Evaluating petroleum contamination risk and implementing remedial measures in agricultural soil rely on indicators such as soil metal(loid)s and microbiome alterations. However, the response of these indicators to petroleum contamination remains under-investigated. The present study investigated the soil physicochemical features, metal(loid)s, microbial communities and networks, and phospholipid fatty acids (PLFAs) community structures in soil samples collected from long-(LC) and short-term (SC) petroleum-contaminated oil fields. The results showed that petroleum contamination increased the levels of soil total petroleum hydrocarbon, carbon, nitrogen, sulfur, phosphorus, calcium, copper, manganese, lead, and zinc, and decreased soil pH, microbial biomass, bacterial and fungal diversity. Petroleum led to a rise in the abundances of soil Proteobacteria, Ascomycota, Oleibacter, and Fusarium. Network analyses showed that the number of network links (Control vs. SC, LC = 1181 vs. 700, 1021), nodes (Control vs. SC, LC = 90 vs. 71, 83) and average degree (Control vs. SC, LC = 26.244 vs. 19.718, 24.602) recovered as the duration of contamination increased. Petroleum contamination also reduced the concentration of soil PLFAs, especially bacterial. These results demonstrate that brief exposure to high levels of petroleum contamination alters the physicochemical characteristics of the soil as well as the composition of soil metal(loid)s and microorganisms, leading to a less diverse soil microbial network that is more susceptible to damage. Future research should focus on the culturable microbiome of soil under petroleum contamination to provide a theoretical basis for further remediation. (c) 2025 The Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences. Published by Elsevier B.V.

The intrusion of petroleum into soil ecosystems causes severe environmental damage. A synergistic plant-microbe-electrochemical soil remediation technology offers a strategic and eco-friendly solution to address this issue. However, the significant mass transfer resistance in soil poses a major limitation for long-distance site remediation. This research introduces a novel technique that leverages water circulation driven by plant transpiration to facilitate the long-distance migration, adsorption, and electrochemical degradation of hydrocarbons. Experimental results demonstrate that the incorporation of Iris tectorum, polyurethane sponge (as an electrode support matrix), and water-retaining agents significantly enhanced soil water circulation, enabling the migration of soluble organic carbon over distances of up to 60 cm. Additionally, the application of a weak voltage (0.7 V) to the electrode further improved total organic carbon (TOC) removal, achieving a reduction of 193 +/- 71 mg/L. After 42 days of remediation, hydrological circulation accelerated the degradation of n-alkanes and aromatics, with removal efficiencies reaching 57 % and 44 %, respectively, within the 20-60 cm range in the microbial electrochemical cell (MEC) group. The functional microbiota, enriched with electroactive microorganisms, was effectively cultivated on the anode, with the total abundance of potential hydrocarbon-degrading bacteria increasing by 42 % compared to the control. Furthermore, a scalable configuration has been proposed, offering a novel perspective for multidimensional ecological soil remediation strategies.

Rampant industrial growth and urbanization have caused a wide range of hazardous contaminants to be released into the environment resulting in several environmental issues that could eventually lead to ecological disasters. The unscientific disposal of urban and industrial wastes is a critical issue as it can cause soil contamination, bioaccumulation in crops, groundwater contamination, and changes in soil characteristics. This article explores the impact of various industrial and urban wastes, including petroleum hydrocarbons (PHs), coal-fired fly ash, municipal solid waste (MSW) and wastewater (MWW), and biomedical waste (BMW) on various types of soil. The contamination and impact of each of these wastes on soil properties such as compaction characteristics, plasticity, permeability, consolidation characteristics, strength characteristics, pH, salinity, etc is studied in detail. Most of the studies indicate that these wastes contain heavy metals, organics, and other hazardous compounds. When applied to the soil, PHs tend to cause large settlements and reduction in plasticity, while the effect of coal-fired fly ash varies as it mainly depends on the type of soil. From the studies it was seen that the long-term application of MWW improves the soil health and properties for agricultural purposes. Significant soil settlements were observed in areas of MSW disposal, and studies show that MSW leachate also alters soil properties. While the impacts of direct BMW disposal have not been extensively studied, few researchers have concentrated on utilizing certain components of BMW, like face masks and nitrile gloves to enhance the geotechnical characteristics of weak soil. Soil remediation is required to mitigate the contamination caused by heavy metals and PHs from these wates to improve the soil quality for engineering and agricultural purposes, avert bioaccumulation in crops, and pose less environmental and public risks, and ecotoxicity. Coal-fired fly ash and biomedical waste ash contain compounds that promote pozzolanic reactions in soil, recycling and reuse as soil stabilizers offer an effective strategy for their reduction in the environment, thus complying to sustainable practices. In essence, this study offers a contemporary information on the above aspects by identifying the gaps for future research and mitigation strategies of contaminated soils.

Petroleum-based plastic resistance to biodegradation contributes to environmental pollution, depletes natural resources, and affects humans, animals, and plants. Plastic fragmentation into microplastics and nanoplastics further poses adverse effects on human health. Thus, switching to eco-friendly packaging holds great potential to combat these predicaments. Herein, soyhull lignocellulosic residue (SLR) was extracted using 20% NaOH treatment, solubilized in ZnCl2 solution and crosslinked the chains with calcium ions (CaCl2) and glycerol. Box Behnken Design was used to optimize the SLR, CaCl2, and glycerol amounts against the responses water vapor permeability (WVP), tensile strength (TS), and elongation at break (EB). The optimized SLR film biodegrades within 33 days at 24% soil moisture content. It is semitransparent with UV-blocking properties and displays the tensile strength (TS), elongation at break (EB), water vapor permeability (WVP), and IC50 value of 16.8 (3) MPa, 14.7 (2)%, 0.22 (4) x 10-10 gm- 1s- 1Pa- 1, and 0.4 (1) g/mL, respectively. The residual lignin retained in the SLR significantly increased film's TS. The film extends strawberries' shelf-life by 3 more days than plastic film and retains the original color, total soluble solids, ascorbic acid, and total phenolic compounds. Overall, the valueadded soyhull lignocellulose-based packaging films are advantageous in addressing plastic-related issues, leading to sustainable waste management and preserving fruits for longer durations.

Polycyclic aromatic hydrocarbons (PAHs) are bonded organic compounds with numerous structures with different toxicity levels. They can be of low molecular weight with 2-3 rings or high molecular weight with more than four rings and are persistent in nature. They possess high molecular weight and boiling point, hydrophobic with minimal solubility in water, and lipophilic with high solubility in organic solvents. With the gain in molecular weight, their susceptibility to oxidation-reduction decreases. They are generated during incomplete combustion of organic materials. They can be natural, such as forest fires, or artificial agents, such as coal, oil, wood burning, smoke, and auto-emissions. Due to strong molecular bonds and structural complexity, PAHs are highly malignant under normal conditions. They cause environmental damage due to improper handling and disposal in the surrounding air, water, soil, etc. PAH contamination is highly toxic because of mutagenic and potentially immune toxicants, often resulting in higher workplace casualties. Various physical, biological, and chemical processes remediate the PAHs in contaminated land. Indigenous microbial communities can effectively degrade it in-situ or ex-situ conditions. The degradation process depends on the type of microorganism, its life cycle, PAH substrate, pH, temperature, pressure, and the reaction mechanism. The present article discusses current literature, chemistry, natural and anthropogenic sources of generation, impacts on the environment, biota, etc., merits of physical, biological, and chemical remediation mechanisms with emphasis on microbial degradation, and novel options of technology intermix suitable for sustainable remediation outcomes.

The application of persulfate (PS) for the remediation of petroleum hydrocarbon contamination is among the most widely employed in situ chemical oxidation (ISCO) techniques, and it has received widespread attention due to its limited impact on soil integrity. This study employed a FeSO4-activated PS oxidation method to investigate the feasibility of remediating soil contaminated with total petroleum hydrocarbons (TPHs). The factors tested included the TPH concentration, different PS:FeSO4 ratios, the reaction time for remediation, soil physical and chemical property changes before and after remediation, and the effect of soil before and after remediation on soybean growth. The TPH degradation rate in soil was highest for high-, medium-, and low-TPHs soils-81.5%, 81.4%, and 72.9%, respectively, with minimal disruption to the soil's physicochemical properties-when PS:FeSO4 = 1:1. The remediation verification results indicated that the condition of the soybeans was optimal when PS:FeSO4 = 1:1. Under this condition, the net photosynthetic rate, stomatal conductance, intercellular CO2 concentration, and transpiration rate all remained high. Therefore, the best remediation effect was achieved with PS:FeSO4 = 1:1, which also minimized the damage to the soil and the effects on crop growth.

Petroleum pollution in soil is very damaging to the areas affected by the accidental release of petroleum hydrocarbons and has destructive impacts on natural resources and environmental health. Therefore, its monitoring and analysis are critical, however, due to the cost and time associated with chemical approaches, finding a quick and cost-effective analytical method is valuable. This study was conducted to evaluate the potential of using visible near infrared (Vis-NIR) spectroscopy to predict total petroleum hydrocarbons (TPH) in polluted soils around the Shadegan ponds, in southern Iran. One hundred soil samples showing various degrees of pollution were randomly collected from topsoil (0-10 cm). The soil samples were analyzed for TPH using Vis-NIR reflectance spectroscopy in the laboratory and then following application of preprocessing transformation, partial least squares PLS regression as well as two machine learning models including random forest (RF), and support vector machine (SVM) were examined. The results showed that the reflectance values at 1725 nm and 2311 nm, respectively, served as indicative TPH reflectance features, exhibiting weaker reflection with rising TPH. Among the preprocessing methods, the baseline correction method indicated the highest performance than the others. According to the evaluation model criteria in the validation dataset, the efficiency of the three selected models was observed in the following order SVM > RF > PLS regression. The SVM model provided the best performance in the validation dataset with r(2) = 0.85, root mean of square (RMSEP = 1.59 %, and the ratio of prediction to deviation (RPD) = 2.6. Overall, this study provided strong evidence supporting the considerable potential of Visible-NIR spectroscopy as a rapid and cost-effective technique for estimating TPH levels in oil-contaminated soils, surpassing traditional chemical analytical methods. Applying the mid-infrared spectrum (MIR) in combination with Visible-NIR data is expected to provide more comprehensive and accurate results when assessing soils in polluted areas, thereby enhancing the accuracy and reliability of the results across a diverse range of soil types.

Kerosene is widely used in various types of anthropogenic activities. Its environmental safety is mainly discussed in the context of aerospace activities. At all stages of its life cycle, aerospace activity impacts the environment. In aviation, the pollution of atmospheric air and terrestrial ecosystems is caused, first of all, by jet fuel and the products of its incomplete combustion and is technologically specified for a number of models in the case of fuel leak during an emergency landing. In the rocket and space activities, jet fuel enters terrestrial ecosystems as a result of fuel spills from engines and fuel tanks at the crash sites of the first stages of launch vehicles. The jet fuel from the second and third stages of launch vehicles does not enter terrestrial ecosystems. The fuel components have been studied in sufficient detail. However, the papers with representative data sets and their statistical processing not only for the kerosene content, but also for the total petroleum hydrocarbons in the soils affected by aerospace activity are almost absent. Nevertheless, the available data and results of mathematical modeling allow us to assert that an acceptable level of hydrocarbons, not exceeding the assimilation potential, enters terrestrial ecosystems during a regular aerospace activity. Thus, the incoming amount of jet fuel disappears rapidly enough without causing any irreversible damage.

Featured Application Python application that uses data science and machine learning to estimate the main properties of acid tars. Its main advantage is that determinations for acid tar properties are no longer necessary, thus saving time and money. However, good machine learning estimations are highly dependent on the number and quality of the training data, meaning that the larger and more consistent the training database, the better the estimations.Abstract Hazardous petroleum wastes are an inevitable source of environmental pollution. Leachates from these wastes could contaminate soil and potable water sources and affect human health. The management of acid tars, as a byproduct of refining and petrochemical processes, represented one of the major hazardous waste problems in Romania. Acid tars are hazardous and toxic waste and have the potential to cause pollution and environmental damage. The need for the identification, study, characterization, and subsequently either the treatment, valorization, or elimination of acid tars is determined by the fact that they also have high concentrations of hydrocarbons and heavy metals, toxic for the storage site and its neighboring residential area. When soil contamination with acid tars occurs, sustainable remediation techniques are needed to restore soil quality to a healthy production state. Therefore, it is necessary to ensure a rapid but robust characterization of the degree of contamination with hydrocarbons and heavy metals in acid tars so that appropriate techniques can then be used for treatment/remediation. The first stage in treating these acid tars is to determine its properties. This article presents a software program that uses machine learning to estimate selected properties of acid tars (pH, Total Petroleum Hydrocarbons-TPH, and heavy metals). The program uses the Automatic Machine Learning technique to determine the Machine Learning algorithm that has the lowest estimation error for the given dataset, with respect to the Mean Average Error and Root Mean Squared Error. The chosen algorithm is used further for properties estimation, using the R2 correlation coefficient as a performance criterion. The dataset used for training has 82 experimental points with continuous, unique values containing the coordinates and depth of acid tar samples and their properties. Based on an exhaustive search performed by the authors, a similar study that considers machine learning applications was not found in the literature. Further research is required because the method presented therein can be improved because it is dataset dependent, as is the case with every ML problem.

The permeability of treated contaminated soil is an important factor to consider when reusing polluted soil in engineering projects. In this study, lime and fly ash were chosen as solidification materials due to their ability to both adsorb and solidify contaminants. The permeability coefficients of petroleum-contaminated soil before and after solidification, as well as the residual petroleum content within the soil, was investigated under varying parameters such as confining pressure, osmotic pressure and contamination intensity. X-ray diffraction and scanning electron microscopy were used to analyze the evolution of permeability and the migration and diffusion patterns of pollutants, providing insights into the engineering reutilization potential of solidified petroleum-contaminated soil. The results showed that the adsorption effect of the solidified product on petroleum molecules weakened the hydrophobicity of the petroleum, increasing the effective permeation pathways in the soil. The permeability coefficient of solidified petroleum-contaminated soil was two orders of magnitude higher compared to unsolidified soil. Both solidified and unsolidified petroleum-contaminated soil exhibited decreased permeability due to the enhanced adsorption and interception capacity of the soil matrix for petroleum, as well as the elevated confining pressure, osmotic pressure, and contamination level, which intensified the interception among soil particles. The solidification process effectively controlled the migration and diffusion of petroleum contaminants under permeation conditions. The residual petroleum content in various locations closely approximated the initial content, reducing the risk of pollution through permeation. Considering the mechanical properties (compressive strength of 1 280.1 kPa, shear strength of 388.88 kPa), permeability (ranging from 4.28x10(-6) cm/s to 7.39x10(-6) cm/s), and migration control characteristics (fluctuation rate from 0.3% to 4.9%) of lime and fly ash, it can be concluded that lime and fly ash solidified petroleum-contaminated soil can be reused in the construction of subgrade materials that require impermeability.