New insights into thermal desorption remediation of pyrene-contaminated soil based on an optimized numerical model

Optimized bacterial consortium-based strategies for bioremediation of PAHs-contaminated soils: insights into microbial communities, and functional responses

Microbial technologies hold great promise for in situ remediation of polycyclic aromatic hydrocarbons (PAHs)-contaminated soils. However, the selection of enhancement measures and corresponding remediation strategies remains insufficiently understood. In this study, a series of enhancement treatments, including bacterial consortium inoculation (comprising Achromobacter denitrificans BP1, Rhodococcus aetherivorans BW2, and Lysinibacillus sp. BS3), nutrient addition, and bio-ventilation, were implemented to develop effective in situ remediation strategies for PAHs-contaminated soil. Over a 60-day incubation, the enhancement treatments achieved phenanthrene (PHE) degradation efficiencies of 68.0-94.7 % and benzo[a]pyrene (BaP) degradation efficiencies of 12.9-82.4 %. Degradation rates across soil layers followed the pattern: upper layer > lower layer > middle layer. Enhancement treatments significantly boosted soil dehydrogenase (DH) and fluorescein diacetate (FDAH) activities. Among these, the sequential consortium inoculation with nutrient addition treatment (T6) demonstrated the highest degradation efficacy. In the treatment T6, the relative abundance of consortium genera was significantly increased, playing critical roles in PAHs degradation. The connectivity and stability of the soil bacterial network were enhanced, providing greater resilience to pollutants. Quantitative PCR analysis showed that the enhancement strategy increased RHDα-GN gene abundance by 1.98-fold at the initial and maintained a positive correlation with PAHs residues throughout the process (p < 0.05), and the phe gene exhibited a continuous upward trend during remediation, ultimately reaching 1.61-1.96 times its initial abundance. Overall, this study provides a strong candidate of integrated enhancement strategies to advance in situ bioremediation of PAH-contaminated sites.

Polycyclic Aromatic Hydrocarbons (PAHs) in Freshwater Systems: A Comprehensive Review of Sources, Distribution, and Ecotoxicological Impacts

This comprehensive review offers new perspectives on the distribution, sources, and ecotoxicological impacts of polycyclic aromatic hydrocarbons (PAHs) in freshwater systems. Unlike previous reviews, this work integrates recent findings on PAH dynamics within environmental matrices and emphasizes spatiotemporal variability across geographic regions. It critically examines both anthropogenic and natural sources, as well as the physical, chemical, and biological mechanisms driving PAH transport and fate. Special attention is given to the ecotoxicological effects of PAHs on freshwater organisms, including bioaccumulation, endocrine disruption, and genotoxicity. Notably, this review identifies key knowledge gaps and proposes an interdisciplinary framework to assess ecological risk and guide effective monitoring and management strategies for the protection of freshwater ecosystems.

Prediction of BTEX volatilization in polluted soil based on the sorption potential energy theory

Initial volatile concentration (Cs0) is a crucial parameter for the migration and diffusion of volatile organic pollutants (VOCs) from the soil to the atmosphere. The acquisition of Cs0 is, however, time-consuming and labor-intensive. This study developed a prediction model for Cs0 based on theoretical analysis and experimental simulations. The model was established by correlating the molecular kinetic and sorption potential energy. The pore structure and pore size distribution of the soil were analyzed based on the fractal theory of porous media, followed by calculating the sorption potential energy corresponding to each pore size. It was observed that the pore size distribution of soil influenced BTEX (benzene, toluene, ethylbenzene, and xylene) volatilization by impacting sorption potential energy. The soil parameters, such as organic matter and soil moisture content, and the initial concentration and physical properties of BTEX were coupled to the prediction model to ensure its practicability. Red soil was finally used to verify the accuracy and applicability of the model. The experimental and predicted values' maximum relative and root-mean-square errors were determined to be 24.2% and 11.7%, respectively. The model provides a simple, rapid, and accurate assessment of soil vapor emission content due to BTEX contamination. This study offers an economical and practical method for quantifying the amount of volatile BTEX in contaminated sites, providing a reference for its monitoring, control, and subsequent remediation.

Mechanisms and extended kinetic model of thermal desorption in organic-contaminated soil

Thermal desorption is a preferred technology for site remediation due to its various advantages. To ensure the effective removal of different pollutants in practical applications, it is necessary to understand the kinetic behaviors and removal mechanisms of pollutants in thermal desorption process. This paper explored the thermal desorption processes of five organic pollutants (nitrobenzene, naphthalene, n-dodecane, 1-nitronaphthalene, and phenanthrene) at 50-350 °C in two different subsoils with 6-18% moisture content. The results suggested that the thermal desorption process was well-fitted by the exponential decay model (R2 = 0.972-0.999) and could be divided into two distinct stages. The first stage was relatively fast and highly influenced by soil moisture, while the second stage showed a slower desorption rate due to the constraints imposed by the soil texture and structure. The influence of soil moisture on thermal desorption depended on the octanol/water partition coefficient (KOW) of pollutants. Pollutants with log KOW values lower than the critical value exhibited enhanced thermal desorption, while those with log KOW values higher than the critical value were inhibited. The critical value of log KOW might be between 3.33 and 4.46. Changes in soil texture and structure caused by heating promoted thermal desorption, especially for naphthalene, 1-nitronaphthalene and phenanthrene. The differences in texture and structure between the two soils diminished as the temperature increased. Finally, an extended kinetic model under changing temperature conditions was derived, and the simulation results for the two subsoils were very close to the actual thermogravimetric results, with the differences ranging from -1.28% to 0.94% and from -0.67% to 1.35%, respectively. These findings propose new insights into the influencing mechanisms of soil moisture and structure on the thermal desorption of organic pollutants. The extended kinetic model can provide reference for future kinetic research and guide practical site remediation.

A novel remediation strategy of mixed calcium peroxide and degrading bacteria for polycyclic aromatic hydrocarbon contaminated water

Polycyclic aromatic hydrocarbons (PAHs) are a class of toxic organic pollutants commonly detected in the aqueous phase. Traditional biodegradation is inefficient and advanced oxidation technologies are expensive. In the current study, a novel strategy was developed using calcium peroxide (CP) and PAH-degrading bacteria (PDB) to effectively augment PAH degradation by 28.62-59.22%. The PDB consisted of the genera Acinetobacter, Stenotrophomonas, and Comamonas. Applying the response surface model (RSM), the most appropriate parameters were identified, and the predictive degradation rates of phenanthrene (Phe), pyrene (Pyr), and ΣPAHs were 98%, 76%, and 84%, respectively. The constructed mixed system could reduce 90% of Phe and more than 60% of ΣPAHs and will perform better at pH 5-7 and lower salinity. Because PAHs tend to bind to dissolved organic matter (DOM) with larger molecular weights, humic acid (HA) had a larger negative effect on the PAH-degradation efficiency of the CP-PDB mixed system than fulvic acid (FA). The proposed PAH-degradation pathways in the mixed system were based on the detection of intermediates at different times. The investigation constructed and optimized a novel environmental PAH-degradation strategy. The synergistic application of PDB and oxidation was extended for organic contaminant degradation in aqueous environments.

Predicting thermal desorption efficiency of PAHs in contaminated sites based on an optimized machine learning approach

Thermal desorption (TD) remediation of polycyclic aromatic hydrocarbon (PAH)-contaminated sites is known for its high energy consumption and cost implications. The key to solving this issue lies in analyzing the PAHs desorption process, defining remediation endpoints, and developing prediction models to prevent excessive remediation. Establishing an accurate prediction model for remediation efficiency, which involves a systematic consideration of soil properties, TD parameters, and PAH characteristics, poses a significant challenge. This study employed a machine learning approach for predicting the remediation efficiency based on batch experiment results. The results revealed that the extreme gradient boosting (XGB) model yielded the most accurate predictions (R2 = 0.9832). The importance of features in the prediction process was quantified. A model optimization scheme was proposed, which involved integrating features based on their relevance, importance, and partial dependence. This integration not only reduced the number of input features but also enhanced prediction accuracy (R2 = 0.9867) without eliminating any features. The optimized XGB model was validated using soils from sites, demonstrating a prediction error of less than 30%. The optimized XGB model aids in identifying the most optimal conditions for thermal desorption to maximize the remediation efficiency of PAH-contaminated sites under relative cost and energy-saving conditions.