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Ind. Eng. Chem. Res. 2008, 47, 5376–5385
Sewage Sludge Pyrolysis in Fluidized Bed, 1: Influence of Operational Conditions on the Product Distribution Isabel Fonts,* Alfonso Juan, Gloria Gea, María B. Murillo, and Jose´ L. Sa´nchez Arago´n Institute of Engineering Research (I3A), Chemical and EnVironmental Engineering Department, Thermochemical Processes Group (GPT), UniVersity of Zaragoza, Campus Río Ebro, Calle María de Luna 3, 50018 Zaragoza, Spain
In this work, pyrolysis of sewage sludge in a fluidized bed was studied experimentally in order to obtain a liquid product able to be used in energetic applications. The influence of operational conditions on the product distribution was studied. The operational variables were as follows: temperature (450-650 °C), nitrogen flow rate (3.5-5.5 L(NTP) min-1), and solid feed rate (3.0-6.0 g min-1). Their influence was considered on the yields to the three pyrolysis products: solid, liquid, and gas. The liquid yield was mainly influenced by the bed temperature but also by the nitrogen flow rate and the solid feed rate. The bed temperature and the nitrogen flow rate showed a quadratic effect, and the maximum liquid yield was achieved at around 540 °C and around 4.5 L(NTP) min-1 of nitrogen. The solid feed rate just affected on the liquid yield at the lower temperatures studied, and the maximum liquid yield was obtained at the lowest solid feed rates. The design of experiments (DOE) statistical tool was used in the preparation of the work. Introduction Sewage sludge is the waste left over after the purification of water in wastewater treatment plants. It consists of a complex heterogeneous mixture of organic (undigested organics, such as cellulosic and dead bacteria and microbes) and inorganic materials.1,2 In recent years, due to the application of European Directive 91/271/CEE,3 the number of wastewater treatment plants and consequently the production of sewage sludge has increased. There are several ways of managing and valorizing sewage sludge, the most common being agricultural use and other composting practices. However, due to legislation in the European Union (Directive 86/278/CEE),4 not all the sewage sludge produced can be used as fertilizer. Thermal treatments (pyrolysis, gasification, or combustion) provide an interesting energetic alternative. Pyrolysis is the chemical decomposition of organic materials by heating in the absence of oxygen or any other reagents. Fast pyrolysis is aimed at producing high yields to the liquid product. If the biooil production is to be maximized with respect to the other pyrolysis products (solid and gas), reactors with a rapid heating rate and good temperature control are required.5 The technology used for this purpose includes fluidized bed reactors, circulating fluidized bed reactors, ablative pyrolysis, and vacuum pyrolysis. Nowadays, pyrolysis of sewage sludge is being studied in order to obtain a liquid with a high heating value. Domínguez et al.6 have studied the microwave-assisted pyrolysis of sewage sludge, and other authors7–11 have studied sewage sludge pyrolysis in fluidized bed. The objectives of the present work are to study experimentally how the operational conditions of sewage sludge pyrolysis in a fluidized bed affect the product distribution and to find out how the product yields evolve within the ranges studied. The experimental methodology is based on experimental design techniques. In this work, in addition to the experimental study, * To whom correspondence should be addressed. Tel.: +34976762897. E-mail:
[email protected].
empirical models are obtained to explain by means of statistical tools the trends of the product yields within the ranges studied. Materials and Methods This section describes the characteristics of the sewage sludge used in this study, the experimental apparatus and procedure, and the planning of the experimental work based on the experimental design. Material. The sewage sludge was supplied by an urban wastewater treatment plant where the sludge is anaerobically digested and thermally dried. Two samples of sludge were received at different times, the first (S1) being used for most of the experiments. Proximate and ultimate analyses were made of this sample (see Table 1). The lower heating value (LHV) was also determined by means of a calorimeter IKA A-2000 (standard procedure, ISO-1928-89). The value obtained for LHV was 11.2 MJ/kg. These analyses were performed by the “Instituto de Carboquı´mica” (CSIC, Zaragoza, Spain). Moreover, the sewage sludge (S1) was analyzed by X-ray diffraction. The main minerals found were ilite, caolinite, magnetite, albite, quartz, calcite, microline, and dolomite. These minerals contain some alkali and alkaline metals such as K, Na, Mg, and Ca, that can act as catalyst in some reactions that take place in the pyrolysis process12 and also some other elements such as Al, Fe, and Si. Table 1. Proximate Analyses (Moisture Basis) and Ultimate Analyses (Moisture Basis) of the Raw Materials
moisture ash volatiles fixed carbon carbon hydrogena nitrogen sulfur b
analytical standard
S1 wt %
S2 wt %
ISO-589-1981 ISO-1171-1976 ISO-5623-1974 by difference
6.7 39.9 47.0 6.4 28.5 4.3 4.1 0.8
7.1 41.0 46.6 5.3 27.7 4.4 3.9 0.8
b b b b
a The percent of hydrogen includes the hydrogen of the moisture. Elemental analyses were carried out using a Carlo Erba 1108.
10.1021/ie7017788 CCC: $40.75 2008 American Chemical Society Published on Web 06/25/2008
Ind. Eng. Chem. Res., Vol. 47, No. 15, 2008 5377
Figure 1. Diagram of the laboratory scale plant.
In some additional experiments the second sewage sludge sample (S2) was used. Proximate and ultimate analyses were also performed (see Table 1). The value obtained for LHV was 10.8 MJ/kg. Experimental System. The sewage sludge pyrolysis experiments were carried out in a laboratory-scale plant operating at atmospheric pressure, with continuous feed of solids and nitrogen as fluidizing gas and equipped with a continuous ash removal system. The experimental plant is shown in Figure 1. Sewage sludge was smashed and sieved to provide a feed sample in the size range of 250-500 µm. Sand was also sieved in the size range of 150-250 µm. These were fed in 100:20 weight proportions into the reactor by a variable-speed screw feeder through a sloping pipe, entering the reactor 10 mm above the distributor plate. The sloping pipe was refrigerated with air in order to avoid the reaction taking place in the pipe and therefore outside the bed. This air did not come into contact with the sewage sludge. The solid feed rate was one of the operational variables under study and was varied between 3.0 and 6.0 g min-1. The different solid feed rate values enabled the solid residence time to be varied. Nitrogen was used as fluidizing gas. Two-thirds of the nitrogen flow was introduced through the distributor plate in order to fluidize the bed, while the rest of the flow was fed into the reactor with the solid feed in order to facilitate its entry. The nitrogen flow rate was controlled by a mass flow controller, and its influence was also studied. The flow was varied between 3.5 and 5.5 L(NTP) min-1, NTP signifying normal temperature and pressure (0 °C and 1 atm). The different nitrogen flow rate values enabled the gas residence time to be changed. The fluidized bed reactor was made of refractory steel (AISI 310), with an inner diameter of 38 mm and a height of 800 mm. The bed height was kept at 150 mm by means of a concentric pipe of 12 mm diameter passing through the distributor plate, enabling the bed material to overflow and be collected in a solid vessel. This ash removal system is very useful for materials with high ash content as it allows an increase in the bed height to be avoided. The reactor was heated by an electrical furnace with three heating zones (bed, free-board, and cyclone), which could be controlled independently. The temperature of the bed zone was
one of the variables under study and was varied between 450 and 650 °C. The free-board temperature was set at 450 °C. The cyclone was also maintained at 450 °C in order to avoid the vapors cracking or condensing because of the temperature. A hot filter was put in place behind the cyclone to remove the smaller particles.13 It is important to separate the solid particles because they can cause a decrease in the liquid stability.12,14 The temperature of this filter was also maintained at 450 °C. The liquid recovery system was placed behind the heated filter. This system was composed of two cooled condensers and a cotton filter. When the gas flow arrived at the liquid recovery system, the organic vapors and the water condensed and the exiting gas was made up of noncondensable gases (NCG). The production of noncondensable gases was measured by a volumetric gas meter. The gas composition was determined by means of a micro-gas chromatograph (micro-GC; Agilent 3000A) connected online. Experimental Procedure. Before the start of the pyrolysis experiment, the feed hopper was filled with the sewage sludge and sand (100/20 (w/w)). The bed reactor was filled with a mixture of sand and solid product obtained from a previous sewage sludge pyrolysis experiment developed under the same temperature conditions. This was in order to minimize the nonstationary period15 which can occur as a result of bed composition changes. The condensers were cooled to 0 °C with ice, water, and salt, the ice being replaced as necessary during the experiment. The frequency of the screw feeder was regulated to the desired solid feed rate (3.0-6.0 g min-1). The nitrogen flow rate was set using a mass flow controller. Once there was no lack of gas, the temperature controllers were switched on. When the bed, cyclone, and hot filter reached the desired temperatures, the sewage sludge and sand began to be fed. The pyrolysis reaction then took place inside the fluidized bed reactor, and the resulting vapors and gases exited the reactor. During the experiment, the liquid was collected in the condensers and the solid collected in the fine vessel and the solid vessel. The gas volumetric flow production and its composition were measured online. The experiment was halted by stopping the feeder. The run time was 75 min in order to minimize the effect of the nonstationary period16 on the overall results.
5378 Ind. Eng. Chem. Res., Vol. 47, No. 15, 2008 Table 2. Product Yields Obtained for the Experiments Performed sewage sludge (block)
T (°C)
QN2 (L(NTP) min-1)
Qfeed (g min-1)
ηsolid a (wt %)
ηliquid a (wt %)
ηgas a (wt %)
ηsolid b (wt %)
ηliquid b (wt %)
ηgas b (wt %)
S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S1 S2 S2 S2 S2
450 650 650 450 550 550 450 650 650 450 550 550 550 450 650 550 550 550 550
3.5 3.5 5.5 5.5 4.5 4.5 5.5 5.5 3.5 3.5 4.5 4.5 4.5 4.5 4.5 3.5 5.5 4.5 4.5
6.0 6.0 6.0 6.0 4.5 4.5 3.0 3.0 3.0 3.0 4.5 4.5 4.5 4.5 4.5 4.5 4.5 3.0 6.0
60.3 52.1 49.9 63.0 51.3 52.9 58.5 53.2 46.1 61.4 53.2 55.8 53.2 51.5 47.2 48.8 52.3 52.0 55.6
23.5 28.6 28.1 23.4 34.6 33.0 28.0 27.2 27.2 24.7 32.0 33.5 32.3 31.3 25.0 34.8 30.9 40.7 30.5
16.2 19.3 21.9 13.6 14.1 14.1 13.5 19.6 26.6 13.9 14.8 10.7 14.5 17.2 27.9 16.3 16.7 7.35 13.8
38.2 22.8 18.7 43.3 21.3 24.3 34.8 24.9 11.6 40.3 24.9 29.8 24.9 21.7 13.7 15.0 21.8 21.2 28.1
31.5 41.0 40.1 31.3 52.2 49.3 39.9 38.4 38.4 33.7 47.4 50.2 47.9 46.1 34.3 53.4 45.9 64.7 45.1
30.3 36.1 41.0 25.5 26.4 26.4 25.3 36.7 49.8 26.0 27.7 20.0 27.2 32.2 52.2 31.4 32.2 14.2 26.6
a
Yields calculated as moisture-ash basis. b Yields calculated as moisture-ash free basis.
After the experiment the solid and liquid products were quantified by weight, the solid sample being collected from the bed, fine vessel, solid vessel, and hot filter. A sample of 1 g of the solid was placed in a muffle and heated according to the standard UNE 32-004-84 in order to determine the carbonaceous matter not devolatilized during the experiment. The LHV of the gas product was calculated by means of its composition measured with the micro-gas chromatograph. Experimental Design. The influence of the experimental conditions on the pyrolysis products was studied experimentally with a factorial design, using as raw material the first sewage sludge received, S1. This method is suitable for studying the influence of the experimental variables, and also the influence of their interactions on the product distribution. In this case, in terms of experimental design, the studied experimental variables were called factors, and the product yields called response variables. These variables are defined as follows: ηsolid (wt %) is the percentage ratio between the increase of the weight of solid collected from the bed, the fine vessel, solid vessel, and the hot filter at the end of the experiment calculated by difference without taking into account the fed sand, and the weight of sewage sludge introduced into the system. ηliquid (wt %) is the percentage ratio between the weight of liquid collected from the condensers and from the cotton filter at the end of the experiment and the weight of sewage sludge introduced into the system. ηgas (wt %) is the percentage ratio between the weight of gas produced and the weight of sewage sludge introduced into the system. It is calculated by difference with the other product yields. Additionally, two response variables that define the characteristics of the solid and the gas product were studied. These properties are the carbonaceous matter content (CM) for the solid and the LHV for the gas and can be defined as follows: CM (wt %) is the ratio between the loss of weight produced in the solid product when heated in the muffle and the total weight of solid product recovered. LHV (kcal m-3(NTP)) is the lower heating value of the gas produced calculated using the gas composition given by the micro-GC. In this study three operational variables or factors are studied: bed temperature (T, 450-650 °C), nitrogen flow rate (QN2, 3.5-5.5 L(NTP) min-1), and solid feed rate (Qfeed, 3.0-6.0 g
min-1). These variables must be independent.17 The nitrogen flow rate, together with bed temperature, affects the gas residence time. The solid feed rate affects the solid residence time. These three factors together with their respective ranges of study were chosen on the basis of works of other authors concerning pyrolysis of sewage sludge in fluidized bed reactors7–9 and several gasification studies carried out in the same plant and with the same material.18 As the number of factors was not high (3), a full factorial design (FFC) was chosen to study their influence and interactions. An interaction occurs when a factor influences the response variable in a different way depending on the value of another factor.17 This kind of design has already been used by other authors in similar studies.19 In this work a two-level full factorial design has been used. This consists of 2n runs and nc center runs, where n indicates the number of factors studied and nc the number of replicates at the center point. The replicates are used to evaluate the experimental error and the curvature of the evolution of a response variable, that is to say, whether or not the evolution of the response variable is linear within the experimental range studied. The number of replicates in the center point depends on the variability of the system. Five replicates have been carried out in this study. Therefore 23 + 5 ) 13 experiments have been run in this part of the work, all of them carried out with S1. The operational conditions of these experiments are shown in Table 2. The experimental results obtained for each response variable were analyzed statistically by means of an analysis of variance (ANOVA), using the software Design Expert version 7.0. These ANOVA analyses allow a determination of how the factors affect the response variables. To be precise, the ANOVA analysis of a full factorial design with two levels evaluates whether the principal effects of the factors, the interactions between them, and the curvature have a significant influence on the response variables. Once the analysis of the full factorial is made, it is important to determine whether or not the curvature is significant, that is to say whether the evolution of the response variable in the interval studied is linear or not. If the evolution of the response variable is linear, then the influence of the factors on the response variable will be known from the analysis of the full factorial design only. But if, on the other hand, the ANOVA reveals that the curvature is significant, it will be necessary to undertake more experiments in different conditions
Ind. Eng. Chem. Res., Vol. 47, No. 15, 2008 5379
Figure 3. Interaction plots of solid yield vs T for the lowest and highest QN2: (a) Qfeed ) 3.0 g min-1; (b) Qfeed ) 6.0 g min-1.
Figure 2. Product distribution versus temperature: (a) solid yield, (b) liquid yield, and (c) gas yield.
in order to determine the evolution of the response variable in the ranges studied and to find out which factor(s) is (are) causing the curvature. The ANOVA analyses from the full factorial design performed for some of the response variables studied in this work have revealed significant curvature. For this reason the experimental design was augmented with six additional experiments. The operational conditions of these experiments are also shown in Table 2. The full factorial design with these six additional experiments was transformed into a response surface design called a central composite design.17 Those kinds of designs are used when there is a curvature for a response variable, and it is necessary to identify the operational conditions that optimize the value of this response variable in the interval studied. For example, some authors have used these designs to find the operational conditions for the pyrolysis of fryer grease in fixed bed that maximize the production of hydrogen and syngas.20 The first two experiments of the augmented design were carried out with sludge S1, but due to the supply becoming exhausted the last four experiments were carried out with the second sewage sludge received, S2, of a similar, but not equal, composition. This change may have introduced a degree of variability in the system which must be studied in order to check if the change in the material significantly affects the response variables by using blocks.17 If this change does not significantly affect the response variables, their values in all 19 experiments can be used to analyze the influences of the operational conditions. If, however, the change does have a significant effect, then only the experiments with the same sewage sludge (15
experiments) will be useful for studying the evolution of the response variable. Table 2 shows all the experiments performed together with the operational conditions used for each. The runs are shown in chronological order. The results of the ANOVA analyses were also used to develop empirical models correlating the values of the response variables as a function of the significant terms. First-order models were proposed for response variables whose curvature was not significant and second-order models for cases where the curvature was significant. These models predict the value of the response variables using the following polynomial equations: k
y ) β0 +
∑ β x +∑ β x x i i
i)1
k
y ) β0 +
∑ i)1
ij i j
first-order model
(1)
i
