A simple empirical model for phenanthrene adsorption on soil clay minerals

Role of humic acid on benzo[a]anthracene: Insights from aging on adsorption, speciation distribution and bioavailability

As a crucial component of soil organic matter, humic acid (HA) persists in soil and exert a complex interaction with hydrophobic organic pollutants, yet its specific role still remains unclear. In this study, HA was obtained from weathered coal via alkaline dissolution and acidic precipitation for the adsorption of benzo[a]anthracene (BAA). Subsequently, an aging simulation was employed to assess its long-term performance. The results demonstrated a theoretical maximal adsorption capacity of 0.29 mg/g for BAA on HA, and aging led to a 32.7% decline in its adsorption performance. While the speciation distribution of sorbed BAA remained largely unchanged. Combined with the characterization results, it can be inferred that the surface interactions between HA and BAA, including partitioning, van der Waals forces, hydrophobic interactions and hydrogen bonds, could be identified as the mechanisms underlying the desorbing BAA fraction, whereas strong hydrogen bonds, n-π and π-π staking contribute to the formation of non-desorbing BAA. The bound residue fraction of BAA was ascribed to the internal sequestration by porous structure in HA. Upon inoculation with BAA-degrading bacteria, all three fractions of sorbed BAA were decreased, demonstrating their availability. Further applied HA into soil media, a significant passivation effect was obtained as a substantial amount of desorbing and non-desorbing BAA was converted into bound-residue and non-extractable fractions. Overall, this study highlighted the potential of HA as adsorbent for mitigating PAHs environmental activity and its synergistic remediation with microorganisms.

Low-temperature treatment optimization for diesel-contaminated kaolin: Mutual impacts of generated pyrolytic carbon and particle agglomeration

Efficiency improvement in low-temperature treatment for diesel-contaminated sites is urgent because changes in soil properties and the generation of new substance during the remediation process can influence the duration and energy utilization. This paper focuses on low-temperature treatment optimization based on the mutual impacts of pyrolytic carbon and kaolin aggregation. Results reveal that the peak mass loss rate occurred between 100 and 150 °C, with minimal loss beyond 200 °C. Samples thermally treated at 150-200 °C exhibited darker colors, indicating pyrolytic carbon formation, corroborated by x-ray photoelectron spectroscopy (XPS), fourier transform infrared spectroscopy (FTIR), and three-dimensional fluorescence spectrum (3D-EEM) analyses. Additionally, diesel contamination influenced the fractal dimension of aggregates by influencing adhesion forces (<10000 mg/kg) and forming liquid bridges (≥10000 mg/kg) in untreated kaolin, resulting in an initial increase and subsequent fall in fractal dimension with increasing concentration. Decline rates of pollutant gas concentration were closely correlated with fractal dimension changes under thermal conditions due to pollutant volatilization and pyrolytic carbon formation. Based on the consistency between fractal dimension and decline rate, two critical remediation concentrations (C0) and temperatures (T0) indices were identified to optimize the low-temperature remediation.

AI-assisted systematic review on remediation of contaminated soils with PAHs and heavy metals

This systematic review addresses soil contamination by crude oil, a pressing global environmental issue, by exploring effective treatment strategies for sites co-contaminated with heavy metals and polycyclic aromatic hydrocarbons (PAHs). Our study aims to answer pivotal research questions: (1) What are the interaction mechanisms between heavy metals and PAHs in contaminated soils, and how do these affect the efficacy of different remediation methods? (2) What are the challenges and limitations of combined remediation techniques for co-contaminated soils compared to single-treatment methods in terms of efficiency, stability, and specificity? (3) How do various factors influence the effectiveness of biological, chemical, and physical remediation methods, both individually and combined, in co-contaminated soils, and what role do specific agents play in the degradation, immobilization, or removal of heavy metals and PAHs under diverse environmental conditions? (4) Do AI-powered search tools offer a superior alternative to conventional search methodologies for executing an exhaustive systematic review? Utilizing big-data analytics and AI tools such as Litmaps.co, ResearchRabbit, and MAXQDA, this study conducts a thorough analysis of remediation techniques for soils co-contaminated with heavy metals and PAHs. It emphasizes the significance of cation-π interactions and soil composition in dictating the solubility and behavior of these pollutants. The study pays particular attention to the interplay between heavy metals and PAH solubility, as well as the impact of soil properties like clay type and organic matter on heavy metal adsorption, which results in nonlinear sorption patterns. The research identifies a growing trend towards employing combined remediation techniques, especially biological strategies like biostimulation-bioaugmentation, noting their effectiveness in laboratory settings, albeit with potentially higher costs in field applications. Plants such as Medicago sativa L. and Solanum nigrum L. are highlighted for their effectiveness in phytoremediation, working synergistically with beneficial microbes to decompose contaminants. Furthermore, the study illustrates that the incorporation of biochar and surfactants, along with chelating agents like EDTA, can significantly enhance treatment efficiency. However, the research acknowledges that varying environmental conditions necessitate site-specific adaptations in remediation strategies. Life Cycle Assessment (LCA) findings indicate that while high-energy methods like Steam Enhanced Extraction and Thermal Resistivity - ERH are effective, they also entail substantial environmental and financial costs. Conversely, Natural Attenuation, despite being a low-impact and cost-effective option, may require prolonged monitoring. The study advocates for an integrative approach to soil remediation, one that harmoniously balances environmental sustainability, cost-effectiveness, and the specific requirements of contaminated sites. It underscores the necessity of a holistic strategy that combines various remediation methods, tailored to meet both regulatory compliance and the long-term sustainability of decontamination efforts.

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.

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.

Multiscale computational simulation of pollutant behavior at water interfaces

The investigation of pollutant behavior at water interfaces is critical to understand pollution in aquatic systems. Computational methods allow us to overcome the limitations of experimental analysis, delivering valuable insights into the chemical mechanisms and structural characteristics of pollutant behavior at interfaces across a range of scales, from microscopic to mesoscopic. Quantum mechanics, all-atom molecular dynamics simulations, coarse-grained molecular dynamics simulations, and dissipative particle dynamics simulations represent diverse molecular interaction calculation methods that can effectively model pollutant behavior at environmental interfaces from atomic to mesoscopic scales. These methods provide a rich variety of information on pollutant interactions with water surfaces. This review synthesizes the advancements in applying typical computational methods to the formation, adsorption, binding, and catalytic conversion of pollutants at water interfaces. By drawing on recent advancements, we critically examine the current challenges and offer our perspective on future directions. This review seeks to advance our understanding of computational techniques for elucidating pollutant behavior at water interfaces, a critical aspect of water research.

Adsorption of tetracycline by polycationic straw: Density functional theory calculation for mechanism and machine learning prediction for tetracyclines' remediation

The abuse of antibiotics causes serious environmental pollution, whose removal has become a hot topic. The adsorption of tetracycline (TC) on a prepared polycationic straw (MMS) was investigated. The kinetic, thermodynamic and adsorption isotherm models showed that adsorption of TC by MMS was a spontaneous, monolayer reaction with coexistence of physical and chemical process. Density functional theory indicated that the adsorption of TC resulted from electrostatic interaction and hydrogen bonds, which proved the mechanism of TC by macromolecular biomass for the first time. The expected and empirical values of TC adsorption showed a high fit degree, through predication of machine learning, indicating the feasibility and avoiding lots of experiments. Further, the adsorption ability of MMS to other TCs was predicted, founding that the highest removal efficiency was doxycycline, which provides a novel strategy for removal of other pollution and reduce of economic and time cost in practical application.

Toxicity and risk management of oil-spiked sediments by diluted bitumen for two freshwater benthic invertebrates

Diluted bitumen (dilbit) is an unconventional oil produced by the oil sands industry in Canada. Despite the knowledge available on hydrocarbon toxicity, the effects of diluted bitumen on benthic organisms are still largely unknown. Moreover, in Quebec there are only provisional threshold values of 164 mg/kg C₁₀-C₅₀ for chronic effects and 832 mg/kg for acute effects. The protectiveness of these values for benthic invertebrates has not been tested for heavy unconventional oils such as dilbit. Two benthic organisms, the larvae of Chironomus riparius and Hyalella azteca, were exposed to these two concentrations and to an intermediate concentration (416 mg/kg) of two dilbits (DB1 and DB2) and a heavy conventional oil (CO). The aim of the study was to assess the sublethal and lethal effects of spiked sediment by dilbit. The oil was rapidly degraded in the sediment, especially in the presence of C. riparius. Amphipods were much more sensitive to oil than chironomids. LC_50-14d values for H. azteca were 199 mg/kg C₁₀-C₅₀ for DB1, 299 mg/kg for DB2 and 8.42 mg/kg for CO compared to LC_50-7d values for C. riparius of 492 mg/kg for DB1, 563 mg/kg for DB2 and 514 mg/kg for CO. The size of the organisms was reduced compared to controls for both species. The defense enzymes (GST, GPx, SOD and CAT) were not good biomarkers in these two organisms for this type of contamination. The current provisional sediment quality criteria seem too permissive for heavy oils and should be lowered.

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.

Insight into core -shell microporous zinc silicate adsorbent to eliminate antibiotics in aquatic environment under the COVID-19 pandemic

Under the new crown pneumonia (COVID-19) epidemic, the intensive use of therapeutic drugs has caused certain hidden danger to the safety of the water environment. Therefore, the core-shell microporous zinc silicate (SiO₂@ZSO) was successfully prepared and used for the adsorption of chloroquine phosphate (CQ), tetracycline (TC) and ciprofloxacin (CIP) for eliminating the threat of COVID-19. The adsorption efficiencies of 20 mg L^-1 of CQ, TC and CIP by SiO₂@ZSO were all up to 60% after 5 min. The adsorption capacity of SiO₂@ZSO for CQ, TC and CIP can reach 49.01 mg g^-1, 56.06 mg g^-1 and 104.77 mg g^-1, respectively. The adsorption process is primarily physical adsorption, which is heterogeneous, spontaneous and preferential. Moreover, the effects of temperature, pH, salinity, and reusability on the adsorption of CQ, TC, and CIP on SiO₂@ZSO were investigated. The adsorption mechanism mainly involves electrostatic attraction, partitioning and hydrogen bonding, which is insightful through the changes of the elements and functional groups before and after adsorption. This work provides a solution to the problems faced by the treatment of pharmaceuticals wastewater under the COVID-19 epidemic.

Adsorption of Naphthalene on Clay Minerals: A Molecular Dynamics Simulation Study

Naphthalene, as one of the representative polycyclic aromatic hydrocarbons, widely exists in contaminated sites and is a potential threat to human health due to its high mobility in soil. The interaction between naphthalene and clay minerals is of great significance to the environmental behavior of naphthalene and the design of remediation technology. In this study, montmorillonite and kaolinite were selected as representative clay minerals. Naphthalene adsorption behavior on mineral surfaces and water-wet kaolinite surfaces was investigated using molecular dynamics (MD) simulation. The interaction energy was calculated to represent the interaction between naphthalene and soil fractions, and the relative concentration and density distribution of naphthalene was analyzed to describe the distribution of naphthalene on the clay surfaces. The self-diffusion coefficient of naphthalene was obtained to represent its mobility under different water content. The electron density calculation was performed to reveal the different adsorption behavior of naphthalene on different surfaces of kaolinite. The simulation results show that montmorillonite had a stronger interaction with naphthalene due to larger electrostatic interaction energy compared to kaolinite, and naphthalene distributed more intensively on the montmorillonite surface. With regards to kaolinite, naphthalene tended to be absorbed on the alumina octahedral surface rather than the silicon tetrahedral surface due to the weak hydron bond interaction. The results indicate that water impeded the adsorption of naphthalene, and the optimal initial thickness of water film, which was 10 Å, was put forward for the application of thermal remediation technology. Furthermore, the average interaction energies between water and mineral surfaces largely depended on the water content, and the competitive adsorption between water and naphthalene only occurred under absorbed and bound water conditions. Overall, the knowledge of naphthalene–soil fractions interaction gained in this study is critical to the understanding of the environmental behavior of naphthalene and the reference for remediation technology.

Structural Study of Nano-Clay and Its Effectiveness in Radiation Protection against X-rays

With the increasing applications of nuclear technology, radiation protection has become very important especially for the environment and the personnel close to radiation sources. Natural clays can be used potentially for shielding the X-ray radiations. In this study, the correlation between structural parameters and radiation shielding performance of natural clay extracted from Algerian Sahara (Adrar, Reggan, and Timimoune) was investigated. Phase composition and structural parameters (lattice parameters, average crystallite size, and microstrain) were determined by the Rietveld refinements of X-ray diffraction patterns in the frame of HighScore Plus software. The obtained results showed that the studied clays are nanocrystalline (nano-clay) since the calculated crystallite size was ≈3 nm for the feldspar phase. FTIR spectra confirmed the presence of all phases already detected by XRD analysis besides Biotite (around the band at 3558 cm⁻¹). The remaining bands corresponded to absorbed and adsorbed water (3432 cm⁻¹ and 1629 cm⁻¹, respectively) and atmospheric CO₂ (2356 cm⁻¹). The shielding properties (mass absorption coefficient—µ/ρ and radiative attenuation rate—RA) for (green-yellow, green, and red) clays of Adrar, (red, white, and white-red) clays of Reggan, and red clay of Timimoune at same energy level were examined. The results of clay samples were compared with each other. The obtained results indicated that the green clay of Adrar exhibited the superior radiation shielding, i.e., 99.8% and 243.4 cm²/g for radiative attenuation rate and mass absorption coefficient, respectively.