1 Introduction

Developing a sustainable energy system requires encouraging renewable energy, reducing environmental impact, and high efficiency at competitive costs. The use of renewable energy to diversify the energy mix for achieving the net zero emission target is increasing. Various countries compete in promoting renewable energy and include long-term roadmaps in their energy mix. Biomass is a crucial alternative to renewable energy because it is considered carbon neutral and widely spread evenly worldwide [1]. Carbon neutral is a term to describe the state where the net release of carbon dioxide (CO2) or other greenhouse gases (GHGs) into the atmosphere is zero. It means that the amount of GHGs emitted into the atmosphere is balanced by the amount removed from the atmosphere or prevented from being emitted through various measures, such as reducing emissions, carbon sequestration, or using renewable energy sources. Biomass is a complex compound with components generally consisting of starch, cellulose, hemicellulose, lignin, proteins, and other minerals. Analyzing and considering the different characteristics of each type of biomass can significantly determine the appropriate biomass treatment, including suitable conversion methods [2]. For example, high moisture biomass requires drying as a pretreatment to increase its calorific value. Also, high alkali and alkaline earth metals in the feedstock must be washed before utilization [3]. However, the energy input demand for drying and water washing can significantly reduce the overall efficiency [4].

Based on human intervention, biomass can be categorized into three types: natural plants (aquatic and terrestrial plantations), energy crops, and biomass waste, as depicted in Fig. 1 [2]. Forestry is an example of the first category, where resources can grow naturally and be utilized for human needs. In addition, biomass is grown and dedicated to energy sources such as biofuel production in energy crops. In energy crops, the fuel produced can be solid, liquid, or gas. Furthermore, they can be converted depending on the demand to generate electricity or heat. Finally, biomass waste is advantageous for energy use because it is inexpensive and can reduce the environmental impacts of inappropriate disposals and treatments, such as open burning and landfilling.

Fig. 1
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General classification of biomass

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Based on the region, biomass can be classified into the tropical, sub-tropical, boreal, and temperate domains. The tropics is the area between the tropic of Cancer (23.5°N) and Capricorn (23.5°S), with complex weather patterns and various environments. The tropical domain covers most global forests, up to 45%, followed by the boreal, temperate and subtropical domains [5]. The temperature in the tropical area tends to be uniform without significant differences except in the highlands. This area has an average temperature of at least 18 °C and receives enough rainwater in its soils [6]. Since most terrestrial biomass is located in the tropical domain, it can become essential to the global carbon cycle and climate change mitigation [7]. Tropical forests are believed to accommodate more than 50% of the world’s biodiversity and store two-thirds of all the carbon in terrestrial plants, making them incredibly valuable [8, 9]. Burning biomass for energy use has been carried out for a long time and can significantly impact atmospheric chemistry and climate [10].

Indonesia is an archipelagic tropical country with abundant and diverse biomass potential. There are many sources of biomass from forests, plantations, and agriculture, which include wood residue, rice husks, corn residue, and special wood plantations [11]. Wallacea, as part of the tropical region, attracts much attention from researchers because it is a meeting point between Asia and Australia and has rich biodiversity [12]. This paper discusses the scenarios for using biomass as an energy source, including the available technologies, especially for the Wallacea region. Constructing feasible technological scenarios and end-products is also important to build sustainable bioenergy-based systems. Furthermore, it is aligned with Indonesian policy targets for bioenergy generation to achieve a carbon–neutral target by 2060. Firstly, the potential of biomass in the Wallacea region needs to be addressed. The following section discusses several scenarios, routes, and utilization technology options for biomass utilization. Various studies that have been conducted are presented in this section, including the adoption of machine learning (ML) to model and optimize biomass conversion processes. Furthermore, challenges and opportunities are discussed by looking at various factors, such as accessibility, socio-economics, life cycle assessment (LCA), and environmental issues.

2 Energy situation and potential resources in Indonesia

Indonesia’s primary energy supply in 2021 was 225.65 million tonnes of oil equivalent (Mtoe), which was dominated by fossil energy sources, especially coal (36%), followed by oil (32%) and gas (16%), as shown in Fig. 2 [13]. Biomass utilization was estimated at 11% of total energy, equivalent to 23.88 Mtoe, higher than other renewable energy, including hydropower, geothermal, and PV utilization. The national energy mix policy targets a contribution of 31% by 2050 for renewable energy. The Nationally Determined Contribution (NDC) also sets a 29% emission reduction with a contribution of 314 million tonnes (Mt) of reduction in the energy sector [11, 14]. This sector is predicted to generate about 1,669 Mt of CO2 under the business-as-usual (BaU) scenario in 2030 [14]. Adding large coal power plants in recent years will significantly affect the emissions. New coal power plants with a total capacity of 4,800 MW, for example, at least potentially emit 27–32 Mt of CO2 equivalent (CO2-eq) annually if it is not equipped with carbon capture [15].

Fig. 2
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Primary energy supply in 2021 (a) and in 2050 (b), as targeted by the government

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Four types of renewables are promising in the future but have not been utilized optimally: hydro, solar, wind, and biomass (including biomass waste) energy. Indonesia has the potential for geothermal, hydro (including micro-hydro), biomass, and solar of 29.5, 94.5, 32.7, and 207.9 GW, respectively (Table 1). Although with a total potential of 443.2 GW, the installed renewable energy capacity was only 11.6 GW in 2021 [16]. Mahidin et al. reported that the potential biomass in this country is around 130 Mt, equivalent to 34.4 Mtoe [17]. The biggest proportion is crops, followed by forest and agro-industry residues, as shown in Fig. 3.

Table 1 Installed capacity vs. estimated potential of renewable energy
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Fig. 3
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Annual biomass potential in Indonesia [17]

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An assessment of biomass forest potential for bioenergy purposes has been conducted to understand the potential of Indonesia’s forest biomass resource as a fuel feedstock [18]. The findings are meant to encourage higher biomass utilization in the future and to guide the development of energy and forestry policies. They reported that the potential energy of forest biomass in Indonesia was about 132 PJ, with 50.4% from harvesting residues and 49.6% from wood processing residues. A higher number was reported in another study of 1261 PJ [19]. Differences in approaches for estimation are likely to affect the output. Another study reported the breakdown for each type of biomass, especially for crop waste [20]. The study took into account the area of the plantation and the specific waste per area (t/ha). They reported palm oil waste has a potential of about 32.86 Mt annually, followed by coconut (7.11 Mt), rubber trunk (3.79 Mt), and sugar cane (2.73 Mt). This country produces the largest palm oil in the world, owing to the massive expansion of palm plantations and high global demand [21]. A potential of 40 to 168 GL of bio-methanol could be generated for fuel, according to [22]. It equals half of Indonesia’s current power consumption, potentially reducing emissions by 9 to 38% of the total carbon emitted yearly.

In the electricity generation sector, renewable energy utilization is still limited. A study shows fossil-based fuels are still dominant for the next few decades to meet electricity demand (see Fig. 4) [23]. A massive breakthrough is needed to achieve the government’s decarbonization target, especially for net zero emission in 2060. In the energy sector, efforts have been focused on strategies such as switching to cleaner fuels as alternative approaches to reduce emissions and environmental impacts, including co-firing of coal and biomass and hydrogen energy development. This approach is considered suitable because both can replace hydrocarbon fuels completely. Biomass utilization as a power plant has a potential capacity of 32 GW, spread over many islands [24]. The agricultural and forestry sectors are very promising fuel sources, especially from their waste. Palm oil waste, such as palm kernel shells (PKS), empty fruit bunch (EFB), and palm oil mill effluent (POME), has the greatest potential (more than 10,000 MWe) compared to other biomass wastes, such as rice husk and municipal solid waste [11]. Stich et al. estimated a biomass potential of about 407 TWh annually [25]. Power generation with biomass, in general, can be performed via co-firing with coal. This method is considered promising because of its relatively low cost. However, co-firing has several challenges, primarily related to boiler performance due to the impact of the ash produced. The characteristics of the ash produced can interfere with the performance of boiler heat exchangers. Further investigation is required to ensure co-firing sustainability for the long term [21].

Fig. 4
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The demand for power generation by type of fuel [23]

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3 Biomass potential in the Wallacea region

The Wallacea archipelagic region is the islands in the central part of Indonesia, consisting of Sulawesi, the Nusa Tenggara, Timor Island, and the Maluku Islands, as illustrated in Fig. 5. The area comprises approximately 1680 islands (with Sulawesi as the biggest island), covering an area of 338,000 km2, and is estimated to have a forest area of 141,080 km2 [26, 27]. Wallacea has a drier climate with lower humidity than other parts of Indonesia, except around the Maluku Islands [28]. Mountain forest vegetation is spread around Sulawesi. Closed, tall, and dense plant species characterize the mountain forest biome. Not only mountain forests but there are also mixed forests in the Maluku region, which are equipped with various types of spices, such as cloves, cinnamon, walnuts, and ebony wood [29, 30].

Fig. 5
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Wallacea region in the central part of Indonesia [12, 31]

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Due to its vital role, various attempts have been made to estimate the potential of a forest. Multiple approaches have been taken to produce accurate data and minimize errors. Forest biomass is an essential variable in calculating the amount of carbon that can be absorbed, including its role as a source of bioenergy. Therefore, an accurate forest biomass estimation is necessary to analyze terrestrial ecosystems’ carbon cycle in large areas [32]. Forest biomass, in general, can be estimated by field calculations and remote sensing methods. The former can produce optimal results for small forests and is not feasible for larger areas considering the cost required, amount of labor load, and time consumed [33]. Remote sensing is needed to estimate the regional scale because this approach requires less manual work and can cover large areas, including inaccessible areas [34]. Sensors can easily acquire data without directly contacting the measured object. Sensors can be divided into passive and active sensors, whereas platforms range from satellites and planes to unmanned aerial vehicles (UAVs) [35].

Simangunsong reported a study that focused on forest residues primarily from natural production forests and industrial forest plantations, as well as wood processing mill residues [18]. Using secondary data, they analyzed the residual factors to determine the potential of biomass as biofuel. However, their investigation did not cover material from early silvicultural thinnings and trees grown in energy plantations due to data availability. A study with remote sensing utilizing UAV-based high-resolution RGB images processed by ML algorithms has been carried out by Kurniawan et al. [9]. The biomass considered were sugar palm, clove, and coconut trees. In addition, a study on mapping Mangrove vegetation has been reported by Rudiastuti et al. [36]. They performed data integration and field study to overview Mangrove vegetation comprehensively. They found Southeast Sulawesi has the largest mangrove forest area with 62,446.4 ha, followed by Central Sulawesi (33,538), North Sulawesi (11,884 ha), South Sulawesi (10,412 ha), Gorontalo (8006 ha), and West Sulawesi (3720 ha).

Furthermore, using Landsat ETM + and MODIS data, tropical rainforests in Sulawesi have been estimated [37]. The up-scaling approach has been developed to identify tropical rainforests and overcome the problem of resolution mismatch between the ground sampling plots and the MODIS data. The study concluded about 48.74 to 612.21 t/ha biomass spread across Sulawesi with a total of about 2408.3 Mt. However, further investigation is needed to determine the potential of biomass utilized in the energy sector. In addition, the raw data of existing biomass needs to be further projected to ensure a sustainable supply. Almulqu and Boonyanuphap studied dynamic ecosystem biomass to accurately estimate the biomass potential in Rote Ndao Regency (East Nusa Tenggara) [38]. The research only focused on common tree species, such as Schleicera oleosa, Dryobalanops aromatic, Mangifera indica, Cordirchotoma torsi, Tamarindus indica, Ficus benyamina, and Vitex parviflora. They highlighted the importance of essential information, such as wood density, to improve the data quality. Research related to biomass potential in the Wallacea region is summarized in Table 2.

Table 2 Research related to biomass potential in Wallacea region
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In practice, all available biomass cannot be used as an energy source. The safest to use is waste which has no competition with other uses such as material and food, including conservation purposes. Furthermore, most available wastes are not utilized due to collection difficulties and their inherent characteristics. Therefore, minimizing costs and risks can be anticipated by mapping the biomass potential considering conversion methods [2]. The waste is economically preferable with great environmental benefits. However, if an available crop is grown solely for energy, it could lead to environmental destruction. Rhofita et al. [17] offered a framework for biomass waste assessment in Indonesia, as shown in Fig. 6.

Fig. 6
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The proposed perspective of biomass waste utilization in Indonesia [19]

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Indonesia’s representative has presented Sulawesi’s biomass potential for energy use and reported that rice husk (1.11 GW), palm oil waste (0.32 GW), corn waste (0.25 GW), and others could provide 1.9 GW of electricity [11]. Unfortunately, the presented biomass potential is not accompanied by a data collection method. The study conducted by Japan International Cooperation Agency (JICA) revealed a higher biomass potential in the Wallacea region, with about 71 TWh annually, which is dominated by wood waste, rice waste, and corn waste, as depicted in Fig. 7 (accounting for almost 90%) [40]. As a country with the third largest tropical forest, Indonesia has enormous potential for waste forests, including in the Wallacea region. Wood waste usually comes from logging activities, rubber residue, sawdust, wood chips, and plywood waste. With a wider forest area, Sulawesi dominates the total wood waste produced with almost 19.29 TWh annually.

Fig. 7
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Potential energy from biomass in the Wallacea region (in TWh/y)

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If converted into GW capacity units, the potential of the biomass in each island in the Wallacea region is very high to generate electricity (see Fig. 8). However, conversion to electrical units is intended to help for better understanding and does not mean that all raw biomass wastes must be converted to electricity. For example, Sulawesi has a higher biomass waste potential (of about 5.27 GW) than net electricity capacity in 2025 (estimated based on the government plan [41]). However, the latest report in 2016 stated that the potential for biomass waste in Sulawesi is around 2.5 GW [42]. It is unclear whether the differences in approaches or due to significant deforestation on the island. In addition, several power plants have been demonstrated to co-fire to maximize biomass waste utilization. However, a techno-economic evaluation of co-firing technology and further study of other technological options is needed.

Fig. 8
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Biomass potential capacity compared to net power capacity in 2025

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A study on using pellets from sorghum for electricity production has also been carried out for the East Nusa Tenggara region by Wiloso et al. [39]. The capacity of sorghum biomass produced was assumed to be 25% of the marginal land or around 100,000 ha. Their study also analyzed the LCA to evaluate replacing coal fuel with biomass thoroughly. However, the results depend on the assumptions of the data obtained. More intensive trials are also needed to get a technical report on the performance of coal-fired power plants, such as combustion efficiency and the effect of biomass on ash deposits. It was reported that sorghum pellets could result in high slagging or fouling tendencies and threaten the durability of boilers. Based on the annual estimated potential, 8500 GWh of electricity could be generated from biomass yield or reduced emissions of 7.9 Mt of CO2-eq. In addition, West Nusa Tenggara has potential biomass waste, especially from rice husk and corn residues of more than 20,000 TJ/y, including biofuel (from Jatropha Curcas) and biogas [43]. It is equivalent to the energy generation of more than 600 MW of biomass-based plants.

Biomass waste can be used directly or indirectly as fuel. Charcoal, rice husk, twigs, and dry leaves briquettes are examples of biomass fuels that can be used directly as heating or power sources [44]. The heating value of biomass fuel varies depending on the source. The use of biomass can make a significant contribution to waste management, fuel security, and climate change. In rural areas, especially in developing countries, biomass from wood, leaves, rice husks, and straw is the primary fuel for heating and cooking. Several solutions are offered to reduce the impact of the direct burning of biomass on the environment and health, one of which is better conversion technology using biomass stove technology [45]. Biomass stove technology can increase the efficiency of burning biomass and reduce pollution emissions significantly, thereby preventing the negative impacts of using biomass on family health. The National Electricity Company (PLN) has planned to use biomass for power generation and is targeting a total of 45 MW (5 locations) in Maluku starting in 2024. In Sulawesi, 50 MW of biomass power generation was also prepared, as well as 9.8 MW in Gorontalo and about 10 MW in Nusa Tenggara [41]. Apart from being utilized for dedicated biomass power generation, the existing potential can be used for co-firing in coal power plants. Around 19 GW of coal power plants in Indonesia have the potential to be co-fired. More than 500 MW of coal power plants in the Wallace region have been planned to be co-fired with biomass, and, up to now, they have been successfully demonstrated in three locations. East Nusa Tenggara has also established a 1 MW gasification system from biomass.

4 Energy conversion scenarios, routes, and technologies for tropical biomass

4.1 Tropical biomass conversion technologies

Biomass waste generally consists of cellulose, hemicellulose, lignin (aromatic polymer), and extractives (in small amounts). Because it is resistant to hydrolysis, complex cellulose must be pretreated to break into simple sugars before fermentation to produce biofuel. Hemicellulose, a complex polysaccharide produced from various five- and six-carbon sugars, is weaker than cellulose. Hemicellulose hydrolysis is simpler than cellulose hydrolysis because of the amorphous nature of its structure and the involvement of a smaller number of hydrogen bonds [46]. Hemicellulose is easily degraded into simple sugars, unlike strong and crystalline cellulose. Cellulosic biomass contains lignin, a group of complex organic polymers that provide the cell wall’s mechanical strength. Lignin can be used for biofuel production or converted into energy through a thermochemical process [2]. Table 3 estimates the chemical composition of several different biomass wastes [47,48,49,50].

Table 3 Typical chemical composition of available biomass in the Wallacea region
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Technological advances to harness the energy contained in biomass are growing dramatically. Appropriate procedures are used to increase the collected biomass waste (depending on circumstances). Size reduction, compaction, drying [51], and torrefaction are required before being converted using the primary technologies. The main pathways of biomass conversion to energy can be categorized into thermochemical and biochemical conversions, as illustrated in Fig. 9. The thermochemical approach involves heat and chemical processes to obtain primary products from biomass waste, such as direct combustion, gasification, pyrolysis, and more advanced method using thermochemical cycles. In addition, the biochemical conversion uses microorganisms to decompose and convert raw fuel with gaseous or liquid fuels as products: anaerobic digestion, fermentation, and photobiological hydrogen production. The biofuel products can be varied depending on microorganisms’ selection; hydrogen [52], biogas/methane [53, 54], ethanol, acetone, butanol, organic acids, butanediol, isobutanol, xylitol, mannitol, and xanthan gum. Biochemical conversion methods are preferred because of their simplicity and do not require dry input materials as required in thermal conversion [53]. In addition, the final product can be used directly or stored before being distributed to final users.

Fig. 9
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A simplified guide for biomass utilization in the Wallacea region

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Although potentially very high, biomass utilization still faces many technical and non-technical challenges. The government provides several prioritized programs and guides related to bioenergy, including (1) the utilization of waste as a source of electricity generation, (2) biofuel programs, and (3) waste utilization from agriculture, plantation, and forest land, as well as degraded land. Based on this program, the biomass potential in Wallacea can be simplified, as depicted in Fig. 9. Although biomass waste can be converted through various methods, the condition of the raw material itself may influence the selection of the most suitable technology.

The use of biodiesel nationally continues to grow in terms of quality, volume, mix, and the number of stakeholders (producers and consumers). Biodiesel products in Indonesia refer to first-generation biodiesel, which is produced through a transesterification reaction using methanol and an alkaline catalyst, such as sodium methylate (Na-methylate), sodium hydroxide (NaOH), or potassium hydroxide (KOH). In this process, biodiesel is the main product, with glycerol as a by-product. Biodiesel has reached B30, a mixture of 30 vol% fatty acid methyl ester (FAME) in automotive diesel oil. Furthermore, a matrix related to feedstock and its utilization technology has been proposed, as listed in Table 4 [24]. Almost all of the existing biomass waste can be utilized as a source of bioethanol raw materials through pyrolysis or cellulosic bioethanol. In addition to producing biofuels, using biomass to generate power is also a promising technology option. The gasification route is also an attractive option besides direct combustion to produce steam to drive turbines. The National Electricity General Plan (RUKN) states that PLN plans to implement co-firing to their 52 units of coal power plants. Co-firing is a thermochemical conversion method by substituting coal at a specific ratio with biomass materials such as wood pellets, PKS, and sawdust. In 2024, it is estimated that the total co-firing capacity at PLN’s power plants will reach 18 GW. The co-firing plan is intended to support renewable energy development without constructing new generators. Compared to conversion with other methods, co-firing has several characteristics, such as low costs, ignition acceleration [55], no need to build a new power plant, and reduced coal utilization, but it requires a sufficient biomass supply. A co-firing trial on the 26 coal power plants has demonstrated up to a 5% biomass ratio, including in the Wallacea region.

Table 4 A proposed matrix related to feedstock and its utilization technology
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Applying co-firing biomass in a circulating fluidized bed (CFB) or pulverized coal boilers could reduce combustion efficiency [56, 57]. In other words, a larger fuel mass is required to produce the same energy output. Alfian et al. [58] investigated the effect of co-firing coal with wood chip biomass (up to 30%) on the performance of coal feeder and draught plants of 50 MW circulating fluidized bed. They reported that biomass co-firing could increase the feeder and draught plant’s auxiliary power consumption and the net plant heat rate (NPHR). This co-firing technology can be used on various power plant scales from 100 to 3000 MW. However, pretreatments, such as drying and pulverizing, may be required depending on the characteristics of the boiler [59].

A report issued by Economic Research Institute for ASEAN and East Asia (ERIA) discussed the challenges during biomass fuel combustion in the CFB boiler, especially for tropical biomass (see Fig. 10). However, this CFB boiler is designed to tolerate various fuel types and accommodate biomass that cannot be used in pulverized boilers. Even though they have a relatively lower tendency, CFB boilers also have the potential to have ash-related problems such as slagging, fouling, and corrosion due to biomass mixture in the combustion [60]. Hariana et al. [21] studied combustion performance, including slagging-fouling behavior during coal co-firing with EFB and frond. They found that co-firing 25% biomass with bituminous coal potentially increases the probability of slagging, confirmed by lowered ash melting temperatures, deposition, and sticky material in the boiler probe. Instead of drying, pretreatment through hydrothermal treatment is claimed to improve raw biomass quality significantly [61,62,63,64]. It is a pressurized thermal conversion process conducted under supercritical water conditions between 150 and 350 °C. The improved biomass fuel can then be co-fired with coal to produce better combustion performance and lower emissions [65, 66]. Practically, additional energy is required for continuous operation, so it is feared that it will reduce the overall efficiency.

Fig. 10
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The adaptability of fuel for CFB boiler [67]

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In several simulated case study scenarios, palm oil waste as a co-firing material (with a ratio of 25%) can reduce emission intensity (g/kWh) to 20% lower than dedicated coal [67]. If biomass utilization is increased to 50% in the boiler, the reduction is quite linear, with a 44% reduction in CO2 emissions. However, raising the biomass ratio from 25 to 50% is expected to slightly decrease the overall efficiency from 34 to 32% (based on lower heating value).

Pyrolysis is another option for converting biomass waste into useful products. This method can be divided into flash, fast, and slow/conventional, as summarized in Table 5. Flash pyrolysis is carried out at temperatures of about 700–1000 °C with very short residence times and higher heating rates, generating gas, liquid/bio-oil, and a small amount of biochar. It generates bio-oil at moderate temperatures with a 0.5–2 s residence time. Fast pyrolysis is more developed than flash and slow pyrolysis because it can produce higher efficiency and related environmental issues [68]. The compositions of the bio-oil, gas, and charcoal yields are 70–75, 13, and 12%, respectively. This process requires heat which can be obtained from the gas or solid fuel produced. Bio-oil has the potential to act as an intermediary before being upgraded and fractionated to produce higher-quality fuels. Furthermore, wider applications, such as transportation fuel, require a feasibility assessment.

Table 5 Classification of pyrolysis methods
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Fast pyrolysis has been commonly used for industrial combustion. Some tropical biomasses, including ogbono wood, mango wood, neem wood, ogbono shell, ogirisi wood, and tropical almond wood, were studied for biofuel production through pyrolysis [69]. The highest bio-oil yield of 66 wt% was obtained from neem wood. The efficiency could be increased by combining bio-oil yield of about 80% and biochar combustion for heat sources [70]. Improved reactor and operational conditions may lead to higher bio-oil production. However, it may also be challenging to identify precise reasons that cause variations in the amount of bio-oil produced from these species because so many variables might affect them, including process temperature, heating rate, the composition of biomass, and residence time [71, 72]. A study on the case of tropical biomass in developing countries reported that fast and slow pyrolysises are quite effective in reducing CO2 emissions at a moderate cost. Gasification tends to be high-cost unless aided by high carbon and electricity costs [73].

The main thermochemical conversion methods for biomass conversion include combustion, gasification, and pyrolysis. Apart from that, there is also a chemical looping method that is still in development. These processes are inherently related to one another. An overall summary of these conversions is tabulated in Table 6. It should be noted that carbon capture can be added to the back end of conventional biomass thermochemical conversion processes to capture CO2 for a net CO2-negative process [74].

Table 6 Characteristics of main thermochemical conversion technologies [74,75,76,77,78,79,80,81]
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Unlike combustion and pyrolysis, gasification is a partial oxidation process with complex chemical reactions at a high-temperature range of 500–1300 °C. In this process, a gasifying agent such as water, steam, or oxygen is generally used to produce a mixture of syngas (H2, CO, CH4) and CO2, H2O, N2, and light hydrocarbons. The utilization of gasification to convert biomass waste, such as rice husk [82] and wheat straw [83], has been reported. The gas produced can be used in power plants and processed into H2, dimethyl ether (DME), methanol, ethanol, or other fuels. Gasification can also be combined with an integrated system to produce higher efficiency, called the integrated gasification combined cycle (IGCC). Among the common problems faced by the gasification process is the production of tar and unwanted contaminants, such as alkaline compounds, increasing the cost of purification. A gasification reactor’s performance can be influenced by the type and design of the gasification reactor/gasifier, biomass composition, temperature, catalyst, and gasification agent. Gasification technologies can be classified into types: fixed or moving bed, fluidized bed, and entrained flow, as shown in Fig. 12. Compared to the other gasifier, a fluidized bed has numerous benefits such as uniform heat transfer, high biomass-to-gas conversion rates, and flexibility for large-scale production [84, 85]. Even though it might be suitable for coal on a large scale, using an entrained gasifier for biomass waste is not applicable due to its high moisture content and required fine particles [84, 86].

4.2 Advanced methods for optimization

An approach using a mathematical model is needed to solve problems that involve high complexity, non-linear parameters, and high-dimensional, including those related to the design of thermal conversion processes, optimization, and intensification [87]. As depicted in Fig. 11, models can be used to determine optimal operating conditions, including various possible outputs for a system. Models can also enable real-time process control and optimization and forecast critical process performance parameters [88]. Among these strategies, ML has recently attracted considerable attention to optimizing biomass conversion processes, yield prediction, real-time monitoring, and process control, where artificial neural networks (ANN) have been the most commonly used algorithms [89]. The ANN is frequently employed to solve complex non-linear problems for biomass conversion via thermochemical or biochemical processes. Other ML approaches, such as support vector machine (SVM), decision tree (DT), random forest (RF), extreme gradient boosting (XGBoost), and adaptive-network-based fuzzy inference system (ANFIS), are also widely employed.

Fig. 11
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Using ML in biomass utilization, presented by Muzammil et al. [89]

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Lijian et al. [90] developed a model to predict several parameters during hydrothermal treatment using biomass wastes such as algae and food waste. The dataset is a compilation of 18 published papers, considering several features, including elemental composition, temperature, and other operating conditions. They found that nitrogen content, solid content, and temperature are the most critical factors in determining some output properties. In addition, Mohammadreza et al. [91] compared ML methodologies for predicting the kinetics of hydrothermal carbonization of selective biomass. They found that when the reaction kinetics were fast, the ML models differed from the experimental data. However, it is generally inferred that the ML techniques are suitable for interpolating and extrapolating the kinetics of the hydrothermal carbonization process. Gopirajan et al. [92] also concluded that an ML-driven optimization approach is better suited for a process that involves many parameters, such as the hydrothermal liquefaction of biomass.

Li et al. [93] used ML to understand, predict, interpret, and optimize biomass gasification using information obtained from raw material conditions and gasifier specifications. The results revealed that the gradient boosting regression (GBR) model predicted the compositions of three-phase products and syngas well. Higher H2 yield could be achieved under several conditions, such as high temperatures (> 800 °C), higher carbon, and lower nitrogen contents. ML-based models were developed for co-pyrolysis biomass to generate biofuel and biochar [94]. The models were trained, tested, and validated using hundreds of biochar and bio-oil data to predict yields of biomass pyrolysis. The authors also offered some analysis techniques to understand the effect of different parameters, thus providing excellent insight into this topic. Huang et al. [95] also used big data and ML to maximize char yield and higher heating value from biomass or other solids pyrolysis. They found that the developed polynomial regressions could accurately predict the desired outputs if the inputs are well known. The gradient boosting model also performed well with high accuracy based on pyrolysis feedstock and operation conditions. In addition, coal-biomass co-pyrolysis models were also studied using collected experimental results from the literature [96]. The data involved 30 biomass and 28 coal samples, such as corn stalks, husks, white pine, and wood waste. The solid fuel compositions were collected and analyzed, including experiment parameters such as the heating rate and the coal-biomass ratio. Among the results, temperature conditions are the most determining factor during co-pyrolysis, followed by mixture ratio, fuel characteristics, and heating value.

ML is also widely used to predict and solve complex biochemical conversion problems. The ANN, DT, SVM, and other approaches have been used to perform scientific tasks in methane, bio-oil, hydrogen, or ethanol productions via biochemical conversion. Based on a NARX-BP hybrid neural network, Xiao et al. [97] developed methane production using two-stage models involving microbial electrolysis cells and in-situ biogas upgrading. The results suggested two-stage approach performs better than the traditional one-stage model in predicting methane production. ANN method could also achieve a high level among different ML methods in modeling and could support long-term prediction and optimal performance for complex biochemical conversion.

Estimation of biogas and methane production from treating potato starch processing wastewater was developed using three-layered feedforward backpropagation ANN (BP-ANN) and multiple non-linear regression (MnLR) [98]. At several parameters, optimized methanation of 65–75% was achieved. BP-ANN showed better performance than the MnLR method since it could accommodate control of the anaerobic digestion process. Furthermore, a fermentative hydrogen production model has been developed using the ANN approach [99]. Sugarcane vinasse was utilized as raw materials during anaerobic fermentation, and some parameters were employed, such as fermentation time and volatile fatty acids (VFA) production. The model could predict H2 yield with high accuracy with R2 > 0.987. The authors also suggested that employing a model based on acetate and butyrate is recommended for complex or mixed cultures. Althuri et al. [100] optimized bioethanol production from lignocellulosic biomass using co-fermentation. A non-isothermal simultaneous pretreatment and saccharification were also performed. AI-ANN was employed in optimization modeling, adopting process parameters such as temperature, residence time, strain ratio, and substrate loading. In conclusion, every modeling and optimization approach developed has advantages and disadvantages. Using only one evaluation criterion to pick the best ML model is insufficient because each study has different objectives and methodologies. ML and optimization algorithms have advantages over conventional approaches in terms of precision and accuracy and potentially boost the use of biomass as an energy source in the future.

5 Challenges and opportunities

Currently, sustainable renewable energy development in the Wallacea region faces specific challenges from both technical and regulatory perspectives, such as economic, social, and environmental. Several points need to be highlighted, including the following:

  • Renewable electricity is relatively more expensive than conventional power plants (coal). However, as the production and introduction of renewable energy increase massively, the cost of renewable electricity decreases gradually, reaching a competitive level with fossil fuels;

  • Intermittent power plants (solar and wind) require energy storage to maintain the stability of the power supply and balance of the whole electrical grid;

  • Power plants with the least cost and good capacity factor, such as hydro and geothermal, are generally located in conservation areas far from power load, so they take a relatively long time to build due to licensing constraints, geographical constraints, and the potential for landslides;

  • Developing biomass and biogas for generating power requires a guaranteed feedstock supply over time.

The massive use of biomass requires a continuous supply. On a regional scale, information is needed regarding how much biomass can be utilized. As shown in Fig. 12, not all the total biomass waste can be used for energy. This estimate also needs to consider future projections, providing short-, mid-, and long-term estimates [101]. Although forestry and biomass industries offer relatively cheap and easy access, field measurement may still be required to calculate the recoverable biomass accurately. Even though it is abundant, if it is not easily accessible, it will increase recovery costs due to location constraints and tenure/land management constraints [102]. Location constraints are challenges in collecting and distributing biomass from harvesting to processing locations. Location-related costs are also determined by distance, mode of transportation, and terrain encountered. A study reports energy consumption while transporting biomass, assuming that one truck can transport 5 t of biomass with 3 km/L of fuel [103]. From the calculation, it is obtained that to distribute a distance of 30 km, 75 MJ/t of dry biomass energy is needed. This value is considered relatively small compared to the energy required in the drying process. In addition to location factors, social, political, and cultural conditions will influence the decision-making process related to the use of biomass because it involves land ownership/land rights.

Fig. 12
figure 12

The hierarchy from available biomass to recoverable biomass

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In the economic aspect, the assessment shows that converting biomass residues into wood pellets will increase the country’s forest resources’ value and government revenues from natural resource assets. The economic value of forest biomass is approximately 5.6 USD/t, including wood residues [18]. The cost of producing wood pellets is estimated to be around 103.0 USD/t or 5.7 USD/GJ, lower than other countries such as Finland, Germany, Norway, Sweden, and the United States [18, 104]. In addition, converting crop residues into wood pellets will also support Indonesia’s poverty alleviation strategy and other socio-economic benefits for rural communities, especially those who live on the edge of the forest and are vulnerable to poverty. The development of national bioenergy projects by 2050 will provide broad economic benefits, including creating jobs and avoiding environmental costs [11]. According to a cost and benefit analysis, the total economic benefits gained are 55 billion USD, including 12 billion USD from resilient job creation. Currently, in the Wallace region, 3 million people are living below the poverty line, according to Indonesia Statistics. Although the link between energy and poverty alleviation can be direct or indirect, the benefits of developing biomass for energy in poor areas are undeniable.

Furthermore, LCA for biomass utilization in the energy sector has been widely reported, including in tropical regions. Aberilla et al. [105] reported the LCA of the environmental sustainability of agricultural waste for power generation at a small scale in rural areas. The LCA evaluation has been performed following ISO14040/44. They concluded biomass conversion via anaerobic digestion is the best option based on 14 out of 18 impacts. The results also suggest that gasification has up to 12 times lower impacts per kWh than combustion to generate electricity. In addition, a review of the LCA study on biomass thermochemical conversion is reported, involving various technologies: combustion, co-combustion, pyrolysis, gasification, and liquefaction [106]. The work was mainly focused on lignocellulosic biomass to produce high-value end products such as power, biofuel, solid fuel, and chemical products. The reported LCA evaluation is commonly limited and divided into three main phases, from cultivation to plant demolition and recycling, as shown in Fig. 13. The author concluded it is important to investigate the co-generation process via multiple routes.

Fig. 13
figure 13

Three main phases for the LCA [106]

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Unsustainable biomass utilization due to excessive harvesting and consumption on a centralized or large system can lead to forest degradation, reduced biodiversity, and soil degradation [107]. In addition, other indirect impacts can arise, such as flooding, wastewater issues, and long-term health impacts due to direct burning. On a large scale, biomass energy is considered carbon–neutral but not nutrient neutral since extracted biomass contains nitrogen and other nutrients, not solely the cycle of carbon [108]. So far, LCA studies have tended to ignore this point, but in large-scale utilization, a more careful evaluation is needed to minimize environmental impacts. Biomass energy utilization can intersect and compete with urbanization, forests, and crops due to the massive use of land [108]. Palm oil expansion is responsible for Indonesia and Malaysia’s 1.5% annual deforestation rate [109]. In the thermochemical method, considerable impacts should also be addressed, including GHGs emissions, fly/bottom ash generation, water pollution, hazards due to prolonged exposure to toxic materials, and unintentional incidentals with the high-temperature operation.

6 Conclusion

As a meeting point between Asia and Australia with rich biodiversity, Wallacea has attracted much attention from researchers. Studies regarding the potential of those bio-resources and their utilization are vital to achieving sustainable biomass utilization in the area. This work addresses biomass utilization in the Wallacea region aligned with Indonesian policy targets for bioenergy generation to reach the net zero emission target by 2060. Some essential points from the study can be concluded as follows:

  • As a country with the third largest tropical forest, Indonesia has enormous potential for waste forests, including in the Wallacea region. Biomass waste comes from logging activities, such as rubber residue, sawdust, wood chips, and plywood waste. A study reveals biomass potential in the Wallacia region with about 71 TWh, dominated by wood, rice, and corn.

  • Although potentially very high, biomass utilization is still relatively low. It still faces many technical and non-technical challenges. The government provides several prioritized programs and guides related to bioenergy, including (1) the utilization of waste as a source of electricity generation, (2) biofuel programs, and (3) waste utilization from agriculture, plantation, and forest land, as well as degraded land.

  • In addition, ML and optimization algorithms can be used and have advantages over conventional approaches in terms of precision and accuracy and potentially boost the use of biomass. This approach can solve problems that involve high complexity, non-linear parameters, and high-dimensional, including those related to the design of conversion processes, optimization, and intensification. They can also assist policymakers in optimum long-term planning considering energy/price forecast, demand projection, and emission-cost optimization based on selected conversion technologies.