Particulate matter removal in drinking water treatment via direct granular filtration requires specific flocculation conditions (a process typically termed 'high energy flocculation'). Predicting filtered water turbidity based on flocculated water characteristics remains difficult. This study has sought to establish a relationship between filtered water turbidity and the flocculated water characteristics. Flocculation oflow-turbidity raw water was evaluated online using a Photometric Dispersion Analyser (PDA) and a Dynamic Particle Analyser in a modified jar test followed by a bench-scale anthracite filter. Coagulants used were alum, PASS100 and ferric sulphate, in addition to a polydiallyldimethylammonium chloride (polyDADMAC) cationic polymer. They were dosed in warm and cold waters, and flocculated with intensities (G) from 0 to 100 s(-1). Of the two instruments selected to analyse flocculation performance, the Dynamic Particle Analyser was shown to be the most sensitive, detecting small changes in floc growth kinetics and even floc growth under low flocculation conditions which remained undetected by the PDA. Floc size was shown to be insufficient in predicting particulate matter removal by direct granular filtration as measured by turbidity, although a threshold d(v) value (50 microm) could be identified for the test conditions evaluated in this project, above which turbidity was systematically lower than 0.2 NTU.
The impregnated active carbon used in air purification systems degrades over time due to exposure to contamination and mechanical effects (packing, settling, flow channeling, etc.). A novel approach is proposed to detect contamination in active carbon filters by combining the electromechanical impedance spectroscopy (EMIS) and electrochemical impedance spectroscopy (ECIS). ECIS is currently being used to evaluate active carbon filtration material; however, it cannot differentiate the impedance changes due to chemical contamination from those due to mechanical changes. EMIS can detect impedance changes due to mechanical changes. For the research work presented in this paper, Piezoelectric wafer active sensor (PWAS) was used for the EMIS method. Some remarkable new phenomena were unveiled in the detection of carbon filter status. 1.PWAS EMIS can detect the presence of contaminants, such as water and kerosene in the carbon bed 2. PWAS EMIS can monitor changes in mechanical pressure that may be associated with carbon bed packing, settling and flow channeling 3. EMIS and ECIS measurements are consistent with each other and complimentaryA tentative simplified impedance model was created to simulate the PWAS-carbon bed system under increasing pressure. Similar impedance change pattern was observed when comparing the simulation results with experimental data.
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