Texttile wastewater

View with images and charts Textile Wastewater and its effect Chapter 1 Introduction One of the major problems concerning textile wastewater is colored effluent. The discharge of color waste is not only damaging to the aesthetic nature of the receiving streams but also toxic aquatic life. In addition, color interferes with the transmission of sunlight into the stream and therefore reduces photosynthetic action. The color in the effluent is mainly due to unfixed dye. The concentration of unused dyes in the effluent depends upon the nature of dyes and dyeing process underway at the time (McMullan, et al., 2001). Inefficiency of dyeing process results in 10-25 % of all dye stuffs being lost directly to the wastewater (Perineau, et al., 1982). Although the textile dyes contribute only a small portion of the total volume of discharged wastewater after the dyeing process, yet they make it deeply colored (McKay, et al., 1985). Considerable work has been carried out on the removal of dye from wastewater (Perineau, et al., 1982; McKay, et al., 1985; Gupta, 1985; Khattri, 2000; Low, et al., 2000; Liversidge, et al., 1997; Choy, et al., 1999, Asilian, et al., 2006).

Water insoluble dyes (e.g. disperse and vat dyes) generally exhibit good exhaustion properties i.e. most of the dye bonds to the fiber and have been reported to be removed by physical means such as flocculation. When effluents containing these classes of dyes are discharged to a conventional sewage treatment works most of the color is removed by adsorption on biomass. However, since the introduction of water soluble dyes (reactive dyes), which are extensively used in the industry, conventional biological treatment processes such as the primary and secondary treatment systems are no longer able to achieve adequate color removal. The color of reactive dyes is due to the presence of N=N azo bonds and chromophoric groups. These dyes are first absorbed on the cellulose and then react with fiber by forming covalent bond between the dye molecule and the fiber. After fixation of the dyes on the fiber, about 10–50% of the initial loading is present in the dye bath effluent which gives rise to a highly colored effluent. Because of non-biodegradability due to chemical structure and molecular size they can create a problem in the environment. It is necessary, therefore, to use tertiary treatment to remove color before discharging the wastewater into natural streams.

Adsorption appears to offer the best prospects over all the other techniques of dye removal at tertiary stage (Robinson, et al., 2001; Kamel, et al., 1991; Keith, et al., 1999; McKay, 1981).

From literature survey, it is revealed that a number of biological adsorbents have been investigated for removing reactive dyes, these include amongst others; maize cob, wood and rice hull (Low et. al 1997). It is known that activated carbon is a versatile adsorbent because of its sufficient surface area, pore volume, high degree of surface reactivity and exhibits reasonable adsorption capacities for decolorants in aqueous solutions. Dye adsorption is enhanced because of the presence of mesopores together with micropores in the activated carbon. There are some commercially available active carbons but these are expensive (Bhattacharya et. Al 1984, Singh and Rawat 1994, McKay et. al. 1986, Khare et al. 1987).

Now one aspect is that what technology is to be used for removing color. As more and more stringent regulations for industrial effluent deposition into water bodies are being applied,

selection of a treatment method with high removal efficiencies for dyes and less operational problems is becoming inevitable. Liquid effluent treatment is commonly done in fixed beds for large-scale operation. However, fluidized bed or mechanically agitated suspensions are preferred for medium/small-scale ones. Another aspect to be considered is that wastewaters always contain suspended solids (e.g., fibers, waxes and gums), which clog fixed beds, requiring frequent backwashing or fluidization to dislodge the foreign material. Besides, fluidized bed technology can overcome the setbacks of the fixed bed treatment process by increasing adsorbent surface area, efficient mixing, and better contact of adsorbent and adsorbate. Typical problems encountered in fixed bed are dead zones, gas/vapor pockets, and channeling. In addition, pressure drops in fixed bed increases with the increase in flow rate causing high pumping cost compared to fluidized bed where pressure drop remains almost constant with increase in flow rate.

Textile dyeing industry is an important labor-based, export orientated sector in Bangladesh.

The full flourishment of this industry is significant for the country’s economy. In the dyeing industries, above 30-60 L of water are consumed per kg of cloth dyed and large quantities of the effluents are released during processing. It amounts to about 16% of the total water consumed in the factory (Denold 1984, Namasivayam et. al. 1994). Most of the factories have no effluent treatment plants. They are sometimes directly drained to the rivers or canals causing severe water pollution and in other cases they are treated to some extent but not enough vigorously, so that all the dissolved colored materials can be decreased below the tolerable limit. Human and ecological health concerns have prompted the government to require textile effluent discharges to have increasingly lower color and nitrogen levels. The removal of dye in an economic fashion, however, remains an important problem. Thus, despite being aware of the problem, many textile manufactures have failed to adequately remove azo dye compounds from their wastewaters. So in Bangladesh context an efficient but cost effective method for removal of colored materials from effluent is crucial. The current practice of a very few local industries who have undertaken tertiary stage water treatment is to use low grade activated carbon as single use adsorbent in a fixed bed and discard the spent for further use as fuel. To make such practice economically viable low-cost adsorbent as well as maximum utilization of it are necessary.

While the research for low cost adsorbent and indigenously prepared activated carbon is going on (G. Mckay et. al. 1986, Mohammad et al, 2006), the present study is focusing on the performance of fluidized bed of activated carbon in decolorizing tertiary stage waste water.

1.1 Objectives with Specific Aims and Outcome The objectives of this study are to investigate the followings:  Physical properties and adsorption characteristics of commercially available activated carbon  Performance of a fluidized bed of activated carbon in removing colored materials from water  Mass transfer characteristics of the fluidized bed With these specific aims in mind physical properties and equilibrium isotherm of granular activated carbon collected from Graphics Textiles Ltd. Sreerampur, Savar, Dhaka, Bangaldesh were investigated. The decolorizing performance of the fluidized bed is investigated by generating breakthrough curves. The breakthrough curves were obtained for

dyed water prepared in the laboratory as well as industrial effluent collected from …at tertiary stage. Finally, based on the isotherm and breakthrough curves mass transfer analysis of the fluidized bed was carried out.

Chapter 2 Literature Review Color is one of the characteristics of an effluent which is easily detected and readily traced back to source. Most of the dyes are stable to biological degradation. Color affects the nature of the water and inhibits sunlight penetration into the stream and reduces photosynthetic action. The primary concern about effluent color is not only its toxicity but also its undesirable aesthetic impact on receiving waters. Non-biodegradable nature of most of the dyes reducing aquatic diversity by blocking the passage of sunlight through the water represents serious problems to the environment. In some cases, dyes in low concentration are harmful to aquatic life. Since many dyes have adverse effect on human beings, the removal of color from the effluent or process has appeared of importance for ensuring healthy environment. It is pointed out that less than 1 ppm of dye content causes obvious water coloration [Allen et.al 1998].

From an environmental point of view, for removal of dyes from wastewater, lots of research works have been done in the past and still are going on at present on stability of liquid solid of both fixed bed and fluidized bed technology. The reviews of some earlier research works related to the present investigation are presented below: 2.1 Color removal efficiency The textile finishing industry generates a large amount of wastewater. Wastewaters from dyeing and subsequent rinsing steps form one of the largest contributions to wastewater generation in the textile industry. Because dyes are almost invariably toxic, their removal from effluent stream is ecologically necessary. Reactive dyes pose the greatest problem in terms of color, which is exacerbated by the dominance of cotton in today’s fashion industry.

The human eye can detect concentrations of 0.005 mg/L of reactive dye in water, and therefore, presence of dye exceeding this limit would not be permitted on aesthetic grounds (Pierce, 1994). After the reactive dyeing process is complete, up to 800 mg/l of hydrolyzed dye remains in the bath (Steankenrichter and Kermer, 1992). Fixation rates for reactive dyes tend to be in the range of 60–70% although the values tend to be higher in dyes containing two reactive groups (Carr, 1995). Therefore, up to 40% of the color is discharged in the effluent from reactive dyeing operation resulting in a highly colored effluent. An additional problem is that the reactive dyes in both ordinary and hydrolyzed forms are not easily biodegradable, and thus, even after extensive treatment, color may still remain in the effluent.

The conventional processes such as coagulation, flocculation and biological methods adopted for decolorizing effluents containing reactive dyes are no longer able to achieve an adequate color removal.

2.2 Adsorbents for color removal Adsorption methods have been invariably successful to decolorize textile effluents but according to the Santhy (2005) this application is limited by the high cost of adsorbents. The removal efficiency of activated carbon prepared from coir pith towards three highly used reactive dyes in textile industry was investigated. Batch experiments showed that the adsorption of dyes increased with an increase in contact time and carbon dose. Maximum decolorization of all the dyes was observed at acidic pH. Adsorption of dyes was found to

follow the Freundlich model. The column experiments using granular form of the carbon (obtained by agglomeration with polyvinyl acetate) showed that adsorption efficiency increased with an increase in bed depth and decrease of flow rate. The bed depth service time (BDST) analysis carried out for the dyes indicated a linear relationship between bed depth and service time. The exhausted carbon could be completely regenerated and put to repeated use by elution with 1.0 M NaOH. The coir pith activated carbon was not only effective in removal of color but also significantly reduced COD levels of the textile wastewater.

G. McKay et. al (1985) removed color by using some low cost materials. The low-cost materials can be used once and discarded by burning them. A variety of materials are reported in the literature for adsorption of different pollutants. Tree bark, coal, cotton waste, clay, hair etc., have been reported to adsorb different pollutants like heavy metals, pesticides, phosphates and sulphates, viruses etc. Since low-cost materials have been tried to remove different types of pollutants in different ionic forms, experiments were conducted to assess the feasibility of six low-cost materials to adsorb various types of dyes. He represents a number of low-cost materials (teakwood bark, ricehusk, coal, bentonite clay, hair and cotton waste) have been used as adsorbents for dyestuffs in aqueous solutions. Four red and four blue dyes have been studied; each color group consisted of an acidic, a basic, a disperse and a direct dye. The equilibrium isotherm for each dye-adsorbent system was determined and an adsorption capacity from zero to 200 mg dye g -1 of adsorbent was obtained. In general basic dyes adsorbed to a greater extent than the other dye classes but no single characteristic of the dye or adsorbent seemed responsible for such dye-adsorbent interactions and adsorption capacities.

M. EL Guend et.al (1986) has been studied the adsorption of four dyestuffs, namely, Basic Blue 69 (BB69), Basic Red 22 (BR22), Acid Red 114 (AR114) and Acid Blue 25 (AB25), onto bagasse pith. Bagasse pith is a cheap, abundant waste product from the sugar industry in Egypt and was found to have the following monolayer equilibrium saturation capacities: 158, 77, 23 and 22 mg dye/g pith. The effects of pith particle size range and dye solution temperature were studied.

Ahsan Habib et.al (2006) used tuberose sticks as an adsorbent for the removal of dyes present in industrial effluents. Methylene blue was selected as a model dye as an attempt to use waste tuberose sticks as an adsorbent for the removal of dye from wastewaters. The use of low-cost and eco-friendly adsorbents has been investigated as an ideal alternative to the current expensive methods of removing dyes from wastewater. Methylene Blue was used as model compound. The effects of contact time, initial dye concentration (20, 30, 40, 50 mg/L), pH and adsorbent dosages have been studied at 25 °C. The equilibrium time was found to be 30 min for all the dye concentrations. A maximum removal of 80% was obtained at pH 11.0 for an adsorbent dose 50 mg/50 mL of 40 mg/L dye concentration. Adsorption increased with increase in pH. Maximum desorption of 50% was achieved in water medium at pH 2.0.

There is a growing interest in using low cost, commercially available materials for the adsorption of dye colors. A wide variety of low cost materials, such as clay minerals, bagasse pith, wood, maize cob and peat are being tried as viable substitutes for activated carbon to remove dyes from colored effluents. That’s why Nassar and Magdy (1996) studied the adsorption of three basic dyes (basic yellow, basic red and basic blue) from an aqueous solution on palm-fruit bunch particles. The experimental results indicate that maximum adsorption capacities of the palm-fruit bunch particles were found to be 327 mg yellow dye per gram of adsorbent, 180 mg red dye per gram of adsorbent and 92 mg blue dye per gram of adsorbent. A comparative case study, based on the adsorption capacity alone, has shown

that the costs of the adsorbent required are 1.9%, 4.4% and 7.1% respectively, compared with the case of commercial activated carbon granules.

According to the Nigam et. al (2000) the release of dyes into the environment constitutes only a small proportion of water pollution, but dyes are visible in small quantities due to their brilliance. Tightening government legislation is forcing textile industries to treat their waste effluent to an increasingly high standard. Currently, removal of dyes from effluents is by physio-chemical means. Such methods are often very costly and although the dyes are removed, accumulation of concentrated sludge creates a disposal problem. There is a need to find alternative treatments that are effective in removing dyes from large volumes of effluents and are low in cost, such as biological or combination systems. This article reviews the current available technologies and suggests an effective, cheaper alternative for dye removal and decolorization applicable on large.

2.3 Adsorption in Fixed bed In terms of fixed bed adsorption one of the more successful simple modeling methods is the bed depth service time (BDST) model of hutchins (1973). This model assumed a linear relationship between the bed depth and the service time required for a chosen percentage content of impurity to reach the selected breakpoint in the bed. This model was applied to several fixed bed studies for the adsorption of various dyestuffs onto chitin by McKay et al.4 with considerable success. However, the model does not consider the mass transport kinetics of the adsorption process and therefore is limited in accuracy to the data under investigation and great care must be adopted in extending this model to predict design data.

Consequently, Mckay, Blair and Gradner (1986) has been developed a model. The model is based on external mass transport a pore diffusion, which is controlled by an effective diffusion coefficient. The model has been tested using experimental data obtained for the adsorption of Acid Blue 25 on chitin. Chitin has the ability to adsorb substantial quantities of dyestuffs from aqueous solutions. Hence, it may be a useful adsorbent for effluent treatment from textile mills. Mckay, Blair and Gradner (1984) investigate also the design procedures for batch and continuous fixed bed adsorption columns have been investigated for four dyestuffs. Batch type process are usually limited to the treatment of small volumes of effluent, but small adsorbent particle sizes may be used hence large external surface areas are available for mass transfer. Fixed bed systems, however, would sustain high pressure drop losses if fine adsorbent particles were used, but they have an advantage because adsorption depends on the concentration of solute in the solution being treated. The adsorbent is continuously in contact with fresh solution; hence the concentration in the solution in contact with a given layer of adsorbent in a column is relatively constant. Conversely, the concentration of solute in contact with a given quantity of adsorbent is continuously changing due to the solute being adsorbed.

Walker and Weatherley (1997) shown the reduction in effluent color produced by acid dyestuffs. This work involved the treatment of industrial wastewater from a nylon-carpet printing plant in Northern Ireland which currently receives no treatment and is discharged straight to sea. As nylon is particularly difficult to dye, acid dyes are required for successful coloration, but they cause major problems with the plant's effluent disposal. Granular activated carbon Filtrasorb 400 was used to treat this effluent in a fixed-bed column system.

Breakthrough curves from the fixed-bed column were shallow, even at low flow rates, which indicated a large mass transfer zone and inefficient use of adsorbent. Decrease in adsorbent particle size and decrease in linear flow rate produced a better bed performance. The bed

depth service time (BDST) model proved effective for comparison of column variables, with calculated BDST constants providing a useful indication of bed performance. The BDST model also gave good approximation in predicting a bed performance using the relationships postulated by Hutchins (1973).

On the other side Arvind Varma and Dmitrios Chatzipoulos (1994) investigates the aqueousphase adsorption and desorption of toluene in Filtrasorb-300 (F-300) activated carbon fixedbed adsorbers at 25째C under a wide range of operating conditions. Process dynamics were described successfully using a homogeneous surface diffusion model with external mass transfer and a surface diffusion coefficient that increases with surface coverage. The model also accounted for irreversible toluene adsorption on F-300. The adsorption isotherm parameters, the surface diffusion coefficient and its dependence on surface concentration were determined independently in batch adsorption studies. The value of the external mass transfer coefficient as a function of the Reynolds number was determined by fitting the adsorption breakthrough curves. The fraction of irreversible toluene adsorption as a function of initial surface loading was found from the desorption breakthrough curves. Use of these independently measured equilibrium and transport parameters in the model permitted the successful description of experimental rates of toluene adsorption and desorption in F-300 fixed beds under a variety of operating conditions.

2.4 Adsorption on Activated Carbon: Comparative studies in a fixed bed and fluidized bed For removal of color at tertiary level treatment adsorption on a fixed or packed bed of activated carbon is much popular, due to the properties of activated carbon of high organic color removal capacity. Though with activated carbon both organic and inorganic dyestuff can be adsorbed but it is more efficient in removing the organic color as it is an organic substance itself. The dyestuff or colored materials get adsorbed on the surface by external mass transfer and when the surface gets covered with adsorbate, the adsorption rate decreases as internal mass transfer is slower due to complicated process path of inside molecular structure. So after a certain period the activated carbon loses the ability of further adsorption and then it has to be either regenerated, which is still a difficult and expensive process or it has to be replaced by new activated carbon.

There are some difficulties faced in the operation of fixed or packed bed, such as: Clogging, channeling, gas/vapor pocket and dead zone may be created inside the bed, which reduces the flow and make it nonuniform, thus decreases adsorption rate. More over large pressure drop and non uniform temperature has to be often faced in fixed bed operation.

These set backs of fixed bed operation can be overcome by fluidized bed operation.

Advantages of using Fluidized bed adsorption process over fixed bed adsorption: 1 2 3 4 5 6

Adsorption surface area increases due to fluidization, more free adsorption sites become reachable to the adsorbate Efficient mixing and good contact between adsorbent and adsorbate is ensured Pressure drop is almost constant and thus required pumping energy does not vary Temperature in the system can assumed to be uniform or constant No clogging or channeling takes place Dead zone, gas/ vapor pocket creation inside the bed can also be avoided.

2.5 Adsorption in Fluidized bed Liquid effluent treatment in fluidized beds has received limited attention as adsorption onto activated carbon is commonly done in fixed beds for large-scale operation. But for the advantages of applying fluidized bed technology over fixed bed have drawn attentions of researchers for several years and research is still going on the industrial application of this process.

Adsorption with activated carbon is widely employed for the removal of organics in water purification. Several adsorber configurations are possible for treatment with activated carbon; these include batch vessel, continuous flow stirred tank, fixed bed, moving bed, and fluidized bed [e.g. Gulp et al. (1978)]. Traditionally, the treatment of choice has been packed-bed adsorption due to the ease and reliability of this operation. Nevertheless, several problems, such as excessive head loss, air binding, and fouling with biological and particulate matter are associated with packed-bed operation. These problems are significantly reduced in fluidizedbed adsorption; hence, Veeraraghavan, Fan and Mathews (1989) have focused on this mode of operation. Under certain conditions, the breakthrough time in a fluidized-bed adsorber is considerably shorter than that in a comparable fixed-bed adsorber. This phenomenon is probably due to the appreciable macro scale or axial mixing occurring in the solid and liquid phases of the fluidized bed. An axial dispersion model has been adapted to characterize the fluidized bed adsorber. The model takes into account the effects of axial mixing in the solid and liquid phases, mass transfer resistance in the laminar fluid boundary surrounding an individual adsorbent particle, and diffusional resistance within the particle. The model has been solved numerically to simulate the performance of a laboratory-scale adsorber. The results of the simulation closely represent experimental observations over wide ranges of the influent flow rate, fluidized bed height and adsorbent particle size.

Gordan Mckay (1988) studied the fluidized bed adsorption of pollutants onto activated carbon. The pollutants were phenol, p-chlorophenol and sodium dodecyl sulphate, and the effects of the flow rate of the solution and of the pollutant concentration have been studied.

He have shown the correlations between the external mass transfer coefficient k f and the liquid-phase Reynolds number and Analysis of the kinetic data seems to indicate that both external and internal mass transfer coefficients are rate controlling.

Correa et al (2006) developed a fluidized bed system for adsorption of phenol from aqueous solutions. This work is related to removal of phenol from wastewaters by adsorption onto polymeric resins, a current alternative to activated carbon. A closed circuit, bench-scale liquid fluidized bed system was developed for this purpose. Phenol aqueous solutions with initial concentrations in the range of 0.084 to 0.451 kg/m3 were used to fluidize small permeable capsules of stainless steel screen containing a commercial resin at 308 K. Experiments were carried out using a fluidizing velocity 20% above that of the minimum fluidization of the capsules. Typically, 30 passages of the liquid volume circulating through the bed were required to reach a quasi-equilibrium concentration of phenol in the treated effluent. A simple batch adsorption model using the Freundlich isotherm successfully predicted final phenol concentrations. Suspended solids, often present in residual waters and a common cause of fixed bed clogging, were simulated with wood sawdust.

Kargi and Eyiisleyen (1995) investigated the kinetics of biological removal of COD and nitrogen from a synthetic wastewater in a fluidized bed operating in batch mode. Synthetic wastewater consisted of diluted molasses, urea, KH 2PO4, and MgSO4, resulting in COD/N/P = 100/l0/2. The fluidized bed contained sponge particles surrounded by stainless-steel wires

as support particles for microorganisms, The system was operated with different initial COD and nitrogen concentrations, and COD-nitrogen consumption profiles were obtained. From the initial slopes of these curves, the initial rates of COD and nitrogen consumption and kinetic constants were determined. The system operated under a COD limitation with no dissolved oxygen limitations. The kinetic analysis for COD removal has shown a Monod type of kinetics with possible inhibition on the Ks term. Nitrogen removal rate data indicated an inhibition for nitrogen concentrations above 1,200 mg/l Wang et. Al (1996) analyzed the performance of granular activated carbon in a liquid-solid fluidized bed to remove phenols. Although the use of activated carbon for treatment of water and wastewater has received a lot of interest, the fundamental kinetic study of the adsorption process should be considered in advance. For an efficient adsorption process, the kinetic study provides the rapid removal of pollutants from solution and the adsorption equilibrium is the ultimate capacity for adsorption. Several physical configurations of adsorbers are available for activated carbon adsorption, e.g. batch vessel, continuous stirred tank, fixed bed and fluidized bed. Fluidized-bed operation has the advantage that the particles are in continuous motion with efficient mixing of the fluid, but suffers from particle attrition and erosion. Successful design of a fluidized-bed adsorption column requires the prediction of the effluent concentration time profile, i.e. the breakthrough curve.

2.6 Kinetics of adsorption on activated carbon Adsorption on activated carbon is one of the most effective and dependable technologies currently available for the treatment of drinking water and wastewaters contaminated with low concentrations of hazardous compounds (Irvin 1993). The role of activated carbon in effective water pollution control is well established. The rate of adsorption on activated carbon from a liquid phase is rather slow. The removal of man-made pollutants often is the predominant goal of adsorption by granular activated carbon in waste water treatment. As a cost consideration, granular activated carbon is much cheaper than the powdered form (Wang, R. et. Al 1996).

Liquid-phase adsorption has been shown to be highly efficient for removal of colors, odors, organic and inorganic matter from process or waste effluents. Activated carbons (granular or powdered) are widely used adsorbents because of their excellent adsorption capability for organic pollutants (Juang et. al. 2000). Fettig and Sontheimer [1987] investigate the adsorption kinetics of a variety of single substances on activated carbon is investigated a low liquid-phase concentrations. Experimental data they have obtained by the mini column method show the influence of dissociation and molecular weight of the adsorbates o their external mass transfer behavior. Modeling of mini column breakthrough curves proves the internal mass transport resistances have to be taken into account at low concentrations as well as high. A differential fixed-bed reactor technique was used to determine intraparticle mass transport parameters. For strongly adsorbate substances, diffusion in the adsorbend phase proves to be prevailing, whereas for weakly adsorbable or high molecular weight assorbates, pore diffusion also contributes to the internal mass transport. However the surface diffusivities depend on the carbon loading in an adsorbate-specific manner.

Kannan and Sundaram [2001] have been using activated carbon which is come from various indigenously prepared activated carbons from agricultural wastes and to compare their adsorption capacity for the removal of methylene blue under optimum experimental conditions. The effects of various experimental parameters have been investigated using a batch adsorption technique to obtain information on treating effluents from the dye industry.

The kinetics of adsorption were found to be first order with regard to intra-particle diffusion rate. The adsorption capacities of indigenous activated carbons have been compared with that of the commercial activated carbon. The results indicate that such carbons could be employed as low cost alternatives to commercial activated carbon in wastewater treatment for the removal of colour and dyes.

Sakoda, Nomura and Suzuki (1996) used activated carbon membrane which is to be used in water treatments was developed and the decolorization of the coke furnace wastewater was successfully demonstrated as a model case. The activated carbon membrane was prepared by carbonizing poly-vinylydenchloride (PVdC) and poly-vinylalcohol (PVA) microspheres aggregating on and within a ceramic pipe. The membrane developed in this work was suspected to have a bidispersed structure, which made it possible to play the roles of both a porous membrane having the molecular weight cut-off of about 10,000 and an activated carbon bed where the dissolved organics with low molecular weight could be adsorbed. The activated carbon membrane developed in this work appears to be useful for compact water treatment processes.

Mansi(1996) using sawdust as an adsorbent in a fixed bed adsorber for decolorizing wastewater. Fuller’s earth and bauxite were found to be successful as adsorbents for color removal on a laboratory scale, but considerable flow problems were encountered in a fixed bed system. Mc.kay et. al. investigate the removal of basic astrazone blue from effluents using silica gel as an adsorbents. Investigations by Mckay et. al. were made to determine whether cheap, commercially available materials hold promise in the treatment of wastewater. Their initial findings indicated that peat wood has a high adsorptive capacity for dyes and is relatively cheap. The cheapness of the adsorbent means that regeneration is not necessary and the spent adsorber can be burned. The batch adsorption is usually limited to the treatment of small volumes of effluent, whereas a fixed bed flow systems has an advantage because the solute concentration is changing continuously while the solute is being adsorbed.

Hak Lee et. al (2006) have been used zinc chloride treated indigenous activated carbon. The adsorption of colored compounds from the textile dyeing effluents of Bangladesh on granulated activated carbons produced from indigenous vegetable sources by chemical activation with zinc chloride was studied. The most important parameters in chemical activation were found be the chemical ratio of ZnCl2 to feed (3:1), carbonization temperature (450–465 ◦C) and activation time (80 min). It is observed that adsorption of reactive dyes by all sorts of activated carbons is higher than disperse dyes. It is explained that activated carbon, because of its acidic nature, can better adsorb reactive dye particles containing large number of nitrogen sites and –SO3Na group in their structure. The use of carbons would be economical, as saw-dust and water hyacinth are waste products and abundant in Bangladesh.

Granular activated carbon is the most popular adsorbent and has been used with great success (McKay, 1982), but is expensive. Consequently, new materials as chitin (McKay, 1982), silica gel (McKay et al., 1980), natural clay (El-Geundi, 1991, 1993a, b), bagasse pith (McKay, 1998) are being studied. A very limited amount of information is available on the use of natural zeolites as a method for dye removal (Meshko et al., 1999). So Meshko studied the adsorption of basic dyes from aqueous solution onto granular activated carbon and natural zeolite using an agitated batch adsorber S. J. Allen (1999) describes the adsorption capacities for anionic reactive dyes, namely Remazol Yellow, Remazol Red and Remazol Black B were determined using Filtrasorb 400 activated carbon. F-400 was selected because of its high adsorption capacity for a large

number of contaminants in aqueous solutions. Competitive adsorption for reactive dyes in a mixture was investigated to test the efficiency of the activated carbon for purifying real effluent containing dyes. Chemical surface properties for F-400, including surface acidity, surface basicity, H+ and OH- adsorption capacities as well as the zero point of charge of the carbon (pHZPC) were estimated. pHZPC is a critical value for determining quantitatively the net charge (positive or negative) carried on the activated carbon surface during adsorption of reactive dyes.

Ahsan Habib et. at. (2006) have been used tuberose, the low-cost and ecofriendly adsorbent as an ideal alternative to the current expensive methods of removing dyes from wastewater.

Methylene Blue was used as model compound. The effects of contact time, initial dye concentration (20, 30, 40, 50 mg/L), pH and adsorbent dosages have been studied at 25 °C. The equilibrium time was found to be 30 min for all the dye concentrations. A maximum removal of 80% was obtained at pH 11.0 for an adsorbent dose 50 mg/50 mL of 40 mg/L dye concentration. Adsorption increased with increase in pH. Maximum desorption of 50% was achieved in water medium at pH 2.0.

McKay, Blair and Gardner (1983) studied the intraparticle diffusion processes for the adsorption of dyestuffs onto chitin. The amount of dye adsorbed per gram of chitin has been plotted against the square root of time. Sometimes two and even three linear regions are apparent on the root time plots indicating a possible branched pore mechanism. The controlling mechanisms are due to macropores and micropores in the chitin particle creating rapidly and slowly diffusing regions. McKay, Otturburn and Sweeney (1979) have been used Sorbsil silica as an adsorbent and the rate of adsorption of Astrazone Blue, a basic dye, on Sorbsil Silica has been studied.

Yang and Sun using peat–resin particle as a adsorbent for the adsorption of basic dyes from aqueous solution. Peat, as an adsorbent, is porous and rather complex material, containing lignin and cellulose. Recently, peat has been used to remove some pollutants (such as heavy metals, dyes and oil) from aqueous solution [ Coupa et. al.1976, McKay et. al. 1980, Couillard 1921 and Couillard 1994]. Many studies showed peat could effectively remove the dyes from aqueous solution. Peat can effectively remove the pollutants from solution and is inexpensive. However, when raw peat is directly used in wastewater treatment, there are many limitations, such as low chemical stability and mechanical strength, leach of fulvic acid from peat and difficult regeneration. In order to overcome these limitations, they prepared the modified peat–resin particle by mixing modified-peat with polyvinyl alcohol (PVA) and formaldehyde. The modified peat–resin particle contains polar functional groups, such as alcohols and acids. Both modified peat and resin in particle can adsorb the dyes from solution. Finally they analyze the adsorption isotherm and kinetics experiments of basic dyes (Basic Magenta and basic Brilliant Green) were conducted and the different kinetic models were used to analyze adsorption processes of basic dyes on modified peat–resin particle.

2.7 Mass transfer in fluidized bed in case of wastewater treatment Mass transfer in fluidized beds has been studied because of its fundamental importance in many engineering operations. Many experimental studies of the mass transfer in fluidized beds have been reported in the past 40 years (Garim et. at. 1999). Packed bed has disadvantages of low mass-transfer coefficient, large pressure drop, bed clogging, and therefore, periodic operation. It is a semi-batch process with low water treatment capacity.

Fluidized bed partially overcomes these problems. Fluidization of bed increases the mass transfer coefficient and therefore, water treatment capacity. It also partly eliminates bed

clogging. But, it is still a semi batch process and needs periodic operation to replace the saturated adsorbent with fresh adsorbent in the bed (Kishore and Verma 2005).

Wright and Glasser (2000) have developed a model and solved to describe phenol adsorption in a fluidized bed. Liquid-solid mass transfer, adsorption and hydrodynamic effects were taken into account. The model was examined for both pore and homogeneous diffusion.

Parametric sensitivity analysis showed that superficial velocity and particle radius had the largest effects on breakthrough behavior for all conditions. The effect of axial dispersion, film mass transfer and solid diffusion coefficients were less significant contributors to breakthrough at all expansions and bulk phase viscosities. The simulation results for pore diffusion were affected more significantly by changes in superficial velocity and particle radius than the simulation results for homogeneous diffusion. The performance of the fluidized-bed adsorption unit was limited by intraparticle mass-transfer effects, especially at high degrees of bed expansion.

Kishore and Verma (2005) developed a counter current multi-stage fluidized bed ion exchanger to study mass transfer during the continuous removal of dissolved anions from wastewater using commercially available resin. OH ion is used as an example in the study. A higher removal efficiency in the multi-stage fluidized bed than in a single-stage fixed and fluidized bed is demonstrated. The experiment shows progressive fluidization on a stage, smooth flow of resin across the stage and transfer of resin from one stage to the other. In each stage of the fabricated four-stage perspex made column, a downspout has been provided to facilitate the downward flow of resin on to the next stage, while water flows counter currently upward through the mesh of the stage. In addition, provision has been made to adjust the down comer height on the stage without disturbing the operation with the aid of the rack and pinion arrangement. The experimental variables in the multi-stage column operated under steady state includes the flow rates of water and resin, feed concentration, stage height and the number of stages. A mathematical model is also developed for determining the key parameters that affect the overall mass transfer in the multi-stage continuous counter current column. In general, number of stages and diffusional resistance on the resin side control the extent of separation in the column Mckay, G. et. al (1989) have investigated the external mass transfer during adsorption of various pollutants onto activated carbon. He explores a wide range of experimental studies which are reported for the adsorption of phenol and p-chlorophenol onto activated carbon-Type Filtrasorb 400--in an agitated batch adsorber. A model has been used to determine the external mass transfer coefficient for the systems and the effects of several experimental variables have been investigated: these include agitation, initial pollutant concentration, carbon mass, carbon particle size and solution temperature. The mass transfer coefficient has been correlated in terms of the dimensionless Sh/Sc0.33 against each variable. The Sherwood number relates the external mass transfer coefficient k/ to particle radius, R, and molecular diffusivity. The Schmidt number, Sc, is the ratio of kinematic viscosity, v, to molecular diffusivity. A few results are also reported for the adsorption of sodium dodecyl sulphate and mercuric ions onto activated carbon.

According to Mc.kay et. al (1989) several steps can be used to explain the mechanism of solute adsorption onto an adsorbent. However, for the purposes of the present work the overall adsorption process is assumed to occur using a three step model: (i) Mass transfer of solute from the bulk solution to the particle surface; (ii) Adsorption of solute onto sites;

(iii) Internal diffusion of solute via either a pore diffusion model or a homogeneous solid phase diffusion model.

Throughout the present work it has been assumed that step (ii) is rapid with respect to the other two processes and therefore is not rate limiting in any kinetic analysis. Consequently, the two controlling factors are film mass transfer and internal mass transfer. The development of models based on two such mass transport steps is quite complex, requiring a coupling equation and its subsequent solution. Initially, therefore simplifying assumptions were made and attempts to describe the adsorption processes in terms of either a film mass transfer coefficient of an internal diffusion mass transfer parameter have been undertaken. That’s why Mckay, Bino and Altamemi (1989) determined a single resistance model which has been developed enabling the external mass transfer coefficient.

Mckay, Blair and Gardener (1984) have developed Two-Resistance Mass Transfer Model for the Adsorption of Various Dyestuffs onto Chitin. The mass transfer model is based on the assumption of a pseudoirreversible isotherm and two resistances to mass transfer. These are external mass transfer and internal pore diffusion mass transfer. The rate of adsorption of dyestuffs onto chitin can thus be described by an external mass transfer coefficient and a pore diffusion coefficient.

In 1988 McKay, Geundi, and Wahab described two resistance mass transfer model for describing the adsorption of four dyes from aqueous solutions onto bagasse pith, a waste product from the sugar industry. The dyes studied are Basic Blue 69, Basic Red 22, Acid Blue 25 and Acid Red 114 and the system variables are initial dye concentration and pith mass. A method has been presented for the prediction of concentration decay vs time. The model is based on external mass transfer and pore diffusion and enables the external transport coefficients and the effective diffusivities to be determined. Constant mass transport coefficients were obtained for each dye-pith system to correlate the effects of varying the initial dye concentration and pith mass.

2.8 Adsorption isotherms The distribution of dye between the adsorbent and dye solution, when the system is at equilibrium, is important to obtain the capacity of the granular activated carbon for the dyes.

A number of equations exist which enable the equilibrium data to be correlated and two most frequently used, for dilute solutions, are the Langmuir and Freundlich isotherms equations which will discussed here. The parameters of these equations are very useful for predicting adsorption capacities and also for incorporating into mass transfer relationships in the design of contacting equipment.

These two equations are used more than 99% of the time to describe the equilibrium adsorption of solutes to activated carbon. The reason is simple: in almost every case, one of these two equations fits the data quite well. Thus, there is no need for more elaborate isotherm equations, particularly those involving two or more parameteres.

2.8.1 Adsorption Adsorption is the accumulation of atoms or molecules on the surface of a material. This process creates a film of the adsorbate (the molecules or atoms being accumulated) on the adsorbent's surface. It is different from absorption, in which a substance diffuses into a liquid or solid to form a solution. The term sorption encompasses both processes, while desorption is the reverse process.

Adsorption is present in many natural physical, biological, and chemical systems, and is widely used in industrial applications such as activated charcoal, synthetic resins, and water purification. Adsorption, ion exchange, and chromatography are sorption processes in which certain adsorbates are selectively transferred from the fluid phase to the surface of insoluble, rigid particles suspended in a vessel or packed in a column.

Similar to surface tension, adsorption is a consequence of surface energy. In a bulk material, all the bonding requirements (be they ionic, covalent, or metallic) of the constituent atoms of the material are filled by other atoms in the material. However, atoms on the surface of the adsorbent are not wholly surrounded by other adsorbent atoms and therefore can attract adsorbates. The exact nature of the bonding depends on the details of the species involved, but the adsorption process is generally classified as physisorption (characteristic of weak van der Waals forces) or chemisorption (characteristic of covalent bonding).

2.8.2 Isotherm Adsorption is usually described through isotherms, that is, the amount of adsorbate on the adsorbent as a function of its pressure (if gas) or concentration (if liquid) at constant temperature. The quantity adsorbed is nearly always normalized by the mass of the adsorbent to allow comparison of different materials.

The first mathematical fit to an isotherm was published by Freundlich and Küster (1894) and is a purely empirical formula for gaseous adsorbates, n

q * → ΑΡ* ……….(1)

where q* is the quantity adsorbed per unit weight of the adsorbent, P* is the pressure of adsorbate and A and n are empirical constants for each adsorbent-adsorbate pair at a given temperature. The function has an asymptotic maximum as pressure increases without bound.

As the temperature increases, the constants A and n change to reflect the empirical observation that the quantity adsorbed rises more slowly and higher pressures are required to saturate the surface.

2.8.2.1 Freundlich equation The Freundlich equation or Freundlich adsorption isotherm is an adsorption isotherm, which is a curve relating the concentration of a solute on the surface of an adsorbent, to the concentration of the solute in the liquid with which it is in contact. There are basically two well established types of adsorption isotherm: the Freundlich adsorption isotherm and the Langmuir adsorption isotherm The Freündlich Adsorption Isotherm is mathematically expressed as q * → ΑΡn ………. (1)

or q * → ΑC n ………. (2)

where p = Equilibrium pressure of adsorbate C = Equilibrium concentration of adsorbate in solution.

A and n are constants for a given adsorbate and adsorbent at a particular temperature

2.8.2.2 Langmuir equation The Langmuir equation or Langmuir isotherm or Langmuir adsorption equation relates the coverage or adsorption of molecules on a solid surface to gas pressure or concentration of a medium above the solid surface at a fixed temperature. The equation was developed by Irving Langmuir in 1916. The equation is stated as: α.Ρ θ= 1 + σ.Ρ ……….. (3) θ or theta is the fractional coverage of the surface, P is the gas pressure or concentration, α alpha is a constant.

The constant α is the Langmuir adsorption constant and increases with an increase in the binding energy of adsorption and with a decrease in temperature.

Equation Derivation The equation is derived starting from the equilibrium between empty surface sites (S * ), particles (P) and filled particle sites (SP) S * + Ρ ↔ SΡ ………….(4)

The Equilibrium constant K is thus given by the equation:

K=

[ S Ρ] [[S * ][ Ρ]]

………... (5)

Because the number of filled surface sites (SP) is proportional to θ, the number of unfilled sites (S *) is proportional to 1-θ, and the number of particles is proportional to the gas pressure or concentration (P) the equation can be rewritten as: α=

θ

[1 − θ ] Ρ* …….. (6)

where α is a constant Rearranging this: θ = α(1 − θ)P θ = Pα − Pθα θ + Pθα = Pα θ(1 + Pα) = Pα θ=

α.Ρ ……….. (7) 1 + σ.Ρ

[Equation Fitting The Langmuir equation is expressed here as:

Κc …………….(8) 1+ Κc

φ = φmax

where K = Langmuir equilibrium constant, C* = aqueous concentration (or gaseous partial pressure), φ = amount adsorbed, and φmax = maximum amount adsorbed as c increases.

The equilibrium constant is actually given by φmax :

φ (c = Κ

−1

)

φ ΚΚ −1 = φ max = max …………..(9) −1 2 1 + ΚΚ

The Langmuir equation can be fitted to data by linear regression and nonlinear regression methods. Commonly used linear regression methods are: Lineweaver-Burk, Eadie-Hofstee, Scatchard, and Langmuir.

The double reciprocal of the Langmuir equation yields the Lineweaver-Burk equation: 1

φ

=

1

φmax

+

1 …………(10) φmax Κc

A plot of (1/ φ) versus (1/c) yields a slope = 1/( φmax K) and an intercept = 1/ φmax . The Lineweaver-Burk regression is very sensitive to data error and it is strongly biased toward fitting the data in the low concentration range. It was proposed in 1934. Another common linear form of the Langmuir equation is the Eadie-Hofstee equation: φ φ = φmax − …………….(11) Κc

A plot of ( φ) versus ( φ/c) yields a slope = -1/K and an intercept = φmax . The EadieHofstee regression has some bias toward fitting the data in the low concentration range. It was proposed in 1942 and 1952. Another rearrangement yields the Scatchard regression: φ = Κφmax − Κφ ……….(12) c

A plot of ( φ/c) versus ( φ) yields a slope = -K and an intercept = K φmax . The Scatchard regression is biased toward fitting the data in the high concentration range. It was proposed in 1949. Note that if you invert the x and y axes, then this regression would convert into the Eadie-Hofstee regression discussed earlier. The last linear regression commonly used is the Langmuir linear regression proposed by Langmuir himself in 1918: c

φ

=

c

φmax

+

1 Κφmax

………….(13)

A plot of (c/ φ) versus (c) yields a slope = 1/ φmax and an intercept = 1/(K φmax ). This regression is often erroneously called the Hanes-Woolf regression. The Hanes-Woolf regression was proposed in 1932 and 1957 for fitting the Michaelis-Menten equation, which is similar in form to the Langmuir equation. Nevertheless, Langmuir proposed this linear regression technique in 1918, and it should be referred to as the Langmuir linear regression when applied to adsorption isotherms. The Langmuir regression has very little sensitivity to data error. It has some bias toward fitting the data in the middle and high concentration range.

There are two kinds of nonlinear least squares (NLLS) regression techniques that can be used to fit the Langmuir equation to a data set. They differ only on how the goodness-of-fit is defined. In the v-NLLS regression method, the best goodness-of-fit is defined as the curve with the smallest vertical error between the fitted curve and the data. In the n-NLLS regression method, the best goodness-of-fit is defined as the curve with the smallest normal error between the fitted curve and the data. Using the vertical error is the most common form of NLLS regression criteria. Definitions based on the normal error are less common. The normal error is the error of the datum point to the nearest point on the fitted curve. It is called the normal error because the trajectory is normal (that is, perpendicular) to the curve.

It is a common misconception to think that NLLS regression methods are free of bias.

However, it is important to note that the v-NLLS regression method is biased toward the data in the low concentration range. This is because the Langmuir equation has a sharp rise at low concentration values, which results in a large vertical error if the regression does not fit this region of the graph well. Conversely, the n-NLLS regression method does not have any significant bias toward any region of the adsorption isotherm.

Whereas linear regressions are relatively easy to pursue with simple programs, such as excel or hand-held calculators, the nonlinear regressions are much more difficult to solve. The NLLS regressions are best pursued with any of various computer programs.

2.9 Fluidized Bed A fluidized bed is formed when a quantity of a solid particulate substance (usually present in a holding vessel) is placed under appropriate conditions to cause the solid/fluid mixture to behave as a fluid. This is usually achieved by the introduction of pressurized fluid through the particulate medium. This results in the medium then having many properties and characteristics of normal fluids; such as the ability to free-flow under gravity, or to be pumped using fluid type technologies.

The resulting phenomenon is called fluidization. Fluidized beds are used for several purposes, such as fluidized bed reactors (types of chemical reactors), fluid catalytic cracking, fluidized bed combustion, heat or mass transfer or interface modification, such as applying a coating onto solid items.

2.9.1 Properties of fluidized beds A fluidized bed consists of fluid-solid mixture that exhibits fluid-like properties. As such, the upper surface of the bed is relatively horizontal, which is analogous to hydrostatic behavior.

The bed can be considered to be an inhomogeneous mixture of fluid and solid that can be represented by a single bulk density.

Furthermore, an object with a higher density than the bed will sink, whereas an object with a lower density than the bed will float, thus the bed can be considered to exhibit the fluid behavior expected of Archimedes' principle. As the "density", (actually the solid volume fraction of the suspension), of the bed can be altered by changing the fluid fraction, objects with different densities comparative to the bed can, by altering either the fluid or solid fraction, be caused to sink or float.

In fluidized beds, the contact of the solid particles with the fluidization medium (a gas or a liquid) is greatly enhanced when compared to packed beds. This behavior in fluidized combustion beds enables good thermal transport inside the system and good heat transfer between the bed and its container. Similarly to the good heat transfer, which enables thermal uniformity analogous to that of a well mixed gas, the bed can have a significant heat-capacity whilst maintaining a homogeneous temperature field

2.9.2 Application Fluidized beds are used as a technical process which has the ability to promote high levels of contact between gases and solids. In a fluidized bed a characteristic set of basic properties can be utilised, indispensable to modern process and chemical engineering, these properties include:  Extremely high surface area contact between fluid and solid per unit bed volume  High relative velocities between the fluid and the dispersed solid phase.  High levels of intermixing of the particulate phase.  Frequent particle-particle and particle-wall collisions 2.9.3 Fluidization Fluidization is defined as an operation through which fine solids are transformed into a fluid like state through contact with either a gas or a liquid.

2.9.3.1 The Phenomenon of Fluidization When a fluid is pumped upward through a bed of fine solid particles at a very low flow rate the fluid percolates through the void spaces (pores) without disturbing the bed. This is a fixed bed process.

If the upward flow rate is very large the bed mobilizes pneumatically and may be swept out of the process vessel. At an intermediate flow rate the bed expands and is in what we call an expanded state. In the fixed bed the particles are in direct contact with each other, supporting each other’s weight. In the expanded bed the particles have a mean free distance between particles and the particles are supported by the drag force of the fluid. The expanded bed has some of the properties of a fluid and is also called a fluidized bed.

First, we consider the behavior of a bed of particles when the upward superficial fluid velocity is gradually increased from zero past the point of fluidization, and back down to zero.

At first, when there is no flow, the pressure drop zero, and the bed has a certain height. As we proceed along the right arrow in the direction of increasing superficial velocity, tracing the path ABCD, at first, the pressure drop gradually increases while the bed height remains fixed.

This is a region where the Ergun equation for a packed bed can be used to relate the pressure drop to the velocity. When the point B is reached, the bed starts expanding in height while the pressure drop levels off and no longer increases as the superficial velocity is increased. This is when the upward force exerted by the fluid on the particles is sufficient to balance the net weight of the bed and the particles begin to separate from each other and float in the fluid. As the velocity is increased further, the bed continues to expand in height, but the pressure drop stays constant. It is possible to reach large superficial velocities without having the particles carried out with the fluid at the exit. This is because the settling velocities of the particles are typically much larger than the largest superficial velocities used.

Fig 1: Typical curves for a liquid-solid fluidized bed of particles of approximately uniform size.

Now, if we trace our path backward, gradually decreasing the superficial velocity, in the direction of the reverse arrows in the figure, we find that the behavior of the bed follows the curves DCE. At first, the pressure drop stays fixed while the bed settles back down, and then begins to decrease when the point C is reached. The bed height no longer decreases while the pressure drop follows the curve CEO. A bed of particles, left alone for a sufficient length of time, becomes consolidated, but it is loosened when it is fluidized. After fluidization, it settles back into a more loosely packed state; this is why the constant bed height on the return loop is larger than the bed height in the initial state. If we now repeat the experiment by increasing the superficial velocity from zero, we’ll follow the set of curves ECD in both directions.

Because of this reason, we define the velocity at the point C in the figure as the minimum fluidization velocity.

2.9.3.2 Calculation of fludization velocity the pressure drop over the fluidized bed is:

∆Ρ = ( ρ s − ρ f )(1 − ε ) Ηg …………….(14)

if the bed expand, the product (1- ε) will remain constant. Using the values of each term appropriate to the condition of incipient fluidization: ∆Ρ = ( ρ s − ρ f )(1 − ε mf )Η mf g ………….(15)

For fine particles the pressure drop velocity relationship can be found from Carman-Kozeny equation:

U mf =

ε mf

3

5(1 − ε mf

)

2

∆Ρ 1 …………….(16) S 2 µ Η mf

Hence from equation (14) and (15):

U mf =

ε mf 3

5(1 − ε mf

)

(ρ

s

− ρ f )g

S 2µ

…..………..(17)

For uniform spherical particles, S = 6/d and taking εmf = 0.4 U mf = 0.00059

d2 g ( ρ s − ρ f ) µ …………….(18)

2.9.3.3 Expansion of a particulately fluidized bed When the superficial velocity of the fluidizing fluid is greater than the incipient velocity i.e. minimum fluidization velocity, the bed expands uniformly to take up the increased flow, the particles spacing themselves out so that the drag on each is equal to the net weight allowing for buoyance. Various authors have measured the expansion of bed. But the most convenient way of showing the variation of sedimentation velocity, or fluidizing velocity, with voidages is by means of correlating the Umf / Ut and ε, because when ε →1, U mf / Ut →1, since ε = 1 we have a single particle in an infinite fluid. According to the Richardson and Zaki the equation is on the basis of fluidization and sedimentation experiments: U mf Ui

= ε n …………………… (19)

Ui is the free falling velocity but it is slightly influenced by the ratio of the diameters of the particle and column (

d ) D

Therefore, for fluidization log U i = log U t −

d …………(20) D

And for index n is given by n = 4.65 +

d D

d   n =  4.4 + 18 ×  Re −0.03 D 

(Re < 0.2) (

0.2< Re < 1)

……. (21)

d   n =  4.4 + 18 ×  Re −0.1 D 

n = 4.4 Re

−0.1

n = 2.4

(1< Re < 200) (200 < Re < 500) (Re > 500)

2.10 Adsorbent: Granular Activated Carbon Activated carbon has long been recognized as one of the most versatile adsorbents for the effective removal of low concentrations of certain substances from solution. Activated carbon has the strongest physical adsorption forces or the highest volume of adsorbing porosity of any material known to mankind. Granular activated carbon is used in different types of water treatment systems to remove chlorine, turbidity, dissolved organics, odor, taste, color, and synthetic organic contaminants from water supplies. The high adsorptive capacity of activated carbon, the main reason for its widespread utilization, is attributed mainly to its highly porous structure, resulting in a relatively large surface area of up to 1500 m2/g 2.10.1 Total surface area Total surface area of activated carbon is primary indicators of its activity level as the greater the surface area, the higher the adsorptive site available. Surface area has been determined by nitrogen gas adsorption process (BET method).

2.10.2 Iodine Number (I.D) Many carbons preferentially adsorb small molecules. Iodine number is the most fundamental parameter used to characterize activated carbon performance. It is a measure of activity level (higher number indicates higher degree of activation), often reported in mg/g (typical range 500-1200 mg/g). It is a measure of the micropore content of the activated carbon (0 to 20 Å, or up to 2 nm) by adsorption of iodine from solution. It is equivalent to surface area of activated carbon between 900 m²/g and 1100 m²/g. It is the standard measure for liquid phase applications.

2.10.3 Methylene blue (M.B) Some carbons have a mesopore structure which adsorbs medium size molecules, such as the dye Methylene Blue. Methylene Blue adsorption is reported in g/100g (range 11-28 g/100g).

2.10.4 Ash content It reduces the overall activity of activated carbon. It reduces the efficiency of reactivation.

The metals (Fe2O3) can leach out of activated carbon resulting in discoloration. Acid/water soluble ash content is more significant than total ash content.

2.10.5 Apparent density Higher density provides greater volume activity and normally indicates better quality activated carbon.

2.10.6 Hardness/abrasion number It is a measure of the activated carbonâ&#x20AC;&#x2122;s resistance to attrition. It is important indicator of activated carbon to maintain its physical integrity and withstand frictional forces imposed by backwashing, etc. There are large differences in the hardness of activated carbons, depending on the raw material and activity level.

2.10.7 Particle size distribution The finer the particle sizes of an activated carbon, the better the access to the surface area and the faster the rate of adsorption kinetics. In vapor phase systems this needs to be considered against pressure drop, which will affect energy cost. Careful consideration of particle size distribution can provide significant operating benefits.

Chapter 3 Theoretical Development The mass transfer in the fluidized bed is characterized by the breakthrough curve, which is the response of an initially fresh bed to an influent containing the solute. The shape of the breakthrough curve depends upon the type of equilibrium isotherm, which in turn is the characteristic of the solute and adsorbent system. In addition, the breakthrough response is influenced by the different transport processes occurring in the bed and within the adsorbent particles.

The following assumptions are made in present analysis: a. Perfect mixing of solids occurs and so q does not change with position but is a function of time; b. The adsorption isotherm corresponds to a Freundlich isotherm.

CL

C (l) L

dl

F Co

Fig 2 Material balance relation for column

The mass balance over the whole fluidized bed is M

dq = F( C0 − C L ) dt

… … … … (22)

Here M is mass of adsorbent, F is the flow rate of liquid feed, C 0 is the initial feed concentration and CL is the concentration of liquid at the bed exit.

The boundary conditions for the above equation are At t = 0, CL = C0, q = 0 The mass transfer processes that are considered here in representing single-component adsorption are (1) film diffusion from the fluid phase to the surface of the particle; (2) adsorption on the surface; (3) pore diffusion in liquid-filled pores on to the particle surface.

The average mass flux in the bed across the phases is given by

(

)

N = KF C − C* =

F (C 0 − C L ) ………………….. (23) a

Here, KF is the overall mass transfer coefficient and a is the interfacial area available for mass transfer; C is the average solute concentration in liquid within the bed and is given by l

C=

∫ C (l )dl ; C* is the solute concentration of liquid in equilibrium with the solid phase 0

L and can be estimated from Freundlich isotherm as n

q C * =   ……………..(24)  A

Here C(l) is the liquid concentration along the bed at any moment of time. In absence of C(l) data along the bed length the average concentration within the bed is approximated as C≅

C0 + C L 2

……………………(25)

The overall mass transfer coefficient KF depends on the individual fluid phase and solid phase mass transfer coefficients and can be expressed as 1 1 1 = + KF kf mk s ……………(26)

Where m is the slope of equilibrium curve and can be obtained by rearranging the Freundlich equilibrium isotherm. kf and ks are fluid phase and solid phase mass transfer coefficients, respectively. The parameter kf depends on the Sherwood number which is defined as the ratio of the molecular mass transfer resistance to the convective mass transfer resistance in the fluid. The particle diameter is considered to be the most significant length in the mass transfer operation. The Sherwood number can be expressed by the following equation

kf dp

Sh =

De

… … 

A number of correlations are reported in terms of Sherwood number to estimate kf which are usually in the form of Sh = p ( Re ) ( Sc) x …………(28) q

Here p, q and r are empirical values and d p and De are particle diameter and effective diffusivity of the solute in the adsorbent, respectively.

Reynolds number and Schmidt number are defined by the following equations: ρUd p ……… (29) µ µ Sc = ……….. (30) ρDe Re =

The internal or solid phase mass transfer coefficient is commonly expressed in terms of particle diameter and effective diffusivity. ks ≅

10 De …….(31) dp

Equations 22-31 are applicable for both fixed bed and fluidized bed adsorption. In fluidized bed the adsorption particles go into suspension and hence a larger surface area will be exposed to the solution. This will increase the mass transfer rate.

Furthermore, the increased fluid velocity will increase the turbulence of the system. As seen from equations (24) – (31), an increase in turbulence results in an increase in the Reynolds number, which in turn increases the Sherwood number. The Sherwood number is directly proportional to the mass transfer coefficient and therefore an increase in the Sherwood number will increase the mass transfer coefficient and the overall mass transfer rate.

Chapter 4 Experimental 4.1 Experimental setup A set of experiments was undertaken to obtain the breakthrough curve and compare different operating conditions. The experimental layout is shown in Figure 3.

Fig 3. Equipment Layout

Fluid Outlet 1"

Sample outlet 5 cm Adsorption Bed 61 cm

1" Activated Carbon

8 cm

Fluid Inlet

Fig 4: Detailed of the fluidized bed The storage tank was used to keep the liquid at a constant initial calculated concentration.

The pump supplied a constant flow to the rotameter and the adsorption bed. This flow was controlled by the rotameter which was calibrated before use to determine the flow rate. The calibration curve can be found in Appendix (A).

The rotameter measured the flow rate, Q. Using the continuity equation: Q = VA and the cross sectional area of the fluidized bed, the velocity of the water was determined. Figure 3 shows a detailed layout of the adsorption bed. A glass made cylinder of 5 cm diameter and 61 cm height was used as the fluidization column. A dye solution of known concentration was made in 60 dm3 capacity plastic storage tank. This solution was then pumped by a 1 hp pump through the activated carbon bed via a rotameter. The flow rate through the fluidized bed was kept constant by adjusting the valve of the bypass line and the manually controlled valve of the main flow path. Samples were collected at a definite time interval from the exit point and exit solution was stored and then drained out from the tank. The storage tank was then washed to set up for a new run.

The minimum fluidization velocity of the bed, Umf, has been determined via the classic plot of bed height (H) versus superficial velocity (U) for decreasing flow rates of water. As was mentioned earlier, the change in exit concentration occurs rapidly in the beginning and then slows down (the breakthrough curve). In order to capture the initial concentration changes,

samples were taken more frequently (every minute) for the first six minutes and less frequently afterwards (every two or five minutes). The parameter altered were the liquid flow rate, particle size of the activated carbon and inlet concentration of the solution. The concentration of the outlet solution was determined by a single cell, Shimadzu UV-1201 V spectrophotometer.

4.2 Adsorbents: Properties of Activated Carbon The activated carbon was collected from Graphics Textiles Ltd. Sreerampur, Dhamrai, Savar, Dhaka, Bangladesh. The carbon is of irregular granular form and made from bituminous coal.

It was then grinded and screened to get the desired particle size. The specifications i.e Iodine value, Mithylene Blue, Ash content and Moisture content were supplied. Total surface area and pore volume of the carbon was determined in the laboratory.

Some properties of adsorbents are listed in table 1: Table 1: Properties of Activated Carbon (Granular form) Total surface area, av (N2, BET method) Pore volume I.D M.B Ash content

273.80 m2/g 0.2198 m3/g 950 min 150% min 180% max 20% max

Moisture content

17.85 % max

4.3 Adsorbates 4.3.1 Colored Water The experiment was carried out with colored solution of reaction black dye (reactive dye).

This dye is commonly used in textile industries as fabric color for cotton, wool and silk.

Three concentrations of colored solutions were prepared 29.45 ppm, 23 ppm and 18.45 ppm.

Most of the experiment was carried out at 23 ppm and 18.45 ppm. The reactive black dye has been supplied by â&#x20AC;&#x153;Dyesin Chemicalsâ&#x20AC;? located at Bijoynagar, Dhaka, Bangladesh.

The molecular structure of the reactive black dye used in sample solution is given below:

Fig 5: Structure of reactive black dye (Vinyl Sulfone Fiber Reactive Dye) Fig. 4.3.2 Industrial Effluent The experiment was also carried out with industrial effluent. The effluent (wastewater) was collected after the secondary stage effluent treatment section of Graphics Textiles Ltd. Sreerampur, Dhamrai, Savar, Dhaka, Bangladesh. Following parameters of the wastewater were measured before the experiment was done Table 2: Measurement parameters of the wastewater collected from Graphics Textiles Ltd. Parameter

Unit

Raw effluent, pH

Concentration 5.97

Raw effluent temperature

0

C

37

DO

ppm

2.30

Raw effluent BOD

ppm

210.6

Raw effluent COD

ppm

125.87

Total Dissolved Solids

ppm

1990

Total Suspended solids

mg/L

650.2

Turbidity

FAU

81

Color

pt-co

520 over

Conductivity

ms/cm

3.78

Sulphide (S-2)

mg/L

228

Chlorine (Cl2)

mg/L

0.36

NH3-N

mg/L

2.900 over

4.4 Equilibrium isotherms

Adsorption isotherm is established with various initial concentration (10-200 ppm) of dye solution (250 ml) by using a definite amount of activated carbon (5 gm) for different particle sizes. Solutions had been kept for twenty nine days at room temperature to ensure the establishment of equilibrium.

4.5 Analysis The concentration of dye of colored solutions was measured with Shimadzu UV-1201 V spectrophotometer at a wavelength 500nm. For industrial wastewater the calibration of the black reactive dye was used to approximate the total concentration of a number of unknown dyes present in the effluent.

Chapter 5 Results and Discussions 5.1 Isotherm The distribution of dye between the adsorbent and dye solution, at equilibrium, is important to determine the capacity of the granular activated carbon. An adsorption isotherm was generated with three different particle sizes of granular activated carbon as shown in fig. 6.

The figure shows that the isotherm rises rapidly initially and flattens at higher equilibrium concentration. The results also indicate that there is no significant effect of particle size on the equilibrium capacities A number of equations exist which enable the equilibrium data to be correlated and two most frequently used, for dilute solutions, are the Langmuir and Freundlich isotherms but in this experiment adsorption equilibrium were described with the Freundlich isotherm (equ.2).

The parameters in these equations are very useful for predicting adsorption capacities and also for incorporating into mass transfer relationships in the design of contacting equipment.

Fig 6 : Adsorbtion isotherm for dye solution for different sizes of activated carbon The parameters in the adsorption isotherms were estimated from the experimental equilibrium data. The parameters of the Freundlich model are represents as A = 14.779 (mg g1 (mg dm3)-1/n), n = 0.9477 and R2 = 0.99.

5.2 Fluidized Bed Characteristics The fig. 7 is the bed height (H) versus superficial velocity, (U) for decreasing flow rates of water. According to established convention, minimum fluidization velocity is defined by the intercept of the horizontal line representing the fixed bed height for a bed that has just been defluidized and the extension of the inclined line corresponding to the fall in fluidized bed height for decreasing flow rates.

Fig.7: Bed height of the fluidized bed at different velocity For three particle size Umf and U are calculated by using the equation (17) to (20)

The experimental minimum fluidization velocity (U mf) and velocity at maximum bed height can be read directly from fig.7.

Table 3: Fluidized bed properties Particle size (mm) 0.84 mm - 0.71 mm 1 mm - 0.84 mm 1.3 mm - 1.15 mm 1 mm (Theoretical)

Minimum fluidization velocity (m/s) 0.01699 0.01698 0.0194 0.0112

Velocity at Maximum bed height (m/s) 0.0724 0.0726 0.0725 0.0725

Adsorption tests with the fluidized bed were carried out using three arbitrarily selected fluidizing velocities. In practice the fluidizing velocity is chosen to expand the bed to a large enough extent to avoid bed clogging. Both concentration and particle size distribution of the incoming suspended solids affect this choice.

5.3 Breakthrough Curves 5.3.1 Effect of Liquid Velocity Figure 8 shows the effect that changing velocity on the concentration of treated solution. It can be seen that the increase in velocity lowers the slope of the breakthrough curve leading to better initial dye removal and longer saturation time. The slope of the breakthrough curve is highest for 0.0254 m/s and lowest for 0.034 m/s, thus the performance of the fluidized bed was found highest for liquid velocity 0.034 m/s. However, increasing velocity further may or may not improve the color removal capacity of the fluidized bed since it reduces the residence time of the fluid in the bed which affects the mass transfer rate adversely.

Fig 8: Effect of velocity change on the concentration of treated solution 5.3.2 Effect of Adsorbent Particle Size The effect of particle diameter on the concentration of the treated solution at constant velocity is shown in Figure 9. It is observed that a reduction in particle size the range 1.3-1.15 mm to 1-0.84 mm gives a better removal of dye and a prolonged adsorption of material. For smaller particle adsorption is better as exposed surface area to the solution is more for same amount of carbon and also it takes longer time to get exhausted. For comparatively larger sizes (1 -0.84 mm and 1.3-1.15 mm) the effect of size reduction is less prominent.

Fig 9: Effect of particle size on the concentration of treated solution 5.3.3 Effect of Liquid Inlet Concentration Figure 10 shows the effect of the feed solution on colored removal. The initial concentrations used for the feed solutions were 29.45 ppm, 23 ppm and 18.45 ppm. For higher initial concentration decrease in concentration of the treated water is less significance than that for the lower initial concentration.

Fig 10: Effect of Initial Concentration treated solution This would be expected as an increase in concentration means there is more material to be adsorbed. Since the amount of carbon and the velocity were constant for this experiment, the particles would adsorb the same amount of dye before becoming saturated. Thus the experiments were higher concentration reaches saturation before the lower one, as shown in Figure 10.

5.4 Mass Transfer Analysis 5.4.1 Estimation of overall mass transfer co-efficient, KF By rearranging equation (23) following expression for KF is obtained. a  C − CL  ΚF =  o  …………….. (32) F  C − C*  a = av × M

F and Co are known. The data of CL vs. t are obtained from the breakthrough curves. C* is obtained from Freundlich Isotherm equn(2) once the q values for different time are calculated.

By integrating equation (22) we get q

q = ∫ dq = 0

F M

t

∫ (C

o

− C L )dt ……..(33)

0

Here Co is constant for a particular run and CL varies with time.

Thus by putting in all the values in equation (32) KF for each run are calculated.

5.4.2 Overall mass transfer coefficient at different velocities and particle size Fig. 11-14 presents the overall mass transfer coefficient for different velocities and particle size with respect to time and q (mg of dye solution per gm of activated carbon).

As expected from the breakthrough curves K F increases with increasing liquid velocity and decreasing particle size.

This can be explained by the equations (26)-(31). K F is a function of kf , ks and slope of the isotherm m. kf is a function of liquid velocity and particle size wheras ks is a function of particle size only.

For fixed flow rate and particle size KF decreases with time and q.

Fig 11: Overall mass transfer coefficient at fluid phase vs. amount adsrobed for various velocities of dye solutions

Fig 12: Overall mass transfer coefficient at fluid phase vs. time for various velocities of dye solutions From fig. 11 and 12, it is observed that increased in fluid velocity will increase the turbulence of the system. As seen from equations (24) â&#x20AC;&#x201C; (31), an increase in turbulence results in an increase in the Reynolds number, which in turn increases the Sherwood number. The Sherwood number is directly proportional to the mass transfer coefficient and therefore an increase in the Sherwood number will increase the mass transfer coefficient and the overall mass transfer rate

Fig 13: Overall mass transfer coefficient at fluid phase vs. amount adsrobed for various particle size changes

Fig 14: Overall mass transfer coefficient at fluid phase vs. time for various particle sizes It is observed from fig.13 and 14 that increasing mean particle diameter results in an increase in the overall mass transfer coefficient. The fact is, for small particles a large external surface

area is presented to the adsorbate molecules, which result in a lower driving force per unit surface area for mass transfer than when larger particles are used. Since C is constant and the mass of carbon is constant, the external particle area increases as particle size decrease.

If velocity and particle size remain fixed KF depends only on m. As time passes, the average concentration of the colored water as well as the amount of adsorbed solute in the bed increases and corresponding m decreases. Consequently from (equ n 26) overall mass transfer coefficient KF decreases.

5.5 Sample run with industrial wastewater treatment Fig 15 and 16 present the breakthrough curves for industrial wastewater collected after secondary treatment. The curves show similar trend of dye removal to those obtained for the prepared solution of black dye, i.e. the dye removal performance improves with increasing effluent velocity and decreasing particle size of the activated carbon.

Effect of Velocity change (Particle size: 1 mm - 0.84 mm, amount of activated carbon 100 gm) 27

Initial Concentration: 26.45455 ppm

Concentration (ppm)

25

23

21 0.034 m /s 0.0254 m/s 0.017 m /s 19 0

9

18 Tim e (m in)

Fig 15: Effect of velocity change on concentration of exit solution

27

Effect of paticle size (velocity- 0.0254 m/ s, Amount of activated carbon- 100 g)

27

Initical concentration: 26.45455 ppm

26

Concentration, ppm

25 24 23 22 21 20

0.84 m m - 0.71 m m 1m m - 0.84 m m

19

1.3 m m -1.5 m m

18 0

5

10

15

Time, min

20

25

30

Fig 16: Effect of change of particle size on concentration of exit solution Different parameters such as color, turbidity, total suspended solids (TSS) and Total dissolved solids (TDS), BOD; COD etc of the wastewater after the adsorption treatment were measured in the laboratory and are presented in table 4. All the parameters after treatment were found to be within the acceptable limit.

Table 4: Measurement parameters of the treated water collected from Graphics Textiles Ltd.

Parameter

Temp.

Units

0

C

pH

0.84-0.71 mm

1-0.84 mm

1.3-1.15 mm

29.5

28.5

29.5

7.97

8.07

Place of Discharge Subsoil Water

Sewerage Irrigation Canal Land

8.00

6~9

6~9

6~9

DO

ppm

4.5

4.5

4.5

4.5~8

4.5~8

4.5~8

COD

ppm

125.57

125.87

125.87

200

400

400

Total Suspended ppm Solids Total Dissolve ppm Solids (TDS) BOD ppm

142.8

149.4

149.4

150

500

200

1620

1580

1310

2100

2100

2100

17

19

20

50

250

100

Turbidity

FAU

104

94

68

Color

Pt.-Co 520 over

380

397

400

400

400

Conductivity

3.08

3.58

Chlorine (Cl2)

mS/c 3.24 m mg/L 0.16

0.17

0.16

Sulphide ( S-2)

mg/L 120

268

231

NH3

mg/L 2.315 NH3- 1.859 1.642 N NH3-N NH3-N

CHAPTER 6 Conclusion The applicability of fluidized bed in decolorizing wastewater was explored here. The findings and observations of the present study are summarized below.

1. Physical properties and equilibrium isotherm of the activated carbon in reactive black dye, supplied by local wastewater treatment plant, were determined. The isotherm was modeled with Freundlich equation and the constants were determined by fitting the equation in the experimental data.

2. Bed heights at different fluidization velocity of the fluidized bed for three different particle sizes were determined.

3. Breakthrough curves (concentration of the treated solution versus time) for prepared dye solution were obtained. Initial dye concentration, liquid velocity and adsorbent particle size were varied. It was observed that the color removal performance of the fluidized bed system improved with increasing velocity and decreasing particle size.

4. The over all mass transfer coefficients of the fluidized bed for each run were determined and presented with respect to time.

5. Experiment was also carried out using industrial effluent collected after the secondary stage treatment section. Various parameters of the effluent were measured in the laboratory before and after the experiment, which shows that the color removal achieved by the adsorption in the fluidized bed brought the color content of the wastewater from an unacceptable level to a satisfactory level.

The main advantage of fluidized bed over fixed bed is the continuous movement of the adsorbent particles that facilitates maximum utilization of the adsorbent surface and leads to less frequent regeneration of it. The present study investigates the adsorption characteristics of commercially available low cost activated carbon currently used by some of the local industries as well as explores the fluidized bed technique for color removal. The investigation shows satisfactory result under the experimental conditions. In order to optimize the process for industrial application further investigation, however, is needed for optimization of different parameters such as the optimum amount of adsorbent per unit volume effluent water, optimum velocity and particle size etc.

CHAPTER 7 Recommendations To improve the results of the experiments a double cell spectrophotometer could be used as it compares the sample with a standard for every reading. An on-line monitor can be used to measure the instantaneous concentration over the length of the experiment. This would provide more accurate results as there would be fewer errors in fitting the curve of best fit.

Although this study was concentrating on the use of a fluidized bed, further study could include using a range of different types of adsorbents and dye to determine the most effective way to remove the unwanted color. This could include activated alumina, sawdust and palmfruit bunch particles, tuberose sticks etc. This should be undertaken when removal of a specific dye is required.

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Couillard D. “Appropriate wastewater management technologies using peat.” J Environ Syst Vol.21, (1991), p.1–20.

Couillard D. “The use of peat in wastewater treatment”Water Res Vol.28, (1994), p.1261–74.

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15-20 G. McKay, H.S. Blair and J. Gardner, “The Adsorption of Dyes in Chitin. 111.Intraparticle Diffusion Processes”, Journal of Applied Polymer Science, Vol. 28, (1983), p.

17671778 G. Reschke, K.H. Radeke and D. Gelbin, “Breakthrough Curves for Single Solutions in Beds of Activated Carbon with a Broad Pore-Size Distributin-II Measuring and Calculating Breakthrough Curves of Phenol and Indole from Aqueous Solutions on Activated Carbons”, Chemical Engineering Science, Vol. 41. No. 3, (1986) p. 549-554 G. McKay, H. S. Blair and J. R. Gardner, “Two Resistance Mass Transport Model for the Adsorption of Acid Dye onto Chitin in Fixed Beds”, Journal of Applied Polymer Science, Vol. 33, (1986), p.1249-1257 G. McKay, H. S. Blair and J. R. Gardner, “The Adsorption of Dyes onto Chitin in Fixed Bed Columns and Batch Adsorbers”, Journal of Applied Polymer Science, Vol. 29, (1984), p.1499-1514 G.M. Walker and L.R. Weatherley, “Adsorption of Acid Dyes on to Granular Activated Carbon in Fixed Beds”, War. Res. Vol. 31, No. 8, (1997) p. 2093~101 Gordon McKay, “Fluidized Bed Adsorption of Pollutants on to Activated Carbon”, The Chemical Engineering Journal, Vol.39, (1988), p.87 - 96 G. McKay, M.J. Bino and A.R. Altamemi, “The Adsorption of Various Pollutants from Aqueous Solutions on to Activated Carbon”, Water Res. Vol. 19. No. 4. (1984), p.

491~495 G. McKay and M.S. El Geundi, “Adsorption of Dyes onto Bagasse Pith Using a Solid Diffusion Model”, Journal of Applied Polymer Science, Vol. 36, 43-54, 1988 Hassani, A.H. Seif, Javid A.H., and Borghei M., “Comparison of adsorption Process by GAC with Novel Formulation of Caogulation-Flocculation for Color Removal of Textile Wastewater”, Int. J. Environ. Res., Vol.2(3), (summer 2008), p. 239-248, Hutchins R.A., “New method simplifies design of activated carbon systems”, Chem.

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Vol. 80 (19), (1973), p.133-138 Kamel, M.M. Magda, M. Kamel, B.M. Youssef Waly, A. “Adsorption of direct dyes by cellulose derivatives”. Am. Dye Rep. Vol. 34, (1991).p.50-57.

Khattri, S.D.; Singh, M.K., “Color removal from synthetic dye waste water using a bioadsorbent.” Water Air Soil Pollut.,Vol.120, (2000), p.283-288 K. Santhy and P. Selvapathy, “Removal of reactive dyes from wastewater by adsorption on coir pith activated carbon”, Biosource Technology Vol. 97, (2006), p. 1329-1336 Kishore and Verma, “Mass transfer study on counter current multi-stage fluidized bed ion exchanger”, Chemical Engineering and Processing, Vol. 45, (2005), p.31–45 K.S. Low, C.K. Lee, Bioresour. Technol. Vol.61, (1997), p.121 Low, K.S.; Lee, C.K.; Tan, B.F., “Quaternised wood as sorbent for reactive dyes.”

Appl. Biochem. Biotechnol. Vol. 87,(2000), p.233-239.

Liversidge, R.M.; Lloyd, G.J.; Wase, D.A.J.; Forster, C.F.,”Removal of basic blue 41 dyes from aqueous solution by linseed cake.” Proc. Biochem., 32(6), (1997), p.473- 476.

Mamdouh M. Nassar and Yehia H. Magdy, “Removal of Different Basic Dyes from Aqueous solutions by Adsorption on Palm-Fruit Bunch Particles” Chemical Engineering Journal Vol. 66, (1996), p.223-226 M.A. Munim, M.M.R. Khan, K.F. Akhter, M.J. Uddin, “Potentiality of open burnt clay as an adsorbent for the removal of Congo Red from aqueous solution”, Int. J. Environ. Sci. Tech., Vol.4(4), (2007), p.525-532 McMullan, G.; Meehan, C.; Conneely, A.; Kirby, N.; Robinson, T., Nigam, P.; Banat, I.M.; Marchant, R.; Smyth, W.F. “Microbial decolorisation and degradation of textile dyes.”

Appl. Microbiol. Biotechnol., Vol.56, (2001), p.81-88.

Metcalf and Eddy Inc. (1997), “Waastewater Engineering, Treatment,Disposal and Reuse,” 3rd. Ed., Mc Gray-Hill.

McKay, G., “Design models for adsorption systems in wastewater treatment.” J. Chem Tech. Biotech., Vol.31,(1981), p.717-722.

Mohammad S. EL-Geundi, “Color Removal from Textile Effluents by Adsorption Techniques”, Wat. Res. Vol. 25, No. 3, (1991), p.271-273 McKay G. “Peat-an adsorbent/filtration medium for wastewater treatment.” Water Services Vol.84, (1980), p.357–9.

Mc.Kay, Bino and Altememi, “External Mass transfer during the adsorption of various pollutants onto activated carbon”, Wat. Res. Vol. 20, No. 4, (1985), p.435~442 N.M. Al, Mansi, “Decolorizing Wastewater in a Fixed Bed using Natural Adsorbents”, Separation Science and Technology, 31(14), (1996), p. 1989-1995 Nagarethinam Kannan, Mariappan Meenakshi Sundaram, “Kinetics and mechanism of removal of methylene blue by adsorption on various carbons—a comparative study” Dyes and Pigments, Vol. 51, (2001), p.25-40 Perineau, F.; Molinier, J.; Gaset, A., « Adsorption of ionic dyes onto charred plant-

material,” J. Chem. Tech. Biotech., Vol.32, (1982), p.749-755.

Pierce, J., “Colour in Textile Effluents—the origins of the problem” Journal of the Society of Dyers and Colourists, Vol.110,(1994), p.131–133 Qingye Sun and Linzhang Yang, “The Adsorption of Basic Dyes from Aqueous Solution on Modified Peat–Resin particle”, Water Research, Vol.37 (2002), p. 1535–1544 R.S. Juang, R.L. Tseng, F.C. Wu, J. Environ. Sci. Health A, Vol. 31, (1996), p.325 R. Denold, “Technology for dyeing. Wadale, Bombay: Technology of Textile processing” Sevan publications. Vol. XI, (1984).

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Steankenrichter, I., Kermer, W.D., “Decolorizing Textile Effluents”, Journal of the Society of Dyers and Colourists, Vol.108,(1992), p.182–186 S. Veeraraghavan, L.T. Fan and A.P.Mathews, “Modeling Adsorption in Liquid-Solid Fluidized Beds”, Chemical Engineering Science. Vol. 44. No. 10, (1989), p.23332344, Song et. al. , “Fundamentals of Hydrodynamics and Mass Transfer in a Three-Phase Fluidized Bed System”, Chemical Engineering Science Vol.54, (1999), p.4967-4973 Tim Robinson, Geo. McMullan, Roger Marchant, Poonam Nigam, “Remediation of Dyes in Textile Effluent: a Critical Review on Current Treatment Technologies with a Proposed Alternative”, Bioresource Technology, Vol.77, (2000), p.247-255 Vinod and Reddy, “Mass Ttransfer Correlation for Phenol Biodegradation in a Fluidized Bed Bioreactor”, Journal of Hazardous Materials, Vol. B136, (2006), p.727–734 Wright and Glasser, “Modeling Mass Transfer and Hydrodynamics in Fluidized-Bed Adsorption of Proteins”, AIChE Journal, Vol. 47, No. 2, (February 2001) Yoshitaka Sudo and Dragoslay M. Misic, “Concentration Dependence of Effective Surface

Diffusion Co-efficients in Aqueous Pase Adsorption on Activated Carbon”, Chemical Engineering Science, Vol. 33, (1977), p.1287-1290 CHAPTER 9 Appendices Appendix A: Calibration Curves Calibration Curve of Spectrophotometer: Data for the calibration curve of UV-VIS spectrophotometer by using reaction black ATM solution for λ= 500 nm Concentration of solution Absorbance (ppm) 100 80 60 50 40 30 20 10 5 4 3 2 1

0.988 0.925 0.667 0.59 0.52 0.387 0.26 0.188 0.145 0.108 0.109 0.102 0.085

Calibration curve of UV-VIS spectrophotometer (UV-1201) for Reaction black ATM solution (For 位-500nm) 1.2

1 y = 0.0111x R2 = 0.9539

Absorbance

0.8

0.6

0.4

0.2

0 0

20

40

60

80

100

Concentration (ppm)

Figure 17: Calibration Curve of UV-VIS Spectrophotometer for Raction Black solution

(a)

120

(b) Fig 18 (a) UV-VIS Spectrophotometer (UV 1201) (b) Cell section of the spectrophotometer Calibration for measuring of total surface area and pore volume Before beginning calibration , ensure that: 1 At least one empty sample holder is in place 2 The SMAPLE SELECT knob is set to the TEST for that location 3 The DELAY knob is on LONG 4 The PATH SELECT knob is on SAMPLE 5 A Dewar of liquid nitrogen or other cryogen is positioned about a loop of the gas delivery tube if the dryness of the 30%N2 /70% He gas is questionable 6 The N2/He gas is flowing such that flowmeter indicates 16 7 The DET, X1 and REL COND. Push buttons are pressed.

Now start calibration 1

Fill the 1ml precision syringe wth nitrogen gas by holding the needle tip immediately about the level of liquid nitrogen in Dewar, the evaporating liquid providing an atmosphere of pure nitrogen. Flush the syringe a few times to be sure of obtaining a proper fill. Wipe the needle tip free of accumulated frost and lay the syringe aside, perhaps on the rubber mat of the instrument, allowing the gas inside the syringe to reach room temperature.

2

Zero the instrument display using, as appropriate, the COARSE and FINE ZERO knobs. Observe the display for a few minutes to establish syetem stability.

3 4

Pres the PEAK AREA and CLEAR DISPLAY push buttons.

Adjust the syringe to the 1 ml mark and insert the needle in the septum at INJECT, being sure to push it all the way in. Inject the gas at a moderate rate. Withdraw the needle when the syringe is completely dischargerd.

5

The greshold light will begin flashing and the indicator will acumultating surface area information after approxiamately 5 minutes. The rates of flashing will increse and then dercrease. When the THRESHOLD light registers no flash for 15 to 20 seconds, which will typically occure after about 3 minutes, the accumulation may be considered complete. Another check for completeness is the number displayed when the DET. Pursh button is pressed, it should be 0.02 or less.

The number displayed by the indicator with the PEAK AREA button pressed is now set with the CALIBRATE contrl knob beside the indicator to read the value for S as calculated by using the following equation:

6

S =V

273.3 Atm. Pr essure 6.023 ×10 2 ×16.2 ×10 −20 RoomTemp.

760 22.414 ×10 3

…………..(33)

 % N 2  Atm. Pr ess  1−   = V .const. ………………..(34)  100  Sat. Pr ess 

Where S is the surface are in square meters. The instrument is now calibrated.

Measurement of Total Surface Area and Pore Volume We have used N2 BET method for measuring the total surface area Procedure: At first we sieve the granular activated carbon to a mesh size 16 to 25. Then take 0.5gm from there and dry it to 120 oC approximate at 1 hour for the purposes of remove moisture or water from the carbon pore. Again take weight.

There are three sample gas which to be passed in the activated carbon sample for measuring surface area. The three sample gases are: Sample gas 1: He = 85% N2 = 15%

Sample gas 2: He = 70% N2 = 30%

Sample gas 3: He = 50% N2 = 50%

First sample gas 1 is passed through the activated carbon kept in the analyzer. When the Detector is in stable condition we fill liquid N2 in the Dewar and are passing it to the analyzer with 15% N2. Observed how much adsorption takes places and its reading (peak area) are taken from the Detector. Monolayer is form in the sample activated carbon. Now Dewar (liquid N2) reject from the analyzer and passed same amount of liquid N2 into the sample (activated carbon) and observed that how much desorption take places and again its reading are taken (peak area) from the Detector. In this way we passed sample gas 2 and sample gas 3 through the analyzer and collecting peak area from the Detector. From the adsorption and desorption we can calculate total surface area of activated carbon and using the equation 33: Where S is the surface are in square meters.

For measuring total pore volume, we passed 100% N2 throughout the analyzer and then passed (95% N2 + 5% He) mixture again. Then we calculate pore volume from the equation: V =

273.2  Atm. Pr ess  ×  × 0.00155 ×100 × v ……………..(35) RoomTemp.  760 

Where v = gas volume

Appendix B: Raw Data For measuring Bed Height: Area, A= Ď&#x20AC;D2/4 D= 5cm Data for bed height of the fluidized bed at different velocity Sr. no.

Flow rate Particle size Lit/min 25 mesh 2o mesh 18 mesh

16 mesh

0.701 mm

0.883 mm

0.992 mm

1.18 mm

1

0

4.25

4

3.875

3.75

2

0.5

4.25

4

3.875

3.75

3

0.8

4.25

4

3.875

3.75

4

1

4.25

4

3.875

3.75

5

1.5

4.25

4

3.875

3.75

6

2

4.375

4.25

3.9375

3.75

7

2.5

4.5

4.625

4

3.875

8

3

4.75

4.75

4.125

4.875

9

3.5

5

5

4.375

5

10

4

5.375

5.125

5.25

5.125

11

4.5

6

5.25

5.9375

5.75

12

5

6.75

6.8125

7

6.125

13

5.5

7.75

7.125

7.125

7.625

14

6

8.5

8.1875

8.8125

8.375

15

6.5

10

11.8125

11.625

9.9375

16

7

12.25

14.9375

13.8125

12.125

17

7.5

15.75

16.125

16.9375

15.6875

18

8

18.25

18.125

17.625

17.125

19

8.5

Fluidized

Fluidized

19

19.25

20

9

Fluidized

Fluidized

Adsorption Isotherm Data From Calibration Curve of Spectrophotometer, x=y/0.011 Data taken after 29 days activated carbon = 5.02 gm mesh size: -18+20 ( 1 mm --0.84 mm ) Data for adsorption isotherm for dye solution for different sizes of activated carbon Ce C0 absorbence x=y/0.011 (c0-ce) Q = (c0-ce)/m 11.2792 2.24686 12 0.008 0.720721 8 8 18.7090 3.72689 19.7 0.011 0.990991 1 4 32.6486 6.50371 34 0.015 1.351351 5 5 40.3783 8.04350 42 0.018 1.621622 8 2 48.2882 9.61918 50 0.019 1.711712 9 1 12.5892 65 0.02 1.801802 63.1982 8 13.5458 80 0.022 2 68 2 87.3636 17.4031 90 0.029 2.636364 4 1 106.636 110 0.037 3.363636 4 21.2423 28.6852 150 0.066 6 144 6 181.

34.2031 7 0.11 10 171.7 9 210.

196.254 39.0945 8 0.16 14.54545 5 3 mesh size: -20+25 ( 0.84 mm -- 0.71 mm) Ce C0 absorbence x=y/0.011 (c0-ce) 15

0.009

0.818182

14.18

23.8 34

0.011 0.019

1 1.727273

22.80 32.27

47

0.021

1.909091

45.09

55 65.3

0.023 0.03

2.090909 2.727273

52.91 62.57

Q = (c0-ce)/m 2.82506 3 4.54183 3 6.42883 8.98225 3 10.5396 6 12.4646

81.7 115.4 9

0.037

3.363636

78.34

0.068

6.181818

109.31

140.4

0.089

8.090909

132.31

161.6

0.096

8.727273

152.87

182.3

0.12

10.90909

171.39

200.5

0.15

13.63636

186.86

9 15.6048 5 21.7745 4 26.3563 9 30.4527 3 34.1416 2 37.2238 3

mesh size: -14+16 ( 1.3 mm -- 1.15 mm) Co 12.2 20.8 31 40.9 51 67 82.5 112.4 142.7 167.1 181.6 201.5

Absorbence Ce 0.63063 0.007 1 0.81081 0.009 1 1.17117 0.013 1 1.71171 0.019 2 1.98198 0.022 2 2.61261 0.029 3 3.09090 0.034 9 3.72727 0.041 3 5.36363 0.059 6 8.81818 0.097 2 0.11 10 13.3636 0.147 4

Co-Ce

(Co-Ce)/m

11.56937

2.27439

19.98919

3.92962

29.82883

5.863967

39.18829

7.703918

49.01802

9.636317

64.38739

12.65774

79.40909

15.61327

108.6727

21.36703

137.3364

27.00282

158.2818 171.6

31.12108 33.73968

188.1364

36.99103

Data of Dye Solution: Particle size: -14+16 mesh (U.S standard) Run-1 Amount of activated carbon = 80g Concentration of stock solution = 18.45 ppm Flow rate = 2 dm3/min Time (min) 0.5 1 2 3 4 6 9 12 15 18 21 22

Absorbance 0.177 0.179 0.182 0.179 0.187 0.196 0.2 0.188 0.19 0.197 0.198 0.204

Concentration (g/l) 16.09 16.27 16.55 16.27 17.00 17.82 18.18 17.09 17.27 17.91 18.00 18.55

Particle size: -18+20 mesh (U.S standard) Run-2 Amount of activated carbon = 80g Concentration of stock solution = 18.45 ppm Flow rate = 2 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.115

10.45

1

0.139

12.64

2

0.149

13.55

3

0.16

14.55

4

0.162

14.73

6

0.169

15.36

8

0.172

15.64

10

0.175

15.91

13

0.179

16.27

16

0.174

15.82

19

0.178

16.18

22

0.186

16.91

25

0.187

17.00

31

0.188

17.09

34

0.189

17.18

37

0.189

17.18

Run-3 Amount of activated carbon = 80g Concentration of stock solution = 18.45 ppm Flow rate = 3 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

1 2 3 4 6 8 11 14 15 17 20

0.168 0.172 0.182 0.18 0.189 0.185 0.186 0.194 0.198 0.203 0.2

15.27 15.64 16.55 16.36 17.18 16.82 16.91 17.64 18.00 18.45 18.18

Run-4 Amount of activated carbon = 80g Concentration of stock solution = 23 ppm Flow rate = 2 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.21

19.09

1

0.215

19.55

2

0.217

19.73

3

0.22

20.00

4

0.217

19.73

6

0.221

20.09

8

0.223

20.27

10

0.224

20.36

13

0.224

20.36

16

0.227

20.64

19

0.229

20.82

22

0.236

21.45

25

0.238

21.64

28

0.24

21.82

31

0.245

22.27

34

0.247

22.45

Run-5 Amount of activated carbon = 80g Concentration of stock solution = 23 ppm Flow rate = 3 dm3/min Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.202

18.36

1

0.207

18.82

2

0.211

19.18

3

0.213

19.36

4

0.222

20.18

6

0.225

20.45

9

0.227

20.64

12

0.228

20.73

15

0.236

21.45

20

0.2376

21.6

25

0.2409

21.9

30

0.24354

22.14

34

0.2453

22.3

Time (min)

Run-6 Amount of activated carbon = 80g Concentration of stock solution = 23 ppm Flow rate = 4 dm3/min Time (min)

Absorbance

0.5

0.214

Concentration (ppm) (From calibration curve) 19.45

3

0.232

21.09

6

0.232

21.09

9

0.244

22.18

12

0.234

21.27

15

0.244

22.18

18

0.248

22.55

21

0.25

22.73

24

0.252

22.91

27

0.249

22.64

30

0.252

22.93

Run-7 Amount of activated carbon = 80g Concentration of stock solution = 29.45 ppm Flow rate = 2 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.293

26.64

2

0.293

26.64

3

0.298

27.09

4

0.294

26.73

12

0.3

27.27

15

0.299

27.18

18

0.295

26.82

21

0.297

27.00

24

0.305

27.73

27

0.308

28.00

30

0.308

28.00

Particle size: -20+25 mesh (U.S standard) Run-8 Amount of activated carbon = 80g Concentration of stock solution = 18.45 ppm Flow rate = 3 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.131

11.91

1

0.145

13.18

2

0.145

13.18

3

0.146

13.27

4

0.15

13.64

6

0.161

14.64

9

0.165

15.00

12

0.167

15.18

15

0.169

15.36

18

0.172

15.64

21

0.177

16.09

24

0.188

17.09

27

0.2

18.18

Industrial Effluent Data: Particle size: -14+16 mesh (U.S standard) Run-1 Amount of activated carbon = 100g Industrial Effluent Concentration = 0.291 ppm or 26.45455 mg/l Flow rate = 3 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.231

20.81081

1

0.239

21.53153

2

0.251

22.61261

5

0.263

23.69369

7

0.276

24.86486

9

0.277

24.95495

12

0.284

25.58559

15

0.287

25.85586

18

0.288

25.94595

21

0.29

26.12613

23

0.29

26.12613

Particle size: -18+20 mesh (U.S standard) Run-2 Amount of activated carbon = 100g Industrial Effluent Concentration = 0.291 ppm or 26.45455 mg/l Flow rate = 4 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.22

20

1

0.231

21

2

0.237

21.54545

5

0.241

21.90909

7

0.249

22.63636

9

0.251

22.81818

12

0.253

23

15

0.257

23.36364

18

0.261

23.72727

21

0.269

24.45455

24

0.278

25.27273

26

0.29

26.36364

Particle size: -18+20 mesh (U.S standard) Run-3 Amount of activated carbon = 100g Industrial Effluent Concentration = 0.291 ppm or 26.45455 mg/l Flow rate = 3 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.224

20.36364

1

0.233

21.18182

2

0.243

22.09091

5

0.251

22.81818

7

0.259

23.54545

9

0.263

23.90909

12

0.267

24.27273

15

0.269

24.45455

18

0.275

25

21

0.281

25.54545

23

0.288

26.18182

Particle size: -18+20 mesh (U.S standard) Run-4 Amount of activated carbon = 100g Industrial Effluent Concentration = 0.291 ppm or 26.45455 mg/l Flow rate = 2 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.23

20.72072

1

0.242

21.8018

2

0.253

22.79279

5

0.268

24.14414

7

0.278

25.04505

9

0.281

25.31532

12

0.288

25.94595

15

0.289

26.03604

18

0.289

26.03604

21

0.291

26.21622

0.5

0.23

20.72072

Particle size: -20+25 mesh (U.S standard) Run-5 Amount of activated carbon = 100g Industrial Effluent Concentration = 0.291 ppm or 26.45455 mg/l Flow rate = 3 dm3/min Time (min)

Absorbance

Concentration (ppm) (From calibration curve)

0.5

0.207

18.81818

1

0.211

19.18182

2

0.219

19.90909

5

0.23

20.90909

7

0.237

21.54545

9

0.242

22

12

0.25

22.72727

15

0.249

22.63636

18

0.251

22.81818

21

0.253

23

23

0.263

23.90909

Appendix C: Calculated data Data obtained for mass transfer coefficient calculation: Mesh size: 1 mm -0.84 mm Velocity = 0.034 m/s , Initial concentration = 23 ppm amount of activated carbon: 80 gm time 0.5 3 6 9 12 15 18 21 24 27 30 31 33 34 36 37 38

q 0.391 2.345931 4.690898 7.032423 9.366374 11.68697 13.98677 16.25669 18.48599 20.66228 22.7715 23.45701 24.79797 25.45211 26.72433 27.34096 27.94363

Kf*10-3, m/s 0.071205 0.068586 0.066212 0.06449 0.063283 0.062005 0.062206 0.061716 0.061782 0.061708 0.059176 0.057868 0.056575 0.055124 0.05223 0.050782 0.04933

Velocity = 0.0254 m/s time 0.5 1 2 3 4 6 9 12 15 20 25 30 34

q 0.2921 0.584198 1.16837 1.752446 2.336312 3.502731 5.245301 6.970898 8.666559 11.3792 13.86086 15.98295 17.31708

Kf*10-3, m/s 0.050975 0.050508 0.049662 0.048922 0.048281 0.047269 0.046356 0.046109 0.042621 0.038965 0.037481 0.037094 0.033044

Velocity = 0.017 m/s tim e 0.5 1 2 3 4 6 8 10 13 16 19 22 25 28 31 34

q 0.1955 0.390999 0.781986 1.172931 1.563782 2.344898 3.124518 3.9015 5.058723 6.200294 7.318227 8.402882 9.442969 10.42554 11.33601 12.15811

Kf*10-3, m/s 0.032929 0.032693 0.032256 0.031863 0.031509 0.030901 0.030404 0.029996 0.029508 0.029117 0.028776 0.028438 0.028063 0.027613 0.027058 0.026374

Particle size: 1 mm - 0.84 mm velocity: 0.0254 m/s amount of activated carbon: 80 gm Time (min) 0.5 1 3 4 6 8 11 14 15 17 20

q 0.23431 5 0.46862 5 1.40547 9 1.87322 2.80519 6 3.72823 2 5.08055 4 6.36566 7 6.77227 5 7.54242 3 8.5598

Kf*10-3, m/s 0.030286 0.029958 0.028909 0.028509 0.027891 0.027439 0.026913 0.026378 0.026165 0.02565 0.024587

Particle size:0.84 mm -0.71 mm velocity: 0.0254 m/s amount of activated carbon: 80 gm tim e q Kf*10-3, m/s 0.5 0.234315 0.038153 1 0.468624 0.037505 2 0.937169 0.036404 3 1.405427 0.035517 4 1.873057 0.034808 6 2.804373 0.033825 9 4.180174 0.033167 12 5.505054 0.033173 15 6.740128 0.033478 18 7.835402 0.033578 21 8.729771 0.032784 24 9.65102 0.030509 27 10.49582 0.026825 Particle size: 1.3 mm - 1.15 mm velocity: 0.0254 m/s amount of activated carbon: 80 gm Initial concentration Co = 18.45 ppm tim e q Kf*10-3, m/s 0.5 0.234314 0.029465 1 0.468622 0.029029 2 0.937128 0.028306 3 1.405221 0.027752 4 1.872407 0.027336 6 2.801082 0.02683 9 4.163509 0.026636 12 5.452384 0.026814 15 6.611541 0.027044 18 7.568763 0.026998 21 8.235789 0.026362 22 8.376077 0.025978