Membrane modification is one of the most feasible and effective solutions to membrane fouling problem which tenaciously hampers the further augmentation of membrane separation technology. Blending modification with nanoparticles (NPs), owing to the convenience of being incorporated in established membrane production lines, possesses an advantageous viability in practical applications. However, the existing blending strategy suffers from a low utilization efficiency due to NP encasement by membrane matrix. The current study proposed an improved blending modification approach with amphiphilic NPs (aNPs), which were prepared through silanization using 3-(Trimethoxysilyl)propyl methacrylate (TMSPMA) as coupling agents and ZnO or SiO2 as pristine NPs (pNPs), respectively. The Fourier transform infrared and X-ray photoelectron spectroscopy analyses revealed the presence of appropriate organic components in both the ZnO and SiO2 aNPs, which verified the success of the silanization process. As compared with the pristine and conventional pNP-blended membranes, both the ZnO aNP-blended and SiO2 aNP-blended membranes with proper silanization (100% and 200%w/w) achieved a significantly increased blending efficiency with more NPs scattering on the internal and external membrane surfaces under scanning electron microscope observation. This improvement contributed to the increase of membrane hydrophilicity. Nevertheless, an extra dosage of the TMSPMA led to an encasement of NPs, thereby adversely affecting the properties of the resultant membranes. On the basis of all the tests, 100% (w/w) was selected as the optimum TMSPMA dosage for blending modification for both the ZnO and SiO2 types.
● A new adsorption-membrane separation strategy is used for phosphate removal.● PVC/Zr-BT shows a selective adsorption ability to low-concentration phosphate.● Low concentration of P below 0.05 mg/L was achieved in actual wastewater treatment.● Algal biomass production served as a demonstration of phosphorus recycling. Enhanced phosphorus treatment and recovery has been continuously pursued due to the stringent wastewater discharge regulations and a phosphate supply shortage. Here, a new adsorption-membrane separation strategy was developed for rational reutilization of phosphate from sea cucumber aquaculture wastewater using a Zr-modified-bentonite filled polyvinyl chloride membrane. The as-obtained polyvinyl chloride/Zr-modified-bentonite membrane was highly permeability (940 L/(m2·h)), 1–2 times higher than those reported in other studies, and its adsorption capacity was high (20.6 mg/g) when the phosphate concentration in water was low (5 mg/L). It remained stable under various conditions, such as different pH, initial phosphate concentrations, and the presence of different ions after 24 h of adsorption in a cross-flow filtration system. The total phosphorus and phosphate removal rate reached 91.5% and 95.9%, respectively, after the membrane was used to treat sea cucumber aquaculture wastewater for 24 h and no other water quality parameters had been changed. After the purification process, the utilization of the membrane as a new source of phosphorus in the phosphorus-free f/2 medium experiments indicated the high cultivability of economic microalgae Phaeodactylum tricornutum FACHB-863 and 1.2 times more chlorophyll a was present than in f/2 medium. The biomass and lipid content of the microalgae in the two different media were similar. The innovative polyvinyl chloride/Zr-modified-bentonite membrane used for phosphorus removal and recovery is an important instrument to establish the groundwork for both the treatment of low concentration phosphate from wastewater as well as the reuse of enriched phosphorus in required fields. 相似文献
• A spectral machine learning approach is proposed for predicting mixed antibiotic.• Pretreatment is far simpler than traditional detection methods.• Performance of the model is compared in different influencing factors.• Spectral machine learning is promising in the detection of complex substances. Antibiotics are widely used in medicine and animal husbandry. However, due to the resistance of antibiotics to degradation, large amounts of antibiotics enter the environment, posing a potential risk to the ecosystem and public health. Therefore, the detection of antibiotics in the environment is necessary. Nevertheless, conventional detection methods usually involve complex pretreatment techniques and expensive instrumentation, which impose considerable time and economic costs. In this paper, we proposed a method for the fast detection of mixed antibiotics based on simplified pretreatment using spectral machine learning. With the help of a modified spectrometer, a large number of characteristic images were generated to map antibiotic information. The relationship between characteristic images and antibiotic concentrations was established by machine learning model. The coefficient of determination and root mean squared error were used to evaluate the prediction performance of the machine learning model. The results show that a well-trained machine learning model can accurately predict multiple antibiotic concentrations simultaneously with almost no pretreatment. The results from this study have some referential value for promoting the development of environmental detection technologies and digital environmental management strategies. 相似文献
● A PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed. ● The property of flax fiber could be switched from hydrophobicity to hydrophilicity. ● The mechanism of the acquired UV-induced switchable wettability was discussed. ● The developed flax fiber was successfully used for multipurpose oil-water separation. The large number of oily wastewater discharges and oil spills are bringing about severe threats to environment and human health. Corresponding to this challenge, a functional PAA-ZnO-HDTMS flax fiber with UV-induced switchable wettability was developed for efficient oil-water separation in this study. The developed flax fiber was obtained through PAA grafted polymerization and then ZnO-HDTMS nanocomposite immobilization. The as-prepared PAA-ZnO-HDTMS flax fiber was hydrophobic initially and could be switched to hydrophilic through UV irradiation. Its hydrophobicity could be easily recovered through being stored in dark environment for several days. To optimize the performance of the PAA-ZnO-HDTMS flax fiber, the effects of ZnO and HDTMS concentrations on its switchable wettability were investigated. The optimized PAA-ZnO-HDTMS flax fiber had a large water contact angle (~130°) in air and an extremely small oil contact angle (~0°) underwater initially. After UV treatment, the water contact angle was decreased to 30°, while the underwater oil contact angle was increased to more than 150°. Based on this UV-induced switchable wettability, the developed PAA-ZnO-HDTMS flax fiber was applied to remove oil from immiscible oil-water mixtures and oil-in-water emulsion with great reusability for multiple cycles. Thus, the developed flax fiber could be further fabricated into oil barrier or oil sorbent for oil-water separation, which could be an environmentally-friendly alternative in oil spill response and oily wastewater treatment. 相似文献
The distribution of heavy metals (Pb, Zn, Cd and As) in sediments of the Pearl River Estuary was investigated. The spatial distribution of heavy metals displayed a decreasing pattern from the turbidity maxima to both upstream and downstream of the estuary, which suggested that suspended sediments played an important role in the trace metal distribution in the Pearl River Estuary. In addition, metal concentrations were higher in the west part of the estuary which received most of the pollutants from the Pearl River. In the sediment cores, fluxes of heavy metals were consistent with a predominant anthropogenic input in the period 1970-1990. From the mid-1990s to the 2000s, there was a significant decline in heavy metal pollution. The observed decline has shown the result of pollution control in the Pearl River Delta. However, it is noteworthy that the metal concentrations in the most recent sediment still remained considerably high. Taken together, the enrichment of heavy metals in sediments was largely controlled by anthropogenic pollution. 相似文献
Experimental data are presented to test and validate a kinetic model for the oxidation of 2-chlorophenol wastewater by photo-assisted Fenton process. The data showed that this process had produced good effects under acidic conductions. Up to 90% 2-chlorophenol was removed after 90-minute reaction time with H2O2 of 25% CODCr. in, while in UV/H2O2 system ordy 16.8% 2-chlorophenol was removed after one hour treatment. The optimal pH in this reaction occurred between pH 3.0 and pH 4.0. The reaction kinetics for photo-assisted Fenton process experimented in this research was investigated. Kinetic models were proposed for the treatment of 2-chlorophenol wastewater. The reaction was found to follow the 2nd order. The equations of reaction kinetics are as follows:-d[RH]/dt=KRH[RH][H2O2]0exp(-KH2o2t);-d[CODCr]/dt=KCODCr[CODCr][H2O2]0exp(-K′t).The prediction of the models was found to be in a good agreement with experimental results, thus confimfing the proposed reaction mechanism. 相似文献
