Hydrocarbon Pollution Research Articles

Development of a Novel Lyophilization Method for the Production of Bacterial Strain Powders to Enhance the Cleanup Efficiency of Petroleum Hydrocarbon–Polluted Soils

Development of a Novel Lyophilization Method for the Production of Bacterial Strain Powders to Enhance the Cleanup Efficiency of Petroleum Hydrocarbon–Polluted Soils

Isolation and Identification of Hydrocarbon-Degrading Bacteria from Diesel-Contaminated Soils

Aim: To Isolate, screen and identify bacterial species with hydrocarbon biodegradative potentials from diesel-polluted soils using redox indicator (2% v/v of 2,6 – dichlorophenol indophenols- DCPIP) and Turbidity measurements. Place and Duration of Study: Microbiology laboratory in the Department of Environmental Management and Toxicology, Federal University of Petroleum Resources, Effurun, between 2022 and 2024. Methodology: Soil samples from diesel-contaminated site were collected from diesel mechanic workshop, analysed using the spread plate isolation technique on Bushnell Haas mineral salt agar selective medium, were screened for Bacterial species with hydrocarbon degradative potential using the redox indicator (2% v/v of 2,6 – dichlorophenol indophenols- DCPIP) and Turbidity measurement. Selected Bacterial isolates were used for the hydrocarbon degradation studies, were characterized based on biochemical tests and identified with the aid of the Biolog database and 16S rRNA gene sequencing techniques. Results: Eight diesel degrading Bacteria species were identified, belonging to the following genera; Acinetobacter, Klebsiella, and Pseudomonas. Among these, the four most potent degraders were identified as Acinetobacter rudis (M2712942.1), Acinetobacter bereziniae (MT111619.1), Pseudomonas koreensis (MW794239.1), and Klebsiella aerogenes (CP070520.1) and the % diesel reduction achieved in 15 days were; 70%, 48%, 47% and 45%, while the % Turbidity increase were 84%, 79%, 78% and 76% respectively. Consequently, the partial 16S rRNA gene sequences revealed the two most potent diesel degrading bacterial strains were Acinetobacter rudis and Acinetobacter bereziniae with 70% and and 48% respectively. Conclusion: These findings demonstrate the potential of indigenous bacteria for effective bioremediation of petroleum-contaminated environments. The study provides critical insights into sustainable solutions for mitigating hydrocarbon pollution, contributing to advancements in environmental microbiology and ecosystem restoration.

Research progress in tolerance of petroleum hydrocarbon pollutant-degrading strains

Petroleum hydrocarbon pollution has become one of the global environmental problems, posing a serious threat to the environment and human health. Microbial remediation plays an important role in the remediation of petroleum hydrocarbon-contaminated environment. Nevertheless, the stress factors present in the environment polluted by petroleum hydrocarbons limit the effectiveness of microbial remediation. This paper reviews the common stress factors in petroleum hydrocarbon-polluted environment and the response mechanisms of microorganisms to these factors. Furthermore, we introduce the methods to improve microbial tolerance, such as irrational modification, rational modification based on systems biology tools or tolerance mechanisms, and the construction of microbial consortia. The application of these methods is expected to improve the viability and remediation efficiency of microorganisms in petroleum hydrocarbon-contaminated environment and provide new perspectives and technical support for environmental remediation.

Asymmetric Pt1O4-Ov Dual Active Sites Induced by NbOx Clusters Promotes CO Synergistical Oxidation.

Pt/CeO2 single-atom catalysts are attractive materials for CO oxidation but normally show poor activity below 150 °C mainly due to the unicity of the originally symmetric Pt1O4 structure. In this work, a highly active and stable Pt1/CeO2 single-site catalyst with only 0.1 wt % Pt loading, achieving a satisfied complete conversion of CO at 150 °C, can be obtained through fabricating asymmetric Pt1O4-oxygen vacancies (Ov) dual-active sites induced by well-dispersed NbOx clusters. Specifically, the formation of new Ce-O-Nb interactions weakened the strength of the original Pt-O-Ce bond, thus transferring the originally near-perfect square-planar Pt1O4 into the distorted square-planar one, along with forming abundant Ov around the Pt site. Hence, the promoted CO activation on the asymmetric Pt1O4 structure and the facilitated dissociation of the O2 on the neighboring Ov site synergistically improved the CO catalytic oxidation performance. The fabrication of such asymmetric Pt1O4-Ov double-active sites was also active for the oxidation of other typical hydrocarbons pollutants such as C7H8 and C3H6 from exhaust gases, shedding light on engineering high-efficiency Pt-based oxidation catalysts for low-temperature environmental catalysis.

Process development and utilization of organic and inorganic fertilizer combinatorial in the remediation of petroleum hydrocarbon polluted soil

The aim of the study is to examined fertilizers obtained from poultry manure (PM), poultry manure biochar (PMB), inorganic fertilize (IF), poultry manure + poultry manure biochar (PM + PMB), poultry manure + inorganic fertilizer (PM + IF), poultry manure biochar + inorganic fertilizer (PMB + IF), poultry manure + poultry biochar + inorganic fertilizer (PM + PMB + 6 IF) on reduction of petroleum hydrocarbon pollutant and nutrients retention of petroleum hydrocarbon polluted soil. Unpolluted sandy loam soil used for study was collected from farm land in Mosogar, Delta State, Nigeria using standard procedure. The soil was sparked with weathered crude oil of 3 different concentrations, 2%, 4%, 6%. The polluted soil was treated with fertilizers, the physico-chemical properties of unpolluted soil (US) and fertilizers was analyzed for pH, nutrients and petroleum hydrocarbon (PHC). The same analysis was also performed on polluted soil. The results of the study revealed that PM and PMB contained remarkable value of nutrients, the results also revealed that interaction of fertilizers on petroleum hydrocarbon polluted boost the pH and nutrients value at the first 21 days of incubation while after 21 days the pH and nutrients value of study polluted soil began to decrease. In addition, PM + PMB fertilizer retained highest value of nutrients after 63 and 84 days incubation period, in addition PM + PMB also displayed over 94% reduction of petroleum hydrocarbon pollutant. Therefore, this study has proved that PM + PMB is a fertilizer of choice to address petroleum hydrocarbon polluted.

Novel Approaches to Decomposing Hydrocarbon Pollutants from the Environment

In the modern era, petrochemical industries' production of hydrocarbon pollution is a significant environmental problem that causes biodiversity loss. Alkanes constitute a substantial proportion of crude oil, and refined fuels are found in small amounts in various uncontaminated environments. They are prevalent in underground fossil fuel reserves and shallow subsurface habitats polluted with hydrocarbons, such as aquifers. Using microorganisms to break down alkane hydrocarbon pollutants in environmental areas has great potential. Considerable advancements have been achieved in identifying microorganisms and metabolic processes responsible for the breakdown of alkanes in both oxygen-free and oxygen-rich conditions in the last two decades. A wide range of prokaryotic and eukaryotic organisms have been identified and observed to possess the ability to utilize various carbon and energy sources as substrates. Bioremediation is essential for environmental safety and management; various methods have been established for petroleum hydrocarbon bioremediation. Numerous microbial species have been employed to investigate the bioremediation of petroleum hydrocarbons, highlighting the crucial functions of varied microbial communities. Phytoremediation is an environmentally sustainable method that may effectively rehabilitate heavy metal- contaminated soil cost-efficiently. This manuscript provides an overview of prevalent alkane hydrocarbon pollutants, microorganisms capable of degrading hydrocarbons, key pathways and enzymes involved in hydrocarbon degradation, factors influencing hydrocarbon degradation, and various strategies employed to harness the degrading capabilities of microbes for remedial purposes.

Impact of salinity on density and mechanical strength of <i>Avicennia germinans</i> wood exposed to marine oil pollution in the Gabon Estuary

Located at the interface between land and sea, mangroves develop both near the sea and inland. However, mangroves that develop inland have to cope with variable, high salinity; and urban pollution, as is the case with the mangroves of the Ambowé lagoon in Greater Libreville. Salinity is an important parameter for mangrove growth. The aim of this work was; yes itto show the impact of salinity on the density and mechanical strength of A. germinans wood exposed to hydrocarbon pollution. To this end, wood samples taken from the polluted Ambowé site were analyzed in the laboratory for wood and physical-mechanical properties. The data obtained were compared with wood samples taken from the unpolluted Oveng site, which has a higher salinity. The results show that for the polluted wood showed wider rings, lower wood density and mechanical strength with values of 0.91 ± 0.05 and 70.28 MPa, respectively. Also, the rings and vessels of Oveng wood are narrower than those of Ambowé wood. These differences are linked to salinity. Salinity therefore affects the density and mechanical strength of A. germinans wood exposed to hydrocarbon pollution.

Environmental DNA-based assessment of multitrophic biodiversity in a typical river located in the Loess Plateau, China: Influence of PAHs and suspended sediments.

Polycyclic aromatic hydrocarbon (PAH) pollution and high suspended sediment (SS) contents are significant anthropogenic and natural stressors that threaten aquatic biodiversity. However, the characteristics of multitrophic biological communities and their co-occurrence patterns in response to PAHs in sediment-laden rivers remain unclear. This study investigated the spatial distribution of species across three trophic levels, including algae, metazoan, and fish, in the Beiluo River on the Loess Plateau, China, using environmental DNA metabarcoding. Biodiversity was assessed in relation to 16 PAHs, SS, and environmental variables. The PAH in the dissolved phase ranged from 19.70 to 1613.30 ng/L dominated by low molecular weight (LMW) PAHs. Partial least squares path modeling (PLS-PM) revealed a negative correlation between PAH distribution and SS in the river. In terms of biodiversity, the richness and Shannon index of algae (Chlorophyta and Dinophyceae) were positively associated with acenaphthene (ACE) levels. Conversely, the Shannon index and richness of metazoans (Rotifera and Arthropoda) appeared to decline in response to Benzo[a]anthracene (BaA) and pyrene (PYR). Fishes (Cypriniformes and Clupeiformes) demonstrated greater tolerance to PAH contamination than algae and metazoans, and their reduced richness and Shannon index were linked to the high SS loads (> 0.45 μm). The co-occurrence patterns highlighted a stronger association connection between algae and metazoan communities than fish. This study provides valuable insights into how PAHs could reshape the structure of riverine multitrophic communities under conditions of elevated SS loads.

Identification of driving factors for heavy metals and polycyclic aromatic hydrocarbons pollution in agricultural soils using interpretable machine learning.

This study integrated data-driven interpretable machine learning (ML) with statistical methods, complemented by knowledge-driven discrimination diagrams, to identify the primary driving factors of heavy metal (HM) and polycyclic aromatic hydrocarbon (PAH) contamination in agricultural soils influenced by complex sources in a rapidly industrializing region of a megacity in southern China. First, the statistical characteristics of the concentrations of HMs and PAHs, and their correlations with the environmental covariates were explored. Three ML models and a statistical model comprising multiple environmental variable predictors were developed and assessed to predict the concentration of HMs in the agricultural soil. The Shapley Additive Explanations (SHAP) tool was introduced to reveal the influences of the main driving factors on pollutant concentrations. In addition, knowledge-based discrimination diagrams were adopted to discriminate the potential sources of the PAHs. Our findings indicated that Cd, Hg and Cu could be effectively predicted by the LightGBM and RF models. The identification of pollution drivers revealed that traffic emission, industry activity and irrigation significantly contributed to the pollution of Cd, Hg, Cu and high-ring PAHs in the study area, while the soil nature properties including SOM and pH also played crucial roles in influencing the HM and PAH concentrations. This work introduced an innovative approach to leverage ML for understanding complex urban soil pollution, thereby setting a precedent for data-driven environmental protection strategies to mitigate the pollution of HMs and PAHs. Future research is encouraged to optimize the models, enhance the prediction accuracy, and incorporate a broader range of influential parameters.

Electrochemical reduction for chlorinated hydrocarbons contaminated groundwater remediation: Mechanisms, challenges, and perspectives.

Electrochemical reduction technology is a promising method for addressing the persistent contamination of groundwater by chlorinated hydrocarbons. Current research shows that electrochemical reductive dechlorination primarily relies on direct electron transfer (DET) and active hydrogen (H⁎) mediated indirect electron transfer processes, thereby achieving efficient dechlorination and detoxification. This paper explores the influence of the molecular charge structure of chlorinated hydrocarbons, including chlorolefin, chloroalkanes, chlorinated aromatic hydrocarbons, and chloro-carboxylic acid, on reductive dechlorination from the perspective of molecular electrostatic potential and local electron affinity. It reveals the affinity characteristics of chlorinated hydrocarbon pollutants, the active dechlorination sites, and the roles of substituent groups. It also comprehensively discusses the current progress on electrochemical reductive dechlorination using metal, carbon-based, and 3D electrode catalysts, with an emphasis on the design and optimization of electrode materials and the impact of catalyst microstructure regulation on dechlorination performance. It delves into the current application status of coupling electrochemical reduction technology with biodegradation and electrochemical circulating well technology for the remediation of groundwater contaminated by chlorinated hydrocarbons. The paper discusses practical application challenges such as electron transfer, electrode corrosion, water chemistry environment, and aquifer heterogeneity. Finally, considerations are presented from the perspectives of environmental impact and sustainable application, along with a summary and analysis of potential future research directions and technological prospects.

A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution.

Petroleum hydrocarbon pollution causes significant damage to soil, so accurate prediction and early intervention are crucial for sustainable soil management. However, traditional soil analysis methods often rely on statistical methods, which means they always rely on specific assumptions and are sensitive to outliers. Existing machine learning based methods convert features containing spatial information into one-dimensional vectors, resulting in the loss of some spatial features of the data. This study explores the application of Three-Dimensional Convolutional Neural Networks (3DCNN) in spatial interpolation to evaluate soil pollution. By introducing Channel Attention Mechanism (CAM), the model assigns different weights to auxiliary variables, improving the prediction accuracy of soil hydrocarbon content. We collected soil pollution data and validated the spatial distribution map generated using this method based on the drilling dataset. The results indicate that compared with traditional Kriging3D methods (R2 = 0.318) and other machine learning methods such as support vector regression (R2 = 0.582), the proposed 3DCNN based method can achieve better accuracy (R2 = 0.954). This approach provides a sustainable tool for soil pollution management, supports decision-makers in developing effective remediation strategies, and promotes the sustainable development of spatial interpolation techniques in environmental science.

Temporal development of chlorinated hydrocarbons in the Baltic Sea sediments: Characterization of the pollution maximum.

The Baltic Sea, a semi-enclosed marginal sea with a catchment area four times its size, acts as a sink and continues to show detectable levels of persistent organic pollutants (POPs) in its sediments. This is attributed to the synthesis and industrial use of commercial polychlorinated biphenyls (PCB) products, as well as the widespread use and discharge of certain chlorinated pesticides into the natural environment during the last century. Our study investigates chlorinated hydrocarbon pollutants, the polychlorinated biphenyls (PCBs), dichlorodiphenyltrichloroethane (DDT) and its metabolites as well as hexachlorobenzene (HCB) in sediments based on several short sediment cores from different basins covering almost the entire Baltic Sea. In this study, we document the decline of PCB, HCB and DDT metabolites in Baltic Sea sediments, visible in a sevenfold reduction of pollution levels over a period of 50years since their maximum production in the mid-eighties of the last century. We reflect the pollution levels against the global regulations, especially the worldwide ban of the POPs at the beginning of the 21st century. Based on our results, we are now able, for the first time, to evaluate the fate of POPs in Baltic Sea sediments and to provide further explanation for the detection of POPs in previous and future studies.

Developing and testing a new Ecological Quality Status index based on marine nematode metabarcoding: A proof of concept.

Nematodes are the most diverse and dominant group of marine meiofauna with high potential as bioindicators of the ecological quality status (EcoQS). The present study explores, for the first time, the applicability of the nematode metabarcoding to infer EcoQS index based on the calibration of ecological behaviors of nematodes Amplicon Sequence Variants (ASVs). To achieve this, we analyzed the nematode community in sediment eDNA samples collected in 2018 and 2021 in areas around three offshore oil platforms in the Danish west coast of the North Sea. One training dataset based on eDNA and environmental data from the three platforms in 2021 covering a wide range of environmental gradients has been used as a training dataset to assign the nematodes ASVs to Ecological Groups. These assignments then allowed us to infer the EcoQS both around these three platforms and in an independent dataset (one of the platforms sampled in 2018). The EcoQS inferred from the nema-gAMBI is perfectly in line with the pollution gradient of the platforms. In fact, stations located close to the platforms (i.e., 100m and 250m) show a relatively lower EcoQS than those at greater distance (i.e., reference or 3000m). The nema-gAMBI seems to capture well the EcoQS variability around platforms and correlates well with the environmental parameters (e.g., trace element and hydrocarbon pollution). Indeed, the nema-gAMBI is positively and significantly correlated with the traditional macrofauna-based AMBI. The present proof of concept strongly advocates for the application of the nematode eDNA-based index in the evaluation of EcoQS.

Microbial–physicochemical interplay in Iko River estuary, unraveling the hidden mystery in bioremediation of petroleum hydrocarbons

ABSTRACT The aquatic microbial communities are relatively complex with a high level of prokaryotic diversities. Standard and novel microbiological, analytical, and statistical techniques were employed in the collection, analysis, and comprehensive study of the samples. From the study, the mean values of total heterotrophic bacteria were determined to be 1.35 ± 0.18 (×107), 1.59 ± 0.64 (×107), and 1.56 ± 0.52 (×107) for upstream, midstream, and downstream, respectively, while the mean values for crude oil-utilizing bacteria were 1.08 ± 0.12 (×106), 1.28 ± 0.58 (×106), and 1.24 ± 0.44 (×106) for upstream, midstream, and downstream, respectively. The mean concentrations of physicochemical parameters and heavy metals obtained in the benthic sediment were significantly higher than the mean concentrations in the water samples (tidal and intertidal) (p < 0.02). The result of the component analysis of total petroleum hydrocarbons (including polycyclic aromatic hydrocarbon and benzene, toluene, ethylbenzene, and xylene) revealed significantly higher levels in the sediment than tidal and intertidal water. Structural metagenomics revealed seven top phyla, namely, Proteobacteria, Actinobacteria, Firmicutes, Bacteroidetes, Planctomycetes, Fusobacteria, and Chloroflexi. The significantly (p < 0.05) high levels of hydrocarbon-utilizing microorganisms in Iko River estuary can be taken as a sensitive index of environmental exposure to hydrocarbon pollutants in the estuary. This research revealed the response patterns of microorganisms to natural and anthropogenic gradients toward sustainability in Iko River estuary.

Spatial heterogeneity of polycyclic aromatic hydrocarbons pollution in surface soil of China and its response to regional energy consumption

Spatial heterogeneity of polycyclic aromatic hydrocarbons pollution in surface soil of China and its response to regional energy consumption

Biodegradation of polycyclic aromatic hydrocarbons with enterobacter asburiae

Polycyclic Aromatic Hydrocarbons (PAHs) pollution has been found to be toxic, mutagenic, carcinogenic, teratogenic, and immunotoxicogenic. Naphthalene, Anthracene, and Fluorene are among the polycyclic aromatic hydrocarbons (PAHs) that are frequently detected in wastewater from biomass gasification and refineries. In this study, industrial waste water samples were collected from three sites located in Kafr El-Sheikh Governorate, Egypt and showed presence of PAHs in different concentration varying from 0.42 to 253.1 ppb. This study's findings included the isolation and identification of Enterobacter asburiae the most proficient bacterial isolate capable of biodegrading PAHs among other 7 studied bacterial isolates. Enterobacter asburiae strain No. 1 showed the ability to biologically degrade approximately 79 %, 89.7 % and 82.8 % of Naphthalene, Fluorene and Anthracene active ingredients respectively. The results of toxicity assessment showed that PAHs byproducts after 14 days of incubation had no toxicity; consequently, there was no antibacterial activity detected against B. subtilis as a test organism. Such biological approaches used in this study can be further applied in various polluted sites to get rid of ubiquitous organic pollutants.

Hydrocarbon Pollution of Water and Bottom Sediments in Coastal Areas of the Caucasian Sector of the Black Sea (2021, 2022)

Hydrocarbon Pollution of Water and Bottom Sediments in Coastal Areas of the Caucasian Sector of the Black Sea (2021, 2022)

Rankings of Shorelines of Georgian Black Sea Sector According to the Ecological Sensitivity Index (ESI)

Georgia is concidered as one of the best alternative transit countries connecting Asia and Europe. The transportation of oil and oil products from the Caspian and Central Asian regions to European countries is especially significant. This boosts the country’s economy, but it also increases the risk of marine environment pollution from oil hydrocarbons. In response to the risk of oil hydrocarbon pollution, it is necessary to intensify preventive monitoring efforts. This includes assessing the extent of oil hydrocarbon contamination on shores, in coastal waters, and in bottom sediments, as well as identifying and classifying areas along the coastline that are most sensitive to pollution. The division of shorelines into sensitive areas is carried out according to the ecological sensitivity index ESI, wich contains a numeric or alpha-numeric coded description of the shoreline characteristics for each shoreline segment. According to the 10 levels of sesitivity against oil pollution, the shoreline segments are classified from "low" sensitivity ESI 1 to "very high" sensitivity ESI 10, respectively 10 main classes and up to 30 sub-classes are identified. In Georgia coastal area, for the 113 km section from Ganmukhuri to Sarpi, we have identified shoreline segments with 7 main classes and 9 sub-classes of sensitivity. Keywords: Black sea, Georgia, oil, sensitivity, rankings , pollution

Graphene oxide and hydroxyapatite-based composite extracted from fish scale: Synthesis, characterization and water treatment application

In this study the removal of hydrocarbon pollutants from refinery waste water has been described through a convenient adsorption technique using a novel composite of graphene oxide (GO) and n-hydroxyapatite (n-HAp). The main aim was to synthesized composite which are not only sustainable and biodegradable but also exhibit high adsorption capacity and selectivity for hydrocarbon pollutants. Both the HAp and GO were synthesized from fish scales in the laboratory. The synthesized material was then characterized by XRD, FTIR, SEM, and EDX. At 40 °C and 80 min of reaction time, the adsorbent utilized in a batch mode study attained a maximum 97 % organic pollutant adsorption rate. The adsorption activity was spontaneous, exothermic, useful, and it adhered to the pseudo-2nd order kinetic model. without noticeably losing its activity, the adsorbent retained a high level of efficiency over four consecutive cycles. Adsorption of hydrocarbon wastes using composite adsorbent was carried out under batch mode of adsorption experiments. We also studied the effect of dose, temperature, time and pH of the solution on adsorption. Ethanol was used to regenerate the adsorbent, and it was then dried at 70 °C for re-use. The SEM investigation showed that the morphology of huge caves is rough, layered, and wrinkled. The oxygen and phosphate containing groups were found via FT-IR analysis. Freundlich and Langmuir kinetic models were used to measure the adsorption behavior by applying them to the adsorption data. The results demonstrated a strong correlation between the Freundlich isotherm model and the real data. This study showed a highly effective and cost-efficient methodology for the removal of toxic hydrocarbon contaminants in refinery wastewater.

Determination of Polycyclic Aromatic Hydrocarbons in Water Samples Using Solid‐Phase Extraction Procedure and High‐Performance Liquid Chromatography With Fluorescence Detection

ABSTRACTSolid phase extraction (SPE) procedure followed by high‐performance liquid chromatography with fluorescence detection was evaluated for determination of 14 priority polycyclic aromatic hydrocarbons (PAHs) pollutants in water samples. Diverse parameters affecting extraction efficiency such as the nature and volume of eluent solvent, volume and pH of the water sample, and quantity and nature of sorbent phase were studied and optimized. SPE was carried out on Bond Elut C18 cartridge and high recoveries were obtained using 1000 mg of the sorbent for the treatment of a 500 mL water sample. PAH recoveries ranged from 60.3% to 93.3% for 500 mL treated water samples. The developed method gives very low detection limits ranging between 0.03 and 12 ng/mL and it has been applied successfully to different environmental water samples such as tap water, mineral water, surface water, treated wastewater, and industrial effluents. Results showed the presence of PAHs especially in industrial effluent from the Bizerte region with ∑PAHs means value of 33.76 mg/L and in treated wastewater samples collected from North Tunisia with ∑PAHs concentrations levels of 0.81, 1.17, 0.97, and 0.72 mg/L in Bizerte, Tunis, Ben Arous, and Beja wastewater treatment plants, respectively.