Stimulated leaching of metalloids along 3D-printed fractured rock vadose zone

A Critical Review of Groundwater Table Fluctuation: Formation, Effects on Multifields, and Contaminant Behaviors in a Soil and Aquifer System

The groundwater table fluctuation (GTF) zone is an important medium for the hydrologic cycle between unsaturated soil and saturated aquifers, which accelerates the migration, transformation, and redistribution of contaminants and further poses a potential environmental risk to humans. In this review, we clarify the key processes in the generation of the GTF zone and examine its links with the variation of the hydrodynamic and hydrochemistry field, colloid mobilization, and contaminant migration and transformation. Driven by groundwater recharge and discharge, GTF regulates water flow and the movement of the capillary fringe, which further control the advection and dispersion of contaminants in soil and groundwater. In addition, the formation and variation of the reactive oxygen species (ROS) waterfall are impacted by GTF. The changing ROS components partially determine the characteristic transformation of solutes and the dynamic redistribution of the microbial population. GTF facilitates the migration and transformation of contaminants (such as nitrogen, heavy metals, non-aqueous phase liquids, and volatile organic compounds) through colloid mobilization, the co-migration effect, and variation of the hydrodynamic and hydrochemistry fields. In conclusion, this review illustrates the limitations of the current literature on GTF, and the significance of GTF zones in the underground environment is underscored by expounding on the future directions and prospects.

Unraveling the aging dynamics in the simultaneous immobilization of soil metal(loid)s using oxides

Immobilization represents the most extensively utilized technique for the remediation of soils contaminated by heavy metals and metalloids. However, it is crucial to acknowledge that contaminants are not removed during this process, thereby leaving room for potential mobilization over time. Currently, our comprehension of the temporal variations in immobilization efficacy, specifically in relation to amendments suitable for industrial sites, remains very limited. To address this knowledge gap, our research delved into the aging characteristics of diverse oxides, hydroxides, and hydroxy-oxides (collectively referred to as oxides) for the simultaneous immobilization of arsenic (As), cadmium (Cd), and antimony (Sb) in soils procured from 16 contaminated industrial sites. Our findings unveiled that Ca-oxides initially showed excellent immobilization performance for As and Sb within 7 days but experienced substantial mobilization by up to 71 and 13 times within 1 year, respectively. In contrast, the efficacy of Cd immobilization by Ca-oxides was enhanced with the passage of time. Fe- and Mg-oxides, which primarily operate through encapsulation or surface complexation, exhibited steady immobilization performances over time. This reliable and commendable immobilization effect was observed across distinct soils characterized by varying physicochemical properties, including pH, texture, CEC, TOC, and EC, underscoring the suitability of such amendments for immobilizing metal(loid)s in diverse soil types. MgO, in particular, displayed even superior immobilization performance over time, owing primarily to gradual hydration and physical entrapment effects. Remarkably, Mg-Al LDHs emerged as the most effective candidate for the simultaneous immobilization of As, Cd, and Sb. The results obtained from this study furnish valuable data for future investigations on the immobilization of metals and metalloids in industrial soils. They enable the projection of immobilization performance and offer practical guidance in selecting suitable amendments for the immobilization of metal(loid)s.

Multi-technological integration in a smelting site: Visualizing pollution characteristics and migration pattern

Heavy metal(loid)s pollution of industrial legacies has become a severe environmental issue worldwide. Linking soil pollution to groundwater contaminant plumes would make invisible pollution features visible across the site, but related studies are lacking and require the convergence of multiple technologies. This study uniformly managed the soil and groundwater data in a 3D visualization model to pellucidly assess the spatial distribution of critical contaminants beyond simple drilling information. The distribution of Pb, Zn, As, and Cd in soil-groundwater system has a strong correlation to historical production, substance type, soil property, and groundwater flow direction. Over 2600 measurements of High-density electrical resistivity tomography (ERT) data were used to guarantee the exactness of soil structures. Hydraulic conductivity showed a strongest correlation (R2 = 0.86), yielding a calibrated model to reveal the anisotropic and contaminant transport in the region, with the consequent minimize the drilling tests. This study provides a template for the description of a verifiable scenario of hydrogeological conditions and pollution characteristics at smelting sites, coupled with traditional exploration and non-invasive techniques. The findings highlight the significance of visualizing the internal state of the soil-groundwater system under consideration, thus providing a basis for targeted control measures against site contamination.

Heavy metal pollution in Mongolian-Manchurian grassland soil and effect of long-range dust transport by wind

Grasslands provide a range of valuable ecosystem services, but they are also particularly fragile ecosystems easily threatened by human activities, such as long-term open-pit mining and related industrial activities. In grassland area, dust containing heavy metal(loid)s generated by mines may further migrate to remote places, but few studies have focused on the long-range transport of contaminants as an important pollution source. In the present study, one of the largest and most intact grassland ecosystems, the Mongolian-Manchurian steppe, was selected to investigate its pollution status and track potential sources. A total of 150 soil samples were collected to explore reginal distribution of nine heavy metal(loid)s that has potential risk in grassland. We conducted a combined multi-variant analysis of positive matrix factorization (PMF) and machine learning, which foregrounded the source of long-range transport of contaminants and inspired the hypothesis of a novel stochastic model to describe contaminants distribution. Results showed four different sources accounting for 44.44% (parent material), 20.28% (atmospheric deposition), 20.39% (farming), and 14.89% (transportation) of the total concentration, respectively. Factor 2 indicated that coal surface mining lead to a significant enrichment of As and Se with their concentration far above the global average level, which was different from other reported grassland areas. Machine learning results further confirmed that atmospheric and topographic features were their contamination controlling factors. The model results proposed that As, Se and Cu released by surface mining will be transported over long distance under prevailing monsoon, until finally deposited in the windward slope of mountain due to terrain obstruction. The long-range transport by wind and deposition of contaminants may be a prevailing phenomenon in temperate grassland, making it a pollution source that cannot be ignored. Evidence from this study reveals the urgency of precautions for fragile grassland ecosystems around industrial areas and provides a basis for its management and risk control policies.