Characteristics of dissolved organic matter in point-source wastewaters at a petrochemical plant: Molecular constituents and contributions to the influent of wastewater treatment plant.

Dissolved organic matter (DOM) in point-source petrochemical wastewaters (PCWs) from different operating units is closely linked to the efficiency of wastewater treatment plant (WWTP). However, systematic studies on DOM characters of point-source PCWs and their influences on WWTP influents were seldom conducted. In this study, DOM in three low-salinity point-source PCWs and four high-salinity point-source PCWs at a typical petrochemical plant were comprehensively characterized at a molecular level. Orbitrap mass spectrometry results indicated that point-source PCWs had diverse DOM constituents tightly related to the corresponding petrochemical processes. Phenols in oily wastewaters (OW), phenols and N-containing compounds in coal partial oxidation wastewater (POXW), and naphthenic acids (NAs) and aromatic acids in crude oil electric desalting unit wastewater (EDW) were characteristic DOM constituents for low-salinity point-source PCWs. While S-containing compounds (mercaptans, thiophenes) and NAs in spent caustic liquors (SCL), alcohols and esters in butanol-octanol plant wastewater (BOW), high molecular weight aromatic ketones in phenol-acetone plant wastewater (PAW), and oxygenated NAs as well as short chain N-containing compounds in concentrate from reverse osmosis unit (ROC) were characteristic DOM constituents for high-salinity point-source PCWs. Spearman correlation analysis indicated that though with relative low pollutant contents (OW) and discharge volume (EDW), N/O/S-containing compounds of OW and EDW greatly contributed to the polar DOM constituents of low-salinity influent in WWTP (R > 0.5, P < 0.001). While N-containing compounds of ROC mainly contributed to the polar DOM of high-salinity influent (R > 0.5, P < 0.001). Though N-/S-containing species in PAW had low contents, they also posed obvious impacts on DOM constituents of high-salinity influent. Interestingly, some O-/S-containing species were newly formed during the confluent process of high-salinity point-source PCWs. The results strengthened the combined contributions of pollutants contents, discharge emission and DOM constituents of point-source PCWs to the water matrix of WWTP influents, which would provide reference for the management of PCW streams.

Role of pretreatment type and microbial mechanisms on enhancing volatile fatty acids production during anaerobic fermentation of refinery waste activated sludge.

This study compared the effects of alkaline, thermal, thermal-peroxymonosulfate (PMS), and alkyl polyglucose (APG) pretreatments on volatile fatty acids (VFAs) production from refinery waste activated sludge (RWAS), including VFAs yield, composition, organics components, microbial communities, and the potential improvement of mechanisms. All pretreatments effectively enhanced the bioconversion of RWAS and consequently promoted the hydrolysis process, which inhibited the methanogenesis process. However, the release of lignin/carboxyl-rich alicyclic molecules (CRAM)-like compounds and tannin substances in Thermal-PMS and APG groups significantly influenced the acidogenesis and acetogenesis processes. Among all pretreatments, alkaline pretreatment showed the highest VFAs yield of 95.06 mg/g volatile solids (VS) and VS removal of 17%. This result could be associated with the enrichment of functional hydrolytic-acidification bacteria, such as Planococcus and Soehngenia, and increased metabolism of amino acids, carbohydrates, and nucleotides. By considering an economical and efficient perspective, this study recommended the alkaline pretreatment for the anaerobic fermentation of RWAS.

Transformation of dissolved organic matter at a full-scale petrochemical wastewater treatment plant.

Transformation of dissolved organic matter (DOM) in petrochemical wastewater (PCW) treatment has rarely been studied. In this work, low- and high-salinity PCW were collected from a treatment plant and the transformations of DOM at molecular level along the treatment processes of both PCW were comparatively investigated. By using Orbitrap MS, the polar DOM constituents were categorized into five molecular classes namely saturated compounds, aliphatics, highly unsaturated and phenolic compounds (Huph), polyphenols and condensed polycyclic aromatics (Cpla). Aliphatics (58.62%) with low molecular weight (150-250 Da) and O/C (0-0.2) were dominant in raw low-salinity PCW; while Huph (65.03%) with O/C at 0.2-0.8 were rich in raw high-salinity PCW. After full-scale treatment, differentiated DOM constituents in both raw PCWs were transformed into aliphatics and Huph with O/C at 0.3-0.5. Anoxic/Oxic treatment of low-salinity system (L-A/O) removed a high fraction of aliphatics (53.05%); while Huph with low O/C (0.1-0.3) (65.68%) in the effluent of L-A/O were further mineralized by ozonation of low-salinity system (L-ozonation). In comparison, anoxic/oxic treatment of high-salinity system (H-A/O) mainly removed unsaturated Huph (34.10%) and aliphatics (30.86%). This resulted in a decrease of dissolved organic carbon as indicated via Spearman correlation. Different from L-ozonation, ozonation of high-salinity system (H-ozonation) degraded aliphatics (26.09%) and Huph (41.85%) with a relatively high O/C (0.2-1.2). After L-A/O and L-ozonation treatments, remaining saturated compounds that were originated from raw low-salinity PCW, were removed by subsequent biological aerated filter. Comparatively, after H-A/O and H-ozonation treatments, residual Huph and aliphatics which were mainly bio-derivates and ozonated intermediates, were further removed by air flotation filter. Hence, DOM transformation of different PCWs along similar treatments varied significantly. This study provides in-depth insights on DOM transformation along a full-scale PCW treatment process.

A Synthetic Minority Oversampling Technique Based on Gaussian Mixture Model Filtering for Imbalanced Data Classification.

Data imbalance is a common phenomenon in machine learning. In the imbalanced data classification, minority samples are far less than majority samples, which makes it difficult for minority to be effectively learned by classifiers A synthetic minority oversampling technique (SMOTE) improves the sensitivity of classifiers to minority by synthesizing minority samples without repetition. However, the process of synthesizing new samples in the SMOTE algorithm may lead to problems such as "noisy samples" and "boundary samples." Based on the above description, we propose a synthetic minority oversampling technique based on Gaussian mixture model filtering (GMF-SMOTE). GMF-SMOTE uses the expected maximum algorithm based on the Gaussian mixture model to group the imbalanced data. Then, the expected maximum filtering algorithm is used to filter out the "noisy samples" and "boundary samples" in the subclasses after grouping. Finally, to synthesize majority and minority samples, we design two dynamic oversampling ratios. Experimental results show that the GMF-SMOTE performs better than the traditional oversampling algorithms on 20 UCI datasets. The population averages of sensitivity and specificity indexes of random forest (RF) on the UCI datasets synthesized by GMF-SMOTE are 97.49% and 97.02%, respectively. In addition, we also record the G-mean and MCC indexes of the RF, which are 97.32% and 94.80%, respectively, significantly better than the traditional oversampling algorithms. More importantly, the two statistical tests show that GMF-SMOTE is significantly better than the traditional oversampling algorithms.

Influences of coagulation pretreatment on the characteristics of crude oil electric desalting wastewaters.

Highly polluted crude oil electric desalting wastewaters (EDWs) severely affect the efficiency of refinery wastewater treatment plants (WWTPs). Coagulation is an efficient pretreatment to reduce the impacts of EDWs. In the present study, the influences of coagulation pretreatment on the characteristics of EDWs of three typical Chinese crude oils, Liaohe heavy oil (LHO), Karamay heavy oil (KHO) and Daqing light oil (DLO), were investigated. The stability of three raw EDWs was broken and the contents of organic pollutants were significantly reduced by aluminum sulfate coagulation. More soluble COD and polar oils were removed from LHO-EDW (1241 and 98 mg L-1) and KHO-EDW (779 and 57 mg L-1) compared to DLO-EDW (417 and 11 mg L-1). Coagulation significantly changed the compositions of the organic pollutants of two heavy oil EDWs; however, slightly influenced DLO-EDW, particularly the polar organic pollutants. Most types of aromatic compounds, aliphatic acids and Ox polar compounds were removed from two heavy oil EDWs, but mainly alkanes were removed from DLO-EDW. As such, the differences in the types of dominant polar compounds became insignificant among treated heavy oil and light oil EDWs. Coagulation notably decreased the acute biotoxicity and improved the biodegradability of all treated EDWs. The residual organic nitrogen compounds in treated KHO-EDW contributed to a higher residual biotoxicity compared to treated LHO-EDW. The results demonstrate that coagulation can effectively improve the qualities of heavy oil EDWs by lowering the contents of organic pollutants and removing recalcitrant compounds, thus guaranteeing the efficiency of refinery WWTPs.

A hybrid sampling algorithm combining M-SMOTE and ENN based on Random forest for medical imbalanced data.

The problem of imbalanced data classification often exists in medical diagnosis. Traditional classification algorithms usually assume that the number of samples in each class is similar and their misclassification cost during training is equal. However, the misclassification cost of patient samples is higher than that of healthy person samples. Therefore, how to increase the identification of patients without affecting the classification of healthy individuals is an urgent problem. In order to solve the problem of imbalanced data classification in medical diagnosis, we propose a hybrid sampling algorithm called RFMSE, which combines the Misclassification-oriented Synthetic minority over-sampling technique (M-SMOTE) and Edited nearset neighbor (ENN) based on Random forest (RF). The algorithm is mainly composed of three parts. First, M-SMOTE is used to increase the number of samples in the minority class, while the over-sampling rate of M-SMOTE is the misclassification rate of RF. Then, ENN is used to remove the noise ones from the majority samples. Finally, RF is used to perform classification prediction for the samples after hybrid sampling, and the stopping criterion for iterations is determined according to the changes of the classification index (i.e. Matthews Correlation Coefficient (MCC)). When the value of MCC continuously drops, the process of iterations will be stopped. Extensive experiments conducted on ten UCI datasets demonstrate that RFMSE can effectively solve the problem of imbalanced data classification. Compared with traditional algorithms, our method can improve F-value and MCC more effectively.

Catalytic Ozonation of Recalcitrant Organic Chemicals in Water Using Vanadium Oxides Loaded ZSM-5 Zeolites.

The discharge of wastewater having recalcitrant chemical compositions can have significant and adverse environmental effects. The present study investigates the application of a catalytic ozonation treatment for the removal of recalcitrant organic chemicals (ROCs) from the water. Novel catalytic materials using vanadium (V) oxides deposited onto the surface of NaZSM-5 zeolites (V/ZSM) were found to be highly efficient for this purpose. The highly-dispersed V oxides (V4+ and V5+) and Si-OH-Al framework structures were determined to promote the surface reaction and generation of hydroxyl radicals. The constructed V1/ZSM450 (0.7 wt% of V loading and 450°C of calcination) exhibited the highest activity among the developed catalyst compositions. The V1/ZSM450-COP increased the mineralization rate of nitrobenzene and benzoic acid by 50 and 41% in comparison to single ozonation. This study demonstrates the enhanced potential of V/ZSM catalysts used with catalytic ozonation process (COP) for the treatment of chemical wastewaters.

Activated petroleum waste sludge biochar for efficient catalytic ozonation of refinery wastewater.

Large quantities of hazardous activated petroleum waste sludge and wastewaters are generated from petroleum refining. The present disposal of the sludge via incineration or landfill may cause secondary pollution as well as additional costs. Treatment of petroleum refinery wastewater (PRW) by catalytic ozonation process (COP) remains a great challenge of developing low-cost and high-efficiency catalysts. Use of waste sludge derived biochar as catalysts in COP of PRW not only solves the solid wastes and wastewaters problems but also improves profitability. The elements of carbon (C), silicon (Si) and metals originally found in activated petroleum waste sludge contribute to the formation of active sites during pyrolysis. The biochar contains functional C groups, SiO structures, and metallic oxides that promote oxidation through the formation of hydroxyl radicals (OHs) mineralizing petroleum contaminants. Catalytic ozonation of PRW using this sludge biochar (SBC) doubles the total organic carbon removal (53.5%) relative to single ozonation (26.9%). Oxygen (Ox)-, nitrogen (NOx)- and sulfur (OxS)-containing contaminants were decreased by 33.4% (989 vs 659), 58.2% (912 vs 384) and 12.5% (384 vs 336). The present study shows the potential of a "wastes-treat-wastes" process for wastewater treatment.

In Situ Electrodeposition of Cobalt Sulfide Nanosheet Arrays on Carbon Cloth as a Highly Efficient Bifunctional Electrocatalyst for Oxygen Evolution and Reduction Reactions.

As one of the advanced cobalt-based materials, cobalt sulfides with novel architecture have attracted huge interest due to the low cost, easy availability, and promising bifunctional activity for both the oxygen evolution reaction (OER) and oxygen reduction reaction (ORR), which is essential for next-generation energy storage devices. Herein, we demonstrated a facile and clean electrochemical technique to directly synthesize CoS nanosheets with high purity onto the surface of carbon cloth, and a quick thermal treatment was performed to further improve the catalytic performance (CoS-A). This novel electrochemical technique avoids the use of the binder, surfactant, and other organic additives, which may cause poor electric conductivity as well as undesirable surface wettability, exhibiting great potential of the large-scale applications. The obtained CoS-A exhibits a superior electrocatalytic performance for the OER and ORR, with a high ORR current density (-1.51 mA cm-2 at 0.2 V), considerable OER current density (148 mA cm-2 at 1.9 V), and excellent durability in continuous measurement for over 12 h. The approach offers a powerful yet simple method to control the phase, composition, and morphology of a highly active CoS catalyst, which provides a new idea for the design of high-performance catalysts.

Electrochemical Oxidation of Chlorine-Doped Co(OH)2 Nanosheet Arrays on Carbon Cloth as a Bifunctional Oxygen Electrode.

The primary challenge of developing clean energy conversion/storage systems is to exploit an efficient bifunctional electrocatalyst both for oxygen reduction reaction (ORR) and oxygen evolution reaction (OER) with low cost and good durability. Here, we synthesized chlorine-doped Co(OH)2 in situ grown on carbon cloth (Cl-doped Co(OH)2) as an integrated electrode by a facial electrodeposition method. The anodic potential was then applied to the Cl-doped Co(OH)2 in an alkaline solution to remove chlorine atoms (electro-oxidation (EO)/Cl-doped Co(OH)2), which can further enhance the electrocatalytic activity without any thermal treatment. EO/Cl-doped Co(OH)2 exhibits a better performance both for ORR and OER in terms of activity and durability because of the formation of a defective structure with a larger electrochemically active surface area after the electrochemical oxidation. This approach provides a new idea for introducing defects and developing active electrocatalyst.