Characterization of South African Woody and Non-Woody Invasive Alien Plant Species for Sustainable Bio-Oil Production

Abstract

Bio-oil energy use in agricultural systems provides sustainable solutions for powering machinery operations and heating and cooling environments in facilities. However, its potential in South Africa is constrained by the limited availability of energy substrate that does not compromise food production, land use, and water resources. This study investigated the physical and chemical properties of six invasive alien plant species (IAPs), three woody species (Acacia mearnsii, Eucalyptus grandis, and Pinus patula), and three nonwoody species (Lantana camara, Chromolaena odorata, and Solanum mauritianum) to assess their suitability for bio-oil production. Key analyses included structural, elemental, proximate, atomic ratio, higher heating value (HHV), and thermogravimetric analysis (TGA) analyses. The results showed that woody IAPs had a significantly higher structural composition (p < 0.05), improving bio-oil yield. The bio-oil can be blended with diesel for agricultural use, while lignin-derived biochar serves as a soil amendment. Higher carbon and hydrogen contents enhanced HHV and combustion, while lower nitrogen and sulfur levels reduced emissions. Despite oxygen hindering pyrolysis, its bioactive properties support crop protection. Compared to South African coal, IAP-derived bio-oil shares similarities with peat coal and could be used for greenhouse heating. This study promotes energy efficiency in agriculture, reduces fossil fuel dependence, and supports environmental sustainability by repurposing IAPs. Additional studies should focus on lignin pretreatment and bio-oil upgrading to reduce oxygenated compounds.

1. Introduction

The cumulative demand for renewable energy in agricultural machinery is driven by the heavy reliance on fossil fuels, which not only accelerates climate change but also causes major economic challenges [1]. Despite the environmental and economic crises, South Africa has faced persistent load-shedding since 2007, leading to substantial losses in the agricultural sector [2]. These challenges highlight the urgent need for sustainable and cost-effective energy alternatives in agricultural operations.

Biomass energy is a renewable energy source derived through the thermochemical or biochemical degradation of biomass, producing biofuels that can be utilized for heat, electricity generation, and transport fuel [3]. It is valued for its cost-effectiveness, with lower carbon emissions while supporting a circular bioeconomy, serving as a viable energy source to enhance agricultural production [4]. South Africa lags in biomass utilization, contributing only 0.12% to its energy mix, far behind Morocco (5.14%) and Kenya (2.82%) [5]. Minimum exploration includes land use competition and food security concerns, water resource strain, and a lack of limited conversion technologies [6]. This gap highlights the need to optimize biomass resources for sustainable energy production.

To address land use and food security challenges, invasive alien plant species (IAPs) have been considered alternative energy substrates. These plants, which invade a certain habitat and negatively impact biodiversity, livelihood, and the economy [7], infest over 10 million hectares in South Africa [8]. Additionally, dense infestation destructs field agricultural operations, requiring significant financial investment for control and management. Research has shifted toward clearing IAPs for energy generation as a strategy to control their spread. However, limited studies in South Africa have specifically explored their potential for biofuel production [9]. Previous studies, such as [10] and [11], have primarily focused on the environmental and economic impacts of invasive species without specifically evaluating their potential for biofuel production. Similarly, Ref. [12] concluded their viability for biogas generation, leaving a clear research gap in assessing their suitability for bio-oil production through pyrolysis.

Bio-oil is a liquid fuel derived from fast pyrolysis, which can be used for energy applications after upgrading [13]. Recent research has predominantly concentrated on conventional biomass sources such as algae and crop residues (e.g., wheat straw, sugarcane straw, and switchgrass), which typically yield bio-oil with a high oxygen content and nitrogen oxide emissions during combustion [14,15,16]. This focus has resulted in a limited investigation of invasive species as an alternative feedstock. There remains a clear research gap in evaluating the physicochemical suitability and energy potential of IAPs for bio-oil production.

Therefore, the objective of this study is to evaluate the physical and chemical characteristics of three woody IAPs (Acacia Mearnsii, Eucalyptus Grandis, and Pinus Patula) and three nonwoody IAPs (Lantana Camara, Chromoleana Odorata, and Solanum mauritianum) for bio-oil production. This includes detailed characterization of their proximate, elemental, structural composition, atomic ratios, and thermal degradation behavior to determine their influence on bio-oil quantity and quality. The novelty of this research lies in managing the negative impact of IAPs with renewable energy generation. Unlike previous studies that focused on the economic, environmental, and biogas production of IAPs, this study assesses their viability for bio-oil production in the South African context. It further compares its energy potential, cost-effectiveness, and sustainability to conventional bio-oil substrate. Additionally, this study identifies optimal pyrolysis conditions using thermogravimetric analysis, offering practical recommendations in bio-oil production industries. Overall, this dual-purpose approach addresses ecological, economic, and energy security challenges in agriculture operations.

2. Materials and Methods

Three woody IAPs, namely, Acacia mearnsii, Eucalyptus grandis, and Pinus patula, as well as three nonwoody IAPs, namely, Lantana camara, Chromoleana odorata, and Solanum mauritianum, were selected and evaluated for bio-oil production. Woody IAPs and nonwoody IAPs were sourced from the Institute of Commercial Forestry Research and Athlone region, respectively, both of which are in Pietermaritzburg, South Africa. Pietermaritzburg is located at 29°37′ S, 30°23′ E, and has a mean rainfall of 832 mm. The typical maximum and lowest temperatures are 26 °C and 11 °C, respectively.

2.1. Materials

The woody part of the biomass (stem), aged 10 years, was used as a working sample for woody IAPs, as suggested by the authors of [17]. The woody and nonwoody biomass samples were chopped into approximately 20 mm pieces for drying and grinding. An identical preparation protocol was used for both woody and nonwoody biomass samples, which involved setting an oven air dryer to 60 °C for 24 h [18]. After drying, a 1 mm sieve was fitted to a grinding machine to grind the dry materials. After being ground, the samples were wrapped in plastic bags with labels and kept in a desiccator to keep moisture out [4]. Figure 1 illustrates the stages of preparing woody and nonwoody IAPs for characterization.

2.2. Methods

An experimental investigation was conducted to assess the potential of woody and nonwoody IAPs as energy substrates for bio-oil production via pyrolysis. The biomass was characterized via the structural, elemental, proximate, atomic ratio, heating value, and thermal behavior analyses. Each analysis was performed via standardized protocols and instruments, as outlined in the subsequent sections. To ensure the reliability of the findings, experiments were conducted in three repetitions, and the findings are presented as the means.

2.2.1. Structural Analysis

Biomass contains cellulose, hemicellulose, and lignin in its structural makeup. The van Soest fiber analysis by [19,20] was used to determine the structural composition. The experiment was conducted at Cedara College of Agriculture, Pietermaritzburg, South Africa. Van Soest fiber analysis uses neutral detergent fiber (NDF), which removes all nonstructural extracts and leaves hemicellulose, cellulose, and lignin, as well as acid detergent fiber (ADF), which removes hemicellulose, leaving cellulose and lignin. The acid detergent lignin (ADL) leaves lignin only.

The NDF was determined according to NDF-ISO 16472:2006 methods, as referenced by the authors of [21]. Approximately 1 g of the powdered sample was placed in a crucible, and approximately 100 ml of a neutral detergent solution (sodium borate decahydrate) with 0.5 g of sodium sulfate, and some drops of n-octanol were added at room temperature [19]. The solution was boiled at $400 °\mathrm{C}$ and refluxed for 60 min from the onset of boiling. The crucible was dried at $105 °\mathrm{C}$ for 8 h and weighed. Equation (1), where Wt is the weight (g), was used to determine the total fiber content of the plant [19].

$$\mathrm{N}\mathrm{D}\mathrm{F}={\displaystyle \frac{\left(\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}+\mathrm{N}\mathrm{D}\mathrm{F}\right)-\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}}{\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}}\times 100$$

(1)

The analysis of ADF was according to ISO 13906: 2008 methods, as referenced by the authors of [21]. The same procedure was used but with acid detergent (sulfuric acid 1 N). Equation (2) was used to calculate the cellulose and lignin contents in the fiber.

$$\mathrm{A}\mathrm{D}\mathrm{F}={\displaystyle \frac{\left(\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}+\mathrm{A}\mathrm{D}\mathrm{F}\right)-\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}}{\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}}\times 100$$

(2)

The acid detergent lignin (ADL) was determined according to ISO 13906:2008 methods, as referenced by the authors of [21], where the content was determined by adding 72% sulfuric acid and constantly stirring for 3 h. The mixture was then filtered, washed with water twice, and placed in a hot air oven at $105 °\mathrm{C}$ for 8 h, after which weight loss was recorded. Equation (3) was used to calculate the lignin content in the fibers.

$$\mathrm{A}\mathrm{D}\mathrm{L}={\displaystyle \frac{\left(\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e} \mathrm{a}\mathrm{f}\mathrm{t}\mathrm{e}\mathrm{r} \mathrm{a}\mathrm{c}\mathrm{i}\mathrm{d} \mathrm{s}\mathrm{o}\mathrm{a}\mathrm{k}\right)-\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{t}\mathrm{h}\mathrm{e} \mathrm{c}\mathrm{r}\mathrm{u}\mathrm{c}\mathrm{i}\mathrm{b}\mathrm{l}\mathrm{e}}{\mathrm{W}\mathrm{t} \mathrm{o}\mathrm{f} \mathrm{s}\mathrm{a}\mathrm{m}\mathrm{p}\mathrm{l}\mathrm{e}}}\times 100$$

(3)

Equations (4)–(6) were used to calculate the amount of hemicellulose, cellulose, and lignin in a substrate [4].

$$\mathrm{H}\mathrm{e}\mathrm{m}\mathrm{i}\mathrm{c}\mathrm{e}\mathrm{l}\mathrm{l}\mathrm{u}\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{e}=\mathrm{N}\mathrm{D}\mathrm{F}\mathrm{\%}-\mathrm{A}\mathrm{D}\mathrm{F}\mathrm{\%}$$

(4)

$$\mathrm{C}\mathrm{e}\mathrm{l}\mathrm{l}\mathrm{u}\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{e}=\mathrm{A}\mathrm{D}\mathrm{F}\mathrm{\%}-\mathrm{A}\mathrm{D}\mathrm{L}\mathrm{\%}$$

(5)

$$\mathrm{L}\mathrm{i}\mathrm{g}\mathrm{n}\mathrm{i}\mathrm{n}=\mathrm{A}\mathrm{D}\mathrm{L}\mathrm{\%}$$

(6)

2.2.2. Elemental Analysis

The elemental composition of biomass includes major organic elements, namely, carbon (C), sulfur (S), hydrogen (H), oxygen (O), and nitrogen (N) [19]. The elemental analysis was performed at the University of Kwa-Zulu Natal (UKZN) Physics and Chemistry Laboratory in Pietermaritzburg via a Thermo Scientific Flash 2000 CHNS analyzer. This elemental analysis method was used by [19], where approximately 1 mg of each powdered sample was placed in a tin capsule. The tin capsule with biomass was weighed and heated at $980 °\mathrm{C}$ with a constant flow of helium enriched with oxygen. The mass percentages of C, H, N, and S were determined via Eager 300 software. Equation (7) was used to calculate the mass percentage of oxygen by subtracting the amount of CHNS from 100, as proposed by the authors of [22].

$$\mathrm{O}\mathrm{x}\mathrm{y}\mathrm{g}\mathrm{e}\mathrm{n}\left(\mathrm{O}\mathrm{\%}\right)=100-(\mathrm{C}+\mathrm{H}+\mathrm{N}+\mathrm{S})$$

(7)

2.2.3. Proximate Analysis

The percentage weights of the moisture content, ash content, volatile content, and fixed carbon are referred to as the proximate composition. The proximate properties were determined according to the standards of the ASTM.

The moisture content (MC) was determined according to the ASTM D 2974-8 standard, as referenced by the authors of [23]. Approximately 5 g of the solid sample was placed in a crucible and weighed at room temperature. The crucible was placed in an oven air dryer at $105\pm 3 °\mathrm{C}$ for $24\mathrm{h}.$ After 24 h, the sample was placed in a desiccator to cool. Once the sample reached room temperature, it was weighed again, and the MC was calculated via Equation (8), where ${(\mathrm{W}}_{\mathrm{s}\mathrm{i}})$ represents the initial weight of the sample before heating (g) and where (${\mathrm{W}}_{\mathrm{s}\mathrm{f}}$) represents the final weight of the sample after heating (g).

$$\mathrm{M}\mathrm{C}={\displaystyle \frac{{\mathrm{W}}_{\mathrm{s}\mathrm{i}}-{\mathrm{W}}_{\mathrm{s}\mathrm{f}}}{{\mathrm{W}}_{\mathrm{s}\mathrm{i}}}}\times 100$$

(8)

The ash content (AC) was determined following the ASTM 3173-87 standard, as referenced by the authors of [23]. A dried sample weighing 5 g was stored in a crucible and placed in a preheated muffle furnace at $575 °\mathrm{C}$ for 3 h for combustion. After the sample had cooled, it was weighed, and Equation (9) was used, where (${\mathrm{W}}_{\mathrm{a}\mathrm{s}\mathrm{h}}$) is the weight of the sample after combustion (g).

$$\mathrm{A}\mathrm{C}={\displaystyle \frac{{\mathrm{W}}_{\mathrm{a}\mathrm{s}\mathrm{h}}}{{\mathrm{W}}_{\mathrm{s}\mathrm{f}}}}\times 100$$

(9)

The volatile content (VC) was determined following the ASTM D4559-99 standard, as referenced by the authors of [23]. A dried sample weighing 5 g with a particle size of 1 mm obtained via the MC determination technique was placed in a furnace for 7 min at $900 °\mathrm{C}$; the sample was removed and allowed to cool to room temperature, and the final mass was weighed. Equation (10) was used to calculate VC, where (${\mathrm{W}}_{\mathrm{r}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{n}\mathrm{g}}$) is the weight of the content remaining after volatile compounds were released (g).

$$\mathrm{V}\mathrm{C}={\displaystyle \frac{{\mathrm{W}}_{\mathrm{s}\mathrm{f}}-{\mathrm{W}}_{\mathrm{r}\mathrm{e}\mathrm{m}\mathrm{a}\mathrm{i}\mathrm{n}\mathrm{i}\mathrm{n}\mathrm{g}}}{{\mathrm{W}}_{\mathrm{s}\mathrm{f}}}}\times 100$$

(10)

The fixed carbon (FC) content was determined via Equation (11) using the values of ash content and volatile content obtained by utilizing Equations (9) and (10) [24].

$$\mathrm{F}\mathrm{C}=100-(\mathrm{A}\mathrm{C}+\mathrm{V}\mathrm{C})$$

(11)

2.2.4. Van Krevelen Diagram

The Van Krevelen diagram was employed to assess the energy density of IAPs compared with bio-oil substrates in South Africa, such as cow manure, fruit and vegetable waste, cassava, algae, and crop residues. The atomic ratios of hydrogen to carbon (H:C), oxygen to carbon (O:C), and nitrogen to carbon (N:C) were calculated via Equations (12), (13) and (14), respectively. The values were then used to plot the van Krevelen diagram [25].

$$\mathrm{H}:\mathrm{C} \mathrm{R}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}={\displaystyle \frac{\mathrm{H}}{\mathrm{C}}}$$

(12)

$$\mathrm{O}:\mathrm{C} \mathrm{R}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}={\displaystyle \frac{\mathrm{O}}{\mathrm{C}}}$$

(13)

$$\mathrm{N}:\mathrm{C} \mathrm{R}\mathrm{a}\mathrm{t}\mathrm{i}\mathrm{o}={\displaystyle \frac{\mathrm{N}}{\mathrm{C}}}$$

(14)

2.2.5. Higher Heating Value (HHV)

The HHV was obtained via formulas derived from the literature based on structural, elemental, and proximate compositions of woody and nonwoody biomasses. This approach provides a comprehensive understanding of how each characteristic impacts the thermal stability, energy content, and combustion behavior of IAP species. Three equations were adopted from each composition to increase the reliability of the results, as depicted in

Table 1. HHV estimation equations are derived from the structural, elemental, and proximate compositions.

HHV Formula	Author	R2	Biomass	Accuracy
HHV from structural composition
$\mathrm{H}\mathrm{H}\mathrm{V}=16.1964+0.0555\mathrm{L}$	[27]	-		1.13%
$\mathrm{H}\mathrm{H}\mathrm{V}=0.0889+16.8218$	[28]	0.95	Wood/nonwood	0.056%
$\mathrm{H}\mathrm{H}\mathrm{V}=16.292+0.0979\mathrm{L}$	[29]	0.93	Wood/nonwood	-
HHV from elemental composition
$\mathrm{H}\mathrm{H}\mathrm{V}=-0.763+0.30\mathrm{C}+0.525\mathrm{H}+0.064\mathrm{O}$	[30]	0.792	Biomass	1.78
$\mathrm{H}\mathrm{H}\mathrm{V}=0.3516\mathrm{C}+1.16225\mathrm{H}-0.1109\mathrm{O}+0.0628\mathrm{N}+0.10465\mathrm{S}$	[31]	0.720	Biomass	−0.59%
$\mathrm{H}\mathrm{H}\mathrm{V}=-1.3675+0.3137\mathrm{C}+0.7009\mathrm{H}+0.0318\mathrm{O}$	[32]	0.834	Biomass	0.07%
HHV from proximate composition
$\mathrm{H}\mathrm{H}\mathrm{V}=-3.0368+0.2218\times \mathrm{V}\mathrm{C}+0.2601\times \mathrm{F}\mathrm{C}$	[32]	0.617	Biomass	0.26
$\mathrm{H}\mathrm{H}\mathrm{V}=23.885-0.430\times \mathrm{A}\mathrm{s}\mathrm{h}-0.047\times \mathrm{V}\mathrm{C}$	[30]	-	Biomass	-
$\mathrm{H}\mathrm{H}\mathrm{V}=-10.81408+0.3133(\mathrm{F}\mathrm{C}+\mathrm{V}\mathrm{M})$	[33]	1.16	Biomass	0.533

C, H, O, and S represent the elemental compositions of carbon, hydrogen, oxygen, and sulfur, respectively. L refers to the lignin content, whereas VC, MC, and FC denote the proximate composition, specifically the volatile content, moisture content, and fixed carbon content, respectively.

. These equations have also been utilized by other researchers for similar species, such as A. mearnsii, C. odorata, and A. donax [25,26].

2.2.6. Thermogravimetric Analysis

Thermogravimetric analysis (TGA) was used to analyze the thermal degradation of the sample to better understand the pyrolysis process and temperature ranges for pyrolysis feeding for bio-oil production. The sample preparation procedure followed the same conditions outlined in Section 2.1, including drying, particle size reduction, and homogenization steps to ensure consistency and accuracy in the TGA analysis. For this analysis, a DTG–60H simultaneous analyzer was used, with approximately 10 mg of the sample carefully placed in an aluminum pan within a well-balanced holder [34]. The method adopted in this study was used by [23], where the sample underwent analysis at various temperatures; initially, at 30 °C at a heating rate of 10 °C/min, and the sample was held for 2 min under a $20\mathrm{m}/\mathrm{m}\mathrm{i}\mathrm{n}$ nitrogen atmosphere. The sample was subsequently subjected to 600 °C at 10 °C/min and held for 2 min under a $20\mathrm{m}\mathrm{L}/\mathrm{m}\mathrm{i}\mathrm{n}$ nitrogen atmosphere for further degradation. Throughout the experiment, the sample mass loss was continually recorded and displayed via TGA and differential thermogravimetry (DTG) curves. TGA measures the change in mass of a sample, whereas DTG provides information on the rate of mass loss, which aids in understanding the heat breakdown behavior of a material [35].

2.2.7. Data Analysis

Data analysis was conducted using SPSS software version 11 to evaluate variations and trends in the physicochemical composition of woody and nonwoody IAPs for bio-oil production. Descriptive statistics, including means, were used to summarize the data. Furthermore, t-tests at the 5% significance level and two-way ANOVA were conducted to determine significant differences between the groups.

3. Results and Discussion

3.1. Structural Analysis

While a study by the authors of [12] characterized nonwoody IAPs for biofuel production, research on their structural composition remains limited, especially in comparison to woody IAPs. This study addresses the knowledge gap by assessing the influence of the structural composition on bio-oil production. The percentages of cellulose, hemicellulose, and lignin in the IAPs were 47.5, 22.6, and 25.5%, respectively, for woody IAPs and 23.6, 15.9, and 9.8%, for nonwoody IAPs, as shown in

Table 2. Physiochemical characteristics of woody and nonwoody IAPs.

Sample Name	Woody IAPs			Nonwoody IAPs
	A. Mearnsii	E. Grandis	P. Patula	L. Camara	C. Odorata	S. Mauritianum
Structural analysis
(%)
Cellulose	43.73 ± 1.10	53.54 ± 0.11	45.27 ± 0.26	26.65 ± 0.08	24.07 ± 0.07	20.08 ± 0.17
Hemicellulose	23.67 ± 0.70	20.26 ± 0.26	23.88 ± 0.12	19.28 ± 0.02	16.18 ± 0.03	12.16 ± 0.15
Lignin	22.83 ± 0.15	23.86 ± 0.18	29.82 ± 0.12	12.23 ± 0.03	9.92 ± 0.07	7.39 ± 0.26
Elemental analysis
(%)
Carbon	44.58 ± 3.01	50.83 ± 3.06	50.52 ± 1.29	48.09 ± 1.08	46.11 ± 0.50	48.51 ± 2.20
Hydrogen	5.63 ± 0.25	6.08 ± 0.56	6.11 ± 0.37	6.08 ± 0.25	6.18 ± 0.21	6.29 ± 0.25
Nitrogen	ND	ND	ND	2.32 ± 0.10	2.86 ± 0.18	4.54 ± 0.50
Oxygen	48.79 ± 3.53	43.09 ± 3.57	43.98 ± 0.63	43.50 ± 1.26	45.13 ± 0.50	40.65 ± 2.30
Sulfur	ND	ND	ND	ND	ND	ND
Proximate analysis
(%)
Moisture content	3.90 ± 0.09	1.89 ± 0.13	2.89 ± 0.12	4.24 ± 0.03	3.34 ± 0.59	3.61 ± 0.15
Volatile content	87.15 ± 0.21	87.90 ± 0.06	86.82 ± 0.15	84.03 ± 0.09	85.34 ± 0.45	82.89 ± 0.29
Ash content	0.94 ± 0.07	3.79 ± 0.001	1.80 ± 0001	8.14 ± 0.03	9.63 ± 0.34	9.63 ± 0.46
Fixed carbon	7.92 ± 0.08	6.42 ± 0.03	8.45 ± 0.09	3.36 ± 0.06	3.91 ± 0.38	3.87 ± 0.38

All values are means of three values ± standard deviations. ND means not detected.

.

Compared with nonwoody IAPs, woody IAPs were significantly greater (p < 0.05), supported by non-overlapping 95 percent confidence interval error bars in Figure 2a. This difference is attributed to the maturity of woody species, which develop stronger tissues over their longer lifespan (10 years) than the flexible, less structured tissues of perennial nonwoody species [36]. This is also validated by the authors of [37], who reported a greater structural composition in sapwood (31%) than in herbaceous species (10%).

In terms of bio-oil production, woody IAPs, particularly P. patula, presented greater potential for higher yields than nonwoody IAPs. This is due to their relatively high contents of cellulose (30 to 60%) and hemicellulose (20 to 40%), both of which fall within acceptable thresholds and contain volatile compounds that readily condense to bio-oil. Although higher bio-oil yields are expected, the stable and resistant structure of lignin favors biochar over bio-oil production, requiring higher temperatures for optimal pyrolysis [38]. This suggests that bio-oil production from woody IAPs demands higher energy input and effective pre-treatment, such as acid or alkaline treatments, to break down lignin, resulting in increased processing costs.

However, the byproduct biochar can be applied to the soil to improve water infiltration, pH, and microbial biomass, ultimately enhancing the growth of plants [39]. Ref. [40] noted similar trends for Acacia mearnsii, which contained 40.2% cellulose, 21.3% hemicellulose, and 14.7% lignin. Variations in lignin content are attributed to differences in growing conditions, such as high rainfall promoting faster growth with less lignin.

Breaking down structural analysis provides a guide in optimizing the pyrolysis process, particularly for lignin degradation and selecting cost-effective and energy-dense biomass.

3.2. Elemental Analysis

The amount and quality parameters of bio-oil derived from IAPs can be influenced by the elemental composition; hence, these factors require investigation. Figure 2b indicates the overlapping confidence intervals for the elemental compositions of woody and nonwoody IAPs, suggesting no significant variation (p < 0.05). This is because the IAPs have similar compounds, such as cellulose, hemicellulose, and lignin, that have the same element profile with the same synthesis process. Both woody and nonwoody IAPs have carbon contents between 30% and 60% and hydrogen contents between 5% and 6%, which are optimal for HHV, increasing the efficiency of combustion. The bio-oil derived from both woody and nonwoody IAPs can be blended with ethanol and used in gas turbine combustors providing power in irrigation systems or heating greenhouses.

The oxygen content of the woody IAPs was 45.1%, whereas that of the nonwoody IAPs was 43.0%, as shown in Table 2. Other researchers have obtained similar values that tend to range between 30 and 45%, and such concentrations reduce the HHV of bio-oil, resulting in poor flame stability [41]. This requires upgrading techniques such as hydrotreating and catalytic cracking that involve substantial financial input and technical complexity [42]. However, oxygen forms fatty acids, esters, and phenolic derivatives known as biopesticide compounds for crop protection [43]. This offers an eco-friendly alternative to synthetic chemicals, managing pests without harming the environment and non-target organisms.

Nonwoody IAPs contained approximately 3.2 to 4.6% nitrogen with no detectable sulfur, whereas woody IAPs contained no nitrogen or sulfur. The reason for the lack of detection was that elements present at lower concentrations (less than 1%) could not be detected using the CHNS element analyzer [44]. The absence of detectable nitrogen and sulfur in IAPs suggests that bio-oil production can have a minimal environmental impact and reduce health risks, as it limits the formation of NOx and SOx emissions. The elemental composition of woody and nonwoody biomass in a study performed by the authors of [4] was comparable to that of carbon (44.9 to 47.6%), hydrogen (5.9 to 6.2%), oxygen (45.9 to 46.3%), nitrogen (0.3 to 1.5%), and sulfur (0.03 to 1.5%).

Knowledge of elemental composition allows operators to select biomass feedstocks with reduced oxygen and nitrogen content, thereby minimizing operational and economic challenges. Furthermore, this information can be leveraged to support alternative solutions, such as biopesticides, offering cost-effective options for communities with limited financial resources.

3.3. Proximate Analysis

The pyrolysis process, along with the quantity and quality of bio-oil derived from IAPs, is affected by the proximate composition. Hence, investigating these factors is mandatory. The overlapping confidence intervals in Figure 2c for moisture content suggest no significant difference between woody and nonwoody IAP (p > 0.05). The proximate analysis yielded 2.9% moisture content and 87.3% volatile content for woody IAPs, 3.7% moisture content, and 84.1% volatile content for nonwoody IAPs. The results of this study indicate that both woody and nonwoody IAPs have greater potential for increasing yields of bio-oil. This is attributed to an MC below 10%, which enables more energy for pyrolysis than energy for moisture evaporation [45]. Furthermore, the higher concentrations of volatile compounds (between 65% and 85%) indicate that greater amounts of volatile compounds can be condensed into bio-oil during pyrolysis (Refs. [24,46]). The MCs of the other nonwoody and woody biomasses were between 6.48% and 7.13%, which differed from what was obtained in this work [4]. This may be attributed to the lack of standardized methods for determining proximate analysis, as shown in studies by the authors of [47], who conducted their analysis at 105 °C for only 3 h, and by the authors of [48], who conducted their analysis at 105 °C for 24 h.

The results in Table 2 show that there were significant variations (p < 0.05) in ash and fixed carbon contents between woody and nonwoody IAPs. The analysis yielded 2.2% ash content and 7.6% fixed carbon for woody IAPs and 8.8% ash content and 3.5% fixed carbon content for nonwoody IAPs. This difference is related to a study conducted by the authors of [49] on the accumulation of ash in nonwoody plants because higher silica uptake strengthens the cell walls of plants to protect them against harsh environmental conditions. For this work, the ash content in woody IAPs is ideal for bio-oil production, as it is within the acceptable threshold of 0.1 to 5%. However, for nonwoody IAPs, the ash content concentrations are higher than the acceptable threshold, which may lead to toxic components such as silica, slagging, and corroding pyrolysis reactors [50].

Woody IAPs are more suitable for bio-oil production due to lower levels of moisture and ash content, ensuring efficient combustion. Standardized testing methods for proximate analysis are crucial for reliable and comparable results.

3.4. Van Krevelen Diagram

Bio-oil research has primarily focused on conventional feedstocks such as fruit and vegetable waste, cassava tubers, crop residues, and algae, with limited attention given to IAPs. This section bridges the gap by comparing the energy content, emissions, and cost-effectiveness of IAPs with these more commonly studied feedstocks. The hydrogen-to-carbon (H:C), oxygen-to-carbon (O:C), and nitrogen-to-carbon (N:C) atomic ratios of these substrates are shown in Table 3. This comparison highlights the potential of IAPs as competitive feedstocks for bio-oil production relative to alternative energy substrates, as presented in Figure 3.

The H:C ratio indicates hydrogen content, which facilitates hydrodeoxygenation, enhancing bio-oil energy stability and density [51]. Woody and nonwoody IAPs exhibited moderate H:C ratios (1.47 and 1.55), indicating a balance between chemical stability and energy content. In contrast, fruits, vegetable waste, sugarcane bagasse, and microalgae had higher H:C ratios, correlating with greater HHV. Despite their energy potential, fruits and vegetable waste have a high moisture content (58.4%), leading to higher transport costs and lower energy conversion efficiency [12]. Sugarcane bagasse, though cost-effective, contains 27.8% lignin, requiring higher energy input for bio-oil production and increasing processing costs [52]. Microalgae, while promising, demands specialized cultivation systems and growth condition monitoring, significantly raising operational expenses [14]. Thus, while alternative feedstocks offer high energy content, IAPs provide a more cost-effective and sustainable option for bio-oil production.

The O:C ratio indicates the presence of oxygen-containing compounds, influencing the thermal stability and caloric value [53]. Fruits, vegetable waste, and cassava, with their low O:C ratios, produce fewer undesirable oxygen compounds, minimizing the need for costly upgrading techniques. In contrast, sugarcane bagasse and microalgae have high O:C ratios, necessitating catalytic upgrading, which increases energy demand and greenhouse gas emissions [15]. Invasive species (IAPs) offer a moderate O:C ratio, striking a balance between energy efficiency, processing costs, and environmental sustainability. Their reduced reliance on intensive upgrading makes them a viable and cost-effective bio-oil feedstock compared to high O:C alternatives.

The N:C ratio indicates the potential for nitrogen oxide (NOx) emissions during combustion, necessitating effective control measures to minimize environmental impact [54]. Woody IAPs exhibited undetectable N:C ratios, indicating negligible nitrogen content; similarly, cassava had low nitrogen concentrations, enhancing their suitability as a cleaner-burning biofuel. In contrast, higher N:C ratios were observed in other biomass types, particularly microalgae, which poses greater emission challenges. To mitigate these effects, pre-treatment strategies such as zeolite-based or biochar catalysts can be employed to adsorb ammonium ions and reduce nitrogen-related emissions before combustion [55].

Regarding the quality of bio-oil, the van Krevelen diagram in Figure 2 classifies bio-oil compounds in this manner: lipids (0 ≤ O/C ≤ 0.2, 1.7 ≤ H/C ≤ 2.25), unsaturated hydrocarbons (UHs, 0 ≤ O/C ≤ 0.1, 0.7 ≤ H/C < 1.7), condensed aromatic hydrocarbons (CAHs, 0 ≤ O/C ≤ 1.0, 0.3 ≤ H/C ≤ 0.7), phenolic-like species (0 ≤ O/C ≤ 0.6, 0.6 ≤ H/C ≤ 1.3), and saccharides (sugars, 0.5 ≤ O/C ≤ 0.9, 1.2 ≤ H/C ≤ 2.5) [56]. The results suggest that all the substrates predominantly produce saccharide-derived sugars. These sugars, such as levoglucosan and cellobiosan, are produced during the degradation of cellulose and hemicellulose and reduce the hydrogen content, promote coke formation, and deactivate catalysts [57]. This means that bio-oil remains highly oxygenated and can cause potential corrosion in pyrolysis reactors.

The atomic ratio analysis provides a direct link to the energy content and combustion behavior of the biomass, facilitating the selection of IAPs that offer a high energy yield with low environmental risk.

Table 3. Atomic ratios of woody and nonwoody IAPs compared to other South African substrates.

Biomass	H:C	O:C	N:C	References
Woody IAPs	1.47	0.70	ND	Present study
Nonwoody IAPs	1.55	0.68	0.058	Present study
Scenedesmus obliquus microalgae	2.33	0.71	0.135	[15]
Sugar bagasse	1.62	0.73	0.0027	[52]
Fruit and vegetable waste	1.78	0.57	0.047	[58]
Cassava tuber	1.33	0.58	0.028	[58]

Table 3. Atomic ratios of woody and nonwoody IAPs compared to other South African substrates.

Biomass	H:C	O:C	N:C	References
Woody IAPs	1.47	0.70	ND	Present study
Nonwoody IAPs	1.55	0.68	0.058	Present study
Scenedesmus obliquus microalgae	2.33	0.71	0.135	[15]
Sugar bagasse	1.62	0.73	0.0027	[52]
Fruit and vegetable waste	1.78	0.57	0.047	[58]
Cassava tuber	1.33	0.58	0.028	[58]

3.5. Higher Heating Values

Although significant research has focused on HHV and estimation equations, few studies have identified which biomass composition affects the energy content of bio-oil, especially for IAPs. This study bridges that gap by evaluating the influence of the structural, elemental, and proximate composition on HHV.

Table 4 shows that the HHV of woody IAPs based on the structural composition was 18.4 MJ/kg, whereas that of nonwoody IAPs was 17.2 MJ/kg. The non-overlapping confidence intervals (CIs) in Figure 4a suggest a statistically significant difference, which can be attributed to variation in cellulose, hemicellulose, and lignin, as discussed in Section 3.1. These results suggest that prioritizing woody IAPs could improve bio-oil quality, which could translate into an efficient combustion process. Although woody IAPs exhibit HHVs, pretreatment methods with higher energy inputs are essential during pyrolysis to depolymerize the complex structure of lignin.

While woody IAPs exhibit higher HHV based on the elemental composition, certain non-woody species, such as L. camara (19.5 MJ/kg), surpass some woody species, such as A. mearnsii (17.9 MJ/kg). The lower HHV of A. mearnsii is linked to its lower carbon (44.6%) and hydrogen (5.6%) content, along with a higher oxygen level (48.8%) compared to other IAPs. These variations underscore the importance of upgrading techniques, such as acid-catalyzed deoxygenation, that can be employed to convert oxygenated compounds into lighter hydrocarbons, enhancing the energy quality of bio-oil.

Notably, the HHV from the elemental composition was the highest among all the HHV derived from the proximate and structural compositions, as shown in Figure 4a, because of the combustible elements such as carbon and hydrogen [59,60]. A study by the authors of [32] revealed that the proximate composition indirectly estimates the heating value, as it accounts for noncombustible components such as moisture and ash, whereas the structural composition may be affected by the complex lignin structure, leading to incomplete combustion. HHVs ranging from 17 to 20 $\mathrm{M}\mathrm{J}/\mathrm{k}\mathrm{g}$ and 15 to 19 $\mathrm{M}\mathrm{J}/\mathrm{k}\mathrm{g}$, respectively, from other researchers were reported for both woody and nonwoody samples, which is in accordance with the results obtained in this study [61]. This introduces an innovative multi-layered approach compared a single method, providing a comprehensive understanding of how IAPs influence the biofuel energy potential.

Table 4 further presents different South African energy coal types, and both woody and non-woody IAPs resemble peat coal, as shown in Figure 4b, which is a low-energy fuel that can be utilized for heating in agriculture. Unlike high-rank coals such as anthracite and bituminous coal, IAPs contain a lower carbon content, higher moisture levels, and reduced energy density [62]. This section contributes to understanding which compositional factors are essential for making IAPs suitable for applications similar to coal while offering a cleaner and more environmentally friendly alternative.

Table 4. HHV of woody and nonwoody IAPs derived from structural, elemental, and proximate compositions.

Species	HHV from Structural Composition (MJ/kg)	HHV from Elemental Composition (MJ/kg)	HHV from Proximate Composition (MJ/kg)
Woody IAPs
A. mearnsii	18.28$\pm$ 0.73	17.87 $\pm$ 0.96	18.94 $\pm$ 0.52
E. grandis	18.13 $\pm$ 0.56	20.39 $\pm$ 0.10	18.54 $\pm$ 0.72
P. patula	18.83 $\pm$ 0.87	20.20 $\pm$ 0.13	18.81 $\pm$ 0.35
Nonwoody IAPs
L. camara	17.32 $\pm$ 0.39	19.45 $\pm$ 0.18	16.40 $\pm$ 0.12
C. odorata	17.24 $\pm$ 0.48	18.88 $\pm$ 0.29	16.71 $\pm$ 0.29
S. mauritianum	17.04 $\pm$ 0.44	19.03 $\pm$ 1.45	16.19 $\pm$ 0.31
South African Coal
Coal	Higher heating value (MJ/kg) [63]
Peat	17.4 to 22.4
Lignite	26.5 to 31.7
Bituminous	19.9 to 36.4
Anthracite	30.6–36.2

All values are means of three values ± standard deviations.

Table 4. HHV of woody and nonwoody IAPs derived from structural, elemental, and proximate compositions.

Species	HHV from Structural Composition (MJ/kg)	HHV from Elemental Composition (MJ/kg)	HHV from Proximate Composition (MJ/kg)
Woody IAPs
A. mearnsii	18.28$\pm$ 0.73	17.87 $\pm$ 0.96	18.94 $\pm$ 0.52
E. grandis	18.13 $\pm$ 0.56	20.39 $\pm$ 0.10	18.54 $\pm$ 0.72
P. patula	18.83 $\pm$ 0.87	20.20 $\pm$ 0.13	18.81 $\pm$ 0.35
Nonwoody IAPs
L. camara	17.32 $\pm$ 0.39	19.45 $\pm$ 0.18	16.40 $\pm$ 0.12
C. odorata	17.24 $\pm$ 0.48	18.88 $\pm$ 0.29	16.71 $\pm$ 0.29
S. mauritianum	17.04 $\pm$ 0.44	19.03 $\pm$ 1.45	16.19 $\pm$ 0.31
South African Coal
Coal	Higher heating value (MJ/kg) [63]
Peat	17.4 to 22.4
Lignite	26.5 to 31.7
Bituminous	19.9 to 36.4
Anthracite	30.6–36.2

All values are means of three values ± standard deviations.

3.6. Thermogravimetric Analysis

The objective of performing thermal analysis was to examine the thermal behavior of IAPs and determine the optimal stages and temperature ranges for pyrolysis to achieve the maximum bio-oil yield. Figure 5 and Figure 6 show the thermogravimetric analysis (TGA) and differential thermogravimetry (DTG) curves produced for nonwoody and woody IAPs after thermal analysis, respectively. A summary of the data extracted via TGA and DTG is shown in

Table 5. Three stages of pyrolysis in woody and nonwoody IAPs from TGA.

	Dehydration			Active Pyrolysis				Passive Pyrolysis
Woody IAPs
Sample	${\mathrm{m}}_{\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}}\left(\mathrm{\%}\right)$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$	${\mathrm{m}}_{\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}}\left(\mathrm{\%}\right)$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{p}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$
E. grandis	2.5	33	147	77.6	147	468	279	468	600
A. mearnsii	1.6	33	205	98.1	205	470	305	470	600
P. patula	3.4	34	155	75.5	155	446	286	446	600
Nonwoody IAPs
Sample	${\mathrm{m}}_{\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}}\left(\mathrm{\%}\right)$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$	${\mathrm{m}}_{\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}}\left(\mathrm{\%}\right)$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{p}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{i}}(°\mathrm{C})$	${\mathrm{T}}_{\mathrm{f}}(°\mathrm{C})$
L. camara	5.1	35	176	58.5	176	476	315	476	600
C. odorata	6.2	33	177	59.5	177	474	308	474	600
S. mauritianum	5.3	33	180	59	180	480	326	480	600

, with ${\mathrm{m}}_{\mathrm{l}\mathrm{o}\mathrm{s}\mathrm{s}}$ representing weight loss, ${\mathrm{T}}_{\mathrm{i}}$ representing the initial temperature, ${\mathrm{T}}_{\mathrm{f}}$ representing the final temperature, and ${\mathrm{T}}_{\mathrm{p}}$ representing the peak temperature. The results in Table 5 show three stages of pyrolysis. The first stage is the dehydration region at temperatures ranging from 33 to $180 °\mathrm{C}$ for nonwoody IAPs and 33 to 205 °C for woody IAPs, with a negative peak observed at 110 °C in DTG (Figure 5). This stage is not designed for bio-oil production but primarily involves the released moisture with no volatile compound emissions. The second stage, referred to as active pyrolysis, occurs between 180 and 480 °C for nonwoody IAPs and between 205 and 470 °C for woody IAPs. This stage is crucial for ensuring the optimal yield of bio-oil because of the degradation of cellulose and hemicellulose, which release volatile compounds that readily condense to bio-oil. The final stage, termed passive pyrolysis, occurs between 480 and 600 °C for nonwoody IAPs and between 470 and 600 °C for woody IAPs. This stage is attributed to lignin decomposition and the formation of char at relatively high temperatures [64]. The results obtained in this work are supported by a study performed by the authors of [65] in which no bio-oil was obtained at 300 °C, and the bio-oil yield was 6.2% at 450 °C, which decreased to 5.7% at 600 °C.

These findings imply that the active pyrolysis stage is the most important stage for maximum bio-oil. Performing TGA allows informed decisions on reactor design and better control of the temperature and reaction rate. The limitation observed was an inability to show temperature ranges for cellulose and hemicellulose separately, as this would assist in understanding thermal stability and improving material characterization and processing.

4. Conclusions

This study demonstrates the dual-purpose potential of invasive species as both a renewable energy source and a solution for ecological management. The analysis of the proximate, elemental, and structural composition identifies biomass characteristics that optimize the yield and quality of bio-oil. For instance, the presence of higher carbon and hydrogen in IAPs correlates with higher HHV, improving combustion efficiency, while elevated oxygen levels contribute to chemical instability and corrosion risks. This enables the strategic selection of high-performing biomass substrates, reducing the need for post-processing and making bio-oil production cost-effective. Additionally, it provides guidance on bio-oil upgrading techniques such as hydrodeoxygenation or catalytic cracking, which remove excess oxygen, mitigating engine corrosion risks in agricultural machinery.

Furthermore, understanding biomass traits contributes to optimizing pyrolysis efficiency; the complex structure of lignin in IAPs requires a higher energy input for degradation. By understanding this relationship, this study enables the fine-tuning of pyrolysis conditions and the designing of advanced pyrolysis reactors that improve heat transfer and, ultimately bio-oil production. Integrating biomass selection with pyrolysis optimization, this research contributes to economically viable and sustainable biofuel production for agricultural systems.

Adopting a proximate, elemental, and structural composition in estimating IAP HHV offers a multi-faceted approach with more accuracy and reliability in bio-oil energy density predicting methods. By identifying elemental composition as a factor that contributes to high HHV, this approach allows for the prioritization of biomass with a high energy return per unit mass, optimizing fuel cost efficiency. Additionally, the comparative analysis of IAPs with various coal introduces a direct energy potential reference, enabling the practical evaluation of bio-oil viability as an alternative fuel, reducing reliance on fossil fuels.

Identifying the optimal pyrolysis temperature range between 450 and 600 °C allows the pyrolysis reactor to operate at peak efficiency, minimizing energy waste and optimizing the bio-oil production rate.

Overall, this study contributes to converting IAPs into bio-oil, highlighting their viability as fuel for agricultural machinery, reducing reliance on fossil fuels, and providing cost-effective energy sources for operations. Additionally, clearing IAPs reclaims agricultural land that outcompetes native crops, restoring soil health with biochar byproducts and ultimately improving agricultural production. Further research could focus on optimizing IAP collection processes and the potential implementation of biomass plant units in South Africa.