Co-pyrolysis of biomass and binary single-use plastics: synergy, kinetics, and thermodynamics

ABSTRACT

Waste management is an increasing global concern due to the rise in urbanization and industrialization. This study examines the co-pyrolysis of date pits (DP) and single-use plastics (polypropylene-PP and Styrofoam-PS) as a way to create value-added products. Single, binary, and ternary mixtures were pyrolyzed at three different heating rates to understand the synergy, kinetics, and thermodynamics. The results showed positive synergy and reduced activation energies during co-pyrolysis, due to varying reaction mechanisms. The positive values of ∆H, ∆G, and negative ΔS indicate endothermic non-spontaneous reactions and disorder in the products instead of the reactants during pyrolysis. Future studies should explore upscaling this process for sustainable energy production.

KEYWORDS:

• Co-pyrolysis
• plastics
• biomass
• kinetics
• thermodynamics
• TGA

1. Introduction

Due to urbanisation, industrialisation, and associated waste generation, waste management is an increasing global concern. Predictions by the World Bank show the annual production of municipal solid waste (MSW) – comprised mainly of organic wastes, and plastics – will double by 2025 from 1.3 million tons in 2012 (Das et al. 2019). The most common methods of disposing of waste is landfilling and incineration. However, economical and straightforward, they pose severe health and environmental issues due to emissions to both air and water bodies and lack of management (Das et al. 2019; Foong et al. 2020). In addition to the associated environmental regulations, the lack of land space for landfilling presents an imperative need for other ways to treat waste (Parthasarathy et al. 2022). A thermochemical processing technology – pyrolysis – has recently gained attention due to its being environmentally friendly. The products received from pyrolysis include char, oil, and gas, depending on the operating conditions, such as feedstock type, heating rate, temperature, solid residence times, and particle size (Foong et al. 2020). The products have proved the technology economical, providing an alternative to landfilling.

Thermogravimetric analysis (TGA) is often used to understand and evaluate the effects of heating rates on the kinetic parameters and thermodynamic parameters, thereby providing useful guidance on designing pyrolysis systems (Mariyam et al. 2022). The data received from TGA reflects changes in materials’ weight loss over time and temperature (Elkhalifa et al. 2022). Several studies have conducted TGA analysis of various mixed feedstocks, including lignocellulosic biomass food wastes (Fermanelli et al., 2020) and swine manure with plastic wastes (Ro et al., 2014), depicting co-pyrolysis systems. A positive synergy was observed when pine sawdust was mixed with low-density polyethylene (LDPE) due to lowered activation energies (AE) and solid residues (Zheng et al. 2018). Subsequently, Wen et al. found that increasing the polyethylene (PE) fraction from 0 to 75% increased cardboard decomposition, with increasing AE with temperature (Wen et al. 2021). On the other hand, when sewage sludge (SS) and LDPE were co-pyrolyzed, it was found that the blending ratios of SS and LDPE showed that a 1:1 ratio of the biomass and plastic (SL:50) is optimal in decreasing AE, owing to radicals from LDPE accelerating the biomass pyrolysis (Zaker et al. 2021). Kinetic and thermodynamic studies using model-free kinetic models found that AE, Gibbs free energy, and lower enthalpy indicated great potential for bioenergy production. Therefore, plastics are suitable and attractive feedstocks for co-pyrolysis with biomass. Co-pyrolyzing microalgae (Dunaliella salina) with plastics such as polypropylene (PP), polystyrene (PS), polyethylene terephthalate (PET), and polyvinyl chloride (PVC) showed that the solid residues and AE decreased but differently for different plastics (PET > PP > PS > PVC) (Chen et al. 2021). Therefore, different plastics have different effects when co-pyrolyzed. Other studies show that co-pyrolyzing several plastics with pinewood produced synergistic effects aiding in better carbon conversion efficiencies and volatiles yield due to higher AE from biomass decomposition (Burra and Gupta 2018). The TGA studies demonstrated that although some plastics showed synergy during the TGA of PET and black polycarbonate (BPC), others do not show such behavio (PP).

Several reviews have been published to direct the research using plastic wastes via pyrolysis (Yuan et al. 2022; Papari, Bamdad, and Berruti 2021). Studies finalise the positive outcomes of mixing biomass and plastics for products generation.

The wastes of interest in this research are date pits (DP) and single-use plastics – polypropylene (PP) and expanded polystyrene (PS). Dates are significant as date palms are among the few fruits bearing trees in arid regions. There are about 120 million date palm trees globally, and 10% of the date fruit comprises DP, which is often thrown away (Tahir, Al-Obaidy, and Mohammed 2020). On the other hand, plastic is a modern synthetic product whose production has increased from 1.7 million metric tonnes in 1950–360 million tonnes metric tonnes in 2018, with almost half of it being single-use plastics and 40% of it being used for packaging materials (Chen et al. 2021). Both PP and PS or Styrofoam are extensively used in the packaging industry, especially for food and beverages. Styrofoam is often used for takeaway food packaging and cutlery, and on the other hand, PP is widely used as cold beverage holders and lids. Both date and plastic wastes have immense potential for product generation and are ideal candidates for co-pyrolysis using sustainable feedstock blends. Recently, there have been TGA studies published on date wastes (Parthasarathy et al. 2022; Raza et al. 2022), PP (Jiang et al. 2022; Dubdub and Al-Yaari 2020), Styrofoam or expanded PS (Varma et al. 2021; Zhang et al. 2021) and co-pyrolysis of biomass and plastics (as discussed above). However, mixing DP with two different single-use plastics in binary and ternary blends has not been studied previously. This study is essential to understand the thermal degradation behaviour of feeds individually and together under the influence of different heating rates under inert conditions. Additionally, to the best of our knowledge, based on literature surveys, this paper reflects the gap in studying the kinetics and thermodynamics of blending DP in binary and ternary mixtures with single-use plastics.

Most studies focus on iso-conversational models, such as Flynn and Wall, Kissinger, Ozawa, and Friedman due to the lack of reaction model assumption. However, the models are built on the assumption that there is a constant conversion value as a temperature function. Also, they cannot provide kinetic descriptions of complex feeds, so model-free methodologies are preferred (Dhyani and Bhaskar 2018). This study's primary focus will be to understand the reaction mechanism based on a model-fitting approach using non-isothermal models to understand the complex effects of mixing biomass (DP) with single-use-plastics of PP and PS. Since most studies focus on model-free kinetics, understanding reaction mechanisms when mixing biomass and plastics becomes imperative. Although an advantage of the model-based approach is utilising a single heating rate, this study also focuses on the change in reaction mechanisms due to the heating rate. The Coats Redfern is an integral model-fitting method utilised to understand seventeen reaction mechanisms based on reaction order, diffusion, geometric, and nucleation models; hence, the effect of an important operating parameter on the reaction mechanism due to complex feed co-pyrolysis is studied. The data from this study will help provide valuable information in designing pyrolysis systems of biomass with two single-use plastics since the TGA shows the kinetics, thermodynamics, volatiles, and char yields, therefore, assisting in sustainable energy production via co-pyrolysis of common wastes.

Therefore, this research work has three main objectives: (i) to understand the thermal decomposition behaviour and synergistic effects and using the three wastes individually (DP, PP, and PS) and in binary and ternary blends during co-pyrolysis; (ii) to study the kinetics of the single, binary and ternary blends using equal masses at different heating rates and applying model-based reaction models of Coats Redfern; and (iii) to study the thermodynamics parameters of the samples under the conditions for the best kinetic fit mechanisms.

2. Materials and methods

According to the objectives of this study, the pyrolysis and co-pyrolysis of DP, PP and PS are studied, and the methodology follows the order (i) material preparation and characterisation (Section 2.1) (ii) synergistic studies (section 2.2) (iii) Model based kinetic studies (Section 2.3) (iv) thermodynamic analysis (section 2.4).

2.1 Materials preparation and characterisation

DP was extracted from commercially purchased dates (Doha Dates, National Food Co.) washed with distilled water, and dried at 323.15 K for 24 h before grinding using an electric grinder. PP and PS were purchased as food packaging materials from the market. Both PP and PS were washed, dried, and ground into small pieces for experimentation purposes. All samples were sieved to 710 µm using the sieve bank supplied by Haver & Boecker, Germany. For mixed wastes, each feedstock was mixed in equal proportions (50 wt.% each) to yield a total of seven samples in this study: single (DP, PP, PS), binary (DP:PP, DP:PS, PP:PS), and ternary (DP:PP:PS).

The proximate analysis of the samples was conducted using a thermogravimetric analyzer (SDT650, TA Instruments). A standard procedure of ASTM D7582-12 was followed, and the moisture, volatiles, fixed carbon, and ash were determined. Approximately 9 ± 0.1 mg of the samples was heated from room temperature to 378.15 K in an inert nitrogen environment for 30 min to evaluate the moisture content. Furthermore, the temperature was increased to 1223.15 Kat a rate of 30 K/min, and the sample was kept at this temperature for seven minutes under isothermal conditions. Then oxygen was used to combust the samples for 10 min to evaluate the ash content. The amount of fixed carbon was calculated on a weight basis by subtracting the measured components (moisture, volatile matter, and ash) from the original mass.

The ultimate analysis was conducted using a CHNS elemental analyzer (EA3000 CHNS elemental analyzer, EuroVector). A standard procedure of ASTM D 3176–8 was followed to analyse the weight percentage of carbon, hydrogen, nitrogen, oxygen, sulfur, chlorine, and ash in each sample of feedstock. Triplicate samples of about 0.5–1.5 mg of each mass were measured and analyzed. The oxygen content was calculated by subtracting the elements’ weight and ash content obtained from the samples’ total mass.

Before the TGA studies, the samples were sieved using a 710 µm sieve (Haver & Boecker, Germany). The analysis was conducted at 10, 20, and 30 K/min heating rates from room temperature to 1173.15 K using a thermogravimetric analyzer (SDT650, TA Instruments) for the single, binary and ternary samples amounting to a total of 21 runs. The binary and ternary mixtures employed the feeds at 1:1 and 1:1:1 ratio. The runs were performed under an N₂ atmosphere purged at 100 ml/min. Each run was conducted three times to ensure the reproducibility and accuracy of results. The data from the TGA and derivate thermogravimetric (DTG) curves obtained from the analysis help study the feeds’ synergistic, kinetics and thermodynamics.

2.2 Synergistic studies

The synergistic effects are studied based on the additive formula in equation (1(1) $\mathrm{\Delta }\mathrm{W}=Wexp-Wcal=Wexp-(X_1{W}_1+X_2{W}_2)$(1) ) employed previously to understand the impact of biomass and various plastics (Jiang et al. 2022; Hassan, Hameed, and Lim 2020; X. Wang et al. 2019; Alam et al. 2020) for two feedstocks. Pyrolysis usually produces char and volatiles. (1) $\mathrm{\Delta }\mathrm{W}=Wexp-Wcal=Wexp-(X_1{W}_1+X_2{W}_2)$(1) Where X₁, and X₂ are mass fractions of individual feedstocks in the blend and W₁, W_2, are the residual weight % from the TGA of the individual samples. The equation has further been updated to include three feedstocks for the ternary samples using equation (2(2) $\mathrm{\Delta }\mathrm{W}=Wexp-Wcal=Wexp-(X_1{W}_1+X_2{W}_2+X_3{W}_3)$(2) ): (2) $\mathrm{\Delta }\mathrm{W}=Wexp-Wcal=Wexp-(X_1{W}_1+X_2{W}_2+X_3{W}_3)$(2)

X₃ and W₃ are the mass fraction and residual weight % of the third feedstock in the ternary blend. While a ΔW (difference in weight percentage of experimental and calculated TGA data) greater than zero reflects a positive synergistic effect (promotion) in the solid-state, less than zero reflects a passive synergy (inhibition). ΔW at the final temperature (ΔW_final) and throughout the temperatures are analyzed in this study.

Alternatively, overall synergistic effects during co-pyrolysis of the studied feedstocks were studied using a simple statistical analysis through the root mean square error (RMSE) as in equation (3(3) $RMSE=\sqrt{{\displaystyle \frac{{\sum }_{i=1}^n{(W_{Experimental}(i)-W_{Calculated}(i))}^2}{\mathrm{N}}}}$(3) ). An RMSE value of zero reflects no synergistic effect during the co-pyrolysis process. The correlation coefficient (r) is calculated using equation (4(4) $r={\displaystyle \frac{\mathrm{Cov}({\mathrm{W}}_{Experimental},{\mathrm{W}}_{Calculated})}{\sqrt{\mathrm{D}({\mathrm{W}}_{Experimental})\mathrm{D}({\mathrm{W}}_{Calculated})}}}$(4) ) and should be between – 1 and 1. In the case that the value of r equals 1 and less than 1, in this way, the absence and presence of a synergistic effect is confirmed. (3) $RMSE=\sqrt{{\displaystyle \frac{{\sum }_{i=1}^n{(W_{Experimental}(i)-W_{Calculated}(i))}^2}{\mathrm{N}}}}$(3) (4) $r={\displaystyle \frac{\mathrm{Cov}({\mathrm{W}}_{Experimental},{\mathrm{W}}_{Calculated})}{\sqrt{\mathrm{D}({\mathrm{W}}_{Experimental})\mathrm{D}({\mathrm{W}}_{Calculated})}}}$(4)

2.3 Model-based kinetic studies

The rate kinetics help to understand the energy requirement for the pyrolysis system and help determine the reactor size (Varma et al. 2021). The following equation describes the general kinetic equation for the kinetic behaviour of biomass, and plastic transformation is heterogeneous in solid states and at a linear heating rate (Zheng et al. 2018). (5) $\mathrm{Biomass}+\mathrm{PS}+\mathrm{PP}->\mathrm{Char}+\mathrm{volatiles}$(5) Developing kinetic models to describe the pyrolysis process via kinetic parameters such as activation energy (AE) and pre-exponential or frequency factor (A) is essential for a pyrolysis reactor design. Although many models using iso-conversional methods of Kissinger – Akahira – Sunose (KAS), Flynn – Wall – Ozawa (FWO), Friedman, and Starink have been employed to study co-pyrolysis of various biomass with different types of plastics (Zaker et al. 2021; Özsin, Pütün, and Pütün 2019; Varsha et al. 2021; Singh et al. 2021; Alam et al. 2020), this study uses a model-fitting correlation model, namely, the Coats-Redfern (integral) model (CR). This model is chosen due to its applicability in predicting and correlating the effect of single heating rates. Table S1 shows the different solid-state kinetic models based on the CR models used in this study and employed by other studies (Elkhalifa et al. 2022; Coats and Redfern 1964).

The rate of non-isothermal solid decomposition can be depicted by equations (6(6) ${\displaystyle \frac{d\alpha }{dt}=k(T)(1-\alpha )}$(6) ) and (7(7) ${\displaystyle \frac{d\alpha }{dt}=A{e}^{-{\displaystyle \frac{AE}{RT}}}{\displaystyle \frac{dt}{dT}(1-\alpha )}}$(7) ). (6) ${\displaystyle \frac{d\alpha }{dt}=k(T)(1-\alpha )}$(6) (7) ${\displaystyle \frac{d\alpha }{dt}=A{e}^{-{\displaystyle \frac{AE}{RT}}}{\displaystyle \frac{dt}{dT}(1-\alpha )}}$(7) where A (min⁻¹) is the pre-exponential factor, AE (kJ/mol) is the activation energy, k (T) is the reaction rate constant, t (min) is time, T (K) is the absolute temperature, R (J/mol K) is the universal gas constant, α is the pyrolysis conversion factor given by the equation (7(7) ${\displaystyle \frac{d\alpha }{dt}=A{e}^{-{\displaystyle \frac{AE}{RT}}}{\displaystyle \frac{dt}{dT}(1-\alpha )}}$(7) ). The value of α and T is determined from the TGA and DTG data. ∝ is expressed as: (8) $\propto ={\displaystyle \frac{W_0-W_t}{W_0-W_f}}$(8) Where $W_0$ is the weight of the sample before decomposition (kg), $W_t$ is the weight of the sample at a time t (kg), and $W_f$ is the final weight after decomposition (kg). For a constant heating rate, β = dT/dt, equation (8(8) $\propto ={\displaystyle \frac{W_0-W_t}{W_0-W_f}}$(8) ) is the repositioned and integrated to give an equation based on the original CR equation (Coats and Redfern 1964): (9) $ln{\displaystyle \frac{g(\alpha )}{T^2}=\ln {\displaystyle \frac{AR}{\beta E}-{\displaystyle \frac{AE}{RT}}}}$(9)

Α linear regression model is developed on Microsoft Excel, and the linear regression formula is in the form of $y=B+Cx+Dz$. The linear relationship between ln g ($\alpha$) /T² and I/T provides the AE and A from the slope and intercept of the equation, respectively. The authors studied seventeen reaction mechanisms of the CR models, based on reaction order, power law, diffusion, nucleation, and geometrical contraction models, which are shown in Table S1. Satisfactory AE and A (reported in kJ/mol and s⁻¹) values were received from models which depicted the highest coefficient of determination, R^2,, to the fitted regression line. The modeling is performed in regions with the highest weight loss, as depicted in the DTG curves.

The effect of mixing biomass and plastic feeds on the degradation of the pseudo components was also analyzed using the deconvoluted DTG curves. The deconvolution of the feeds using asymmetric peak fitting function – bi-gaussian – are represted in equations 10(10) $y=y_0+H{e}^{-0.5{\left({\displaystyle \frac{x-x_c}{w_1}}\right)}^2}(x<x_c)$(10) and 1(1) $\mathrm{\Delta }\mathrm{W}=Wexp-Wcal=Wexp-(X_1{W}_1+X_2{W}_2)$(1) 1. The asymmetrical peaks obtainedalign with hemicellulose, cellulose and lignin as part of the biomass degradation. The parameters of single conversion rate curves (pseudo-component curves) were defined by adjusting the fitting results with the global curve (summed experimental DTG curve) using the OriginPro software version OriginPro 2022b). (10) $y=y_0+H{e}^{-0.5{\left({\displaystyle \frac{x-x_c}{w_1}}\right)}^2}(x<x_c)$(10) (11) $y=y_0+H{e}^{-0.5{\left({\displaystyle \frac{x-x_c}{w_2}}\right)}^2}(x\ge x_c)$(11) y₀ is the baseline where the bi-gaussian variable function at x₀, x is the independent variable, x_c is the centre value or the abscissa of the maximum reaction rate, and w₁ and w₂ is the left and right half peak width.

2.4 Thermodynamic analysis

From the values of kinetic parameters of the best fit model (highest R² values), the thermodynamic properties such as a change in enthalpy (ΔH), Gibbs free energy (ΔG), and change in entropy (ΔS) were determined by equations (12), (13), and (14). Thermodynamic parameters help evaluate the heating and cooling requirements during co-pyrolysis. Several studies have determined the parameters from the kinetics of mixed feeds (W. Wang et al. 2022; Rasam et al. 2020; Naqvi et al. 2019). (12) $\mathrm{\Delta }H=AE-R{T}_m$(12) (13) $\mathrm{\Delta }G=AE+R{T}_m\ln \left({\displaystyle \frac{k_b{T}_m}{hA}}\right)$(13) (14) $\mathrm{\Delta }S={\displaystyle \frac{\mathrm{\Delta }H-\mathrm{\Delta }G}{T_m}}$(14)

Where T_m is the peak decomposition temperature (K), k_b denotes the Boltzmann constant (1.38 × 10⁻²³ J/K), and h represents the Planck constant (6.63 × 10⁻³⁴ Js).

3. Results and discussion

The results and discussion follow the objectives (section 1) and the materials and methodology section (section 2). The characterisation of the single, binary and ternary feedstocks (section 3.1) is followed by the discussion of the thermal decomposition behaviour retrieved from the TGA and DTG curves (section 3.2). Furthermore, section 3.3, 3.4, and 3.5 discuss the results of synergistic effects; reaction mechanisms, and kinetics using Coats Redfern models; and thermodynamics using the kinetic parameters from the best fit models, respectively.

3.1 Characterisation of feedstocks

Table 1 shows the proximate and ultimate analysis of the single, binary and ternary feeds. Since DP is biomass, its constituents are different from waste plastics. The proximate analysis shows the DP has higher moisture, ash, and fixed carbon content but lower volatiles than the plastics (PP and PS). Most of the plastics comprised volatiles, ∼98 and ∼99% of PP and PS, with little moisture (0.76% for PS), respectively. DP and the plastics have 80-90% volatiles when mixed in equal proportions. Also, fixed carbonand moisture of the binary biomass-plastic mixture are less than individual DP and more than PP and PS. When the plastics are mixed in equal proportions, they have the same constituents. Finally, when all three are mixed, the moisture is 1.69%, and the majority are volatiles (90.76%) with some ash (1.01%) and 5.64% of fixed carbon. The ash content is much lower than the DP value in the biomass plastic mixtures,

Table 1. The proximate and ultimate analyses of feeds.

	DP	PP	PS	DP:PP	DP:PS	PP:PS	DP:PP:PS
Proximate analysis (% w/w) *
Moisture	2.63	0.00	0.76	1.92	1.40	0.39	1.69
Volatiles	63.4	98.3	99.2	80.4	87.88	99.0	90.7
Ash	12.7	1.57	0.05	2.46	0.72	0.51	2.01
Fixed carbon**	21.3	0.04	0.00	13.22	10.00	0.09	5.64
Ultimate analysis (% w/w) ***
Carbon	45.9	84.4	91.4	69.3	67.2	88.2	82.3
Hydrogen	6.20	13.2	7.72	8.11	11.94	10.79	9.62
Oxygen**	30.8	0.75	0.81	17.9	18.0	0.99	6.99
Sulphur	–	–	–	–	–	–	–
Nitrogen	4.27	–	–	2.21	2.10	–	–

*air-dried basis.

**by difference.

***dry basis.

The ultimate analysis reflected the mixed behaviour pattern (refer to table 1). DP had the lowest carbon content (∼45.95%) and the highest nitrogen content (∼4.27%). All the feedstocks did not contain any sulfur, and the plastics did not have any nitrogen. The carbon content increased in the order of DP > PP > PS in the range of 45.95–91.42%, and the hydrogen content increased in the order of DP > PS > PP in the range of 13.26–6.20%. The most significant difference between the biomass and plastic samples (in addition to the carbon content) was the difference in the oxygen content. While DP had ∼31% of oxygen, the oxygen content in plastics was less than 1%. When DP is mixed with the plastics, the oxygen content is around 17-18%, the carbon content is approximately 67-69%, and the nitrogen is about 2%. Binary plastic mixtures have similar constituents as single plastics in terms of carbonWhen all three feedstocks were mixed, the carbon content was around 82%, which is more than DP and less than individual plastics; however, since most of the mixture is plastics, the carbon content is high. No nitrogen was detected when all three were mixed.

3.2 Thermal decomposition behaviour of single, binary, and ternary

The thermal degradation behaviour is reflected in the TGA and DTG curves of the single feeds (Figure 1a-f), binary (Figure 1g-l) and ternary feeds (Figure 1m-n). Table S2 shows the onset, peaks, and end temperature of the detected peaks in the DTG curves. The peak ranges reflect the various stages in the degradation process of the feed. The curves also indicate how the feeds behave during pyrolysis and co-pyrolysis in nitrogen atmosphere conditions.

Figure 1. TGA (a, c, e, g, i, k, m) and DTG (b, d, f, h, j, l, n) curves of the single, binary and ternary biomass and plastic feeds.

For the single feed, degradation occurs in a single stage. For the plastics, a linear degradation behaviour (maximum weight loss in one stage between 600 and 770 K), is reflected in an inverted S-shape which has been reported previously for single o-pyrolysis of sewage sludge and low-density polyethylene – A thermogravimetric study of thermo-kinetics and thermodynamic parameters (Burra and Gupta 2018; Zaker et al. 2021) and binary plastic mixtures (Dubdub and Al-Yaari 2021). The same behaviour is also seen in the binary plastic mixture in this study (Figure 1 h).

Alternatively, DP behaves as a typical biomass feed as seen in other publications in three major stages (Parthasarathy et al. 2022; Elkhalifa et al. 2020; Zhou et al. 2018) – room temperature to 1173.15 (the studied end temperature) following dehydration (first step), lignin, cellulose, hemicellulose, protein, fat degradation (one endotherm reflects this step), and char degradation (final step). DP majorly degrades between 441.0 and 790.6 K (Stage I), with the onset temperature and end temperature increasing with increasing heating rates. Unlike plastics, the DTG curve shows small peaks between 600 K and the end temperature. However, the peaks are not distinctly separated; the degradation is assumed to occur by a one-step process. The total weight loss for the DP at the final temperature for all samples is 74-78%. On the other hand, the total weight loss for PP and PS is 100% at all heating rates. As seen in Table S2, the peak temperatures and the weight loss at the peak temperatures increase with increasing heating rates. With increasing temperatures, char yield – reflected in the weight percentage during the TGA analysis – decreases considerably for all the samples. It is observed that plastics are better suited for volatiles (gas and oil) production at higher temperatures (>700 K) rather than char due to the absence of residual solids. The TGA data show us that the potential for char production (refer equation 5(5) $\mathrm{Biomass}+\mathrm{PS}+\mathrm{PP}->\mathrm{Char}+\mathrm{volatiles}$(5) ) usingDP even at the finaltemperatures range from ∼19-17% with increasing heating rates. The effect of the heating rate was observed in not only the residual char yield but also the maximum weight loss at peak temperatures. The exact char yield quantification from the residual solid yields in TGA should be verified against pyrolysis reactor studies (not in the scope of this study).

The effect of mixing biomass and plastic (1:1 wt.%) is observed in the TGA and DTG curves. Since biomass (DP) and plastics (PP and PS) reflect different behaviours, mixing them shows distinct behaviour. The DTG curves of the binary and ternary mixtures of biomass and plastics show two distinct peaks, reflecting two main degradation stages. Two distinct peaks were shown when cardboard and PE were mixed (Wen et al. 2021), microalgae and different plastics (including PP and PS) (Chen et al. 2021), Eucalyptus and single-use plastics (PS and LDPE) (Vanapalli et al. 2021), and cyanobacteria and PP (L. Li et al. 2021). The first peak reflects biomass degradation from 503 - 638 K, and the second peak reflects plastics (PP degradation occurring between 629 and 734 K, and PS degradation between 617 and 744 K). Additionally, it is observed that when DP is mixed with plastics in equal measure, biomass degradation starts and ends at lower temperatures compared to single-feed degradation. Alternatively, plastic degradation occurs at almost the same temperatures as single plastic degradation. Subsequently, the binary plastic mixtures show one main peak, as the single plastics. However, there seems to be an embedded small peak at around 716, 731, and 742 at 10, 20, and 30 K/min heating rates, respectively, which is absent in the individual DTG curves. Since the individual PP degradation occurred at slightly higher and wider temperature ranges, the second embedded peak could be attributed to its degradation in the binary mixture. Also, since the peak is not distinctly separate, the degradation is considered a single step, and the kinetics are calculated for one stage.

Furthermore, the embedded peak is also seen in the ternary samples, which show two district peaks like the binary biomass plastic mixtures. In essence, the plastic degradation occurring at later temperatures is confirmed when the embedded peak from the binary plastic mixtures is observed in the ternary mixtures at higher temperatures. The weight loss in all binary and ternary mixtures ranges between 90.60 - 100%. The results show that mixing biomass and plastics is excellent due to maximum product generation, especially volatiles. Char could be produced at lower temperatures, and considerable volatiles could be generated with minimum solid residues at higher temperatures. Another study discussed the hydrogenation reaction between the unsaturated products from plastics and biomass, yielding lower char production when microalgae were co-pyrolyzed with PP, PS, and PET in binary blends (Chen et al. 2021). Subsequently, another study states that plastic suppresses residue char formation due to polymerisation inhibition and crosslinking reactions when pyrolyzed with biomass (Wen et al. 2021). Hence, such mechanisms could also be the reason for the reduced char yield in our study.

Due to multiple overlapping peaks, the deconvolution procedure of asymmetrical functions is utilised for analysing the biomass degradation. In this study, the bi-gaussian function has been applied to study the thermal degradation behaviour of the biomass (DP), plastics PP and PS when mixed with binary and ternary mixtures to enhance the discussion. Table S3 shows the deconvolution parameters of the components at a heating rate of 30 K/min. Figure 2 shows the deconvoluted DTG curves for the studied feeds fitted with R² values ranging from 0.988 for DP to 0.999 for DP:PP:PS. The biomass consists of three pseudo-components (hemicellulose, cellulose, and lignin). The binary and ternary biomass-plastic feeds have 4 and 5 pseudo-components since plastic constitutes the fourth and fifth components. The biomass components in DP of hemicellulose degradation occur first at around 575 K, followed by cellulose (666 K) and lignin (747 K).

Figure 2. Deconvoluted DTG curves fitting with bi-gaussian functions for single (a-c), binary (d-f) and ternary (g) feeds.

The degradation of pseudo-hemicellulose occurs at temperatures close to 575 K for the binary and ternary mixtures. The cellulose degradation occurs at slightly higher temperatures when pyrolyzed with plastics. The most variation occurs during the lignin degradation since it occurs around the same temperature as the plastics. The PP, PS degradation is at 752 and 735 K; these temperatures shift to lower temperatures for the binary mixtures (PP at 742 K and PS at 710 K). Plastics are degraded at similar temperatures in the binary and ternary biomass and plastic feed. However, the lignin degradation occurs at different expected temperatures (∼707 K), especially when mixed with PS. While the single PS degrades at 706 K, both lignin and PS degrade around 707 K during the DP:PS degradation. The degradation of PS through random scission produces free radicals, which interact with the free radicals produced from the homolytic cleavage resonance of lignin, thereby interrupting lignin radical coupling. This mechanism has also been proposed by an earlier co-pyrolysis study of lignocellulosic biomass and PS (Vanapalli et al. 2021). The tendency of PS to interact with the lignin portion to enhance biomass conversion to produce volatiles and reduce char formation by forming stable low molecular aromatics which aid in the synergistic effects and similar peak degradation temperatures.

3.3 Synergistic effects

A positive and passive synergistic effect in the solid-state is reflected when ΔW_final is greater and less than zero, respectively. This study observed a positive synergy when DP is mixed with the plastics (binary and ternary mixtures) in the solid-state at lower heating rates (10 and 20 K/min) and a passive synergy at higher heating rates (30 K/min) and the final temperatures (Table S4). Alternatively, when the plastics are mixed, there is a passive synergy at all heating rates due to the absence of char yield. Furthermore, the negative values reduce heating rates, reflecting reduced passivity with increasing heating rates. The positive synergistic effect shows promise in increasing char yield when mixing biomass and plastics, especially at lower heating rates. This behaviour reflects lower volatiles generation than mixed plastic samples since positive synergy occurs in the solid state. However, the overall synergy in mixed plastic samples observed in the RMSE and correlation coefficient values shows synergy in both solid and non-solid-state conditions, hence providing benefits in mixing waste for gas and oil production. The correlation coefficient is always less than 1 and not equal to 1, and the RMSE values are always higher than zero showing the presence of synergy at all heating rates and for all studied feeds.

The interactions between the volatiles with the char from earlier biomass degradation, unreacted feedstock, and the volatiles (from biomass) all contribute to the synergy when biomass and plastics are mixed (Liu et al. 2020). As the proximate analysis shows, the volatiles content is significantly higher for the plastics than for the DP. However, the difference in the exact components when mixing the two different plastics requires further analysis and is not in the scope of this study. A previous study assigned the synergistic effects due to the volatiles from textile dyeing sludge interacting with the alkane groups from the polyolefin cracking when mixed with PP or PE (medical plastic wastes) (Ding et al. 2021). Subsequently, another study stated that the oligomer radicals from PP with the OH from cellulose (biomass) created long alcohol chains, which lowers AE and char yields (Burra and Gupta 2018).

This study showed differences in synergy when the biomass was mixed with the two different plastics – the RMSE values increase more when mixed with PS (rather than PP), reflecting more synergy. The ΔW_final is also higher for DP: PS than DP:PP at 10 and 20 K/min, which shows that adding biomass to the PS causes more char yields than PP, although individual plastics produce no chars (refer to table S2). Adding PP and PS to DP at higher temperatures has shown better carbon conversion of biomass at 30 K/min, aiding in volatiles generation, therefore reducing char residues. Such observation was also seen when pinewood was mixed with PP and PET in binary mixtures (Burra and Gupta 2018) and microalgae with different plastics, including PP and PS (Chen et al. 2021). Furthermore, blending PS has previously exhibited synergistic and inhibitory effects when mixed with Eucalyptus biomass. While the inter-radical chemical interactions aided in synergistic effects, the inhibitory effects on the biomass due to the plastics resulted in chars with better thermal properties, increased surface areas, and lower carbon contents (Vanapalli et al. 2021). The inhibitory effects arose with increasing temperature after the degradation of plastic, which had condensed to form a polymer coat on the surface of the char (absent in biochars). Such effects could have occurred in our study, which is reflected in the increased char production during co-pyrolysis with respect to the zero residual weights for the individual plastic pyrolysis. In this study, with the increase in temperature, the synergistic effects of promotion and inhibition vary considerably for the different feeds. When the ΔW is positive, there is a promoting effect, while a negative value shows an inhibiting effect. Figure S1 shows the synergistic effects in the solid state of the feeds over the temperature. The synergistic effects reduce considerably as the heating rate increases for all feeds. The inhibiting effect in the binary plastics is highest at 700, 500, and 400 K as the heating rate increases from 10 to 30 K/min. The highest inhibiting effect occurred between 600 and 800 K in the case of DP:PS, which confirms the radicals interaction discussion in section 3.2. Alternatively, the promoting effects are highest in the case of DP:PS and DP:PP:PS at 700 and 500 K for 10 and 20 K/min, respectively. The complex nature of volatiles-biomass interaction with increasing heating rates requires investigation using molecular analytical tools such as TGA coupled with Fourier Transform Infrared Spectroscopy (FTIR).

Table 2. Kinetic parameters of feeds at various heating rates at the first major mass loss region (Stage I).

	10 K/min			20 K/min			30 K/min
Reaction Models	AE (kJ/mol)	A (s^1)	R^2	AE (kJ/mol)	A (s^1)	R^2	AE (kJ/mol)	A (s^1)	R^2
DP
F1	19.66	3.18E + 06	0.928	22.97	1.98E + 06	0.925	21.80	2.93E + 06	0.920
F2	36.59	8.92E + 04	0.955	41.97	3.70E + 04	0.956	37.85	1.14E + 05	0.968
F3	36.59	1.78E + 05	0.955	41.97	7.40E + 04	0.956	37.85	2.28E + 05	0.968
P2/3	46.44	4.83E + 05	0.891	52.64	1.71E + 05	0.885	21.80	2.93E + 06	0.920
D1	27.69	3.12E + 06	0.865	31.80	1.66E + 06	0.864	37.85	1.14E + 05	0.968
D2	33.08	1.85E + 06	0.899	37.84	8.64E + 05	0.896	37.85	2.28E + 05	0.968
D4	15.99	5.87E + 09	0.978	16.85	7.26E + 09	0.979	16.71	6.59E + 09	0.984
A2	19.66	6.35E + 06	0.928	22.97	3.97E + 06	0.925	21.80	5.86E + 06	0.920
A3	19.66	9.53E + 06	0.928	22.97	5.95E + 06	0.925	21.80	8.79E + 06	0.920
A4	19.66	1.27E + 07	0.928	22.97	7.94E + 06	0.925	21.80	1.17E + 07	0.920
R2	4.21	9.21E + 07	0.864	–	–	–	3.87	8.21E + 07	0.815
R3	6.44	2.02E + 08	0.969	6.14	1.80E + 08	0.960	6.39	9.16E + 03	0.9642
PP
F1	205.88	3.63E + 12	0.903	144.64	1.17E + 08	0.981	244.12	8.18E + 14	0.977
F2	260.62	8.16E + 16	0.806	195.15	1.86E + 12	0.878	297.09	1.07E + 19	0.893
F3	260.62	4.08E + 16	0.806	195.15	9.29E + 11	0.878	297.09	5.36E + 18	0.893
P2	170.11	2.47E + 09	0.940	115.29	1.96E + 05	0.993	210.34	9.33E + 11	0.994
P3	170.11	1.64E + 09	0.940	115.29	1.31E + 05	0.993	210.34	6.22E + 11	0.994
P4	170.11	1.23E + 09	0.940	115.29	9.80E + 04	0.993	210.34	4.67E + 11	0.994
P2/3	533.38	2.05E + 35	0.945	368.57	2.15E + 23	0.994	654.59	7.87E + 42	0.995
D1	351.74	5.75E + 22	0.944	241.93	4.82E + 14	0.993	432.46	6.32E + 27	0.994
D2	370.60	8.16E + 23	0.937	256.22	3.70E + 15	0.996	450.05	7.26E + 28	0.993
D4	–	–	–	25.39	3.57E + 10	0.805	–	–	–
A2	205.88	1.82E + 12	0.903	144.64	5.83E + 07	0.981	244.12	4.09E + 14	0.977
A3	205.88	1.21E + 12	0.903	144.64	3.89E + 07	0.981	244.12	2.73E + 14	0.972
A4	205.88	9.08E + 11	0.903	144.64	2.92E + 07	0.981	244.12	2.05E + 14	0.977
R1	170.11	4.93E + 09	0.940	115.29	3.92E + 05	0.993	210.34	1.87E + 12	0.994
PS
F1	225.10	1.47E + 15	0.958	218.96	2.17E + 14	0.936	205.32	1.01E + 13	0.961
F2	375.09	2.65E + 27	0.860	308.93	4.54E + 21	0.826	353.54	6.58E + 24	0.961
F3	375.09	1.08E + 27	0.860	308.93	2.27E + 21	0.826	353.54	3.29E + 24	0.961
P2	148.54	3.29E + 08	0.959	165.56	4.40E + 09	0.966	131.64	5.33E + 06	0.895
P3	148.54	2.19E + 08	0.959	165.56	1.33E + 05	0.966	131.64	3.56E + 06	0.895
P4	148.54	1.64E + 08	0.959	165.56	9.95E + 04	0.966	131.64	2.67E + 06	0.895
P2/3	467.90	5.59E + 32	0.963	519.08	1.09E + 36	0.968	418.22	3.65E + 27	0.906
D1	308.22	3.83E + 17	0.938	342.32	8.84E + 24	0.968	274.94	3.27E + 17	0.903
D2	342.13	3.07E + 23	0.966	368.75	1.14E + 25	0.964	306.22	5.34E + 19	0.920
D3	–	–	–	–	–	–	25.50	4.55E + 06	0.831
D4	46.76	3.41E + 12	0.851	–	–	–	44.83	1.96E + 12	0.914
A2	225.10	7.33E + 14	0.958	218.96	1.08E + 14	0.936	205.32	5.05E + 12	0.961
A3	225.10	4.89E + 14	0.958	218.96	1.08E + 14	0.936	205.32	3.36E + 12	0.961
A4	225.10	3.67E + 14	0.958	218.96	5.41E + 13	0.936	205.32	4.07E + 12	0.961
R1	148.54	6.57E + 08	0.959	165.56	8.79E + 09	0.966	131.64	1.07E + 07	0.895
R2	25.59	3.38E + 06	0.844	–	–	–	–	–	–
PP:PS
F1	172.11	3.74E + 10	0.972	178.72	8.70E + 10	0.973	171.38	1.64E + 10	0.968
F2	234.28	5.65E + 15	0.929	242.92	1.56E + 16	0.921	229.74	8.98E + 14	0.905
F3	234.28	2.83E + 15	0.929	242.92	7.78E + 15	0.921	229.74	4.49E + 14	0.905
P2	134.08	1.16E + 07	0.949	138.30	1.96E + 07	0.961
P3	134.08	7.73E + 06	0.949	138.30	1.30E + 07	0.961	133.71	4.41E + 06	0.969
P4	134.08	5.79E + 06	0.949	138.30	9.78E + 06	0.961	133.71	3.30E + 06	0.969
P2/3	424.66	4.19E + 27	0.954	405.13	1.36E + 29	0.965	424.05	6.29E + 27	0.972
D1	279.38	1.40E + 18	0.953	287.94	3.97E + 18	0.964	278.88	4.78E + 17	0.971
D2	298.51	2.75E + 19	0.961	308.63	9.77E + 19	0.97	298.47	9.23E + 18	0.974
D4	30.42	1.12E + 11	0.881	32.18	1.53E + 11	0.863	30.92	1.13E + 11	0.843
A2	172.11	1.87E + 10	0.972	178.72	4.35E + 10	0.973	171.38	8.21E + 09	0.968
A3	172.11	1.25E + 10	0.972	178.72	2.90E + 10	0.973	171.38	5.47E + 09	0.968
A4	172.11	9.36E + 09	0.972	178.72	2.17E + 10	0.973	171.38	4.11E + 09	0.968
R1	134.08	2.32E + 07	0.949	138.30	6.19E + 06	0.961	133.71	1.32E + 07	0.969
DP: PP
F1	33.15	9.39E + 05	0.929	36.70	6.18E + 05	0.899	36.84	6.15E + 05	0.924
F2	37.39	3.82E + 05	0.936	41.29	2.39E + 05	0.911	41.81	2.23E + 05	0.935
F3	37.39	7.64E + 05	0.936	41.29	4.78E + 05	0.911	41.81	4.46E + 05	0.935
P2	29.22	4.27E + 06	0.919	32.44	2.96E + 06	0.885	34.04	3.28E + 06	0.928
P3	29.22	6.41E + 06	0.919	32.44	4.44E + 06	0.885	34.04	4.93E + 06	0.928
P4	29.22	8.55E + 06	0.919	32.44	5.91E + 06	0.885	34.04	6.57E + 06	0.912
P2/3	106.37	1.21E + 05	0.945	116.60	6.18E + 05	0.919	121.49	5.61E + 05	0.938
D1	67.79	7.70E + 03	0.940	74.52	3.10E + 03	0.912	74.21	3.40E + 03	0.933
D2	70.32	8.68E + 03	0.942	77.26	3.39E + 03	0.915	77.16	3.58E + 03	0.936
D3	3.38	8.31E + 07	0.881	3.12	7.51E + 07	0.826	2.79	6.31E + 07	0.822
D4	10.65	1.02E + 09	0.997	11.03	1.13E + 09	0.998	11.28	1.21E + 09	0.998
A2	33.15	1.88E + 06	0.929	36.70	1.24E + 06	0.899	36.84	1.23E + 06	0.924
A3	33.15	2.82E + 06	0.929	36.70	1.85E + 06	0.899	36.84	1.85E + 06	0.924
A4	33.15	1.45E + 07	0.929	36.70	2.47E + 06	0.899	36.84	2.46E + 06	0.924
R1	29.22	2.14E + 06	0.919	32.44	1.48E + 06	0.855	32.24	1.56E + 06	0.912
R2	3.85	9.40E + 07	0.917	3.63	8.73E + 07	0.876	6.26	2.12E + 08	0.987
R3	6.37	2.17E + 08	0.989	6.38	2.51E + 08	0.984	3.36	7.65E + 07	0.881
DP:PS
F1	26.07	2.29E + 06	0.943	36.99	6.09E + 05	0.915	44.53	3.21E + 05	0.927
F2	31.43	7.51E + 05	0.935	41.48	2.40E + 05	0.927	46.72	8.95E + 04	0.938
F3	31.43	1.50E + 06	0.935	41.48	4.80E + 05	0.927	46.72	1.79E + 05	0.938
P2	21.24	1.22E + 07	0.900	32.81	2.87E + 06	0.902	39.38	8.88E + 05	0.913
P3	21.24	1.83E + 07	0.900	32.81	4.30E + 06	0.902	39.38	1.33E + 06	0.913
P4	21.24	2.43E + 07	0.900	32.81	5.73E + 06	0.902	39.38	1.78E + 06	0.913
P2/3	89.46	1.84E + 03	0.940	117.71	7.09E + 05	0.931	137.51	4.90E + 07	0.936
D1	51.91	8.91E + 04	0.932	75.26	2.87E + 03	0.925	88.45	1.41E + 04	0.931
D2	54.95	8.94E + 04	0.364	77.94	3.18E + 03	0.928	91.74	1.56E + 04	0.934
D3	2.83	5.83E + 07	0.829	3.23	8.01E + 07	0.874
D4	11.47	1.32E + 09	0.997	10.99	1.11E + 09	0.998	11.46	1.28E + 09	0.997
A2	26.07	4.59E + 06	0.921	36.99	1.22E + 06	0.915	41.32	2.86E + 05	0.927
A3	26.07	6.88E + 06	0.921	36.99	1.83E + 06	0.915	41.32	4.29E + 05	0.927
A4	26.07	9.18E + 06	0.921	36.99	2.44E + 06	0.915	41.32	5.73E + 05	0.927
R1	26.07	7.47E + 06	0.900	32.81	1.43E + 06	0.902	39.38	4.44E + 05	0.913
R2	3.50	3.02E + 10	0.895	3.73	9.18E + 07	0.909	–	–	–
R3	6.13	1.93E + 08	0.986	6.44	2.27E + 08	0.988	5.84	1.81E + 08	0.983
DP:PP:PS
F1	31.62	1.23E + 06	0.932	31.18	2.34E + 06	0.917	30.98	2.43E + 06	0.870
F2	34.65	8.86E + 05	0.939	33.96	1.32E + 06	0.925	34.07	1.30E + 06	0.882
F3	34.65	1.77E + 06	0.939	33.96	2.64E + 06	0.925	34.07	2.60E + 06	0.882
P2	28.73	6.07E + 06	0.925	28.53	5.06E + 06	0.886	28.06	8.71E + 06	0.856
P3	28.73	9.11E + 06	0.925	28.53	7.59E + 06	0.886	28.06	1.31E + 07	0.856
P4	28.73	1.21E + 07	0.925	28.53	1.01E + 07	0.886	28.06	1.74E + 07	0.856
P2/3	105.01	4.04E + 04	0.940	104.81	1.90E + 04	0.938	103.73	1.47E + 04	0.902
D1	58.56	1.38E + 04	0.944	66.67	2.63E + 04	0.932	65.89	3.09E + 04	0.893
D2	68.75	2.06E + 04	0.946	72.06	3.78E + 04	0.934	67.79	4.08E + 04	0.896
D3	4.68	1.59E + 08	0.968	5.22	2.05E + 08	0.975	5.02	1.89E + 08	0.948
D4	10.14	8.56E + 08	0.999	10.25	8.82E + 08	0.999	10.54	9.63E + 08	0.999
A2	31.62	8.74E + 06	0.932	31.18	4.67E + 06	0.917	30.98	4.86E + 06	0.870
A3	31.62	5.02E + 06	0.932	31.18	7.01E + 06	0.917	30.98	7.28E + 06	0.870
A4	31.62	6.69E + 06	0.932	31.18	9.34E + 06	0.917	30.98	9.71E + 06	0.870
R1	28.73	3.04E + 06	0.925	28.53	3.99E + 06	0.908	28.06	4.37E + 06	0.856
R2	4.98	1.61E + 08	0.973	5.48	2.02E + 08	0.978	5.32	1.90E + 08	0.956
R3	7.05	2.83E + 08	0.995	7.42	3.28E + 08	0.995	6.98	3.07E + 08	0.991

The decreased solid residue with increasing heating rates reflects the enhanced volatiles and carbon conversion degree of synergy reported previously in the literature(Burra and Gupta 2018; Jiang et al. 2022). As seen in Table S2, pyrolysis solid residual yields are between 19.06 - 17.25 wt.% for the single DP, reducing to as high as 11.14 (DP: PS at 10 K/min) and low 4.96 (DP: PP: PS at 30 K/min). Additionally, an apparent synergistic effect is observed at peak degradation temperatures. When the plastics are mixed in binary mixtures, the maximum weight loss rate is reduced significantly compared to individual pyrolysis degradation at all heating rates. Although the final residual weight is 0% for all samples and the weight loss rates ranges were similar for PP and PS, the weight loss heating rates vary when the plastics are mixed, proving synergistic effects during degradation (also observed in the deconvolution peak in figure 2d). Alternatively, the reduced degradation temperature ranges (seen in DTG curves) and decreased maximum weight loss rate for the first peak in the binary DP and plastic mixtures (reflecting biomass degradation) compared to the individual DP degradation reflect synergy as well.

3.4 Reaction mechanisms and kinetic parameters using coats redfern models

The Coats-Redfern model showed the reaction mechanism for the single, binary, and ternary mixtures at the three heating rates (Table S1). The major weight loss regions are considered for the kinetic parameter studies, as reported in Table S2. For single feeds and binary plastic feeds, only one stage is studied, while for biomass plastic binary and ternary mixtures, the kinetic parameters for the two distinct weight loss regions are studied (Stage I and Stage II).

The solid-state reaction mechanisms by plotting linear regression models helped calculate AE and A. Table 2 (first major weight loss region) and Table 3 (second major weight loss region) show the kinetic parameters – AE and A – received from all models that showed R² values higher than 0.8. Based on the main peaks associated with the significant degradation of the samples (figure 1 b, d, f, h, j, l, n) reflected in the main stages of degradation mentioned in Table S2, the kinetic parameters were calculated from the regression models and reported. While the AE suggests the minimum energy required for the reaction to occur, the A reflects the number of times the molecules hit to trigger reactions (Zaker et al. 2021). Ideally, the lower the AE, the faster the reaction occurs; therefore, lower values are favoured for pyrolysis (Zaker et al. 2021), (Dubdub and Al-Yaari 2021). Additionally, a higher than and less than E + 9 s⁻¹ show dependence and independence on the surface area of the feeds.

Table 3. Kinetic parameters of feeds at various heating rates at the second major mass loss region (Stage II).

	10 K/min			20 K/min			30 K/min
Reaction Models	AE (kJ/mol)	A (s^1)	R^2	AE (kJ/mol)	A (s^1)	R^2	AE (kJ/mol)	A (s^1)	R^2
DP:PP
F1	66.62	7.54E + 03	0.800	–	–	–	61.92	1.80E + 04	0.859
P2	27.18	9.47E + 06	0.844	27.89	1.00E + 07	0.805	30.32	6.36E + 06	0.923
P3	27.18	1.42E + 07	0.844	27.89	1.50E + 07	0.802	30.32	9.55E + 06	0.923
P4	27.18	1.90E + 07	0.844	27.89	2.00E + 07	0.802	30.32	1.27E + 07	0.923
P2/3	104.81	2.11E + 04	0.897	85.51	1.62E + 04	0.866	114.20	1.05E + 05	0.948
D1	65.99	2.81E + 04	0.886	67.51	2.95E + 04	0.853	72.26	1.10E + 04	0.943
D2	83.12	2.72E + 03	0.873	82.21	4.56E + 03	0.897	87.86	2.21E + 03	0.929
D4	31.94	1.47E + 11	0.885	29.23	7.84E + 10	0.861	30.35	1.02E + 11	0.899
A2	66.62	1.51E + 04	0.800	–	–	–	61.92	3.60E + 04	0.859
A3	66.62	2.26E + 04	0.800	–	–	–	61.92	5.41E + 04	0.859
A4	66.62	3.01E + 04	0.800	–	–	–	61.92	7.21E + 04	0.859
R1	27.18	4.74E + 06	0.844	27.89	5.01E + 06	0.802	30.32	3.18E + 06	0.923
DP:PS
F1	68.43	3.29E + 03	0.896	95.59	6.31E + 04	0.901	75.64	1.60E + 03	0.901
F2	134.26	2.79E + 08	0.879	179.22	5.39E + 11	0.868	134.42	1.31E + 08	0.875
F3	134.26	1.40E + 08	0.879	179.22	2.69E + 11	0.868	134.42	6.54E + 07	0.875
P2	29.10	5.18E + 06	0.885	46.24	5.16E + 05	0.908	37.73	1.87E + 06	0.902
P3	29.10	7.77E + 06	0.885	46.24	7.82E + 05	0.908	37.73	2.81E + 06	0.902
P4	29.10	1.04E + 07	0.885	46.24	1.04E + 06	0.908	37.73	3.74E + 06	0.902
P2/3	109.94	1.48E + 05	0.924	161.70	9.08E + 08	0.930	136.24	9.09E + 06	0.937
D1	69.52	8.01E + 03	0.916	103.97	9.31E + 04	0.921	86.98	4.05E + 03	0.932
D2	88.30	5.87E + 03	0.917	111.32	3.99E + 06	0.924	106.21	9.22E + 04	0.929
D4	34.85	3.06E + 09	0.938	39.85	7.66E + 09	0.917	35.22	2.92E + 09	0.927
A2	68.43	6.57E + 03	0.896	95.59	3.16E + 04	0.901	75.64	3.19E + 03	0.901
A3	68.43	9.86E + 03	0.896	95.59	2.10E + 04	0.901	75.64	4.79E + 03	0.901
A4	68.43	1.31E + 04	0.896	95.59	1.58E + 04	0.901	75.64	6.38E + 03	0.901
R1	29.10	2.59E + 06	0.885	46.24	2.61E + 05	0.908	37.73	9.36E + 05	0.913
DP:PP:PS
F1	53.02	1.56E + 03	0.922	111.68	4.68E + 06	0.888	90.95	1.47E + 04	0.933
F2	137.80	2.99E + 08	0.867	–	–	–	159.81	6.29E + 09	0.875
F3	137.80	1.50E + 08	0.867	–	–	–	159.81	3.14E + 09	0.875
P2	41.96	1.03E + 06	0.920	53.18	1.01E + 07	0.918	49.48	4.65E + 05	0.936
P3	41.96	1.54E + 06	0.920	53.18	1.52E + 07	0.918	49.48	6.97E + 05	0.936
P4	41.96	2.05E + 06	0.920	53.18	2.03E + 07	0.918	49.48	9.29E + 05	0.936
P2/3	149.27	7.85E + 07	0.940	182.63	3.80E + 04	0.936	171.91	1.83E + 09	0.951
D1	95.73	1.78E + 04	0.936	117.90	5.27E + 04	0.932	110.69	1.49E + 05	0.948
D2	113.05	3.03E + 05	0.940	140.80	7.58E + 04	0.935	130.88	3.58E + 06	0.951
D3	–	–	–	–	–	–	12.38	2.13E + 07	0.809
D4	31.34	1.38E + 11	0.927	37.16	1.77E + 09	0.908	35.16	2.65E + 11	0.926
A2	77.96	2.16E + 03	0.922	111.68	9.36E + 06	0.888	90.95	7.34E + 03	0.933
A3	77.96	3.16E + 03	0.922	111.68	1.40E + 07	0.888	90.95	4.89E + 03	0.933
A4	77.96	4.33E + 03	0.922	111.68	1.87E + 07	0.888	90.95	3.67E + 03	0.933
R1	42.19	5.16E + 05	0.920	53.18	8.00E + 06	0.918	49.48	2.32E + 05	0.936

The calculated AE for DP, PP and PS ranged between 3.87 - 46.44, 115.29 - 654.59, 25.59 - 519.08 kJ/mol, and the A factor ranged between E + 04 – E + 09, E + 04 – E + 35, E + 06 – E + 36 s⁻¹. The range for the plastics is larger than the biomass for both the kinetic parameters. Furthermore, when the plastics are mixed, the range increases and reduces for the AE and A, respectively (30.42 - 424.66 kJ/mol and E + 06 – E + 29 s⁻¹). Furthermore, the ranges are much lower during the two stages than the individual plastics values for binary and ternary biomass-plastic mixtures. Moreover, the AE for the Stage I, for DP: PP, DP:PS, and DP:PP:PS ranged from 2.79 - 121.49, 3.50 - 137.51, 4.98 - 105.01, and Stage II ranged between 27.18–114.20, 29.10–179.22, 31.34– 182.63 kJ/mol. It is observed that the ranges in Stage I are higher than the values in Stage II – however, the highest values are still much lower compared to the AE required for plastics degradation. Furthermore, although the range for ternary wastes is smaller than the binary biomass-plastic wastes, the lowest energy required is still higher than the binary biomass-plastic and single biomass mixtures. It is evident in other publications that the overall AE has increased when plastic is mixed with biomass (with respect to the latter). However, it depends on the type of biomass and plastic and the blending ratios (refer to Table 4). For example, mixing more plastic with textile dyeing sludge was shown to increase the AE to values close to the values for the individual pyrolysis of plastics and much higher than the biomass (Ding et al. 2021).

Table 4. Average activation energy (AE) results and studied models from various publications.

Feeds	Average AE (kJ/mol)	Models	Reference
Textile dyeing sludge and medical plastic wastes	Syringe – 278.29 Medical bottle – 247.64 TDS – 43.00 Increasing plastic fraction with TDS – Syringe – 149.47 - 271.31 Medical bottle – 142.85 −273.65	Coats Redfern	(Ding et al. 2021)
Organic food waste and PVC	Increasing PVC – 34.17 - 183.58	Coats Redfern	(Tang et al. 2018)
Corn cob and HDPE (1:0, 0:1, 1:1) at different heating rates	43.61 - 83.03; 412.32 - 510.72 and 28.98 - 93.18	Coats Redfern	(Liew et al. 2021)
Pine needles and styrofoam (PS) (1:1)	96.44	KAS	(Varma et al. 2021)
	109.73	OFW
Samanea saman seeds and PET (1:0, 0:1, 1:1, 3:1, 5:1)	188.28, 230.71, 166.98, 129.51, 150.71	KAS	(Mishra, Sahoo, and Mohanty 2019)
	187.20, 230.55, 168.57, 131,20, 150.83	FWO
	204.93, 225.64, 178.50, 138.56, 157.82	Friedman
	188.45, 231.03. 166.96, 129.88, 150.95	Starink
Bamboo sawdust and LLDPE (ratios: 1:0, 3:1, 1:1. 1:3, 0:1)	265, 357, 371, 143, 207	KAS	(Alam et al. 2020)
	265, 368, 400,165, 230	OFW
	352, 468, 356, 255, 175	FM
	294, 397, 376, 188, 204	Isoconversional method/average of above three models

Similarly, increasing PVC increased AE from 34.17–183.58 kJ/mol (Tang et al. 2018). Iso-conversational modeling results from pine needles and Styrofoam co-pyrolysis showed AE, higher than the former and lower than the latter. Also, the more plastic, the higher the AE (Mishra, Sahoo, and Mohanty 2019). It is worth noting that such behaviour has rarely been opposed; for example, when LLDPE and bamboo sawdust were mixed, the AE reduced with respect to the biomass (refer to Table 4) (Alam et al. 2020), mainly attributed to the structure and arrangement of the polymer leading to higher thermal reactivity in the blends. However, our feeds follow typical biomass-plastic co-pyrolysis behaviour. Additionally, although the lowest values range from E + 03 for the biomass-plastic mixtures, the highest values are E + 09, E + 10, and E + 08 for Stage I for DP:PP, DP:PS, and DP:PP:PS, respectively, and E + 11 for Stage II for all feeds. The A values show lower ranges (similar to AE ranges) when the feeds are co-pyrolyzed relative to individual plastic samples.

The highest R² values for the samples were amongst the diffusion models (D1, D2, and D4), Mampel power law (P2/3), first-order reaction (F1), and the nucleation models (A2, A3, and A4) had the highest R² values. The diffusion model – Ginstlinge Brounshtein (D4) was the most common fit reaction mechanism, including Stage I for DP, DP: PP, DP: PS, DP: PP: PS, and the DP: PS for Stage II, for all heating rates. Using the Coats Redfern models, another study has reported a similar reaction mechanism for date palm fibres kinetics (Raza et al. 2022). Additionally, plastics (both single and binary) followed one of the following mechanisms: P2/3 and D2, D1, F1, A2, A3, A4 – the last four being the highest R² for both the 10 and 20 K/min for PP:PS degradation and 30 K/min for PS. The majority of the Stage II mechanisms followed the Power Law (P2/3), with the exceptions of DP: PP – 10, DP: PP – 20, and DP: PS 10 K/min with D1, D3, and D3, respectively.

For the single feeds, with a single main degradation step, the AE for the biomass is significantly lower than the plastics, which was also seen in other biomass-plastic studies (Chen et al. 2021). The biomass energy for different heating rates ranges from 15.99-16.85 kJ/mol, while the PP and PS energies range from 256–533 and 205.32-519.08 kJ/mol. The highest AE arose when the reaction mechanism follows the power-law – P2/3. Other studies have reported AE of 249.7 kJ/mol for LDPE; 312 for PS, 337 for PP, 341 for LDPE, and 445 for HDPE (H. Li et al. 2005); 151.5 for PVC, 226.8 for PET, and 210.8 for PS (Özsin, Pütün, and Pütün 2019); 295.65 for PP and 254.55 for LDPE (Uzun and Yaman 2017) degradation using various kinetic models, and owing to the thermal stability of plastic samples.

Additionally, the AE is lower, especially at lower heating rates, for the binary plastics than the single plastics, which showed an easier degradation pathway when mixing feeds. The lower values are due to differences in reaction mechanisms, with the highest R² values, in single and binary feeds. Subsequently, the two separate stages of degradation for DP: PP, DP: PS, and DP: PP: PS yields separate kinetic parameters. In Stage I, the reaction mechanisms for every heating rate follow D4, which reflects biomass degradation at lower temperatures, followed by plastics in Stage II. The values are slightly lower for DP: PP (average – 10.98 kJ/mol) than DP: PS (11.30 kJ/mol); however, both are lower than the single DP AE. Therefore, confirming quicker reaction mechanisms when mixed with plastics. Furthermore, the ternary mixtures follow the D4 reaction mechanism in Stage II – but the AE is lower than in the binary mixtures (average – 10.31 kJ/mol).

Compared to Stage I, Stage II has much higher AE, which confirms plastic degradation occurring at higher temperatures. However, the values are much lower than the individual plastic feeds. Like Stage II, the AE is lower for DP: PP than DP:PS, averaging 87.46 and 110.9 kJ/mol. Alternatively, the ternary mixtures have higher values than the binary mixtures (average – 167.9 kJ/mol). The higher values in Stage II of ternary samples further reflect the two-plastic degradation at higher temperatures. Additionally, the binary plastic mixtures PP: PS averaged 216.4 kJ/mol.

The A of the single, binary and ternary mixtures behave similarly to AE. Moreover, for PS-30, PP: PS-10 and 20 – with multiple highest R² reaction mechanisms – the A 1.95E + 13, 7.09E + 10, and 1.65E + 11 s^1, respectively. Furthermore, the biomass feed (at E + 09 s⁻¹) reflects lower values for single plastic feeds (E + 12 – E + 36 s⁻¹). The binary plastic mixtures are much lower than the single plastic feeds, like the AE values (E + 10 to E + 18 s⁻¹). For Stage, I, for the binary biomass and plastic mixtures, the A for heating rates are at E + 09 s⁻¹.

Furthermore, the values become lower to E + 08 s⁻¹ for ternary mixtures. Subsequently, for Stage II, the A varies with different heating rates. DP: PP ranges from E + 03 to E + 05 s^−1, and DP: PS from E + 06 to E + E11 s⁻¹. Finally, the values range from E + 04 to E + 09 s⁻¹ for the ternary mixtures. Additionally, values higher than and less than E + 9 s⁻¹ show dependence and independence on the surface area of the feeds. It is clear from the results that biomass degradation does not rely on surface area, but the plastics are otherwise when pyrolyzed individually. Furthermore, the reliance on the surface is completely reduced since all the values are equal to or less than E + 9 in binary and ternary mixtures (at both stages).

3.5 Thermodynamic parameters

The AE and A values of the best fit models were employed to calculate the thermodynamic parameters from equations 12-14. Table 5 shows the change in enthalpy (ΔH), Gibbs free energy (ΔG), and change in entropy (ΔS) values. Since ΔH is positive for all samples, it shows that energy should be provided outside to help the reaction occur. Positive values of ΔH and ΔG reflect endothermic and non-spontaneous reactions for all samples and all studied reaction mechanisms.

Table 5. Thermodynamic parameters of single, binary and ternary biomass and plastic equi-weight blends at various heating rates.

	Stage I			Stage II
Feeds – heating rate	ΔH (kJ/mol)	ΔG (kJ/mol)	ΔS (kJ/mol K)	ΔH (kJ/mol)	ΔG (kJ/mol)	ΔS (kJ/mol K)
DP – 10	11.32	51.46	−0.0715
DP – 20	12.14	51.48	−0.0694
DP – 30	11.91	52.78	−0.0708
PP – 10	527.3	224.1	0.415
PP – 20	250.1	222.6	0.037
PP – 30	426.2	223.1	0.271
PS – 10	336.4	206.6	0.189
PS – 20	513.2	214.3	0.429
PS – 30	199.4	203.6	−0.0059
PP:PS – 10	166.3	202.4	−0.0524
PP:PS – 20	172.9	204.7	−0.0456
PP:PS – 30	292.5	219.0	0.102
DP:PP – 10	6.050	53.54	−0.0859	59.94	187.61	−0.1755
DP:PP – 20	6.330	54.47	−0.0852	76.05	217.35	−0.190
DP:PP – 30	6.460	55.63	−0.0849	108.0	229.03	−0.164
DP:PS – 10	6.790	54.04	−0.0839	29.14	56.81	−0.0403
DP:PS – 20	6.270	54.79	−0.0854	155.9	217.76	−0.0888
DP:PS – 30	6.660	55.33	−0.0844	130.3	220.77	−0.127
DP:PP:PS – 10	5.550	53.77	−0.0873	143.5	205.10	−0.0892
DP:PP:PS – 20	5.570	54.70	−0.0873	176.8	238.75	−0.0886
DP:PP:PS – 30	5.750	55.74	−0.0867	165.9	229.07	−0.0885

Furthermore, the ΔG values ranged from 51.46–52.78 kJ/mol for the biomass (DP), and 203.64–224.14 for the plastics at different heating rates. The ΔG values of the binary plastic mixtures are lower than all heating rates of PP and the lesser heating rates of PS. As previously discussed in the the plastic degradation stage, the Stage II values of the biomass and plastics mixtures show values of ΔH and ΔG greater than 59.93 and 187.6 kJ/mol, respectively. Furthermore, the various heating rates’ Stage I ΔH, and ΔG values for the biomass plastic mixtures range from 5.55–6.79 kJ/mol and 53.54–55.74 kJ/mol, respectively.

Also, the negative values of ΔS reflect the disorder of products less than the initial reactants. The results show that it is negative for most single, binary, and ternary feeds. However, for the different heating rates of PP and the 30 K/min for PS and PP:PS feeds, the ΔS values were positive. Positive ΔG, ΔH, and negative ΔS have previously been reported in date palm fibres (Raza et al. 2022), vegetable wastes (Elkhalifa et al. 2022), and high ash sewage sludge (Naqvi et al. 2019). Alternatively, biomass-plastic (Zaker et al. 2021) and biomass-biomass mixtures (Parthasarathy et al. 2022) have shown positive ΔG and H values, but both negative and positive ΔS values due the complicated nature products generation, which needs to be studied using advanced molecular techniques (not in the scope of this study).

4. Conclusion

Co-pyrolysis blends of biomass and plastics are increasingly being studied to improve efficient waste management and value-added product generation. This study observed a positive synergy when DP is mixed with the plastics (PP and PS) in the solid-state at lower heating rates (10 and 20 K/min) and a passive synergy at higher heating rates (30 K/min). Alternatively, when the plastics are mixed, there is a passive synergy at all heating rates due to the absence of any char yield. Additionally, the diffusion model Ginstlinge Brounshtein (D4) was the most common best fit reaction mechanism for Stage I for DP, DP: PP, DP: PS, DP: PP: PS, and the DP: PS for Stage II, for all heating rates, followed D4 reaction mechanism. In Stage I, the activation energy (AE) is slightly lower for DP: PP (average – 10.98 kJ/mol) than DP: PS (11.30 kJ/mol); however, both are lower than single DP with an AE (average 16.52 kJ/mol). Therefore, confirming quicker reaction mechanisms and degradation of DP when mixed with plastics.

Furthermore, Stage II of the mixtures’ degradation aligns with the degradation of the plastic in both the binary and ternary samples due to a relatively higher AE than Stage II and DP. Like Stage I, the AE is lower for DP: PP than DP:PS, averaging 87.46 and 110.93 kJ/mol compared to individual plastics. Additionally, the binary plastic mixtures PP: PS averaged 216.43 kJ/mol. Alternatively, the ternary mixtures have higher values than the binary mixtures (average – 167.93 kJ/mol). The higher values in Stage II of ternary samples further reflect the two-plastic degradation at higher temperatures.

The pre-exponential factors (A) of the single, binary and ternary mixtures behave similarly to AE. It is clear from the results that biomass degradation does not rely on surface area, but the plastics are otherwise when pyrolyzed individually. Furthermore, the reliance on the surface is reduced significantly since all the values are equal to or less than E + 9 in binary and ternary mixtures (at both stages). Positive values of ΔH and ΔG reflect endothermic and non-spontaneous reactions under all conditions and samples. Furthermore, the ΔS was negative for the DP and plastic mixtures, reflecting disorder due to bonds breaking is lower than the initial reactants. However, for the three heating rates of PP and the 30 K/min for PS and PP:PS feeds, the ΔS values were positive, showing varying disorders amongst the studied feeds. Future studies should utilise the current study to upscale the co-pyrolysis of DP and SUPs and analyze the generation of energy generation products (oil, gas and oil). Additionally, mixing biomass is desirable due to the decreased energy requirement for biomass-plastics binary and ternary mixtures. However, future studies should employ model-free kinetics to validate the model-based kinetic and thermodynamic values from this study.

Acknowledgements

Open Access funding provided by the Qatar National Library.

Declaration of statement

The authors report there are no competing interests to declare.

Acknowledgment

This publication was made possible by NPRP – Standard (NPRP-S) 11 cycle grant – NPRP11S-0117-180328 from the Qatar National Research Fund (a member of Qatar Foundation). The findings herein reflect the work and are solely the responsibility of the authors.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

All data used in this study are available upon request.

Additional information

Funding

This work was supported by Qatar National Research Fund: [Grant Number NPRP11S-0117-1803,NPRP11S-0117-180328].