Plant uptake of elements in soil and pore water: field observations versus model assumptions

Development of simplified probabilistic models for predicting phytoextraction timeframes of soil contaminants: demonstration at the DDX-contaminated Kolleberga tree nursery in Sweden

Phytoextraction, utilizing plants to remove soil contaminants, is a promising approach for environmental remediation but its application is often limited due to the long time requirements. This study aims to develop simplified and user-friendly probabilistic models to estimate the time required for phytoextraction of contaminants while considering uncertainties. More specifically we: i) developed probabilistic models for time estimation, ii) applied these models using site-specific data from a field experiment testing pumpkin (Cucurbita pepo ssp. pepo cv. Howden) for phytoextraction of DDT and its metabolites (ΣDDX), iii) compared timeframes derived from site-specific data with literature-derived estimates, and iv) investigated model sensitivity and uncertainties through various modelling scenarios. The models indicate that phytoextraction with pumpkin to reduce the initial total concentration of ΣDDX in the soil (10 mg/kg dw) to acceptable levels (1 mg/kg dw) at the test site is infeasible within a reasonable timeframe, with time estimates ranging from 48-123 years based on literature data or 3 570-9 120 years with site-specific data using the linear or first-order exponential model, respectively. Our results suggest that phytoextraction may only be feasible at lower initial ΣDDX concentrations (< 5 mg/kg dw) for soil polishing and that alternative phytomanagement strategies should be considered for this test site to manage the bioavailable fraction of DDX in the soil. The simplified modes presented can be useful tools in the communication with site owners and stakeholders about time approximations for planning phytoextraction interventions, thereby improving the decision basis for phytomanagement of contaminated sites.

Prediction models based on soil properties for evaluating the heavy metal uptake into Hordeum vulgare L. grown in agricultural soils amended with different rates of sewage sludge

The current study aims at forming new prediction models to be employed in the approximating the possible uptake of a range of 10 heavy metals (HMs) (Cd, Co, Cr, Cu, Fe, Mn, Mo, Ni, Pb and Zn) by Hordeum vulgare tissues including roots, shoots and grains following its growth in soil amended with sewage sludge (SS) using conditions employed in greenhouses. The present study determined an insignificant difference between the actual and predicted quantities of the HMs in the three tissues using t values. The majority of the predicted quantities of the HMs were acceptable with the exception of Cd in the shoots, Cu in grains and Pb in roots. Consequently, it is possible to use these models in assessing the cultivation of barley plants in soil amended with SS in a safe way, while simultaneously monitoring any potential risks to the health of humans.

Regression Models to Estimate Accumulation Capability of Six Metals by Two Macrophytes, Typha domingensis and Typha elephantina, Grown in an Arid Climate in the Mountainous Region of Taif, Saudi Arabia

In this study, we explored the capacity for two promising macrophytes, Typha domingensis and Typha elephantina, to be used for the surveillance of contamination by six metals, i.e., Cu, Fe, Mn, Ni, Pb, and Zn, in the mountainous area of Taif City in Saudi Arabia. Regression models were generated in order to forecast the metal concentrations within the plants’ organs, i.e., the leaves, flowers, peduncles, rhizomes, and roots. The sediment mean values for pH and the six metals varied amongst the sampling locations for the respective macrophytes, indicating that similar life forms fail to indicate equivalent concentrations. For instance, dissimilar concentrations of the metals under investigation were observed within the organs of the two rooted macrophytes. The research demonstrated that the segregation of metals is a regular event in all the investigated species in which the metal concentrations vary amongst the different plant constituent types. In the current study, T. domingensis and T. elephantina varied in their capacity to absorb specific metals; the bioaccumulation of metals was greater within T. domingensis. The relationships between the observed and model-estimated metal levels, in combination with high R2 and modest mean averaged errors, offered an appraisal of the goodness of fit of most of the generated models. The t-tests revealed no variations between the observed and model-estimated concentrations of the six metals under investigation within the organs of the two macrophytes, which emphasised the precision of the models. These models offer the ability to perform hazard appraisals within ecosystems and to determine the reference criteria for sediment metal concentration. Lastly, T. domingensis and T. elephantina exhibit the potential for bioaccumulation for the alleviation of contamination from metals.

Evaluation of uptake of eight metals by Sorghum bicolor grown in arable soil combined with sewage sludge based on prediction models

Prediction models were developed to estimate the extent to which aluminium, chromium, copper, iron, manganese, nickel, lead, and zinc were absorbed in the grains, leaves, stems, and roots of Sorghum bicolor cultivated in soil with various amendment rate of sewage sludge (0, 10, 20, 30, 40, and 50 g/kg) under greenhouse conditions. It was found that, aside from lead, all the examined metals occurred in significantly higher content in the roots compared to aerial tissues. Furthermore, the r-values were significantly negative between the bioconcentration factors of all metals, apart from aluminium and lead, and soil pH, whereas they were significantly positive between the bioconcentration factors, apart from lead, and soil organic matter content (OM). The r-values were typically significantly positive between the levels of all eight metals in the investigated tissues and in the soil. Moreover, the content of all the eight metals in the tissues exhibited a significant negative r-value with soil pH but a significant positive r-value with soil OM. The eight metal contents in the tissues given by the prediction models were quite similar to the real values, suggesting that the created models performed well, as shown by t-tests. It was thus concluded that prediction models were a viable option for evaluating how safe it was to grow S. bicolor in soils with sewage sludge content and at the same time for keeping track of possible human health hazards.

Biomonitoring potential of the native aquatic plant Typha domingensis by predicting trace metals accumulation in the Egyptian Lake Burullus

The ability of the native emergent macrophytes Typha domingensis for monitoring pollution with trace metals in Egyptian Lake Burullus was investigated through developing regression models for predicting their concentrations in the plant tissues. Plant samples (above-ground shoot and below-ground root and rhizome) as well as sediment samples were collected monthly during one growing season and analyzed. The association of trace metals concentration with several sediment characteristics (pH, organic matter, clay and silt) was also studied using the simple linear correlation coefficient (r). The concentration of some trace metals was significantly proportional to its values in the sediment such as Cd in the shoot, rhizome and root, Fe in the rhizome, and Ag in the root. There was positive relationship between the bioaccumulation factor (BAF) of Ag, Cd, Fe, Pb and Zn and sediment pH, organic matter and clay content. The developed regression models were significantly valid with high model efficiency and coefficient of determination, and low mean normalized average error. Trace metals were accumulated in the below-ground root and rhizome rather than in the shoot. Only Ag, Co and Ni provided bioaccumulation factor (BAF) < 1, while Ag was the only trace metal that could be transferred to some extend from the root to the rhizome and from there to the shoot [translocation factor (TF) 2.55 and 1.15, respectively]. Typha domingensis in Lake Burullus could be regarded as a bioindicator of trace metals pollution, and a good candidate as phytoremediator for Ag. The information on the phytoremediation capacity of T. domingensis certainly helps to solve contamination problems at Egyptian Lake Burullus region using this native plant.

Projecting impacts of climate change on metal mobilization at contaminated sites: Controls by the groundwater level

Heavy metal and metalloid contamination of topsoils from atmospheric deposition and release from landfills, agriculture, and industries is a widespread problem that is estimated to affect >50% of the EU's land surface. Influx of contaminants from soil to groundwater and their further downstream spread and impact on drinking water quality constitute a main exposure risk to humans. There is increasing concern that the present contaminant loading of groundwater and surface water systems may be altered, and potentially aggravated, by ongoing climate change, through large-scale impacts on recharge and groundwater levels. We investigated this issue by performing hydrogeological-geochemical model projections of changes in metal(loid) (As and Pb) mobilization in response to possible (climate-driven) future shifts in groundwater level and fluctuation amplitudes. We used observed initial conditions and boundary conditions for contaminated soils in the temperate climate zone. The results showed that relatively modest increases (0.2 m) in average levels of shallow groundwater systems, which may occur in Northern Europe within the coming two decades, can increase mass flows of metals through groundwater by a factor of 2-10. There is a similar risk of increased metal mobilization in regions subject to increased (seasonal or event-scale) amplitude of groundwater levels fluctuations. Neglecting groundwater level dynamics in predictive models can thus lead to considerable and systematic underestimation of metal mobilization and future changes. More generally, our results suggest that the key to quantifying impacts of climate change on metal mobilization is to understand how the contact between groundwater and the highly water-conducting and geochemically heterogeneous topsoil layers will change in the future.

Prediction models for monitoring heavy-metal accumulation by wheat (Triticum aestivum L.) plants grown in sewage sludge amended soil

Prediction of heavy-metal concentration in the edible parts of economic crops, based on their concentration in soil and other environmental factors, is urgently required for human risk assessment. The present investigation aimed to develop regression models for predicting heavy-metal concentration in wheat plants via their contents in sewage sludge amended soil, organic matter (OM) content and soil pH. The concentration of heavy metals in the plant tissues reflected its concentration in the soil with high Fe followed by Al, Mn, Cr, Zn, Ni, Co, Cu, and Pb. Soil OM content had a significant positive correlation with all investigated heavy-metal concentrations in the different tissues of wheat plants, while soil pH was negatively significant with most heavy metals except spike Pb and grain Cr. The bio-concentration factor of Al, Cu, and Zn from soil to wheat root was >1, while that of shoot, spikes, and grains was <1 for all heavy metals. Significantly valid regression models were developed with fluctuated coefficient of determination (R²), high model efficiency (ME) values and low mean normalized average error (MNAE). The significant positive correlations between the concentration of some heavy metals in the soil and the same in wheat tissues indicate the potential of this plant as a biomonitor for these metals in contaminated soils. The significant correlations between heavy-metal concentrations in soil and its properties (pH and OM) with metal concentrations in wheat plants support the prediction model as an appropriate option. This study recommends the use of models with R² greater than 50% and recommend other researchers to use our models according to their own specific conditions.

Improving prediction of metal uptake by Chinese cabbage (Brassica pekinensis L.) based on a soil-plant stepwise analysis

It is crucial to develop predictive soil-plant transfer (SPT) models to derive the threshold values of toxic metals in contaminated arable soils. The present study was designed to examine the heavy metal uptake pattern and to improve the prediction of metal uptake by Chinese cabbage grown in agricultural soils with multiple contamination by Cd, Cu, Ni, Pb, and Zn. Pot experiments were performed with 25 historically contaminated soils to determine metal accumulation in different parts of Chinese cabbage. Different soil bioavailable metal fractions were determined using different extractants (0.43M HNO3, 0.01M CaCl2, 0.005M DTPA, and 0.01M LWMOAs), soil moisture samplers, and diffusive gradients in thin films (DGT), and the fractions were compared with shoot metal uptake using both direct and stepwise multiple regression analysis. The stepwise approach significantly improved the prediction of metal uptake by cabbage over the direct approach. Strongly pH dependent or nonlinear relationships were found for the adsorption of root surfaces and in root-shoot uptake processes. Metals were linearly translocated from the root surface to the root. Therefore, the nonlinearity of uptake pattern is an important explanation for the inadequacy of the direct approach in some cases. The stepwise approach offers an alternative and robust method to study the pattern of metal uptake by Chinese cabbage (Brassica pekinensis L.).

A global sensitivity analysis of two-phase flow between fractured crystalline rock and bentonite with application to spent nuclear fuel disposal

Geological disposal of spent nuclear fuel in deep crystalline rock is investigated as a possible long term solution in Sweden and Finland. The fuel rods would be cased in copper canisters and deposited in vertical holes in the floor of deep underground tunnels, embedded within an engineered bentonite buffer. Recent experiments at the Äspö Hard Rock Laboratory (Sweden) showed that the high suction of unsaturated bentonite causes a de-saturation of the adjacent rock at the time of installation, which was also independently predicted in model experiments. Remaining air can affect the flow patterns and alter bio-geochemical conditions, influencing for instance the transport of radionuclides in the case of canister failure. However, thus far, observations and model realizations are limited in number and do not capture the conceivable range and combination of parameter values and boundary conditions that are relevant for the thousands of deposition holes envisioned in an operational final repository. In order to decrease this knowledge gap, we introduce here a formalized, systematic and fully integrated approach to study the combined impact of multiple factors on air saturation and dissolution predictions, investigating the impact of variability in parameter values, geometry and boundary conditions on bentonite buffer saturation times and on occurrences of rock de-saturation. Results showed that four parameters consistently appear in the top six influential factors for all considered output (target) variables: the position of the fracture intersecting the deposition hole, the background rock permeability, the suction representing the relative humidity in the open tunnel and the far field pressure value. The combined influence of these compared to the other parameters increases as one targets a larger fraction of the buffer reaching near-saturation. Strong interaction effects were found, which means that some parameter combinations yielded results (e.g., time to saturation) far outside the range of results obtained by the rest of the scenarios. This study also addresses potential air trapping by dissolution of part of the initial air content of the bentonite, showing that neglecting gas flow effects and trapping could lead to significant underestimation of the remaining air content and the duration of the initial aerobic phase of the repository.

Heavy metal accumulation in balsam pear and cowpea related to the geochemical factors of variable-charge soils in the Pearl River Delta, South China

Variable-charge (v-c) soils in subtropical areas contain considerable amounts of iron/aluminum (Fe/Al) oxides that can strongly influence the fate of heavy metals in agricultural ecosystems. However, the relationship between heavy metal accumulation in vegetables and the geochemical factors associated with v-c soils in subtropical regions remains unknown. The present study investigated heavy metal accumulation under field conditions in the Pearl River Delta (PRD) by measuring the content of 8 heavy metals (zinc (Zn), arsenic (As), copper (Cu), mercury (Hg), lead (Pb), chromium (Cr), nickel (Ni) and cadmium (Cd)) in 43 pairs of v-c soil and vegetable (balsam pear and cowpea) samples. Soil physicochemical properties including pH, texture, organic matter and oxide minerals (Fe2O3, SiO2, Al2O3, CaO, MgO, K2O and Na2O) were also analyzed. Heavy metal accumulation from soil to vegetables was assessed based on bioconcentration factors (BCFs). The results showed that soil extractable Fe, oxide minerals and chemical weathering indices of v-c soils strongly affected heavy metal accumulation, whereas the content of Zn, Cu, Cr and Ni in vegetables was strongly affected by the soil clay content. Significant correlations were found between the BCFs of heavy metals and oxide minerals. However, no significant relationship was found between pH and heavy metal accumulation (except for Cu) in balsam pear and cowpea. Correlation analyses showed that a lower oxalate/DCB- extractable Fe content might indicate greater heavy metal (Zn, Cu, Hg, Cr and Ni) accumulation in vegetables. Therefore, it can be deduced that oxalate/DCB- extractable Fe content is a critical geochemical factor that determines the bioavailability of heavy metals and that iron biogeochemical cycles play vital roles in the fate of heavy metals in vegetable fields in this area. These findings provide new insights into the behaviors and fate of heavy metals in subtropical v-c soils and can be used to develop possible guidelines for vegetable safety management.