Enhancing refinery heavy oil fractions analytical performance through real-time predicative modeling.

This study introduces a suite of robust models aimed to advance the determination of physiochemical properties in heavy oil refinery fractions. By integrating real-time analytical technique inside the refinery analysis, we have developed a single analyzer capable of employing six partial least square regression equations. These designed models enable to provide real-time prediction of critical petroleum properties, such as sulfur content, micro carbon residues (MCR), asphaltene content, heating value, and the concentrations of nickel and vanadium metals. Specifically tailored for heavy oil in refinery feeds with an American petroleum institute (API) gravity range of 3° to 32° and sulfur content of 2.8 to 5.5 wt%, the models streamline the analysis process within refinery operations, bridging the gap between catalytic and non-catalytic processes across refinery units. The accuracy of our physiochemical prediction models has been validated against American Society for Testing and Materials (ASTM) standards, demonstrating their capability to deliver precise real-time property values. This approach not only enhances the efficiency of refinery analysis but also sets a new standard for the monitoring and optimization of heavy oil processing in real-time approach.

Cancer incidence in Swedish oil refinery workers exposed to benzene.

BACKGROUND: Oil refinery workers are exposed to benzene, which is a well-known cause of leukaemia, but results on leukaemia in oil refinery workers have been mixed, and the data on workers' exposure is limited. Oil refinery workers are also exposed to asbestos and several studies have shown increased risk of mesothelioma. AIM: The objective was to investigate cancer incidence, especially leukaemia, at low to moderate exposure to benzene in an update of a previous study of employees at three Swedish oil refineries. METHODS: Cancer incidence was followed up in 2264 men (1548 refinery operators) employed at three oil refineries in Sweden for at least one year. Job types and employment times were collected from complete company files. A retrospective assessment of the benzene exposure was performed by occupational hygienists in collaboration with the refineries using historic measurements as well as detailed information on changes in the industrial hygiene and technological developments. Cases of cancer were retrieved by a linkage with the Swedish Cancer Register through 35-47 years of follow-up and standardized incidence ratios (SIR) with 95% confidence intervals (CI) were calculated. RESULTS: In total, 258 tumors had occurred versus 240 expected (SIR 1.07; 95% CI 0.95-1.21). There were 10 cases of leukaemia, all in refinery operators (SIR 2.4; 95% CI 1.18-4.51). There were three cases of pleural mesothelioma, two of which in refinery operators. The mean estimated cumulative benzene exposure for the cases of leukaemia was 7.9 ppm-years (median 4.9, range 0.1-31.1). DISCUSSION: The study suggests that low to moderate average cumulative benzene exposure increases the risk of leukaemia. Limitations include the modest number of cases and potential misclassification of exposure. CONCLUSION: The present study indicated an increased risk of leukaemia in male oil refinery workers with low to moderate exposure to benzene.

Solvent-thermal approach of MIL-100(Fe)/Cygnea/Fe3O4/TiO2 nanocomposite for the treatment of lead from oil refinery wastewater (ORW) under UVA light.

The main purpose of this research endeavor is to reduce lead concentrations in the wastewater of an oil refinery through the utilization of a material composed of oyster shell waste (MIL-100(Fe)/Cygnea/Fe3O4/TiO2. Initially, iron oxide nanoparticles (Fe3O4) were synthesized via solvent-thermal synthesis. It was subsequently coated layer by layer with the organic-metallic framework MIL-100 (Fe) using the core-shell method. Additionally, the solvent-thermal method was utilized to integrate TiO2 nanoparticles into the magnetic organic-metallic framework's structure. Varieties of analytical analysis were utilized to investigate the physical and chemical properties of the synthetic final photocatalyst. Nitrogen adsorption and desorption technique (BET), scanning electron microscopy (SEM), scanning electron diffraction pattern (XRD), and transmission electron microscopy (TEM). Following the characterization of the final photocatalyst, the physical and chemical properties of the nanoparticles synthesized in each step, several primary factors that significantly affect the removal efficiency in the advanced oxidation system (AOPs) were examined. These variables consist of pH, photocatalyst dosage, lead concentration, and reaction temperature. The synthetic photocatalyst showed optimal performance in the removal of lead from petroleum wastewater under the following conditions: 35 °C temperature, pH of 3, 0.04 g/l photocatalyst dosage, and 100 mg/l wastewater concentration. Additionally, the photocatalyst maintained a significant level of reusability after undergoing five cycles. The findings of the study revealed that the photocatalyst dosage and pH were the most influential factors in the effectiveness of lead removal. According to optimal conditions, lead removal reached a maximum of 96%. The results of this investigation showed that the synthetic photocatalyst, when exposed to UVA light, exhibited an extraordinary capacity for lead removal.

Response surface methodology optimization of the effect of pH, contact time, and microbial concentration on chemical oxygen removal potential of vegetable oil industrial effluents.

The vegetable oil refinery industry generates highly polluted effluents during oil production, necessitating proper treatment before discharge to prevent environmental hazards. Treating such wastewater has become a major environmental concern in developing countries. Chemical oxygen demand (COD) is a key parameter in assessing the wastewater's organic pollutant load. High COD levels can lead to reduced dissolved oxygen in water bodies, negatively affecting aquatic life. Various technologies have been employed to treat oily wastewater, but microbial degradation has gained attention due to its potential to remove organic pollutants efficiently. This study aims to optimize the biodegradation treatment process for vegetable oil industrial effluent using response surface methodology (RSM). The wastewater's physicochemical properties were characterized to achieve this, and COD removal was analyzed. Furthermore, RSM was used to investigate the combined effects of pH, contact duration, and microbial concentration on COD removal efficiency. The result showed that the microbial strain used recorded a maximum COD removal of 92%. Furthermore, a quadratic model was developed to predict COD removal based on the experimental variables. From the analysis of variance (ANOVA) analysis, the model was found to be significant at p < 0.0004 and accurately predicted COD removal rates within the experimental region, with an R2 value of 90.99% and adjusted R2 value of 82.89%. Contour plots and statistical analysis revealed the importance of contact duration and microbial concentration on COD removal. PRACTITIONER POINTS: Response surface methodology (RSM) optimization achieved a significant chemical oxygen demand (COD) removal efficiency of 92% in vegetable oil industrial effluents. The study's success in optimizing COD removal using RSM highlights the potential for efficient and environmentally friendly wastewater treatment. Practitioners can benefit from the identified factors (pH, contact time, and microbial concentration) to enhance the operation of treatment systems. The developed predictive model offers a practical tool for plant operators and engineers to tailor wastewater treatment processes. This research underscores the importance of sustainable practices in wastewater treatment, emphasizing the role of microbial degradation in addressing organic pollutant loads.

Phytotoxicity assessment of treated vegetable oily wastewater via environmentally coagulation/flocculation and membrane filtration technologies using lettuce (Lactuca sativa) seeds.

The present investigation highlights the necessity of monitoring some basic physico-chemical water quality indicators and their phytotoxic effect using ecotoxicological bioassays such as "seed germination tests." The phytotoxicity of raw and treated vegetable oil refinery wastewater (VORW) using different treatment processes was assessed through some physiological responses (relative seed germination (RSG), seedling elongation, and germination index (GI)) using Lactuca sativa cultivar. Biotest results of different raw water samples revealed a noticeable correlation between the organic matter content and water phytotoxicity. In fact, VORW showed a very low RSG (17 ± 0.7 to -47 ± 0.58%) and high phytotoxic effects (GI < 50%). The use of coagulation/flocculation (CF) allowed a satisfactory phytotoxicity removal where RSG obtained ranged from 83 ± 1.58 to 90 ± 1.2%. However, the effluent still presents high to moderate phytotoxicity since GI remained below 80% which indicates the presence of toxic elements remaining after CF treatment. When VORW were treated using membrane processes, their phytotoxicity was gradually decreased with the decrease in the membrane pore size. The use of microfiltration membranes (MF), with pore size of 5 µm, 1.2 µm, 0.45 µm, and 0.22 µm, showed RSG values ranged from 37 ± 1.15 to 77 ± 1.68% and GI of less than 80% indicating a moderate to high phytotoxicity. However, the use of ultrafiltration (UF) membranes with molecular weight cut-off (MWCO) of 100 kDa, 30 kDa, and 10 kDa made it possible to achieve an RSG of 100% and an IG exceeding 80% showing that the VORW-treated using UF does not exhibit any phytotoxicity effect. Hence, UF appears to be the most efficient and environmentally friendly technology that could be used for safely treated VORW irrigation purposes compared to CF and MF processes.

Removal of pollutants and accumulation of high-value cell inclusions in a batch reactor containing Rhodopseudomonas for treating real heavy oil refinery wastewater.

Treating wastewater using purple non-sulfur bacteria (PNSB) is an environmentally friendly technique that can simultaneously remove pollutants and lead to the accumulation of high-value cell inclusions. However, no PNSB system for treating heavy oil refinery wastewater (HORW) and recovering high-value cell inclusions has yet been developed. In this study, five batch PNSB systems dominated by Rhodopseudomonas were used to treat real HORW for 186 d. The effects of using different hydraulic retention times (HRT), sludge retention times (SRT), trace element solutions, phosphate loads, and influent loads were investigated, and the bacteriochlorophyll, carotenoid, and coenzyme Q10 concentrations were determined. The community structure and quantity of Rhodopseudomonas in the systems were determined using a high-sequencing technique and quantitative polymerase chain reaction technique. The long-term results indicated that phosphate was the limiting factor for treating HORW in the PNSB reactor. The soluble chemical oxygen demand (SCOD) removal rates were 67.03% and 85.26% without and with phosphate added, respectively, and the NH4+-N removal rates were 32.18% and 89.22%, respectively. The NO3--N concentration in the effluent was stable at 0-3 mg/L with or without phosphate added. Adding phosphate increased the Rhodopseudomonas relative abundance and number by 13.21% and 41.61%, respectively, to 57.35% and 8.52 × 106 gene copies/µL, respectively. The SRT was the limiting factor for SCOD removal, and the bacteria concentration was the limiting factor for nitrogen removal. Once the inflow load had been increased, the total nitrogen (TN) removal rate increased as the HRT increased. Maximum TN removal rates of 64.46%, 68.06%, 73.89%, 82.15%, and 89.73% were found at HRT of 7, 10, 13, 16, and 19 d, respectively. The highest bacteriochlorophyll, carotenoid, and coenzyme Q10 concentrations were 2.92, 4.99, and 4.53 mg/L, respectively. This study provided a simple and efficient method for treating HORW and reutilizing resources, providing theoretical support and parameter guidance for the application of Rhodopseudomonas in treating HORW.

Investigation of a membrane bioreactor's performances in treating sunflower oil refinery wastewater containing high oleic acid at different SRTs.

This study investigated the MBR performance, sludge morphology, and membrane fouling potential in treating sunflower oil refinery wastewater containing high oleic acid at three different SRTs of 10 days, 40 days, and infinite. The analysis of mixed liquor morphology including sludge volume index, PSD, EPS, and SMP showed that the sludge flocs compressibility and bioflocculation considerably improved at 40-days SRT. Additionally, at this SRT, the mixed liquor O&G, COD, and SMP accumulation were low, and the microbial activity and COD removal were enhanced. The gas chromatography/mass spectrometry analysis results confirmed the formation of three different new compounds related to non-readily biodegradable recalcitrant oily compounds and SMP at all SRTs. The analysis of mixed liquor EPS, PSD, SMP, and effluent COD at three different SRTs suggests that under the industrial conditions of MBR operation treating SORW with high oleic acid, the optimal operating conditions are predicted to be at 40-days SRT.

Soft Sensing of LPG Processes Using Deep Learning.

This study investigates the integration of soft sensors and deep learning in the oil-refinery industry to improve monitoring efficiency and predictive accuracy in complex industrial processes, particularly de-ethanization and debutanization. Soft sensor models were developed to estimate critical variables such as the C2 and C5 contents in liquefied petroleum gas (LPG) after distillation and the energy consumption of distillation columns. The refinery's LPG purification process relies on periodic sampling and laboratory analysis to maintain product specifications. The models were tested using data from actual refinery operations, addressing challenges such as scalability and handling dirty data. Two deep learning models, an artificial neural network (ANN) soft sensor model and an ensemble random forest regressor (RFR) model, were developed. This study emphasizes model interpretability and the potential for real-time updating or online learning. The study also proposes a comprehensive, iterative solution for predicting and optimizing component concentrations within a dual-column distillation system, highlighting its high applicability and potential for replication in similar industrial scenarios.

NO2 emissions from oil refineries in the Mississippi Delta.

Of the >17,943 thousand barrels per calendar day (bbl/d) of oil refining capacity located in the US, the Petroleum Administration for Defense District 3 (PADD-3) region has the largest number of refineries and accounts for >53 % (or 9607 tbbl/d) of all US oil refining capacity. Processing facilities in this area are mainly located on the Gulf of Mexico coast in Texas and Louisiana. This study selected a sub-region for analysis within the Mississippi River delta in the state of Louisiana between the cities of New Orleans and Baton Rouge. This region is characterized by intensive industrial activity connected with oil refining and related activities. The TROPOspheric Monitoring Instrument (TROPOMI) detected highly localized NO2 vertical column densities (VCDs) over the two largest US refineries in Baton Rouge (503,000 bbl/d) and Garyville (578,000 bbl/d). TROPOMI NO2 VCD over these stations were 100 µmol/m2 and 80 µmol/m2, respectively. A high correlation coefficient (r = 0.65, p < 0.05) was also found between TROPOMI NO2 and population density. Data from the National Emissions Inventory (NEI) showed high NOx emissions from refineries and other industries including coal-fired power generation, chemical, and aluminum processing plants. The results of the NO2 analysis are of practical interest for a comparative assessment of air pollution, as well as for the exchange of best practices in the field of low-waste fuel combustion technologies.

Sustainability of the anaerobic digestion of oil refinery secondary sludge.

Among the waste generated at oil refineries, secondary sludge from biological wastewater treatment processes (activated sludge systems) stands out. This paper aimed to assess the use of anaerobic digestion (AD) to treat sludge by SWOT (Strength, Weakness, Opportunity, and Threat) analysis, ranking the different factors based on sustainability criteria. Additionally, the SWOT factors were matched (TOWS matrix) to help interpret the results. AD was found to be compatible with sustainability. The results demonstrated that the strength of AD (reduced organic load) compensates for its weaknesses (need for operational control and initial implementation costs), thereby avoiding the threat (sludge composition) and making the most of the opportunity (lower disposal cost). AD and co-digestion (added with food waste) used to treat oil refinery sludge showed that around 60% of the factors analyzed were confirmed experimentally. It was concluded that AD should be considered in the sustainable treatment of oil refinery waste activated sludge, especially when mixed with other readily biodegradable wastes.

Anaerobic digestion (AD) is a potential treatment for secondary sludge from refineries.AD is compatible with sustainability.Anaerobic co-digestion of refinery sludge contributed positively to sustainable treatment.The strength (reduced organic load) of AD counteract its weaknesses (operational control and implementation costs).The threat of AD (sludge composition) should be avoided and the opportunity (low disposal cost) leveraged.

Treatment vegetable oil refinery wastewater by sequential electrocoagulation-electrooxidation process.

In the present study a sequential process composed of electrocoagulation (EC) followed by electrooxidation (EO) was utilized at the laboratory scale to remove the chemical oxygen demand (COD) from wastewater generated in Iraqi vegetable oil refinery plant.in the EC, impacts of operating variables such as current density (10-30 mA cm-2) and pH (4-10),and EC time (30-90 min) on the COD removal (RE%) were investigated using response surface methodology (RSM) based on Box- Behnken design(BBD). a mathematical correlation that relates the operating factors with RE% was developed and its regression coefficient was 99.02% confirming the significant of the model. Response surface plots showed that RE% increased with increasing current density and time while it decreased with increasing pH. The optimum removal with a lower cost for EC process were achieved at current density of 30mA/cm2, pH of 4, and electrolysis time of 90 min in which RE% of 69.19% was obtained with requirement of 0.513kWh/kg COD as specific energy consumption (SEC). The effluent exit from EC was treated by EO for a period of 240min at a current density of 30mA/cm2 and an initial pH value of 4 to obtain RE% of 96% at SEC of 1.554 kWh/kg COD. Combining EC with EO resulted in a total RE% of 98.72% and a total SEC of 2.067 kWh/kg COD. Based on the results of present study, the applicability of a sequential electrocoagulation-electrooxidation process for treatment vegetable oil wastewaters is feasible.

The effect of petroleum levels on some soil biological properties under phytoremediation and bioaugmentation.

With the development of industries and excessive use of petroleum compounds, petroleum pollution has become a serious threat to the environment. The aim of this study was to the effect of petroleum levels on the biological activities of soil affected by phytoremediation and bioaugmentation. A surface soil sample was collected from the polluted areas around Bandar Abbas Oil Refinery Company, and the petroleum-degrading bacteria were isolated. M. yunnanensis (native) was selected among the isolated colonies for further experiment. The used soil in this study was a surface soil collected from Baghu region of Bandar Abbas, Sothern Iran, and treatments were added to soil samples. To evaluate removal of petroleum levels (0, 4, and 8%) from the soil by phytoremediation (control, sorghum, barley, and bermudagrass) and bioaugmentation (control, A. brasilense (non-native) and M. yunnanensis) and bioaugmented phytoremediation, a factorial pot experiment with completely randomized design and three replications was performed. The results demonstrated that sorghum and bermudagrass were more resistant than barley to the toxic effects of petroleum. Positive effect of bacteria on dry weight in polluted soil was greater than in the non-polluted soil. The degradation of petroleum reaches 77% in sorghum + M. yunanesis + 4% petroleum. Plants had stronger ability to degrade total petroleum hydrocarbon (TPH), while bacteria could better degrade polyaromatic hydrocarbons (PAHs). Application of bacteria and plants stimulated soil biological characteristics (dehydrogenase, arylsulfatase, lipase, bacterial population, and respiration) in polluted soil. Among measured enzymes, dehydrogenase exhibited a stronger response to petroleum levels. Four-percent level had greater irritating effect on soil biological properties. Plants and bacteria rely on differences in biological properties to attain synergy in petroleum degradation. Results indicated that M. yunnanensis has a high ability to remove petroleum from soil, and plants enhance the efficiency of this bacterium.

Ecological and human health risk assessment of polycyclic aromatic hydrocarbons (PAH) in Tigris river near the oil refineries in Iraq.

Recent Iraqi battles against ISIS in 2014 and 2015 resulted in the destruction or severe damage to several refineries' infrastructure. This, along with other factors, has led to the release and accumulation of a wide range of hazardous chemicals into the environment, for instance, polycyclic aromatic hydrocarbons (PAH). Thus, for the first time, a comprehensive 16 PAHs measurements campaign over the course of six months near the oil refineries along the Tigris River and its estuaries was investigated. The 16 PAHs concentrations in surface water and the sediments for the following oil refineries: Baiji, Kirkuk, Al-Siniyah, Qayyarah, Al-Kasak, Daura, South Refineries Company, and Maysan were examined. The overall findings indicated that the 16 PAHs concentrations ranged from 567.8 to 3750.7 ng/L for water and 5619.2-12795.0 ng/g for sediment. Water samples in South Refineries Company recorded the highest PAH concentrations while Baiji oil refinery registered the highest PAH concentrations in the sediment samples. The percentages of high molecular weight PAH (5-6 rings) in water and sediment samples were the highest, ranging from 49.41% to 81.67% and from 39.06% to 89.39% of total PAH for water and sediment, respectively. The majority of 16 PAHs measured in water and sediment samples of the Tigris River were derived from pyrogenic sources. Based on sediment quality guidelines (SQGs), most sites showed a possible effect range with occasional biological effects of most of the PAH concentrations in all sediments' samples. The calculated incremental lifetime cancer risk (ILCR) value was high risk with adverse health effects, including cancer.

Identification of cultivable bacterial strains producing biosurfactants/bioemulsifiers isolated from an Algerian oil refinery.

Algerian petrochemical industrial areas are usually running spills and leakages of hydrocarbons, which constitutes a major source of toxic compounds in soil such as aromatic hydrocarbons. In this paper, samples of crude oil-polluted soil were collected from Skikda's oil refinery and were subjected to mono and polyaromatic hydrocarbons threshold assessment. Soil physicochemical parameters were determined for each sample to examine their response to pollution. Amid 34 isolated bacteria, eleven strains were selected as best Biosurfactants (Bs)/Bioemulsifiers (Be) producers and were assigned to Firmicutes and Proteobacteria phyla based on molecular identification. Phylogenetic analysis of partial 16S rDNA gene sequences allowed the construction of evolutionary trees by means of the maximum likelihood method. Accordingly, strains were similar to Bacillus spp., Priesta spp., Pseudomonas spp., Enterobacter spp. and Kosakonia spp. with more than 95% similarity. These strains could be qualified candidates for an efficient bioremediation process of severally polluted soils.

Atmospheric odor dispersion from oil refinery flare system: a case study.

A flare stack is an indispensable device in the oil and gas industry for allowing the safe combustion of gases into the atmosphere, especially during emergencies. However, it is not ideal for the routine disposal of gaseous waste, as it is subject to meteorological influences and poor operational control. In addition, it can be affected by toxic currents and thus pose a potential risk of odors; in view of this, an assessment must be made of the implications of burning on the environment and health. Atmospheric dispersion modelling has proved to be a very useful tool for this purpose. In light of this, an attempt has been made in this work to evaluate the impact of H2S on the well-being (odor perception) of the community in the surrounding area of an oil refinery, where the temporary burning of rich gas in H2S occurs in a chemical flare, and operational factors have an influence on atmospheric dispersion. The odor assessment was carried out with the aid of AERMOD which was adapted to estimate the maximum odor concentration for very short periods by means of peak-to-mean ratios. The results showed that H2S detection can reach a probability rate of 42% at 3.5 km distance from the flare (in a time interval of 5 s) with a relatively high degree of annoyance (3.0 AU). However, some operational procedures can reduce the probability of odor detection to 29% and the degree of annoyance to 2.6 AU.

Robust productivity growth and efficiency measurement with undesirable outputs: evidence from the oil industry.

This paper aims to contribute to the contemporary and imperative research on the performance and productivity growth of the oil industry. Among cutting edge methods, frontier analysis is a successful approach that has been widely used to assess the efficiency and productivity of entities with multiple resources and multiple outputs. This study first develops a unique framework based upon data envelopment analysis (DEA) to measure efficiency and productivity in the way that it tackles the uncertainty in data and undesirable outputs and, in turn, provides useful information to decision-makers. An adaptive robust optimisation is utilised to combat uncertain data whose distributions are unknown and consider the nexus between the level of conservatism and decision-makers' risk preference. The key advantage of the proposed robust DEA approach is that the results remain relatively unchanged when uncertain conditions exist in the problem. An empirical study on the oil refinery is presented in situations of data uncertainty along with considering CO2 emissions as the undesirable output to conduct environmental efficiency and productivity analysis of the 25 countries over the period 2000-2018. The empirical results obtained from the proposed approach give some imperative implications. First, results show that the price of robustness does not affect identically for varying technologies when assessing productivity in a global oil market, and the USA oil industry is observed as the highest productivity growth in all cases confirming its efforts for the rapid rise in oil extraction and production at low costs. There may be practical lessons for other nations to learn from the USA oil industry to improve productivity. Findings also support a considerable regress during the 2008 Global Financial Crisis in the oil industry compared to the rest of the periods in question, and due to monetary and fiscal stimulus, there is a sharp productivity growth from 2009 to 2011. The other implication that can be drawn is that the GDP growth rate and technology innovation can more effectively improve the productivity of the oil industry across the globe. Supplementary Information: The online version contains supplementary material available at 10.1007/s00291-022-00683-y.

Free-living amoebae in an oil refinery wastewater treatment facility.

Free Living Amoebae (FLA) are ubiquitous microorganisms reported from harsh environmental conditions. Oil refinery facilities consume vast volumes of water during their processes, generating a large amount of wastewater. The present study aimed to evaluate the wastewater treatment process in an oil refinery wastewater treatment facility (ORWWTF) for the presence of FLA. Water samples were collected from an oil refinery wastewater (ORWW) for nine months. After recording physical-chemical features, samples were cultivated onto non-nutrient agar (NNA). The discriminative fragments of the ribosomal RNA (rRNA) gene were amplified and sequenced to characterize the isolated FLA. Phylogenetic tree, and network analysis were employed to evaluate genetic relationships. The thermo- and osmotolerant tests were performed on the isolated FLA. Twenty-five (32.9%) samples were positive for FLA cultivation. Acanthamoeba spp., Vahlkampfiids, and Vermamoeba spp. were detected, of which Acanthamoeba species were predominant. There was no statistical correlation between pH, NH3, PO4, H2S, and TDS with the presence of FLA. A statistical correlation between the presence of FLA and the type of wastewater treatment plants (WWTPs) was significant (P-value = 0.011). All Acanthamoeba spp. isolates belonged to the genotypes T4 (17/21; 80.95%) and T11 (4/21; 19.05%). Vahlkampfiids were Naegleria spp., (7/10; 70%), Tetramitus aberdonicus (1/10; 10%), Learamoeba spp., (1/10; 10%), and Vahlkampfia spp., (1/10; 10%). All three Vermamoeba spp. were V. vermiformis. The ORWW contains toxic materials, and a few microorganisms can stay active in these environments. This is the first study which isolates FLA from such super harsh conditions. For the first time, T. aberdonicus, and Learamoeba spp., were isolated from oily wastewater. Our findings signify the concern due to the distribution of potentially pathogenic FLA to downstream lands via treated wastewater that may be released after treatment processing.

Enhanced pollutants removal and high-value cell inclusions accumulation with Fe2+ in heavy oil refinery treatment system using Rhodopseudomonas and Pseudomonas.

Metal ions has been widely used as a method of improving pollutant removal efficiency in wastewater biological treatment system. In order to enhance pollutants removal and high-value cell inclusions accumulation in heavy oil refinery wastewater treatment systems using PSB, different reactors were built feeding with different Fe2+ concentrations respectively, and run with enriching Rhodopseudomonas and Pseudomonas in the reactors. Solute chemical oxygen demand (SCOD), ammonia (NH4+-N), nitrate nitrogen (NO3--N), nitrous nitrogen (NO2--N), Fe2+, and related cell inclusions were all detected, moreover, microbial community structure and the quantity of Rhodopseudomonas and Pseudomonas were also detected. The results showed that at the optimal dosage of Fe2+ with 20 mg/L, the corresponding removal ratios of solute chemical oxygen demand and ammonia were 73.51% and 92.26%, respectively. The yields of carotenoid, bacteriochlorophyll, and coenzyme Q10 were 11.18, 6.75, and 9.84 mg/g-DCW respectively. Furthermore, with 20 mg/L Fe2+ dosage, the relative abundance and gene number of Rhodopseudomonas were the highest in the system, which were 91.57% and 1.843 × 106 gene copies/µL, while Fe2+ had no obvious effect on the growth of Pseudomonas. The results showed that adding Fe2+ has improved the removal of pollutants and accumulation of high-value cells inclusions, also provided theoretical guidance for the treatment of heavy oil refinery wastewater using PSB.

Anaerobic co-digestion of oil refinery waste activated sludge and food waste.

The technology of anaerobic co-digestion to treat the excess biological sludge discharged from activated sludge systems in oil refineries was evaluated in bench scale experiments. Mixing food waste rich in fruits and vegetables with this sludge increased the reduction of volatile solids and biogas yield. An experimental design indicated that the best co-digestion condition was the use of waste activated sludge without previous dewatering (3.5% total solids) and food waste in an 80:20 ratio (% v/v), without the addition of inoculum. After 45 days at 35 °C, this condition resulted in volatile solid (VS) removal of 52% and biogas yield of 80.7 mL biogas/g VSadded, against only 19% and 38.5 mL biogas/g VSadded in mono-digestion of sludge alone. Anaerobic co-digestion demonstrates promising results and the potential for a simple and effective treatment method for excess biological sludge generated at refineries.

Psychological and Psychosocial Impact and Related Factors during the COVID-19 Pandemic among Iranian Oil Refineries Personnel: A longitudinal study.

BACKGROUND: The COVID-19 outbreak is currently a critical challenge, and proper perception of the mental health situation of individuals in the working environments has become a crucial issue. This study aimed to investigate the psychological and psychosocial impact during the COVID-19 pandemic among Iranian oil refineries personnel. METHODS: This longitudinal study was conducted in two phases from November 2019 to July 2020 among the 850 employees of three refineries in Iran. To study the mental workload, job burnout, lifestyle, occupational stress, general health, and memory quotient of personnel, the NASA-TLX questionnaire, Maslach Burnout Inventory (MBI) questionnaire, Walker's health-promoting lifestyle questionnaire, health and safety executive (HSE) job stress questionnaire, general health questionnaire, and Wechsler memory scale were used, respectively. Data were analyzed using paired sample t test, independent sample t test, and one-way ANOVA in SPSS version 25. RESULTS: The study results revealed that the mean age of studied personnel was 34.62±13.48 years. There was a meaningful correlation between the values of mental workload, job burnout, occupational stress, general health, healthy lifestyle, and memory quotient of personnel before and during the COVID-19 pandemic (P value<0.05). CONCLUSION: The COVID-19 pandemic can significantly affect the psychological and psychosocial parameters of employees in working environments. Therefore, implementing psychological interventions is absolutely necessary to promote personnel's mental health during the COVID-19 pandemic.