Response surface methodology as a tool for modeling and optimization of Bacillus subtilis spores inactivation by UV/ nano-Fe 0 process for safe water production

Applicability of bio-synthesized nanoparticles in fungal secondary metabolites products and plant extracts for eliminating antibiotic-resistant bacteria risks in non-clinical environments

The abundance of antibiotic-resistant bacteria in the prawn pond effluents can substantially impact the natural environment. The settlement ponds, which are the most common treatment method for farms wastewater, might effectively reduce the suspended solids and organic matter. However, the method is insufficient for bacterial inactivation. The current paper seeks to highlight the environmental issue associated with the distribution of antibiotic resistant bacteria (ARB) from prawn farm wastewater and their impact on the microbial complex community in the surface water which receiving these wastes. The inactivation of antibiotic-resistant bacteria in prawn wastewater is strongly recommended because the presence of antibiotic-resistant bacteria in the environment causes water pollution and public health issues. The nanoparticles are more efficient for bacterial inactivation. They are widely accepted due to their high chemical and mechanical stability, broad spectrum of radiation absorption, high catalytic activity, and high antimicrobial activity. Many studies have examined the use of fungi or plants extract to synthesis zinc oxide nanoparticles (ZnO NPs). It is evident from recent papers in the literature that green synthesized ZnO NPs from microbes and plant extracts are non-toxic and effective. ZnO NPs inactivate the bacterial cells as a function for releasing reactive oxygen species (ROS) and zinc ions. The inactivation of antibiotic-resistant bacteria tends to be more than 90% which exhibit strong antimicrobial behavior against bacterial species.

Novel antimicrobial bioplastic based on PLA-chitosan by addition of TiO2 and ZnO

PURPOSE

The purpose of this study was to develop antimicrobial bioplastics based on Poly Lactic Acid (PLA) with the addition of chitosan-ZnO, and chitosan-TiO₂ to improve antimicrobial properties.

METHODS

For the preparation of the bioplastics, PLA with chitosan-ZnO or chitosan-TiO₂ were used. The antimicrobial activity, mechanical and thermal properties, and water vapor permeability of bioplastics were evaluated.

RESULTS

PLA-chitosan-ZnO indicated a robust antimicrobial activity against bacteria such as Salmonella typhi, Bacillus subtilis, Escherichia coli, Staphylococcus aureus, yeast such as Candida albicans, and fungus Aspergillus niger. No formation of new functional groups in PLA-chitosan-ZnO composites. In comparison to other PLA-based bioplastics, this bioplastic has medium tensile strength, tensile modulus, and elongation percentages with low barrier ability to water vapor. Chitosan-ZnO itself has a greater tensile strength compared to chitosan-TiO₂. These two compounds undergo 2 stages of decomposition in a temperature range of 43 °C to 265 °C. The addition of PLA into chitosan-ZnO or chitosan TiO₂ causes the bioplastics decomposed in a single stage. It also increases the decomposition temperature of bioplastic. However, compared to chitosan-ZnO or TiO₂, the PLA-chitosan-ZnO or TiO₂ bioplastics tend to produce a fragile composite indicating by decrease in their tensile strength.

CONCLUSION

In general, the addition of chitosan-ZnO into in PLA-based bioplastic produces better antimicrobial properties compared to TiO₂.

Spatial modeling of environmental vulnerability in the biggest river in Iran using geographical information systems

BACKGROUND AND PURPOSE

The Karoon River, located in southwest Iran, has always been considered as an important water source for people in the southward areas. Khuzestan Province is one of the strategic provinces of Iran thus the development of this province is significantly affected by the water pollution of the Karoon River system. Therefore, the current study aims to assess the environmental vulnerability of the Karoon River as well as preparing a classified map of its vulnerabilities using the fuzzy logic method via the geographical information systems (GIS).

METHODS

In this study, the required data were gathered from the Water and Electricity Organization of Khuzestan Province. Afterward, the primary maps were created by converting the map of the study origin into a raster format. Then, fuzzy membership was performed by placing the digits in the range of zero and one using the fuzzy membership function. The primary maps were mixed, and finally, the risk map was prepared by applying the fuzzy overly function.

RESULTS

According to the results, a clear trend of water quality deterioration exists since water moves from upstream to downstream areas. The ecological vulnerability of the Karoon basin is mostly located at a low-level (78.05 %) rank. The vulnerable areas were ranked extremely high, high, medium, and low as 2.09, 8.09, 12.08, and 78.05, respectively.

CONCLUSIONS

Considering that 22 % of the Karoon River drainage basin in Khuzestan province is considered to have a medium to extremely high risk range, it is mandatory for the authorities to take precautions to prevent the entry of polluting sources into this precious river.

A novel stochastic wastewater quality modeling based on fuzzy techniques

Measurement and prediction of wastewater quality parameters are crucial for evaluating the risk to the receiving waters. This study presents new methods for the identification of outlier data and smoothing as an effective pre-processing technique prito to modelling. This new data processing method uses a combination of the autoregressive integrated moving average (ARIMA) model and -the adaptive neuro fuzzy inference system with fuzzy C-means clustering (FCM) (ANFIS-FCM). These new pre-processing methodsare compared to previously employed non-linear approaches for modelling of wastewater influent/effluent 5-day biochemical oxygen demand (BOD₅), chemical oxygen demand (COD) and total suspended solids (TSS). Linear modelling of each parameter, 242 linear models, were investigated, and a linear model for each parameter was selected. The results of the non-linear models led to an acceptable prediction for qualitative parameters so that the high coefficient of determination (R ² ) was observed for the influent and effluent BOD and TSS, respectively. The range of the R ² for all models was recorded as 0.8-0.87 and 0.83-0.89, respectively. By a combination of the linear and non-linear mothods a hybrid model was introduced. The proposed hybrid model for the influent BOD with the highest correlation between the observed and predicted values, and limited scattering was identified as the optimal model (R² = 0.95). The use of hybrid models to predict wastewater quality parameters improved the performance and efficiency of the models. In addition, a comparison of the hybrid model with the recently developed models in the literature indicates that the developed ARIMA-ANFIS-FCM outperformed other models.

Real diesel engine exhaust emission control: indirect non-thermal plasma and comparison to direct plasma for NOX, THC, CO, and CO2

Recently, diesel engine exhaust emission control by non-thermal plasma (NTP) technology has been shown to be promising. However, carbon and soot deposition on the inner surface of the NTP reactor for direct plasma processing decreased the efficiency of the plasma process throughout the experiments. In the present work, the feasibility of indirect plasma processing was investigated as an innovative and novel method compared to direct plasma processing. Air was directed through an NTP at an applied voltage of VP-P  = 7 kV and a flow rate of 1-4 L/min, and then, it was combined with engine exhaust gas at a flow rate of 5 L/min. In this case, the maximum conversion of NOX was 64.9% at 4 L/min. However, for direct plasma processing at 5 L/min, NO conversion was 58%, which proves that the indirect NTP process can decrease NOX concentration effectively. The maximum conversion for unburned hydrocarbon (UHC), carbon monoxide (CO) and carbon dioxide (CO2) was obtained as 2%, 4% and 0.7% at 4, 2 and 3 L/min in indirect plasma processing; While their remove rate for direct plasma processing was 16.3%, -0.5% and 13.2%, respectively.

Chlorpyrifos removal: Nb/boron-doped diamond anode coupled with solid polymer electrolyte and ultrasound irradiation

Chlorpyrifos is an organophosphorus insecticide, acaricide and miticide used worldwide for the control of soil-borne insect pests. It must be considered as a substance of growing concern, given its use, toxicity, environmental occurrence, and potential for regional to long-range atmospheric transport. Considering the incomplete removal attained by conventional water treatment processes, we investigated the efficiency of electrolytic radicals production and sonoelectrolysis on the degradation of the pesticide. The treatment has been conducted in a novel electrochemical reactor, equipped with a boron-doped diamond anode and a solid polymer electrolyte (SPE). Different current intensity and times have been tested and coupled with sonication at 40 kHz. Up to 69% of chlorpyrifos was completely removed in 10 min by electrolysis operated at 0.1 mA, while 12.5% and 5.4% was converted into the treatment intermediates 3,5,6-trichloro-2-pyridinol (TCP) and diethyl (3,5,6-trichloropyridin-2-yl) phosphate, respectively. Ultrasound irradiation did not enhance the removal efficiency, likely due to mass transport limitations, while the energy consumption increased from 8.68∙10- 6 to 9.34∙10- 4 kWh µg- 1 removed. Further research is encouraged, given the promising processing by the SPE technology of low conductivity solutions, as pharmaceuticals streams, as well as the potential for water and in-situ groundwater remediation from different emerging pollutants as phytosanitary and personal care products.

Characterization and reusability suggestions of the sludge generated from a synthetic acid mine drainage treatment using sodium ferrate (VI)

Mining activities are the main cause of generation of the voluminous sludge waste, loaded with metals precipitated from the treatment of acid mine drainage (AMD) and this is always disposed to the landfill. This study aimed at characterizing and suggesting the reusability potential of AMD sludge to reduce the environmental problem caused by its accumulation so that it could become a valuable material. The sludge was obtained after treating a synthetic AMD with a green oxidant sodium ferrate (VI) (Na₂FeO₄) that was prepared by a wet oxidation method. Chemical and physical characterization of a dried sludge generated after treatment was then performed using the Fourier Transform-Infrared and X-Ray powder Diffraction spectroscopy. Scanning Electron Microscopy-Energy Dispersive X-ray Spectroscopy also served to identify the surface morphology of the sludge. The sludge presented a high weight percentage of Fe and O and lower concentrations of other metals such as Al, Mn, Si, and Na. Nitrogen adsorption/desorption isotherms or Brunauer-Emmett-Teller (BET) was used to assess the surface area, pore volume and diameter of the sludge. The BET results showed that the surface area of the sludge obtained after treating the synthetic AMD using Na₂FeO₄ was 31.50 ± 0.03 m²/g with pore diameter and volume of 52.50 nm and 0.41 cm³/g, respectively. However, the produced sludge could serve as an adsorbent to remove pollutants from water or to synthesize different magnetic nanocomposites due to its high surface area (>natural zeolite) and high composition of Fe and O.

Preparation of Multifunctional Dopamine-Coated Zerovalent Iron/Reduced Graphene Oxide for Targeted Phototheragnosis in Breast Cancer

The present study aimed to develop a multifunctional nanoparticle platform with properties that are beneficial in imaging, targeting, and synergistic cancer phototherapy. To this end, we synthesized novel nanoparticles composed of polydopamine, nano zero-valent iron (nZVI), and reduced graphene oxide (rGO). We immobilized nZVI on the surface of GO (nZVI/GO), then further modified nZVI/GO with dopamine to form polydopamine-conjugated nZVI/rGO (nZVI/rGO@pDA). Because nZVI/rGO@pDA absorbs near infrared radiation (NIR) and binds biomolecules of cancer cells, this platform is highly efficacious in photothermal and photodynamic cancer therapy and enables specific targeting of breast cancer cells. Use of nZVI/rGO@pDA at a low concentration (10 μg/mL) resulted in irreversible damage to MCF-7 cells under NIR irradiation (808 nm) without inducing cytotoxic effects in normal cells. Furthermore, nZVI/rGO@pDA showed high sensitivity in magnetic resonance imaging (MRI), comparable to nZVI@pDA, even at low concentration. Monitoring the treatment response through evaluation of MRI signal intensity of nZVI/rGO@pDA in phototherapeutic therapy revealed that the novel material combines the advantages of nZVI, rGO, and pDA to provide specific targeting capabilities, excellent biocompatibility, and cancer phototherapeutic and tumor imaging abilities. Thus, this platform offers great potential in terms of imaging and therapeutic effects in phototherapy treatment for breast cancer.

Dopamine-Modified Zero-Valent Iron Nanoparticles for Dual-Modality Photothermal and Photodynamic Breast Cancer Therapy

Phototherapy has the advantages of minimal invasion, few side effects, and improved accuracy for cancer therapy. The application of a polydopamine (PDA)-modified nano zero-valent iron (nZVI@PDA) as a new synergistic agent in combination with photodynamic/photothermal (PD/PT) therapy to kill cancer cells is discussed here. The nZVI@PDA offered high light-to-heat conversion and ROS generation efficiency under near-infrared (NIR) irradiation (808 nm), thus leading to irreversible damage to nZVI@PDA-treated MCF-7 cells at low concentration, without inducing apoptosis in normal cells. Irradiation of nZVI@PDA using an NIR laser converted the energy of the photons to heat and ROS. Our results showed that modification of the PDA on the surface of nZVI can improve the biocompatibility of the nZVI@PDA. This work integrated the PD and PT effects into a single nanodevice to afford a highly efficient cancer treatment. Meanwhile, nZVI@PDA, which combines the advantages of PDA and nZVI, displayed excellent biocompatibility and tumoricidal ability, thus suggesting its huge potential for future clinical research in cancer therapy.

Degradation of 4-chlorophenol in aqueous solution by dielectric barrier discharge system: effect of fed gases

A dielectric barrier discharge system with a discharging zone where degradation processes happen is designed to remove 4-chlorophenol from water. The removal of 4-chlorophenol was influenced by the processing parameters such as gas flow rate, flow ratio of oxygen and argon, applied voltage and total applied power. Increasing the power or gas flow rates within a certain range enhanced the removal efficiency. 99% of 4-chlorophenol was removed in 6.5 min at reactor's efficient point which is set by adjusting the flow ratio of introduced gases and voltage. The removal percent was about 95% at 5 min of non-thermal plasma treatment with peak voltage of 10 kV and oxygen and argon flow rate of 20 SCCM and 200 SCCM respectively. Then by adjusting the flow ratios in order to find the optimum point. At this point the efficiency reached its peak due to excessive introduction oxygen gas which results in production of more oxidative agents. HPLC and GC-MS analysis have been carried out in order to investigate the by-products of degradation process. After 6.5 min of treatment at efficient point of degradation reactor, a 64% decrease in COD index has been indicated.

Performance prediction of an aerobic granular SBR using modular multilayer artificial neural networks

Aerobic granulation is a complex process that, while proven to be more effective than conventional treatment methods, has been a challenge to control and maintain stable operation. This work presents a static data-driven model to predict the key performance indicators of the aerobic granulation process. The first sub-model receives influent characteristics and granular sludge properties. These predicted parameters then become the input for the second sub-model, predicting the effluent characteristics. The model was developed with a dataset of 2600 observations and evaluated with an unseen dataset of 286 observations. The prediction R² and RMSE were >99% and <5% respectively for all predicted parameters. The results of this paper show the effectiveness of data-driven models for simulating the complex aerobic granulation process, providing a great tool to help in predicting the behaviour, and anticipating failures in aerobic granular reactors.