Scholarly article on topic 'Parametric Study and Optimization of Methane Production in Biomass Gasification in the Presence of Coal Bottom Ash'

Parametric Study and Optimization of Methane Production in Biomass Gasification in the Presence of Coal Bottom Ash Academic research paper on "Chemical engineering"

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Abstract of research paper on Chemical engineering, author of scientific article — Muhammad Shahbaz, Suzana Yusup, Angga Pratama, Abrar Inayat, David Onoja Patrick, et al.

Abstract Methane production from biomass gasification is an alternative route compared to conventional techniques for the efforts to reduce the carbon foot print. In the current work, production of methane is studied from steam gasification of palm kernel shell (PKS) in thermo gravimetric analyser (TGA) and mass spectrometer (MS). Response surface methodology (RSM) is applied to investigate the effect of operating parameters and to identify the optimized parameters. The four main process variables were investigated within the specific range of temperature of 650 -750°C, particle size of 0.5-1mm, CaO/biomass of 0.5-2 and coal bottom ash % of 0.02-1. Temperature and CaO/biomass ratio were found to be the most influencing variables on methane production. The optimised conditions obtained were temperature of 750°C, particle size of 0.99mm, CaO/biomass of 1.25 and coal bottom ash of 0.08%. The presence of Fe, Mg, Al oxides in the coal bottom ash catalysed the process and enhanced the methane yield from 37 to 43.3 vol %.

Academic research paper on topic "Parametric Study and Optimization of Methane Production in Biomass Gasification in the Presence of Coal Bottom Ash"

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Procedía Engineering 148 (2016) 409 - 416

Procedía Engineering

www.elsevier.com/locate/procedia

4th International Conference on Process Engineering and Advanced Materials

Parametric Study and Optimization of Methane Production in Biomass Gasification in the Presence of Coal Bottom Ash

Muhammad Shahbaz a *, Suzana Yusupa, Angga Pratamaa, Abrar Inayatb, David Onoja

Patricka , Muhammad Ammara

aBiomass Processing Lab, Centre of Biofuel and Biochemical Research, Department of Chemical Engineering, Universiti Teknologi PETRONAS, Bandar Sen Iskandar, 32610, Perak, Malaysia.. bDepartment of Sustainable and Renewable Energy Engineering, University of Sharjah, 27272 Sharjah, United Arab Emirates

Abstract

Methane production from biomass gasification is an alternative route compared to conventional techniques for the efforts to reduce the carbon foot print. In the current work, production of methane is studied from steam gasification of palm kernel shell (PKS) in thermo gravimetric analyser (TGA) and mass spectrometer (MS). Response surface methodology (RSM) is applied to investigate the effect of operating parameters and to identify the optimized parameters. The four main process variables were investigated within the specific range of temperature of 650 -750°C, particle size of 0.5-1 mm, CaO/biomass of 0.5-2 and coal bottom ash % of 0.02-1. Temperature and CaO/biomass ratio were found to be the most influencing variables on methane production. The optimised conditions obtained were temperature of 750 °C, particle size of 0.99 mm, CaO/biomass of 1.25 and coal bottom ash of 0.08%. The presence of Fe, Mg, Al oxides in the coal bottom ash catalysed the process and enhanced the methane yield from 37 to 43.3 vol %.

© 2016 The Authors.PublishedbyElsevierLtd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.Org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of ICPEAM 2016 Keywords: Methane;Gasification; Biomass; H2; Syn gas; ANOVA; RSM;

1. Introduction

Natural gas is an important part of world energy mix. From last two decades its importance has dramatically increased due to vast utilization in industry. Natural gas has been considered as a clean fuel among the fossil fuel.

* Corresponding author. Tel.: +605-368-7642; fax: +605-368-8205. E-mail address: shabimooz@hotmail.com

1877-7058 © 2016 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license

(http://creativecommons.org/licenses/by-nc-nd/4.0/).

Peer-review under responsibility of the organizing committee of ICPEAM 2016

doi: 10.1016/j.proeng.2016.06.432

Natural gas is not abundantly available and current global proven reserves at current consumption rate are only enough for the next 5 to 6 decade [1].

Bio methane or synthetic natural gas production has an advantage in that it could be used directly in existing gas distribution net without any major modification [2]. The 200-700 EJ per annum availability of biomass [3] has made it as a prominent renewable sources for fuel production like methane (CH4) [4]. Biomass has been utilized for methane production by both digestion and thermochemical conversion in the form of biogas [5] and syngas or synthetic natural gas (SNG) [6]. The production of methane from fermentation of biomass or manure known as biogas are widely used all over world [7]. The biogas production is not commercially viable at large scale due to the problems associated with it regarding pre-treatment process, feeding problem of different type of biomass, inefficient fermentation due to flotation, removal of wasted feed continuously and excess volatile fatty acids [8]. The thermochemical conversions of biomass are classified into pyrloysis, combustion and gasification [4]. Gasification is the most efficient among the above mentioned technologies to convert biomass into methane [2, 4]. The major reactions involved in the gasification of biomass for CH4 production are given below [9].

Bourdouard reaction C + CO2 ~ 2CO +175 MJ/kg (R1)

Methanation reaction C + 2H2 ^ CH4 -75 MJ/kg (R2)

Methanation reaction 2C + 2H2O ^ CH4 + CO2 + 103 MJ/k (R3)

Water gas shift reaction C+ H2O ~ CO + H2 +131 MJ/kg (R4)

Water gas shift reaction CO+ H2O ~ CO2 + H2 - 41 MJ/kg (R5)

The high content of CO and H2 in the product gas is due to water gas shift reaction. This high content of CO and H2 can be converted into methane by methanation reaction. Van der Meijden et al. [3] studied three different types of gasifiers i.e. fluidized, allothermal and entrained flow for the syngas production and conversion to methane by methanator. Molino et al. [2] developed a thermodynamic model for production of methane from syngas via wood gasification. Gasification of biomass has been done by using gasifying agent like O2, steam, air and CO2. Methane production is low in the case of steam due to methane reforming and water gas shift reaction [10]. Gasification process has an advantage to utilize biomass waste for methane production which does not affect cultivated land for food crops. Malaysia is rich in biomass wastes that includes palm oil waste, rice husk, forest residue [11]. This large scale production yields about 51.2 Mt/year of palm oil wastes consisting mainly of palm kernel shell (PKS), empty fruit bunches (EFB) and palm oil fronds (POF). Many researchers utilized palm oil residue for gasification process. Zakir et al. [12] produced 84.2 vol% H2 from steam gasification of PKS at 600 -750 °C in which maximum methane is 11.9 vol% as by product. The lower yield of methane is due to water gas shift reaction and use of commercial Ni catalyst for methane reforming. Mohammed et al. [13] reported about 16 vol% methane production from air gasification of EFB between 700-900 °C.

The use of catalyst does not only enhance the gasification but also directs the targeted product. Basically three types of catalyst are used, namely dolomite, Ni and alkaline metal catalyst [14]. Each catalyst has its pros and cons. Some are effective for tar reduction, some enhanced H2 yield, some reduced CO2, some are costly and some has short active life. Coal bottom ash (CBA) is the waste product of coal power plants. It is mostly dumped or used in construction industry. Recent research explored the presence of some alkali metals and Ca in CBA. Xiong et al. [15] reported the oxides of Fe, Ca, Mg and Al in coal bottom ash. He used CBA as bed material for coal pyrolysis and gasification process and noted the good effect on tar yield. Wood ash has been utilized as catalyst to increase the gasification reactivity [14]. In literature, use of CBA in biomass gasification has very less coverage. Furthermore, very little investigation has been done to produce methane specifically from palm oil waste gasification. Reza et al. [16] used Ni for steam gasification of PKS with polyethylene and reported 12 vol% methane and 76 vol% H2. Khan et al. [17] studied PKS gasification in the presence of a new Fe based catalyst in TGA and gas chromatography set up and obtained about 20 mole % of methane up to 530 °C. Water gas shift reaction and reforming reaction was enhanced at steam to biomass ratio of 1 which suppressed the methane formation [17]. Limited work has been reported for methane yield from direct gasification of biomass. The aim of this investigation is to produce the methane from gasification of PKS in the presence of steam in TGA with MS to measure the evolved gas. In

addition, to investigate the effect of different parameters (temperature 650-750 °C, particle size 0.5-1 mm, CaO/biomass ratio 0.5-2 and coal bottom ash % age 0.02-1 %) on methane yield. RSM is used for the parametric study and optimization.

2. Methodology

2.1. Material

Palm oil wastes PKS was used for methane production obtained from Kilang Sawit Felcra Nasarudin Sdn. Bhd. Malaysia. The moisture content was reduced by oven drying. The larger and coarse particles were granulated into smaller fragments by using ball mill. The pulverised PKS were sieved in the size of 0.5, 0.75, and 1 mm. PKS was choose for methane production due to its higher heating value of 18.46 MJ/kg [18]. The elemental and component compositions were determined experimentally as shown in Table 1.

Table 1: Proximate and Ultimate Analysis of PKS.

Proximate analysis (dry mass fraction basis) Ultimate analysis (dry mass fraction basis)

Volatile matter (%) 80.81 C (%) 48.87

Fixed carbon (%) 14.25 H (%) 5.70

Ash content (%) 4.94 N (%) 1.01

HHV MJ/kg (%) 18.82 S (%) 0.21

O (%) by difference 44.3

Coal bottom ash (CBA) is used as catalyst due to presence of alkaline metal and Ca within it [19]. CBA was collected from TNB Janamanjung Sdn Bhd power plant Selangor Malaysia. The component composition was determined by X-ray fluorescence (XRF) as shown in Table 2. The CO2 removal in gasification is very costly method that affects the overall economies of the process [20]. CaO is used to absorb the CO2 in an in-situ process to avoid the cost of additional equipment. CaO was acquired from Kinetic Chemical Sdn. Bhd. Malaysia. CaO and CBA both were grounded to the size of 0.250 mm.

Table 2: XRF Analysis of coal bottom ash. Compound SiO Fe2O3 CaO AbO3 MgO K2O3

Concentration wt % 44.1 24.3 13 9.21 1.88 1.25

2.2. Design of experiment

In order to see the parametric and their interactive effect on methane production experiment were designed based on central composite design (CCD) by using Design Expert 8® software. This gives good information as compared to classical "one factor at a time" method. In the RSM a relationship between process variables and responded variables has been developed. This will help to find area at which respond varied according to variation in process parameters in design range [21]. The stable response within this area enterprise the optimum input process variables. The developed surface is equally effective with small and large no of experiments. In this study methane (%) is the output variables. It responded to four independent variables, A, temperature of 650-750°C, B, particle size of 0.5-1 mm, C, CaO/biomass of 0.5-2 and D, coal bottom ash % of 0.02-0.1. A total of 46 experiments were designed in which includes 8 axial runs, 6 centre runs and 32 factorial runs. Central runs were duplicated runs. Factorial runs were replicated by a factor of 2 for precision in the experiment as shown in Table 3.

2.3. Gasification in TGA-MS set up

The set up used for steam gasification of PKS is shown in Fig 1. TGA (EXSTAR TG/DTA 6300, from SII) was

attached with mass spectrometer to measure the evolved gas. In order to supply the steam a setup of heater and micro pump was used. 5 mg of biomass was used in each run and other materials were admitted according to design runs. The biomass sample was heated up to the desired temperature with 100 ml/min flow rate of N2 at heating rate of 25 °C/min. Trapped gases were removed at 50 °C by keeping the sample temperature constant for 20 minute. Steam was tuned at 110 °C to evade the liquefaction. The sample was kept constant at desired gasification temperature for complete gasification process for about 30 minute. Steam to biomass ratio was maintained at 0.5 to accelerate the methanation reaction.

Fig. 1 Process flow diagram Table 3: Experiment design with Response.

Runs Temp Particle CaO/PKS Bottom Methane Runs Temp Particle CaO/PKS Bottom Methane

(°C) Size (mm) Ash % (%) (°C) Size (mm) Ash % (%)

1 700 1.34 1.25 0.06 40.4516 24 700 0.75 -0.53 0.06 39.1204

2 700 0.75 3.03 0.06 40.4018 25 700 0.75 1.25 0.16 39.8395

3 650 1.00 2.00 0.10 38.6809 26 650 0.50 2.00 0.02 43.4149

4 819 0.75 1.25 0.06 43.0585 27 650 0.50 2.00 0.10 39.638

5 700 0.75 1.25 0.06 37.3036 28 750 1.00 0.50 0.10 43.925

6 650 0.50 0.50 0.02 40.5410 29 650 1.00 0.50 0.02 39.315

7 700 0.75 1.25 0.06 37.303 30 750 0.50 2.00 0.10 37.8072

8 750 1.00 0.50 0.02 41.993 31 700 0.75 1.25 0.04 38.3989

9 750 0.50 0.50 0.10 41.0278 32 750 0.50 0.50 0.02 40.2671

10 650 1.00 0.50 0.10 41.0556 33 750 1.00 2.00 0.02 39.6808

11 650 1.00 0.50 0.10 41.0556 34 650 0.50 0.50 0.02 39.1698

12 750 0.50 2.00 0.02 40.468 35 650 0.50 2.00 0.02 41.057

13 750 0.50 0.50 0.02 40.669 36 750 1.00 0.50 0.02 41.886

14 750 0.50 2.00 0.10 37.8072 37 581 0.75 1.25 0.06 40.1287

15 650 1.00 2.00 0.02 41.4869 38 750 0.50 2.00 0.02 39.6990

16 650 1.00 0.50 0.02 38.7141 39 750 1.00 2.00 0.02 38.8636

17 650 0.50 0.50 0.10 38.681 40 700 0.75 1.25 0.06 37.303

18 650 1.00 2.00 0.02 38.4170 41 750 0.50 0.50 0.10 40.3238

19 650 1.00 2.00 0.10 38.6809 42 650 0.50 2.00 0.10 39.307

20 750 1.00 0.50 0.10 43.06 43 700 0.16 1.25 0.06 39.8891

21 700 0.75 1.25 0.06 37.303 44 650 0.50 0.50 0.10 39.4842

22 700 0.75 1.25 0.06 37.30367 45 750 1.00 2.00 0.10 41.2403

23 700 0.75 1.25 0.06 37.30367 46 750 1.00 2.00 0.10 41.2403

3. Results and Discussions

3.1. Regression model equation Development

The CCD was used to obtain a relation between methane production from PKS gasification and the process variables. The model was also incorporated with the combine and interactive effect of process variable on methane vol % (respond variable). The replication of central runs and repetition of factorial runs by one factor helped to measure and minimized the experimental error respectively. The higher order polynomial suggested that quadratic model to fit this experimental data for methane vol% by using regression analysis .The experimental results is shown in Table 4. An equation is developed by the model in terms of coded factor of significant terms that shows the relation between process variables and their combine and interactive effect on methane vol%.

Methane (%) = 37.57371 + 0.420826*A - 0.260219*B - 0.47958*C - 0.13219*D + 0.55336*A*B - 0.5941*A*C + 0.2636677*A*D -0.263677 - 0.36712*B*C + 0.618495*B*D - -0.46073*C*D (1)

3.2. Statistical Varian analysis

The variance analysis (ANOVA) has been made for the justification of the model. The (ANOVA) results of effective variable and their combine effect on methane vol% as shown in Table 4. The lower P-value > 0.0001 and higher F-value of 14.00189 shows the significance of the model. Normally P-value is related to the model significant and F-value is related to the influence of process variables on methane vol %. The operating factor CaO/biomass, C and temperature, A are more significant and have more influenced on methane yield. The effects of the other two variables which are the particles size and coal bottom ash % are less. On the other hand the combine effect of D with A and C is most prominent. The "Lack of Fit" is not significant, that shows that all terms in the model are significant. The higher value of R2 is 0.96 is near to unity which showed higher quality of the model. The difference between Adj-R2 of 0.91 and Predicted-R2 of 0.81 is less than 0.20 and shows a good agreement between variance and response. According to varian analysis the Adj-R2 gives explanation on the estimation of variation in the model and the predicted R2 measures the quality of prediction of the response model [22].

Table 4: Result of ANOVA Analysis.

source Sum of squares df Mean square F-value P-value

Model 115.0109 14 8.215063 14.00189 < 0.0001

A-Temperature 7.670638 1 7.670638 13.07396 0.0010

B-Particle Size 2.932952 1 2.932952 4.99897 0.0327

C-CaO/Biomass 7.926229 1 7.926229 13.50959 0.0009

D-Coal Bottom Ash % 0.587824 1 0.587824 1.001896 0.3246

AB 9.797789 1 9.797789 16.69951 0.0003

AC 11.2947 1 11.2947 19.25087 0.0001

AD 2.22481 1 2.22481 3.792003 0.0606

BC 4.312832 1 4.312832 7.35086 0.0108

BD 12.24116 1 12.24116 20.86403 < 0.0001

CD 6.792603 1 6.792603 11.57742 0.0019

Residual 18.18805 31 0.586711

Lack of Fit 7.860239 10 0.786024 1.598258 0.1753

Cor Total 133.1989 45

significant

Not significant

R2 0.96 Adj- R 2 0.90

3.3. Parametric study

The individual and combine effect of variables on methane production has been investigated by using 3D graph as shown in Fig 2a -d. The CaO/biomass, C is the most influencing variables on methane (%) having lower p-value of 0.0009 and higher F-value of 13.509. Temperature is almost equally influencing variable with p-value of 0.0010 and F- value of 13.07396. The smaller p-value of 0.001 and larger F-value of 19.352 depicted the combine effect of both variables which influenced the amount of methane (%) as shown in Fig 2a. It is observed from Fig. 2a methane vol (%) decreased to 37.1 vol (%) by increasing the temperature from 650 to 700 °C. But the methane yield started increase after 700 °C and reached up to 40.5 vol % at 750 °C. Similar behaviour is observed for particle size effect. Slight drop in maximum yield to 40.2 vol % at 750°C is observed as shown in Fig 2c. The drop in methane yield is due to steam that enhanced the water gas shift reaction and methane reforming [23]. The increased in methane production at higher temperature is due to presence of Fe2O3 that react with H2 produced at 500 °C and Fe that accelerated the methanation reaction [24]. The higher yield of methane which is more than 40% is due to low steam to biomass ratio of 0.5 that suppressed the WGS reactions.

0 50 650 00 0 02 650

(a) (b)

Fig.2 Effect of opreating parameters in the range of Temp A, 650-750 °C , Particle size B 05.-1 mm, CaO/biomass 0.5-2 and Coal bottom ash % D 0.02 - 1

The CaO/biomass, C is the most influencing variable. The methane % decreased from 37.8 to 37 by increasing the CaO/biomass C till 1.25 and further increased up to 38.6 vol % as depicted in Fig. 2a. Similar kind of trend has shown for the effects of combination of coal bottom ash % D meet maximum value of 37.4 as shown in Fig 2c. CaO is used to absorb the CO2. The increased in methane yield is due to less amount of steam that suppressed the WGS reaction and in-situ deactivation of CO2 which accelerate methanation [20].

Particle size, B and coal bottom ash % D are relatively less influencing variable than others indicated by (P-value 0.0327 and 0.326) and (F-value 4.99a and 1.009) respectively. But their combine effect is higher in all combination as shown by smaller P-value <0.0001 and largest F- value of 20.864 as described in table 4. The surface developed by their combined effect is shown in Fig 2d. The methane % increased when particle size decreases up to 0.75 mm and then starts to increase to 40 vol% at 1 mm particle size. The increase in methane % by decreasing particle size is due to high active surface area available for reaction at smaller particle size. Coal bottom ash % that was used as a catalyst in this study the methane (%) dropped up to a certain value by increasing coal bottom ash % D to 0.06 % and rose up to 39.2 vol%. CBA shows same trend for combined study with CaO/biomass and temperature, A with some variation in maximum yield as shown in Fig. 2b and 2c. The presence of Fe and MgO content enhanced the methane yield was identified by XRF analysis. The effect of these oxides is also reported by many researchers [25]. Zakir et al. [12] shows that methane yield is 1.33 vol% for particle size range of 0.2-0.5 mm and 11.43 vol % with 1 mm particle size.

3.4. Optimization

The obtained experimental results were utilized to determine the optimized operating parameters for methane yield. Using numerical method, the operating factors, temperature of 750 °C, particle size of 0.99 mm, CaO/biomass of 1.25 and Coal bottom ash % of 0.08 were obtained reached to 40.73 vol% methane. Three confirmation runs were carried out at this operating condition and standard deviation was calculated as given in Table 5. The maximum standard deviation was 0.42. The results showed a close agreement between predicted and actual values.

Table 5: Predicted and actual runs and optimized values.

Predicted Confirmation runs Std dev.

Run 1 Run 2 Run 3

Temperature(°C) 750 750 750 750 -

Particle size (mm) 0.99 0.99 0.99 0.99 -

CaO/biomass wt/wt 1.25 1.25 1.25 1.25 -

Coal bottom ash % 0.08 0.08 0.08 0.08 -

Methane (%) vol 40.799 40.732 40.81 40.89 0.42

4. Conclusion

In this study, the steam gasification of PKS was carried out in TGA integrated with MS to measure the methane vol (%). The effect of four operating parameters such as temperature °C, particle size mm, CaO /biomass, and coal bottom ash % were studied by using RSM. The CaO/biomass ratio and temperature were the most influencing variables on methane vol (%). The CaO was used as CO2 adsorbent. The coal bottom ash used as catalyst to enhance the methane production as an alternative catalyst for the system. The optimized values of parameters including temperature of 750 °C, particle size of 0.99 mm, CaO/biomass of 1.25 and coal bottom ash % of 0.085 were determined by using RSM. The maximum methane production was obtained as 40.732 vol % at optimum condition. This high yield of methane production was due to limited amount of steam and due to the presence of oxides of Mg and Fe in the CBA.

Acknowledgment

The authors are grateful to Ministry of Higher Education Malaysia to finance this research under Longterm Research Grant Scheme (LRGS) project. The authors also thankful to TNB Janamanjung Sdn Bhd power plant Selangor Malaysia for supplying the material.

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