Optimizing stabilization of waste-activated sludge using Fered-Fenton process and artificial neural network modeling (KSOFM,MLP)

Sludge management is a fundamental activity in accordance with wastewater treatment aims. Sludge stabilization is always considered as a significant step of wastewater sludge handling. There has been a progressive development observed in the approach to the novel solutions in this regard. In this research, based on own initially experimental results in lab-scale regarding Fered-Fenton processes in view of organic loading (volatile-suspended solids, VSS) removal efficiency, a combination of both methods towards proper improving of excess biological sludge stabilization was investigated. Firstly, VSS removal efficiency has been experimentally studied in lab-scale under different operational conditions taking into consideration pH [Fe²⁺]/[H₂O₂], detention time [H₂O₂], and current density parameters. Therefore, the correlations of the same parameters have been determined by utilizing Kohonen self-organizing feature maps (KSOFM). In addition, multi-layer perceptron (MLP) has been employed afterwards for a comprehensive evaluation of investigating parameters correlation and prediction aims. The findings indicated that the best proportion of iron to hydrogen peroxide and the optimum pH were 0.58 and 3.1, respectively. Furthermore, maximum retention time about 6 h with a hydrogen peroxide concentration of 1,568 mg/l and a current density of 650–750 mA results to the optimum VSS removal (efficiency equals to 81 %). The performance of KSOFM and MLP models is found to be magnificent, with correlation ranging (R) from 0.873 to 0.998 for the process simulation and prediction. Finally, it can be concluded that the Fered-Fenton reactor is a suitable efficient process to reduce considerably sludge organic load and mathematical modeling tools as artificial neural networks are impressive methods of process simulation and prediction accordingly.     

Simultaneous Cr (VI) reduction and diazinon oxidation with organometallic sludge formation under photolysis: kinetics,degradation pathways,and mechanism

Environmental Science and Pollution Research - In this study, simultaneous removal of an organic matter (diazinon, DIZ) and an inorganic substance (chromium, Cr) was used. Breaking down of organic...     

Photo–degradable and recyclable starch/Fe3O4/TiO2 nanocomposites: feasibility of an approach to reduce the recycling labor cost in plastic waste management

Environmental Science and Pollution Research - In this research, a biodegradable starch/Fe3O4/TiO2 bio-nanocomposites (SFT) were produced using different nano Fe3O4/TiO2 (FT) (3, 5, and 10 (wt% dry...     

Evaluation of a novel hollow fiber membrane technique for collection of 1,1-dimethylhydrazine in air

The purpose of this study was to develop a novel one-step method for the time-weighted average determination of 1,1-dimethylhydrazine (UDMH) in the air followed by spectrophotometric detection. For this reason, 0.1% hydrochloric acid as the absorbent was used in hollow fiber (HF) membrane for sampling of UDMH from an atmospheric standard chamber. Response surface methodology (RSM) with central composite design (CCD) was used to optimize the sampling parameters, such as flow rate and sampling time. Moreover, several analytical parameters including breakthrough (BT) volume, storage time, and carryover effect of the proposed HF were investigated. The results showed that optimal sampling rate was 9.90 mL/min. In order to validate the proposed method, it was compared with the National Institute for Occupational Safety and Health (NIOSH) 3515 method, which showed good compatibility between the two methods. Intra- and inter-day repeatability values of the HF method were in the range 0.082–0.1 and 0.091–0.12, respectively, and the limits of detection (LODs) and limits of quantitation (LOQs) were 0.002 and 0.006 ng/mL, respectively. The storage time of the proposed HF was 7 days at 2 °C. These results demonstrated that the one-step HF membrane offered a high sensitivity for sampling of UDMH in air.     

Water and waste load allocation in rivers with emphasis on agricultural return flows: application of fractional factorial analysis

In this paper, a new methodology is developed to handle parameter and input uncertainties in water and waste load allocation (WWLA) in rivers by using factorial interval optimization and the Soil, Water, Atmosphere, and Plant (SWAP) simulation model. A fractional factorial analysis is utilized to provide detailed effects of uncertain parameters and their interaction on the optimization model outputs. The number of required optimizations in a fractional factorial analysis can be much less than a complete sensitivity analysis. The most important uncertain inputs and parameters can be also selected using a fractional factorial analysis. The uncertainty of the selected inputs and parameters should be incorporated real time water and waste load allocation. The proposed methodology utilizes the SWAP simulation model to estimate the quantity and quality of each agricultural return flow based on the allocated water quantity and quality. In order to control the pollution loads of agricultural dischargers, it is assumed that a part of their return flows can be diverted to evaporation ponds. Results of applying the methodology to the Dez River system in the southwestern part of Iran show its effectiveness and applicability for simultaneous water and waste load allocation in rivers. It is shown that in our case study, the number of required optimizations in the fractional factorial analysis can be reduced from 64 to 16. Analysis of the interactive effects of uncertainties indicates that in a low flow condition, the upstream water quality would have a significant effect on the total benefit of the system.     

Analysis of gross alpha, gross beta activities and beryllium-7 concentrations in surface air: their variations and statistical prediction model

Measurement of gross α, gross β activities and cosmogenic beryllium-7 (⁷Be) concentrations were made both daily and weekly during the years 2001–2004 from samples of atmospheric aerosols filtered from the air at Tehran Nuclear Research Center (35 41′ N) and Zahedan (28 29′ N). Weekly aerosol samples collected with the high-volume air samplers on cellulose filters were used to determine the ⁷Be contents of samples, using a semiconductor gamma spectrometer. Airborne dust samples were collected daily on fiber glass filters and used to determine the gross β and gross α activities with automatic beta analyzer and a ZnS(Ag) counter, respectively. In this work, the concentration and meteorological data were used to determine models for gross α, gross β and ⁷Be. The air concentrations of gross β and gross α activities and ⁷Be concentrations displayed lognormal distributions during the study period. Both β and ⁷Be have maximum activity concentrations during warm mid-year months.     

Contaminants of emerging concern: a review of new approach in AOP technologies

The presence of contaminants of emerging concern (CECs) such as pharmaceuticals and personal care products (PPCPs), endocrine-disrupting compounds (EDCs), flame retardants (FRs), pesticides, and artificial sweeteners (ASWs) in the aquatic environments remains a major challenge to the environment and human health. In this review, the classification and occurrence of emerging contaminants in aquatic environments were discussed in detail. It is well documented that CECs are susceptible to poor removal during the conventional wastewater treatment plants, which introduce them back to the environment ranging from nanogram per liter (e.g., carbamazepine) up to milligram per liter (e.g., acesulfame) concentration level. Meanwhile, a deep insight into the application of advanced oxidation processes (AOPs) on mitigation of the CECs from aquatic environment was presented. In this regard, the utilization of various treatment technologies based on AOPs including ozonation, Fenton processes, sonochemical, and TiO₂ heterogeneous photocatalysis was reviewed. Additionally, some innovations (e.g., visible light heterogeneous photocatalysis, electro-Fenton) concerning the AOPs and the combined utilization of AOPs (e.g., sono-Fenton) were documented.     

Evaluating two test methods used for characterizing leaching properties

A standard leaching test method (EN 12457-3) was compared with a modified pHstat-column leaching test method with respect to leaching information obtained for aggregates composed of different alkaline solid wastes. In addition to a different experimental set-up, the major dissimilarity between the two test methods was the chemical equilibrium condition, i.e., in the first test the system approaches equilibrium while in the second test the system is far from equilibrium conditions. The leaching trends of sodium, calcium, chloride, sulfate and cadmium were studied. Results showed that these two test methods were comparable in respect to the total amount sodium and sulfate leached. It was also concluded that the two test methods provide different information for the constituents for which dissolution reaction is highly dependent on pH and other experimental conditions, e.g., flow rate. It was found that a batch test can be used in order to investigate the total amount leached, while a modified column-pHstat test generates more detailed results on leaching trends of some constituents.