Using colloidal AFM probe technique and XDLVO theory to predict the transport of nanoplastics in porous media

A review of flow field characteristics in submerged hollow fiber membrane bioreactor: Micro-interface, module and reactor

As an important part of the membrane field, hollow fiber membranes (HFM) have been widely concerned by scholars. HFM fouling in the industrial application results in a reduction in its lifespan and an increase in cost. In recent years, various explorations on the HFM fouling control strategies have been carried out. In the current work, we critically review the influence of flow field characteristics in HFM-based bioreactor on membrane fouling control. The flow field characteristics mainly refer to the spatial and temporal variation of the related physical parameters. In the HFM field, the physical parameter mainly refers to the variation characteristics of the shear force, flow velocity and turbulence caused by hydraulics. The factors affecting the flow field characteristics will be discussed from three levels: the micro-flow field near the interface of membrane (micro-interface), the flow field around the membrane module and the reactor design related to flow field, which involves surface morphology, crossflow, aeration, fiber packing density, membrane vibration, structural design and other related parameters. The study of flow field characteristics and influencing factors in the HFM separation process will help to improve the performance of HFM in full-scale water treatment plants.

Adsorption interactions between typical microplastics and enrofloxacin: Relevant contributions to the mechanism

Microplastics (MPs) are increasingly contaminating the environment and they can combine with antibiotics as carriers to form complex contaminants. In this study, we systematically investigated the interactions between the antibiotic enrofloxacin (ENR) and MPs comprising polyethylene (PE), polyvinyl chloride (PVC), and polystyrene (PS). Characterization was performed by using conventional techniques and the mechanisms involved in interactions were initially explored based on adsorption kinetics, isotherms, and resolution experiments, and the adsorption capacities of the MPs were determined. In addition, the extended Derjaguin-Landau-Verwey-Overbeek theory was used to investigate the interaction mechanisms. The results showed that the interactions were weaker in strong acidic and alkaline environments, and the interactions were also inhibited at higher salt ion concentrations. The saturation adsorption amounts of ENR on PVC, PE, and PS were 74.63 μg/g, 103.09 μg/g, and 142.86 μg/g, respectively. The interactions between MPs and ENR were dominated by hydrophobic interactions, followed by van der Waals forces and acid-base forces. This study provides new insights into the adsorption behavior of ENR by MPs.

The intelligent prediction of membrane fouling during membrane filtration by mathematical models and artificial intelligence models

Recently, membrane separation technology has been widely utilized in filtration process intensification due to its efficient performance and unique advantages, but membrane fouling limits its development and application. Therefore, the research on membrane fouling prediction and control technology is crucial to effectively reduce membrane fouling and improve separation performance. This review first introduces the main factors (operating condition, material characteristics, and membrane structure properties) and the corresponding principles that affect membrane fouling. In addition, mathematical models (Hermia model and Tandem resistance model), artificial intelligence (AI) models (Artificial neural networks model and fuzzy control model), and AI optimization methods (genetic algorithm and particle swarm algorithm), which are widely used for the prediction of membrane fouling, are summarized and analyzed for comparison. The AI models are usually significantly better than the mathematical models in terms of prediction accuracy and applicability of membrane fouling and can monitor membrane fouling in real-time by working in concert with image processing technology, which is crucial for membrane fouling prediction and mechanism studies. Meanwhile, AI models for membrane fouling prediction in the separation process have shown good potential and are expected to be further applied in large-scale industrial applications for separation and filtration process intensification. This review will help researchers understand the challenges and future research directions in membrane fouling prediction, which is expected to provide an effective method to reduce or even solve the bottleneck problem of membrane fouling, and to promote the further application of AI modeling in environmental and food fields.

Mechanism of transport and toxicity response of Chlorella sorokiniana to polystyrene nanoplastics

The toxicity of nanoparticles to freshwater microalgae is of significant importance in maintaining the overall stability of aquatic ecosystems. However, the transport mechanism and toxicity response of microalgae towards nanoplastics (NPs) remain to be further investigated. In this study, we examined the toxicity and internalization mechanisms of polystyrene nanoplastics (PS-NPs) in the microalga Chlorella sorokiniana. The results revealed that the PS-NPs inhibited algal cells' growth and disrupted cell integrity upon contact, leading to cell shrinkage or rupture. Moreover, amino-modified PS-NPs (Nano-PS-NH2) exhibited greater toxicity to C. sorokiniana than carboxyl-modified PS-NPs (Nano-PS-COOH). Furthermore, significant inhibition of PS-NPs internalization was observed when four different endocytosis-related inhibitors were used, indicating that internalized PS-NPs can enter algal cells through endocytic pathways. More importantly, C. sorokiniana exposed to Nano-PS-NH2 responded to the reduction in carbon sources and energy resulting from the suppression of photosynthesis by regulating the metabolism of carbohydrates. These findings elucidate the effects of PS-NPs on C. sorokiniana, including their impact on cell morphology and metabolism, while shedding light on the internalization mechanisms of NPs by C. sorokiniana which deepen our understanding of the toxicity of nanoplastics on algae and provide important theoretical support for solving such aquatic ecological environment problems.

A new insight into the low membrane fouling tendency of liquid-liquid hollow fiber membrane contactor capturing ammonia from human urine

To unravel the low membrane fouling tendency and underlying membrane fouling mechanism of liquid-liquid hollow fiber membrane contactor (LL-HFMC) capturing ammonia from human urine, the ammonia flux decline trend, membrane fouling propensity, foulant-membrane thermodynamic interaction energy and microscale force analysis at different feed urine pH were comprehensively investigated. The 21-d continuous experiments showed that the ammonia flux decline trend and membrane fouling propensity significantly strengthened with the decrease of feed urine pH. The calculated foulant-membrane thermodynamic interaction energy decreased with the decreasing feed urine pH and agreed with the ammonia flux decline trend and membrane fouling propensity. The microscale force analysis showed that the absence of hydrodynamic water permeate drag force resulted in the foulant located at long distance from the membrane were difficult to approach the membrane surface, thus considerably alleviating membrane fouling. Additionally, the vital thermodynamic attractive force near the membrane surface increased with the decrease of feed urine pH, which made the membrane fouling further relieved at high pH condition. Therefore, the absence of water permeate drag force and operating at high pH condition minimized the membrane fouling during the LL-HFMC ammonia capture process. The obtained results provide a new insight into the low membrane tendency mechanism of LL-HFMC.