A novel mathematical model for modeling viscosity and temperature relationship for dead oils.

Viscosity is crucial in subsurface and surface transport, used in engineering domains like heat transfer and pipeline design. However, measurements are limited, necessitating predictive viscosity relationships. Existing models lack precision or pertain to limited fluids, and accurately forecasting dead oil viscosity remains challenging due to errors. The study presents a mathematical algorithm to accurately estimate viscosity values in hydrocarbon fluids. It uses a robust non-linear regression technique to establish a reliable relationship between fluid viscosity and temperature within a specific temperature range. The algorithm is applied to extra-heavy to light crude oil samples from Iranian oilfields, revealing viscosity values ranging from 0.29 cp to 5328.74 cp within a dataset of 243 viscosity data points. After modeling each of these five fluids, the highest values obtained for the maximum absolute error and relative error are related to the fluid with an API gravity of 12.92. The maximum absolute error and relative error for this fluid sample are 1.25 cp and 6.04%, respectively. The algorithm offers acceptable precision in outcome models, even with limited training data, demonstrating its effectiveness in training models with less than 30% of available data. Moreover, these models end up with a near-unity coefficient of determination in testing data, reaffirming their proficiency at reflecting empirical data with remarkable accuracy.

RV-FELM: Futures commodity price forecasting based on RIME-VMD algorithm coupled with FA-ELM.

Commodity futures are an important hedging tool in material trade, and by accurately predicting prices, countries and firms are able to make informed production and consumption decisions. This paper introduces a novel machine learning ensemble method that combines decomposition algorithms and physical optimization algorithms to predict commodity futures prices. First, the VMD(Variational mode decomposition) is optimized by the RIME algorithm (Rime optimization algorithm) to obtain the optimal modal decomposition results, and the trend and seasonal terms are predicted using the ELM (Extreme Learning Machines) and FA (Fourier Attention) models, respectively, and the results are finally synthesized. The results show that the MAPE(mean absolute percentage error) of one-step, three-step, and six-step methods for predicting crude oil prices are 0.48%, 0.66%, and 0.75%, respectively, and the MAPE of soybean prediction results are 0.22%, 0.27%, and 0.37%, respectively. The empirical results and ablation experiments show that it outperforms other benchmark models in terms of both horizontal and directional accuracy. Notably, it outperforms in predicting soybean futures prices, which demonstrates the ability of our model to better capture the characteristics of both the time and frequency domains of the series, to take sufficient consideration of the series characteristics, and to ensure robustness.

Rhizobacterial-assisted phytoremediation for accelerated petroleum-hydrocarbon removal in crude-oil sludge.

Almost over ten years, environmental experts have concentrated on implementing risk-based management strategies for the remediation of sites contaminated with total petroleum hydrocarbons (TPHs), which can potentially have detrimental ecological impacts. Phytoremediation widely recognized as a green technology a plant-based and economically efficient technology, emerges as a promising method to offer an alternative to existing treatment technologies in TPH contaminated ecosystems. The utilization of Scirpus grossus, a perennial plant, has been proposed as a practical, safe, and cost-effective method for remediating soil contaminated with petroleum hydrocarbons. This study aimed to evaluate the efficacy of S. grossus in removing total petroleum hydrocarbons (TPH) in real crude-oil sludge. Employing a batch phytoremediation system with S. grossus, the experiment was conducted in crates within a greenhouse, maintaining ambient temperatures (30 °C-35 °C) for a duration of 28 days. Each crate was populated with 9-month-old plants of uniform size, initially cultivated in the greenhouse before being transplanted into crates containing 100 % crude-oil sludge with an initial TPH concentration of 37,554 mg/kg for the treatment phase. TPH removal rates were assessed after 14, 21, and 28 days of exposure, resulting in removal rates of 67 %, 74 %, and 75 %, respectively. The highest concentration of rhizobacteria recorded in both sample (with contaminants and without contaminants) were 5.56 × 104 and 5.72 × 104 CFU/mL respectively. Furthermore, TPH extraction from both stems and roots of S. grossus was analysed, revealing the highest TPH concentration of 15,319 mg/kg and about 8000 mg/kg of TPH at day 28 by roots and stem sample respectively. In conclusion, S. grossus demonstrated substantial potential in effectively mitigating the toxicity of TPH in real crude-oil sludge contamination scenarios.

Connectivity reliability evaluation and most reliable shipping route choice in a seaborne crude oil network.

The connectivity reliability of strait and canal nodes in seaborne crude oil networks is uncertain because of various risk factors. Existing studies have mainly focused on road networks and often ignored real-world factors by assuming fixed and identical values for the connectivity reliability of each node, leading to inaccurate estimations. Few studies have considered node reliability when identifying the most reliable routes for oil shipments in response to various external and changing risks. To address these limitations, we first establish new connectivity reliability evaluation methods for both nodes and networks. Then, we develop the α-most reliable shipping route and the very most reliable shipping route models using uncertain programming to dynamically identify the most reliable routes for crude oil, ensuring timely and safe transportation. We apply these models to China's seaborne network of imported crude oil. The results show a network connectivity reliability of 0.6228, which is impacted by unreliable origin-destination pairs in the Middle East. The risk values of the most reliable oil shipping routes vary regionally, with higher values in Africa and the Middle East than in Asia and Latin America. As node risk increases, regional disparities also increase. These findings will aid in the development of energy transportation and import strategies to enhance transportation reliability.

In-situ upgrading of Egyptian heavy crude oil using matrix polymer carboxyl methyl cellulose/silicate graphene oxide nanocomposites.

This study delves into catalytic aquathermolysis to enhance the economic viability of heavy oil production by in-situ upgrading technique. It is known that introducing nanocatalysts would promote the aquathermolysis reaction. Therefore, in this study, the effect of matrix polymer carboxyl methyl cellulose/silicate graphene oxide nanocomposites (CSG1 and CSG2) in the catalytic aquathermolysis of Egyptian heavy crude oil was studied. Characterization techniques including Fourier-transform infrared (FTIR), X-ray diffraction (XRD), Dynamic light scattering (DLS), Brunauer-Emmett-Teller (BET) surface area analysis, Scanning electron microscopy (SEM), and thermogravimetric analysis (TGA) were used to evaluate the structure of the synthesized nanocomposites. Results reveal CSG2 has higher crystallinity and superior dispersion compared to CSG1, and both exhibited a good stability in aqueous suspensions. CSG2 enriched with graphene oxide, demonstrates superior thermal stability, suitable for high-temperature applications such as catalytic aquathermolysis process. Single factor and orthogonal tests were used to assess the catalytic aquathermolysis performance of the prepared nanoparticles. The obtained results revealed that the optimum conditions to use CSG1 and CSG2 are 40% water concentration, 225 °C temperature, and 0.5 wt% catalyst percentage. Where, CSG2 showed better viscosity reduction (82%) compared to CSG1 (62%), highlighting its superior performance in reducing the viscosity of heavy oil. Numerical results from SARA analysis, gas chromatography, and rheological testing confirmed the catalytic aquathermolysis's efficacy in targeting asphaltene macromolecules and producing lighter hydrocarbon fractions.

The Effect of Hydrophobic Modified Block Copolymers on Water-Oil Interfacial Properties and the Demulsification of Crude Oil Emulsions.

The demulsification effect of three types of block copolymers, BP123, BPF123, and H123, with the same PEO and PPO segments but different hydrophobic modification groups on crude oil emulsions and the properties of oil-water interfaces were investigated using demulsification experiments, an interfacial tensiometer, and surface viscoelastic and zeta potential instruments in this paper. The results showed that the hydrophobic modification group of the block copolymers had great effects on the demulsification performance. The H123 block copolymers with the strongest hydrophobicity had the best demulsification effect on the crude oil emulsions. The properties of the oil-water interfaces indicated that the modified block copolymers achieved the demulsification of crude oil emulsions by reducing the strength of the oil-water interfacial film and the interfacial tension.

Acute gastrointestinal symptoms associated with oil spill exposures among U.S. coast guard responders to the Deepwater Horizon oil spill.

PURPOSE: Research investigating gastrointestinal (GI) symptoms from oil spill-related exposures is sparse. We evaluated prevalent GI symptoms among U.S. Coast Guard responders deployed to the Deepwater Horizon oil spill cleanup. METHODS: Crude oil (via skin contact, inhalation, or ingestion routes), combined crude oil/oil dispersant exposures, other deployment exposures, deployment characteristics, demographics, and acute GI symptoms during deployment (i.e., nausea/vomiting, diarrhea, stomach pain, and constipation) were ascertained cross-sectionally via a post-deployment survey (median time between deployment end and survey completion 185 days) (N = 4885). Log-binomial regression analyses were employed to calculate prevalence ratios (PRs) and 95 % confidence intervals (CI). Effect modification was evaluated. RESULTS: In adjusted models, responders in the highest (versus lowest) tertile of self-reported degree of skin contact to crude oil were more than twice as likely to report nausea/vomiting (PR=2.45; 95 %CI, 1.85-3.23), diarrhea (PR=2.40; 95 %CI, 2.00-2.88), stomach pain (PR=2.51; 95 %CI, 2.01-3.12), and constipation (PR=2.21; 95 %CI, 1.70-2.89). Tests for trend were statistically significant (p < 0.05). Results were similar for crude oil exposure via inhalation and ingestion. Higher PRs for all symptoms were found with combined crude oil/dispersant exposure than with crude oil exposure alone. CONCLUSIONS: These results indicate positive associations between self-reported crude oil and combined crude oil/oil dispersant exposures and acute GI symptoms.

Multi-model transfer function approach tuned by PSO for predicting stock market implied volatility explained by uncertainty indexes.

This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical threats to the CBOE Volatility Index (VIX). In this study, the relationship between the various uncertainty metrics throughout the period 2012-2022, using a multi-model transfer function technique optimized by particle swarm optimization (PSO) is estimated. Furthermore, we utilize PSO for parameter optimization within the multi-model framework, improving model performance and convergence speed. According to empirical findings, the CBOE Volatility Index reacts nonlinearly to the uncertainty indices. Specifically, the conclusions of the performance metrics show that the OVX index (MAPE: 4.1559%; RMSE: 1.0476% and W: 96.74%) outperforms the geopolitical risk index, the Bloomberg energy index, and the economic policy uncertainty index in predicting the volatility of the US equities market. Although individual models have generated respectful performance, results from the aggregate simulation show that when all predictors are combined, they simultaneously provide better performance indicators (MAVE: 2.7511 %; RMSE: 0.7361%; R2: 98.93%) than when they are estimated separately. In addition, results provide evidence that, when considering non-linear patterns in the data, the multi-model transfer function technique calibrated using PSO demonstrates its outperformance over autoregressive baseline models, traditional econometric models, and deep learning techniques. The effectiveness and accuracy of the multi-model transfer function method tuned by PSO as a forecasting tool are confirmed by the convergence analysis of the cost function. Our methodology innovates by employing a multi-model transfer function technique, which captures the complex and nonlinear relationships between uncertainty indicators and the VIX more comprehensively than traditional single-model approaches. These results are important for traders in terms of hedging as well as portfolio diversification by investing in defensive equities and for policymakers in terms of reliability and preciseness of volatility forecasts.

Use of cardiac cell cultures from salmonids to measure the cardiotoxic effect of environmental pollutants.

Environmental stressors such as micro- and nanosized plastic particles (MNPs) or crude oil have a detrimental effect on aquatic animals; however, the impact upon the cardiovascular system of fish remains relatively under-researched. This study presents a novel approach for investigating the effect of crude oil and MNPs on the cardiac system of fish. We used salmonid larvae and cardiac cell cultures derived from hearts of salmonid fish and exposed them to environmental stressors. Following exposure to plastic particles or crude oil, the larvae exhibited some variation in contraction rate. In contrast, significant alterations in the contraction rate were observed in all cardiac cell cultures. The greatest differences between the control and treatment groups were observed in cardiac cell cultures derived from older brown trout. Following 7 days of exposure to MNPs or crude oil in Atlantic salmon larval hearts or cardiac cell cultures, there were only minor responses noted in mRNA expression of the selected marker genes. These findings show the use of a novel in vitro technique contributing to the existing body of knowledge on the impact of MNPs and crude oil on the cardiovascular system of salmonids and the associated risk.

Wood Sponge for Oil-Water Separation.

In addition to filtering some sediments, hydrophobic wood sponges can also absorb many organic solvents, particularly crude oil. The leakage of crude oil poses a serious threat to the marine ecosystem, and oil mixed with water also generates great danger for its use. From the perspective of low cost and high performance, wood sponges exhibit great potential for dealing with crude oil pollution. Wood sponge is a renewable material. With a highly oriented layered structure and a highly compressible three-dimensional porous frame, wood sponges are extremely hydrophobic, making them ideal for oil-water separation. Currently, the most common approach for creating wood sponge is to first destroy the wood cell wall to obtain a porous-oriented layered structure and then enhance the oil-water separation ability via superhydrophobic treatment. Wood sponge prepared using various experimental methods and different natural woods exhibits distinctive properties in regards to robustness, compressibility, fatigue resistance, and oil absorption ability. As an aerogel material, wood sponge offers multi-action (absorption, filtration) and reusable oil-water separation functions. This paper introduces the advantages of the use of wood sponge for oil-water separation. The physical and chemical properties of wood sponge and its mechanism of adsorbing crude oil are explained. The synthesis method and the properties are discussed. Finally, the use of wood sponge is summarized and prospected.

Do OPEC+ policies help predict the oil price: A novel news-based predictor.

The OPEC+, composed of the Organization of the Petroleum Exporting Countries (OPEC) and non-OPEC oil-producing countries, exerts considerable influence over the global crude oil market. However, existing literature lacks a comprehensive application of this factor in oil price forecasting, primarily due to the complexity of measuring such policy evolutions. To address this research gap, this study develops a news-based OPEC+ policy index based on text mining methods for comprehensive analysis and forecasting of the oil price. First, by crawling and mining news headlines related to OPEC+ production decisions, a dynamic and high-frequency (weekly) OPEC+ policy index is established. Second, the linear and nonlinear relationship between the proposed OPEC+ policy index and the WTI crude oil futures price is thoroughly examined, assessing the potential predictive power of the index in explaining the movements of the crude oil price. Third, the forecasting efficacy of the constructed index on the oil price is rigorously evaluated across eight econometric and machine learning models. Key findings include: (1) The proposed weekly OPEC+ policy index demonstrates strong concordance with OPEC+ production change decisions, exhibiting notable peaks and troughs corresponding to OPEC+ Ministerial Meetings. (2) The relationship analysis demonstrates a strong linear and nonlinear association between the proposed OPEC+ policy index and the crude oil price. (3) For oil price prediction, models incorporating our proposed OPEC+ policy index demonstrate superior performance compared to models without this index. In particular, the index exhibits a more significant predictive effect within three-week forecasting horizons and performs exceptionally well during periods of pandemic and the Russia-Ukraine conflict. In addition, the OPEC+ policy index also exhibits a significant predictive effect on the daily crude oil price and natural gas price, further confirming the robust and powerful forecasting capability of this index within the energy system.

Efficient solar-driven crude oil cleanup via graphene/cellulose aerogel with radial and centrosymmetric design.

Frequent oil spills pose significant threats to ecosystems; therefore, strict requirements are needed for prompt remediation and reclamation of spilled oil. Influenced by the structure of coniferous trees and their water transport, this experiment used cellulose nanofiber (CNF), polyvinyl alcohol (PVA), and methyltrimethoxysilane (MTMS) to prepare radially centrosymmetric aerogels. By utilizing the in-situ polycondensation reaction of MTMS, CNF, and PVA were connected, and the hydrophobicity and mechanical properties of the aerogel were greatly enhanced. Furthermore, the introduction of graphene oxide (GO), enshrouded within the cross-linked network, engenders heightened photo-thermal effects. The resultant composite aerogel exhibits expeditious oil absorption under solar irradiation and radial layered channel architecture, significantly curtailing the crude oil absorption timeframe (achieving a maximum absorption capacity of 51.7 g/g). Moreover, it demonstrates superior performance in rapidly and repeatedly adsorbing highly viscous crude oil, surpassing existing literature. Notably, continuous absorption of high-viscosity crude oil is achieved by integrating the composite aerogel with a peristaltic pump. This study offers a novel approach to the absorption and retrieval of high-viscosity crude oil, broadening the potential application horizons of CNF-based aerogels within environmental remediation.

Impact of various aggregation kinetics on thermophoretic velocity of asphaltene deposition.

Asphaltene deposition may pose serious challenges to flow assurance of crude oil in well columns. Different aggregation kinetics would partly be responsible for asphaltene particle growth ending in deposition on the surface of well columns. This work primarily investigates the thermophoretic deposition velocity caused by temperature gradients inside well columns for various asphaltene aggregation kinetics, including crossover behaviour, sedimentation, reaction-limited aggregation (RLA), and diffusion-limited aggregation (DLA). To do so, the experimental observations of size distribution for a live crude oil was performed at 80 °C and pressure range of 4500-5500 psia. Moreover, various patterns of different size distributions were gathered from the literature for the sake of comparison. Next, a well column in southern Iran was selected to study the kinetic behaviour of thermophoretic velocity of deposition, with a difference between geothermal and static temperatures of around 5 to 50 °C. The non-isothermal deposition velocity was shown to decrease from the top to the bottom of the well column, according to the findings of the study. The results also revealed that the thermophoretic velocity decreases as particle size increases and vice versa. This was confirmed by examining a comparably large range of asphaltene particle sizes, ranging from approximately 100 nm to roughly 9 µm. Practical implications of these findings were also discussed which would provide guidance for mitigation of asphaltene deposition in well columns.

Exposure of Polycyclic Aromatic Hydrocarbons (PAHs) and Crude Oil to Atlantic Haddock (Melanogrammus aeglefinus): A Unique Snapshot of the Mercapturic Acid Pathway.

Fish exposed to xenobiotics like petroleum-derived polycyclic aromatic hydrocarbons (PAHs) will immediately initiate detoxification systems through effective biotransformation reactions. Yet, there is a discrepancy between recognized metabolic pathways and the actual metabolites detected in fish following PAH exposure like oil pollution. To deepen our understanding of PAH detoxification, we conducted experiments exposing Atlantic haddock (Melanogrammus aeglefinus) to individual PAHs or complex oil mixtures. Bile extracts, analyzed by using an ion mobility quadrupole time-of-flight mass spectrometer, revealed novel metabolites associated with the mercapturic acid pathway. A dominant spectral feature recognized as PAH thiols set the basis for a screening strategy targeting (i) glutathione-, (ii) cysteinylglycine-, (iii) cysteine-, and (iv) mercapturic acid S-conjugates. Based on controlled single-exposure experiments, we constructed an interactive library of 33 metabolites originating from 8 PAHs (anthracene, phenanthrene, 1-methylphenanthrene, 1,4-dimethylphenanthrene, chrysene, benz[a]anthracene, benzo[a]pyrene, and dibenz[a,h]anthracene). By incorporation of the library in the analysis of samples from crude oil exposed fish, PAHs conjugated with glutathione and cysteinylglycine were uncovered. This qualitative study offers an exclusive glimpse into the rarely acknowledged mercapturic acid detoxification pathway in fish. Furthermore, this furnishes evidence that this metabolic pathway also succeeds for PAHs in complex pollution sources, a notable discovery not previously reported.

Exploring the use of microbial enhanced oil recovery in Kazakhstan: a review.

Microbial enhanced oil recovery (MEOR) is a promising method for improving oil recovery from challenging reservoirs such as those found in Kazakhstan. MEOR relies on the activities of microorganisms to modify the properties of the reservoir, such as reducing the oil viscosity, increasing the reservoir permeability, and generating by-products that mobilize the oil. Implementing MEOR in Kazakhstan could lead to significant economic benefits for the country by increasing oil production and royalties from fossil fuel exports. Oil production in Kazakhstan has seen fluctuations in recent years, with 2018 recording a production level of 1.814 million barrels per day. Among regions, Atyrau region contributed the most to oil production with 23.4 million tons of oil. Following Atyrau, the Mangystau region produced 8.2 million tons, and Aktobe produced 2.4 million tons. Overall, the use of MEOR in Kazakhstan's oil fields could offer a promising solution for enhanced oil recovery, while minimizing environmental impact and cost. While specific data on the current use of MEOR in field conditions in Kazakhstan might be limited, the fact that studies are underway suggests a growing interest in applying this technology in the country's oil fields. It is exciting to think about the potential benefits these studies could bring to Kazakhstan's oil industry once their findings are implemented in field operations. These studies have significant implications for Kazakhstan's oil production in the future.

Oil uptake via marine snow: Effects on blue mussels (Mytilus sp.).

Accidental oil spills into the ocean can lead to downward transport and settling of oil onto the seafloor as part of marine snow, as seen during the Deepwater Horizon incident in 2010 in the Gulf of Mexico. The arctic and subarctic regions may favor conditions leading to this benthic oil deposition, prompting questions about the potential impacts on benthic communities. This study investigated the effects of oil-contaminated marine snow uptake on the blue mussel (Mytilus sp.). We exposed mussels for four days to 1) oil-contaminated marine snow (MOS treatment), or to 2) chemically-enhanced water-accommodated fraction (CEWAF) of oil plus unaggregated food particles (CEWAF treatment). Both oil treatments received the same nominal concentration of oil and food. Two controls were included: 1) Clean seawater plus unaggregated food (agg-free control) and 2) clean seawater plus marine snow (marine snow control). After the exposure, mussels were allowed to recover for ten days under clean, running seawater. Samples were taken right before and after the exposure period, and after the recovery phase for the following endpoints: distribution (partitioning) of oil compounds between seawater and MOS, and between seawater and mussel tissue; DNA damage (assessed via the comet assay); clearance rate; and condition index [tissue dry weight (g) divided by shell length (mm)]. Some discernable patterns were found in the partitioning of oil compounds between seawater and MOS. However, these patterns did not translate to any significant differences in the partitioning of oil compounds into mussel tissue between the two oil treatments. DNA damage did not exceed background levels (10% tail DNA or less; to be expected in healthy, viable cells) at any sampling time point, but significantly higher DNA damage was observed in CEWAF-T compared to MOS-T mussels after the recovery phase. After the exposure, a significant difference emerged in the clearance rate between the CEWAF treatment and the agg-free control, but not between the MOS treatment and the marine snow control. All mussels except those from the CEWAF treatment exhibited an increased condition index after the exposure time. Together, these results suggest that aggregates could moderate the effects of oil exposure on blue mussels, possibly by providing better, more concentrated nutrition than unaggregated food particles.

Phytoremediation of crude oil-contaminated soil using Vigna Unguiculata and associated rhizosphere bacteria.

Persistent crude oil contamination poses a significant environmental challenge. In this study, the efficacy of Vigna unguiculata (L.) and associated rhizospheric microorganisms in remediating crude oil-contaminated soil within a microcosm setting was investigated. A randomized block design was employed, and soil samples were subjected to varying degrees of contamination: 0% (UR), 2.5% (CR2), 5.0% (CR5), 7.5% (CR7), and 10.0% (CR10) w/w crude oil. The investigation aimed to assess the potential of Vigna unguiculata (L.) in mitigating crude oil contamination across these defined contamination gradients. The plant growth and crude oil removal were monitored concurrently post-emergence. Plant emergence and growth were significantly affected due to contamination, especially among plants in CR5 and CR10. The bacterial population was higher in the rhizosphere, and the treatments with lower hydrocarbon contamination. It was shown that plant density encouraged the growth of bacterial communities. Significant reduction in soil TPH was observed in CR2 (76.61%) and CR7 (65.88%). There was a strong correlation between plant growth and oil-utilizing bacterial population (r2 = 0.966) and plant growth and hydrocarbon reduction (r2 = 0.956), signifying the role of plant-bacterial synergy. Saturate fractions (C30 - C32) were significantly degraded to lower molecular weight compounds (C11 - C14). Except in CR5 and CR10, the remediation within the cowpea rhizosphere was effective even at regulatory standards. Understanding the rhizosphere ecological dynamics would further highlight the role the bacteria played; hence, it is recommended.

The present study established a direct link between bacterial-plant interaction and biodegradation of crude oil. It extensively explored the nature of the degradation and also the fate of the residual oil. The present study achieved high rate of TPH removal within 12 weeks using cowpea alone as against the several previous reports that used other stimulants.

Compositional change of bacterial communities in oil-polluted seawater amid varying degrees of nanoplankton bacterivory.

Petroleum hydrocarbons are being released into the marine environment continuously. They will undergo weathering and may eventually be biodegraded by bacteria and other microbes. While nanoplankton (2-20 µm) are the major consumers of marine bacteria, their effect on the process of biodegradation of oil hydrocarbons is still debated. A 14-day microcosm experiment was conducted to investigate the effects of crude oil hydrocarbons on nanoplankton bacterivory and bacterial community in coastal waters. The coefficients of population growth (0.56-1.80 d-1 for all treatments considered) and grazing mortality (0.38-1.65 d-1 for all treatment considered) of bacteria estimated with the dilution method did not differ among the treatments of control (Ctrl), low dose chemically dispersed oil (LDOil, 2 µL L-1 of crude oil), and high dose chemically dispersed oil (HDOil, 8 µL L-1 of crude oil). Bacterial abundance ranged between 0.21-0.86 × 106 cells mL-1 on average for all treatments. The lack of drastic increases in the cell density of bacterial cells in the oil-loaded treatments was observed throughout the experiment period. Sequencing analysis of the 16S rRNA gene revealed the progressive changes in the community compositions of bacteria in all treatments. The relatively high abundance of oil-degrading bacteria, including Cycloclasticus and Alcanivorax on Days 3-14 of the experiment reflected the presence of biodegradation of oil in the LDOil and HDOil treatments. Throughout the 14 days, the community composition of bacteria in the LDOil and HDOil treatments became more similar and they both differed from that in the Ctrl treatment. This study concluded that, in oil-polluted seawater, the changes in the bacterial community composition were mainly resulting from the addition of chemically dispersed crude oil.

A solar-driven nanocellulose Janus aerogel with excellent floating stability and dual functions of oil-water separation and photocatalytic degradation of organic pollutants.

Effective and practical cleanup of viscous crude oil spills is extremely important in real harsh marine environments. Herein, we designed a solar-driven, nanocellulose-based Janus aerogel (Janus-A) with excellent floating stability and dual function of oil-water separation and degradation of aqueous organic pollutants. Janus-A, with its amphiprotic nature, was prepared through polypyrrole (PPy) deposition, freeze-drying, octyltrichlorosilane (OTS) impregnation, TiO2 spraying on the bottom surface, and UV irradiation treatment. The photothermal conversion effect of PPy coating raised the surface temperature of aerogel to 75.8 °C within 6 min under one simulated solar irradiation, which greatly reduced the viscosity of the crude oil and increased the absorption capacity of the aerogel to 36.7 g/g. Benefiting from the balance between the buoyancy generated by the hydrophobic part and water absorption of the hydrophilic part, Janus-A showed excellent floating stability under simulated winds and waves. In addition, Janus-A exhibited high degradation efficiency for organic pollutants in water owing to the synergistic photocatalytic properties of TiO2 and PPy. These excellent performances make Janus-A ideal for integrated water-oil separation and water remediation.

Acidic process fluid from hydrothermal carbonization improves dechlorination of waste PVC and produces clean solid and liquid fuels.

Dechlorination of waste PVC (WPVC) by hydrothermal treatment (HTT) is a potential technology for upcycling WPVC in order to create non-toxic products. Literature suggests that acids can improve the HTT process, however, acid is expensive and also results in wastewater. Instead, the acidic process fluid (PF) of hydrothermal carbonization (HTC) of orange peel was utilized in this study to enhance the dechlorination of WPVC during HTT. Acidic HTT (AHTT) experiments were carried out utilizing a batch reactor at 300-350 °C, and 0.25-4 h. The finding demonstrated that the dechlorination efficiency (DE) is high, which indicates AHTT can considerably eliminate chlorine from WPVC and relocate to the aqueous phase. The maximum DE of 97.57 wt% was obtained at 350 °C and 1 h. The AHTT temperature had a considerable impact on the WPVC conversion since the solid yield decreases from 56.88 % at 300 °C to 49.85 % at 350 °C. Moreover, AHTT char and crude oil contain low chloride and considerably more C and H, leading to a considerably higher heating value (HHV). The HHV increased from 23.48 to 33.07 MJ/kg when the AHTT time was raised from 0.25 to 4 h at 350 °C, indicating that the AHTT time has a beneficial effect on the HHV. The majority fraction of crude oil evaporated in the boiling range of lighter fuels include gasoline, kerosene, and diesel (57.58-83.09 wt%). Furthermore, when the AHTT temperature was raised from 300 to 350 °C at 1 h, the HHV of crude oils increased from 26.11 to 33.84 MJ/kg. Crude oils derived from AHTT primarily consisted of phenolic (50.47-75.39 wt%), ketone (20.1-36.34 wt%), and hydrocarbon (1.08-7.93 wt%) constituents. In summary, the results indicated that AHTT is a method for upcycling WPVC to clean fuel.