Mechanistic studies of congener-specific adsorption and bioaccumulation of polycyclic aromatic hydrocarbons and phthalates in soil by novel QSARs

Photodegradation of polycyclic aromatic hydrocarbons on soil surface: Kinetics and quantitative structure-activity relationship (QSAR) model development

Polycyclic aromatic hydrocarbons (PAHs) have attracted much attention because of their widespread existence and toxicity. Photodegradation is the main natural decay process of PAHs in soil. The photodegradation kinetics of benzopyrene (BaP) on 16 kinds of soils and 10 kinds of PAHs on Hebei (HE) soil were studied. The results showed that BaP had the highest degradation rate in Shaanxi (SN) soil (kobs = 0.11 min-1), and anthracene (Ant) was almost completely degraded after 16 h of irradiation in HE soil. Two quantitative structure-activity relationship (QSAR) models were established by the multiple linear regression (MLR) method. The developed QSAR models have good stability, robustness and predictability. The model revealed that the main factors affecting the photodegradation of PAHs are soil organic matter (SOM) and the energy gap between the highest occupied molecular orbital and the lowest unoccupied molecular orbital (Egap). SOM can function as a photosensitizer to induce the production of active species for photodegradation, thus favoring the photodegradation of PAHs. In addition, compounds with lower Egap are less stable and more reactive, and thus are more prone to photodegradation. Finally, the QSAR model was optimized using machine learning approach. The results of this study provide basic information on the photodegradation of PAHs and have important significance for predicting the environmental behavior of PAHs in soil.

Arsenic species in soil profiles from chemical weapons (CWs) burial sites of China: Contamination characteristics, degradation process and migration mechanism

In this study, soil profiles and pore water from Japanese abandoned arsenic-containing chemical weapons (CWs) burial sites in Dunhua, China were analyzed to understand the distribution of arsenic (As) contamination, degradation, and migration processes. Results of As species analysis showed that the As-containing agents underwent degradation with an average rate of 87.55 ± 0.13%, producing inorganic pentavalent arsenic (As5+) and organic arsenic such as 2-chlorovinylarsonic acid (CVAOA), triphenylarsenic (TPA), and phenylarsine oxide (PAO). Organic arsenic pollutants accounted for 1.27-18.20% of soil As. In the vertical profiles, total As concentrations peaked at about 40-60 cm burial depth, and the surface agricultural soil exhibited moderate to heavy contamination level, whereas the contamination level was insignificant below 1 m, reflecting As migration was relatively limited throughout the soil profile. Sequential extraction showed Fe/Al-bound As was the predominant fraction, and poorly-crystalline Fe minerals adsorbed 33.23-73.13% of soil As. Oxygen-susceptible surface soil formed poorly-crystalline Fe3+ minerals, greatly reducing downward migration of arsenic. However, the reduction of oxidizing conditions below 2 m soil depth may promote As activity and require attention.

Contribution of molecular structures and quantum chemistry technique to root concentration factor: An innovative application of interpretable machine learning

Root concentration factor (RCF) is a significant parameter to characterize uptake and accumulation of hazardous organic contaminants (HOCs) by plant roots. However, complex interactions among chemicals, plant roots and soil make it challenging to identify underlying mechanisms of uptake and accumulation of HOCs. Here, nine machine learning techniques were applied to investigate major factors controlling RCF based on variable combinations of molecular descriptors (MD), MACCS fingerprints, quantum chemistry descriptors (QCD) and three physicochemical properties related to chemical-soil-plant system. Compared to models with variables including MACCS fingerprints or solitary physicochemical properties, the XGBoost-6 model developed by the variable combination of MD, QCD and three physicochemical properties achieved the most remarkable performance, with R2 of 0.977. Model interpretation achieved by permutation variable importance and partial dependence plots revealed the vital importance of HOCs lipophilicity, lipid content of plant roots, soil organic matter content, the overall deformability and the molecular dispersive ability of HOCs for regulating RCF. The integration of MD and QCD with physicochemical properties could improve our knowledge of underlying mechanisms regarding HOCs accumulation in plant roots from innovative structural perspectives. Multiple variables combination-oriented performance improvement of model can be extended to other parameters prediction in environmental risk assessment field.

Predicting adsorption capacity of pharmaceuticals and personal care products on long-term aged microplastics using machine learning

We investigated the adsorption mechanism of 66 coexisting pharmaceuticals and personal care products (PPCPs) on microplastics treated with potassium persulfate, potassium hydroxide, and Fenton reagent for 54, 110, and 500 days. The total adsorption capacity (q_e) of 66 PPCPs on 15 original microplastics was 171.8 - 1043.7 μg/g, far below that of 177 long-term aged microplastics (7114.0 - 13,114.4 μg/g). Around 69.8% of q_e was primarily influenced by the total energy, energy of the highest occupied molecular orbital, and energy gap of PPCPs, calculated using the B3LYP/6-31 G* level. Furthermore, 111 aged microplastics exhibited similar total q_e values. Additionally, we developed predictive models based on attenuated total reflectance Fourier transform infrared spectroscopy to predict the individual and total q_e on 192 microplastics. These models, including the maximal information coefficient and gradient boosting decision tree regression, exhibited high accuracy with R_training² values of 0.9772 and 0.9661, respectively, and p-values below 0.001. Spectroscopic analysis and machine learning models highlighted surface functional group alterations and the importance of the 1528-1700 cm^-1 spectral region and carbon skeleton in the adsorption process. In summary, our findings contribute to understanding the adsorption of PPCPs on microplastics, particularly in the context of long-term aging effects.

Estimation and potential ecological risk assessment of multiphase PAEs in mangrove wetlands in Dongzhai Harbor, Hainan

With the application of plastic products, phthalates now widely occur in various environmental media. A large number of ecological risk assessment experiments have only been carried out on a single medium such as water or sediment. There are few reports of ecological risk assessments based on the phase states of phthalic acid esters (PAEs) such as the free dissolved state and the dissolved organic carbon (DOC) adsorption state. In this study, the concentrations of the free dissolved state, the DOC adsorption state, and the easily released PAEs in the sediments, as well as the dissolved organic carbon release potential and their influencing factors were calculated in the Dongzhaigang water body. The potential ecological risks posed by state-of-the-art PAEs were investigated. The average concentration of six freely dissolved PAEs in water was 0.542 (0.226-1.115) μg/L, accounting for 76.3 % of the total PAEs. The PAEs with the highest concentrations in the free dissolved state were di-n-butyl phthalate (DBP, 0.383 μg/L), followed by Di(2-ethylhexyl) phthalate (DEHP, 0.094 μg/L). The average concentration of all six PAEs (∑6PAEs) adsorbed by the DOC in the water was 0.172 μg/L, accounting for 23.74 % of all of the PAEs. The DOC-adsorbed DEHP (0.148 μg/L) accounted for about 86 % of the six adsorbed PAEs. Sediment organic carbon may affect the release potential of the DOC through changing the soluble organic carbon concentration. Most types of PAEs in water posed low risk to organisms. However, DBP posed low and medium risk to algae and crustaceans, and medium risk to fish. Medium or high risk of DEHP to algae, crustaceans and fish was observed. The high ecological risk of PAEs related to sediments were only found at S13 and S14. Generally, the potential ecological risk of PAEs in sediment was more stable than that in water bodies.

Novel insights into the predominant factors affecting the bioavailability of polycyclic aromatic hydrocarbons in industrial contaminated areas using PLS-developed model

Bioavailability is recognized as a useful technical standard for risk assessment and pollution rehabilitation. However, knowledge on the bioavailability of polycyclic aromatic hydrocarbons (PAHs) in contaminated site soils is still limited, especially concerning the influential mechanism. With an abundance of soil collections from nine industrial areas in China, the bioavailabilities, as conceptually defined as bioconcentration factors (BCFs) of PAHs were analyzed using biomimetic extraction of hydroxypropyl-β-cyclodextrin (HPCD). Apart from the total content of PAHs varying with the different pyrogenic sources, the BCFs were greatly dependent on the soil physicochemical properties from the spatial scale and inversely proportional to the number of rings. Pearson correlation analysis indicated a weak relationship between bioavailability and the soil dissolved organic matter (DOM), pH and particle size. To incorporate the soil physicochemical properties and structural characteristics of PAHs determined by density functional theory (DFT), the optimum model for bioavailability was developed for BCFs by partial least square (PLS) analysis. The PLS-derived model was shown to be predictive within the applicability domain (AD). The structural characteristics, e.g., molecular polarizability and frontier orbital energy level that favor the soil adsorption of PAH isomers via dispersion interactions, and electron exchanges were indicated to be more impactful on bioavailability than soil environmental factors. However, soil factors should not be neglected, because the pH, DOM, etc. were significantly influential. It makes sense that the higher DOM causes greater bioavailability via increasing the free-dissolved fractions of PAHs. Interestingly, the effect of pH on bioavailability was spectrally validated by excitation-emission matrix (EEM) fluorescence, showing that the interaction between DOM and pyrene strengthened the fluorescence quenching of chromophores with the decline in pH.

Surface functional groups determine adsorption of pharmaceuticals and personal care products on polypropylene microplastics

The pervasiveness of microplastics (MPs), which can absorb pharmaceuticals and personal care products (PPCPs), has a certain impact on pollutant migration in natural waters. The adsorption behaviors of PPCPs on the aged polypropylene (PP) followed the pseudo-second-order kinetics and Langmuir isotherm, and the adsorption capacity (q_e) on the aged PP was much higher than that on the fresh PP. The Weber-Morris and Boyd models confirmed that the liquid-film and intra-particle diffusion affected the adsorption of PPCPs on the aged PP while the surface diffusion was a rate-limiting step for the fresh PP. The analysis of SEM-EDS, BET, FT-IR, and XPS further showed that changes in the type and content of the surface functional groups of PP led to differences in adsorption capacity and adsorption interactions. The Dragon-descriptor-based LFER and the quantum-chemical-descriptor-based QSAR models reflected the difference in adsorption interaction mechanisms. The examined models showed that the adsorption of the fresh PP toward PPCPs relied on hydrophobic and hydrogen bonding interaction, while for the aged PP electrostatic interaction and hydrogen bonding controlled the adsorption. The findings clarified interactions between PPCPs and MPs and provided a theoretical basis for the assessment of environmental behavior and ecological risk when MPs and PPCPs coexist.

Organophosphate pesticides sequestered in tissues of a seagrass species - Zostera capensis from a polluted watershed

Organophosphate pesticides (OPPs) are persistent in the environment, but little information is available on their bioaccumulation in seagrass. In this study, the seagrass - Zostera capensis was collected from Swartkops Estuary in South Africa to investigate the bioaccumulation of OPPs from contaminated sediments and the water column. This plant was chosen because it grows abundantly in the estuary's intertidal zone, making it a viable phytoremediator in the urban environment. Extraction was performed by the QuEChERS method followed by GC-MS analysis. The mean concentration of ∑OPPs ranged from 0.01 to 0.03 μg/L for surface water; 6.20-13.35 μg/kg dw for deep-rooted sediments; 18.79-37.75 μg/kg dw for leaf tissues and 12.14-39.80 μg/kg dw for root tissues of Z. capensis. The biota-sediment accumulation factors (BSAFs) were greater than one, indicating the potential for Z. capensis to bioaccumulate and intercept the targeted pesticides. A weak insignificant correlation observed between log BSAFs and log Kow indicates that the bioaccumulation of OPPs in tissues of Z. capensis were not dependent on the Kow. Eight of the selected pesticides had root-leaf translocation factors (TFr-l) greater than 1, indicating that Z. capensis can transport these chemicals from roots to leaves. The results from this study implies that this plant species can clean up OPP contamination in the environment.

Prediction of phthalate acid esters degradation in soil using QSAR model: A combined consideration of soil properties and quantum chemical parameters

Phthalic acid esters (PAEs) are predominant hazardous substances and endocrine-disrupting compounds to be controlled in soil. The degradation behaviors of PAEs in soil had been long term concerned. Thus, the degradation rate (K) is important for assessing theexposure risk and is of great significance in evaluating the ecological risk of PAEs in soil environment. But by far, quantitative structure activity relationship (QSAR) models for PAEs degradation have rarely been considered in soil environment. In this study, quantum chemical parameters were considered along with soil properties as two kinds of descriptors in QSAR model. A total of 32 logk of PAEs were collected from reference and experiment. Degradation kinetics in soils were determined by pseudo-first order kinetic models. The residual concentration of PAEs in Udic ferrosols and Aquic cambisols suggesting a potential expose risks of PAEs to ecosystem in soil. The QSAR model between logk and quantum chemical parameters revealed that E_HOMO and qC- are two predominant factors in determining logk value. Furthermore,our study further indicated that soil organic matter (SOM) as new predictor contributes more to predict logk values of PAEs during degradation process than pH. Results from this study make a new contribution for methods to predict the degradation of PAEs in soil environment and highlight the potential to evaluate the environmental risks of degradation of PAEs.

Insights into the facet-dependent adsorption of antibiotic ciprofloxacin on goethite

Goethite is the most ubiquitous iron oxide mineral in soils, and adsorption of organic pollutants on goethite dominates the fate and transportation in the environment. In this study, the facet-dependent adsorption behavior of ciprofloxacin (CIP) on goethite was systematically investigated with in situ attenuated total reflectance Fourier transform infrared (ATR-FTIR) spectra and two-dimensional correlation analysis (2D-COS). The experimental results indicated that the goethite samples with higher facet proportion of {021}/{110} exhibited the better adsorption capacity compared to goethite with lower facet proportion of {021}/{110}. The reason is the more existence of singly coordinated sites with higher reactivity on the {021} facet. Moreover, CIP was found to be adsorbed on {021} and {110} facets by forming a tridentate complex involving the bridge coordination of bidentate ligands, H-bonding, and a bidentate chelate complex.

Recent Attempts in the Design of Efficient PVC Plasticizers with Reduced Migration

This paper reviews the current trends in replacing commonly used plasticizers in poly(vinyl chloride), PVC, formulations by new compounds with reduced migration, leading to the enhancement in mechanical properties and better plasticizing efficiency. Novel plasticizers have been divided into three groups depending on the replacement strategy, i.e., total replacement, partial replacement, and internal plasticizers. Chemical and physical properties of PVC formulations containing a wide range of plasticizers have been compared, allowing observance of the improvements in polymer performance in comparison to PVC plasticized with conventionally applied bis(2-ethylhexyl) phthalate, di-n-octyl phthalate, bis(2-ethylhexyl) terephthalate and di-n-octyl terephthalate. Among a variety of newly developed plasticizers, we have indicated those presenting excellent migration resistance and advantageous mechanical properties, as well as those derived from natural sources. A separate chapter has been dedicated to the description of a synergistic effect of a mixture of two plasticizers, primary and secondary, that benefits in migration suppression when secondary plasticizer is added to PVC blend.