Extension of biotic ligand model to account for the effects of pH and phosphate in accurate prediction of arsenate toxicity

Derivation of ecotoxicologically acceptable Cu concentrations in soil from different land uses in South Korea

This study aimed to establish ecotoxicologically acceptable Cu concentrations for soil-residing species by integrating the biotic ligand model and the species sensitivity distribution. Statistical analyses were performed on 35 soil solution samples collected from four distinct land use sites: residential, agricultural, forested, and industrial regions. The environmental parameters of these samples, including pH, dissolved organic carbon (DOC), Ca2⁺, Mg2⁺, K⁺, and Na⁺ concentrations, exhibited wide variations across the four regions. Specifically, pH and the concentrations of Mg2⁺, K⁺, and Na⁺ showed significant variability. Additionally, a strong correlation was observed between pH and Ca2⁺, as well as between the DOC concentration and Mg2⁺ and Na⁺. Using the biotic ligand model, we derived the half-maximal effective activities of Cu (EC50{Cu2+}) for 10 soil organisms based on the chemical compositions of the soil solution samples. Additionally, a species sensitivity distribution approach was employed to determine the 5% hazardous concentration (HC5) for soil biota, which was closely associated with DOC and Na⁺ concentrations, with Mg2⁺ playing a secondary role. We attributed these relationships to the formation of DOC complexes that mitigate Cu toxicity, along with competitive interactions with cations. Notably, HC5 values did not differ significantly across sampling sites (p = 0.523). Clustering based on environmental factors grouped the samples into four clusters, each containing soils from different land use types. However, the third cluster included an outlier from agricultural soil due to its unusually high pH and DOC levels. These findings suggest that it is crucial to consider site-specific soil characteristics when determining ecotoxicologically acceptable Cu concentrations, and soil solution characteristics do not always align with specific land use patterns.

Extension of a biotic ligand model for predicting the toxicity of neodymium to wheat: The effects of pH, Ca2+ and Mg2

The damage excessive neodymium (Nd) causes to animals and plants should not be underestimated. However, there is little research on the impact of pH and associated ions on the toxicity of Nd. Here, a biotic ligand model (BLM) was expanded to predict the effects of pH and chief anions on the toxic impact of Nd on wheat root elongation in a simulated soil solution. The results suggested that Nd3+ and NdOH2+ were the major ions causing phytotoxicity to wheat roots at pH values of 4.5-7.0. The Nd toxicity decreased as the activities of H+, Ca2+, and Mg2+ increased but not when the activities of K+ and Na+ increased. The results indicated that H+, Ca2+, and Mg2+ competed with Nd for binding sites. An extended BLM was developed to consider the effects of pH, H+, Ca2+, and Mg2+, and the following stability constants were obtained: logKNdBL = 2.51, logKNdOHBL = 3.90, logKHBL = 4.01, logKCaBL = 2.43, and logKMgBL = 2.70. The results demonstrated that the BLM could predict the Nd toxicity well while considering the competition of H+, Ca2+, Mg2+ and the toxic species Nd3+ and NdOH2+ for binding sites.

Toxicity of antimony to Daphnia magna: Influence of environmental factors, development of biotic ligand approach and biochemical response at environmental relevant concentrations

Acute toxicity of antimony pentavalent to neonatal Daphnia magna and the influence of water quality parameters were investigated, and enzymatic activities of organisms at environmentally relevant levels of antimony were determined. EC50 values of antimony to neonatal D. magna were 90.3 and 63.8 mg/L at 24 and 48 h of exposure, respectively. Dissolved organic matter (FA and HA) and cation (Ca2+, Mg2+ or Na+) had significant protective effects on D. magna against antimony toxicity. With increasing pH in the range from 7.4 to 8.5, increase of EC50 were observed due to the competition of OH- on biotic ligands. Based on the biotic ligand model (BLM) concept, stability constants for the binding of Sb(OH)6- and OH- to the biotic ligand were estimated, and the Log [Formula: see text] - and LogKXOH- were 3.137 and 2.859, respectively. Moreover, antimony exposure in low concentrations significantly increased MDA levels and maybe exert oxidative stress to the organisms. Antimony can also induce toxicity in D. magna by affecting oxidative stress and neurotransmitter systems. The relatively comprehensive toxicological data can contribute to the toxicity prediction and ecological risk assessments of antimony.

Comparative analysis of the capability of the extended biotic ligand model and machine learning approaches to predict arsenate toxicity

Assessment of inorganic arsenate (As(V)) is critical for ensuring a sustainable environment because of its adverse effects on humans and ecosystems. This study is the first to attempt to predict As(V) toxicity to the bioluminescent bacterium Aliivibrio fischeri exposed to varying As(V) dosages and environmental factors (pH and phosphate concentration) using six machine learning (ML)-guided models. The predicted toxicity values were compared with those predicted using the extended biotic ligand model (BLM) we previously developed to evaluate the toxic effect of oxyanion (i.e., As(V)). The relationship between the variables (input features) and toxicity (output) was found to play an important role in the prediction accuracy of each ML-guided model. The results indicated that the extended BLM had the highest prediction accuracy, with a root mean square error (RMSE) of 12.997. However, with an RMSE of 14.361, the multilayer perceptron (MLP) model exhibited quasi-accurate prediction, despite having been trained with a relatively small dataset (n = 256). In view of simplicity, an MLP model is compatible with an extended BLM and does not require expert knowledge for the derivation of specific parameters, such as binding fraction and binding constant values. Furthermore, with the development and employment of reliable in-situ sensing techniques, monitoring data are expected to be augmented faster to provide sufficient training data for the improvement of prediction accuracy which may, thus, allow it to outperform the extended BLM after obtaining sufficient data.

Quantitative ion character-activity relationship methods for assessing the ecotoxicity of soil metal(loid)s to lettuce

New pollution elements introduced by the rapid development of modern industry and agriculture may pose a serious threat to the soil ecosystem. To explore the ecotoxicity and risk of these elements, we systematically studied the acute toxicity of 18 metal(loid)s toward lettuce using hydroponic experiments and quantitative relationships between element toxicity and ionic characteristics using ion-grouping and ligand-binding theory methods, thereby establishing a quantitative ion character-activity relationship (QICAR) model for predicting the phytotoxicity threshold of data-poor elements. The toxicity of 18 ions to lettuce differed by more than four orders of magnitude (0.05-804.44 μM). Correlation and linear regression analysis showed that the ionic characteristics significantly associated with this toxicity explained only 23.8-50.3% of the toxicity variation (R2Adj = 0.238-0.503, p < 0.05). Relationships between toxicity and ionic properties significantly improved after separating metal(loid) ions into soft and hard, with R2Adj of 0.793 and 0.784 (p < 0.05), respectively. Three ligand-binding parameters showed different predictive effects on lettuce metal(loid) toxicity. Compared with the binding constant of the biotic ligand model (log K) and the hard ligand scale (HLScale) (p > 0.05), the softness consensus scale (σCon) was significantly correlated with toxicity and provided the best prediction (R2Adj = 0.844, p < 0.001). We selected QICAR equations based on soft-hard ion classification and σCon methods to predict phytotoxicity of metal(loid)s, which can be used to derive ecotoxicity for data-poor metal(loid)s, providing preliminary assessment of their ecological risks.

Microwave-enhanced simultaneous immobilization of lead and arsenic in a field soil using ferrous sulfate

Remediation of soil contaminated by mixed heavy metals and metalloids has been a major challenge in the global environmental field. To address this critical issue, we tested a new technology for simultaneous immobilization of lead (Pb) and arsenic (As) in a field contaminated soil using a microwave-assisted FeSO₄·7H₂O treatment process. The process was able to rapidly reduce the TCLP-based leachability of Pb from 12.74 to 0.1 mg L^-1 and As from 2.704 to 0.002 mg L^-1 (MW power = 800 W, Irradiation time = 20 min, and FeSO₄·7H₂O = 4 wt%). The effects of FeSO₄·7H₂O dosage, microwave power, and irradiation time were determined and optimized. After 365 days of curing under atmospheric conditions, the TCLP-leached concentration of Pb and As in the treated soil remained below the regulatory limits of 0.1 and 0.002 mg L^-1, respectively. The microwave irradiation promoted the formation of insoluble PbSO₄(s) and Fe₃(AsO₄)₂·8H₂O(s), resulting in the long-term stability of Pb and As in the soil. The technology offers an effective alternative for remediation of Pb- and/or As-contaminated soil and groundwater.

Investigating and modeling the toxicity of arsenate on wheat root elongation: Assessing the effects of pH, sulfate and phosphate

Excessive arsenic in soil and groundwater will not only seriously affect the growth of plants, but also endanger human health through the food chain. However, there are few studies on the effects of metalloid speciation and anion competition on the toxicity of arsenate [As(Ⅴ)]. To investigate the effects of accompanying anions and pH on the toxicity of As(Ⅴ) on wheat root elongation, wheat roots were exposed to the concentrations of As(Ⅴ) in the solution ranged from 0 to 500 mM and different levels of pH (4.5-8.0) and different accompanying anions (H₂PO₄^-, SO₄^2-, NO₃^- and Cl^-) for five days. The root length of wheat was measured and the biotic ligand model (BLM) was developed to predict the potential toxicity of As(V) speciation to wheat roots. The results illustrated that EC50 of total As(V) (EC50{As(Ⅴ)_T}) values increased from 6.88 to 33.9 μM with increasing pH values from 4.5 to 8.0, suggesting that increasing pH alleviated As(Ⅴ) toxicity. The EC50{AsO₄^3-} and EC50{HAsO₄^2-} values increased from 0.001 to 4342 μM and from 0.0214 to 27.4 μM, respectively, while the EC50{H₂AsO₄^-} and EC50{H₃AsO₄} values sharply decreased from 6.62 to 2.68 μM and from 41.8 μM to 5.34 nm, respectively, when pH increased from 4.5 to 8.0. The toxicity of As(Ⅴ) decreased as the H₂PO₄^- and SO₄^2- activities increased but not when the activities of NO₃^- and Cl^- increased, indicating that SO₄^2- and H₂PO₄^- showed competitive effects with As(Ⅴ) on the binding sites. Based on BLM theory, the stability constants were obtained: [Formula: see text] = 3.70; [Formula: see text] = 4.08; [Formula: see text] = 4.77; [Formula: see text] = 6.50; [Formula: see text] = 2.09 and [Formula: see text] = 1.86, with f_AsBL^50%= 0.30 and β = 1.73. Results implied that BLM performed well in As(Ⅴ) toxicity prediction when coupling toxic species AsO₄^3-, HAsO₄^2-, H₂AsO₄^-, and H₃AsO₄, and the competition of SO₄^2- and H₂PO₄^- for binding sites. The current study provides a useful tool to accurately predict As(V) toxicity to wheat roots.

Interspecies-Extrapolated Biotic Ligand Model to Predict Arsenate Toxicity to Terrestrial Plants with Consideration of Cell Membrane Surface Electrical Potential

Arsenic is a metalloid that is highly toxic to living organisms in the environment. In this study, toxicity caused by inorganic arsenate (As(V)) to terrestrial plants, such as barley Hordeum vulgare and wheat Triticum aestivum, was predicted using the existing biotic ligand model (BLM) for bioluminescent Aliivibrio fischeri via interspecies extrapolation. Concurrently, the concept of cell plasma membrane electrical potential (Ψ₀) was incorporated into the extrapolated BLM to improve the model predictability in the presence of major cations such as Ca²⁺. The 50% effective As(V) toxicity (EC₅₀{HAsO₄²⁻}) to H. vulgare decreased from 45.1 ± 4.34 to 15.0 ± 2.60 µM as Ca²⁺ concentration increased from 0.2 to 20 mM owing to the accumulation of H₂AsO₄⁻ and HAsO₄²⁻ on the cell membrane surface. The extrapolated BLM, which only considered inherent sensitivity, explained well the alteration of As(V) toxicity to H. vulgare and T. aestivum by Ca²⁺ with in an order of magnitude, when considering a linear relationship between Ψ₀ and EC₅₀{HAsO₄²⁻}.

Predicting the thresholds of metals with limited toxicity data with invertebrates in standard soils using quantitative ion character-activity relationships (QICAR)

Terrestrial invertebrates are often used as indicator organisms in ecological risk assessments. However, determining the risk of metals to invertebrates is laborious and time-consuming due to the lengthy testing and ethical approval procedures. In this study, a review of the literature was conducted to provide toxicity data for two standard soils (OECD and LUFA 2.2). An attempt was made to establish models for predicting the toxicity of elements to invertebrates using quantitative ion character-activity relationships (QICARs). In OECD soil, the element toxicity of four groups (Enchytraeus albidus mortality and reproduction, Folsomia candida and Eisenia fetida reproduction) showed significant correlations with atomic number, atomic mass and atomic ionization potential (0.852 ≤ R² ≤ 0.989, P < 0.05). For LUFA 2.2 soil, polarization force parameters and boiling point were most significant parameters for toxicity values of F. candida and Enchytraeus crypticus, respectively (0.866 ≤ R² ≤ 0.962, P < 0.05). Finally, QICAR models were established, and LC₅₀ or EC₅₀ of elements were predicted. Then, models were verified using standard and natural soils, and showed that errors between observed and predicted logLC₅₀/EC₅₀ were mostly < 0.5 orders of magnitude. Thus, the developed QICAR models have potential for predicting the toxicity of elements for soils.

Sorption of arsenate(Ⅴ) to naturally occurring secondary iron minerals formed at different conditions: The relationship between sorption behavior and surface structure

Arsenic (As) is a problematic pollutant that can cause cancer and other chronic diseases due to its potential toxicity. Iron (oxyhydr)oxides can readily sorb As and play important roles in the geochemical cycle of As. Attention has mainly been given to the affinity and mechanism of As sorption by synthetic pure iron (oxyhydr)oxides, and little is known about the relationship between As behavior and multicomponent secondary iron minerals (SIMs) naturally formed in acid mine drainage (AMD). To investigate this relationship, we performed sorption kinetics, isotherm and competitive sorption experiments to investigate As(V) sorption behaviors on naturally formed SIMs harvested from different runoff zones of an abandoned coal mine. Several spectroscopic analyses were used to evaluate the structural and component changes and phase transformation. Three environmental SIMs formed at nascent (n-SIM), transient (t-SIM) and mature (m-SIM) stages were determined to be similar in the element components of Fe, S and O but different in structure. As(V) sorption behaviors on these environmental SIMs followed a pseudo-second-order kinetic model, and the sorption extent followed the sequence of n-SIM > t-SIM > m-SIM. As(V) sorption is not significantly influenced by Na⁺/Ca²⁺ concentration or ionic strength except for that of PO₄^3-, and it slightly decreases as the Cr(Ⅲ) concentration increases but increases with increasing Sb(Ⅲ)/(V) concentration. The results of spectral analyses indicate that As(V) immobilization mainly depends on exchange with SO₄^2- and surface complexation, along with the phase transformation of schwertmannite/jarosite to goethite and other phases. These findings are helpful for better understanding the geochemical behaviors of As(V) associated with environmental SIMs.

Biotic ligand modeling to predict the toxicity of HWO4- and WO42- on wheat root elongation in solution cultures: Effects of pH and accompanying anions

Increasing evidence demonstrates that hexavalent tungsten (W(VI)) can affect the survival of various organisms. This study explored the influences of pH and common anions on W(VI) toxicity on wheat and established a biotic ligand model (BLM) for predicting W(VI) toxicity. It was found that as the pH value increased from 6.0 to 8.5, the EC50[W(VI)]_T values increased greatly from 24.7 to 46.6 μM, indicating that increasing pH values can alleviate W(VI) toxicity. A linear relationship between the ratio of HWO₄^- to WO₄^2- and EC50{WO₄^2-} indicated that WO₄^2- and HWO₄^- were two toxic species of W(VI). The toxicity of W(VI) decreased as the H₂PO₄^- and SO₄^2- activities increased but not when the activities of Cl^- and NO₃^- increased, demonstrating that the competition from H₂PO₄^- and SO₄^2- significantly influenced W(VI) toxicity. By applying BLM theory, the stability constants for HWO₄^-, WO₄^2-, H₂PO₄^-, and SO₄^2- were obtained: logK_WO4BL = 4.08, logK_HWO4BL = 6.44, logK_H2PO4BL = 2.09, and logK_SO4BL = 1.87, f_WBL^50% = 0.300, β = 1.99. Results demonstrated that BLM outperformed the free metal activity model(FIAM) in predicting W(VI) toxicity when considering the influences of pH, W(VI) species, and H₂PO₄^- and SO₄^2- competition for active ligand sites.

Modeling of selenite toxicity to wheat root elongation using biotic ligand model: Considering the effects of pH and phosphate anion

It has not been well understood that the binding affinity and potential toxicity of different chemical forms of selenite (Se(IV)), which are predominant forms of selenium with plant availability. The influences of pH and major anions on Se(IV) toxicity to wheat root elongation were determined in solutions and modeled based on the biotic ligand model (BLM) and free ion activity model (FIAM) concepts. Results showed that EC50[Se(IV)]_T values increased from 164 to 273 μM as the pH raised from 4.5 to 8.0, indicating the increase of pH induced weakened Se(IV) toxicity. The EC50{SeO₃^2-} values increased from 0.019 to 71.3 μM while the EC50{H₂SeO₃} values sharply decreased from 2.08 μM to 0.760 nM with the pH increasing from 4.5 to 8.0. The effect of pH on Se(IV) toxicity could be explained by the changes of Se(IV) species in different pH solutions as H₂SeO₃, HSeO₃^- and SeO₃^2- were differently toxic to wheat root elongation. The toxicity of Se(IV) decreased with increasing H₂PO₄^- activity but not for SO₄^2-, NO₃^- and Cl^- activities, indicating that only H₂PO₄^- had a competitive effect with Se(IV) on the binding sites. A site-specific BLM was developed to count in effects of pH and H₂PO₄^-, and stability constants of H₂SeO₃, HSeO₃^-, SeO₃^2- and H₂PO₄^- to the binding sites were obtained: log [Formula: see text]  = 4.96, log [Formula: see text]  = 3.47, log [Formula: see text]  = 2.56 and log [Formula: see text]  = 2.00. Results implied that BLM performed much better than FIAM in the wheat root elongation prediction when coupling toxic species H₂SeO₃, HSeO₃^-, SeO₃^2-, and the competitions of H₂PO₄^- for the binding sites while developing the Se(IV)-BLM.

Extension of a biotic ligand model for predicting the toxicity of metalloid selenate to wheat: The effects of pH, phosphate and sulphate

It has not been well understood that the influences of pH and accompanying anions on the toxicity of selenate (Se(VI)). The influences of pH and major anions on Se(VI) toxicity to wheat root elongation were determined and modeled based on the biotic ligand model (BLM) and free ion activity model (FIAM) concepts. Results showed that EC50[Se(VI)]_T values increased from 162 to 251 μM as the pH values increased from 4.5 to 8.0, indicating that the pH increases alleviated the Se(VI) toxicity. The EC50{SeO₄^2-} values increased from 133 to 203 μM while the EC50{HSeO₄^-} values sharply decreased from 210 to 0.102 nM with the pH increasing from 4.5 to 8.0. The effect of pH on Se(VI) toxicity could be explained by the changes of Se(VI) species in different pH solutions as SeO₄^2- and HSeO₄^-were differently toxic to wheat root elongation. The toxicity of Se(VI) decreased with the increasing activities of H₂PO₄^- and SO₄^2- but not for NO₃^- and Cl^- activities, indicating that only H₂PO₄^- and SO₄^2- had competitive effects with Se(VI) on the binding sites. An extended BLM was developed to consider effects of pH, phosphate and sulphate, and stability constants of SeO₄^2-, HSeO₄^-, H₂PO₄^- and SO₄^2- to the binding sites were obtained: log [Formula: see text]  = 3.45, log [Formula: see text]  = 5.98, log [Formula: see text]  = 2.05, log [Formula: see text]  = 1.85. Results implied that BLM performed much better than FIAM in the wheat root elongation prediction when coupling with toxic species SeO₄^2- and HSeO₄^-, and the competitions of H₂PO₄^- and SO₄^2- for the binding sites while developing the Se(VI)-BLM.