Fate and transport of chromium in industrial sites: Dynamic simulation on soil profile

Spatial distribution and migration characteristics of heavy metals at an abandoned industrial site in the Southwest of China

The rapid acceleration of global industrialization has rendered heavy metal contamination at abandoned industrial sites a severe challenge, particularly in geologically complex and fragile karst regions of Southwest China, posing significant threats to ecosystems and public health. However, existing research lacks a comprehensive understanding of the spatial distribution and migration mechanisms of heavy metals in this region. In this study, 523 soil samples and 30 groundwater samples were collected, and the pollution levels were systematically assessed using the Geo-Accumulation Index, Single Pollution Index, and Nemerow Integrated Pollution Index. Horizontal and vertical spatial heterogeneity was explored through Moran's I and Voronoi polygon analysis. Furthermore, 3D geological modeling and groundwater flow simulations were employed to investigate the influence of hydrogeological conditions on contaminant migration. The results indicate elevated concentrations of Cd, Hg, Pb, and As in the surface layer, with concentrations initially decreasing and then increasing with depth, likely due to the presence of discontinuous clay layers. Moran's I revealed significant clustering effects at depths of 0.2 m and 4 m, while Voronoi analysis confirmed vertical heterogeneity. This study provides a scientific basis for pollution assessment and targeted remediation in karst regions.

Simultaneously mapping the 3D distributions of multiple heavy metals in an industrial site using deep learning and multisource auxiliary data

Three-dimensional (3D) distributions of multiple soil pollutants in industrial site are crucial for risk assessment and remediation. Yet, their 3D prediction accuracies are often low because of the strong variability of pollutants and availability of 3D covariate data. This study proposed a patch-based multi-task convolution neural network (MT-CNN) model for simultaneously predicting the 3D distributions of Zn, Pb, Ni, and Cu at an industrial site. By integrating neighborhood patches from multisource covariates, the MT-CNN model captured both horizontal and vertical pollution information, and outperformed the widely-used methods such as random forest (RF), ordinary Kriging (OK), and inverse distance weighting (IDW) for all the 4 heavy metals, with R2 values of 0.58, 0.56, 0.29 and 0.23 for Zn, Pb, Ni and Cu, respectively. Besides, the MT-CNN model achieved more stable predictions with reasonable accuracy, in comparison with the single-task CNN model. These results highlighted the potential of the proposed MT-CNN in simultaneously mapping the 3D distributions of multiple pollutants, while balancing the model training, maintaining and accuracy for low-cost rapid assessment of soil pollution at industrial sites.

Distribution, assessment, and causality analysis of soil heavy metals pollution in complex contaminated sites: a case study of a chemical plant

To effectively prevent and control pollution from heavy metals (HMs) in urban soils, it is essential to thoroughly understand the contamination status of contaminated sites. In this study, the contamination status and sources of six HMs (As, Cu, Cr, Ni, Pb, Cd) in the soil of a decommissioned chemical plant in southern China were comprehensively analyzed. The results indicated that the average concentration of HMs followed the sequence: Cr > Pb > Cu > Ni > As > Cd. Heavy metal accumulation in the upper soil layer was predominantly observed in industrial zones and low-lying areas, with notable variations in concentration along the vertical profile. Certain sections of the site exhibited severe HM contamination, particularly with Cu levels exceeding the background value by 46.77 times. Cd presented significant ecological risks in specific areas, with an average Ecological Index of 96.09. Carcinogenic and non-carcinogenic risks were identified at three and six sampling points, respectively, with sampling point S103 demonstrating both types of risks. The causes of HM contamination were primarily attributed to anthropogenic activities. Horizontal dispersion was mainly influenced by production operations and topographical features, while vertical distribution was predominantly affected by the permeability characteristics of the strata. The causality analysis incorporating production activities and topographical factors provides novel perspectives for understanding sources of contamination at contaminated sites. The study outcomes can offer guidance for the assessment and surveying of urban industrial pollution sites.

Highly alkaline electrokinetic extraction: Characteristics of chromium mobilization, conversion and transport in high alkalinity soil

In site chromium (Cr) contaminated soil characterized by high alkalinity and carbonate content, protons are not effectively targeted for Cr(III) mobilization but rather accelerate the reduction of easily transportable Cr(VI) within the acidification electrokinetic (EK) system. As an alternative, the highly alkaline extraction conditions (HAECs) maintained by anolyte regulation are explored owing to the ability to desorb strong binding Cr(VI) and form anionic Cr(III)-hydroxides (Cr(OH)4-, Cr(OH)52-). The results demonstrate that HAECs were more efficient in mobilizing ions in severe alkalinity and electrical conductivity soil compared to organic acid acidifying extraction conditions (OAECs). Simultaneously, a limited amount of soluble Cr(III) was produced; however, its transportation was hindered and more noticeable in the case of Cr(VI), displaying a distinct retention phase within the intermediate soil chamber. The antagonistic interplay between electromigration and electroosmotic flow was considered the main responsible factor. The conversion intensity of Cr(VI) to Cr(III) was inhibited at HAECs. The promising mobilization and low conversion intensity contributed to total Cr removal. At HAECs, enhanced electromigration and electroosmotic flow combined with a favorable oxidation environment may facilitate in situ delivery of oxidants, offering practical implications for the EK detoxification of high alkalinity site soil contaminated with Cr. The practicability of HAECs is likely to be enhanced when the cost-benefit balance of providing a simultaneous energy supply during site treatment is resolved.

Simulation of vertical migration behaviors of heavy metals in polluted soils from arid regions in northern China under extreme weather

Heavy metal migration behaviors and mechanisms in soils are important for pollution control and remediation. However, there are few related studies in arid areas under extreme weather patterns. In this study, we developed a one-dimensional continuous point source unsaturated solute transport model, and utilized Hydrus-1D to simulate the transport of Cu, As and Zn, in the pack gas zones of soils within the impact areas of two typical mining areas in Inner Mongolia. The results show that the soil has a significant interception capacity, with a short heavy metal vertical migration distance of ≤100 cm. Soil texture and heavy metal sorption affinity are two key factors that influence heavy metal transport. In soils with high contents of sands but low contents of clays, heavy metals have large mobility and thus migrate deeper and are more evenly distributed in the soil profile. The migration of different heavy metals in the same soil also varies considerably, with large migration depth for metals having low binding affinities onto soils. Scenario analysis for extreme drought and rainfall shows that, rainfall amount and intensity are positively correlated with heavy metal transport depth and negatively correlated with the peak concentration. Increasing rainfall/intensity results in a more uniform distribution of heavy metals, and lower profile concentrations owing to enhanced horizontal dispersion of surface runoff. When the total amount and intensity of rainfall remain constant, continuous or intermittent rainfall only affects the transport process but has almost no effect on the final pollutant concentration redistribution in the soil. These results provide theoretical data for estimating the degree of heavy metal pollution, and help design control and remediation strategies for polluted soils.

Spatial distribution, chemical fractionation and risk assessment of Cr in soil from a typical industry smelting site in Hunan Province, China

The closure or relocation of many industrial enterprises has resulted in a significant number of abandoned polluted sites enriched in heavy metals to various degrees, causing a slew of environmental problems. Therefore, it is essential to conduct research on heavy metal contamination in the soil of industrial abandoned sites. In this study, soils at different depths were collected in a smelting site located in Hunan Province, China, to understand the Cr distribution, speciation and possible risks. The results revealed that the high-content Cr and Cr(VI) contamination centers were mainly concentrated near S1 (Sample site 1) and S5. The longitudinal migration law of chromium was relatively complex, not showing a simply uniform trend of decreasing gradually with depth but presenting a certain volatility. The vertical distribution characteristics of chromium and Cr(VI) pollution suggest the need for attention to the pollution from chromium slag in groundwater and deep soil layers. The results of different speciation of Cr extracted by the modified European Community Bureau of Reference (BCR) method showed that Cr existed primarily in the residual state (F4), with a relatively low content in the weak acid extraction state (F1). The correlation analysis indicated that Cr was affected by total Cr, pH, organic matter and total carbon during the longitudinal migration process. The RSP results revealed that the smelting site as a whole had a moderate level of pollution. Soil at depths of 2-5 m was more polluted than other soil layers. Consequently, it is necessary to treat the site soil as a whole, especially the subsoil layer (2-5 m). Health risk assessment demonstrated that the soil chromium pollution was hazardous to both adults and children, and the probability of carcinogenic and non-carcinogenic risk was relatively high in the latter group. As a result, children should be a group of special concern regarding the assessment and remediation of soil contaminated with Cr. This study can provide some insight into the contamination characteristics, ecological and health risks of chromium in contaminated soils and offer a scientific basis for the prevention and control of chromium pollution at abandoned smelting sites.

Comprehensive distribution characteristics and factors affecting the migration of chromium in a typical chromium slag-contaminated site with a long history in China

The contamination of abandoned chromium slag-contaminated sites poses serious threats to human health and the environment. Therefore, improving the understanding of their distribution characteristics and health risks by multiple information is necessary. This study explored the distribution, accumulation characteristic, and the role in the migration process of chromium. The results showed that the contents of total Cr and Cr (VI) ranged from 12.00 to 7400.00 mg/kg, and 0.25 to 2160.00 mg/kg, respectively. The average contents of both total Cr and Cr (VI) reached the highest value at the depth of 7-9 m, where the silt layer retaining total Cr and Cr (VI) was. The spatial distribution analysis revealed that the total contamination area percentages of total Cr and Cr (VI) reached 7.87% and 90.02% in the mixed fill layer, and reduced to 1.21% and 34.53% in the silty layer, and the same heavily polluted areas were located in the open chromium residue storage. Soil pH and moisture content were the major factors controlling the migration of total Cr and Cr(VI) in soils. Results of probabilistic health risk assessment revealed that carcinogenic risk was negligible for adults and children, and the sensitive analysis implied that the content of Cr(VI) was the predominant contributor to carcinogenic risk. The combination of chemical reduction and microbial remediation could be the feasible remediation strategy for soil Cr(VI) pollution. Overall, this study provides scientific information into the chromium post-remediation and pollution management for various similar chromium-contaminated sites.

Utilizing machine learning algorithm for finely three-dimensional delineation of soil-groundwater contamination in a typical industrial park, North China: Importance of multisource auxiliary data

Intensive industrial activities cause soil contamination with wide variations and even perturb groundwater safety. Precision delineation of soil contamination is the foundation and precondition for soil quality assurance in the practical environmental management process. However, spatial non-stationarity phenomenon of soil contamination and heterogeneous sampling are two key issues that affect the accuracy of contamination delineation model. Taking a typical industrial park in North China as the research object, we constructed a random forest (RF) model for finely characterizing the distribution of soil contaminants using sparse-biased drilling data. Results showed that the R2 values of arsenic and 1,2-dichloroethane predicted by RF (0.8896 and 0.8973) were greatly higher than those of inverse distance weighted model (0.2848 and 0.2908), indicating that RF was more adaptable to actual non-stationarity sites. The back propagation neural network algorithm was utilized to establish a three-dimensional visualization of the contamination parcel of subsoil-groundwater system. Multiple sources of environmental data, including hydrogeological conditions, geochemical characteristics and anthropogenic industrial activities were integrated into the model to optimize the prediction accuracy. The feature importance analysis revealed that soil particle size was dominant for the migration of arsenic, while the migration of 1,2-dichloroethane highly depended on vertical permeability coefficients of the soil. Contaminants migrated downwards with soil water under gravity-driven conditions and penetrated through the subsoil to reach the saturated aquifer, forming a contamination plume with groundwater flow. Our findings afford a new idea for spatial analysis of soil-groundwater contamination at industrial sites, which will provide valuable technical support for maintaining sustainable industry.

Source apportionment and migration characteristics of heavy metal(loid)s in soil and groundwater of contaminated site

The rapid industrial growth has generated heavy metal(loid)s contamination in the soil, which poses a serious threat to the ecology and human health. In this study, 580 samples were collected in Henan Province, China, for source apportionment, migration characterization and health risk evaluation using self-organizing map, positive matrix factorization and multivariate risk assessment methods. The results showed that samples were classified into four groups and pollution sources included chromium slag dump, soil parent rock and abandoned factory. The contents of Cr, Pb, As and Hg were low in Group 1. Group 2 was characterized by total Cr, Cr(Ⅵ) and pH. The enrichment of total Cr and Cr(Ⅵ) in soil was mainly attributed to chromium slag dump, accounting for more than 84.0%. Group 3 was dominated by Hg and Pb. Hg and Pb were primarily attributed to abandoned factory, accounting for 84.7% and 70.0%, respectively. Group 4 was characterized by As. The occurrence of As was not limited to one individual region. The contribution of soil parent rock reached 83.0%. Furthermore, the vertical migration of As, Hg, Pb and Cr(Ⅵ) in soil was mainly influenced by medium permeability, pH and organic matter content. The trends of As, Pb, and Hg with depth were basically consistent with the trends of organic matter with depth, and were negatively correlated with the change in pH with depth. The trends of Cr(Ⅵ) with depth were basically consistent with the changes in pH with the depth. The content of Cr(Ⅵ) in the deep soil did not exceed the detection limits and Cr(Ⅵ) contamination occurred in the deep aquifer, suggesting that Cr(Ⅵ) in the deep groundwater originated from the leakage of shallow groundwater. The assessment indicated that the non-carcinogenic and carcinogenic risks for children and adults could not be neglected. Moreover, children were more susceptible than adults.

Analysis of soil pollution characteristics and influencing factors based on ten electroplating enterprises

The electroplating industry encompasses various processes and plating types that contribute to environmental pollution, which has led to growing public concern. To investigate related soil pollution in China, the study selected 10 sites with diverse industrial characteristics distributed across China and collected 1052 soil samples to determine the presence of industrial priority pollutants (PP) based on production process and pollutant toxicity. The factors influencing site pollution as well as proposed pollution prevention and control approaches were then evaluated. The results indicate the presence of significant pollution in the electroplating industry, with ten constituents surpassing the risk screening values (RSV). The identified PP consist of Cr(VI), zinc (Zn), nickel (Ni), total chromium (Cr), and petroleum hydrocarbons (C10-C40). PP contamination was primarily observed in production areas, liquid storage facilities, and solid zones. The vertical distribution of metal pollutants decreased with soil depth, whereas the reverse was true for petroleum hydrocarbons (C10-C40). Increase in site production time was strongly correlated with soil pollution, but strengthening anti-seepage measures in key areas can effectively reduce the soil exceedance standard ratio. This study serves as a foundation for conceptualizing site repair technology in the electroplating industry and offers a reference and methodology for pollution and source control in this and related sectors.