BASIC: A Comprehensive Model for SO x Formation Mechanism and Optimization in Municipal Solid Waste (MSW) Combustion.

Municipal solid waste (MSW) incineration is one of the main techniques currently used for waste to energy (WTE) conversion in China. Although the sulfur content in MSW is lower than that in coal, its emission cannot be neglected due to environmental pollution, malodor, health problems, and global climate change. Therefore, it is particularly important to effectively predict and control the sulfur pollutants. In this study, a comprehensive model was developed and coupled with the full combustion process bed model bulk accumulated solids incineration code (BASIC) to investigate the formation and transformation processes of sulfur in MSW incineration. The submodels of the four stages in the MSW combustion processes; governing equations of mass, momentum, and energy conservation; and various chemical reactions were included in the model. Based on this model, the effects of different parameters on the formation of sulfur pollutants during the incineration process were studied under different operating conditions. The study finds that for SO X formation, initial temperature, primary air volume, and material particle size have significant impacts, whereas pressure shows a less significant effect. This article also considers H2S, COS, and CS2 formation under different conditions. An optimization study was performed to reduce SO X pollutants.

Introduction

The worldwide concern with the rising production of municipal solid waste (MSW) and the limit of fossil fuels have accelerated global interest in waste to energy (WTE) conversion.[1] About 1.3 billion tons of MSW was produced worldwide in 2010 and the global MSW generation is expected to reach 2.2 and 4.2 billion tons by 2025 and 2050, respectively, which could lead to wastage of resources and environmental pollution.[2] As a well-proven and established method for treating MSW, incineration can extract up to 80% of the energy contained in waste and reduce the solid volume by up to 90%.[3,4] Currently, more than 325 million tons of MSW is treated globally in more than 2500 MSW incineration plants with power generation around the world.[5] SO emissions are generated from the high-temperature oxidation process of MSW combustion, which is mainly composed of SO2 and SO3.[6] The sulfur content of MSW is lower than that of the traditional fossil fuels, but MSW combustion is still one of the major contributors to sulfur pollution. According to the current EU directive on the SO2 emission limit, the daily average limit is 50 mg/Nm3 (O2 content 11%) for MSW incineration plants.[7] However, the daily average limits of SO2 from WTE plants and coal-fired plants in China are 80 mg/Nm3 (O2 content 11%) and 50 mg/Nm3, respectively. This means SO2 emission control from WTE plants still needs to be emphasized in the near future.

The release of sulfur under various conditions has been studied in detail by several researchers. Pollutants such as SO2 and SO3 are the main sources of acid rain. Up to 10% of SO2 is converted to SO3 during combustion.[8] Furthermore, SO2 and H2S are the major species during combustion. H2S is much toxic; even trace amounts of H2S will have a strong effect on the human respiratory tract and eyes. Another type of sulfur gas CS2 is produced in combustion and has a low chemical reactivity, but it can be oxidized to SO2 through photochemical reactions in the atmosphere, which will also cause the formation of acid rain. Therefore, it is necessary to study the formation mechanisms and concentration trends of sulfur species during MSW combustion. However, this study is difficult to investigate in industrial-scale incinerator experiments. In contrast, numerical simulation seems to be an attractive method.

Until now, there are a few studies on the incineration model of sulfur, and most of them are merely based on the kinetics of chemical reactions. Mueller et al. established a chemical reaction kinetic model of SO in a fluidized bed reactor, and the simulation results of SO2 showed that the conversion rate of SO2 to SO3 was about 10%.[9] Zarei used a modified reaction kinetic model to describe the generation process of SO pollutants in the Claus reaction furnace. He optimized the operating parameters during the waste combustion process and obtained the best-operating conditions such as the initial temperature of the reactor to reduce the COS emissions from waste heat boilers.[10] Ghahraloud et al. established a one-dimensional mathematical model to change the inlet temperature of the fixed bed reactor, the feed rate along with the furnace, and the airflow in the furnace to improve the recovery rate of S and reduce the emission of S-type pollutants. Simulation results show that compared with the conventional process, the S recovery rate is improved by about 4.63%.[11] In addition, Gungor et al. also conducted simulation studies on SO2 and other gas pollutants produced by coal combustion on a circulating fluid bed. Their results showed that the increase of excess air could reduce SO2 production and the concentration of SO2 was lower under the condition of higher inlet pressures.[12]

Although the above researchers have investigated SO concentration prediction models based on incineration and simulated SO pollutants under different operating conditions, these studies have not explored the transformation process of SO pollutants in the gas–solid phase in the incineration bed. They only focused on the gas-phase process and involved relatively less SO pollutants and initial operating conditions. A fixed bed reactor is mainly composed of two parts: a packed bed region containing solid waste and gas and a gas-based freeboard region. Commercial computational fluid dynamics (CFD) software such as Fluent can be used to easily simulate the freeboard area. However, accurate modeling of packed bed areas is a challenging part due to the various homogeneous and heterogeneous reactions and corresponding heat- and mass-transfer processes in the boundary area. MSW combustion in the packed bed region is an important part of the incineration process because it is the place where most of the pollutants (SO, NO, heavy metals, etc.) are generated.[13,14] Therefore, there is a need to study the changing trend of various SO gas pollutants in the packed bed region to explore the production of SO pollutants under different operating conditions.

To study the generation mechanism and emission characteristics of SO and other sulfur pollutants, we took advantage of the most relevant descriptions of early studies. We have developed the bulk accumulated solids incineration code (BASIC) model for simulating the behavior of a burning MSW bed.[15] This model targets the packed bed region and can facilitate the freeboard CFD simulation by providing the inlet conditions from the packed bed region. The model is based on the CFD theory and simulates the overall incineration process within the packed bed, including MSW drying, devolatilization, volatile combustion, and char oxidation processes. To develop a comprehensive model, various operating conditions including pressure, initial temperature, primary airflow rate, and material particle size are taken into account to investigate the effect of these parameters on the formation of different sulfur contaminants (SO2, SO3, H2S, CS2, COS, S2). Furthermore, the results predicted by BASIC are validated by comparing with experimental data from the literature, and the formation mechanism of all sulfur species is revealed in detail.

Model Development

The model of MSW bed combustion is based on the description of the most actual physical, chemical, and thermal phenomena. The kinetic data of reactions and the equations of energy, momentum, and mass fractions are used to describe these phenomena and calculate the local velocity, pressure, temperature, and composition. Figure shows a conceptual view of the combustion process of solid waste particles. It describes the physical, chemical, and thermal reactions of solid waste particles during combustion. The incineration processes are simplified in the following description. First, primary air is injected from the bottom of the reactor. The bed of waste that contains a certain amount of moisture is then heated by the thermal radiation causing the waste on the surface to catch fire from the freeboard; the heated waste undergoes evaporation of water. As the heating continues, the organic matter is decomposed into volatile components, including tar, char, and gases. As the reaction progresses, it will also experience gas combustion and oxidation of the char.[16] During the combustion reaction with oxygen, the heat generated from these reactions will continue to increase the temperature in the packed bed region.[17] When the combustion process is complete, the fixed carbon is consumed, cooled by the air supply, and finally turn into ash.[18,19]

Figure 1

Illustration of different combustion subprocesses of solid waste particle.

Referring to the MSW incineration process mentioned above, the corresponding chemical reaction equation and chemical reaction kinetic model were determined. Subsequently, the reaction rate was substituted into the source term of Navier–Stokes (N–S) governing equations based on the CFD theory. Finally, according to the physical characteristics of the top and bottom boundaries of the packed bed during the incineration process, the boundary conditions were determined, and the incineration model of the packed bed was established as well. The establishment of the model is described in detail as follows.

Modeling of the Packed Bed

As a one-dimensional unsteady-state model, BASIC divides the MSW incineration process into four parts, namely, drying, devolatilization, volatiles combustion, and char oxidation. The corresponding chemical reactions and reaction rates of each process are described in Table S1. MSW incineration is a complex physical and chemical process, appropriate assumptions can simplify the simulation process and reduce the amount of calculation, which is inevitable for the simulation work. For the modeling of MSW combustion, six assumptions were made to facilitate the description of this phenomenon: (1) the physical parameters at the same height are consistent with the physical parameters at the center point of the height;[20] (2) MSW is considered as homogeneous porous media;[21] (3) the solid phase and gas phase have the same temperature in the same grid;[22] (4) MSW is considered to be mainly composed of C, H, O, N, and S. The gas species involved in the model are N2, O2, CO, CO2, CH4, H2, H2O, NO, NH3, HCl, SO2, SO3, H2S, S2, CS2, and COS, and the solid species considered are moisture, volatiles, fixed carbon, and ash.[15,19,23] (5) Primary air is injected into the reactor at the bottom of the reactor; (6) the gas is considered to be incompressible and perfect;[24] and (7) the particle size of the MSW particles is constant.

After the drying process, volatile products emerging from the surface of the particles are first mixed with air in the interstices of the particles. Obviously, the combustion of volatile compounds is not only affected by the reaction kinetics (temperature-dependent) but also by the mixed ratio of volatiles to air. The actual volatile combustion reaction rate follows the minimum values of the mixing rate and kinetic rate of the gas phase as follows[25]

The gases are mixed with the surrounding air during combustion; the mixing rate of volatiles under fire can be expressed as follows

The kinetic constants of the chemical reaction of volatile combustion are shown in Table . The reaction rate constant is calculated according to the Arrhenius formula

Table 1

Main Combustion Reactions in the Model

reaction	A	b	E	reaction rate (Rkin)	refs
R1	6.8 × 1015	–1	1.67 × 108	k[H2]0.25[O2]1.5	(18)
R2	5.012 × 1011	0	2 × 108	k[CH4]0.7[O2]0.8	(30)
R3	3 × 108	0	1.26 × 108	k[CH4][H2O]	(18)
R4	2.239 × 1012	0	1.702 × 108	k[CO][O2]0.25[H2O]0.5	(18)
R5	2.75 × 109	0	8.4 × 107	k[CO][H2O]	(18)

Governing Equations and Boundary Conditions

According to the conservation of energy, mass, and momentum, the governing equations are established for the solid phase and gas phase. They are used to describe the combustion phenomena such as flow, diffusion, and reactions of the solid and gas phases in the calculation region of the packed bed. The heat and mass loss from the top and bottom boundaries are governed by the boundary conditions, and there is no inner heat and mass loss inside the bed. The specific equations are described in Table S2.[26]

In this model (Figure ), the bottom boundary layer transfers heat and mass to the higher part, and the top boundary surface transfers heat and mass to the freeboard region. Therefore, the boundary conditions are essential for the heat- and mass-transfer process between the packed bed region and the freeboard region.

Figure 2

Model computing region and grid division.

At the bottom of the bed, the equation for the temperature is written as follows[15]where Ts* is the assumed temperature of the boundary layer and is generally set as the initial primary air temperature.

At the bottom of the bed, the concentration of gaseous species at the boundary layer of the fixed bed is obtained from the following equation[15]

At the top surface of the bed, the temperature and gaseous concentrations are governed by equations similar to eqs and 5.

Due to the large difference in the grid density between the boundary layer and the calculation area, the top surface speed needs to be modified as followswhere u is the velocity of the top boundary, M is the mass of gas out of the layer, and u and M refer to the corresponding factor in the last grid.

Sulfur Formation Model

This section mainly describes the generation and reaction mechanism of sulfur pollutants and their corresponding chemical reaction kinetic models inside the reactor, laying a foundation for the subsequent prediction of concentration fields of various sulfur gas pollutants. In this model, it mainly involves five sulfur substances, SO2, SO3, H2S, CS2, and COS, and eight related chemical reactions, two of which are reversible reactions. The main reaction routes of sulfur species conversion during the combustion are shown in Figure .

Figure 3

Major routes of sulfur conversion.

Among the main reactions routes, the reactions involving sulfur substances mainly occur in the volatile combustion process of the MSW combustion. First, H2S gas is produced from the volatilization (pyrolysis) process. Subsequently, one part of H2S is oxidized in the gas-phase region of the fixed bed to produce SO2 (R6R6), which is further oxidized to SO3 (R7R7, R8R8). In addition, as the temperature increases, the other part of H2S decomposes to S2 gas (R13R13), and S2 reacts with CO, CH4, and H2O (R9R9–R11) in the gas phase of the bed to generate sulfur gas pollutants such as CS2 and COS. A sulfur model with eight global homogeneous reactions is introduced in this work, as illustrated in Table .

Table 2

Gas-Phase Chemical Reactions Regarding Sulfur Species Introduced into the Model

reaction	A	b	E	reaction rate (Rkin)	refs
R6	6.5 × 1014	0	10 800	k[H2S][O2]	(15)
R7	9.2 × 1010	0	8.5 × 105	k[SO2][O2]	(30)
R8	4.4 × 1011	0	2.55 × 107	k[SO3]	(18)
R9	31 081	0	35 564	k[S2]0.75[H2O]	(18)
R10	5.53 × 1010	0	19 320	k[S2][CH4]	(18)
R11	3.18 × 105.	0	55 800	k[S2][CO]	(15)
R12	4.36 × 109	0	1.8 × 105	k[COS]	(31)
R13	3.6 × 108	0	2.01 × 105	k[H2S]	(31)

Solving Method

In the above model description, all of the governing equations are composed of a transient term, a convection term, a diffusion term, and a source term (some equations do not have the convection term and diffusion phase, the correlation coefficient of which can be regarded as 0). Therefore, all of the governing equations can be written into a general equation form as follows

This study uses the finite volume method to divide the entire calculation area into a finite number of volumes, calculates the discrete governing equations for each finite volume, and uses the central difference scheme for the convection term. In this process, the diffusion term is processed with the full implicit algorithm, the source term is processed with the linear treatment, and the governing equation (eq ) is discretized into the form of a linear matrix. All governing equations are solved through the SIMPLE algorithm.[27]

Modeling Validation

For the sulfur model developed, the simulation prediction results are compared with the relevant results of the MSW incineration experiment conducted by Tang et al. in a tube furnace to illustrate the accuracy of the established sulfur model.[28] In this experiment, the initial parameters of the treated MSW are shown in Table :

Table 3

Initial Parameters of the Raw Material

proximate analysis (wt %)				ultimate analysis (wt %)
moisture	volatile	fixed carbon	Ash	C	H	O	N	S
3.57	73.33	12.64	10.46	41.37	7.10	34.22	1.37	1.94

The initial parameters of the experiment were inputted into the developed sulfur model. After the debugging and running processes, the relevant simulation results were compared with the results of SO2 concentration measured in the experiment at 1173 and 1273 K to verify the accuracy of the sulfur model. The comparison results are shown in Figure .

Figure 4

Comparison of simulation and experimental profiles:[28] (a) SO2 concentration (1173 K) and (b) SO2 concentration (1273 K).

Since only SO2 in SO pollutants was studied in the original experiment, this section mainly verified the sulfur model from the perspective of SO2 production. As shown in Figure , the red curve represents the simulation results, while the black curve represents the experimental results. By comparing the production of SO2 at 1173 and 1273 K, the simulated and experimental results are in good agreement. Hence, the compared results illustrate that the development of the sulfur model has a certain degree of accuracy and it can be used for predicting the SO pollutant production during the MSW combustion process.

Results and Discussion

The validated model is used to simulate and predict the main sulfur substances (SO2, SO3, H2S, COS, CS2) and calculate their production under different working conditions. Furthermore, the variation trend of SO pollutants in various working conditions was compared by changing four key parameters in the model: initial temperature, primary air volume, pressure, and material particle size. The simulation results indicate the lowest SO production in the MSW combustion process under different conditions so as to achieve the goal of controlling the emission of SO pollutants.

Effect of Temperature on the Concentration of Sulfur Substances

Figure shows the changes of different sulfur substances (SO2, SO3, H2S, COS, CS2) with time at different initial temperatures (1073, 1173, 1273, 1373 K). It can be appreciated that the model reflects rigorously the strong influence of temperature on the concentration of sulfur substances. This shows that the higher the initial furnace temperature, the faster the reaction rates, which is consistent with the expression of the Arrhenius formula. For SO2, the higher the initial temperature, the lower the production. The peak concentration of SO2 decreases from 158 ppmv at 1073 K to 60 ppmv at 1373 K with a total decrease of 60 ppmv. This shows that the increasing initial temperature has a significant effect on reducing the SO2 formation. In addition, it can be seen from Figure b that the production of SO3 also shows a similar trend to that found for SO2. The peak concentration of SO3 decreases from 125 ppmv at 1073 K to 20 ppmv at 1373 K with a total decrease of 105 ppmv.

Figure 5

Simulation of different sulfur species (a) SO2, (b) SO3, (c) H2S, (d) COS, and (e) CS2 concentration overtime at different initial temperatures (1073, 1173, 1273, 1373 K).

Moreover, as the main sulfur substance, the production concentration peak of H2S increases with an increase of temperature. The peak concentration of H2S increases from 700 ppmv at 1073 K to 1150 ppmv at 1373 K with a high increase of 450 ppmv. However, with a further increase of temperature, the shortening of its release time becomes more and more limited. It can be seen that although the temperature can reduce the production of SO2 and SO3, it can as well cause an increase in the release of H2S. Nonetheless, as the temperature gradually increases, the increasing trend of H2S becomes slower, and its release time becomes shorter.

Finally, for COS and CS2, the overall change trend gradually increases with increasing temperature; it can be seen that the production of COS and CS2 also shows a similar trend that can be found in H2S. The peak concentration of COS and CS2 increases from 35 and 9 ppmv at 1073 K to 72 and 18 ppmv at 1373 K with a high increase of 450 ppmv, respectively, increasing by 37 and 9 ppmv. As observed, the increasing temperature not only advances the overall incineration reaction but also promotes the transformation of S2 to COS and CS2.

Effect of Pressure on the Concentration of Sulfur Species

Because the total density of the mixed gas changes with pressure, it can be known from the ideal gas formula that the higher the pressure, the greater the density of the gas. In this model, the total density of the mixed gas is updated by the ideal gas formula, so it is particularly important to study the pressure change during the entire bed incineration process. In addition, low pressure exists in many high-altitude areas in China (such as Tibet), so it is of practical significance to study the incineration under different pressures, especially for the MSW incineration characteristics under low pressure in plateau areas. Figure presents the predicted overall concentration of sulfur species in the fixed bed as a function of time with different pressures (91.3, 101.3, 111.3 KPa). As illustrated in Figure a,c, when the pressure increases, the concentrations of SO2 and H2S change slightly, while the production of SO3, COS, and CS2 shows an upward trend with an increase of pressure, increasing by 10, 27, and 4 ppmv, respectively. The main reason for the results is that the molecular diffusion coefficient Dg of the gas is affected by the pressure, and its value increase with pressure. The mixture reaction rate Rmix is positively related to the molecular diffusion coefficient Dg of the gas (eq ). From eq , when the value of Rmix is less than the kinetic reaction rate Rkin, the reaction rate is determined by Rmix. Thus, when the reaction rate increases along with pressure, the reaction rates of R7, R10, and R11 determined by Rmix increase as well. Therefore, the production of SO3, COS, and CS2 increases at high pressures. As for the reactions that are mainly controlled by temperature, the value of Rkin is smaller than Rmix, so the reaction (R7, R9, R10, R13) rate is mainly affected by Rkin and the impact of pressure on SO2 and H2S production is relatively small.

Figure 6

Changes of different sulfur species (a) SO2, (b) SO3, (c) H2S, (d) COS, and (e) CS2 over time under different pressures.

Effect of Particle Size on the Concentration of Sulfur Species

This section mainly simulates the changes of various sulfur gas pollutants under the condition of different average particle sizes (40, 50, 60 mm). As shown in Figure a, when the average particle size is 40 mm, the peak concentration of SO2 is 95 ppmv and it is generated at around 170 s. With an increase of the particle size to 60 mm, the peak concentration increase to 152 ppmv, increasing by 58%, but the generation time is shortened to 150 s. Similarly, for SO3, when the particle size is 40 mm, its concentration is only 40 ppmv, but with an increase of the particle size, its peak concentration eventually becomes 100 ppmv, increasing by more than twice. As observed, an increase in the particle size has a greater impact on the generation of SO3. The increase of the peak concentrations of SO2 and SO3 is mainly because the heat transfer between the gas phase and the solid phase in the incinerator bed plays a significant role in the generation of NO when the average particle size increases from 40 to 60 mm. The heat transfer between the gas and solid phases in the fixed bed has a significant effect on the formation of SO. With an increase in the particle size, the heat transfer between the gas phase and the solid phase in the bed increases, the reaction time advances, and the burning rate of the bed increases, which affects the temperature of the bed and leads to an increase in the concentrations of SO2 and SO3.[29] Therefore, SO2 and SO3 generated in the packed bed region increase when the average particle size increases from 40 to 60 mm.

Figure 7

Changes of different sulfur species (a) SO2, (b) SO3, (c) H2S, (d) COS, and (e) CS2 over time under different particle sizes (40, 50, 60 mm).

For H2S, Figure c shows that the changes in the particle size have less effect on the amount of H2S produced; however, when particle size increased from 40 to 60 mm, the concentration of the peak value increased from 580 to 700 ppmv. This shows that the increasing particle size facilitates the occurrence of the volatile pyrolysis process, which leads to a higher level of H2S released into the gas phase. Finally, for the other two substances COS and CS2, their total production has also increased with an increase in the particle size. Their production increased from 43 to 60 ppmv and from 10 to 15 ppmv, respectively. The increasing trend with the particle size can also be attributed to an increase of heat transfer between solid and gas phases in the packed bed region, which promotes the homogeneous reaction on the bed and thus results in an increase of the related gas product production.

Effect of Primary Airflow on the Concentration of Sulfur Species

Since the primary air volume can affect the redox atmosphere in the system and thus affect the generation of various gas-phase products, this study also stimulates the generation of sulfur substances under different primary air volumes. As shown in Figure , the changes of SO2, SO3, H2S, COS, and CS2 generation are simulated under the conditions of different primary airflows (0.04, 0.05, and 0.06 kg/(m3 s)). Figure a shows that when the air volume increases to 0.04 kg/(m3 s), the peak value of the SO2 concentration is 135 ppmv. As the air volume further increases to 0.06 kg/(m3 s), the peak concentration of SO2 gradually decreases to 112 ppmv. Therefore, it can be predicted that as the increase of SO2 in the air gradually convert into SO3, the increase of the primary airflow will enhance the content of N2 and O2 in the system and play the role of air volume to dilute SO2. In addition, Figure b shows that the peak concentration of SO3 increased from 54 ppmv at 0.04 kg/(m3 s) to 81 ppmv at 0.06 kg/(m3 s), which has a total increase of about 50%. Therefore, the simulation further demonstrates that SO2 in the packed bed region will be converted into SO3 at a higher primary air volume, which results in a surge in its peak concentration.

Figure 8

Changes of different sulfur species (a) SO2, (b) SO3, (c) H2S, (d) COS, and (e) CS2 over time under different primary airflows (0.04, 0.05, 0.06 kg/(m3 s)).

For COS and CS2 as well, their total production decreases significantly with an increase of primary air volume in the system. The peak concentration of COS decreases from 110 ppmv at the beginning of 0.04 kg/(m3 s) to 39 ppmv at the end of 0.06 kg/(m3 s), and the peak concentration of CS2 decreases from 21 ppmv at the beginning of 0.04 kg/(m3 s) to 8 ppmv at the end of 0.06 kg/(m3 s), with decreases of 65 and 62%, respectively. It can be seen that an increase of primary airflow significantly inhibits the generation of these two trace substances and inhibits the transformation of S2 to COS and CS2 in the gas phase.

Conclusions

Based on the self-developed one-dimensional unsteady-state bed model BASIC, sulfur chemistry is added to BASIC to predict the concentration of sulfur substances in the fixed bed region under different operating conditions including initial temperatures, pressures, particle sizes, and primary airflow conditions. The formation of sulfur species was discussed from the perspective of the chemical reaction mechanism.

At different initial temperatures (1073, 1173, 1273, 1373 K), the production of SO2 and SO3 decreased by 98 and 105 ppmv, respectively, showing a significant downward trend, while the peak concentrations of H2S, COS, and CS2 showed an increasing trend by 450, 37, and 9 ppmv, respectively.

For different average particle sizes (40, 50, 60 mm), the production of SO2, SO3, COS, and CS2 gradually increased with an increase of the particle size, especially for SO3. The main reason is that the heat transfer between the gas phase and the solid phase in the bed increases with an increase of particle size and the reaction time is advanced, which affects the temperature and leads to the change of its production.

For different primary airflows (0.04, 0.05, 60 kg/(m2 s)), the production of SO3 increases with an increase of primary air volume, while the other products SO2, H2S, COS, and CS2 show a downward trend with an increase of primary air volume due to the enhancement of an oxidizing atmosphere in the system and the dilution effect of sulfur substances.

The suggested optimal operating condition was found to have an initial temperature of 1373 K, a feedstock particle size of 40 mm, and a higher primary airflow rate of 0.06 kg/(m2 s). Pressure has no significant influence on nitrogen species formation.

According to the simulation results, the model reasonably well predicts the major sulfur species. The optimum parameters for the lowest SO production in fixed bed combustion, such as temperature and particle size, can be also predicted. Through the simulation study, the real effects of optimum parameters on the combustion characteristics can be more fundamentally investigated and the direction can be provided for the design and optimization of the MSW fixed bed.