Synthesis and Characterization of Zeolites Produced from Low-Quality Coal Fly Ash and Wet Flue Gas Desulphurization Wastewater

This study investigated a low-energy-consuming procedure for the synthesis of zeolite materials from coal fly ash (CFA). Materials containing zeolite phases, namely Na–X, Na–P1, and zeolite A, were produced from F–class fly ash, using NaOH dissolved in distilled water or in wastewater obtained from the wet flue gas desulphurization process, under atmospheric pressure at a temperature below 70 °C. The influence of temperature, exposure time, and alkaline solution concentration on the synthesized materials was tested. In addition, chemical, mineralogical, and textural properties of the obtained materials were determined by X-ray diffraction (XRD), X-ray fluorescence (XRF), scanning electron microscopy (SEM), and cation exchange capacity (CEC). Cd(II), Ni(II), NH4+ cation, and Se(VI) anion sorption experiments were conducted to compare the sorption properties of the produced synthetic zeolites with those of the commercially available ones. Zeolitization resulted in an increase of CEC (up to 30 meq/100 g) compared to raw CFA and enhanced the ability of the material to adsorb the chosen ions. The obtained synthetic zeolites showed comparable or greater sorption properties than natural clinoptilolite and synthetic Na–P1. They were also capable of simultaneously removing cationic and anionic compounds. The structural, morphological, and textural properties of the final product indicated that it could potentially be used as an adsorbent for various types of environmental pollutants.

Sulphite measurement and its influence on Hg behaviour in wet-limestone flue-gas desulphurization

The most abundant and typical reducing agent for oxidized mercury in the slurry of wet flue-gas desulphurization (FGD) is the absorbed sulphur dioxide (SO2), which is present as different species of bisulphite or sulphite, depending on the pH of the slurry. In this study, two different measurement principles for continuous sulphite measurement in the slurry of lab-scale FGD were investigated to check their feasibility to be implemented in a wet FGD. The first method is based on light absorbance at the characteristic wavelength of sulphite measurement using a spectrophotometer and, in the second method, sulphite is measured as sulphur dioxide using a gas sensor. In addition, the correlation of sulphite concentration and mercury (Hg) in the slurry can be shown by measuring sulphite semi-continuously. It was concluded that using a spectrophotometer leads to distorted results. In contrast, measuring sulphite as SO2 in the gas phase proved to be more selective. The implementation of the measurement technique in the lab-scale FGD showed promising results for sulphite measurement. Thus, the correlation of Hg and sulphite concentration could be shown at different synthetic slurries containing different halides. Using a slurry without halides demonstrated the ambivalent influence of sulphite in reactions involving Hg, in which sulphite acts as a ligand for Hg complexes as well as a reducing agent, depending on the existing concentration. However, in the presence of halides, the role of sulphite was less significant.

Multimodel Anomaly Identification and Control in Wet Limestone-Gypsum Flue Gas Desulphurization System

Sulphur dioxide, as one of the most common air pollutant gases, brings considerable numbers of hazards on human health and environment. For the purpose of reducing the detrimental effect it brings, it is of urgent necessity to control emissions of flue gas in power plants, since a substantial proportion of sulphur dioxide in the atmosphere stems from flue gas generated in the whole process of electricity generation. However, the complexity and nondeterminism of the environment increase the occurrences of anomalies in practical flue gas desulphurization system. Anomalies in industrial desulphurization system would induce severe consequences and pose challenges for high-performance control with classical control strategies. In this article, based on process data sampled from 1000 MW unit flue gas desulphurization system in a coal-fired power plant, a multimodel control strategy with multilayer parallel dynamic neural network (MPDNN) is utilized to address the control problem in the context of different anomalies. In addition, simulation results indicate the applicability and effectiveness of the proposed control method by comparing with different cases.