd in rice: A case study of Heng County, Guangxi.

It is well-known that Cd concentration in the soil, Cd bioavailability, and Cd bioaccumulation in rice (Oryza sativa L.) grains vary greatly in different soil parent materials. Therefore, the classification of agricultural land environmental quality and agricultural land safe usage based on the Cd content in the soil has a wide deviation. By the application of systematic sampling and analysis of soil and rice samples, and in comparison with the different soil parent materials in Heng County, it was found that soil derived from carbonate rocks has higher total Cd and lower mobile Cd proportion than soil from the non-karst areas. This result indicated that soil carbonates raised soil pH and the adsorption of Fe/Mn oxide/hydroxide on Cd significantly reduced the bioavailability of Cd in karst areas. In contrast, acidic soils with relatively lower CaO, TFe2O3, Mn and total Cd contents, the grown rice plants accumulated higher Cd in their grains. Further research confirmed significant differences in Cd bioaccumulation abilities in the soil between karst and non-karst areas. On this basis, the bioaccumulation factor prediction models of Cd in rice grains were developed in karst and non-karst areas. According to the total concentration of Cd in topsoil samples obtained from the area survey and the predicted Cd content in rice grains, an agricultural land safe usage scheme was put forward. The results showed that the agricultural land classification method based on Cd concentration in the soil and rice grains was more accurate and scientific than that based on the Cd contents in the soil alone.

Transfer mechanism and bioaccumulation risk of potentially toxic elements in soil-rice systems comparing different soil parent materials.

Although the accumulation of potentially toxic elements in soil and crops has attracted widespread attention, the characteristics of the transfer and accumulation of potentially toxic elements in soil-crop systems with different soil parent materials are still not clear. Soil and crop samples were collected from agricultural regions with different soil parent materials in Guangxi, China. This study analyzed the concentrations of Cd, Zn, and Fe in the roots, straws, and seeds of rice (Oryza sativa L.) and soils with Quaternary sediments and clastic rocks as the parent materials. The concentration of several potentially toxic elements in rice tissue from the two areas followed the order of Croot> Cstraw> Cseed. The transport capability of Cd and Zn from roots to straws is higher than straws to seeds, and Fe showed a strong capability for transport from straws to seeds. In general, the transfer capacity of potentially toxic elements in the soil-rice system in the Quaternary sediments area was stronger than that in the soil-rice system in the clastic rocks area. Soil pH and minerals, which were represented by major elements, were the main factors affecting the transfer of metals from soil to seeds. This approach could help to evaluate the bioaccumulation risk of potentially toxic elements in crops in different areas quantitatively.

Effects of Soil pH and Mineral Nutrients on Cadmium Uptake by Rice Grain in the Pearl River Delta, China.

Alluvial soils are rich in mineral nutrients, and contain high heavy metals, especially Cd. The interactions of mineral nutrients with Cd in soil-rice grain systems on natural condition of alluvial plain are highlighted in this study. 110 pairs of rice grain and soil (0-20 cm) samples from the Pearl River Delta were investigated and measured. The results indicated that pH, organic matter, cation exchange capacity, clay, Ca, Cd, Fe, Mn and Zn are the most important soil characteristics controlling Cd uptake by rice grain. There are synergetic interactions between Cd and mineral elements in the soils, and antagonistic interactions between them in the rice grains. It could provide useful information for the risk assessment of heavy metals in the soils of alluvial plain.

Safe utilization and zoning on natural selenium-rich land resources: a case study of the typical area in Enshi County, China.

Selenium (Se) is an essential trace element. However, Se in soil is often accompanied by heavy metals, such as cadmium (Cd), because of geological background. The safe utilization of such Se-rich land resources remains a challenge. A typical Se-rich area located in Enshi County, China, was systematically investigated with geochemical and epidemiological methods. The results show that Se in the topsoil is 0.84 ± 1.39 µg/g, whereas that of Cd is 0.93 ± 1.63 µg/g. And the concentration of Se and Cd in corn is 0.22 ± 0.96 µg/g and 0.15 ± 0.32 µg/g, respectively, which is mainly related to the high concentrations in soil. The benchmark dose limit of urinary Cd for ß2-microglobulin in subjects (n = 160) was calculated as 3.27 µg/g Cr. In view of crop-human dose effect and combining the relationship among the concentrations of crops and human biomarkers and the concentrations of crops and topsoil, this study established the models of land resource safety zoning. With that, the risk screening value of Cd in the soil could be obtained as 0.98 µg/g in this typical area. The proportions of priority utilization, safe utilization, and strict management of agricultural land area were 58.85%, 22.90%, and 18.25%, respectively, in Enshi, China. These results could provide scientific support for local agricultural development and ecological sustainability.

Application of ecogeochemical prediction model to safely exploit seleniferous soil.

Seleniferous soil and crops have recently attracted attention worldwide. Cultivating seleniferous crops in the absence of heavy metals is greatly challenging. This study aimed to develop approaches for the safe exploitation of seleniferous soil. We collected 246 pairs of rice grain samples and their corresponding rhizosphere soil samples and 8542 topsoil samples from Binyang and Xingbin in Guangxi. The Cd, Cu, Hg, Pb, Zn, and Se contents of soil and rice grain samples were tested. Several soil properties, including CaO, Mn, Mo, and S contents; total organic carbon content; and pH were also measured. Soil and rice grain samples that were classified as seleniferous accounted for 85.77% and 88% of all samples, respectively. More than 30% of soil and rice grain samples were potentially polluted by Cd. The percentage of seleniferous rice grain samples increased as soil Se concentration increased. Notably, however, the percentage of Cd-polluted rice grain samples decreased with the increase in soil Cd concentration. Models for the prediction of BAFs of heavy metal and Se were accurately established on the basis of significant partial correlations between log10 (BAFs) and log10 (soil properties). Farmlands with seleniferous soil under preferential protection and with safely exploited seleniferous soil accounted for 82.61% of the total study area. Sites that require remediation or land-use changes accounted for only 14.7% of the total study area and were mainly distributed in the center of the study area.

Using machine learning to predict selenium and cadmium contents in rice grains from black shale-distributed farmland area.

Cadmium (Cd) and selenium (Se) are widely enriched in soil at black shale outcropping areas, with Cd levels exceeding the standard (2.0 mg/kg in 5.5 < pH ≤ 6.5) commonly. The prevention of Cd hazards and the safe development of Se-rich land resources are key issues that need to be urgently addressed. To ensure safe utilization of Se-rich land in the CdSe coexisting areas, 158 rice samples, their corresponding rhizosphere soils, and 8069 topsoil samples were collected and tested in the paddy fields of Ankang City, Shaanxi Province, where black shales are widely exposed. The results showed that 43 % of the topsoil samples were Se-rich soil (Se > 0.4 mg/kg) wherein 79 % and 3 % of Cd concentrations exceeded the screening value and control value, respectively, according to the GB15618-2018 standard. Meanwhile, 63 % of the rice samples were Se rich (Se > 0.04 mg/kg) and the Cd content exceeded the prescribed limit (0.2 mg/kg) in Se-rich rice by 26 %. There was no significant positive correlation between the Se and Cd contents in the rice grains and the Se and Cd contents in the corresponding rhizosphere soil. The factors influencing Se and Cd uptake in rice were SiO2, CaO, P, S, pH, and TFe2O3. Accordingly, an artificial neural network (ANN) and multiple linear regression model (MLR) were used to predict Cd and Se bioaccumulation in rice grains. The stability and accuracy of the ANN model were better than those of the MLR model. Based on survey data and the prediction results of the ANN model, a safe planting zoning of Se-rich rice was proposed, which provided a reference for the scientific planning of land resources.

Impacts of periodic saltwater inundation on heavy metals in soils from the Pearl River Delta, China.

The alluvial plain delta is vulnerable to complex land-sea interactions as a result of rising sea levels and increasing storm surges due to global environmental change. Topsoil samples (0-20 cm) from the Pearl River Delta (PRD) were subjected to periodic artificial saltwater inundation treatments with varying salinities (0, 35‰, 40‰, 50‰) for 50 days to explore the impacts of saltwater inundation on heavy metals (Cd, Pb, Zn) in soils. The inundation treatments reached dynamic equilibrium in approximately 20 days, and heavy metals were promoted to release into leachate. The extraction rate of heavy metals was highest with artificial saltwater at 40‰ salinity, which was generally attributed to pH variation, increasing ionic strength and reductive dissolution of Fe-Mn oxyhydroxides. However, once the salinity reached 50‰, a higher SO2- 4concentration could depress the release of heavy metals by providing more negative adsorption sites. Cd in soils was most likely to leach, followed by Zn, but Pb showed higher retention. After saltwater inundation, the bioavailability of heavy metals decreased in the order Cd > Zn > Pb. Redundancy analysis (RDA) results demonstrated that Cd and Zn are more susceptible to soluble salt ions in soils than Pb. The retention of Pb could be attributed to its larger ionic radius and reduced hydrated radius as well as the stable species under the pH conditions of the treatments. This study suggests that the migration of heavy metals could reduce the water quality and increase the ecological risk of the interaction zone between land and sea.

Distribution of potentially toxic elements in soils and sediments in Pearl River Delta, China: Natural versus anthropogenic source discrimination.

Although anthropogenic contamination has been regarded as the most important source of potentially toxic elements (PTEs) in soils of large river delta plains, the extent to which human activities affect PTEs in soils is worth exploring. This study used high density geochemical data to distinguish source patterns of PTEs in soils of the Pearl River Delta Economic Zone, a large industrialized and urbanized area in China. Enrichment factor, discriminant analysis, principal components analysis, cumulative distribution function, and positive matrix factorization were used to identify sources of PTEs in soils. The results indicated that parent material was the most significant factor affecting geochemical characteristics of PTEs in soils. Median concentrations of Cd, Cr, Cu, Hg, Pb, and Zn were 0.400, 88.5, 40.5, 0.143, 43.0, and 116.0 mg/kg for stream sediments, 0.333, 75.7, 39.0, 0.121, 42.6, and 98.5 mg/kg for deep soils, and 0.365, 74.0, 45.1, 0.143, 44.6, and 119.5 mg/kg for surface soils, respectively, all of which exceed relevant reference standards. Compared with stream sediments and deep soils, surface soils exhibit substantial concentrations of PTEs. Chemical weathering and erosion of parent materials distributed in the Pearl River Delta were the main sources of PTEs in soils. Diffuse contamination and many small local contamination sources distributed throughout the study area were the most significant anthropogenic sources of PTEs in surface soils. Intensive human activities failed to change the soil geochemical characteristics derived from the parent material at the regional scale. However, it could induce non-point source pollution and local severe PTEs pollution in surface soils.

Identification of soil parent materials in naturally high background areas based on machine learning.

Recently, farmlands with high geological background of Cd derived from carbonate rock (CA) and black shale areas (BA) have received wide attention. However, although both CA and BA belong to high geological background areas, the mobility of soil Cd differs significantly between them. In addition to the difficulty in reaching the parent material in deep soil, it is challenging to perform land use planning in high geological background areas. This study attempts to determine the key soil geochemical parameters related to the spatial patterns of lithology and the main factors influencing the geochemical behavior of soil Cd, and ultimately uses them and machine-learning methods to identify CA and BA. In total, 10,814 and 4323 surface soil samples were collected from CA and BA, respectively. Hot spot analysis revealed that soil properties and soil Cd were significantly correlated with the underlying bedrock, except for TOC and S. Further research confirmed that the concentration and mobility of Cd in high geological background areas were mainly affected by pH and Mn. The soil parent materials were then predicted using artificial neural network (ANN), random forest (RF) and support vector machine (SVM) models. The ANN and RF models showed higher Kappa coefficients and overall accuracies than those of the SVM model, suggesting that ANNs and RF have the potential to predict soil parent materials from soil data, which might help in ensuring safe land use and coordinating activities in high geological background areas.

Soil selenium enrichment in the Loess Plateau of China: Geogenic evidence, spatial distribution, and it's influence factors.

The selenium (Se)-deficient soil belt in China has gained widespread attention. During large-scale soil surveys in China, Se-rich soils within low-Se belts have been identified. However, the sources of Se in those soils and the controlling factors for their enrichment remain unclear. Here we summarize Se concentrations and spatial distributions in the Yuanzhou district of the Loess Plateau. We evaluated Se variations in soil profiles, Se migration into water bodies, and considered soil indicators, topographic characteristics and the influence of land-use types on soil Se concentrations. The average Se concentration in the topsoil of the Yuanzhou district was 0.164 µg/g. High-Se soils (>0.222 µg/g) were found in the western valley plain and the southern red bed hilly area, as well as sporadically in higher elevation forestland and grassland areas in the east. Enrichment of Se in the topsoil in the eastern and southern areas was primarily due to Se adsorption and accumulation by soil organic matter as well as enrichment in gypsum, berlinite, and clay minerals during soil formation. Widespread enrichment in the southern area was linked to high Se concentrations in red Tertiary sedimentary rocks. In the western area, enrichment of Se in topsoil was found on both sides of the Qingshui River at low elevations with gentle slopes, with river water being the primary carrier of Se enrichment. These findings provide valuable insights into the epigenetic geochemical behavior of soil Se in China's low-Se belt that accounts for development of Se-rich soils in the region.

One-step separation of Cu, Fe, Zn and Cd and isotope ratio analysis by MC-ICP-MS for geological samples.

Multi-isotope systems have shown great application potential in tracing geological and environmental processes. In order to obtain the isotopic composition of multiple elements of interest, the common protocol is to separate each element from the matrix by independent procedures, which has some limitations, including poor efficiency, being time-consuming, requiring large samples and being unsuitable for rare samples (e.g., meteorite, lunar soil and atmospheric aerosol samples). In this study, we present an integrated and optimized one-step method to separate Cu, Fe, Zn and Cd from complex matrix elements using the AG MP-1M anion exchange resin. By experimentally optimizing the resin volume, eluent concentration and eluent amount, these target elements can be effectively separated from the matrix elements, such as Cu separation from Ti and Co, Zn separation from Fe and Cd, and Cd separation from Sn. The recoveries of Cu, Fe, Zn and Cd were 100.1 ± 0.8% (2SD, n = 3), 99.8 ± 0.7% (2SD, n = 3), 100 ± 0.8% (2SD, n = 3) and 99 ± 1% (2SD, n = 3), respectively. Moreover, the resolution (R) between the elements of interest and interfering elements was in the range of 1.8-28.1. The process blanks of Cu, Fe, Zn and Cd were 1-1.6 ng, 62-70 ng, 2.1-3 ng and 66-74 pg, respectively. The obtained isotope ratios for the standard reference materials agreed well with the published values. Meanwhile, we have reported the Cu, Fe and Zn isotope ratios of six soil and sediment standard reference materials, namely NIST 2711a, GSS-1, GSD-5a, GSD-7a, GSD-12 and GSD-23, for the first time. These new data can be used for the intercalibration and quality control of soils and sediments in other laboratories. The one-step separation of Cu, Fe, Zn and Cd shows obvious economic and efficiency advantages, making it suitable for the simultaneous separation of multiple elements of interest in geological samples.

Leaching experiments and risk assessment to explore the migration and risk of potentially toxic elements in soil from black shale.

Black shale is rich in potentially toxic elements (PTEs) that migrate through rock weathering or rainfall, adversely affecting human health and the environment. In this study, simulated rainfall leaching experiments were used to investigate the migration patterns and leaching kinetics of PTEs in black shale from the Lower Cambrian Hetang Formation and to analyze the water quality index (WQI) of PTEs in the leachate. A comparison between the risk of PTEs in the leachate and those in the soil was also made to determine the risk sources, risk status, and distribution characteristics of PTEs in the study area. The WQI of the indoor column experimental leachate indicated the highest As contamination. The geo-accumulation index (Igeo) and potential ecological risk (Er) of soils in the entire region revealed that the risk of Cd was the highest. Furthermore, by mapping the distribution of Igeo and Er in soils, the risk level in the region where black shale is located was found to be significantly higher than that in other areas. Comparing the leaching rate of PTEs with the WQI from leaching experiments, the risk associated with As in soil can be inferred to originate mainly from the leaching of black shale. Previous studies on PTEs in black shale in the study area tended to focus on Cd; however, this study found that the risk of As was not negligible. The health risk assessment also showed that the risk at the location of black shale was beyond the accepted range. Overall, this study provided a new and important evaluation law for the level of pollution by PTEs and health risks in typical black shale regions.

Use of artificial neural network to evaluate cadmium contamination in farmland soils in a karst area with naturally high background values.

In recent years, the naturally high background value region of Cd derived from the weathering of carbonate has received wide attention. Due to the significant difference in soil Cd content and bioavailability among different parent materials, the previous land classification scheme based on total soil Cd content as the classification standard, has certain shortcomings. This study aims to explore the factors influencing soil Cd bioavailability in typical karst areas of Guilin and to suggest a scientific and effective farmland use management plan based on the prediction model. A total of 9393 and 8883 topsoil samples were collected from karst and non-karst areas, respectively. Meanwhile, 149 and 145 rice samples were collected together with rhizosphere soil in karst and non-karst areas, respectively. The results showed that the higher CaO level in the karst area was a key factor leading to elevated soil pH value. Although Cd was highly enriched in karst soils, the higher pH value and adsorption of Mn oxidation inhibited Cd mobility in soils. Conversely, the Cd content in non-karst soils was lower, whereas the Cd level in rice grains was higher. To select the optimal prediction model based on the correlation between Cd bioaccumulation factors and geochemical parameters of soil, artificial neural network (ANN) and linear regression prediction models were established in this study. The ANN prediction model was more accurate than the traditional linear regression model according to the evaluation parameters of the test set. Furthermore, a new land classification scheme based on an ANN prediction model and soil Cd concentration is proposed in this study, making full use of the spatial resources of farmland to ensure safe rice consumption.

Impacts of parent material on distributions of potentially toxic elements in soils from Pearl River Delta in South China.

Assessing the impacts of parent material on distributions of potentially toxic elements (PTEs) in soils has significant consequences in the apportionment of their sources. In this study, geochemical distributions and sources of PTEs in the soils developed in quaternary sediments and granite plutons of Pearl River Delta (PRD), South China, were investigated. The results indicate that there are systematic differences between the concentrations of oxides and PTEs in the soils developed in these two parent materials. The parent material predominantly determines the element distributions in the soils. The PTEs of the deep soils developed in quaternary sediments originated mainly from mafic, felsic, and carbonate sources materials as well as polymetallic deposits. For the deep soils developed in granite plutons, the element associations are governed mainly by their geochemical affinities and behaviors and the mineral compositions of granite plutons. Anthropogenic activities impact the features of the PTEs in the surface soils of PRD. However, superimposed regional-scale pollution was found to not hide the effect of the parent material on the distribution of PTEs in the surface soils.

Prediction and risk assessment of five heavy metals in maize and peanut: A case study of Guangxi, China.

To assess the contamination levels and health risk of cadmium (Cd), copper (Cu), mercury (Hg), lead (Pb), and zinc (Zn) to human beings, the concentrations of these heavy metals in soil were surveyed and the concentrations in maize and peanut grains were estimated by models. The geo-accumulation index (I geo) was calculated, and chronic daily intake (CDI), hazard quotient (HQ) and hazard index (HI) were estimated. Results indicated that the concentrations of Cd, Cu, Hg, Pb, and Zn in the soil samples exceeded the limit set by authorities in China. However, the concentrations in maize and peanut grains were rarely higher than the allowable concentrations suggested by the Ministry of Health of China (MHC). In accordance with geo-accumulation, these heavy metals in soil samples were polluted to different extents. Prediction models were developed to effectively assess the health risk of using TOC, Mn, pH, and CaO to human beings. Therefore, the concentrations of these heavy metals in the grains could be decreased by changing their levels in soil. The CDI, HQ, and HI were estimated by estimating concentrations of Cd, Cu, Pb, and Zn in maize grains, indicating that these metals exhibited a slight health risk to adult residents.

[Spatial Interpolation Methods and Pollution Assessment of Heavy Metals of Soil in Typical Areas].

It is important to choose the best spatial interpolation method to reflect spatial distribution features and evaluate soil heavy metal pollution. The spatial distribution of arsenic (As) and cadmium (Cd) concentrations in top soil samples from Hubei Province were studied by four frequently-used spatial interpolation methods, including inverse distance weighted (IDW), radial basis function (RBF), local polynomial interpolation (LPI) and ordinary kriging (OK). The interpolation precision and effect of the spatial distribution of the four methods were compared with the results of cross validation and spatial distribution, and the pollution was assessed by the geoaccumulative index (Igeo) and indicator kriging (IK). The results showed that the four interpolation methods had small prediction errors, but that the interpolation effects were quite different. Among them, LPI had the most serious smoothing effect, followed by OK. The IDW and RBF best retained the extreme value information for element concentrations, and interpolation results were more detailed-and so to accurately understand the distribution of soil heavy metals, IDW or RBF methods were recommended. Taking the arithmetic mean of heavy metal concentrations in deep soil of Hubei Province as the background value, the evaluation result of geo-cumulative index pollution allowed exceedance percentages for As and Cd accounted for 5.5% and 99.0% respectively. The soils of the study areas were heavily contaminated with Cd. The pollution evaluation result from IK showed that high probability contaminated areas, with moderate-heavy contamination levels, were mainly located in the central part of the study area. The authors concluded that development of agriculture in the research area should include attention to Cd pollution and that soils there required the effective treatment and restoration of Cd levels.

Practicability of monitoring soil Cd, Hg, and Pb pollution based on a geochemical survey in China.

Repeated visiting, i.e., sampling and analysis at two or more temporal points, is one of the important ways of monitoring soil heavy metal contamination. However, with the concern about the cost, determination of the number of samples and the temporal interval, and their capability to detect a certain change is a key technical problem to be solved. This depends on the spatial variation of the parameters in the monitoring units. The "National Multi-Purpose Regional Geochemical Survey" (NMPRGS) project in China, acquired the spatial distribution of heavy metals using a high density sampling method in the most arable regions in China. Based on soil Cd, Hg, and Pb data and taking administrative regions as the monitoring units, the number of samples and temporal intervals that may be used for monitoring soil heavy metal contamination were determined. It was found that there is a large variety of spatial variation of the elements in each NMPRGS region. This results in the difficulty in the determination of the minimum detectable changes (MDC), the number of samples, and temporal intervals for revisiting. This paper recommends a suitable set of the number of samples (nr) for each region under the balance of cost, practicability, and monitoring precision. Under nr, MDC values are acceptable for all the regions, and the minimum temporal intervals are practical with the range of 3.3-13.3 years.

Ecological geochemical assessment and source identification of trace elements in atmospheric deposition of an emerging industrial area: Beibu Gulf economic zone.

Industrialization and urbanization have led to a deterioration in air quality and provoked some serious environmental concerns. Fifty-four samples of atmospheric deposition were collected from an emerging industrial area and analyzed to determine the concentrations of 11 trace elements (As, Cd, Cu, Fe, Hg, Mn, Mo, Pb, Se, S and Zn). Multivariate geostatistical analyses were conducted to determine the spatial distribution, possible sources and enrichment degrees of trace elements in atmospheric deposition. Results indicate that As, Fe and Mo mainly originated from soil, their natural parent materials, while the remaining trace elements were strongly influenced by anthropogenic or natural activities, such as coal combustion in coal-fired power plants (Pb, Se and S), manganese ore (Mn, Cd and Hg) and metal smelting (Cu and Zn). The results of ecological geochemical assessment indicate that Cd, Pb and Zn are the elements of priority concern, followed by Mn and Cu, and other heavy metals, which represent little threat to local environment. It was determine that the resuspension of soil particles impacted the behavior of heavy metals by 55.3%; the impact of the coal-fired power plants was 18.9%; and the contribution of the local manganese industry was 9.6%. The comparison of consequences from various statistical methods (principal component analysis (PCA), cluster analysis (CA), enrichment factor (EF) and absolute principle component score (APCS)-multiple linear regression (MLR)) confirmed the credibility of this research.