Modelling assessment of regional groundwater contamination due to historic smelter emissions of heavy metals

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.

Determination of conditioning factors for mapping nickel contamination susceptibility in groundwater in Kanchanaburi Province, Thailand, using random forest and maximum entropy

Groundwater pollution from nickel (Ni) has been a severe concern in Kanchanaburi Province, Thailand. Recent assessments revealed that the Ni concentration in groundwater, particularly in urban areas, often exceeded the permissible limit. The challenge for groundwater agencies is therefore to delineate regions with high susceptibility to Ni contamination. In this study, a novel modeling approach was applied to a dataset of 117 groundwater samples collected from Kanchanaburi Province between April and July 2021. Twenty site-specific initial variables were considered as influencing factors to Ni contamination. The Random Forest (RF) algorithm with Recursive Feature Elimination (RFE) function was used to select the fourteen most influencing variables. These variables were then used as input features to train a ME model to delineate the Ni contamination susceptibility at a high confidence (Area Under the Curve (AUC) validation value of 0.845). Ten input variables of the altitude, geology, land use, slope, soil type, distance to industrial areas, distance to mining areas, electric conductivity, oxidation-reduction potential, and groundwater depth were discovered in the most explaining the variation of spatial Ni contamination at very high (95.47 km²) and high (86.65 km²) susceptibility. This study devises the novel machine learning approach to identify the conditioning factors and map Ni contamination susceptibility in the groundwater, which provides a baseline dataset and reliable methods for the development of a sustainable groundwater management strategy.

The Impact of Climate Change on Metal Transport in a Lowland Catchment

This study investigates the impact of future climate change on heavy metal (i.e., Cd and Zn) transport from soils to surface waters in a contaminated lowland catchment. The WALRUS hydrological model is employed in a semi-distributed manner to simulate current and future hydrological fluxes in the Dommel catchment in the Netherlands. The model is forced with climate change projections and the simulated fluxes are used as input to a metal transport model that simulates heavy metal concentrations and loads in quickflow and baseflow pathways. Metal transport is simulated under baseline climate ("2000-2010") and future climate ("2090-2099") conditions including scenarios for no climate change and climate change. The outcomes show an increase in Cd and Zn loads and the mean flux-weighted Cd and Zn concentrations in the discharged runoff, which is attributed to breakthrough of heavy metals from the soil system. Due to climate change, runoff enhances and leaching is accelerated, resulting in enhanced Cd and Zn loads. Mean flux-weighted concentrations in the discharged runoff increase during early summer and decrease during late summer and early autumn under the most extreme scenario of climate change. The results of this study provide improved understanding on the processes responsible for future changes in heavy metal contamination in lowland catchments.

Arsenopyrite weathering under conditions of simulated calcareous soil

Mining activities release arsenopyrite into calcareous soils where it undergoes weathering generating toxic compounds. The research evaluates the environmental impacts of these processes under semi-alkaline carbonated conditions. Electrochemical (cyclic voltammetry, chronoamperometry, EIS), spectroscopic (Raman, XPS), and microscopic (SEM, AFM, TEM) techniques are combined along with chemical analyses of leachates collected from simulated arsenopyrite weathering to comprehensively examine the interfacial mechanisms. Early oxidation stages enhance mineral reactivity through the formation of surface sulfur phases (e.g., S n (2-)/S(0)) with semiconductor properties, leading to oscillatory mineral reactivity. Subsequent steps entail the generation of intermediate siderite (FeCO3)-like, followed by the formation of low-compact mass sub-micro ferric oxyhydroxides (α, γ-FeOOH) with adsorbed arsenic (mainly As(III), and lower amounts of As(V)). In addition, weathering reactions can be influenced by accessible arsenic resulting in the formation of a symplesite (Fe3(AsO4)3)-like compound which is dependent on the amount of accessible arsenic in the system. It is proposed that arsenic release occurs via diffusion across secondary α, γ-FeOOH structures during arsenopyrite weathering. We suggest weathering mechanisms of arsenopyrite in calcareous soil and environmental implications based on experimental data.

Model-based Scenario Analysis of the Impact of Remediation Measures on Metal Leaching from Soils Contaminated by Historic Smelter Emissions

A spatially distributed model for leaching of Cd from the unsaturated zone was developed for the Belgian-Dutch transnational Kempen region. The model uses as input land-use maps, atmospheric deposition data, and soil data and is part of a larger regional model that simulates transport of Cd in soil, groundwater, and surface water. A new method for deriving deposition from multiple sites was validated using soil data in different wind directions. Leaching was calculated for the period 1890 to 2010 using a reconstruction of metal loads in the region. The model was able to reproduce spatial patterns of concentrations in soil and groundwater and predicted the concentration in shallow groundwater adequately well for the purpose of evaluating management options. For 42% of the data points, measurements and calculations were within the same concentration class. The model was used for forecasting under a reference scenario, an autonomous development scenario including climate change, and a scenario with implementation of remediation measures. The impact of autonomous development (under the most extreme scenario of climatic change) amounted to an increase of 10% in cumulative Cd flux after 100 yr as compared with the reference scenario. The impact of remediation measures was mainly local and is less pronounced (i.e., only 3% change in cumulative flux at the regional scale). The integrated model served as a tool to assist in developing management strategies and prioritization of remediation of the wide-spread heavy metal contamination in the region.

Prospective modeling with Hydrus-2D of 50 years Zn and Pb movements in low and moderately metal-contaminated agricultural soils

Results of detailed modeling of in situ redistribution of heavy metals in pedological horizons of low and moderately metal contaminated soils, considering distinctly different long-term land use, are scarcely reported in literature. We used Hydrus-2D software parameterized with abundant available local soil data to simulate future Zn and Pb movements in soils contaminated by metallurgical fallout in the 20th century. In recent work on comparing different modeling hypotheses, we validated a two-site reactive model set with adjusted chemical kinetic constant values by fitting the 2005 Zn and Pb concentration profiles in soils, with estimated 1901-1963 airborne Zn and Pb loads (Mallmann et al., 2012a). In the present work, we used the same approach to simulate 2005-2055 changes in Zn and Pb depth-distribution and soil-solution concentrations, comparing two hypotheses of chemical equilibrium: i) the validated two-site model (one site at equilibrium and the other involved in kinetic reactions with pore water) set with adjusted kinetic EDTA extraction constants, and ii) a non-linear one-surface site adsorption equilibrium model. Simulated transfers were found generally lower and more realistic when using the two-site model. Simulations showed that consistent Zn redistribution and loss occurred in the moderately contaminated soil until 2055, i.e., more than one century after the main metal deposition, but negligible in low contaminated soils. Transfer of Pb was small in the three soils and under both hypotheses. In 2055, simulated Zn outflow concentrations remained under threshold values for drinking water.

Modeling diffusive Cd and Zn contaminant emissions from soils to surface waters

Modeling contaminant transport of diffusive contaminants is generally difficult, as most contaminants are located in the top soil where soil properties will vary strongly with depth and often a strong gradient in contaminant concentrations exists. When groundwater periodically penetrates the contaminated layers, stationary models (like most 3D models) cannot adequately describe contaminant transport. Therefore we have combined a hydrological instationary model using a 1D distributed column approach with a simple geochemical model to describe contaminant transport in the soil. Special to this model is that it includes lateral drainage from the soil column to different types of surface waters, which makes it possible to calculate surface water emissions especially for fluctuating groundwater tables. To test this model approach, we used it to quantify surface water emissions from soils in a catchment in the Kempen area which has been diffusively contaminated with Cd and Zn by zinc smelters. We ran the model for the period 1880-2000, starting with an uncontaminated soil in 1880. The model could describe both water discharge, surface water concentrations and current soil contents of Cd and Zn well. Further the model calculations showed that a stationary approach would underestimate leaching to surface waters considerably.

Climate change impacts on the leaching of a heavy metal contamination in a small lowland catchment

The Keersop catchment (43km(2)) in the south of The Netherlands has been contaminated by the emissions of four zinc ore smelters. The objective of this study was to assess the effects of future projected climate change on the hydrology and the leaching of heavy metals (i.e. Cd and Zn) in the catchment. The numerical, quasi-2D, unsaturated zone Soil Water Atmosphere Plant model was used with 100-year simulated daily time series of precipitation and potential evapotranspiration. The time series are representative of stationary climates for the periods 1961-1990 ("baseline") and 2071-2100 ("future"). The time series of future climate were obtained by downscaling the results of eight regional climate model (RCM) experiments, driven by the SRES A2 emissions scenario, using change factors for a series of climate statistics and applying them to stochastic weather generator models. The time series are characterized by increased precipitation in winter, less precipitation in summer, and higher air temperatures (between 2°C and 5°C) throughout the year. Future climate scenarios project higher evapotranspiration rates, more irrigation, less drainage, lower discharge rates and lower groundwater levels, due to increased evapotranspiration and a slowing down of the groundwater system. As a result, lower concentrations of Cd and Zn in surface water are projected. The reduced leaching of heavy metals, due to drying of the catchment, showed a positive impact on a limited aspect of surface water quality.

Travel time distributions derived from particle tracking in models containing weak sinks

A travel time distribution based on a particle-tracking analysis in a ground water model containing weak sinks is often uncertain because whether a particle is discharged or allowed to pass through a weak sink is unresolved by particle-tracking theory. We present a probability-based method to derive an objective travel time distribution in models containing weak sinks. The method discharges a fraction of the particle at the weak sink and allows the remaining fraction to pass through the weak sink. The weight of the discharged fraction depends on the ratio of the sink flux to the influx into the weak sink cell. We tested this approach on a coarse (100 x 100 m) and a fine (25 x 25 m) horizontal resolution regional scale ground water model (34.5 x 24 km). We compared the travel time distributions in a small subcatchment derived from particle-tracking analysis with one derived from a transport model. We found that the particle-tracking analysis with the coarse model underestimated the travel time distribution of the catchment compared to the transport solution or a particle-tracking analysis with the fine model. The underestimation of travel times with the coarse model was a result of a large area covered by sink cells in this model and the more accurate flow patterns simulated by the fine model. The probability-based method presented here compares favorably with a solute transport solution and provides an accurate travel time distribution when used with a fine-resolution ground water model.