1 Introduction

The demand for paper and paper products is increasing day by day in the world, especially in China and India [1]. For instance, about 3% of the world’s paper production is carried out in India, with an annual production of one million tons of paper [2]. Paper products are manufactured following a series of mechanical and chemical processes, and massive amounts of wastewater, solid, and sludge are released [3]. Paper mill sludge (PMS), one of these wastes, is released during wastewater treatment and contains various organic and inorganic components, and the fact that it is not properly managed is a serious potential threat to the environment and ecology [3]. It is generally known that approximately 50 kg of PMS (dry based) is generated for one ton of paper manufacturing [4]. PMS has dispatched landfills for permanent disposal following the filtration process, but limited storage areas and stringent environmental regulations/laws complicate that. Another disposal option is incineration. However, it is not sustainable and feasible due to the high process cost, the complex content of PMS, and the formation of greenhouse gas emissions [5]. As that, the USA and European countries have serious limitations on disposal and waste management [3]. Therefore, the disposal/evaluation of PMS with safe and innovative technology has become an important issue in terms of sustainable environment and production [1, 6].

Previous researchers have reported the following alternative evaluation techniques for PMS; production of clay bricks [7] and ceramic tiles [8], clinker production [9], mortar preparation [10], activated carbon [11], and adsorbent [12]. However, energy production in the form of biogas and biofuel from paper mill sludge is an eco-friendly approach in terms of reducing the waste load and waste disposal cost of the paper manufacturing facility and meeting environmental regulations [13]. In this sense, seeking to find the best method for sustainable bioenergy production from this PMS is ongoing. Ahmed and Gupta [14] examined the methods of pyrolysis and gasification for energy production from PMS and found that gasification was more effective than pyrolysis. On the other hand, thanks to the biogas production from PMS, the energy costs of the heating units in the facilities are reduced and this energy can be utilized to dry the feedstock [15]. As is seen, thermochemical treatments are of great interest not only in processing this industrial waste but also in converting it into green energy. Pyrolysis, gasification, and combustion processes are classified according to the reactive atmosphere and operating temperature. In terms of combined heat and power generation, combustion is a more preferred method compared to pyrolysis and gasification [16]. In addition, by gasification of carbonaceous compounds in oxidative medium, combustible gases are released and ash is formed [17].

Organic materials can be converted into biochar (solid), pyrolytic oil (liquid) syngas products by pyrolysis [18, 19]. Also, the pyrolysis process requires low energy consumption than gasification [20]. Because of these, pyrolysis is more effective and eco-friendly compared to other thermochemical conversion methods [21, 22]. Conversion of lignocellulose based residues [23, 24], plastic wastes [25], and household bio-wastes [26] into energy and valuable chemical components using pyrolysis is one of the popular research topics of today. PMS contains various organic and inorganic components (Fe and Ca etc.) from the paper manufacturing process and wastewater treatment. With reference to the positive influence of Fe element on the syngas production [27], the presence of inorganic ions in PMS can also contribute to energy recovery during pyrolysis. The detailed information on the mechanism, kinetics, and thermodynamics of PMS pyrolysis is required for sustainable energy production with an eco-friendly approach in an industrial scale.

TGA analysis is an effective method to examine the thermal degradation behavior and thermal stability of various types of materials [28, 29]. Moreover, TGA data is used for mathematical modeling, which is critical for the design and optimization of thermochemical conversion reactors and processes [30, 31]. Two types of methods are commonly used to analyze TGA data; model-fitting method and model-free method. Of these, a model-free method is a simple approach by nature, and there is no risk of error in point of model selection and calculation of kinetic parameters [32]. The model-free method, which determines the kinetic parameters without any assumptions thanks to the different heating rate curves, also predicts the reaction mechanisms of complex materials [33]. These models (Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman and DAEM), known as iso-conversional, are applied at multiple-heating rates and produce lower margin of error (less than 1%). Also, these models only calculate the kinetic parameters of the process for particular conversion ranges (mostly 0.1–0.8) for an independent model.

Although there are considerable investigations on the thermal kinetics of various agricultural and industrial wastes (biomass), there is no detailed data on pyrolysis reaction kinetics of PMS. Therefore, the present paper focused to understand on the physicochemical properties, pyrolysis behavior, and kinetic analysis of PMS. Due to the possibility of peaks shifting at long interval in TG-DTG curves, the pyrolysis experiments were performed at short interval heating rates (5, 10, and 20 °C.min−1) to clearly explain the thermal degradation phenomenon. Four model-free methods (Kissinger-Akahira-Sunose (KAS), Flynn-Wall-Ozawa (FWO), Friedman and DAEM) were studied for thermal analysis and following that the kinetic and thermodynamic parameters were calculated for each model. The physicochemical characteristics of PMS were determined by FTIR, ultimate/proximate analysis.

2 Material and method

2.1 Characterization of paper mill sludge

The paper mill sludge was supplied from a paper manufacturing plant in 2019. Before pyrolysis, PMS was dried at room temperature and then it was ground, sieved and the uniform particle sizes of less than 30 μm were obtained. The PMS powders were placed in a closed container for subsequent experiments.

The moisture, ash, and volatile matter contents (proximate analysis) of the PMS were determined according to E 1756 [34], E 1755 [35] and E 872 [36], respectively. The fixed carbon content was calculated by subtracting the sum of ash, moisture, and volatile matter from 100%. Ultimate analysis (carbon, hydrogen, nitrogen, sulfur, and oxygen content) of PMS was performed using the elemental analyzer (LECO CHNS 932). Functional groups in PMS structure were determined by FTIR analysis (Perkin Elmer Spectrum 100). FTIR analysis was performed with 4 cm−1 resolution in the 400–4000 cm−1 scanning range.

2.2 Thermogravimetric analysis

Thermal decomposition behavior of paper mill sludge pyrolysis was examined by thermal analyzer (FEI Quanta 250 FEG) under nitrogen gas atmosphere in the temperature range of 25–800 °C. The nitrogen flow rate was kept at 10 ml/min during the studied temperature range. For each experiment, the initial amount of the paper mill sludge sample is 10 ± 0.2 mg. Pyrolysis was carried out at low heating rates (5, 10, and 20 °C.min−1). For the accuracy of the results, the experiments were repeated at least three times. While TGA data contributed to the illumination of thermal degradation behavior of the materials, it also helped calculate the kinetic and thermodynamic parameters of the paper mill sludge pyrolysis process.

2.3 Kinetic analysis

Pyrolysis of lignocellulose-based wastes is a rather complicated phenomenon because of the wastes containing a wide variety of chemical components. A large number of reactions occur simultaneously during thermal decomposition, which is very difficult to predict reaction mechanisms. However, a reaction mechanism is suggested in the literature as follows [37];

$$ \mathrm{Biomass}\ \left(\mathrm{solid}\right)\overset{\mathrm{k}\left(\mathrm{t}\right)}{\to}\mathrm{Volatile}\ \left(\mathrm{gases}+\mathrm{tar}\right)+\operatorname{char}\ \left(\mathrm{solid}\ \mathrm{residue}\right) $$

Assuming that the conversion of the raw material to the product is a single step process [38], the reaction rate constant (k) can be written according to the Arrhenius equation as follows;

$$ k=A{e}^{-\left(\frac{E}{RT}\right)} $$
(1)

where k, A (min−1), E (kJ mol−1), R (kJ mol−1 K−1) and T (K) represent reaction rate constant, pre-exponential factor, activation energy, the universal gas constant, and absolute temperature, respectively. The conversion of raw material from the solid phase to the gas phase can be expressed by the following equation;

$$ \frac{d\alpha}{d t}=k\ f\left(\alpha \right) $$
(2)

where α is the conversion rate, t is the time. The conversion expression is a function of temperature. Therefore, the conversion factor can be written as follows;

$$ \alpha =\frac{W_o-{W}_t}{W_o-{W}_f} $$
(3)

where Wo is the initial weight of the sample, Wt is the weight of the sample at any given time, and Wf is the weight of the sample at the end of the pyrolysis process. The above equations can be combined as the following;

$$ \frac{d\alpha}{d t}=A{e}^{-\left(E/ RT\right)}f\left(\alpha \right) $$
(4)

In terms of the uniform kinetic reaction, f(α) function can be given as follow;

$$ f\left(\alpha \right)={\left(1-\alpha \right)}^n $$
(5)

and with the combination of the abovementioned equations can be written the following;

$$ \frac{d\alpha}{d t}=A{e}^{-\left(E/ RT\right)}{\left(1-\alpha \right)}^n $$
(6)

Heating rate (δ) is an effective parameter in the pyrolysis process and can be defined as follows;

$$ \delta =\frac{d T}{d t}=\frac{d T}{d\alpha}X\frac{d\alpha}{d t} $$
(7)

The heating rate statement is replaced in the previous equation and simplified;

$$ \frac{d\alpha}{d T}=\frac{A}{\delta }{e}^{-\left(\frac{E}{RT}\right)}{\left(1-\alpha \right)}^n $$
(8)
$$ \frac{d\alpha}{{\left(1-\alpha \right)}^n}=\frac{A}{\delta }{e}^{-\left(\frac{E}{RT}\right)} dT $$
(9)

When the change equation of the conversion rate with temperature is integrated,

$$ g\left(\kappa \right)=\underset{0}{\overset{\alpha }{\int }}\frac{d\alpha}{f\left(\alpha \right)}=\underset{0}{\overset{T}{\int }}\frac{A}{\delta }{e}^{-\left(E/ RT\right)} dT $$
(10)
$$ g\left(\kappa \right)=\frac{AE}{\delta R}\underset{0}{\overset{\alpha }{\int }}{u}^{-2}{e}^{-u} du=\frac{AE}{\delta R}p\left(\alpha \right) $$
(11)

where g(κ) is the integral conversion and α is \( \frac{E}{RT} \). Since there is no definitive solution of p(α), it can only be solved by the numerical approach method. In this sense, p(α) can be simplified according to the chosen approach method [39].

2.3.1 Flynn-Wall-Ozawa method

The Ozawa-Flynn-Wall method calculates the activation energy of the material based on the Doyle approach [40] as;

$$ p\left(\alpha \right)=-2.315+0.457\alpha $$
(12)

Doyle’s approach is put in an equation and rearranged;

$$ \mathit{\ln}\left(\delta \right)=\mathit{\ln}\left[\frac{AE}{Rg\left(\alpha \right)}\right]-2.315-0.457\frac{E}{RT} $$
(13)

For different heating rates, ln(δ) is plotted versus 1/T and linear line is obtained in the 0–1 conversion range. Activation energy is found from the slope of the line.

2.3.2 Friedman method

The Friedman method is one of the general iso-conversional methods used for thermal kinetic analysis of the material. In this method, the conversion function is constant and assumes that material degradation occurs only due to mass loss, independent of temperature. When the logarithms of both sides of the equation are taken,

$$ \mathit{\ln}\left(\frac{d\alpha}{d t}\right)=-\frac{E}{RT}+\mathit{\ln}\left( Af{\left(\alpha \right)}^n\right) $$
(14)

The slope and intercept of the kinetic graph between \( \mathit{\ln}\left(\frac{d\alpha}{d t}\right) \) and 1/T gives \( -\frac{E}{RT} \) and ln(Af(α)n), respectively [41].

2.3.3 Kissinger–Akahira–Sunose method

Thermal kinetic parameters of the material are calculated according to the Kissinger-Akahira-Sunose (KAS) model with the following equation.

$$ \mathit{\ln}\left(\frac{\delta }{T^2}\right)=\mathit{\ln}\left[\frac{AE}{Rg\left(\alpha \right)}\right]-\frac{E}{RT} $$
(15)

The activation energy and frequency factor can be determined using the slope and intercepts of \( \mathit{\ln}\left(\frac{\delta }{T^2}\right) \) versus \( \frac{1}{T} \) graph [42].

2.3.4 Distributed activation energy model

Distributed activation energy model (DAEM) was developed to identify complex reactions that occur during pyrolysis and combustion of fossil fuels [43]. Apart from illuminating the complex reaction mechanisms of various biomass fuels, it was also widely used to determine the thermal kinetic parameters [44,45,46]. According to DAEM model, the activation energies of the first-order reaction and numerous irreversible parallel reactions during pyrolysis are related to the bond structure and strength [47]. On the other hand, DAEM model, which is preferred to examine the pyrolysis kinetics of various materials, is in harmony with experimental data, especially at low heating rates [45]. Simplified DAEM equation with reference to the Arrhenius equation;

$$ \mathit{\ln}\left(\frac{\delta }{T^2}\right)=\mathit{\ln}\left(\frac{AR}{E}\right)+0.6075-\frac{E}{RT} $$
(16)

The left side of the equation \( \mathit{\ln}\left(\frac{\delta }{T^2}\right) \) against \( \frac{1}{T} \) is plotted and a linear line is obtained. The slope is \( \frac{E}{R} \) and intercept value is calculated from \( \mathit{\ln}\left(\frac{AR}{E}\right) \).

The calculation of thermodynamic parameters that are critical to determine the realization potential of a process is based on the following equations;

$$ A=\frac{\alpha .E.\mathit{\exp}\left(\frac{E}{R.{T}_p}\right)}{R.{T}_p^2} $$
(17)
$$ \Delta H=E-R.T $$
(18)
$$ \Delta G=E+R.{T}_p.\mathit{\ln}\left(\frac{K_B.{T}_p}{h.A}\right) $$
(19)
$$ \Delta S=\frac{\Delta H-\Delta G}{T_p} $$
(20)

where KB, h, and Tp represent Boltzmann constant (1.381 × 10−34 J.K−1), Plank constant (6.626 × 10−34 J s), and peak temperature (K) in DTG curve, respectively.

3 Results and discussion

3.1 Physicochemical analysis

The physico-chemical characteristics of PMS are given in Table 1. According to the data in Table 1, PMS contains less than 5% moisture; it can be considered to be a perfect raw material for pyrolysis and combustion processes [48]. Higher moisture content of raw material causes heat loss [49]. On the other hand, it has an amount of volatile compounds (22.70%wt.) and less ash content. The high ash content of raw material is known to cause insufficient combustion, increasing of operating cost, waste disposal problem, and low energy conversion [46, 50]. Therefore, the PMS is highly ignition performance. The high presence of fixed carbon (60.86%) in the PMS means that the heat production and energy value during the combustion are high. The results of the ultimate analysis in Table 1 show that PMS can be used as a biofuel for energy production due to its high carbon content (38.32%). Compared to the carbon content, it is close to the banana peel [51], hazelnut husk [31], and banana leaves [52]. The heating value of the PMS was determined at 29.84 MJ kg−1. Another advantage of the PMS is that it does not contain high amounts of nitrogen and sulfur, which can cause harmful emissions such as SOx and NOx during pyrolysis and combustion reactions. As seen from Table 1, the nitrogen (0.38%) and sulfur (0.74%) content of the PMS is negligible. The data of the chemical analysis indicate that the PMS contains cellulose (57.25%) of high amount and lower percentage of hemicellulose (32.67%). The total cellulose and hemi-cellulose content is 89.92% that is a sign that the PMS is suitable for biofuel production. In addition, the presence of 10.08% lignin causes char formation following pyrolysis or combustion. The following order can be made for the thermal stability of the components in PMS; cellulose < hemicellulose < lignin [53].

Table 1 Proximate, ultimate, and biochemical analysis of PMS
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3.2 FTIR analysis

The FTIR spectrum of the PMS in Fig. 1 presents very wide-ranging and extensive peaks. The peak at 3331 cm−1 is belong to the characteristic stretching –OH of cellulose [54]. The weak peaks in 2918 cm−1 and 2850 cm−1 which are between 2950 to 2800 cm−1 ranges are attributed to the C-H stretching of aromatic and aliphatic groups. Another signal at about 1640 cm−1 indicates the presence of C–O aldehyde group. The strong peak observed at 1417 cm−1 is caused by the presence of calcium carbonate. The strong peak observed at 1417 cm−1 indicates the presence of calcium carbonate, which is due to a large amount of calcite used during the paper manufacturing process. The vibrations of C–O–C bond and glucose stretching of C–O and OH could be seen at 1155 cm−1 and 1028 cm−1 signals, respectively. The other peak at 873 cm−1 represents the presence of the C–O–C bond [55].

Fig. 1
figure 1

FTIR spectrum of paper mill sludge

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3.3 Thermal degradation of PMS

With the pyrolysis process, the solid wastes can be converted into products in different physical forms. The type of raw material and reaction conditions is effective in the composition and amount of the products. Various and complex reactions occur during the pyrolysis of solid wastes. These reactions occur due to the breakdown of cellulose, hemicellulose, and lignin in the solid wastes to form different products.

The thermal degradation characteristics of the PMS under nitrogen atmosphere were determined by TGA analysis. TGA curve in Fig. 2 indicates that the PMS goes through three basic decomposition zones; dehydration (up to 150 °C), devolatilization (250–360 °C); and char formation (> 380 °C). In the first zone up to 160 °C temperature, low molecular weight compounds, and water molecules in PMS structure were removed. The highest weight loss occurred due to the thermal degradation of hemicellulose and cellulose in the range from 200 °C to 360 °C in the second region, also called the active pyrolytic region [56]. For the second zone, it is possible to say that hemicellulose and cellulose convert into lower molecular weight products with the increasing temperature. In this zone, volatile substance formation occurs as a result of two simultaneous exothermic processes of hemicellulose, cellulose, and lignin degradation, respectively. Moreover, the maximum conversion (46.5%) was achieved in the temperature range from 260 °C to 360 °C in the second zone at 5 °C min−1 heating rate. Hemicellulose decomposes at the lowest temperature (210–310 °C), followed by cellulose (310–390 °C) and lignin (from 160 to 800 °C). It is known that the thermal decomposition of cellulose occurs in two stages as follows; breaking chemical bonds into monomers and formation of carbon gases at low temperatures (up to 160 °C for the present study), and liquid formation due to bond integration at higher temperatures (350 °C for the present study) [57]. The third region in Fig. 2 is an endothermic phenomenon and belongs to lignin thermal decomposition at a higher temperature (> 360 °C) [58].

Fig. 2
figure 2

TGA curves of paper mill sludge at different heating rates

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For DTG curves in Fig. 3, the first distinct peaks were observed at 240 °C, 250 °C, and 270 °C for 5, 10, and 20 °C.min−1, respectively, quite likely due to the thermal degradation of hemicellulose. The straight and long-chain cellulose consisting of glucose monomers degraded in the temperature range 300 °C–390 °C and the maximum weight loss occurred at 390 °C [53]. The highest peak observed in the 300–400 °C range may be due to depolymerization and glycosidic linkage of lignocellulosic components [59]. As lignin degrades over a wide temperature range (160–800 °C), no clear boundaries for the decomposition of different components were observed [53]. When the PMS is evaluated in terms of content (Table 1), it can be indicated that the main decomposition peak is due to cellulose.

Fig. 3
figure 3

DTG curves of paper mill sludge at different heating rates

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The characteristic parameters observed for different heating rates, especially the initial and peak temperatures, are given in Table 2. The zone where the main thermal degradation (260–620 °C) took place was divided into two sections. For heating rates of 5, 10, and 20 °C.min−1 in the first section, Ti values are considered 270, 280, and 295 °C, while Tp and Tf temperatures are 310, 320, and 335 °C; 335, 340, and 350 °C, respectively. In the second zone, Ti, Tp, and Tf temperatures were seen as 365, 375, and 390 °C; 480, 500, and 515 °C; 585, 600, and 610 °C for heating rates of 5, 10, and 20 °C.min−1, respectively. As a result, the increase of heating rate improved heat transfer limitations and TG-DTG curves shifted towards higher temperatures [60]. On the other hand, the increase of heating rate caused the peak temperature and degradation rate to raise even more; however, it did not affect the decomposition characteristic [61]. Finally, the release rates of volatile substances also increase to a certain extent with increasing heating rate.

Table 2 TG-DTG characteristics parameters of PMS at heating rates of 5, 10, and 20 °C/min
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3.4 Kinetic and thermodynamic analysis

Thermodynamic and kinetic parameters play a critical role in industrial scale in terms of reactor and process design [61]. Kinetic (pre-exponential factor and activation energy) and thermodynamic calculations (entalphy, entropy, free energy) were carried out for the 260–620 °C temperature range, where the main weight loss occurred. Model-free methods such as KAS, Flynn-Wall-Ozawa (FWO), and Friedman and DAEM were preferred for kinetic analysis. Activation energy, a measure of reaction reactivity, is defined as the minimum energy required to start a chemical reaction [62]. Except for 0.1 conversion rate, all conversion rates were compatible with the models due to the high correlation coefficient. According to the KAS, FWO, and Friedman and DAEM model, the average activation energy values were calculated as 37.73 kJ mol−1, 101.01 kJ mol−1, 46.16 kJ mol−1, and 35.84 kJ mol−1, respectively.

In addition, the activation energy calculated from the FWO method is higher than the other methods. The change of E values calculated for the FWO method reveals that it is not appropriate to explain the thermal degradation phenomenon by a single reaction mechanism. Significant variation of E values depending on the conversion rate in FWO method indicates that a multi-stage kinetics is effective for the PMS pyrolysis [59]. It is seen that the drastic changes of the activation energy are due to the components that prevent the decomposition of the volatile components as a result of thermal decomposition, and this phenomenon corresponds to the char formation zone in TGA curve. Also, the correlation coefficient, which is an indicator of model compatibility with experimental data, is higher than 0.9 for each model as shown in Table 3. When the pre-exponential factories of all model-free methods are analyzed, they vary between 0.56 × 103 s−1 and 14.55 × 103 s−1. The literature reports that the magnitude of A varies according to the reaction types in the pyrolysis process. When the A value is < 109 s−1 or in between 1010 and 1012 s−1, the pyrolysis takes place as only the surface reaction or decomposition of cellulose, respectively. Also, a value higher than 1014 s−1 infers a high number of molecule collisions, which means that the pyrolysis process needs high activation energy [58, 60, 63]. The pre-exponential factor calculated from FWO, Friedman, KAS, and DAEM models varies between 0.56 × 103 s−1 and 14.55 × 103 s−1. Therefore, the pyrolysis of PMS takes place only as a surface reaction.

Table 3 Activation energy and correlation coefficient estimates according to KAS, FWO, and Friedman and DAEM methods
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Thermodynamic parameters for conversion ratios between 0.2 and 0.8 are presented in Table 4. Enthalpy (ΔH) is a state function that shows that the reaction is endothermic or exothermic and reflects the decomposition of chemical bonds under constant pressure [64, 65]. The change of ΔH calculated from KAS, FWO, and Friedman and DAEM models are as follows; 13.10–0.03 kJ mol−1, 54.20–7.08 kJ mol−1, 21.91–0.38 kJ mol−1, 12.45–0.02 kJ mol−1; 48.79–2.30 kJ mol−1, 133.69–14.62 kJ mol−1, 58.24–3.82 kJ mol−1, 46.35–2.18 kJ mol−1; 22.08–1.51 kJ mol−1, 74.95–5.43 kJ mol−1, 31.40–0.38 kJ mol−1, 20.97–1.44 kJ mol−1 for 5, 10, and 20 °C min−1, respectively. As seen in Table 4, the change observed in ΔH due to the increase in conversion rate displays a trend similar to the change in activation energies. The increase of ΔH values means that the temperature rises, which means the breaking of strong chemical bonds in the PMS [65]. Consequently, according to all models, the positive ΔH values calculated for all heating rates and conversion rates reveal that the pyrolysis of PMS under the nitrogen atmosphere is endothermic and needs external energy [64].

Table 4 Thermodynamic parameter estimation of PMS at heating rates of 5, 10 and 20 °C/min
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Whether a chemical reaction occurs spontaneously and the direction of that reaction is defined by Gibbs free energy (ΔG) [64]. As shown in Table 4, ΔG values of KAS, FWO, and Friedman and DAEM models are 196.8 kJ mol−1, 242.67 kJ mol−1, 210.39 kJ mol−1, 186.96 kJ mol−1; 238.64 kJ mol−1, 316.82 kJ mol−1, 241.36 kJ mol−1, 226.71 kJ mol−1; 206.61 kJ mol−1, 261.61 kJ mol−1, 218.05 kJ mol−1, 196.28 kJ mol−1 for 5, 10, and 20 °C.min−1, respectively.

The entropy (∆S) refers to disorders. As presented in Table 4, entropy is negative for all conversion rates. It can be attributed that the irregularity degree of the products released after the pyrolysis process is higher than that of reactants. In addition, considering all heating rates and models, there was no remarkable differ in entropy changes.

4 Conclusions

Thermal degradation behaviors and pyrolysis kinetics of the PMS were quantified by thermogravimetric analysis. TG-DTG curves confirmed that the degradation peak with an increase of heating rate shifted towards the higher zone without changing the thermal decomposition characteristic of the PMS. While physicochemical testing indicated that the PMS has bioenergy potential, FTIR analysis confirmed the presence of beneficial functional groups in the raw material. According to the kinetic analysis, pyrolysis results are compatible with all models and these data provide great benefits in terms of optimization of pyrolysis conditions, design of process, and reactor on an industrial scale. Consequently, industrial biomass with energy potential like the PMS can be utilized in sustainable and clean energy production.