Predicting bilgewater emulsion stability by oil separation using image processing and machine learning.

Bilgewater is a shipboard multi-component oily wastewater, combining numerous wastewater sources. A better understanding of bilgewater emulsions is required for proper wastewater management to meet discharge regulations. In this study, we developed 360 emulsion samples based on commonly used Navy cleaner data and previous bilgewater composition studies. Oil value (OV) was obtained from image analysis of oil/creaming layer and validated by oil separation (OS) which was experimentally determined using a gravimetric method. OV (%) showed good agreement with OS (%), indicating that a simple image-based parameter can be used for emulsion stability prediction model development. An ANOVA analysis was conducted of the five variables (Cleaner, Salinity, Suspended Solids [SS], pH, and Temperature) that significantly impacted estimates of OV, finding that the Cleaner, Salinity, and SS variables were statistically significant (p < 0.05), while pH and Temperature were not. In general, most cleaners showed improved oil separation with salt additions. Novel machine learning (ML)-based predictive models of both classification and regression for bilgewater emulsion stability were then developed using OV. For classification, the random forest (RF) classifiers achieved the most accurate prediction with F1-score of 0.8224, while in regression-based models the decision tree (DT) regressor showed the highest prediction of emulsion stability with the average mean absolute error (MAE) of 0.1611. Turbidity also showed a good emulsion prediction with RF regressor (MAE of 0.0559) and RF classifier (F1-score of 0.9338). One predictor variable removal test showed that Salinity, SS, and Temperature are the most impactful variables in the developed models. This is the first study to use image processing and machine learning for the prediction of oil separation for the application of bilgewater assessment within the marine sector.

Recycling urine for bioelectrochemical hydrogen production using a MoS2 nano carbon coated electrode in a microbial electrolysis cell.

In this study, a novel molybdenum disulfide (MoS2) nano-carbon (NC) coated cathode was developed for hydrogen production in a microbial electrolysis cell (MEC), while treating simulated urine with 2-6 times dilution (conductivity <20 mS cm-1). MoS2 nanoparticles were electrodeposited on the NC coated cathodes at -100, -150 and -200 µA cm-2 and their performances were evaluated in the MEC. The chronopotentiometry (CP) tests showed the improved catalytic activity of MoS2-NC cathodes with much lower cathode overpotential than non-MoS2 coated electrodes. The MoS2-NC200 cathode, electrodeposited at -200 µA cm-2, showed the maximum hydrogen production rate of 0.152 ± 0.002 m3 H2 m-2 d-1 at 0.9V of Eap, which is comparable to the previously reported Pt electrodes. It was found that high solution conductivity over 20 mS cm-1 (>600 mg L-1 NH3-N) can adversely affect the biofilm architecture and the bacterial activity at the anode of the MEC. Exoelectrogenic bacteria for this system at the anode were identified as Tissierella (Clostridia) and Bacteroidetes taxa. Maximum ammonia-nitrogen (NH3-N) and phosphorus (PO4 3--P) removal were 68.7 and 98.6%, respectively. This study showed that the newly fabricated MoS2-NC cathode can be a cost-effective alternative to the Pt cathode for renewable bioelectrochemical hydrogen production from urine.

Nanoparticle-embedded hydrogel synthesized electrodes for electrochemical oxidation of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS).

In this study, sliver (Ag) and gold (Au) nanoparticles (NPs) were embedded on poly (acrylic acid) (PAA)/poly (allylamine) hydrochloride (PAH) hydrogel fibers for improved electrochemical oxidation (EO) of perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) removal. The NPs-loaded PAA/PAHs shows the better charge transport compared to the ceramic nanofiber membranes (CNM) electrodes. At 10 mA cm-2 of current density, the Ag-PAA/PAH electrodes showed a faster removal of PFAS compared to the Ag-CNM electrode probably due to large surface area-volume ratio and high porosity from the hydrogel. Among NPs-loaded PAA/PAH electrodes, the Ag/Au-PAA/PAH electrodes showed the highest removal of PFOA (72%) and PFOS (91%) in 2 h with the maximum removal rate of PFOA (0.0046 min-1) and PFOS (0.0093 min-1). The rapid PFOS removal is possibly due to the high activity of electron transfer with a higher redox potential of SO4•- than •OH. The highly stable F- generation was obtained from each electrode during reproducibility (n = 3). The net energy consumption from Ag/Au-PAA/PAH electrode was 164.9 kWh m-3 for 72% PFOA removal and 90 kWh m-3 for 91% PFOS removal, respectively. The developed Au-PAA/PAH electrodes were applied to lake water samples and showed acceptable PFOS removal (65%) with relative standard deviations (RSD) of 10.2% (n = 3) at 10 mA cm-2 of current density. Overall, the NP-embedded hydrogel nanofibers were proven to be a promising sustainable catalyst for the electrochemical PFAS oxidation in water.

A strategy for power generation from bilgewater using a photosynthetic microalgal fuel cell (MAFC).

Microbial fuel cells (MFCs) have recently been applied to generate electricity from oily wastewater. Although MFCs that utilize microalgae to provide a self-supporting oxygen (O2) supply at the cathode have been well discussed, those with microalgae at the anode as an active biomass for treating wastewater and producing electrons are still poorly studied and understood. Here, we demonstrated a bilgewater treatment using single- and double-chamber microalgal fuel cells (SMAFC and DMAFC) capable of generating energy with a novel microalgal strain (Chlorella sorokiniana) that was initially isolated from oily wastewater. Compared to previous MFC studies using green algae, relatively high voltage output (151.3-160.1 mV, 71.3-83.4 mV m-2 of power density) was observed in the SMAFC under O2 controlled systems (i.e., acetate addition or light/dark cycle). It was assumed that, under the O2 depletion, alternative electron acceptors such as bicarbonate may be utilized for power generation. A DMAFC showed better power density (up to 23.9%) compared to the SMAFC due to the separated cathode chamber which fully utilizes O2 as an electron acceptor. Both SMAFC and DMAFC removed 67.2-77.4% of soluble chemical oxygen demands (SCOD) from the synthetic bilgewater. This study demonstrates that the application of algae-based MFCs is a feasible strategy to treat oil-in-water emulsion while generating electricity.

Recent Developments of PFAS-Detecting Sensors and Future Direction: A Review.

Per- and poly-fluoroalkyl substances (PFASs) have recently been labeled as toxic constituents that exist in many aqueous environments. However, traditional methods used to determine the level of PFASs are often not appropriate for continuous environmental monitoring and management. Based on the current state of research, PFAS-detecting sensors have surfaced as a promising method of determination. These sensors are an innovative solution with characteristics that allow for in situ, low-cost, and easy-to-use capabilities. This paper presents a comprehensive review of the recent developments in PFAS-detecting sensors, and why the literature on determination methods has shifted in this direction compared to the traditional methods used. PFAS-detecting sensors discussed herein are primarily categorized in terms of the detection mechanism used. The topics covered also include the current limitations, as well as insight on the future direction of PFAS analyses. This paper is expected to be useful for the smart sensing technology development of PFAS detection methods and the associated environmental management best practices in smart cities of the future.

A Novel Bismuth-Chitosan Nanocomposite Sensor for Simultaneous Detection of Pb(II), Cd(II) and Zn(II) in Wastewater.

A novel bismuth (Bi)-biopolymer (chitosan) nanocomposite screen-printed carbon electrode was developed using a Bi and chitosan co-electrodepositing technique for detecting multiple heavy metal ions. The developed sensor was fabricated with environmentally benign materials and processes. In real wastewater, heavy metal detection was evaluated by the developed sensor using square wave anodic stripping voltammetry (SWASV). The nanocomposite sensor showed the detection limit of 0.1 ppb Zn2+, 0.1 ppb Cd2+ and 0.2 ppb Pb2+ in stock solutions. The improved sensitivity of the Bi-chitosan nanocomposite sensor over previously reported Bi nanocomposite sensors was attributed to the role of chitosan. When used for real wastewater samples collected from a mining site and soil leachate, similar detection limit values with 0.4 ppb Cd2+ and 0.3 ppb Pb2+ were obtained with relative standard deviations (RSD) ranging from 1.3% to 5.6% (n = 8). Temperature changes (4 and 23 °C) showed no significant impact on sensor performance. Although Zn2+ in stock solutions was well measured by the sensor, the interference observed while detecting Zn2+ in the presence of Cu2+ was possibly due to the presence of Cu-Zn intermetallic species in mining wastewater. Overall, the developed sensor has the capability of monitoring multiple heavy metals in contaminated water samples without the need for complicated sample preparation or transportation of samples to a laboratory.

Improving Electrochemical Pb2+ Detection Using a Vertically Aligned 2D MoS2 Nanofilm.

Recent advancements in MoS2 nanofilms have aided in the development for important water-related environmental applications. However, a MoS2 nanofilm-coated sensor has yet to have been applied for heavy metal detection in water-related environmental samples. In this study, a novel vertically aligned two-dimensional (2D) MoS2 (edge exposed) nanofilm was applied for in situ lead ion (Pb2+) detection. The developed sensor showed an excellent linear relationship toward Pb2+ between 0 and 20 ppb at -0.45 V vs Ag/AgCl using square wave anodic stripping voltammetry (SWASV) with the improved limit of detection (LOD) of 0.3 ppb in a tap water environment. The vertically aligned 2D MoS2 sensor exhibited improved detection sensitivity (2.8 folds greater than a previous metallic [Bi] composite electrode) with lower relative standard deviation for repetitive measurements (n = 11), indicating enhanced reproducibility for Pb2+ detection. The vertically aligned 2D MoS2 layers exhibited 2.6 times higher sensitivity than horizontally aligned 2D MoS2 (basal plane exposed). Density functional theory calculations demonstrated that adsorption energy of Pb on the MoS2 side edge was much higher (4.11 eV) than those on the basal plane (0.36 and 0.07 eV). In addition, the band gap center of vertical MoS2 was found to be higher than the Pb2+ → Pb reduction potential level and capable of reducing Pb2+. Overall, the newly developed vertically aligned 2D MoS2 sensor showed excellent performance for detecting Pb2+ in a real drinking water environment with good reliability.