Application of ridge regression to quantify marginal effects of collinear soil properties on phytoaccumulation of arsenic, cadmium, lead, and zinc

The effect of particle size on oral bioavailability and bioaccessibility of soil Ni from different sources

The goal of the work was to contribute to a unified approach to assessing the risk to human health of soil ingestion, for contaminated sites with elevated [Ni]. Robust relationships between in vitro bioaccessibility and in vivo bioavailability of Ni in various soils, with mechanistic understanding, would enable site-specific assessments of human exposure through soil ingestion. Four soils (three ultramafic Brunisols with geogenic Ni and one Organic soil with anthropogenic Ni) were sieved into PS < 10 μm, 10-41 μm, 41-70 μm, 70-105 μm, 105-150 μm, and 150-250 μm, the [Ni]T for which ranged from 560 to 103000 mg/kg. Mass fraction-adjusted [Ni]IVBA (SBRC gastric) for each soil fraction was similar whether calculated for all particles <250 μm or <150 μm %NiIVBA ranged from 3% to 16% of [Ni]T and %NiABA (accumulated Ni in urine, kidneys, and small intestine of Sprague Dawley rats gavaged with a soil) ranged from 0% to 0.49%. The correlation between these two measurements was weak (R2 = 0.06). Multiple linear dose response relationships attributing variation in %NiABA to %NiIVBA plus soil physicochemical parameters known to influence trace element availability in soils were developed. As many soil properties measured in this study were highly correlated, ridge regression enabled a predictive relationship where the effect of each parameter was its true contribution to variation in %NiABA. Using a ridge constant (k) of 0.012, %NiABA could be predicted from %NiIVBA adjusted for soil absorptive entities (OrgC, and Fe oxides (negative coefficients)) and soil pH (positive coefficient). %NiABA predicted from this relationship was very close to 1:1 with the observed %NiABA except at the lowest observed values which were lower than predicted. This study shows that as the conditions increasingly favour soil Ni solubility, more of the Ni was bioavailable; this generalization was true regardless of particle size or soil origin.

Predicting the modifying effect of soils on arsenic phytotoxicity and phytoaccumulation using soil properties or soil extraction methods

Soils have the ability to modify contaminant bioavailability and toxicity. Prediction the modifying effect of soil on arsenic phytoaccumulation and phytoavailability using either soil property data or soil chemical extraction data in risk assessment of contaminated soil is highly desirable. In this study, plant bioassays important to ecological receptors, were conducted with 20 soils with a wide range in chemical and physical soil properties to determine the relationships between As measured by soil chemical extraction (soil pore water, Bray-1, sodium phosphate solution, hydroxylamine hydrochloride, and acid ammonium oxalate) or soil physico/chemical properties on arsenic phytotoxicity and phytoaccumulation. Soil pore water As and Bray-1 extracted As were significantly (P < 0.01) correlated with lettuce tissue As and those extractants and sodium phosphate were correlated with ryegrass tissue As. Hydroxylamine and acid ammonium oxalate extractions did not correlate with plant bioassay endpoints. Simple regression results showed that lettuce tissue relative dry matter growth (RDMG) was inversely related to tissue As concentration (r² = 0.85, P < 0.01), with no significant relationship for ryegrass. Soil clay exhibited strong adsorption for As and significantly reduce tissue As for lettuce and ryegrass. In addition to clay content, reactive aluminum oxide (AlOx), reactive Fe oxide (FeOx) and eCEC was inversely related to ryegrass tissue As. Multiple regression equation was strongly predictive (r² = 0.83) for ryegrass tissue As (log transformed) using soil AlOx, organic matter, pH, and eCEC as variables. Soil properties can greatly reduce contaminant phytoavailability, plant exposure and risk, which should be considered when assessing contaminant exposure and site-specific risk in As-contaminated soils.

Modeling arsenic content in Brazilian soils: What is relevant?

Arsenic accumulation in the environment poses ecological and human health risks. A greater knowledge about soil total As content variability and its main drivers is strategic for maintaining soil security, helping public policies and environmental surveys. Considering the poor history of As studies in Brazil at the country's geographical scale, this work aimed to generate predictive models of topsoil As content using machine learning (ML) algorithms based on several environmental covariables representing soil forming factors, ranking their importance as explanatory covariables and for feeding group analysis. An unprecedented databank based on laboratory analyses (including rare earth elements), proximal and remote sensing, geographical information system operations, and pedological information were surveyed. The median soil As content ranged from 0.14 to 41.1 mg kg^-1 in reference soils, and 0.28 to 58.3 mg kg^-1 in agricultural soils. Recursive Feature Elimination Random Forest outperformed other ML algorithms, ranking as most important environmental covariables: temperature, soil organic carbon (SOC), clay, sand, and TiO₂. Four natural groups were statistically suggested (As content ± standard error in mg kg^-1): G1) with coarser texture, lower SOC, higher temperatures, and the lowest TiO₂ contents, has the lowest As content (2.24 ± 0.50), accomplishing different environmental conditions; G2) organic soils located in floodplains, medium TiO₂ and temperature, whose As content (3.78 ± 2.05) is slightly higher than G1, but lower than G3 and G4; G3) medium contents of As (7.14 ± 1.30), texture, SOC, TiO₂, and temperature, representing the largest number of points widespread throughout Brazil; G4) the largest contents of As (11.97 ± 1.62), SOC, and TiO₂, and the lowest sand content, with points located mainly across Southeastern Brazil with milder temperature. In the absence of soil As content, a common scenario in Brazil and in many Latin American countries, such natural groups could work as environmental indicators.

Bioaccessibility of trace elements as affected by soil parameters in smelter-contaminated agricultural soils: a statistical modeling approach

An investigation was undertaken to identify the most significant soil parameters that can be used to predict Cd, Pb, and Zn bioaccessibility in smelter-contaminated agricultural soils. A robust model was established from an extended database of soils by using: (i) a training set of 280 samples to select the main soil parameters, to define the best population to be taken into account for the model elaboration, and to construct multivariate regression models, and (ii) a test set of 110 samples to validate the ability of the regression models. Total carbonate, organic matter, sand, P(2)O(5), free Fe-Mn oxide, and pseudototal Al and trace element (TE) contents appeared as the main variables governing TE bioaccessibility. The statistical modeling approach was reasonably successful, indicating that the main soil factors influencing the bioaccessibility of TEs were taken into account and the predictions could be applicable for further risk evaluation in the studied area.

Exchangeable lead from prediction models relates to vetiver lead uptake in different soil types

Prediction models for exchangeable soil lead, published earlier in this journal (Andra et al. 2010a), were developed using a suite of native lead (Pb) paint-contaminated residential soils from two US cities heavily populated with homes constructed prior to Pb ban in paints. In this study, we tested the feasibility and practical applications of these prediction models for developing a phytoremediation design using vetiver grass (Vetiveria zizanioides), a Pb-tolerant plant. The models were used to estimate the exchangeable fraction of Pb available for vetiver uptake in four lead-spiked soil types, both acidic and alkaline, with varying physico-chemical properties and that are different from those used to build the prediction models. Results indicate a strong correlation for predictable exchangeable Pb with the observed fraction and as well with total Pb accumulated by vetiver grass grown in these soils. The correlation coefficient for the predicted vs. observed exchangeable Pb with p < 0.001 was 0.999, 0.996, 0.949, and 0.998 in the Immokalee, Millhopper, Pahokee Muck, and Tobosa soil type, respectively. Similarly, the correlation coefficient for the predicted exchangeable Pb vs. accumulated Pb in vetiver grass with p < 0.001 was 0.948, 0.983, 0.929, and 0.969 for each soil type, respectively. This study suggests that the success of a phytoremediation design could be assessed upfront by predicting the exchangeable Pb fraction in a given soil type based on its properties. This helps in modifying the soil conditions to enhance phytoextraction of Pb from contaminated soils.

Predicting potentially plant-available lead in contaminated residential sites

Lead (Pb)-based paints pose a serious health problem to people living in residential settings constructed prior to 1978. Children are at a greater risk to Pb exposure resulting from hand-to-mouth activity in Pb-contaminated residential soils. For soil Pb, the most environmentally friendly, potentially cheap, and visually unobtrusive in situ technology is phytoremediation. However, the limiting factor in a successful phytoremediation strategy is the availability of Pb for plant uptake. The purpose of this study was to establish a relationship between soil properties and the plant-available/exchangeable Pb fraction in the selected Pb-based paint-contaminated residential sites. We selected 20 such sites from two different locations (San Antonio, Texas and Baltimore, Maryland) with varying soil properties and total soil Pb concentrations ranging between 256 and 4,182 mg kg(-1). Despite higher Pb levels in these soils that exceeds US EPA permissible limit of 400 mg kg(-1), it is known that the plant-available Pb pools are significantly lower because of their sorption to soil components such as organic matter, Fe-Mn oxides, and clays, and their precipitation in the form of carbonates, hydroxides, and phosphates. Principal component analysis and hierarchical clustering showed that the potentially plant-available Pb fraction is controlled by soil pH in the case of acidic Baltimore soils, while soil organic matter plays a major role in alkaline San Antonio soils. Statistical models developed suggest that Pb is likely to be more available for plant uptake in Baltimore soils and a chelant-assisted phytoextraction strategy will be potentially necessary for San Antonio soils in mobilizing Pb from complexed pool to the plant-available pool. A thorough knowledge of site-specific factors is therefore essential in developing a suitable and successful phytoremediation model.

Predicting molybdenum toxicity to higher plants: influence of soil properties

The effect of soil properties on the toxicity of molybdenum (Mo) to four plant species was investigated. Soil organic carbon or ammonium-oxalate extractable Fe oxides were found to be the best predictors of the 50% effective dose (ED50) of Mo in different soils, explaining>65% of the variance in ED50 for four species except for ryegrass (26-38%). Molybdenum concentrations in soil solution and consequently plant uptake were increased when soil pH was artificially raised because sorption of Mo to amorphous oxides is greatly reduced at high pH. The addition of sulphate significantly decreased Mo uptake by oilseed rape. For risk assessment, we suggest that Mo toxicity values for plants should be normalised using soil amorphous iron oxide concentrations.

Acute metal stress in Populus tremula x P. alba (717-1B4 genotype): leaf and cambial proteome changes induced by cadmium 2+

The comprehension of metal homeostasis in plants requires the identification of molecular markers linked to stress tolerance. Proteomic changes in leaves and cambial zone of Populus tremula x P. alba (717-1B4 genotype) were analyzed after 61 days of exposure to cadmium (Cd) 360 mg/kg soil dry weight in pot-soil cultures. The treatment led to an acute Cd stress with a reduction of growth and photosynthesis. Cd stress induced changes in the display of 120 spots for leaf tissue and 153 spots for the cambial zone. It involved a reduced photosynthesis, resulting in a profound reorganisation of carbon and carbohydrate metabolisms in both tissues. Cambial cells underwent stress from the Cd actually present inside the tissue but also a deprivation of photosynthates caused by leaf stress. An important tissue specificity of the response was observed, according to the differences in cell structures and functions.