An Experimental Study on the Simultaneous Phenol and Chromium Removal From Water Using Titanium Dioxide Photocatalyst

Nasiri, Elaheh Faghih; Kebria, Daryoush Yousefi; Qaderi, Farhad

doi:10.28991/cej-0309117

Cited by 41 publications

(6 citation statements)

References 17 publications

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“…Epidemiological studies show that high-level exposure to NO 2 in the air as a pollutant lead to increasing approximately 5-7% of the lung cancers among people (ex-smokers and non-smokers) 9 . Moreover, these studies reveal that a positive correlation between air pollutants such as NO 2 and adverse effects on human health such as changes in the kidney, liver, heart, and decrease resistance immunity to infectious diseases [10][11][12] . World Organization Health (WHO) reported that NO 2 associated with adverse effects such as increases in respiratory symptoms, asthma prevalence and incidence, cancer incidence, adverse birth outcomes and mortality 13 .…”

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confidence: 99%

Artificial intelligence accuracy assessment in NO2 concentration forecasting of metropolises air

Shams

Jahani²,

Kalantary

et al. 2021

Sci Rep

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Air quality has been the main concern worldwide and Nitrous oxide (NO2) is one of the pollutants that have a significant effect on human health and environment. This study was conducted to compare the regression analysis and neural network model for predicting NO2 pollutants in the air of Tehran metropolis. Data has been collected during a year in the urban area of Tehran and was analyzed using multi-linear regression (MLR) and multilayer perceptron (MLP) neural networks. Meteorological parameters, urban traffic data, urban green space information, and time parameters are applied as input to forecast the daily concentration of NO2 in the air. The results demonstrate that artificial neural network modeling (R2 = 0.89, RMSE = 0.32) results in more accurate predictions than MLR analysis (R2 = 0.81, RMSE = 13.151). According to the result of sensitivity analysis of the model, the value of park area, the average of green space area and one-day time delay are the crucial parameters influencing NO2 concentration of air. Artificial neural network models could be a powerful, effective and suitable tool for analysis and modeling complex and non-linear relation of environmental variables such as ability in forecasting air pollution. Green spaces establishment has a significant role in NO2 reduction even more than traffic volume.

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confidence: 99%

Artificial intelligence accuracy assessment in NO2 concentration forecasting of metropolises air

Shams

Jahani²,

Kalantary

et al. 2021

Sci Rep

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“…Kontoudakis et al [52] removed copper from white wine by membrane filtration and recorded a significant reduction. Amongst the various nanoparticles, TiO 2 demonstrated a noticeable influence on the performance of the membranes for the removal of metal ions as reported from several studies [41,[53][54][55][56]. The introduction of 1.0 wt% TiO 2 into membrane matrix structure improves the hydrophilicity and makes the surface more negatively charged.…”

Section: Introductionmentioning

confidence: 90%

Novel PVDF-PVP Hollow Fiber Membrane Augmented with TiO2 Nanoparticles: Preparation, Characterization and Application for Copper Removal from Leachate

et al. 2021

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High proportion of copper has become a global challenge owing to its negative impact on the environment and public health complications. The present study focuses on the fabrication of a polyvinylidene fluoride (PVDF)-polyvinyl pyrrolidone (PVP) fiber membrane incorporated with varying loading (0, 0.5, 1.0, 1.5, and 2.0 wt%) of titanium dioxide (TiO2) nanoparticles via phase inversion technique to achieve hydrophilicity along with high selectivity for copper removal. The developed fibers were characterized based on scanning electron microscopy (SEM), energy dispersive X-ray spectroscopy (EDX), permeability, porosity, zeta potential, and contact angle. The improved membrane (with 1.0 wt% TiO2) concentration recorded the maximum flux (223 L/m2·h) and copper rejection (98.18%). Similarly, 1.0 wt% concentration of TiO2 nanoparticles made the membrane matrix more hydrophilic with the least contact angle of 50.01°. The maximum copper adsorption capacity of 69.68 mg/g was attained at 1.0 wt% TiO2 concentration. The experimental data of adsorption capacity were best fitted to the Freundlich isotherm model with R2 value of 0.99573. The hybrid membrane developed in this study has considerably eliminated copper from leachate and the concentration of copper in the permeate was substantially reduced to 0.044 mg/L, which is below standard discharge threshold.

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“…Hence, this inhibitory effect might also be due to the adsorption of phenanthrene by SDBS [48]. In addition, the SDBS also could be adsorbed onto the sediment to occupy the adsorption site [49][50][51][52].…”

Section: The Single Effect Of Salinity and Sdbsmentioning

confidence: 99%

Effect of Anion Surfactants on the Adsorption of Polycyclic Aromatic Hydrocarbons on Sediment under Estuarine Mix Conditions

Qian¹,

Li²,

Yao³

et al. 2020

Pol. J. Environ. Stud.

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We investigated the adsorption of phenanthrene (PHE) onto estuarine sediment with varied salinity and concentrations of anionic surfactant (sodium dodecyl benzene sulfonate, SDBS). It is a critical step for better understanding of the migration of polycyclic aromatic hydrocarbon (PAH) pollutants to seawater. The concentration of PHE in the experimental system was detected by a fluorescence spectrophotometer and the results were expressed by partition coefficient (in terms of K d ). It found that the salinity promoted and the SDBS inhibit the adsorption of PHE onto sediment in a single system. The combination effect of SDBS and salinity enhance this adsorption behavior but varied significantly with the ratio of salinity to surfactant. It is a confirmed fact that the mobility of phenanthrene in water increased with the combination of the salinity and SDBS. It would lead to the pollution of PHE change from point model to mobility model and increase its flux into the sea. However, the mechanism of those adsorption behaviors is unclear and may relate to the interactions between sediment and SDBS, SDBS and salinity, and sediments and salts, which need further study.

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An Experimental Study on the Simultaneous Phenol and Chromium Removal From Water Using Titanium Dioxide Photocatalyst

Cited by 41 publications

References 17 publications

Artificial intelligence accuracy assessment in NO2 concentration forecasting of metropolises air

Artificial intelligence accuracy assessment in NO2 concentration forecasting of metropolises air

Novel PVDF-PVP Hollow Fiber Membrane Augmented with TiO2 Nanoparticles: Preparation, Characterization and Application for Copper Removal from Leachate

Effect of Anion Surfactants on the Adsorption of Polycyclic Aromatic Hydrocarbons on Sediment under Estuarine Mix Conditions

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