A comparative study of the sorption of O-PAHs and PAHs onto soils to understand their transport in soils and groundwater

Soil colloids can significantly enhance spreading of polybromodiphenyl ethers in groundwater by serving as an effective carrier

Polybromodiphenyl ethers (PBDEs), the widely used flame retardants, are common contaminants in surface soils at e-waste recycling sites. The association of PBDEs with soil colloids has been observed, indicating the potential risk to groundwater due to colloid-facilitated transport. However, the extent to which soil colloids may enhance the spreading of PBDEs in groundwater is largely unknown. Herein, we report the co-transport of decabromodiphenyl ester (BDE-209) and soil colloids in saturated porous media. The colloids released from a soil sample collected at an e-waste recycling site in Tianjin, China, contain high concentration of PBDEs, with BDE-209 being the most abundant conger (320 ± 30 mg/kg). The colloids exhibit relatively high mobility in saturated sand columns, under conditions commonly observed in groundwater environments. Notably, under all the tested conditions (i.e., varying flow velocity, pH, ionic species and ionic strength), the mass of eluted BDE-209 correlates linearly with that of eluted soil colloids, even though the mobility of the colloids varies markedly depending on the specific hydrodynamic and solution chemistry conditions involved. Additionally, the mass of BDE-209 retained in the columns also correlates strongly with the mass of retained colloids. Apparently, the PBDEs remain bound to soil colloids during transport in porous media. Findings in this study indicate that soil colloids may significantly promote the transport of PBDEs in groundwater by serving as an effective carrier. This might be the reason why the highly insoluble and adsorptive PBDEs are found in groundwater at some PBDE-contaminated sites.

The effects of co-existing acridine on adsorption-desorption behavior of carbazole in soils: Co-sorption and mechanism insight

Carbazole (CBZ) and acridine (ACR) are polycyclic aromatic nitrogen heterocycles (PANHs) widely found in combined contaminated soils, while investigations on organic-organic interactions have been very limited. In this study, batch experiments were carried out on five soils with different properties, taking CBZ as a representative of PANHs and ACR as a co-existing contaminant. The adsorption isotherms of CBZ (50-1000 μg/L) were nonlinear. Soil organic matter (SOM) and cation exchange capacity (CEC) showed positive correlations with CBZ adsorption-desorption coefficients. The adsorption mechanisms of CBZ involved hydrogen bonding, π-π interaction, and cation-π bonding. Different concentrations of ACR had varying effects on CBZ. The adsorption of CBZ was inhibited with 250 μg/L ACR. The cooperative adsorption was observed on three soils with increasing ACR concentration (1000 μg/L) and led to more pronounced nonlinear isotherms. The S-shaped isotherms of ACR indicated that ACR was adsorbed to the soil surface in a perpendicular configuration. New adsorption sites were created allowing for increased CBZ adsorption through π-π interaction with ACR. Therefore, variations in soil properties and potential impacts of co-existing contaminants should be well considered when assessing the combined pollution of site soil. This will contribute to a more accurate estimation of environmental and health risks.

A machine learning and experimental-based model for prediction of soil sorption capacity toward phenanthrene

Sorption by soil is the fundamental basis for environment fate of hydrophobic organic contaminants (HOCs), which varies significantly depending on diverse properties of soils. Therefore, a generalized approach to predict HOC sorption by soils is required. In this study, 488 data points were extracted from references and adopted to develop models for estimating the sorption capacities of phenanthrene in soils using six different machine learning (ML) approaches. The extreme gradient boosting (XGBT) model demonstrated the most favorable performance, achieving a coefficient of determination of 0.91 and root-mean-square errors of 0.24 for the testing dataset. The XGBT model's performance was further demonstrated by comparing with experimental data from batch sorption tests conducted on 20 soil samples collected from 17 provinces of China. The differences between the predicted values and the experimental values were statistically equal to zero (p = 0.14). Leveraging the XBGT model together with soil properties from the Harmonized World Soil Database, the distribution of sorption capacities in Chinese soils was successfully depicted on a national scale. This research is expected to contribute to a deeper understanding of the migration of persistent organic pollutants in terrestrial system. Furthermore, the established model holds implications for more precise and scientific soil environmental management.

Effect of waste-derived soil amendments on mitigating leaching impacts from municipal solid waste incineration (MSWI) ash

This study explores modifying a sandy soil with a low solid to liquid partitioning coefficient (Kd) by adding amendments including iron-rich industrial slag byproducts and biochars, which contain sorption sites for trace metals present in MSWI ash leachate (notably Sb, cited as a concern for reuse applications). Kd values for Sb were determined for the sandy soil to be as low as 1.6 ± 0.1 L/kg. With amendments, Kd values varied from 1.4 ± 0.2 L/kg for combined ash leachate exposed to a blend of sandy soil and 20% iron slag, to 990 L/kg for combined ash leachate exposed to a blend of sandy soil and 20% magnetic solids. A blend of 20% magnetic solids showed orders of magnitude increase beyond 100% sandy soil. The biochars showed limited capacity to reduce leached Sb in the ash-derived leachate, which is likely due to negative surface charges of the biochars and Sb at basic pH. A risk assessment (US EPA IWEM) performed using experimental Kd for each blend suggests that using soil amendments could reduce leached concentrations at points of concern, which could open additional avenues for ash reuse.

A machine learning based approach for estimating site-specific partition coefficient Kd of organic compounds: Application to nonionic pesticides

The partitioning coefficient K_d for a specific compound and location is not only a key input parameter of fate and transport models, but also critical in estimating the safety environmental concentration threshold. In order to reduce the uncertainty caused by non-linear interactions among environmental factors, machine learning based models for predicting K_d were developed in this work based on literature datasets of nonionic pesticides including molecular descriptors, soil properties, and experimental settings. The equilibrium concentration (C_e) values were specifically included for the reason that a varied range of K_d corresponding to a given C_e occurred in a real environment. By transforming 466 isotherms reported in the literature, 2618 paired equilibrium concentrations of liquid-solid (C_e-Q_e) data points were obtained. Results of SHapley Additive exPlanations revealed that soil organic carbon, C_e, and cavity formation were the most important. The distance-based applicability domain analysis was conducted for the 27 most frequently used pesticides with 15952 pieces of soil information from the HWSD-China dataset by setting three C_e scenarios (i.e., 10, 100, and 1000 μg L^-1). It was revealed the groups of compounds showing log K_d < 0.06 and log K_d > 1.19 were composed mostly of those with log K_ow of -0.800 and 5.50, respectively. When log K_d varied between 0.100 and 1.00, it was impacted by interactions among soil types, molecular descriptors, and C_e comprehensively, which accounted for 55% of the total 2618 calculations. It could be concluded that site-specific models developed in this work are necessary and practicable for the environmental risk assessment and management of nonionic organic compounds.

Hydroxylated polycyclic aromatic hydrocarbons possess inhibitory activity against alpha-glucosidase: An in vitro study using multispectroscopic techniques and molecular docking

Alpha-glucosidase (GAA) activity can be affected by exogenous substances. Hydroxylated polycyclic aromatic hydrocarbons (OH-PAHs) are typical metabolites of PAHs that can enter the body through various routes. The effects of 1-hydroxynaphthalene (1-OHNap) and 1-hydroxypyrene (1-OHPyr) on GAA activity and the potential mechanisms were investigated viamultispectroscopic methods and molecular docking. First-order derivative synchronous spectrofluorimetry was successfully applied to analyze the fluorescence quenching of GAA in the GAA-1-OHNap and GAA-1-OHPyr systems. 1-OHNap and 1-OHPyr had strong inhibitory effects on GAA activity. GAA could bind with 1-OHNap and 1-OHPyr in 1:1 mode with binding constants of 3.97 × 10⁴ and 9.42 × 10⁴ L/mol at 298 K. Hydrophobic interactions and hydrogen bonds played pivotal roles in the interactions. 1-OHNap was located closer to the active site of GAA than 1-OHPyr. This work suggests that the disturbance of glycometabolism by exogenous pollutants in the human body is worthy of attention and further investigation.