Introduction

Rapid development of daily life leads to high energy consumption and the depletion of traditional fossil fuels. Searching for new renewable energy sources and making efficient use of traditional energy are the two main directions of energy systems (Liu et al. 2022; Zhang et al. 2022b). Recently, biomass as a kind of low-cost and abundant resource has attracted much researcher’s attention all over the world because of alleviating energy pressure and greenhouse gas emissions associated with environmental issue (Ahmad et al. 2019; Yu et al. 2022).

Currently, the major biomass conversion technologies are incineration, pyrolysis (Feng et al. 2022), hydrothermal (Wang et al. 2021), fermentation composting, and fine chemical production (Nenciu et al. 2021). The incineration method requires high operation cost and energy consumption on flue gas treatment. Meanwhile, the landfill method could result in land occupation and risk of secondary pollution. Moreover, engineering and economic feasibility of fine chemicals productions have yet not been fully demonstrated. Remarkably, fermentation is an important method of biomass waste reutilization to produce biofuel, fertilizers, and combustible gas energy with a large amount of fermentation wastes (Barzallo-Bravo et al. 2019; Wang et al. 2022). Importantly, fermentation technology deals with both techniques, i.e., aerobic and anaerobic methods (Ma and Liu 2019). Fermentation residues contain some useful components such as proteins, carbohydrates, and trace compounds, which are widely used in substrate culture (Gupta et al. 2022). Fermented sawdust substrate may be a suitable potting medium for plant growth (Hoang et al. 2019), seed germination (Ahn et al. 2021), mushroom cultivation (He et al. 2022), etc. Ultimately, if they were not handled skillfully, it might cause serious environmental pollution and importantly, energy waste. Thus, the approaches for reusing or handling fermentation waste are urgently required (Wang et al. 2021).

Pyrolysis technologies are mainly used for value‑added products that involve the conversion of organic materials into solids (biochar), condensable liquids (bio-oil), and non-condensable volatiles (gases) (Amenaghawon et al. 2021, Buessing and Goldfarb 2012). Biochar has been widely used in environmental remediation, such as soil improvement, waste water treatment, and antibiotic removal. The absorption capacity of the biochar derived from timber industry wood is found 229 mg/g and 210 mg/g at 45℃ and 25℃, respectively (Herath et al. 2022). Yang et al. (Li et al. 2022) found that activated biochar derived from corncob xylose residue possessed a high surface area of 3043 m2/g and an adsorption capacity of 1429 mg/g which are highly useful to remove antibiotics from waste water. Furthermore, stillage residue–derived biochar was observed to remove silver ions from aqueous solutions with a maximum capacity of 90.06 mg/g (Yao et al. 2015). Moreover, biochars resulted from fermentation residues had been used to make soil remediation agents (Wang et al. 2022) and heavy metal adsorbents (Zhang et al. 2017). It reflects that applying pyrolysis to produce biochar from fermentation residues could be an effective approach to reduce environment issues and recycling biomass energy.

Previously, pyrolysis of pine sawdust to investigate basic characteristics had been performed (Gao et al. 2013; Tian et al. 2021; Zhang et al. 2022a). However, only a few studies can be found associated with pyrolysis process and potential application of biochar derived from fermentation pine sawdust. So, in this study, fermented pine sawdust (FPD) was used as a representative of fermentation residue. The primary purposes of this research were to investigate (1) bioenergy recovery potential of fermented biomass waste during pyrolysis process and (2) industry and elemental analysis. In current research study, pine sawdust (PD) was used as reference material, and the matrix of FPD was based on PD. Besides, the biochars were characterized to explore the effects of fermentation on pore structure formation and surface functional group distribution. Moreover, the applicability of biochar by methylene blue (MB) adsorption experiments was also tested. Overall, the results of this investigation can provide a better understanding of fermented pine sawdust pyrolysis behaviors and basis for recovery of the biomass energy of fermentation residues.

Material and methods

Materials and characterization

PD were taken from a wood processing plant in Xingtai (Hebei, China), and FPD were derived from the mixed fermentation of yeast and pine sawdust at a mass ratio of 1:20 for 15 days at 30℃. The total nitrogen content, amino nitrogen content, and solid content of yeast extract were 6.5%, 2.0%, and 60%, respectively. The PD and FPD were dehydrated at 105℃ using an oven and grinded into fine powders (20–40 mesh). An industrial analyzer (SDTGA5000) was used for proximate analysis to determine the volatiles (V), moisture (M), f”xed carbon (FC), and ash (A) contents. The composition of C/H/N/S/O in the PD and FPD samples was determined with elemental analyzer (Vario MACROCHN).

Pyrolysis characteristics and experimental process

As shown in Fig. 1, pyrolysis characteristics of PD and FPD were analyzed in terms of mass loss using a TG analyzer (TGA/DSC, METTLER Company) with flow of high purity N2 (≧99.99%). Samples about 10 mg were distributed in open alumina crucible and heated from 30 to 800 °C with ramp rates of 20 °C/min, 30 °C/min, 40 °C/min, and 50 °C/min, under a flow rate of 50 mL/min. The thermogravimetric data for kinetic calculation were collected and processed following ICTAC Kinetics Committee recommendations. Meanwhile, the corresponding samples were designated as PD-X or FPD-X, where X represents the different pyrolysis heating rates. In addition, the PD and FPD were put into a fast-annealing furnace to pyrolyze at 500 °C, 600 °C, 700 °C, and 800 °C at a flow rate of 300 mL/min for 60 min. The samples of pyrolytic char were collected and named as PD-X or FPD-X (X represents final temperatures). In addition, the comprehensive pyrolysis index (CPI) is introduced to evaluate the pyrolysis behavior (Eq. (1)) (Bi et al. 2021), the meaning of each letter in the formula has been clarified in Table 2.

Fig. 1
figure 1

The pyrolysis process of PD and FPD

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$$CPI=\frac{{DTG}_{\mathrm{max}}{DTG}_{\mathrm{mean}}{M}_{\infty }}{{T}_{i}{T}_{p}\Delta {T}_{1/2}}$$
(1)

Pyrolysis kinetic models

In this section, the fundamental rate equation (Eq. (2) and Eq. (3)) (Borel et al. 2020; Chhabra et al. 2019) is used in the pyrolysis kinetics calculations.

$$\frac{d\alpha}{dt}=k\left(T\right)f\left(\alpha\right)=A exp\left(-\frac{{E}_{\alpha}}{RT}\right)f\left(\alpha\right)$$
(2)
$$\alpha=\frac{{m}_{0}-{m}_{t}}{{m}_{0}-{m}_{r}}$$
(3)

where k(T) is the rate constant and f(α) is the reaction model function, which is f(α) = (1-α) n. Eα is the activation energy. R expresses the general gas constant (R = 8.314 J⋅mol−1⋅K−1). T stands for the reaction temperature. t represents the reaction time, and α is the conversion ratio. m0, mt, and mr are the initial, instantaneous, and residue weights of the sample, respectively.

Equation (2) was simplified to obtain Eq. (4), and the calculation formula (Eq. (5)) for g(α) was obtained (Khiari et al. 2019, Sarkar and Wang 2020, Soria-Verdugo et al. 2020).

$$\frac{d\alpha}{dT}=\frac{A}{\beta }\mathrm{exp}\left(-\frac{{E}_{\alpha}}{RT}\right)f\left(\alpha\right)$$
(4)
$$g\left(\alpha\right)=\underset{0}{\overset{\alpha }{\int }}\frac{d\alpha}{f\left(\alpha\right)}=\frac{A}{\beta }\underset{{T}_{0}}{\overset{T}{\int }}\mathrm{exp}\left(-\frac{{E}_{\alpha}}{RT}\right)dT$$
(5)

Three thermolysis kinetic models were used in this paper to evaluate the activation energies of the reactions—Eqs. (6, 7, 8) (Meng et al. 2015; Ni et al. 2022; Zhang et al. 2019).

$$\mathrm{KAS model}:\mathrm{ln}\left(\frac{\beta }{{T}^{2}}\right)=\mathrm{ln}\left(\frac{AR}{{E}_{\alpha }g\left(\alpha \right)}\right)-\frac{{E}_{\alpha}}{RT}$$
(6)
$$\mathrm{FWO model}:\mathrm{ ln}\beta =\left(\frac{{AE}_{\alpha }}{Rg\left(\alpha \right)}\right)-5.331-1.052\frac{{E}_{\alpha}}{RT}$$
(7)
$$\mathrm{Starink model}:\mathrm{ln}\left(\frac{\beta }{{T}^{1.92}}\right)=C-1.0008\frac{{E}_{\alpha}}{RT}$$
(8)

Thereafter, thermodynamic assessment thermodynamic parameters (Agnihotri et al. 2022; Fu et al. 2022) were for thermodynamic evaluation.

$$A=\frac{E\times \beta \times exp\left(\frac{E}{{T}_{p}\times R}\right)}{{T}_{P}^{2}\times R}$$
(9)
$$\Delta H=E-R\times {T}_{\alpha }$$
(10)
$$\Delta G=R\times {T}_{p}\times ln\left(\frac{{K}_{B}\times {T}_{p}}{{A}_{0}\times h}\right)+E$$
(11)
$$\Delta S=\frac{\left(\Delta H-\Delta G\right)}{{T}_{p}}$$
(12)

where Tp denotes the average peak absolute temperature obtained from DTG plot and KB and h are the Boltzmann constant (1.381 × 10–23 J/K) and the Planck’s constant (6.626 × 10–34 J·s), respectively.

Characteristic analysis of biochar

The surface morphology of biochar was examined using a scanning electron microscopy (SEM) (JEOL JSM-6700F, Japan). The Fourier transform infrared spectra (4000–400 cm−1) were collected at a resolution of 4 cm−1 with 16 scans co-added using a Nicolet 6700 FTIR (Thermo Electron Corporation, USA). Besides, biochar samples were tested for adsorption applications. A 0.1-g adsorbent was added to 100-mL MB solution (5 mg/L) stirring with a magnetic stirrer to promote the reaction (25 °C) and sampled for the determination of MB concentration using an ultraviolet spectrophotometer (V-1200 MAPADA, Shanghai) at 665 nm. The standard curve of MB determined was demonstrated in Eq. (13), and the amount of MB adsorbed at equilibrium (qe (mg/g)) was calculated by the Eq. (14) (Liu et al. 2021). Other adsorption model calculation formulas are shown in Table 5.

$$Y=6.54X-0.604 \left({R}^{2}=0.999\right)$$
(13)
$${q}_{e}=\frac{{C}_{0}-{C}_{e}}{W}V$$
(14)

where X is the absorbance of MB, Y is the concentration of MB solution (mg/L), qe (mg/g) is the adsorption capacity, C0 (mg/L) and Ce (mg/L) are the initial and equilibrium concentration, respectively, V is the volume of MB solution and W is the mass of PD-X or FPD-X.

Results and discussions

Characterization of PD and FPD

The proximate and ultimate analyses of PD and FPD are shown in Table 1. The ash content of FPD is 4.48%, higher than that of PD (1.86%) in the present study, but lower than that of the reported biomasses (Tao et al. 2021; Zhang et al. 2022b) such as rice straw (16.90%), cabbage waste (12.98%), and cotton stalk (15.60%). The volatile content is 73.89%, lower than that of PD (81.77%) while fixed carbon is 21.63%, respectively. The results clearly demonstrate that fermentation would affect the products’ properties due to the change of volatile content, ash content, and fixed carbon content. For example, the ash composition of biomass was made up of inorganic salts and oxides, and the inorganic salts and oxides, and these constituents may catalyze and promote pyrolysis process, thus affecting the yield of pyrolytic products. The elemental analysis showed that C and O were the major elements contained in FPD, which accounted for 31.59 and 62.20%, respectively, the contents of H and N were 5.12 and 0.93%, and the content of S was only 0.16%. The contents of O and N in FPD were higher, but C was lower than those in PD, which might be attributed to residue sediments including proteins and amino acids and fermentation by-products on the PD during the process of microbial fermentation. The high heating value is 19.22 MJ kg−1, which is higher than that of some terrestrial biomass feedstock, such as cabbage waste (17.29 MJ kg−1), rice husk (16.24 MJ kg−1), and pea waste (18.42 MJ kg−1). These results confirm that FPD is favorable when considered for a pyrolysis process.

Table 1 Physicochemical characterization of PD and FPD
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Pyrolysis characteristics of PD and FPD

The TG/DTG curves of samples at different heating rates are shown in Fig. 2. Although the compositions of PD and FPD were different, they had similar mass loss trend. The main pyrolysis process could be divided into four stages: water devolatilization, active pyrolysis stage, passive pyrolysis stage, and final stage. The water devolatilization was attributed to moisture evaporation and small molecule volatile organic compounds up to 200℃. In line with previous research studies, pine has three main components, hemicellulose, cellulose, and lignin, of which cellulose and hemicellulose account for 65.9–70.9%. Active pyrolysis occurred between 250 and 450 °C with a sharp decrease in weight resulting about 74.09–70.53% of PD and 62.76–56.10% of FPD decomposition of the total weight, respectively. Organic macromolecules such as hemicellulose, cellulose, proteins, and fatty acid decomposition were mainly pyrolyzed in this stage. The third and main stage, i.e., passive stage (450–600℃), is associated with lignin decomposition. The last stage (600–800℃) was attributed with the degradation of inorganic fragments and secondary coking reactions. At the end process temperature, i.e., 800℃, the residue mass of FPD was 28.90–36.59% in Fig. 2(b) lower than 16.45–20.17% of PD in Fig. 2(a), which indicates the fermentation is conducive to the formation of pine biochar.

Fig. 2
figure 2

Thermogravimetric characteristics of PD and FPD at different heating rates. a Pine sawdust and b fermented pine sawdust

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As can be seen from Fig. 2, that with the increase in heating rate, the maximum decomposition temperature of the various components shifted to higher temperatures which is due to thermal hysteresis effect. In this section, the PD-X or FPD-X was used to represent samples at dissimilar heating rates (X represents different heating rate). As shown in Table 2, take FPD as example, the Tp was 331.10℃ corresponding to 20℃/min. It jumped to 349.61℃ for 40℃/min and further shifted to 355.52℃ at a 50℃/min heating rate. Besides, the temperature corresponding to the maximum loss of mass varied between 342.96–380.04℃ for PD and 331.10–355.52℃. It shifted to lower temperatures and had small temperature fluctuation range after fermentation. The comprehensive pyrolysis index was used to evaluate pyrolysis characteristic. CPI increased with the heating rate from 3.08 × 10–7 at 20℃/min for PD to 9.99 × 10–7 at 50℃/min for PD, indicating that a high heating rate was beneficial for the pyrolysis. Meanwhile, the CPIs of FPD were 6.56 × 10–7–16.38 × 10–7 higher than that of PD. A higher CPI value means that the pine sawdust pyrolyzed more vigorously, illustrating fermentation could improve pyrolysis performance and facilitates volatile release (Shahbeig and Nosrati 2020).

Table 2 Pyrolysis characteristics of PD and FPD
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Pyrolysis kinetics of PD and FPD by different models

Kinetic study

The thermal kinetic parameters of biomass are very important parameters in the efficient design of thermochemical processes as pyrolysis is composed of multistep reaction mechanism along with complex reactions. In this study, pyrolysis kinetics of PD and FPD could be used to further understand pyrolysis behaviors and provide a reference for pyrolysis process and reactors design. Least square method fit plots were formed to assess the relationship between 1/T vs ln(β), 1/T vs ln (β/T2), and 1/T vs ln (β/T1.92) at the conversion rates from 0.1 to 0.9 by a hike of 10% in the FWO, KAS, and Starink models. As shown in Fig. 3 and Fig. 4, the lines were nearly parallel, demonstrating calculation methods were reliable.

Fig. 3
figure 3

Plots of the model-free methods of PD a KAS, b FWO, c Starink, and d

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Fig. 4
figure 4

Plots of the model-free methods of FPD. a KAS, b FWO, c Starink, and d plot of activation energy vs conversion

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The three calculation methods followed a similar Eα trend between the conversions of 0.1 and 0.9 with a step-size of 0.1, as shown in Fig. 3(d). The E values were estimated that ranging from 200.44 to 309.53 kJ/mol, 197.63 to 311.97 kJ/mol, and 165.98 to 313.08 kJ/mol with an average of 245.61, 243.51, and 240.91 kJ/mol by KAS, FWO, and Starink models, respectively. Eα values at the beginning are considered low due to the cleavage of contain weak bonds (e.g., O–H) and the elimination of volatile components from PD’s surface. After α = 0.1, the second pyrolysis stage occurs, accompanied by the generation of various volatiles resulting in different rates of volatile escape. The volatiles evolved to cover the surface of pine sawdust and form carbonaceous char, which acts as a barrier insulating the heat from reaching the surface below resulting in decrease of reaction activity. Ultimately, more energy is required to activate the reaction as conversion increases. When α = 0.9, Eα rose sharply. This might be due to deep degradation of lignin and formation of carbon in multi-aromatic ring system.

plot of activation energy vs conversion.

As shown in Fig. 4(d), the activation energies of FPD ranged from 145.34 to 853.13 kJ/mol, 152.59 to 789.19 kJ/mol, and 129.11 to 862.87 kJ/mol attained by KAS, FWO, and Starink method, respectively. Eα values changed significantly with the increase of α. From α = 0.1–0.3, the activation energies were found to increase significantly. High Eα indicates that some highly endothermic reaction occurred at this conversion point, while a decline of Eα shows the gradual transition of reaction mechanism during the pyrolysis process of fatty acids and proteins. Overall, the average Eα of FPD was higher than that of PD which might be due to the destruction of macromolecule crosslinked structure by fermentation and co-pyrolysis of fermentation product and raw material. In future research, focusing on catalytic or co-pyrolysis may be a suitable way to reduce the pyrolysis activation energy.

Thermodynamic parameters

Table 3 shows the thermodynamic parameters (A, ΔH, ΔG, and ΔS) of PD and FPD at different conversion rates. The pre-exponential factor (A) explains the proper orientation for chemistry reaction to take place. A < 109 s−1 mainly shows the surface reaction, while A ≥ 109 s−1 indicates a complex reaction. The enthalpy change (ΔH) reflects the total energy consumed during pyrolysis process for its conversion, while the difference between Eα values and ΔH reflects the reaction’s probability. The Gibbs free energy (ΔG) and entropy (ΔS) exhibit the amount of available energy and the proximity of the reaction system to the equilibrium state.

Table 3 Thermodynamic parameters of PD and FPD
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As shown in Table 3, the A values of PD ranged from 3.77 × 1029 to 2.66 × 1045 by the KAS method, 1.47 × 1029 to 6.01 × 1045 by the FWO method, and 3.54 × 1024 to 8.68 × 1045 by the Starink method. The A values showed that the studied FPD were more complex and had the complicated chemical reaction during pyrolysis due to the complex structure and compositions. Differences of around 5.31 kJ/mol of PD and 5.17 kJ/mol were observed between Eα and ΔH values, showing that product formation would be easier. The average ΔG (83.53–83.61 kJ/mol) of PD was higher when compared to the that of FPD (77.22–77.51 kJ/mol) reflecting the considerable bioenergy potential of samples after fermentation through pyrolysis. Moreover, a wide range of ΔS values indicates complex reaction chemistry.

Biochar of PD and FPD

In the study, all samples of PD and FPD at different temperatures were subjected to adsorption experiments. It was found that PD and FPD samples at 800℃ showed better adsorption effect (Table S1). So, PD-800 and FPD-800 were the main object of analysis in Sect. "Biochar of PD and FPD".

FTIR spectra of PD and FPD

The FTIR spectra of two samples are shown in Fig. S1, indicating that biochar consisted of several functional groups. According to prior research, the main functional groups of PD and FPD include hydroxyl, aromatic, aliphatic, and oxygen-containing functional groups. The bands around 3491, 2850, 1750, and 750 cm−1 bands are attributed with stretching vibrations of OH, CH3, C = O, and the out-of-plane vibration of C-H, respectively (Jiang et al. 2021). As can be seen, the O–H peaks of PD and FPD were gradually weakened after pyrolysis because of the decomposition of cellulose and lignin. Besides, the content of oxygenated functional group (C = O) varied greatly. The PD-800 and FPD-800 with abundant groups on the surface exhibit a better MB adsorption capacity.

To eliminate the effect of multi-peak overlap, the FTIR were deconvolved to fit functional group absorption peak information, and then, a qualitative analysis was adopted. The absorption peaks are predominantly hydroxyl in the range of 3700–3000 cm−1, which could be judged to contain alcohols, phenols, and organic acids. The absorption peaks in the range of 3000–2700 cm−1 are connected with aliphatic structures (Cai et al. 2019). Several significant spectral peaks are fitted at the peaks of 2985–2950, 2840–2720, and 2902 cm−1, and they correspond to the CH3 asymmetric stretching vibration, CH2 symmetric stretching vibration, and CH symmetric stretching vibration, respectively (Guo et al. 2021). Most of the absorption peaks in range of 1800–1000 cm−1 are oxygen-containing functional groups. The bands at 1630–1540 cm−1 and 1010–1280 cm−1 are related to the symmetric stretching vibrations of carboxyl groups (C = O) and the stretching vibrations of alcoholic or carboxylic acid (C–O) band. The absorption peaks in range of 900–700 cm−1 are mainly formed by the benzene ring structure with a single H atom, faintness adjacent H atoms replaced by CH, and the n-alkane side-chain backbone structure (Zhu et al. 2019).

Specific peaks corresponding to the functional group are listed in Table 4. As shown in Fig. 5(a) and Fig. 5(b), the FITR of PD and FPD are deconvolved into 12 and 11 peaks by Gaussian Fitting with R2 > 0.99, respectively. The OH functional group in PD accounted for 35.78% of the total functional group, mainly hydroxyl-ether oxygen-hydrogen bond and hydroxyl self-associating hydrogen bond, accounting for 25.76% and 10.11%, respectively. After fermentation, the abundance of OH functional groups increased with the emergence of free OH (1.72%) and OH tetramers (16.13%). The proportion of aliphatic functional groups increased significantly from 6.20% of PD to 24.41% of FPD. In addition, the content of methylene increased by 13.02%. The ratio of CH2 (2935–2919 cm−1)/CH3 (2975–2950 cm−1) was calculated and found to decrease from 0.48 to 0.45, illustrating that fermentation reduced the length of aliphatic side chains and favored carbon condensation to form aromatic fused rings. The percentage of oxygen-containing functional groups in PD was found more than 50%, but it was decreased by about 15% in biochars after fermentation treatment. The underlying functional groups of PD changed from C = O with 36.66% residence to C-O with 16.14% occupancy, and the functional group distributions were also averaged. The content of 1H on the aromatic ring of FPD (1.79%) was higher than that of PD (0.17%). It indicates that fermentation pretreatment is beneficial for side-chain substitution and reduces the number of branch chains.

Table 4 The groups contents of PD and FPD
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Fig. 5
figure 5

The curve-fitted IR spectra

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Ultimately, fermentation pretreatment can improve the distribution of functional groups on the surface of biochar, change the seam abundance of functional groups, reduce the length and number of branched chains, and also promote the formation of aromatic rings in the charring reaction.

Adsorption application study of PD and FPD

The pore structure, as shown in Fig. S2, influenced the relationship between the adsorption capacity of MB and the adsorption time for PD and FPD. Pore characteristics of PD-800 and FPD-800 are tabulated in Table S2. The BET surface areas are 32.82 m2/g (FPD-800) and 19.69 m2/g (PD-800). Obviously, fermentation treatment could increase the specific surface area of derived biochar. The average pore sizes of FPD-800 and PD-800 are 8.51 and 8.64 nm, respectively. Then, the Fig. 6 shows the curves of nitrogen adsorption desorption and the pore size distribution calculated by DFT model. The adsorption amount of nitrogen of FPD-800 is larger than that of PD-800 (refer to details from Fig. 6(a). As can be seen from Fig. 6(b), both pore sizes of PD-800 and FPD-800 are distributed in the range of mesopores, while pore sizes range from 2 to 17 nm. Noticeably, the pore volume of FPD-800 is higher than that of PD-800. All these results indicate that the biochar derived from fermented pine sawdust may have a larger pore volume, which is conducive to the adsorption application.

Fig. 6
figure 6

Curves of nitrogen adsorption–desorption (a) and pore size distribution (b)

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As shown in Fig. 7, with the increase of adsorption time, the absorbance of MB solution decreased gradually, which indicates that the PD-800 and FPD-800 adsorbed MB. The concentration of MB solution decreased from 5 to 4.24 mg/L (PD-800) and 3.39 mg/L (FPD-800), respectively. Moreover, rapid adsorptions were observed for the first 30 min. The PD-800 obtained adsorption capacity of 0.54 mg/g, while the PDF-800’s adsorption capacity of 1.07 mg/g. The removal of MB was further equilibrated after 180 min obtaining an adsorption capacity of 0.75 mg/g for PD-800. However, the biochars pretreated by fermentation reached stage saturation after 120 min of adsorption, after which the adsorption capacity continued to rise and reached a final saturation after 180 min with a higher adsorption capacity of 0.85 mg/g than that of PD-800.

Fig. 7
figure 7

Effect of reaction time on the adsorption process

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The multistage adsorption characteristics of the samples illustrated that the adsorption process was conducted in multisteps. In the initial stage, there were plenty of adsorption sites available on PD-800 and FPD-800 surface, MB molecules rapidly diffused to sample surface for surface adsorption and adsorption quantity increased rapidly during the first 30 min. As the time increases, the active sites were gradually occupied and gradually decreased due to the hindered of intermolecular collision and inter-channel extrusion. The adsorption slowly increased after 30 min until reaching the adsorption equilibrium for PD-800. Nevertheless, for FPD-800, under the influence of the concentration of solution and the adsorption force of surface functional groups, MB molecules entered the deep pore network of FPD-800, showing further adsorption. Meanwhile, the MB molecules entered in a stable state of adsorption and desorption.

Adsorption kinetics study of PD and FPD

The adsorption mechanism of samples was determined using pseudo-first–order kinetic, pseudo-second–order kinetic, Elovich, intraparticle diffusion models to fit the experimental data. The fitting results of adsorption kinetics and model parameters are shown in Fig. 8 and Table 5, respectively.

Fig. 8
figure 8

The kinetic models for MB adsorption of a pseudo-first–order, b pseudo-second–order, c Elovich, and d intraparticle diffusion

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Table 5 Adsorption kinetics parameters of different models
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In literature, the adsorption mass transfer kinetics includes external diffusion, internal diffusion, and adsorption in the active adsorbent sites (Chen et al. 2022; Zeng et al. 2022). In pseudo-first–order kinetic fitting, the R2 were 0.969 and 0.972 for fitting the adsorption process of PD-800 and FPD-800, reflecting good linear fit. However, deviations could be observed in the experimental equilibrium adsorption capacity and fitted adsorption capacity. The experimental adsorption capacity and calculated adsorption capacity of PD-800 were 0.755 mg/g and 0.347 mg/g, while those of FPD-800 were 1.597 mg/g and 0.669 mg/g, respectively. It could be observed that the pseudo-second–order kinetics model provided a good agreement with the experimental data. The linear fitting effect was excellent showing very slight deviation between the experimental (0.755 mg/g) and the calculated qe (0.824 mg/g) for PD-800. It can be possibly explained that the MB adsorption process of PD-800 and FPD-800 from surface adsorption to water was mainly controlled by the chemisorption mechanism connected to surface functional groups such as hydroxy groups (π-π) and oxygen-containing functional groups (Lv et al. 2022, Sarkar and Wang 2020). Moreover, as shown in Table 3, the correlation coefficient was 0.986, higher than that of other models, for fitting the adsorption process of FPD-800 using the intra-particle diffusion kinetic equation (Table 3). And, the value of c was greater than 0, indicating that the adsorption includes both diffusion of MB by the aqueous solution towards the external surface of the adsorbent and the MB diffusion by the adsorbent pores. Consequently, biochar samples after fermentation pretreatment have larger adsorption capacities, and the adsorption properties shifted from chemisorption to intraparticle diffusion and surface adsorption synergistically.

Fermentation application

Based on above results and discussion, the challenges have been summarized together with future suggestions for the application of fermentation: (a) the characterization study about fermentation feedstocks should have a more detailed classification and strict regulation. (b) It is necessary to establish full evaluation system of fermentation including production of high-value fermentation products, fermentation substrate utilization, and secondary resource recovery of fermentation residues. (c) It is necessary to focus on the multiple co-pyrolysis methods to reduce the pyrolysis energy of fermentation residue, increase the energy substitution of biogas and bio-oil, and directionally regulate the pore structure and functional group distribution of biochar to improve the bioenergy utilization. (d) More research is needed to explore zero-waste fermentation strategy, focusing on energy utilization, environmental benefits, and economic value of fermentation system.

Conclusion

In this study, the physicochemical properties, thermal decomposition kinetics, and biochar properties associated with fermented pine sawdust (FPD) and pine sawdust (PD) were found significantly different. (a) Fermentation pretreatment reduced the ash content of the sample and increased the content of fixed carbon (from 16.35 to 21.63%) and oxygen content of the raw material (from 49.21 to 62.20%). (b) The CPI and activation energy of FPD were higher than that of PD, elucidating that fermentation could improve pyrolysis performance. (c) Fermentation pretreatment increased the abundance of surface functional groups, reduced the length of aliphatic branch chain (from 0.48 to 0.45), and promoted the formation of aromatic benzene ring carbon, which resulted in increased specific surface area from 19.69 (PD-800) to 32.82 m2/g (FPD-800). (d) Biochar’s characteristics further enhanced its adsorption capacity from 0.755 to 1.597 mg/g (MB as adsorbate), while transforming its adsorption mode into coadsorption of intraparticle diffusion and surface adsorption.