Pollution simulation and remediation strategy of a zinc smelting site based on multi-source information

Characterization of Cd transport in a typical Tibetan Plateau watershed and an analysis of its climatic drivers

Under the current global climate change background, the response of soil heavy metals in the Qinghai Tibet Plateau basin to the intensification of climate change is still unclear, leading to the intensification of heavy metal migration in the watershed. We selected cadmium (Cd) in soils of the Taohe River Basin on the Tibetan Plateau as the study object, and established a heavy metal migration simulation model based on the Soil and Water Assessment Tool (SWAT) to estimate the impact of climate change on Cd migration in the basin. The results indicated that the drought indexes and precipitation were the main determinants of the changes in Cd migration in the basin. The multi-scale drought indexes indicated that the optimal time scale for evaluating the effect of drought on Cd migration in the watershed was 3 months. Higher migration rates were apparent in summer and autumn (wet season) than in winter and spring (dry season). Spring precipitation was significantly and positively correlated with the migration of elemental Cd, and the Standardized Precipitation Index (SPI) 3 drought index was significantly and positively correlated with Cd migration in summer, autumn, and winter. For every 5 % increase in precipitation, Cd migration rates increased by 3.55 %, 0.46 %, 0.15 %, and 0.12 % in spring, summer, autumn, and winter, respectively. For every 5 % decrease in precipitation, Cd migration rates decreased by 0.11 %, 0.12 %, 0.14 %, and 0.13 % in spring, summer, autumn, and winter, respectively. The risk of Cd transport in soil continues to increase under future climate change scenarios.

Anthropogenic impacts on regional leaching risks posed by trace metal(loid)s in the soil of an industrial city

The leaching risks associated with trace metal(loid)s (s) in regional soil are complex due to the intricate interplay between pollution levels and soil properties. A Kd-based regional leaching risk assessment method was developed to assess the leaching risks posed by soil TMs. The random forest model was used to identify the effects of the soil environment on the soil Kd and the leaching risks. The reliability of the established method was successfully validated by field monitoring data (R2 = 0.84). The mean total soil groundwater risk was 1.59, the high mobility of Cd contributed the most to total risks. High-risk areas were mainly located in the farmland and forestland around a smelter and areas with severe soil acidification. The high mobility and moderate contamination of TMs resulted in the highest leaching risks. Furthermore, soil acidification and the conversion of farmland to forestland would increase the leaching risk by 33.5 % and 46.4 %, respectively, while urban expansion would reduce the leaching risk by 60.3 %. The Kd-based leaching risk assessment method provided a critical framework for decision-makers to efficiently identify high-risk areas on a regional scale, facilitating a deeper understanding of how anthropogenic activities influenced the leaching risks of TMs in soil.

Simultaneous stabilization of cadmium and arsenic in soil by humic acid and mechanically activated phosphate rock

Competition between phosphorus and arsenic limits the application of phosphate materials in soil remediation. However, it is possible to simultaneously stabilize arsenic and cationic metals by sensible use of phosphate's solubility. In this study, ball-milling and humic acid (HA) activated phosphate rock (PR) were used to stabilize cadmium (Cd) and arsenic (As) in soil. After 30 days of treatment with ball-milling and 5 % humic acid-activated phosphate rock (BMP-HA), the leaching concentrations of Cd and As in the soil decreased from 0.12 mg/L and 0.11 mg/L to 0.0086 mg/L and 0.019 mg/L, respectively. The availability of Cd and As was significantly reduced after BMP-HA treatment. The acid-soluble fraction of Cd decreased from 16.30 % to 1.22 %, indicating its transformation into more stable forms. The water-soluble and surface-adsorbed fraction of As decreased to 0.11 %, while the Ca-associated fraction of As increased from 25.87 % to 31.41 %. Ball-milling increased the specific surface area of PR, enhancing the adsorption and surface complexation of Cd. The addition of humic acid facilitated the dissolution of PR. However, the phosphate release rate in BMP-HA was insufficient to activate As. Meanwhile, the released Ca bound with As, further reducing its availability. Overall, BMP-HA proves to be an effective strategy for remediating cadmium and arsenic-contaminated soils.

Enhanced immobilization mechanisms and transport of simulated acid rain on chromium in contaminated soil mixed with nZVI/Ni

Nano zero-valent iron/nickel (nZVI/Ni) was produced using liquid phase reduction method and characterized by SEM and XRD. In this study, the effect of dose of nZVI/Ni, pH value of acid rain, mixing method of nZVI/Ni by simulating rainfall leaching experiments in the soil column uniformly mixed with nZVI/Ni was studied. The concentration of Cr(VI), pH, conductivity and cumulative release of the leaching solution were measured. The convective dispersion equation model was successfully used to explain the transport behavior of nZVI/Ni in chromium contaminated soil mixed with nZVI/Ni. The speciation of Cr(VI) in the soil after leaching was determined by BCR continuous extraction method. The effect of nZVI/Ni application on the speciation of Cr(VI) in the soil was analyzed. Results showed that the best fixation efficiency was achieved when the nZVI/Ni dosage was 0.10% (w/w%) and pH of the simulated acid rain was 4.5. Pseudo-second-order kinetics characterizes the Cr elimination process better (R2 > 0.99), suggesting that nZVI/Ni predominantly extracts Cr (VI) from polluted soil under acid rain leaching through chemical adsorption/desorption mechanisms. The entire adsorption process included surface diffusion, mesopore diffusion and micropore diffusion. Acid extractable and reduced chromium decreased from 30 to 9%. Oxidizable and residual chromium increased from 70 to 91% in the remediated soil. Cr(VI) in the soil can be reduced Cr (VI) to Cr (III) by nZVI/Ni in the presence of acid rain. The concentrations of Cr leached from the soil by TCLP, SPLP, and SBET methods were 0.11, 0.034 and 0.028 mg/L, which were lower than the standards. There are no obvious differences among the rapeseed stem, root lengths, seed germination rate and clean soil in the remediated soil. nZVI/Ni demonstrated superior treatment of real chromium polluted soil under acid rain. The theoretical foundation and scientific references for treating Cr (VI) polluted soil under acid rain is provided by this study.

Predicting cobalt ion concentration in hydrometallurgy zinc process using data decomposition and machine learning

Solid waste is one of the primary contributors to environmental pollution currently, it is crucial to enhance the prevention and control of solid waste pollution in environmental management. The effectiveness of the second stage of purification in the industrial zinc hydrometallurgy is determined by the concentration of cobalt ion. Manual testing and monitoring of cobalt ion concentration are time consuming and costly, and prone to delays, which can result in discharge of cobalt ion concentration that does not meet the standards, leading to water pollution. Additionally, over-addition of zinc powder leads to a waste of resources, increasing the production cost of the company. Here, this work proposes a hybrid prediction model that combines the advantages of data decomposition and machine learning algorithms to predict the metal cobalt ion concentration in the effluent solution of a section of zinc hydrometallurgy refining purification in factory A. According to the different types of experiments, ablation experiments and contrast experiments are designed in this work under the same training and test data were used in the modeling process. Analytic and experimental results show that the proposed hybrid prediction model has the smallest error and the best fit between the actual and predicted values of cobalt ion concentration, and the appropriate graphs were finally selected for quantitative metrics analysis. The root mean square error was reduced by 4.2 %-73.9 %, the mean absolute error by 7.1 %-93.4 %, the mean percentage error by 7.7 %-86.7 % and the coefficient of determination by 1.3 %-134.6 %. The hybrid prediction model not only avoided the pollution of water resources by the cobalt ion concentration discharged in the purification, which is also of practical significance for the technicians to control the input quantity of zinc powder according to the prediction data in time and reduce the waste of resources.

Development and mechanistic study of phosphate tailings based soil heavy metal prophylactic agents with encapsulated structure for lead stabilization and phosphorus speciation in soils

The development of materials for the remediation of the environment from solid waste represents an effective utilization strategy. This study presents a novel phosphorus-based slow-release soil agent (SLPs) developed through acid activation of phosphorus tailings. SLPs aim to improve soil properties by gradually releasing phosphorus (P), reducing Pb mobility, and preventing heavy metal contamination. SLPs were synthesized by forming an encapsulated structure via calcification of sodium alginate with calcium (Ca2⁺) and magnesium (Mg2⁺) from the tailings, achieving controlled P release. In soil, SLPs increased P content from 0.23 mg/g to 2.53 mg/g and soil organic matter (SOM) from 8.6 g/kg to 40.19 g/kg, significantly enhancing humic acid, fulvic acid, and organic phosphorus (OP) levels. ESP treatment also shifted the soil P pool, increasing apatite inorganic phosphate (AP) from 0.04 mg/g to 0.16 mg/g, non-apatite inorganic phosphate (NAIP) from 0.12 mg/g to 1.48 mg/g, and OP from 0.05 mg/g to 0.67 mg/g, with OP reaching a peak proportion of 28.55%, up from 23.48% in controls. Correlation analysis and microbial pathway data indicate that OP and microbial communities contribute to Pb stabilization in ESP-treated soil, raising soil Pb stabilization capacity from 7.6 to 8.4 mg/g to 36.2 mg/g. This study highlights a sustainable path for phosphorus tailing use, providing theoretical support for SLP development and emphasizing the role of OP in Pb stabilization.

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.

A meta-analysis of influencing factors on soil pollution around copper smelting sites

Non-ferrous smelting activities have caused serious heavy metal(loid) pollution in soil which seriously threatens human health globally. A number of studies have been conducted to assess the characteristics and risks of soil heavy metal(loid) pollution around copper (Cu) smelting sites. However, the current research mainly focuses on soil pollution around a single smelter, and the global impact of Cu smelting on soil and its quantitative relationship with related factors need to be further studied. Meta-analysis can integrate a large amount of data and quantitatively analyze the relationship between multiple factors. To investigate the extent to which Cu smelting sites have contributed to heavy metal(loid) pollution in soils, a meta-analysis was conducted on 189 research publications from 1993 to 2023. Furthermore, a single meta regression was used to analyze the relationship between the soil heavy metal(loid)s (HMs) and influencing factors on a global scale. The results of meta-regression analysis showed that compared with the soil background value, Cu smelting significantly increased the concentration of HMs in soil (315%), with the concentration increase for each heavy metal(loid) being: Cu (1012%) > Cd (622%) > As (315%) > Pb (277%) > Zn (188%) > Cr (96%) > Ni (95%) > Mn (45%). Among these, Cu, Cd, and As were the major pollutants in soils around Cu smelting sites. Land use type was a key factor affecting HMs concentrations in surrounding soils, and the influence of non-agricultural land (381%) was greater than that of agricultural land (203%). In addition, the influence of Cu smelting on HMs were negatively correlated with distance (QM=9.86) and positively correlated with latitude (QM=10.7). There was no significant correlation between heavy metal(loid) pollution and soil chemical properties, average annual rainfall and temperature, longitude, or other factors. Our work may be meaningful to the risk control and remediation for Cu smelting sites.

Pollution characteristics and quantitative source apportionment of heavy metals within a zinc smelting site by GIS-based PMF and APCS-MLR models

The abandoned smelters present a substantial pollution threat to the nearby soil and groundwater. In this study, 63 surface soil samples were collected from a zinc smelter to quantitatively describe the pollution characteristics, ecological risks, and source apportionment of heavy metal(loid)s (HMs). The results revealed that the average contents of Zn, Cd, Pb, As, and Hg were 0.4, 12.2, 3.3, 5.3, and 12.7 times higher than the risk screening values of the construction sites, respectively. Notably, the smelter was accumulated heavily with Cd and Hg, and the contribution of Cd (0.38) and Hg (0.53) to ecological risk was 91.58%. ZZ3 and ZZ7 were the most polluted workshops, accounting for 25.7% and 35.0% of the pollution load and ecological risk, respectively. The influence of soil parent materials on pollution was minor compared to various workshops within the smelter. Combined with PMF, APCS-MLR and GIS analysis, four sources of HMs were identified: P1(25.5%) and A3(18.4%) were atmospheric deposition from the electric defogging workshop and surface runoff from the smelter; P2(32.7%) and A2(20.9%) were surface runoff of As-Pb foul acid; P3(14.5%) and A4(49.8%) were atmospheric deposition from the leach slag drying workshop; P4(27.3%) and A1(10.8%) were the smelting process of zinc products. This paper described the distribution characteristics and specific sources of HMs in different process workshops, providing a new perspective for the precise remediation of the smelter by determining the priority control factors.

Prediction of heavy metal ion distribution and Pb and Zn ion concentrations in the tailing pond area

The pollution caused by tailings ponds has resulted in ecological damage, with soil contamination significantly impacting the daily lives of residents in the vicinity of mining areas and the future development of mining areas. This study assesses the transport status of heavy metal pollution in tailings areas and predicts its impact on future pollution levels. This study focused on lead-zinc tailing ponds, exploring the spatial and chemical distribution characteristics of heavy metals based on the distributions of Pb, Zn, As, Cu, Cr, Cd, Hg, and Ge ions. The concentrations of the major heavy metal ions Pb and Zn in tailings ponds were predicted via the exponential smoothing method. ① The total accumulation of Pb and Zn in the mine tailings ranges from 936.74~1212.61 mg/kg and 1611.85~2191.47 mg/kg, much greater than the total accumulation of the remaining six heavy metals. The total accumulation of associated heavy metal Cu was high, and the lowest total heavy metals were Hg and Ge at only 0.19 mg/kg and 1.05 mg/kg. ② The analyses of soil heavy metal chemical forms reveal that the heavy metals Pb and Zn had the highest exchangeable state content and state ratio and the strongest transport activity in the industrial plaza and village soils. Pb and Zn are the heavy metals with the greatest eco-environmental impacts in the mining area. ③ The predicted results show that the soil concentrations of the heavy metals Pb and Zn around the tailings area in 2026 are 1.335 and 1.191 times the predicted time starting values. The concentrations of the heavy metals Pb and Zn at the starting point of the forecast are already 3.34 and 3.02 times the upper limits of the environmental standard (according to environmental standards for gravelly grey calcium soils). These results have significant implications for heavy metal pollution risk management.

Polymetallic contamination drives indigenous microbial community assembly dominated by stochastic processes at Pb-Zn smelting sites

Indigenous microbial communities in smelting areas are crucial for maintaining fragile ecosystem functions. However, the community assembly process and their responses to polymetallic pollution are poorly understood, especially the taxa in each bin from the amplicons that contributed to the assembly process. Herein, microbial diversity, co-occurrence patterns, assembly process and the intrinsic mechanisms across contamination gradients at a typical PbZn smelting site were systematically unravelled by high-throughput sequencing. The results showed a consistent compositional profile among the indigenous communities across sampling sites, wherein genera KD4-96 from Chloroflexi and Sphingomonas from Proteobacteria emerged as the most abundant taxa. Network modularity of the high- and middle-contaminated communities at Pb and Zn smelting sites was >0.44, indicating that community populations were clustered into modules to resist high heavy metal stress. Stochastic processes dominated the community assembly, with the greatest contribution from drift (DR), which was significantly correlated with Pb, Zn, Cr and Cu contents. What's particular was that the DR-controlled bins were dominated by Proteobacteria (typical r-strategists), while the HoS-controlled bins were by Chloroflexi (typical K-strategists). Furthermore, the proportion of DR in the bins dominated by Sphingomonadaceae (phylum Proteobacteria) increased gradually with the increase of heavy metal contents. These discoveries provide essential insights for community control in restoring and mitigating soil degradation at PbZn smelting sites.

Integrated framework to assess soil potentially toxic element contamination through 3D pollution analysis in a typical mining city

Soil potentially toxic elements (PTEs) pollution of contaminated sites has become a global environmental issue. However, given that previous studies mostly focused on pollution assessment in surface soils, the current status and environmental risks of potentially toxic elements in deeper soils remain unclear. The present study aims to cognize distribution characteristics and spatial autocorrelation, pollution levels, and risk assessment in a stereoscopic environment for soil PTEs through 3D visualization techniques. Pollution levels were assessed in an integrated manner by combining the geoaccumulation index (Igeo), the integrated influence index of soil quality (IICQs), and potential ecological hazard index. Results showed that soil environment at the site was seriously threatened by PTEs, and Cu and Cd were ubiquitous and the predominant pollutants in the study area. The stratigraphic models and pollution plume simulation revealed that pollutants show a decreasing trend with the deepening of the soil layer. The ranking of contamination soil volume is as follows: Cu > Cd > Zn > As > Pb > Cr > Ni. According to the IICQs evaluation, this region was subject to multiple PTE contamination, with more than 60% of the area becoming seriously and highly polluted. In addition, the ecological hazard model revealed the existence of substantial ecological hazards in the soils of the site. The integrated potential ecological risk index (RI) indicated that 45.7%, 10.13%, and 4.15% of the stereoscopic areas were in considerable, high, and very high risks, respectively. The findings could be used as a theoretical reference for applying multiple methods to integrate evaluation through 3D visualization analysis in the assessment and remediation of PTE-contaminated soils.

Driving factors for distribution and transformation of heavy metals speciation in a zinc smelting site

Heavy metal pollution at an abandoned smelter pose a significant risk to environmental health. However, remediation strategies are constrained by inadequate knowledge of the polymetallic distribution, speciation patterns, and transformation factors at these sites. This study investigates the influence of soil minerals, heavy metal occurrence forms, and environmental factors on heavy metal migration behaviors and speciation transformations. X-ray diffraction analysis revealed that the minerals associated with heavy metals are mainly hematite, franklinite, sphalerite, and galena. Sequential extraction results suggest that lead and zinc are primarily present in the organic-sulfide fractions (F4) and residual form (F5) in the soil, accounting for over 70% of the total heavy metal content. Zinc displayed greater instability in carbonate-bound (16%) and exchangeable (2%) forms. The migration and diffusion patterns of heavy metals in the subsurface environment were visualized through the simulation of labile state heavy metals, demonstrating high congruence with groundwater pollution distribution patterns. The key environmental factors influencing heavy metal stable states (F4 and F5) were assessed by integrating random forest models and redundancy analysis. Primary factors facilitating Pb transformation into stable states were available phosphorus, clay content, depth, and soil organic matter. For Zn, the principal drivers were Mn oxides, soil organic matter, clay content, and inorganic sulfur ions. These findings enhance understanding of the distribution and transformation of heavy metal speciation and can provide valuable insights into controlling heavy metal pollution at non-ferrous smelting sites.

Antimony and arsenic migration in a heterogeneous subsurface at an abandoned antimony smelter under rainfall

While antimony (Sb) and arsenic (As) co-contamination in subsurface soil systems due to the legacy of Sb smelting wastes has been documented, the role of inherent heterogeneity on pollutant migration is largely overlooked. Herein this study investigated Sb and As migration in a slag impacted, vertically stratified subsurface at an abandoned Sb smelter. A 2-dimensional flume was assembled as a lab-scale analogue of the site and subject to rainfall and stop-rain events. Reactive transport modeling was then performed by matching the experimental observations to verify the key factors and processes controlling pollutant migration. Results showed that rainfall caused Sb and As release from the shallow slag layer and promoted their downward movement. Nevertheless, the less permeable deeper layers limited physical flow and transport, which led to Sb and As accumulation at the interface. The re-adsorption of Sb and As onto iron oxides in the deeper, more acidic layers further retarded their migration. Because of the large difference between Sb and As concentrations, Sb re-adsorption was much less effective, which led to higher mobility. Our findings overall highlight the necessity of understanding the degree and impacts of physicochemical heterogeneity for risk exposure assessment and remediation of abandoned Sb smelting sites.

Penicillium oxalicum SL2-enhanced nanoscale zero-valent iron effectively reduces Cr(VI) and shifts soil microbiota

Most current researches focus solely on reducing soil chromium availability. It is difficult to reduce soil Cr(VI) concentration below 5.0 mg kg-1 using single remediation technology. This study introduced a sustainable soil Cr(VI) reduction and stabilization system, Penicillium oxalicum SL2-nanoscale zero-valent iron (nZVI), and investigated its effect on Cr(VI) reduction efficiency and microbial ecology. Results showed that P. oxalicum SL2-nZVI effectively reduced soil total Cr(VI) concentration from 187.1 to 3.4 mg kg-1 within 180 d, and remained relatively stable at 360 d. The growth curve of P. oxalicum SL2 and microbial community results indicated that γ-ray irradiation shortened the adaptation time of P. oxalicum SL2 and facilitated its colonization in soil. P. oxalicum SL2 colonization activated nZVI and its derivatives, and increased soil iron bioavailability. After restoration, the negative effect of Cr(VI) on soil microorganisms was markedly alleviated. Cr(VI), Fe(II), bioavailable Cr/Fe, Eh, EC and urease (SUE) were the key environmental factors of soil microbiota. Notably, Penicillium significantly stimulated the growth of urease-positive bacteria, Arthrobacter, Pseudarthrobacter, and Microvirga, synergistically reducing soil chromium availability. The combination of P. oxalicum SL2 and nZVI is expected to form a green, economical and long-lasting Cr(VI) reduction stabilization strategy.

Association of Combined PFOA, PFOS, Metals and Allostatic Load on Hepatic Disease Risk

This study utilizes the National Health and Nutrition Examination Survey (NHANES) 2017-2018 data to explore the relationship between exposure to perfluoroalkyl substances (specifically perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS), metals lead (Pb), mercury (Hg), and cadmium (Cd), allostatic load, and hepatic disease markers, including the fatty liver index a measure of the likelihood of non-alcoholic fatty liver disease, aspartate aminotransferase (AST), alanine aminotransferase (ALT), alkaline phosphatase (ALP), and total bilirubin. The paper identified significant associations and interaction effects by employing descriptive statistics, Spearman's correlation analysis, linear regression, and Bayesian kernel machine regression (BKMR). Descriptive statistics highlight sex-specific differences in contaminant levels. Spearman's analysis underscores strong correlations among metals and per- and polyfluoroalkyl substances (PFAS). Linear regression reveals significant impacts of specific contaminants on AST, ALT, ALP, and bilirubin levels, adjusting for age and alcohol consumption. BKMR results further elucidate the complex, potentially synergistic relationships between these environmental exposures and the likelihood of non-alcoholic fatty liver disease, offering nuanced insights into their combined effects on liver health. The findings emphasize the intricate dynamics of environmental exposures on hepatic function, advocating for targeted public health interventions.

Can we redevelop ammonia nitrogen contaminated sites without remediation? The key role of subsurface pH in human health risk assessment

Nitrogen fertilizer supports global food production, but its manufacturing results in substantial ammonia nitrogen (AN) contaminated sites which remain largely unexplored. In this study, ten representative AN contaminated sites were investigated, covering a wide range of subsurface pH, temperature, and AN concentration. A total of 7232 soil samples and 392 groundwater samples were collected to determine the concentration levels, migration patterns, and accurate health risks of AN. The results indicated that AN concentrations in soil and groundwater reached 12700 mg/kg and 12600 mg/L, respectively. AN concentrations were higher in production areas than in non-production areas, and tended to migrate downward from surface to deeper soil. Conventional risk assessment based on AN concentration identified seven out of the ten sites presenting unacceptable risks, with remediation costs and CO2 emissions amounting to $1.67 million and 17553.7 tons, respectively. A novel risk assessment model was developed, which calculated risks based on multiplying AN concentration by a coefficient fNH3 (the ratio of NH3 to AN concentration). The mean fNH3 values, primarily affected by subsurface pH, varied between 0.02 and 0.25 across the ten sites. This new model suggested all investigated sites posed acceptable health risks related to AN exposure, leading to their redevelopment without AN-specific remediation. This research offers a thorough insight into AN contaminated site, holds great realistic significance in alleviating global economic and climate pressures, and highlights the need for future research on refined health risk assessments for more contaminants.

Brownfield-related studies in the context of climate change: A comprehensive review and future prospects

The global climate change events are expected to augment the vulnerability of persistent organic pollutants within the global brownfield areas to a certain extent, consequently heightening the risk crises faced by these brownfields amidst the backdrop of global environmental changes. However, studies addressing brownfield risks from the perspective of climate change have received limited attention. Nonetheless, the detrimental consequences of brownfield risks are intrinsically linked to strategies for mitigating and adapting to sustainable urban development, emphasizing the critical importance of their far-reaching implications. This relevance extends to concerns about environmental quality, safety, health risks, and the efficacy of chosen regeneration strategies, including potential secondary pollution risks. This comprehensive review systematically surveys pertinent articles published between 1998 and 2023. A selective analysis was conducted on 133 articles chosen for their thematic relevance. The findings reveal that: (1) Under the backdrop of the climate change process, brownfield restoration is necessitated to provide scientific and precise guidance. The integration of brownfield considerations with the dynamics of climate change has progressively evolved into a unified framework, gradually shaping a research paradigm characterized by "comprehensive + multi-scale + quantitative" methodologies; (2) Research themes coalesce into five prominent clusters: "Aggregation of Brownfield Problem Analysis", "Precision Enhancement of Brownfield Identification through Information Technology", "Diversification of Brownfield Reutilization Assessment", "Process-Oriented Approaches to Brownfield Restoration Strategies", and "Expansion of Ecological Service Functions in Brownfield Contexts"; (3) Application methodologies encompass five key facets: "Temporal and Spatial Distribution Patterns of Pollutants", "Mechanisms and Correlations of Pollution Effects", "Evaluation of Pollution Risks", "Assessment of Brownfield Restoration Strategies", and "Integration of Brownfield Regeneration with Spatial Planning". Future brownfield research from the climate change perspective is poised to reflect characteristics such as "High-Precision Prediction, Comprehensive Dimensionality, Full-Cycle Evaluation, Low-Risk Exposure, and Commitment to Sustainable Development".

Effects of three plant growth-promoting bacterial symbiosis with ryegrass for remediation of Cd, Pb, and Zn soil in a mining area

The quality of soil containing heavy metals (HMs) around nonferrous metal mining areas is often not favorable for plant growth. Three types of plant growth promoting rhizobacteria (PGPR)-assisted ryegrass were examined here to treat Cd, Pb, and Zn contaminated soil collected from a nonferrous metal smelting facility. The effects of PGPR-assisted plants on soil quality, plant growth, and the migration and transformation of HMs were evaluated. Results showed that inter-root inoculation of PGPR to ryegrass increased soil redox potential, urease, sucrase and acid phosphatase activities, microbial calorimetry, and bioavailable P, Si, and K content. Inoculation with PGPR also increased aboveground parts and root length, P, Si, and K contents, and antioxidant enzyme activities. The most significant effect was that the simultaneous inoculation of all three PGPRs increased the ryegrass extraction (%) of Cd (59.04-79.02), Pb (105.56-157.13), and Zn (27.71-40.79), compared to CK control (without fungi). Correspondingly, the inter-root soil contents (%) of total Cd (39.94-57.52), Pb (37.59-42.17), and Zn (34.05-37.28) were decreased compared to the CK1 control (without fungi and plants), whereas their bioavailability was increased. Results suggest that PGPR can improve soil quality in mining areas, promote plant growth, transform the fraction of HMs in soil, and increase the extraction of Cd, Pb, and Zn by ryegrass. PGPR is a promising microbe-assisted phytoremediation strategy that can promote the re-greening of vegetation in the mining area while remediating HMs pollution.

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.

More effective than direct contact: Nano hydroxyapatite pre-treatment regulates the growth and Cd uptake of rice (Oryza sativa L.) seedlings

Cd contamination in rice urgently needs to be addressed. Nano hydroxyapatite (n-HAP) is an eco-friendly material with excellent Cd fixation ability. However, due to its own high reactivity, innovative application of n-HAP in the treatment of Cd contamination in rice is needed. In this study, we proposed a new application, namely n-HAP pre-treatment, which can effectively reduce Cd accumulation in rice and alleviate Cd stress. The results showed that 80 mg/L n-HAP pre-treatment significantly reduced Cd content in rice shoot by 35.1%. Biochemical and combined transcriptomic-proteomic analysis revealed the possible molecular mechanisms by which n-HAP pre-treatment promoted rice growth and reduced Cd accumulation. (1) n-HAP pre-treatment regulated gibberellin and jasmonic acid synthesis-related pathways, increased gibberellin content and decreased jasmonic acid content in rice root, which promoted rice growth; (2) n-HAP pre-treatment up-regulated gene CATA1 expression and down-regulated gene OsGpx1 expression, which increased rice CAT activity and GSH content; (3) n-HAP pre-treatment up-regulated gene OsZIP1 expression and down-regulated gene OsNramp1 expression, which reduced Cd uptake, increased Cd efflux from rice root cells.

Simulating arsenic discharge flux at a relic smelting site in Guangxi Zhuang Autonomous Region, China

Anthropogenic groundwater arsenic (As) pollution is common in many aquifers in Southwest China. It is concerned that long-term random disposal of As smelting slag could induce the transport of high-As groundwater into previously uncontaminated aquifers. Here, we used HELP-MODFLOW-MT3DMS model simulations to integrate the percolation, groundwater flow, and solute transport processes at an aquifer at site scale, constrained by weather, hydrogeology, and monitoring data. Our simulations provide a new method framework of the simulated percolation by HELP model and have induced As spatiotemporal distribution in the aquifer. According to the HELP model simulation results, percolation volume accounts for 24% of rainfall over 18 years. This work determined that the As discharge trend was fitted by double-constants kinetics based on the leaching experiment. And this work calculates total mass distribution of As in the aquifer over 18 years. We have found that the sustained As pollution relies on the rainfall that acts as the primary contributor of elevated As concentrations. Model simulation results suggest that 51.70% of the total As mass (1.96 × 104 kg) was fixed in low permeability solid media. The total As mass discharged into groundwater reached 9.3 × 103 kg, accounting for 24.68%. The accumulative outflow mass of arsenic was 8.0 × 103 kg, accounting for 21.62%.

Understanding the driving mechanisms of site contamination in China through a data-driven approach

China currently faces significant environmental risks stemming from contaminated sites. The driving mechanism of site contamination, influenced by various drivers, remain obscured due to a dearth of quantitative methodologies and comprehensive data. Here, we used a data-driven causality inference approach to construct an interpretable random forest (RF) model. Results show that: (1) the trained RF model demonstrated remarkable predictive accuracy for identifying contaminated sites, with an accuracy rate of 0.89. In contrast to conventional correlation analysis, the RF model excels in discerning the key drivers through non-linear and genuine causal relationships between these drivers and site contamination. (2) Among the 25 potential drivers, we identified 18 key drivers of site contamination. These drivers encompass a broad spectrum of factors, including production and operational data, pollutant control level, site protection capability, pollutant characteristics, and physical-geographical conditions. (3) Each key driver exerts varying impacts on site pollution, with diverse directions, intensities, and underlying patterns. The partial dependence plots (PDPs) illuminate the role of each key driver, its critical value contributing to site pollution, and the interplay between these drivers. The key drivers facilitate the realization of three primary contamination processes: uncontrolled release, effective migration, and persistent accumulation. In light of our findings, environmental managers can proactively prevent site contamination by regulating single, dual, and multiple key drivers to disrupt critical pollution processes. This research offers valuable insights for devising targeted strategies and interventions aimed at mitigating environmental risks associated with contaminated sites in China.

Migration and distribution characteristics of soil heavy metal(loid)s at a lead smelting site

Heavy metal(loid)s contamination is a constant issue at smelting sites. It is essential to investigate the spatial distribution and migration characteristics of heavy metal(loid)s in the soil for environmental management and remediation strategies of non-ferrous smelting sites. In this study, 203 soil samples from 57 sites were collected in a typical lead smelting site. The findings demonstrated that there were significant Pb, Zn, Cd, and As contamination in soil samples. The spatial distribution of heavy metal(loid)s showed strong spatial heterogeneity, the contaminated soil areas of Pb, As, Cd, and Zn were 99.5%, 98.9%, 85.3%, and 72.4%, respectively. Pb, Cd, and As contamination of the soil reached a depth of 5 m, which migrated from the surface to deep soil layers. The leaching contents of Zn, Pb, and As decreased obviously in 3-4 m soil layer, but the leaching content of Cd was still high, which indicated the high migration of Cd. With the increase of depth, the proportion of acid soluble fraction of heavy metal(loid)s decreased, and the residual fraction increased. The acid soluble fraction of Cd accounted for a higher proportion, and As mainly existed in reducible and residual fractions in soil. According to the calculation of the migration factor, the migration of heavy metal(loid)s in soils were ordered as Cd > Zn > Pb > As. The outcomes are advantageous for risk reduction and site remediation for non-ferrous metal smelting sites.

Exploitation alters microbial community and its co-occurrence patterns in ionic rare earth mining sites

The exploitation of ion-adsorption rare earth elements (REEs) deposits results in serious ecological and environmental problems, which has attracted much attention. However, the influences of exploitation on the prokaryotic communities and their complex interactions remain poorly understood. In the present study, bacterial and archaeal communities, as well as ammonia-oxidizing bacteria (AOB) and ammonia-oxidizing archaea (AOA), in and around REEs mining area were investigated through high throughput sequencing and quantitative polymerase chain reaction (qPCR). Our results indicated that mining soil was characterized by poor soil structure, nutrient deficiency, and high concentrations of residual REEs. Oligotrophic bacteria (e.g., Chloroflexi and Acidobacteriota) were dominant in unexploited soil and mining soil, while copiotrophic bacteria (Proteobacteria and Actinobacteriota) were more abundant in surrounding soil. Nutrient was the key factor affecting microbial variation and abundance in mining soil. The bacterial community was more sensitive to REEs, while the archaeal communities were relatively stable. As the key members for ammonia oxidation, AOA outnumbered AOB in all the soil types, and the former was significantly influenced by pH, nutrients, and TREEs in mining soil. The microbial co-occurrence network analysis demonstrated that exploitation significantly influenced topological properties, decreased the complexity, and resulted in a much unstable network, leading to a more fragile microbial ecosystem in mining areas. Notably, the abundance of keystone taxa decreased after exploitation, and oligotrophic groups (Chloroflexi) replaced copiotrophic groups (Proteobacteria and Actinobacteriota) as the key to rebuilt a co-occurrence network, suggesting potentially important roles in maintaining network stability. The current results are of great significance to the ecological risk assessment of REEs exploitation.

Spatiotemporal distribution and pollution control of pollutants in a Cr(VI)-contaminated site located in Southern China

Soil and groundwater Cr(VI) pollution resulting from improper disposal and accidental spills is a critical problem worldwide. In this study, a comprehensive study was conducted to assess the hydrogeological conditions of a contaminated site, obtain spatiotemporal distribution and trend forecasts of pollutant Cr(VI), and determine the feasibility of applying clayey engineered barriers for pollution control. The results showed that the hydraulic conductivity (K) of the clayey barrier (1.56E-5 m/d) is several orders of magnitude lower than that of the stratum beneath the contaminated site, with K values ranging from 0.0014 to 4.76 m/d. Cr(VI) exhibits high mobility and a much higher concentration in the vadose zone, with maximum values of 6100 mg/kg in topsoil and 2090 mg/L in the perched aquifer. The simulation results indicated that the groundwater in the vicinity of the contaminated site, as well as downstream of the Lianshui River, is seriously threatened by Cr(VI). Notably, the pollution plume could occur downstream of the Lianshui River after 8 years. The retention efficiency of clayey engineered barriers will decrease over time, at 61.6% after 8 years and 33% after 20 years. This work contributes to an in-depth understanding of Cr(VI) migration at contaminated sites.

Model development and probabilistic risks of cadmium transport in slag-soil-groundwater systems with heterogeneous conditions

Prediction of the long-term risk of trace metals leaching from soils at smelting sites is essential for groundwater protection. Herein, a mass balance-based stochastic model was developed to simulate the transport and probabilistic risks of trace metals in heterogeneous slag-soil-groundwater systems. The model was applied to a smelting slag yard with three stacking scenarios, including (A) fixed stacking amount, (B) stacking amount increasing yearly, and (C) slag removal after 20 years. The simulations suggested that the leaching flux and net accumulation of Cd in soils of the slag yard and abandoned farmland were greatest for scenario (B), which was followed by scenarios (A) and (C). In the slag yard, a plateau occurred in the Cd leaching flux curves, followed by a sharp increase. After 100 years of leaching, only scenario (B) had a high probabilistic risk (>99.9 %) of threatening groundwater safety under heterogeneous conditions. <11.1 % of the exogenous Cd may leach into groundwater under the worst scenario. The key parameters affecting Cd leaching risk include runoff interception rate (IRCR), input flux from slag release (I), and stacking time (ST). The simulation results were consistent with the values measured in a field investigation and laboratory leaching experiments. The results should help guide remediation objectives and measures to minimize the leaching risk at smelting sites.

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.

Effects of Simulated Reclaimed Water on Soil Particle Sizes and Cd Adsorption and Migration in Soils at Smelting Sites

This work studied the vertical migration characteristics of Cd in soil profiles from a zinc smelting site under the influence of simulated reclaimed water containing NaCl and Na2SO4. The isothermal adsorption curves of Cd in the soils of miscellaneous fill and weathered slate well fitted the Freundlich and Langmuir models, with R2 ranging from 0.991 to 0.998. The maximum adsorption capacity of Cd in the soils decreased significantly under the salt ion treatments with NaCl and Na2SO4. After leaching, the Cd concentrations in the leachates and Cd contents in the subsoil layers of 10-60 cm followed the order NaCl treatment > Na2SO4 treatment > CK (p < 0.05), suggesting that the salt ions promoted the vertical migration of exogenous Cd. The proportion of coarse particles (> 0.02 mm) decreased, while that of fine particles (< 0.02 mm) increased under salt ion treatments (p < 0.05). The morphological characterization indicated that salt ions accelerated the erosion and fragmentation of coarse particles to form fine particles. The use of reclaimed water to flush smelting sites may increase the risk of Cd migration with small-sized soil particles from the soil to groundwater.

Effect of potentially toxic elements on soil multifunctionality at a lead smelting site

Contaminated soil at smelting sites affects land utilization and environmental regulation, resulting in soil degradation. However, the extent to which potentially toxic elements (PTEs) contribute to site soil degradation and the relationship between soil multifunctionality and microbial diversity in the process remains poorly understood. In this study, we investigated changes in soil multifunctionality and the correlation between soil multifunctionality and microbial diversity under the influence of PTEs. The change in microbial community diversity was closely related to changes in soil multifunctionality caused by PTEs. Microbial diversity, not richness, drives the delivery of ecosystem services in smelting site PTEs-stressed environments. Structural equation modeling identified that soil contamination, microbial taxonomic profile and microbial functional profile could explain 70% of the variance in soil multifunctionality. Furthermore, our findings demonstrate that PTEs limit soil multifunctionality by affecting soil microbial communities and functionality, whilst the positive effect of microorganisms on soil multifunctionality was mainly driven by the fungal diversity and biomass. Finally, specific fungal genera closely related to soil multifunctionality were identified, with saprophytic fungi being particularly important for maintaining multiple soil functions. The results of the study provide potential guidance for the remediation, pollution control practices and mitigation of degraded soils at smelting sites.

Synergy among extracellular adsorption, bio-precipitation and transmembrane transport of Penicillium oxalicum SL2 enhanced Pb stabilization

As a potential bioremediation strain for Pb contamination, Penicillium oxalicum SL2 sometimes has secondary activation of Pb, so it is crucial to clarify its effect on Pb morphology and its intracellular response to Pb stress. We investigated the effect of P. oxalicum SL2 in medium on Pb2+ and Pb availability in eight minerals, and revealed the prioritization of Pb products. (i)Pb was stabilized within 30 days as Pb3(PO4)2 or Pb5(PO4)3Cl with sufficient phosphorus (P); (ii) under P deficiency but sulfur (S) sufficient, Pb was stabilized mainly in the form of PbSO4; (iii) under conditions of P and S deficiency, Pb was stabilized mainly in the form of PbC2O2. With the help of proteomic and metabolomics analysis, a total of 578 different proteins and 194 different metabolites were found to be matched in 52 pathways. Among them, the activation of chitin synthesis, oxalate production, sulfur metabolism and transporters improved the Pb tolerance of P. oxalicum SL2, and promoted the synergistic effect of extracellular adsorption, bio-precipitation and transmembrane transport on Pb stabilization. Our results fill the gap in the intracellular response of P. oxalicum SL2 to Pb and provide new insights into the development of bioremediation agent and technology for Pb contamination.

Engineering Characteristics and Microscopic Mechanism of Soil-Cement-Bentonite (SCB) Cut-Off Wall Backfills with a Fixed Fluidity

Soil-cement-bentonite (SCB) backfill has been widely used in constructing cut-off walls to inhibit groundwater movement in contaminated sites. This study prepares SCB backfill with fixed fluidity. We conducted a series of experiments to investigate the engineering characteristics and microscopic mechanism of the backfill. The results indicate that the water content in the slurry was more sensitive to the bentonite content. The unconfined compression strength (UCS) value increased with an increase in the cement content, and the change with an increase in bentonite content was not noticeable. The permeability coefficient decreased distinctly with an increase in the cement and bentonite contents. The porosity of the SCB backfill increased with increasing bentonite content and decreased with increasing cement content. The UCS of SCB backfill was linearly and negatively correlated with the porosity; the permeability coefficient was not significantly related to the porosity. The percentage of micro- and small-pore throats in the backfill increased with increasing bentonite and cement contents. As cement and bentonite content increased by 6% in the backfill, the proportion of micro- and small-pore throats increased by 0.7% and 1.2%, respectively. The percentage of micro- and small-pore throats is deduced to be more suitable as a characterization parameter for the permeability of the SCB backfill. The overall results of this study show that the reasonably proportioned SCB backfill has potential as an eco-friendly and cost-effective material. Based on the requirements of strength and permeability coefficient (UCS > 100 kPa, 28 days permeability coefficient <1 × 10^-7 cm/s), we suggested using a backfill with 12% bentonite and 9% cement as the cut-off wall mix ratio.

Anthropogenic processes drive heterogeneous distributions of toxic elements in shallow groundwater around a smelting site

Smelting activities have a far-reaching influence on the quality of soil and groundwater, while most studies have neglected the information on the pollution characteristics of groundwater. The hydrochemical parameters of shallow groundwater and the spatial distributions of toxic elements were investigated in this study. Correlations analysis and groundwater evolution revealed that the major ions were primarily determined by silicate weathering and calcite dissolution process, and anthropogenic processes had a significant effect on groundwater hydrochemistry. Almost 79%, 71%, 57%, 89%, 100%, and 78.6% of samples exceeded the standards of Cd, Zn, Pb, As, SO₄^2-, and NO₃^-, and their distribution is closely related to the production process. Analysis of soil geochemistry indicated that the relatively mobile forms of toxic elements strongly influence the origin and concentration in shallow groundwater. Besides, rainfall with high magnitude would lead to a decrease of toxic elements in shallow groundwater, whereas the area once stacked waste residue was the opposite. It is recommended to strengthen risk management of the limited mobility fraction while devising a plan for waste residue treatment in accordance with the local pollution conditions. The research on controlling the mechanism of toxic elements in shallow groundwater, along with sustainable development in the study area and other smelting zones may benefit from this study.

New insights on the effect of non-ferrous metal mining and smelting activities on microbial activity characteristics and bacterial community structure

Mining and smelting activities have brought potentially serious heavy metal(loid)s pollution to their surrounding locale. However, studies on microbial metabolic activities, community structure, and adaptation in soils proximal to non-ferrous metal mining and smelting areas are still lacking. Here the effects of biotic and abiotic characteristics of soil taken from sites surrounding inactive and active non-ferrous metal mine smelting facilities on microbial enzyme activity, microcalorimetry, and high-throughput sequencing of 16S rRNA gene barcoding were studied. Data indicated that the soils were heavily polluted by toxic metal(loid)s, of which As and Cd were the main contaminants. Microbial acid phosphatase activity and microcalorimetric total heat value were sensitive metabolic indicators in the studied areas. Actinobacteriota had the highest relative abundance, followed by Proteobacteria, Chloroflexi, and Acidobacteria. Microbial metabolic activity, bacterial community structure and phenotype varied between inactive and active sites (p < 0.05). Such analyses indicated that electrical conductivity, total As, Cu, and Mn contents, and bioavailable As, Cu, Cd, and Mn concentrations were key factors determining microbial activities, bacterial community structure, and phenotypes. Knowledge of microbial adaptation to heavy metal stressors is important for better understanding the aerial transfer of fugitive heavy metal(loid)s (and possibly microbes) and for designing future strategies for improved soil bioremediation.

Effects of Fe3O4 nanoparticles and nano hydroxyapatite on Pb and Cd stressed rice (Oryza sativa L.) seedling

Nowadays, Lead (Pb) and Cadmium (Cd) contamination in rice is an important worldwide environmental concern. Fe₃O₄ nanoparticles (Fe₃O₄ NPs) and Nano hydroxyapatite (n-HAP) are promising materials to manage Pb and Cd contamination. This study systematically investigated the effect of Fe₃O₄ NPs and n-HAP on Pb and Cd stressed rice seedlings' growth, oxidative stress, Pb and Cd uptake and subcellular distribution in roots. Furthermore, we clarified the immobilization mechanism of Pb and Cd in the hydroponic system. Fe₃O₄ NPs and n-HAP could reduce Pb and Cd uptake of rice mainly through decreasing Pb and Cd concentrations in culture solution and combining with Pb and Cd in root tissues. Pb and Cd were immobilized by Fe₃O₄ NPs through complex sorption processes and by n-HAP through dissolution-precipitation and cation exchange, respectively. On the 7th day, 1000 mg/L Fe₃O₄ NPs reduced the contents of Pb and Cd in shoots by 90.4% and 95.8%, in roots by 23.6% and 12.6%, 2000 mg/L n-HAP reduced the contents of Pb and Cd in shoots by 94.7% and 97.3%, in roots by 93.7% and 77.6%, respectively. Both NPs enhanced the growth of rice seedlings by alleviating oxidative stress and upregulating glutathione secretion and antioxidant enzymes activity. However, Cd uptake of rice was promoted at certain concentrations of NPs. The subcellular distribution of Pb and Cd in roots indicated that both NPs decreased the percentage of Pb and Cd in the cell wall, which was unfavorable for Pb and Cd immobilization in roots. Cautious choice was needed when using these NPs to manage rice Pb and Cd contamination.

Source apportionment and quantitative risk assessment of heavy metals at an abandoned zinc smelting site based on GIS and PMF models

The abandoned smelters have caused serious hazards to the surrounding environment and residents. Taking an abandoned zinc smelter in southern China as an example, a total of 245 soil samples were collected to study spatial heterogeneity, source apportionment, and source-derived risk assessment of heavy metal(loid)s (HMs) in the region. The results showed that the mean values of all HMs concentrations were higher than the local background values, with Zn, Cd, Pb, and As contamination being the most serious and their plume penetrating to the bottom layer. Four sources were identified by principal component analysis and positive matrix factorization, with their contributions to the HMs contents ranked as: surface runoff (F2, 63.2%) > surface solid waste (F1, 22.2%) > atmospheric deposition (F3, 8.5%) > parent material (F4, 6.1%). Among these, F1 was a determinant source of human health risk with a contribution rate of 60%. Therefore, F1 was considered to be the priority control factor, but it only accounted for 22.2% of HMs contents contribution. Hg dominated the ecological risk with a contribution of 91.1%. Pb (25.7%) and As (32.9%) accounted for the non-carcinogenic risk, while As (95%) dominated the carcinogenic effect. The spatial characteristics of human health risk values derived from F1 indicated that high-risk areas were mainly distributed in the casting finished products area, electrolysis area, leaching-concentration area, and fluidization roasting area. The findings highlight the significance of priority control factors (including HMs, pollution sources and functional areas) for consideration in the integrated management of this region, thus saving costs for effective soil remediation.

Analytical study on heavy metal output fluxes and source apportionment of a non-ferrous smelter in southwest China

Abandoned Pb/Zn smelters are often accompanied by a large amount of smelting slag, which is a serious environmental problem. Previous studies have demonstrated that slag deposits pose an environmental threat even if the smelters are shut down. Herein, a Pb/Zn smelter and its impacted zone in GeJiu, Yunnan, China were selected as the study area. The risk and source apportionment of heavy metals (HMs) in the soil of the impacted zone were systematically studied. Based on the hydrogeological features, the migration path and output fluxes of the HMs released from smelting slag to the impacted zone were investigated. The HM contents (Cd, As, Zn, Pb, and Cu) in the soil substantially exceeded the screening values of the Chinese soil standard (GB15618-2018). Based on the results of the Pb isotopic and statistical analyses for source apportionment, the contaminated sites and agricultural irrigation water had a large impact on the HMs of soil. The hydrological analysis results showed that runoff, as an HM migration path under rainfall, continued to affect the environment. The water balance calculations using the Hydrologic Evaluation of Landfill Performance model showed that the rainfall was distributed on site as follows: evaporation (57.35%), runoff (32.63%), and infiltration (10.02%). Finally, the output fluxes were calculated in combination with the leaching experiment. As, Zn, Cd, Pb, and Cu runoff had the output fluxes of 6.1 × 10^-3, 4.2 × 10^-3, 4.1, 1.4 × 10^-2, and 7.2 × 10^-4 mg/kg/y, and infiltration of 1.9 × 10^-3, 1.3 × 10^-3, 1.3, 4.0 × 10^-4, and 2.2 × 10^-4 mg/kg/y, respectively. Therefore, this study offers theoretical and scientific recommendations for effective environmental management and engineering remediation.

A practical method for identifying key factors in the distribution and formation of heavy metal pollution at a smelting site

Smelting activities are the main pathway for the anthropogenic release of heavy metals (HMs) into the soil-groundwater environment. It is vital to identify the factors affecting HMs pollution to better prevent and manage soil pollution. The present study conducted a comprehensive investigation of HMs in soil from a large abandoned Zn smelting site. An integrated approach was proposed to classify and quantify the factors affecting HMs pollution in the site. Besides, the quantitative relationship between hydrogeological characteristics, pollution transmission pathways, smelting activities and HMs pollution was established. Results showed that the soils were highly contaminated by HMs with a pollution index trend of As > Zn > Cd > Pb > Hg. In identifying the pollution hotspots, we conclude that the pollution hotspots of Pb, As, Cd, and Hg present a concentrated distribution pattern. Geo-detector method results showed that the dominant driving factors for HMs distribution and accumulation were the potential pollution source and soil permeability. Additionally, the main drivers are variable for different HMs, and the interaction among factors also enhanced soil HMs contamination. Our analysis illustrates how the confounding influences from complex environmental factors can be distilled to identify key factors in pollution formation to guide future remediation strategies.

Rapid conversion of alkaline bauxite residue through co-pyrolysis with waste biomass and its revegetation potential

The extreme alkalinity of bauxite residue (BR) leads to difficulty with its reuse. Alkaline leachate and dust generation during the stacking process can pollute surrounding soil, air and water. In this work, co-pyrolysis of bauxite residue and sawdust was applied to rapidly produce a soil-like matrix that met the conditions for plant growth as demonstrated by ryegrass pot experiments. The present study aimed to characterize the detailed changes in physicochemical, mineral weathering, and microbial communities of the pyrolyzed BR with different ratios of saw dust after plant colonization for 2 months. With increasing sawdust addition during co-pyrolysis, the pH of BR decreased from 11.21 to 8.16, the fraction of macro-aggregates 0.25-2 mm in the water-stable agglomerates increased by 29.3%, and the organic carbon concentration increased from 12.5 to 320 mg/kg, whilst facilitating the degree of humification, which were all beneficial to its revegetation performance. The backscattered electron-scanning electron microscope-energy-dispersive X-ray spectrometry (BSE-SEM-EDS) results confirmed the occurrence of sodalite and calcite weathering on aggregate surfaces, and X-ray photoelectron spectroscopy (XPS) results of surface Al and Si compounds identified that some weathering products were clay minerals such as kaolinite. Furthermore, bacterial community composition and structure shifted towards typical soil taxonomic groups. These results demonstrate soil development of treated BR at an early stage. The technique is a combination of alkalinity regulation and agglomerate construction, which accelerates soil formation of BR, thus proving highly promising for potential application as an artificial soil substitute.

Three-dimensional distribution characteristics of multiple pollutants in the soil at a steelworks mega-site based on multi-source information

Soil pollution at steelworks mega-sites has become a severe environmental issue worldwide. However, due to the complex production processes and hydrogeology, the soil pollution distribution at steelworks is still unclear. This study scientifically cognized the distribution characteristics of polycyclic aromatic hydrocarbons (PAHs), volatile organic compounds (VOCs), and heavy metals (HMs) at a steelworks mega-site based on multi-source information. Specifically, firstly, 3D distribution and spatial autocorrelation of pollutants were obtained by interpolation model and local indicators of spatial associations (LISA), respectively. Secondly, the characteristics of horizontal distribution, vertical distribution, and spatial autocorrelations of pollutants were identified by combining multi-source information such as production processes, soil layers, and properties of pollutants. Horizontal distribution showed that soil pollution in steelworks mainly occurred in the front end of the steel process chain. Over 47% of PAHs and VOCs pollution area were distributed in coking plants and over 69% of HMs in stockyards. Vertical distribution indicated that HMs, PAHs, and VOCs were enriched in the fill, silt, and clay layers, respectively. Spatial autocorrelation of pollutants was positively correlated with their mobility. This study clarified the soil pollution characteristics at steelworks mega-sites, which can support the investigation and remediation of steelworks mega-sites.

Metal distribution behavior based on soil aggregate size in a post-restoration coastal mining area

Soil aggregate size plays an important role in controlling the distribution and transport of metals. Metals immobilized in soil particles will pose potential risks through production/sink flow and infiltration. This study explored the distribution behavior of metals based on soil aggregate size in a restored coastal mining area by establishing Structural Equation Model (SEM) and column experiments. The results showed that hydrological factors and a high degree of weathering accelerated the dissolution of metals from the mine, the desorption of Wa-NH₄⁺-N, the release of F^-, and the leaching of NO₃^-. Driven by soil properties, natural factors, and anthropogenic activities, the total metal content (Total_metal) of Cr, Ni, Zn, Mn, and As showed significant spatial heterogeneity compared to Cd, Co, Cu, and Pb. The geochemical fraction of metals (Geo_metal) indicated that Cd, Co, Pb, Zn, As, and Cu are mainly present in iron‑manganese oxidation bound, organically bound, and residual fractions. The results of SEM showed that the physicochemical properties, Wa-NH₄⁺-N, nitrate nitrogen, and inorganic anions of the soil could explain 69.1 %, 76.4 %, 97.1 %, and 80.0 % of the variation in K_d-Mn, K_d-Pb, K_d-Ni, and K_d-Zn, respectively. While K_d-Cd, K_d-Cu, and K_d-Cr could be predicted by the Total_metal, but the Geo_metal seemed to have little influence on metal K_d. The results of column experiments showed that macroaggregates (>0.25 mm) significantly affected the distribution of Co, Cr, Cu, Mn, Ni, Pb, and Zn in the topsoil. The severe disruption of soil aggregate structure resulted in small fluctuations of anthropogenic Cu, Mn, Pb, Zn, and As in different layers of deep soil. In addition, mineral composition in >0.15 mm particle size was more likely to change. Overall, the hydrological cycle of coastal mines increases the uncertainty of their response to risk. Our study provides a basis for future strategies for priority control and risk prevention.

Effect of goethite-loaded montmorillonite on immobilization of metal(loid)s and the micro-ecological soil response in non-ferrous metal smelting areas

In this work, the immobilization stabilization and mechanism of heavy metal(loid)s by goethite loaded montmorillonite (GMt) were investigated, and the soil microbial response was explored. The simulated acid rain leaching experiment showed that GMt had a higher acid tolerance and the more stable heavy metal(loid)s fixation ability. The soil incubation demonstrated that GMt significantly decreased the available Cd, Zn, Pb and As concentration. Interestingly, higher immobilization of heavy metals was observed by GMt in highly acid leached and acidic soils. The richness and diversity of bacterial communities improved after the addition of GMt. GMt induced the enrichment of the excellent functional bacteria of the phylum Proteobacteria as well as the genus Massilia and Sphingomonas. The main immobilization mechanisms of heavy metal(loid)s by GMt include electrostatic interaction, complexation, precipitation and oxidation. The addition of the GMt also optimizes the soil bacterial community structure, which further facilitates the immobilization of heavy metal(loid)s. Our results confirm that the novel GMt has a promising application in the immobilization and stabilization of heavy metal(loid)s contaminated soils in non-ferrous metal smelting areas.

Performance and mechanisms for Cd(II) and As(III) simultaneous adsorption by goethite-loaded montmorillonite in aqueous solution and soil

A series of goethite-modified montmorillonite (GMt) materials was synthesized for the amelioration of cationic cadmium (Cd) and anionic arsenic (As) complex contaminants in soil and water bodies. The results showed that goethite (Gt) was successfully loaded onto the surface of montmorillonite (Mt), which possessed more functional groups (such as Fe-O, and Fe-OH) and a larger specific surface area. GMt-0.5 (Mt loaded with Gt at a ratio of 0.5:1) showed the highest adsorption capacity for Cd(II) and As(III) with the maximum of 50.61 mg/g and 57.58 mg/g, respectively. The removal rate of Cd(II) was highly pH dependent, while the removal rate of As(III) showed little dependence on pH. The goethite on montmorillonite might contribute to the formation of surface complexes with As(III) and oxidation of As(III) to As(V). In the binary system, both, synergistic and competitive adsorption existed simultaneously. Importantly, in the binary system, the removal of As(III) was more favorable because of the electrostatic interaction, formation of a ternary complex, and co-precipitation. In addition, the amendment of GMt-0.5 significantly reduced the availability of Cd and As in the soil. This study suggests that GMt-0.5 is a promising candidate for the simultaneous immobilization of metal (loid)s in both, aqueous solution and mine soil.

A lifelong journey of lead in soil profiles at an abandoned e-waste recycling site: Past, present, and future

Heavy metal pollutants resulting from human activities consistently move from the topsoil to the subsoil profiles under the influence of rainfall leaching. This study intends to predict the long-term transport of heavy metals at an abandoned e-waste recycling site with respect to historical pollution activities, land use, and metal pollutant dynamics. Our results showed that the site was seriously contaminated with heavy metals (Cd, Cu, Pb, and Zn) in the soil profiles. More specifically, Cu and Zn accumulated primarily in the upper layers of the soil profile owing to their weak mobility, while significant migration of Cd and Pb was observed in the deeper soil layers. Furthermore, to clarify the fate of Pb in soil profiles, Pb isotopes and the Hydrus model were used to trace the sources of Pb contamination and predict its long-term distribution. The Pb isotope results suggest that past e-waste recycling activities significantly contributed to the heavy metal concentration in the soil profiles; however, other anthropogenic sources such as vehicle exhaust had smaller impacts. Moreover, our model findings predicted that within the next 30 years, 60% of Pb contaminants will be concentrated in the surface soil. Together these results provide a theoretical foundation and scientific basis for evaluating, controlling, and remediating abandoned e-waste recycling sites.

Penicillium oxalicum augments soil lead immobilization by affecting indigenous microbial community structure and inorganic phosphate solubilization potential during microbial-induced phosphate precipitation

Phosphate-solubilizing microorganisms (PSMs) are critically important for increasing soil phosphate (P) and decreasing lead (Pb) bioavailability during microbial-induced phosphate precipitation (MIPP). However, their relative contributions to the indigenous soil microbial communities and P-cycling genes during the MIPP process remain unclear. In this study, inoculation of the PSM P. oxalicum in hydroxyapatite-cultured and Pb-contaminated soil increased soil phosphatase activities, available P (AP) concentrations and reduced available Pb levels. Metagenomics revealed a 3.9-44.0% increase in the abundance of P-cycling genes by P. oxalicum inoculation. No P-cycling genes were assigned to Penicillium. While P. oxalicum increased the complexity of microbial community co-occurrence networks, and improved the directly interrelationships between Penicillium and genera containing P-cycling gene. These results suggesting that P. oxalicum obviously positively affected the regulation of indigenous P-cycling functional communities during the MIPP process. Inorganic P solubilization genes (gcd, ppa, and ppx) have been shown to affect soil AP, suggesting that inorganic P solubilization is the major driver of Pb immobilization improvement following P. oxalicum inoculation. These results enhance our understanding of the significant ecological role of PSMs in governing soil P-cycling and alleviating Pb²⁺ biotoxicity during the MIPP process.

Simultaneous immobilization of arsenic, lead, and cadmium in soil by magnesium-aluminum modified biochar: Influences of organic acids, aging, and rainfall

Magnesium-aluminum modified biochar (MABs) has an outstanding effect on the simultaneous immobilization of arsenic (As), lead (Pb), and cadmium (Cd) in soil, but the stability of remediation effect of MAB under various natural conditions is still unknown. In this study, we investigated the effects of organic acids, dry-wet cycles (DW), freeze-thaw cycles (FT), and rainfall (pH 4, 7, and 8) on the immobilization of As, Pb, and Cd by MAB. The results showed that oxalic acid decreased the immobilization efficiencies of As, Pb, and Cd by 15.5%-38.5%; meanwhile, humic acid reduced the immobilization efficiency of Pb by 89.7%, but elevated that of Cd by 19.5%. The immobilization mechanisms of MAB-5 on three metals were mainly involved in ion exchange and surface-complexation. Compared with the 7th round, the immobilization efficiencies of As, Pb, and Cd by MAB in the 28th round was decreased by 17%-28% in DW, but was increased by 11%-18% in FT. In addition, MAB was transformed into hydrotalcite after FT and DW. After experiencing simulated rainfall, MAB caused more As, Pb, and Cd to be retained in the upper soil layer, and the immobilization effect of MBA was more significant under the stimulated rainfall with higher pH. The study provides a more theoretical basis for the application of MAB in the actual site remediation.

Application of bovine bone meal and oyster shell meal to heavy metals polluted soil: Vegetable safety and bacterial community

The development of efficient, environmentally friendly soil amendments is necessary in order to minimize the risk of metal contaminants (Cd, Pb, Cu, and Zn) to the soil ecosystem. As soil amendments, bovine bone meal (BM) and oyster shell meal (OS) reduced the mobility and bioavailability of metals primarily by increasing soil pH. Soil geochemical properties (pH, EC, CEC, Ca, P, and K) after amendment supplementation were more likely to affect metal migration than enzyme activity. Furthermore, BM and OS were found to suppress the Cd and Pb uptake by water spinach, keeping them below international standards for safe utilization. The protein and sugar content and peroxidase (POD) activity showed a significant negative correlation with the amount of metal in water spinach, whereas superoxide dismutase (SOD), ascorbate peroxidase (APX) activities and malondialdehyde (MDA) content exhibited a positive correlation with metal content in water spinach. We also found that BM and OS had less perturbation to phylum-level and genus-level bacterial composition during the remediation of heavy metals contaminated soil. Based on the above, we assume that BM and OS are eco-friendly soil amendments, which could improve soil nutrients contents, stabilize heavy metals and regulate bacterial community structure. Our research contributes to resource utilization of waste and holds promise for widespread application in current agricultural systems.

Spatiotemporal characteristics of air pollution in Chengdu-Chongqing urban agglomeration (CCUA) in Southwest, China: 2015-2021

Studying the spatiotemporal characteristics of air pollutants in urban agglomerations and their response factors will help to improve the quality of urban living. In combining air quality monitoring data and wavelet analysis from the Chengdu-Chongqing urban agglomeration (CCUA), this study assessed the spatiotemporal distribution characteristics and influential factors of air pollutants on daily, monthly and annual scales. The results showed that the concentration of air pollutants in the CCUA has decreased year by year, and air quality has improved. Except for O₃, pollutants in autumn and winter were higher than those in summer. The spatial distribution of air pollutants was obvious distributed in Chengdu, Chongqing, Zigong and Dazhou. Pollution incidents were mainly concentrated in winter. The 6 air pollutants and air quality index (AQI) have dominant periods on multiple time scales. AQI showed positive coherence with PM_2.5 and PM₁₀ on multiple time scales, and obvious positive coherence with SO₂, CO, NO₂ and O₃ in the short term scale. AQI was not strongly correlated with the fire point, but exhibited obvious negative coherence in the long term scale. In addition, AQI showed an obvious positive correlation with temperature and sunshine hours in short term, and a clear negative correlation with humidity and rainfall. The research results of this paper will provide a reference for pollution prevention and control in the CCUA.

Geochemical partitioning and spatial distribution of heavy metals in soils contaminated by lead smelting

Heavy metals (HMs) pollution is a universal and complex problem at lead smelting sites. Further understanding on the distribution, coexistence relationship and occurrence form of multi-metals in soils should be taken prior to restoration on the contaminated sites. In this study, 222 soil samples in a typical abandoned lead smelting site were investigated to understand the spatial distribution and geochemical partitioning of HMs. The results showed that soil quality was seriously threatened by As, Pb and Cd, which expressed high spatial heterogeneity. Integration of sequential extraction, X-ray photoelectron spectroscopy and mineral liberation analysers were employed to qualify the geochemical partitioning of HMs. The data showed that Pb and As were mainly partitioned in the reducible phase and residue phase, where the maximum of As were 18% and 79%, and the maximum of Pb were 31% and 64%, respectively, whilst Cd was mainly partitioned with residue phase (about 25%) and weakly acid soluble phase (about 18%). Paulmooreite was the major important mineral host for Pb and As, whereas Cd predominantly existed in willemite. These minerals containing HMs could usually with Fe reside in the octahedral layer of clay minerals such as montmorillonite, and may also reside in the interlayer. Quartz, montmorillonite and goethite were closely associated with HMs minerals in contaminated soils, which limited vertical migration of HMs and potential risks to groundwater. The results enhanced the understanding of spatial distribution and occurrence behavior of HMs, whilst providing potential benefits to heavy metal stabilization and risks control at abandoned non-ferrous metal smelting sites.

Contamination presence and dynamics at a polluted site: Spatial analysis of integrated data and joint conceptual modeling approach

Contaminated sites are complex systems posing challenges for their characterization as both contaminant distribution and hydrogeological properties vary markedly at the metric scale, yet may extend over broad areas, with serious issues of spatial under-sampling in the space. Characterization with sufficient spatial resolution is thus, one of the main concerns and still open areas of research. To this end, the joint use of direct and indirect (i.e., geophysical) investigation methods is a very promising approach. This paper presents a case study aspiring to demonstrate the benefit of a multidisciplinary approach in the characterization of a hydrocarbon-contaminated site. Detailed multi-source data, collected via stratigraphic boreholes, laser-induced fluorescence (LIF) surveys, electrical resistivity tomography (ERT) prospecting, groundwater hydrochemical monitoring, and gas chromatography-mass spectrometry (GC-MS) analyses were compiled into an interactive big-data package for modeling activities. The final product is a comprehensive conceptual hydro-geophysical model overlapping multi-modality data and capturing hydrogeological and geophysical structures, as well as contamination distribution in space and dynamics in time. The convergence of knowledge in the joint model verifies the possibility of discriminating geophysical findings based on lithological features and contamination effects, unmasking the real characteristics of the pollutant, the contamination mechanisms, and the residual phase hydrocarbon sequestration linked to the hydrogeological dynamics and adopted remediation actions. The emerging conceptual site model (CSM), emphasizing the necessity of a large amount of multi-source data for its reliable, high-resolution reconstruction, appears as the necessary tool for the design of remedial actions, as well as for the monitoring of remediation performance.