Impact of Conditioning Substances and Filtration Pressure on Dewatering Efficiency of Sewage Sludge

Dewatered Sludge Decorated with Nanoparticles for Alum Sludge Conditioning towards the Concept of "End-of-Waste"

The circular economy concept is leading environmental engineering in the search for "End-of-Waste" criteria. Untreated waste residue results from drinking water treatment plants, causing severe environmental issues, and its reuse is essential. In this regard, this investigation introduces the beneficial reuses of alum sludge cake to close the loop between sludge waste generation and reuse. Considering alum sludge as a resource for dewatering instead of its categorization as a waste reflects an "End-of-Waste" approach. Alum sludge cake was thermally calcined at 400 °C and named thermally treated alum sludge cake (TAS-cake). In this study, TAS-cake decorated with magnetite with a percent weight of 5 to 1%, respectively, was labeled as TAS-cake@Fe-(5-1). X-ray diffraction (XRD) and morphologies were applied to characterize the hybrid composite. A Fenton-based hybrid composite was applied to extrude water from alum sludge for 7 min of conditioning time. Furthermore, the factorial design based on response surface methodology (RSM) was applied to optimize the operational variables. TAS-cake@Fe-(5-1) and hydrogen peroxide revealed 1.2 g/L and 740 mg/L doses at pH 3.0, showing pronounced performance and revealing the highest capillary suction time (CST) reduction, which reached 53%. A temperature increase also showed a pronounced enhancement effect on the sludge dewaterability that reached 72% when 55 °C was applied. Thus, such a novel conditioner is a promising candidate for alum sludge conditioning.

Optimization of dewatering process of concentrate pressure filtering by support vector regression

This work studies the mechanism and optimization methods of the filter press dehydration process to better improve the efficiency of the concentrate filter press dehydration operation. Machine learning (ML) models of radial basis function (RBF)-OLS, RBF-generalized regression neural network, and support vector regression (SVR) are constructed, and laboratory and industrial simulations are performed separately, finally, optimization methods for the filtration dewatering process are designed and applied. In laboratory, all the machine learning models have obvious mistakes, but it can be seen that SVR has the best simulation effect. In order to achieve the optimization of the entire filtration and dewatering process, we obtained enough data from the industrial filtration and dewatering system, and in the industrial simulation results all the machine learning models performed considerably, SVR achieves the best accuracy in industrial simulation, and the simulated mean relative error of moisture and processing capacity are 1.57% and 3.81%, the model was tested with newly collected industrial data to verify the credibility. The optimal simulation results are obtained by optimization method based on control variables. Results show that the ML method of SVR and optimization methods of control variables applied to the industry not only can save energy consumption and cost but also can improves the efficiency of filter press operation fundamentally, which will provide some options for intelligent dewatering process and other industrial production optimization.

Analysis of Reject Water Formed in the Mechanical Dewatering Process of Digested Sludge Conditioned by Physical and Chemical Methods

Reject water separated from digested sludge may be a potential source of nutrients due to its high content. However, most often, reject water after sludge dewatering is directed to sewage lines at wastewater treatment plants, negatively affecting their operation, especially in the biological part. The activities related to sludge conditioning before dewatering have a direct impact on the quality of the reject water. The reject water of raw digested sludge is characterized by very high concentrations of ammonium nitrogen, at 1718 mgN-NH4+/dm3; phosphates, at 122.4 mgPO43−/dm3; and chemical oxygen demand (COD), at 2240 mgO2/dm3. The objective of the research was to determine the impact of selected sludge conditioning methods on the quality of reject water obtained after sludge dewatering. The following parameters were analyzed in the reject water: the chemical oxygen demand (COD), phosphates, ammonium nitrogen, and total suspended solids (TSS). It has been observed that the sludge sonification process increases the content of impurities (COD, phosphates) in reject water with an increase in the amplitude of the ultrasonic field. On the other hand, the chemical reagents cause a decrease in the concentration of the pollutants with an increase of the chemical dose. It has been found that the inorganic coagulant PIX 113 gives much better results regarding the reduction of contamination than the polyelectrolyte Zetag 8180.

Conditioning of Sewage Sludge with Physical, Chemical and Dual Methods to Improve Sewage Sludge Dewatering

The paper presents the impact of different methods of sewage sludge conditioning on the improvement of sludge dewatering during pressure filtration processes. The following conditioning methods were tested for sludge preparation: sonication, addition of organic and inorganic chemicals (Zetag 8180, PIX 113 and the combined action of both substances). The research covered: physical and chemical analysis of sewage sludge, measurement of capillary suction time as an indicator of sludge dewaterability, some technical parameters of sludge pressure filtration process and the analysis of filtrate to assess the degree of contamination. The results of the research showed that the final water content of the prepared sludge decreased, while the specific filtration resistance increased. Among the tested methods the best results of sludge dewatering effects were obtained for sonicated sludge and its preparation with inorganic coagulant PIX 113. The combined effect of sonication with the addition of chemicals Zetag 8180 and PIX113 to sludge allowed for the reduction of organic substances, ammonium nitrogen and phosphates in filtrate after sludge dewatering.