Interaction analysis of hydrochemical factors and dissolved heavy metals in the karst Caohai Wetland based on PHREEQC, cooccurrence network and redundancy analyses

Impact of soil physicochemical factors and heavy metals on co-occurrence pattern of bacterial in rural simple garbage dumping site

Rural waste accumulation leads to heavy metal soil pollution, impacting microbial communities. However, knowledge gaps exist regarding the distribution and occurrence patterns of bacterial communities in multi-metal contaminated soil profiles. In this study, high-throughput 16 S rRNA gene sequencing technology was used to explore the response of soil bacterial communities to various heavy metal pollution in rural simple waste dumps in karst areas of Southwest China. The study selected three habitats in the center, edge, and uncontaminated areas of the waste dump to evaluate the main factors driving the change in bacterial community composition. Pollution indices reveal severe contamination across all elements, except for moderately polluted lead (Pb); contamination severity ranks as follows: Mn > Cd > Zn > Cr > Sb > V > Cu > As > Pb. Proteobacteria, Actinobacteria, Chloroflexi, and Acidobacteriota predominate, collectively constituting over 60% of the relative abundance. Analysis of Chao and Shannon indices demonstrated that the waste dump center boasted the greatest bacterial richness and diversity. Correlation data indicated a predominant synergistic interaction among the landfill's bacterial community, with a higher number of positive associations (76.4%) compared to negative ones (26.3%). Network complexity was minimal at the dump's edge. RDA analysis showed that Pb(explained:46%) and Mn(explained:21%) were the key factors causing the difference in bacterial community composition in the edge area of the waste dump, and AK(explained:42.1%) and Cd(explained:35.2%) were the key factors in the center of the waste dump. This study provides important information for understanding the distribution patterns, co-occurrence networks, and environmental response mechanisms of bacterial communities in landfill soils under heavy metal stress, which helps guide the formulation of rural waste treatment and soil remediation strategies.

Ecological stoichiometry of C, N, P and Si of Karst Masson pine forests: Insights for the forest management in southern China

Ecological stoichiometry is an effective method to study the stoichiometric relations and laws of elements in biogeochemical cycle, widely used in studies on nutrient cycles, limiting elements and nutrient utilization efficiency in ecosystems. To explore C, N, P, and Si stoichiometric characteristics and reveal these nutrient cycle processes and mechanisms in the karst Masson pine forests, the typical Masson pine forests of the three different stand ages in southern China were selected as the research objects and the C, N, P, and Si stoichiometric characteristics of soil-plant-litter continuum were studied. The followed results and conclusions were obtained: 1) Content range of TOC (total organic carbon), TN (total N), TP (Total P) and TSi (total Si) of the Masson pine forests was 288.31-334.61, 0.34-6.66, 0.11-1.05, and 0.76-11.4 g·kg-1, respectively. And the ratio range of C:N, C:P, C:Si, N:P, N:Si, and P:Si was 49.95-913.57, 99.98-2872.18, 22.48-429.31, 1.85-6.33, 0.17-6.01, and 0.04-0.91, respectively. 2) The significant differences in C, N, P, and Si stoichiometric characteristics were present between different organs or different forest ages. Leaves had the highest N and P content, while roots were the best enriched organ of Si element. Si content and C:Si were obviously correlated with forest age. 3) Significant N limitation was present in the Masson pine forests. And in the young and middle-aged forests, N limitation was more obvious. 4) The litter nutrients mainly came from branches. And the litter decomposed fast, which played an important role in the nutrient return of barren karst soil. The present results not only revealed the stoichiometric characteristics and cycling processes of C, N, P, and Si elements in the Masson pine forests, but also provided important scientific bases for the artificial management of Masson pine plantations in southern China.

Spatial distribution pattern and health risk of groundwater contamination by cadmium, manganese, lead and nitrate in groundwater of an arid area

Combining the results of base models to create a meta-model is one of the ensemble approaches known as stacking. In this study, stacking of five base learners, including eXtreme gradient boosting, random forest, feed-forward neural networks, generalized linear models with Lasso or Elastic Net regularization, and support vector machines, was used to study the spatial variation of Mn, Cd, Pb, and nitrate in Qom-Kahak Aquifers, Iran. The stacking strategy proved to be an effective substitute predictor for existing machine learning approaches due to its high accuracy and stability when compared to individual learners. Contrarily, there was not any best-performing base model for all of the involved parameters. For instance, in the case of cadmium, random forest produced the best results, with adjusted R2 and RMSE of 0.108 and 0.014, as opposed to 0.337 and 0.013 obtained by the stacking method. The Mn and Cd showed a tight link with phosphate by the redundancy analysis (RDA). This demonstrates the effect of phosphate fertilizers on agricultural operations. In order to analyze the causes of groundwater pollution, spatial methodologies can be used with multivariate analytic techniques, such as RDA, to help uncover hidden sources of contamination that would otherwise go undetected. Lead has a larger health risk than nitrate, according to the probabilistic health risk assessment, which found that 34.4% and 6.3% of the simulated values for children and adults, respectively, were higher than HQ = 1. Furthermore, cadmium exposure risk affected 84% of children and 47% of adults in the research area.

Identifying sources of acid mine drainage and major hydrogeochemical processes in abandoned mine adits (Southeast Shaanxi, China)

Acid mine drainage (AMD) has resulted in significant risks to both human health and the environment of the Han River watershed. In this study, water and sediment samples from typical mine adits were selected to investigate the hydrogeochemical characteristics and assess the environmental impacts of AMD. The interactions between coexisting chemical factors, geochemical processes in the mine adit, and the causes of AMD formation are discussed based on statistical analysis, mineralogical analysis, and geochemical modeling. The results showed that the hydrochemical types of AMD consisted of SO4-Ca-Mg, SO4-Ca, and SO4-Mg, with low pH and extremely high concentrations of Fe and SO42-. The release behaviors of most heavy metals are controlled by the oxidation of sulfide minerals (mainly pyrite) and the dissolution/precipitation of secondary minerals. Along the AMD pathway in the adit, the species of Fe-hydroxy secondary minerals tend to initially increase and later decrease. The inverse model results indicated that (1) oxidative dissolution of sulfide minerals, (2) interconversion of Fe-hydroxy secondary minerals, (3) precipitation of gypsum, and (4) neutralization by calcite are the main geochemical reactions in the adit, and chlorite might be the major neutralizing mineral of AMD with calcite. Furthermore, there were two sources of AMD in abandoned mine adits: oxidation of pyrite within the adits and infiltration of AMD from the overlying waste rock dumps. The findings can provide deeper insight into hydrogeochemical processes and the formation of AMD contamination produced in abandoned mine adits under similar mining and hydrogeological conditions.

Carbonate rocks as natural buffers: Exploring their environmental impact on heavy metals in sulfide deposits

Carbonate rocks are closely related to the genesis and spatial distribution of polymetallic sulfide deposits. The natural buffering of carbonate rocks can reduce the ecological impact of heavy metals produced by mining and smelting. Ignoring the buffering effect of carbonate rocks on the heavy metals in the mine environment leads to inaccurate ecological risk assessment, wasting land resources and funds. This study investigates Cd, Zn, and Pb distribution and speciation in the water and soil-rice system in the polymetallic sulfide deposit at Daxin, Guangxi. The study aims to reveal the effects of the natural buffering of carbonate rocks on the migration and transformation of heavy metals. The results show that the water Zn and Cd concentrations decreased from 1857.0 to 0.9 mg L-1 to 0.16 and 0.001 mg L-1, respectively, from the mining area to 4 km downstream. The natural buffering of carbonate increases the water pH from 2.80 to 7.64, resulting in a tendency for Cd, Zn, and Pb to separate from the aqueous phase and enrich the sediments. Soil Cd content in the mining area reached 110.0 mg kg-1 (mean value 55.88 mg kg-1), and rice Cd seriously exceeded the maximum limit. However, the weathering of carbonate reduces the migration ability and bioavailability of Cd. Soil Cd is mainly in the Fe-Mn bound and carbonate-bound fractions, resulting in lower Cd content in downstream soils (mean value 2.73 mg kg-1). Soil CaO, tFe2O3, and Mn hindered the uptake of soil Cd by rice rendering a lower exceedance of Cd in downstream rice. Therefore, this study recommends a farmland management plan under the premise of rice Cd content and integrated soil Cd content, which ensures food safety and fully utilizes farmland resources. This result provides a scientific basis for ecological risk assessment, mine environmental protection, and management in the carbonatite sulfide mine environment.

Groundwater quality evaluation based on water quality indices (WQI) using GIS: Maadher plain of Hodna, Northern Algeria

In a semi-arid region of Maadher, central Hodna (Algeria), groundwater is the main source for agricultural and domestic purposes. Anthropogenic activities and the presence of climate change's effects have a significant impact on the region's groundwater quality. This study's goals were to use water quality indices to evaluate the groundwater's quality and its suitability for drinking and irrigation, as well as to identify contaminated wells using a geographic information system (GIS) and the spatial interpolation techniques of ordinary kriging and inverse distance weighting (IDW). The results reveal that all water samples exceeded the World Health Organization's standards for nitrate ions and had alarming concentrations of calcium, chlorine, and sulfate (WHO). According to Piper's diagram, the groundwater hydrochemical facies is composed of the elements sulfate-chloride-nitrate-calcium (SO₄^2--Cl^-NO₃^--Ca²⁺ water type). The majority of samples fall into the poor water category, slightly more than 10% fall into the very poor water category, and less than 10% fall into the good to the excellent quality category, per the water quality indices, which classify samples in a similar manner. According to irrigation water indices, every sample is suitable for irrigation. Depending on the direction of groundwater flow, the spatial distributions of Ca²⁺, Na⁺, Mg²⁺, SO₄^2-, and Cl^- show that their concentrations are high north of the area and relatively low south of Maadher village (Fig. 3). Nitrate concentrations are high in the majority of samples, particularly those close to the Bousaada wadi. In most samples, particularly those close to the Bousaada wadi, nitrate levels are high. Various water quality models were described, and GIS spatial distribution maps were created using standard kriging and inverse distance weighting (IDW) techniques through selected semi-variograms predicted against measurements. To determine the origin of mineralization and the chemical processes that take place in the aquifer-which include the precipitation and dissolution of dolomite, calcite, aragonite, gypsum, anhydrite, and halite-the groundwater saturation index was calculated.

Trace Metals and Polycyclic Aromatic Hydrocarbons in the Snow Cover of the City of Nizhnevartovsk (Western Siberia, Russia)

The city of Nizhnevartovsk is one of the centers of oil production in Western Siberia (Russia). A survey of the contents of trace metals and metalloids (TMMs) and polycyclic aromatic hydrocarbons (PAHs) in the snow cover was conducted there. It was aimed to study insoluble particles in the snow where the predominant fraction of pollutants in urban areas is concentrated. In contrast to the background area, the deposition of TMMs in Nizhnevartovsk increases by 1-2 orders of magnitude. The deposition of V and Mn increases by 37 and 88 times, respectively, and the deposition of W increases at most (by 98 times). Abrasion of spikes of winter tires, abrasion of metal parts of vehicles, and combustion of motor fuels cause the pollution with W, Co, and V, respectively. The total content of 12 EPA PAHs in the particulate fraction of snow in the urban area averaged 148.2 ng l^-1, and the deposition rate was 17.0 μg/m². In contrast to the background area, the fraction of high molecular weight 5-6-ring PAHs significantly increases in the city, especially dibenzo(a,h)anthracene (DahA). The indicative ratios of PAHs showed that the snowpack composition was influenced by both petrogenic and pyrogenic sources. The proportion of pyrogenic sources is the highest in the low-rise residential area due to fuel combustion to produce heat and burning of household waste. The impact of motor transport is also major and is manifested in the maximum pollution in areas of heavy traffic. No emissions of PAHs from oil spills from the nearby Samotlor oil field have been identified. It is concluded that the hydrocarbon pollution of the atmosphere from the field weakens during the winter period compared to the warm season. Application of the integral TDF index characterizes the majority (72%) of the studied samples as lowly polluted, 24% of the observation sites are classified as moderately polluted, and one (4%), as highly polluted. The maximum TDF values are observed in the industrial area. The data obtained during the study allowed us to identify the central areas and sites along the roads with the heaviest traffic as the most contaminated areas of the city. This study can be a reference for air pollution monitoring in Nizhnevartovsk.

Driving effects and transfer prediction of heavy metal(loid)s in contaminated courtyard gardens using redundancy analysis and multilayer perceptron

The distribution and migration of heavy metal(loid)s in the soil-vegetable systems of courtyard gardens near mining areas have rarely been investigated, leading to potential food safety risks for residents. Moreover, the existing research is mainly focused on the total content of heavy metal(loid)s (tMetals) rather than the bioavailable contents (aMetals). In this study, 26 and 28 pairs of soil and vegetable samples were collected from the courtyard gardens near the Realgar mine in Baiyun Town and the lead-zinc (Pb-Zn) mine in Shuikoushan Town, respectively. The tMetal and aMetal of cadmium (Cd), mercury (Hg), arsenic (As), Pb, chromium (Cr), nickel (Ni), copper (Cu), Zn, manganese (Mn), iron (Fe), and calcium (Ca) in the samples were analyzed in this study. The results showed that courtyard gardens were polluted by various heavy metal(loid)s at varying degrees. The bioavailabilities of different metals varied significantly, among which Cd has the highest bioavailability (> 30%). In the transfer process of heavy metal(loid)s, the transfer rate (Tf) was ranked as soil-roots (1.50) > stems-leaves (1.07) > roots-stems (0.46) > stems-fruits (0.33). Redundancy analysis was used to evaluate the driving effects, and the results revealed that aCa, aZn, and aFe in soil could inhibit the absorption of aCd by plant roots. Soil organic matter was the inhibiting factor regarding the transfer of aAs and aCu, whereas it was also the promoting factor for transferring aPb, aNi, and aCr. Furthermore, the multilayer perceptron (MLP) could effectively predict the Tf of heavy metal(loid)s based on the aMetal. The R² values of the MLP were ranked as follows: 0.91 for As, 0.88 for Zn, 0.85 for Hg, 0.83 for Cu, 0.79 for Cr, 0.66 for Cd, 0.65 for Pb, and 0.52 for Ni. This study emphasizes the aMetal-based ecological characteristics and prediction ability. The study results are significant for guiding residents to strategize appropriate crop planting and ensure the safe production and consumption of vegetables.

A field study to estimate heavy metal concentrations in a soil-rice system: Application of graph neural networks

Accurate prediction of the concentration of heavy metals is of great significance for assessing the quality of agricultural products and reducing health risks. However, the complexity and interconnectivity of the farmland ecosystem restricts the improvement of the prediction accuracy of traditional methods. This research explored the application potential of graph neural network (GNN) technology, which can extract and learn information in large-scale networks in detail, in the field of heavy metal prediction for the first time. In this study, a heavy metal prediction model for rice, CoNet-GNN, was proposed with 17 environmental factors as input variables using the co-occurrence network and GNN. Experimental results using a dataset from a field study showed that the R² of CoNet-GNN for predicting Cd, Pb, Cr, As, and Hg had outstanding values of 0.872, 0.711, 0.683, 0.489, and 0.824, respectively. Sensitivity analysis further indicated that CoNet-GNN had good stability and robustness. Compared with random forest, gradient boosting, and multilayer perceptron, CoNet-GNN made a remarkable improvement to the prediction accuracy of all studied heavy metals. Therefore, CoNet-GNN can effectively simulate the rich relationships and laws between various factors in the soil-rice system and effectively characterize the influence diffusion path. Furthermore, it provides new ideas for heavy metal prediction based on network research methods and expands the technical scope of heavy metal evaluation.

Research trend and dynamical development of focusing on the global critical metals: a bibliometric analysis during 1991-2020

Critical metals are indispensable to a world seeking to transition away from carbon. Yet their extraction, processing, and application leave an unsustainable global environment and climate change footprint. To capture the development dynamics and research emphases of critical metals throughout their life cycle, this paper adopts bibliometrics to analyze the various stages of global critical metal flow in multiple dimensions to reveal the hot issues and future strategic trends. The research results indicate that the number of research papers on critical metals is annually rising, with remarkably rapid growth after 2010. Judging from the number of articles published by the authors and the citations, among the authors, Kawakita, Poettgen, Anwander, Inoue, and Dongmei Cui have a significant influence on critical metal research fields. The institutions with the most research on critical metals are universities, not research institutes. In addition, the focus has extended from a single discipline to the interdisciplinary development of multiple disciplines. Analysis of keywords shows that "rare metals" and "precious metals" are the most popular metals among the researched metals. The researched buzzwords of critical metals are disappearing, convergent, and merging over time. The research has focused on the mining and the whole life cycle process of extraction, treatment, and application. Based on the above characteristics, this paper tries to understand the dynamic development and evolution of global critical metals from multiple dimensions, resorting to giving a reference for follow-up-related research scholars.

Evaluation of MNA in A Chlorinated Solvents-Contaminated Aquifer Using Reactive Transport Modeling Coupled with Isotopic Fractionation Analysis

Groundwater contamination by chlorinated hydrocarbons is a worldwide problem that poses important challenges in remediation processes. In Italy, the Legislative Decree 152/06 defines the water quality limits to be obtained during the cleanup process. In situ bioremediation techniques are becoming increasingly important due to their affordability and, under the right conditions, because they can be more effective than conventional methodologies. In the initial feasibility study phase, the numerical modeling supports the reliability of each technique. Two different codes, BIOCHLOR and PHREEQC were discussed and compared assuming different field conditions. Isotopic Fractionation-Reactive Transport Models were then developed in one synthetic and one simple field case. From the results, the two codes were in agreement and also able to demonstrate the Monitored Natural Attenuation processes occurring at the dismissed site located in Italy. Finally, the PHREEQC model was used to forecast the remediation time frame by MNA, hypothesizing a complete source cleanup: a remediation time frame of about 10–11 years was achieved by means of natural attenuation processes.