Management strategy of activated carbon used in water treatment system from Engine Power Plant based on regeneration and new methods of characterization.

Abstract

In Cuba, power plants as industrial facility generate electricity from primary energy (e.g. diesel). They use electric generators that convert mechanical energy (generated by internal combustion engines) into electrical energy with the aim of supporting the National Electro-energetic System during peak hours where the consumption of electrical energy reaches a maximum value and also to improve its transmission, especially in isolated regions. During combustion, engines produces gases at high temperatures and pressures. To decrease temperatures water is used as cooling medium. However, the quality of the industrial water have to reach specific standards in order to avoid incrustation, corrosion and salt precipitation, which affect the efficiency of the engines. For this reason, a Water Treatment Unit (WTU) is present in the power plant. Among other equipment in the WTU, a granular activated carbon (GAC) fix-bed column (filter) is used which reduce the total hardness of the water. A reverse osmosis membrane set is also present is the WTU for removing several compounds from the cooling water. According to the standards, the GAC filter is exhausted and need to be replaced (by imported virgin GAC) based on the monitoring of the pH and conductivity of the water but these parameters cannot offer quantitative information about the real exhaustion degree of the GAC. Technological limitations of facilities in the country impede a better monitoring of the GAC filter performance. After exhaustion, the landfilled GAC creates a solid waste problem, for this reason, a regeneration process of the exhausted GAC should be applied and the effectiveness of regenerated GAC must be guaranteed in order to improve the current management strategy of this porous material. In addition, a specific quantitative analytical method to characterize the exhaustion degree of the GAC needs to be implemented in order to detect GAC with still has enough adsorption capacity (and evaluate regeneration efficiency) and that could be reused in the filter and therefore reduce the importation cost of the process. In this sense, acoustic emission analysis (AEA) and infrared thermography (IRT) were developed in this research as complementary method to texturally characterize GAC layer samples in the filter. In this thesis, the main objective is to undertake a comprehensive study for improving the GAC management strategy in power plants in Cuba. Including new, accurate and suitable quantitative methods such as AEA and IRT for determining exhaustion level and textural characteristics of this porous material and chemical regeneration after exhaustion. In addition, characterize an exhausted reverse osmosis membrane in order to determine the main compounds deposited during the exploitation process. Using a specific sampler, from a previous declared exhausted filter, the GAC samples were taken from the top to the bottom according to the subsequent order: Top (position = 0 m), 0.2, 0.4, 0.6 and Bottom (position=0.7 m). A full characterization of these GAC samples was performed by applying the new methods developed in this research (AEA and IRT) and by different conventional analytical techniques. Acoustic emission method is a new technique for the characterization of granular activated carbons based on the measurement and analysis of the sound produced by water flooding through a sample of granular activated carbon. In the sudden contact between water and the GAC sample, the sound produced by bubbles escaping from the carbon pores, slits and cracks because of the displacement of the air present in them, can be used to assess to the pores of the material. Exhausted GAC resulted in a reduction of bubbling potential and consequently in a reduction and a change in the sound signal amplitude and intensity because the amounts of compounds with different molecular sizes adsorbed, which block cracks and pores of GAC, creating an important reduction of pore volume and specific surface area. On the other hand, GAC-Virgin presents a much higher amount of available pores and cracks because of its unused condition, which contributes to a stronger sound during experiments. An exhaustion profile in the filter was found taking into account different acoustic parameters obtained from the signal (using a the cut-off frequency to the band-pass filter from 3.5 to 25.6 kHz, representing bubbles from 0.2 to 1.56 mm), such as integrated area under the signal envelope curve (SS), envelope maxima peak (EMP), energy (E) and power (P). A polynomial (for SS (R2 = 0.98)) and linear (for EMP (R2 = 0.96), E (R2 = 0.99) and P (R2 = 0.99)) correlation was obtained by plotting the GAC layer and the acoustic parameters. The use of acoustic measurements makes it possible to determine the overall porosity but also to characterize the porous structure of GAC. A yellow (this color represents the medium power components in the signal) segmentation was applied to the spectrograms obtained from the acoustic signal to characterize the bubbling potential coming from the GAC sound. In addition, the selection of the best binarization method was studied in order to obtain the best correlation with the energy and power from the acoustic signal. The iterative Otsu method described in a better way the exhaustion profile of the GAC in the filter as function of the white pixels (Pw) (obtained after binarization of the yellow segmentation) with R2 = 0.99. IRT analysis during the GAC-water contact allows obtaining thermographic images due to the release of heat during the wetting process of the GAC particles. An optimization study to select the best particle size to perform the experiments was done, resulting in 0.3-0.7 mm. This new technique allows quantifying the exhaustion level of GACs at different depth within the fixed bed filter by using two parameters from the IR images: the surface temperature (T) and the surface thermal density (qsurface) of the GAC particles. GAV-Virgin presented the best IRT parameter (35.30C and 0.037 m2 0C) reflected in more red color in the thermograms and as a consequence of the high amount of available pores to release heat during the experiments. On the other hand, GAC-Exh presented the lowest temperature (more blue color in the thermograms) and surface thermal density (28.10C and 0.013 m2 0C respectively) because the higher amount of pores that have been blocked during the exploitation process, inducing a lower change in temperatures during the experiments. After a fitting process of the thermographic parameters and the studied filter layers, the regression coefficients obtained were 0.99 and 0.98 for T and qsurface respectively. A yellow segmentation of the thermograms was also performed. Later, a grey scale image was obtained in order to apply the direct component of the Fast Fourier Transform in two dimensions (FYs). Considering the FYs value obtained from each IRT image, a linear trend could be obtained for the different GAC layer samples indicating the different exhaustion degrees with a regression coefficient of 0.96. Thermogravimetric analysis was used to compare the ashes content between samples. Difference were found when comparing the GAC-Top, GAC-Bottom and GAC-Virgin (just 3.45%) indicating that the differences in the inorganic content was a consequence of the exploitation process. GAC-Top presents 22.14% more than the GAC-Virgin sample and 2.89% more than GAC-Bottom sample. Scanning electron microscopy was used to compare the sample' surface morphology. Differences were found in the external surface of the GAC-Top, GAC-Bottom and GAC-Virgin samples. The GAC-Top showed more roughness on its surface in comparison to GAC-Virgin sample because of the different inorganic compound adsorbed/precipitated on the GAC’s surface. These results were also confirmed by applying digital images processing where white pixels in the SEM images were associated to the amount of adsorbed compound in the AC. An FTIR analysis allowed attest the presence of CaCO3 and SiO2 on the GAC-Top and GAC-Bottom samples. However, this was not the case for GAC-Virgin sample indicating that these compounds were adsorbed during the filtration process. An analysis of the XRF results allowed confirming that CaCO3 is the compound with higher content present in the GAC samples from the filter. In this sense, GAC-Top presents 30.96% more CaCO3 than GAC-Virgin (just 0.34%). The CaCO3 was decreasing from the top to the bottom of the filter. These results are also consistent with the direction of the mass transfer zone displacement through the GAC bed and the adsorption wave theory. After applying TD-GC/MS, it was confirmed that the organic fraction adsorbed in the GAC was very low but different between samples, presenting GAC-Top sample the highest concentration, follow by GAC-Bottom sample and finally GAC-Virgin sample. NMR was also applied to the GAC samples. 1H-wideline relaxometry allows confirming differences in the porous structure taking into account to the relaxation decay times and their fractional contributions, which was 2.3 more higher for the GAC-Bottom compared to the GAC-Top. In the case of high-resolution 13C solid-state, it was possible to confirm the presence of aromatic moieties and carboxylic acid groups in the top and bottom samples. Finally, a characterization of the samples from the filter using N2 gas adsorption was applied. Results ratified differences in the properties of the GAC samples in term of surface area and pore volume, existing an increasing trend from the top to the bottom of the filter. GAC-Virgin sample presented the highest properties (1288 m2 /g and 0.536 cm3 /g respectively). On the other hand, the ratio between the total pore of GAC-Top and GAC-Bottom samples with GAC-Virgin sample were 19.2% and 36.4% respectively indicating a more deteriorated surface and adsorption capacity of the GAC-Top sample compared with GAC-Bottom. The acoustic and the thermographic parameters were fitted with the gas adsorption results. A correlation between the total pore volume and the energy and the power of the acoustic signal allowed obtaining R= 0.88 for an exponential model. The micropore volume was also fitted with these acoustic parameters resulting in R2= 0.87 for a linear model. Finally, the surface area was fitted with T and qsurface where a regression coefficient of 0.93 and 0.94 respectively for a linear fit was obtained.