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Biofuels and Biomass

Solid waste as a renewable source of energy: A comparative study on thermal and kinetic behaviour of three organic solid wastes Arun K Vuppaladadiyam, Ming Zhao, Muhammad Zaki Hassan Memon, Abdul F. Somroo, and Wei Wang Energy Fuels, Just Accepted Manuscript • DOI: 10.1021/acs.energyfuels.9b00661 • Publication Date (Web): 17 Apr 2019 Downloaded from http://pubs.acs.org on April 18, 2019

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The present work aims to analyze the feasibility of considering organic solid waste biomass for bioenergy production via pyrolysis. 252x147mm (300 x 300 DPI)

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Solid waste as a renewable source of energy: A comparative study on thermal and kinetic behaviour of three organic solid wastes Arun K. Vuppaladadiyam†, Ming Zhao†⁑*, Muhammad Zaki Memon‡, Abdul F. Somroo†, Wang Wei†⁑





School of Environment, Tsinghua University, Beijing 100084, China.

Energy and Environment Engineering Department, Quaid-e-Awam University of Engineering, Science and Technology, Nawabshah 67480, Pakistan



Beijing Engineering Research Center of Biogas Centralized Utilization, Beijing 100084, China.

Keywords: Solid waste, biomass, pyrolysis, thermogravimetric, kinetics, iso-conversional methods.

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Abstract

Pyrolytic characteristics of three different organic solid wastes, municipal solid waste (MSW), digested MSW (DMSW) and digested swine manure (SWD) were investigated at heating rates 10, 15 and 20 °C min-1 in a thermogravimetric analyzer coupled with mass spectrometer. Three stage of devolatilization, dehydration (0 – 200 °C), decomposition of major structural components (200 – 500 °C) and decomposition of solid residue (500 – 800 °C), appeared during the pyrolysis of all the samples. The major devolatilization stage (stage II) is characterized with three peaks at 319, 379 and 438 °C for MSW, two peaks at 339 and 430 for DMSW and one peak with a shoulder on the right at 332 and 444 °C for SWD respectively. The evolved gas species were quantified by using a semiquantitative approach and H2, CO and CO2 were noticed to be predominant gas species in the above mentioned range. While the evolution of H2 is mostly temperature dependent, the evolution of CO and CO2 occurred all through the run. Isoconversional methods along with compensation effect and master-plots were used to determine the kinetic-triplet for the pyrolysis process. The mean activation energies were 172.02 – 172.3, 202.21 –

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202.55 and 213.84 – 215.22 kJ mol-1, while the pre-exponential factor were 1.81×1010, 1.04×1018 and 2.26×1019 for MSW, DMSW and SWD, respectively.

1. Introduction The solid waste sector has been reported to be one of the principal contributors to grave environmental issues around the world. It is reported that the amount of municipal solid waste generated globally would reach 2.2 billion tons per year by 2025.4 The ever growing population and continuous change in the life style has a significant impact on the generation of solid waste in China. In China, it is estimated that around 200 Mt yr-1 of municipal solid waste and 850 Mt yr-1 of animal manure is generated.5 Additionally, China produces around 728–750 and 200–220 Mt yr-1 of agricultural residues and forest biomass, respectively.6 These considerable amounts of wastes present a serious threat to the environment if they are not managed properly. It is reported that solid wastes are major source of water pollution, mainly through the transfer of nitrogen (N) and phosphorus (P) leading to eutrophication.7 Furthermore, these waste are more recognized as pollutant and their potential as bioenergy resource is neglected. However,

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use of solid wastes as bioenergy feedstock could reduce waste disposal problems and alleviate pressure on environment by providing clean energy.8 In particular, generation of energy from municipal solid waste (MSW) and livestock manure eliminates the most common problems, such as reduction in large volumes to be disposed,

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unwanted

transfer of pathogens into ecosystem, eutrophication caused by the leaching of nutrients into nearby water bodies etc.10 Till date, anaerobic digestion (AD) has been widely acknowledged as a means to add value and stabilize solid wastes. However, the high CO2 content of biogas generated from AD process impairs the fuel quality and necessitates several purification steps. Additionally, the carbon deposited in the microorganisms lowers the carbon conversion from manure to biofuels. Pyrolysis is one of the most widely applied method used to convert biomass into highenergy content fuels, which can later be used for internal combustion engines and gas turbines after an intermediate process.11 When compared to gasification and combustion, pyrolysis possesses the following advantages: (i) it does not require high temperatures, (ii) anaerobic conditions,12 and (iii) generation of high quality of oil.13 A number of researchers tested the thermal and kinetic behavior of biomass in thermogravimetrc

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analyzer (TGA) coupled with a mass spectrometer (MS) to establish their potential as a bioenergy resource.14-17 The use of isoconversional methods is the easiest and the most reliable way to determine the kinetic triplet, which include pre-exponential factor, apparent activation energy and reaction mechanism. Furthermore, the International Confederation for Thermal Analysis and Calorimetry (ICTAC) highly recommends the use of isoconversional models to determine the kinetic parameters for biomass pyrolysis.18-19 As the composition of solid waste varies with region, it is important to investigate the pyrolysis and kinetic behavior of the selected solid wastes to understand and extract necessary information regarding their thermal degradation and evolved gas species. Therefore, in the present study, an attempt has been made to access the potential of three categories of solid waste namely, MSW, digested MSW (DMSW) and digested swine manure (SWD), as feedstock for thermochemical conversion. The three solid wastes, MSW, DMSW and SWD were pyrolyzed in a TGA coupled with MS to understand the thermal behavior and evolved gas species. Additionally, two isoconversional methods (Friedman method and Kissenger Akira-Sunnose) were used to determine the apparent activation energy, while compensation effect was used to evaluate the pre-exponential

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factor. The reaction mechanism function was identified by using compensation effect and Z(α) master plots method. Most widely used mechanism functions can be found in the literature

20-21.

The results thus obtained can be considered supportive in designing and

scale-up of reactor for thermal conversion of solid waste biomass.

2. Experiment and Methodology 2.1. Biomass preparation and characterization Municipal solid waste was synthetically prepared in the lab based on the available literature. Different fractions of MSW, such as food waste, paper, textile, rubber and wood, are mixed according to their proportions in real MSW.22 Partially digested manure was collected from swine manure anaerobic digestion plant Donghua, Beijing. MSW and swine manure were then digested in an Automatic Methane Potential Test System II (Bioprocess Control, Sweden) to completely digest the samples. The digestion process was run in triplicates, in a 0.6 L reactors, to ensure the complete digestion. The system consisted of three units: Unit A, a water bath containing 15 glass bottles for anaerobic digestion (AD) and is maintained at mesophilic temperature (35 ˚C); Unit B, CO₂

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Adsorption by the using 3M sodium hydroxide (NaOH); and Unit C, in which the volume of CH₄ released from Unit A was automatically recorded. A mixing rod with slow mechanical rotation was used in each bottle in Unit A. The run was stopped after ensuring the methane generation was less than 10 mL per day. Digestion characteristics of MSW and swine manure, as they are out of the scope of current study, are not discussed. The samples were shredded in a grinder and then sieved to a diameter less than 0.2 mm. A EuroEA3000 Elemental Analyser was used to detect carbon, hydrogen, and nitrogen fractions, and sulfur fraction was determined with 5E-AS3200B Automatic Coulomb Sulfur Analyzer. Oxygen is reported as the difference of total and sum of carbon, hydrogen, and nitrogen. The results of elemental (proximate and ultimate analysis) and structural components (cellulose, hemicellulose and lignin) analysis are reported in Table 1. Table 1. Characterization of biomass samples

Parameters

Sample

MSW

DMSW

SWD

7.13

6.88

5.01

VM

52.73

42.79

53.7

FC

6.38

9.21

4.53

Proximate analysis (wt Moisture %)

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Ultimate analysis (wt %)

Structural analysis (%)

Ash

39.7559

47.61

36.75

C

55.67

31.83

28.37

H

7.57

4.5

4.18

O

33.99

60.53

64.64

N

2.77

3.14

2.81

S

0.43

0.78

0.79

7.38

7.67

6.49

Cellulose

61.74

50.72

59.31

Hemicellulos

12.42

9.49

14.7

component Lignin

e 2.2. TG-DTG-MS Analysis A thermogravimetric analyzer (TA-Q600) coupled with mass spectrometer (Hiden HPR20) was used to assess the biomass samples for its thermal behavior and evolved gas species. A sample of ca. 3 mg in weight was used for each run. The samples were heated from room temperature to 800 °C in an inert atmosphere, maintained by using argon (Ar), at a flow rate of 500 mL min-1, as purge gas. For each sample, the experiments were conducted in two phases. In the first set of experiments, a constant heating rate of 15 °C min-1, was used and the weight loss along with evolved gas species were recorded.

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During the second set of experiments, multiple heating rates, 10 and 20 °C min-1, were used to obtain the data necessary for evaluating the kinetic parameters for the pyrolysis process. In order to evaluate the evolved gas species, a semi-quantitative approach as described in work done by Zhao et al.23 was used. The MS ionises the gas molecules and differentiates the resulting positive ions based on their m/z ratio. The ions scanned by MS and their respective gas species are listed in Table 2. Table 2. Ion fragments and their representative gas species. Ion

m/z

Representative species fragments

2

H 2+

Hydrogen

15

CH4+

Methane

28

CO+

Carbon monoxide

40

Ar+

Argon

44

CO2+

Carbon dioxide

2.3. Kinetic analysis

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Pyrolysis of biomass varies from feedstock to feedstock because of the chemical compositions in the material. However, the process of pyrolysis proceeds as follows: Biomass  Char  Volatiles  Gases

(1)

The rate constant k(T), according to Arrhenius equation, can be defined as follows:

k (T)  Ae

(

 E ) RT

(2)

where A (s-1), Eα (J mole-1), R and T (°K) refer to pre-exponential (or “frequency”) factor, apparent activation energy of the reaction, universal gas constant (8.314 J mol-1 K-1), and absolute temperature, respectively. The degree of conversion (α) reflects the thermal decomposition and can be defined as follows:



m0  mt m0  m

(3)

where m0, m∞, mt reflects the initial, final and instantaneous masses during thermal decomposition, respectively. The kinetics of a heterogeneous solid state reaction can be defined as:24 E

( ) d  k (T) f ( )  Ae RT f ( ) dt

(4)

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where, f (α) represents a reaction mechanism function and t stands for time. Taking logarithm of Eqn. (4) results in Friedman equation,25  d ln   dt

Ea ( )    ln  A( ) f ( )   RT 

(5)

As the temperature is a function of time and increases with a constant heating rate (β), heating rate can be defined as;



dT dT d   dt d dt

(6)

Form Eqns. (2) and (6), E

d A ( RT )  e f ( ) dT 

(7)

The integrated form of f (α) is stated as follows;

g ( )  



0

 Ea

d A T ( RT ) dT   e f ( )  T0

(8)

The above integral has does not have an exact solution and needs to be solved by using approximations or numerical methods. Given their excellent adaptability and validity, isoconversional methods were considered to evaluate the apparent activation energy of pyrolysis process. Thus two isoconversional model free methods, one from

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each category, differential (Friedman method) and integral (Kissinger-Akahira-Sunose) methods were selected to obtain the apparent activation energy (Eα). Further, Eα obtained from Friedman method was used to obtain pre-exponential factor and reaction mechanism function. The Kissinger-Akahira-Sunose (KAS) method is as follows:26

ln(

 T

2

)  ln[

E AR ]  E g ( ) RT

(9)

The slopes of straight lines, obtained by plotting ln(β/T2) vs. 1/T (KAS method) and (ln(dα/dt) vs. 1/T (Friedman method), can be used obtain the apparent activation energy for the conversion process. 2.3.1. Evaluation of pre-exponential factor and reaction mechanism Compensation effect is defined as a strong linear relationship between Arrhenius parameters, lnAi and Eαi, obtained under a single heating rate. The pre-exponential factor (Aα), as it is lumped together with mechanism function f(α), cannot be accurately evaluated by model-free methods such as Friedman or KAS methods. However, the Aα

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can be accurately evaluated by employing compensation effect.19, 27-28 Taking logarithm and re-arranging terms in Eqn. (4),  1 d  E  ( ln    ln Ai ( )  RT  fi ( ) dt 

(10)

where, i refers to the mechanism function listed in Table 1. Every mechanism function from Table 1, when substituted in Eqn. (10) yields a pair of lnAi and Eαi. The compensation equation can then be given by lnAi = a*Eαi + b*

(11)

By linear fitting different pairs of ln Ai and Eα,i the values for a* and b* can be obtained and by using the obtained from isoconversional method the values of A(α) can be obtained from Eqn. (12), lnAα = a* Eα + b*

(12)

From Eqn. (4), by re-arranging the terms, the reaction mechanism function can be defined as,  d    E   f ( )     A exp     dt    RT  

1

(13)

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By using the values obtained for Aα and Eα and experimental values obtained for (dα/dt) and Tα, in Eqn. (13), the mechanism function f(α) can be numerically constructed. It should be noted that all the available reaction mechanism functions listed in Table 1 can be categorized either as accelerating, decelerating or sigmoidal. While, the mechanism function obtained by employing compensation effect categorizes the f(α) into any of these three categories, master-plots method can be used to exactly identify the mechanism function by matching the experimental curves to theoretical curves. In the present study,

Z(α) master-plots method

16

was employed and by using the experimental values

obtained for dα/dt) and Tα the reaction mechanism can be obtained by using Eqn. (14): Z() f ( ) g ( ) 2   T T0.5   d  dt  Z   0.5 f   0.5 g   0.5

 d  dt 0.5

(14)

where, 0.5 implies conversion at α = 0.5. The experimental curves obtained from the term on the right hand side of Eqn. (14) are matched against the theoretical curves obtained from the middle term of Eqn. (14) to obtain the possible reaction mechanism function.

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The other important thermodynamic parameters such as, enthalpy (ΔH), Gibbs free energy (ΔG), and change in entropy (ΔS) were evaluated by using Eqs. (15) to (17):29-30

H  E  RT

(15)

k T  G  E  RTm ln  B m   hA 

(16)

S 

H  G Tm

(17)

where, kB is the Boltzmann constant (1.381 × 10-23 J K-1); Tm is the DTG peak temperature; h is the Plank constant (6.626 × 10-34 J s). 3. Results and discussions 3.1. Thermal behavior of solid wastes The thermogravimetric (TG) and derivative thermogravimetric (DTG) curves for the pyrolysis of three solid wastes, which include MSW, DMSW and SWD, at a constant heating rate of 15 °C min-1 are considered. Fig. 1 presents the mass loss profiles of all the samples selected in this study. It can be noticed from Fig 1a, that the mass loss pattern of MSW vary significantly with the other two forms of wastes, while the mass loss pattern of the digestates (DMSW and SWD) were relatively similar. The overall pyrolysis

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process for all the three samples can be divided in to three stages. In stage I (temperatures below 150 °C), a negligible weight loss was noticed for all the samples, which can be attributed to dehydration and removal of lighter hydrocarbons.31 For all the samples, the second stage occurred in the temperature range 150 – 500 °C. For MSW, three distinct peaks, at 319.38, 379.64 and 438.49 °C and a shoulder at 211.53 °C were noticed. The shoulder on the left of the first peak can be attributed to the degradation of pectin and hemicellulose that is available in wood, fruit and vegetable portion of MSW.32-34 The first peak in stage II, at 319.38 °C can be attributed to the cellulose which is a major constituent in wood. Additionally, MSW contain food, vegetable and fruit wastes, which contain significant proportion of cellulose and food waste, by nature, is starch.35 A similar results were reported for pyrolysis of food and vegetable wastes, were the major peak is because of cellulose degradation.36-37 The second peak at 379.64 °C can be ascribed to the pyrolysis of rubber or paper waste. Similar characteristics were reported in literature.38-39 The third peak at 438.49 °C can be attributed to the degradation of plastic waste in MSW.38, 40 A slight mass loss can be noticed in the third stage and could possibly be because of the degradation of carbonaceous matter.

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For DMSW and SWD, the degradation pattern is noticed to be similar, except that DMSW is characterized with two distinct peaks in the second stage, while SWD is characterized with a single peak. A small weight loss can be noticed for two samples in the first stage (< 150 °C), which can be attributed to the dehydration and removal of lighter hydrocarbons, as it happened in case of MSW. In the second stage, 150 – 500 °C, the DTG curve of DMSW is characterized with two peaks at 339 and 430 °C. The two peaks can be attributed to the degradation of proteins, cellulose and hemicellulose and plastic components, respectively, remained after digestion. The temperature for the first peak of DMSW is noticed to be higher than the temperature for the first peak of MSW. The plausible reason could be the labile organic matter in MSW was biologically degraded during anaerobic digestion.41

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Figure 1. Thermal decomposition process of solid waste samples TG-DTG curves for (a) MSW, (b) DMSW and (c) SWD.

For SWD sample, the second stage of pyrolysis was noticed in the temperature range of 150 – 500 °C, as it was seen in the other two samples. Unlike the other two sample, a single peak followed by a shoulder was noticed for SWD. The main peak at around 332 °C and a shoulder at around 444 °C were observed, which can be ascribed to degradation of protein, cellulose and hemicellulose and lignin and N-containing compounds,

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respectively. As lignin is thermally more stable, its degradation happens all thorough the second stage.15 In the third stage 500 – 800 °C a weak weight loss was noticed for all the samples and a significant peak was noticed at 620, 679 and 690 °C for MSW, DMSW and SWD, respectively. The weight loss in this stage can be attributed to the decomposition of inorganics, such as calcium carbonate.42 Unlike the raw substrate, the anaerobically digested substrates had lower weight loss contents and rates, in accordance with previous studies.43-44 The lower volatilization could be due to the inaccessibility of components and shielding effect of lignin.41 The characteristic parameters for the samples tested in this study are presented in Table 3. Table 3. TG-DTG characteristics of the solid waste samples Main pyrolysis stage (150-500 ⁰C) Heating Temperature (⁰C)

DTGmax

Wt. loss

rate Materia

Peak (⁰C min-1)

l

Initial (Ti)

(mg min-1

Final (Tf)

(%) (Tp)

)

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MSW

15

162

496

438

0.44

76.01

DMSW

15

201.2

489.2

339

0.26

42.38

SWD

15

188.1

496.13

332

0.24

32.731

3.2. Analysis of evolved gas species The gaseous composition from the pyrolysis of solid wastes were analyzed by an online MS coupled to TGA. The trends of evolved gas species and total gas yields for the three samples are presented in Fig. 2 (a) – (d). In agreement with the high oxygen contents in the biomass samples, as shown in Table 2, the production of oxygenated gases such as CO and CO2 was found to be high, which is in agreement with the studies done on biomass reported with high oxygen content.45 The evolution of CO and CO2 was observed throughout the run. Two peaks were noticed for the evolution of CO2 for all the samples, one in the stage II (200 – 500 °C) and the other in stage III (500 – 800 °C). The release of in the stage II can be attributed to the cracking and reforming of carboxyl (COOH) and carbonyl (C=O) groups.46 The two distinct peaks for MSW, (at 309 and 615 °C), DMSW (at 332 and 659 °C) and SWD (at 333 and 688 °C) can be attributed to the decomposition

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of volatiles and solid residue, as it is noticed in the thermogravimetric analysis of the three samples. Similar results were noticed for the pyrolysis of municipal solid waste and cattle manure.47-48 However, the evolution trends of CO were noted to be different for SWD when compared with the other two biomass samples. There were two distinct peaks noticed in the second stage for MSW and DMSW at 301 and 436 °C and 335 and 443 °C, respectively. The plausible reasons for the first peaks could be the decomposition of cellulosic based materials and dissection of ether bonds (R–O–R’),49 suggesting the decomposition of paper waste. The second peak could be could be as a result of degradation of plastic waste, as the rich carbon content of plastic waste were oxidized to CO and CO2.47 For SWD waste biomass, the one peak was noticed for CO at 333 °C, which could be possibly due the decomposition of volatiles. In the stage III (500 – 800 °C), a distinct peak for CO2 evolution was noticed at 615, 658 and 683 °C for MSW, DMSW and SWD, respectively and could be mainly due to the decomposition of solid char residue. The release of CO in the stage III noticed to be constant. However, for DMSW and SWD a peak at 677 and 693 °C, respectively, was noticed could be due to the occurrence of Boudouard reaction. The evolution trends of H2 appear to be similar for

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all the samples. H2 started to get released from 400 and continued thorough out the temperature range. The main reason for H2 release can be due to the tar cracking and reforming reactions. There was very little CH4 evolution noticed in all the samples. The total gas yields are presented in Fig. 2 (d). The total gas yields for the pyrolysis of the samples followed the order MSW > DMSW > SWD.

Fig. 2. Gas yield rates for samples (a) MSW (b) DMSW, (c) SWD, (d) cumulative gas yields for all the samples.

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The ratio of carbon dioxide to carbon monoxide (CO2/CO) can be used to describe the complex processes occurring during the conversion process. The ratio of CO2/CO for the samples investigated in this study are presented in Table 4. The ratio of CO2/CO did not vary much with the heating rate for the three organic solid waste samples. The highest ratio was noted for MSW at heating rate 20 ⁰C min-1 and the lowest was noticed for SWD at eating rate 15 ⁰C min-1. The pyrolysis of few materials results in low CO2/CO ratio because of insufficient oxygen to convert carbon atoms to CO2.50. Similar results were reported by few other researchers during the pyrolysis of coal and char 51 and plastics52. Usually, the values of CO2/CO decrease by decrease in the concentrations of O2.50

Table 4. CO₂/CO ratio for solid waste samples investigated in this study

Material

MSW

Gas species

Heating rate (⁰C min-1)

(mmol g-1)

10

15

20

CO

4.81

4.42

3.81

CO₂

6.06

5.83

5.53

CO₂/ CO

1.26

1.32

1.45

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DMSW

SWD

CO

3.01

3.89

2.53

CO₂

4.17

4.67

3.40

CO₂/ CO

1.38

1.20

1.35

CO

2.89

3.04

2.58

CO₂

2.72

2.44

3.28

CO₂/ CO

0.94

0.80

1.27

3.3. Kinetics and thermodynamic analysis 3.3.1. Evaluation of kinetic triplet In the design and optimization of a reactor for a thermochemical conversion, the description of transport phenomena along with chemical kinetics are considered crucial.53 The thermogravimetric data, obtained at heating rates 10, 15 and 20 °C min-1, and isoconversional methods coupled with compensation effect and master-plots, the ‘kinetictriplet’ including apparent activation energy (Eα), pre-exponential factor (A) and mechanism function f(α) were identified for the pyrolysis process of three solid waste biomasses. Using Eqns. (5) and (9), the apparent activation energies were evaluated in a selected range of conversion, 0.1-0.8, with an interval of 0.05. The variation of Eα with

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respect to conversion is presented in Fig. 3 and the Eα values obtained at different conversions are listed in Table S1 (in supplementary information).

Fig. 3. Variation of activation energy (Eα) with respect to conversion (α) using (a) Friedman method and (b) KAS method.

The activation energy can be defined as the minimum amount of energy that is required to initiate a reaction, which means that the reaction with high activation demands more energy to dissociate the chemical bonds among the atoms and consequently, the reaction proceeds slowly.54 The average values of activation energies, pre-exponential factor and thermodynamic parameters are presented in Table 5. Table 5. Average values of kinetic and thermodynamic parameters for all the solid waste samples.

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Material/

Activation energy, Pre-exponential Activation

Gibbs free

Activation

Parameter

Eα, (kJ mol-1)

factor, A

enthalpy, ∆H energy, ∆G entropy, ∆S

FM

KAS

(s-1)

(kJ mol-1)

(kJ mol-1)

(J mol-1)

MSW

172.3

173.02

1.81×1010

167.12

173.04

-13.5

DMSW

202.55 202.21

1.04×1018

197.37

184.94

36.68

SWD

215.22 213.84

2.26×1019

210.23

185.48

74.55

It should be noted that for any chemical reaction that involve the physical transformation of the material, the Eα value indicates the chemical stability of the material. Hence, for the decomposition of stable components in the biomass more energy needs to be supplied. From Fig. 3, it can be noticed that the Ea varied significantly with respect to conversion indicating the complexity of biomass pyrolysis, where many reactions occur at same stage. The highest activation energy for MSW, DMSW and SWD were noticed to be 194.54, 239.9 and 246.59 kJ mol-1 at α = 0.6, 0.4 and 0.55, respectively. It could be noticed from Fig. 3, that the Ea values for all the samples were low for all the samples at lower conversion (α =0.1) and then started to increase rapidly from α = 0.2, indicating the initiation of decomposition of main components in the biomass.55 It should be noted from Fig. 3, that the Eα decreased at higher conversions and this may be due to fact that less stable components, that are easy to decompose, are formed at

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higher temperatures during the decomposition of stable components resulting in the decrease in activation energy.30 The increase in the activation energies in the conversion range of 0.2 – 0.6 indicate the transition of biomass from drying phase to volatilization of major structural components, such as lignin, cellulose and hemicellulose, along with extractives such as lipids, proteins and carbohydrates. The activation energies were noticed to match the peaks in the DTG curves presented in Fig. 1. The Ea values were noticed to be high at conversions 0.6 for MSW, 0.4 for DMSW and 0.5 for SWD. The corresponding temperatures were 390 °C for MSW, 333 °C for DMSW and 338 °C for SWD, which closely matched with the peak temperatures in DTG curves. The average activation energies obtained in this study, by using two isoconversional methods, for MSW, DMS and SWD were in the range of 172.3 – 173.02, 202.21 – 202.55 and 213.84 – 215.22 kJ mol-1, corresponding to the results reported in the literature.40-41,

47

The

compensation effect, using Eqns. (10 – 12), was used to evaluate the pre-exponential factor and Eqns. (15 – 17) were used to evaluate the thermodynamic parameters, such as activation enthalpy, activation entropy and Gibbs free energy. In order to eliminate the element of error associated with the integral isoconversional methods,56 the Ea obtained

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from Friedman method was used hereafter to obtain the pre-exponential factor, reaction mechanism function and thermodynamic parameters. Using fi(α), from Table 1, in Eqn. (10), a pair of ln Ai and Eαi were obtained for each fi(α) and are shown in Fig. 4. The compensation lines for the selected biomass samples are as follows: For MSW, lnAα = 0.2133*Eα - 7.111

(18)

For DMSW, lnAα = 0.2108*Eα - 6.8623

(19)

and for SWD, lnAα = 0.2192* Eα - 6.8364

(20)

Fig. 4. Compensation line of Arrhenius parameters ln Ai and Eαi for the three solid waste sample, (a) MSW, (b) DMSW and (c) SWD

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On substituting the values of Eα obtained from Friedman method in to the above equations yields the values of pre-exponential factor. The values for pre-exponential factor and other important thermodynamic parameters are presented in Table S2 (in supplementary information). Depending on the biomass, the values of A varied from 1010 to 1020 over the conversion range 0.1 – 0.8. The highest value of A was noticed to be 8.57×1014 at α = 0.6, 9.60×1018 at α = 0.4 and 4.48×1018 at α = 0.5 for MSW, DMSW and SWD, respectively. The mean A values were noticed to be 1.81×1016, 1.04×1018 and 2.26×1019 for MSW, DMSW and SWD, respectively. The A values ≤ 109 s-1 indicate surface reactions and when surface reactions does not occur, the low A values indicate a tight junctional complex. The A values above 109 s-1 correspond to the formation of loose junctional complex.53, 57 The value of A ranging in between 1010 – 1012 s-1 indicate that the activated complex is restricted in rotation when compared to its initial form.58 The complex, in case of unimolecular materials, is expected to expand its size by intensely interacting with its neighbors. From Table S2, it can be noticed that, at higher conversions (α > 0.5), in the decomposition range of stable components such as lignin, the A values varied with a magnitude of over 1013 s-1 indicating the slow and difficult degradation and

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imply the need of high molecular collisions. Under such conditions, the reaction demands more energy, which is evident from Table S1. The thermodynamic parameters, such as activation enthalpy (∆H), Gibbs free energy (∆G) and activation entropy (∆S), for all the samples are listed in Table S2. It can be noticed from Table S2 that the changes in Ea and ∆H are in good agreement with each other. The Ea and ∆H values are taken into consideration, a small energy barrier (~5 kJ mol-1) indicate favorable conditions for the formation of activated complex and possibility of reaction to occur under selected conditions.59 As the enthalpy can be defined as the amount of energy utilized during the conversion of biomass into products, the values of

Ea and ∆H imply the additional energy required for the formation of products, in this study, ~5 kJ mol-1. The ∆S values indicate the degree of disorder of a system. Additionally, for pyrolysis the ∆S values indicate the degree of arrangement of carbon layers in biochar.60 The negative values of ∆S indicate that more thermally stable products are formed from the reactants and thermal equilibrium is attained. The positive values of ∆S imply that the system is far from its equilibrium. The increase amount of energy required by the system to form activated complex is reflected by the values of ∆G.58 The higher the values of ∆G,

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the higher the energy input is required, implying the possibility of unfavourable reactions happening. If the values of ∆G are higher than ∆H and they are accompanied by the negative values of ∆S, it means that a significant part of heat supplied to the system is not used.60 The numerical values for mechanism function were derived by substituting the values obtained for activation energy and pre-exponential factor in Eqn. (13) and are presented in Fig. 5. The experimental master plots obtained under different heating rates are practically identical, which indicate that kinetics degradation process of a material can be explained by a single kinetic model.61 The reaction mechanism function deduced via compensation effect indicated that the mechanism function for all the samples was a continuous decreasing function with respect to conversion. This trend appear with decelerating models.27 Similar behavior was noticed during the thermal conversion of other feedstock.56, 62

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Fig. 5. Reaction mechanism functions obtained by using compensation effect (on the left) and master plots method (on the right), (a), (b) for MSW, (c), (d), DMSW and (e) and (f) SWD.

While the mechanism function obtained via compensation effect help to categorize it into any of the three categories (accelerating, decelerating and sigmoidal models), by

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matching the experimental plots with theoretical plots master plots method can be used to decide the appropriate model for pyrolysis. By using Eqn. (14), the left hand side term was used to generate theoretical plots and the right hand side term was used to generate experimental plots and the results are presented in Fig. 5 (right side plots).The reaction mechanism function for MSW followed reaction order model (F2) till mid conversions (α=0.5) and then shifted to second order diffusion model (D2). For the digestates, DMSW and SWD, the reaction mechanism function followed similar trend. The mechanism function second (F2) and third (F3) order models. The validation of kinetic parameters was done by comparing the simulated and experimental values for conversion vs temperature and are presented in Fig. 6.

Fig. 6. Simulated vs experimental curves for (a) MSW, (b) DMSW and (c) SWD using the obtained kinetic parameters.

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A numerical program build in Excel, as explained in our previous study,30 was used to validate the kinetic parameters. The simulated curves were in good agreement with the experimental curves, indicating the accuracy of the kinetic parameters obtained in the present study. A good fit can be noticed in the low and mid conversion range where the conversion rate confirmed to the conditions of kinetic control, the simulated conversion vs temperature, particularly for SWD at 15 °C min-1, superimposed the experimental curves throughout the conversion range (0.1 – 0.8). With the validation being done, the results can be useful for the design of conversion system aiming the devolitilisation of solid waste.

Conclusions In this study, an attempt has been made to investigate the thermal and kinetic behavior and evolved gas analysis during the pyrolysis of three forms of organic solid wastes in a thermogravimetric analyzer coupled with mass spectrometer. Isoconversional methods, compensation effect and master plots method were used to evaluate the kinetic-triplet, which include activation energy, pre-exponential factor and reaction mechanism function.

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The pyrolysis process can be divided in to three distinct stages. The stage II (200 -500 °C) was noticed to be the major devolatilization zone. In regards to gas yields and trends, H2 evolution was mostly temperature dependent, while CO and CO2 evolved throughout the decomposition process. The kinetic parameters showed that the highest activation energy was needed for SWD during the decomposition process, in comparison to the other waste biomasses. This study indicated the feasibility of solid wastes as feedstock for generating bioenergy. To enable commercial production of H2 via pyrolysis of solid waste, there is still enormous research to be done in the areas such as process optimization for increasing H2 and minimizing CO2, influence of sorbent/catalyst on pyrolysis. Additionally, the kinetic and thermodynamic parameters obtained and validated in this study help optimize the design of reactor for the thermochemical conversion of solid waste biomass. AUTHOR INFORMATION

Corresponding Author * Ming Zhao Email: [email protected] (Ming Zhao)

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Author Contributions

The manuscript was written through contributions of all authors. All authors have given approval to the final version of the manuscript.

Funding Sources

The work was supported by National Natural Science Foundation of China (grant number: 51506112) and Tsinghua University Initiative Scientific Research Program (grant number: 20161080094).

Notes The authors declare no conflict of interest.

Abbreviations AD, anaerobic digestion; DMSW, digested municipal solid waste; FM, friedman method; KAS, kissenger-akira-sunnose; MS, mass spectrometer; MSW, municipal solid waste; SWD, swine manure digestate; TG, thermogravimetric.

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