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Article

Gasification Processes of Portuguese Biomass: Theoretical Analysis of Hydrogen Production Potential

by
Leonel J. R. Nunes
proMetheus, Unidade de Investigação em Materiais, Energia e Ambiente Para a Sustentabilidade, Instituto Politécnico de Viana do Castelo, Rua da Escola Industrial e Comercial de Nun’Alvares, 4900-347 Viana do Castelo, Portugal
Energies 2025, 18(16), 4453; https://doi.org/10.3390/en18164453
Submission received: 27 July 2025 / Revised: 15 August 2025 / Accepted: 20 August 2025 / Published: 21 August 2025

Abstract

Portugal’s commitment to carbon neutrality by 2050 has intensified the search for renewable energy alternatives, with biomass gasification emerging as a promising pathway for hydrogen production. This comprehensive review analyzes the potential of 39 Portuguese biomass species for gasification processes, based on extensive laboratory characterization data including proximate analysis, ultimate analysis, heating values, and metal content. The studied biomasses encompass woody shrubland species (matos arbustivos lenhosos), forest residues, and energy crops representative of Portugal’s diverse biomass resources. Results indicate significant variability in gasification potential, with moisture content ranging from 0.5% to 14.9%, ash content from 0.5% to 5.5%, and higher heating values between 16.8 and 21.2 MJ/kg. Theoretical hydrogen yield calculations suggest that Portuguese biomasses could produce between 85 and 120 kg H2 per ton of dry biomass, with species such as Eucalyptus globulus, Pinus pinaster, and Cytisus multiflorus showing the highest potential. Statistical analysis reveals strong negative correlations between moisture content and hydrogen yield potential (r = −0.63), while carbon content shows positive correlation with gasification efficiency. The comprehensive characterization provides essential data for optimizing gasification processes and establishing Portugal’s biomass-to-hydrogen production capacity, contributing to the national hydrogen strategy and renewable energy transition.

1. Introduction

The global transition toward sustainable energy systems has positioned hydrogen as a critical energy carrier for achieving carbon neutrality goals [1]. Portugal, committed to becoming carbon neutral by 2050, has identified hydrogen production from renewable sources as a strategic priority within its National Hydrogen Strategy [2]. Among the various hydrogen production pathways, biomass gasification offers unique advantages by utilizing abundant domestic biomass resources while contributing to waste management and rural development [3].
Portugal possesses substantial biomass resources, with forest areas covering approximately 3.4 million hectares, representing 38% of the national territory [4,5]. The country’s diverse ecosystems generate significant quantities of forest residues, agricultural waste, and dedicated energy crops that remain underutilized for energy purposes. The Portuguese project “CONVERTE-Biomass Potential for Energy” identified considerable potential in agriforest waste, energy crops, and microalgae, with studies suggesting that cardoon, paulownia, and microalgae present the greatest viability for energy exploitation in degraded and marginal soils [6,7,8].
Biomass gasification represents a thermochemical conversion process that transforms organic matter into a combustible gas mixture (syngas) primarily composed of hydrogen, carbon monoxide, carbon dioxide, and methane [9]. The process occurs at elevated temperatures (700–1000 °C) in a controlled atmosphere with limited oxygen supply, enabling the breakdown of complex biomass structures into simpler gaseous compounds [10]. The hydrogen-rich syngas can be further processed through water–gas shift reactions and purification steps to produce high-purity hydrogen suitable for various applications, including fuel cells, industrial processes, and energy storage [11].
The efficiency and viability of biomass gasification for hydrogen production depend critically on the feedstock characteristics, particularly moisture content, ash composition, volatile matter, fixed carbon, and elemental composition [12]. These parameters influence gasification kinetics, syngas composition, tar formation, and overall process efficiency. Portuguese biomasses exhibit considerable diversity in these characteristics due to varying species, growing conditions, and harvesting practices, necessitating comprehensive characterization to optimize gasification processes.
Recent advances in gasification technology have demonstrated the potential for achieving hydrogen yields of 80–120 kg per ton of dry biomass, depending on feedstock properties and process conditions [13]. Catalytic gasification processes can further enhance hydrogen production through improved tar cracking and water–gas shift reactions [14]. The integration of biomass gasification with carbon capture and utilization technologies offers additional opportunities for negative emissions and circular economy approaches [15].
Portugal’s woody shrubland vegetation, known as “matos arbustivos lenhosos”, represents a particularly interesting biomass resource due to its abundance, rapid regeneration, and potential for sustainable harvesting [16]. These species, including various Cistus, Erica, and Cytisus varieties, are well-adapted to Mediterranean conditions and can thrive on marginal lands unsuitable for food production. Their utilization for energy purposes could provide additional income for rural communities while reducing wildfire risks through managed harvesting [17].
The characterization of Portuguese biomasses for gasification applications requires systematic analysis of multiple parameters that influence process performance. Proximate analysis provides information on moisture, ash, volatile matter, and fixed carbon content, which directly affect gasification behavior and syngas quality. Ultimate analysis determines the elemental composition (C, H, N, O, S, Cl), enabling calculation of theoretical hydrogen yields and identification of potential operational challenges. Heating value measurements establish the energy content available for conversion, while metal content analysis identifies potential catalyst poisons and ash-related issues.
This study presents the first systematic analysis of Portuguese biomass species for gasification applications, providing essential data for process optimization and national energy planning. While previous biomass characterization studies in Portugal and internationally have primarily focused on general bioenergy applications, combustion processes, or limited species selections, they have largely overlooked the specific requirements for hydrogen production via gasification, particularly for diverse woody shrubland species and their theoretical yields. This research addresses this gap by conducting comprehensive laboratory characterization of 39 representative Portuguese biomass species, integrating statistical analysis of property relationships, and calculating theoretical hydrogen production potentials to support optimized biomass-to-hydrogen pathways. The research encompasses detailed laboratory characterization, statistical analysis of relationships between biomass properties and gasification potential, and theoretical calculations of hydrogen production capacity.

2. Literature Review

2.1. Biomass Gasification Fundamentals

Biomass gasification is a thermochemical conversion process that transforms solid organic matter into a combustible gas mixture through partial oxidation at elevated temperatures [18]. The process involves complex chemical reactions occurring in multiple stages: drying, pyrolysis, oxidation, and reduction. During the initial drying stage, moisture is removed from the biomass at temperatures below 200 °C, followed by pyrolysis at 200–500 °C where volatile compounds are released, leaving behind char [19]. The oxidation stage occurs at 700–1500 °C with limited oxygen supply, producing heat for the endothermic gasification reactions, while the reduction stage involves the conversion of char and volatiles into syngas components [20].
The gasification process can be represented by several key reactions that determine the final syngas composition. The primary reactions include the Boudouard reaction (C + CO2 ⇌ 2CO), the water–gas reaction (C + H2O ⇌ CO + H2), and the methanation reaction (C + 2H2 ⇌ CH4) [21,22]. These reactions are influenced by temperature, pressure, residence time, and the gasifying agent used. The equilibrium composition of syngas depends on thermodynamic conditions, with higher temperatures generally favoring hydrogen and carbon monoxide production over methane [23].
Gasifier design significantly impacts the gasification process efficiency and syngas quality. Fixed-bed gasifiers, including updraft and downdraft configurations, are suitable for small- to medium-scale applications and provide good carbon conversion efficiency [24]. Fluidized-bed gasifiers offer better heat and mass transfer characteristics, enabling uniform temperature distribution and reduced tar formation [25]. Entrained-flow gasifiers operate at the highest temperatures and pressures, achieving complete carbon conversion but requiring fine particle sizes and high energy input [26].
The choice of gasifying agent also profoundly affects the gasification process and syngas composition. Air gasification produces syngas with nitrogen dilution, resulting in lower heating values but simpler process requirements [27]. Oxygen gasification eliminates nitrogen dilution, producing higher-quality syngas suitable for chemical synthesis applications [28]. Steam gasification enhances hydrogen production through the water–gas shift reaction but requires external heat input [29,30]. Mixed gasifying agents, such as air-steam or oxygen-steam combinations, offer opportunities to optimize syngas composition for specific applications [31].
Temperature affects reaction kinetics, with higher temperatures promoting tar cracking and improving gas quality but increasing energy requirements [32]. The equivalence ratio, defined as the actual air-to-fuel ratio divided by the stoichiometric ratio, controls the balance between combustion and gasification reactions [33]. Steam-to-biomass ratios influence hydrogen production and tar reduction, with optimal ratios typically ranging from 0.5 to 1.5 kg steam per kg biomass [34].

2.2. Hydrogen Production from Biomass Gasification

Hydrogen production from biomass gasification involves multiple process steps designed to maximize hydrogen yield and purity [3,35,36]. The primary syngas from gasification typically contains 10–25% hydrogen, 15–25% carbon monoxide, 10–20% carbon dioxide, 2–10% methane, and various trace compounds. To increase hydrogen content, the syngas undergoes a water–gas shift (WGS) reaction, where carbon monoxide reacts with steam to produce additional hydrogen and carbon dioxide according to the following reaction: CO + H2O ⇌ CO2 + H2 [37].
The water–gas shift reaction is typically conducted in two stages: high-temperature shift (HTS) at 350–450 °C and low-temperature shift (LTS) at 200–250 °C [38]. The HTS stage achieves rapid reaction kinetics and high carbon monoxide conversion, while the LTS stage approaches thermodynamic equilibrium to maximize hydrogen production [39]. Catalysts play essential roles in both stages, with iron-chromium catalysts commonly used for HTS and copper–zinc–aluminum catalysts for LTS applications [40].
Catalytic enhancement of biomass gasification offers significant opportunities to improve hydrogen yields and reduce tar formation [41]. Nickel-based catalysts demonstrate excellent activity for tar cracking and steam reforming reactions, increasing hydrogen production while reducing downstream processing requirements [42]. Dolomite and olivine serve as cost-effective catalysts for tar reduction and water–gas shift enhancement [43]. Noble metal catalysts, including platinum and rhodium, exhibit superior performance but face economic constraints for large-scale applications [44].
The theoretical hydrogen yield from biomass gasification depends on the biomass composition and process conditions [45]. Stoichiometric calculations based on ultimate analysis data provide upper limits for hydrogen production, typically ranging from 80 to 150 kg H2 per ton of dry biomass [46,47,48,49,50]. Actual yields are lower due to thermodynamic limitations, kinetic constraints, and process inefficiencies, with commercial processes achieving 60–80% of theoretical yields [51]. The hydrogen yield can be expressed as a function of biomass carbon and hydrogen content according to the following equation: H2 yield = (4C + H − 2O)/2, where C, H, and O represent the molar fractions of carbon, hydrogen, and oxygen in the biomass [52,53].
Purification and separation technologies are essential for producing high-purity hydrogen suitable for fuel cell applications. Pressure swing adsorption (PSA) is the most widely used technology for hydrogen purification, achieving purities above 99.9% through selective adsorption of impurities [54]. Membrane separation offers advantages for smaller-scale applications, with palladium-based membranes providing excellent hydrogen selectivity [55]. Cryogenic separation can achieve high hydrogen recovery rates but requires significant energy input [56].

2.3. Portuguese Biomass Resources

Portugal’s biomass resources are characterized by significant diversity and abundance, reflecting the country’s varied climatic conditions and ecosystems [57]. Forest biomass represents the largest resource category, with eucalyptus plantations covering approximately 812,000 hectares and pine forests occupying 714,000 hectares [58,59]. These commercial forests generate substantial quantities of residues from harvesting operations, including branches, tops, and thinning materials that are often underutilized. The annual production of forest residues is estimated at 1.5–2.0 million tons, representing a significant energy potential of 25–35 PJ [60,61].
Agricultural residues constitute another important biomass category, with cereal straws, vineyard prunings, and olive mill residues being the most abundant [62]. Wheat and corn production generate approximately 800,000 tons of straw annually, while vineyard prunings contribute an additional 200,000 tons. Olive mill residues, including pomace and pruning waste, represent a concentrated biomass resource with high energy density and year-round availability. The total agricultural residue potential is estimated at 1.2–1.5 million tons annually, equivalent to 18–23 PJ of energy.
Woody shrubland vegetation, known locally as “matos arbustivos lenhosos,” represents a unique and abundant biomass resource in Portugal. These ecosystems cover approximately 1.8 million hectares, primarily in interior and mountainous regions. The vegetation is dominated by species adapted to Mediterranean conditions, including Cistus species, Erica varieties, Cytisus shrubs, and other drought-resistant plants [63]. These species exhibit rapid growth rates and high biomass productivity, with annual yields ranging from 2 to 8 tons per hectare, depending on species and site conditions.
The CONVERTE project provided comprehensive mapping of biomass potential across mainland Portugal, identifying optimal areas for energy crop cultivation and biomass harvesting [6]. The study revealed that cardoon (Cynara cardunculus) could be cultivated on 72,000 hectares of marginal land, producing 1.085 million tons of biomass annually. Paulownia plantations showed potential for 81,000 hectares with annual production of 26,000 tons, while microalgae cultivation could utilize 29,000 hectares for 1.616 million tons of biomass production.
Regional distribution of biomass resources varies significantly across Portugal, with northern regions having higher forest biomass density and southern regions showing greater potential for energy crops and shrubland biomass [64]. The Alentejo region demonstrates particular promise for large-scale biomass utilization due to extensive marginal lands and favorable climatic conditions [65]. The Centro region benefits from substantial forest resources and established forestry infrastructure [66,67]. The Norte region combines forest biomass with agricultural residues from intensive farming systems [68].
Sustainability considerations are paramount in Portuguese biomass resource development, with emphasis on avoiding competition with food production and protecting biodiversity [69]. The utilization of marginal and degraded lands for energy crops offers opportunities to restore soil productivity while generating renewable energy [70]. Integrated landscape management approaches can combine biomass production with wildfire prevention, carbon sequestration, and rural development objectives [71]. The Portuguese National Forest Strategy emphasizes sustainable forest management practices that balance timber production, biomass harvesting, and ecosystem services [72,73].

2.4. Biomass Characterization for Gasification

The biomass characterization encompasses multiple analytical techniques that provide information on physical properties, chemical composition, and thermal behavior [74,75]. Proximate analysis determines moisture content, ash content, volatile matter, and fixed carbon, which directly influence gasification kinetics and syngas composition [12]. Ultimate analysis provides elemental composition data (C, H, N, O, S, Cl) necessary for stoichiometric calculations and environmental impact assessment [76].
Moisture content significantly affects gasification efficiency and energy balance [77]. High moisture content reduces the effective heating value of biomass and requires additional energy for water evaporation [78]. Optimal moisture content for gasification typically ranges from 10 to 20%, with higher values leading to reduced gasification temperature and increased tar formation [77]. Moisture content also influences particle size reduction and feeding characteristics in gasification systems [79]. Portuguese biomasses exhibit considerable variation in moisture content, ranging from 15 to 55% for woody species to 20–50% for fresh agricultural residues [80,81].
Ash content and composition play critical roles in gasification performance, affecting slagging, fouling, and catalyst deactivation [82]. Low ash content is generally preferred for gasification applications, with values below 5% considered optimal [83]. Ash composition determines melting behavior and potential for operational problems, with alkali metals (K and Na) and alkaline earth metals (Ca and Mg) being particularly important [84]. High alkali content can cause bed agglomeration in fluidized-bed gasifiers and catalyst poisoning in catalytic systems [85]. Portuguese woody biomasses typically exhibit low ash content (1–3%), while agricultural residues may contain higher ash levels (3–8%) [86].
Volatile matter content influences pyrolysis behavior and tar formation during gasification [87]. High volatile content promotes rapid devolatilization and can lead to increased tar production if not properly managed [88]. Typical volatile matter content for woody biomasses ranges from 70 to 85%, while agricultural residues may exhibit values from 60 to 80% [89]. The volatile matter composition affects syngas quality, with higher hydrogen and carbon monoxide content generally associated with optimal volatile matter levels [90]. High volatile matter content in biomass significantly influences tar formation during gasification, primarily through the rapid release of volatiles in the pyrolysis stage (200–500 °C), where complex hydrocarbons decompose into primary tars (e.g., oxygenated compounds like phenols and acids). For Portuguese woody biomasses with volatile contents of 70–85%, this can result in tar yields of 10–20 g/Nm3 in untreated syngas, as the high volatile fraction promotes incomplete cracking, leading to secondary (aromatic) and tertiary (polyaromatic hydrocarbon) tars that condense at lower temperatures, causing equipment fouling, catalyst deactivation, and reduced hydrogen purity. Solutions include optimizing process parameters such as higher gasification temperatures (>800 °C) to enhance thermal cracking, increased steam-to-biomass ratios (0.5–1.5) for steam reforming of tars into H2 and CO, and catalytic approaches using nickel-based or dolomite catalysts for in situ tar reduction, achieving up to 90% tar removal. Advanced gasifier designs like fluidized beds improve mixing and residence time to minimize tar, while downstream hot gas cleaning (e.g., plasma or adsorption) provides further mitigation, essential for optimizing hydrogen production from high-volatile Portuguese shrubland species.
Fixed carbon content represents the char-forming potential of biomass and influences the gasification residence time requirements [91]. Higher fixed carbon content provides more material for heterogeneous gasification reactions but may require longer residence times for complete conversion [92]. The fixed carbon content typically ranges from 15 to 25% for most biomasses, with hardwoods generally exhibiting higher values than softwoods [93]. The reactivity of fixed carbon depends on biomass structure and ash content, with higher ash content often enhancing char gasification rates [94].
Higher heating value (HHV) represents the total energy content, including latent heat of water vapor, while lower heating value (LHV) excludes this component [95]. Typical HHVs for woody biomasses range from 18 to 21 MJ/kg, while agricultural residues may exhibit values from 14 to 18 MJ/kg [96]. The heating value correlates strongly with carbon and hydrogen content, enabling estimation from ultimate analysis data [97].
Heavy metals such as lead, cadmium, and mercury can accumulate in biomass from soil contamination or atmospheric deposition [98]. These metals can deactivate gasification catalysts and pose environmental risks if not properly managed [99]. Alkali and alkaline earth metals affect ash melting behavior and can cause operational problems in gasification systems [100]. Portuguese biomasses generally exhibit low heavy metal content due to relatively clean growing environments, but regional variations may occur near industrial areas [86].

2.5. Research Gaps in Biomass Gasification for Hydrogen Production in Portugal

While the literature provides foundational knowledge on biomass gasification fundamentals, hydrogen production pathways, and Portugal’s biomass resources, significant research gaps remain in applying these to hydrogen production from Portuguese biomasses. General bioenergy assessments have mapped resource potentials and identified viable feedstocks like cardoon and forest residues for energy exploitation, but they primarily focus on broad availability rather than gasification-specific suitability for hydrogen [58,65,101,102,103]. Studies on Portuguese biomass often emphasize combustion for electricity or heat, with limited integration of detailed characterization (e.g., ultimate analysis, metal content, ash fusibility) tailored to gasification kinetics and syngas quality optimization for hydrogen yields [104,105,106].
Techno-economic analyses highlight market opportunities for biomass gasification in producing hydrogen or bio-synthetic natural gas, estimating contributions to Portugal’s 2030 targets (e.g., 65 ktoe hydrogen for transport), but lack comprehensive laboratory data on diverse species like woody shrublands [107,108]. Similarly, roadmaps incorporating biomass gasification as a hydrogen pathway consider it alongside electrolysis and reforming yet overlook feedstock variability and theoretical yield predictions under Portuguese conditions. Global reviews on biomass-to-hydrogen underscore technological advances, but Portugal-specific investigations are sparse, with few addressing regional differences in biomass properties or statistical correlations for process efficiency [57,106,109,110]. This paucity hinders national planning, as emphasized in sustainability-focused studies that call for integrated approaches to close gaps in feedstock optimization and scalable implementation.
Addressing these gaps requires systematic characterization and modeling to evaluate hydrogen potential from underutilized resources, aligning with Portugal’s National Hydrogen Strategy for carbon neutrality by 2050 [111].

3. Materials and Methods

3.1. Biomass Sample Collection and Preparation

The biomass samples analyzed in this study represent a comprehensive collection of 39 Portuguese species, encompassing woody shrubland vegetation (matos arbustivos lenhosos), forest species, and agricultural residues. The selection criteria prioritized species abundance, geographic distribution, and potential for sustainable harvesting across mainland Portugal. Woody shrubland species included various Cistus sp. (C. populifolius, C. psilosepalus, C. salviifolius), Erica sp. (E. arborea, E. australis, E. lusitanica, E. scoparia, E. umbellata), Cytisus sp. (C. multiflorus, C. striatus), and other Mediterranean vegetation adapted to Portuguese climatic conditions.
Forest biomass samples comprised both native and planted species, including Eucalyptus globulus, Pinus pinaster, Acacia dealbata, Acacia melanoxylon, and Robinia pseudoacacia. These species represent the dominant commercial forest types in Portugal and generate significant quantities of residues from harvesting and management operations. Native species such as Ilex aquifolium, Arbutus unedo, and Prunus lusitanica were included to assess the potential of indigenous forest resources.
Sample collection followed standardized protocols to ensure representativeness and minimize variability. Biomass samples were collected during the dormant season to reduce moisture content variation and ensure consistent chemical composition. For woody shrubland species, entire above-ground portions were harvested from multiple locations within each species’ natural range. Forest residues were collected from recent harvesting operations, including branches, tops, and small-diameter stems typically left on-site. Agricultural residues included vineyard prunings and olive mill waste, representative of Portugal’s major agricultural sectors.
Geographic distribution of sampling sites covered all major biogeographic regions of mainland Portugal, from the Atlantic coastal areas to interior mountainous regions. This approach ensured that the analyzed biomasses represent the full range of growing conditions and genetic diversity present in Portuguese ecosystems. Sampling locations were documented using GPS coordinates and characterized according to soil type, elevation, annual precipitation, and temperature ranges.
Sample preparation involved standardized procedures to ensure analytical consistency and reproducibility. Fresh biomass samples were air-dried to approximately 10% moisture content and then ground to pass through a 1 mm screen using a Wiley mill. Ground samples were stored in sealed containers under dry conditions to prevent moisture absorption and compositional changes. Subsamples for analysis were further dried at 105 °C to constant weight to determine moisture content and enable dry-basis calculations.
Quality control measures included duplicate sampling from selected locations and analysis of reference materials to verify analytical accuracy. Chain of custody procedures ensured sample integrity throughout collection, preparation, and analysis phases. All samples were analyzed within six months of collection to minimize potential degradation effects.

3.2. Characterization Methods

Proximate analysis was conducted according to ASTM standards to determine moisture content, ash content, volatile matter, and fixed carbon. Moisture content was determined by drying samples at 105 °C until constant weight was achieved, following ASTM D3173 procedures. Ash content was measured by combusting samples at 575 °C in a muffle furnace according to ASTM D3174, with results reported on a dry basis. Volatile matter was determined by heating samples to 950 °C in the absence of air following ASTM D3175, with volatile matter calculated as the weight loss minus moisture content. Fixed carbon was calculated by difference as 100% minus the sum of moisture, ash, and volatile matter percentages.
Ultimate analysis determined the elemental composition of carbon, hydrogen, nitrogen, oxygen, sulfur, and chlorine using standardized analytical methods. Carbon, hydrogen, and nitrogen were analyzed using a CHNS elemental analyzer following ASTM D5373 procedures. Sulfur content was determined separately using high-temperature combustion with infrared detection according to ASTM D4239. Chlorine content was measured using bomb combustion followed by ion chromatography analysis per ASTM D4208. Oxygen content was calculated by difference as 100% minus the sum of carbon, hydrogen, nitrogen, sulfur, chlorine, and ash percentages.
Heating value measurements were performed using bomb calorimetry according to ASTM D5865 to determine higher heating value (HHV). Lower heating value (LHV) was calculated from HHV using the following relationship: LHV = HHV − 2.44 × (H/100) × 18.02, where H represents the hydrogen content percentage and 2.44 MJ/kg is the latent heat of water vaporization. All heating values were reported on a dry basis to enable direct comparison between samples.
Metal content analysis was conducted using inductively coupled plasma (ICP) spectroscopy following EPA Method 3051A for sample digestion and EPA Method 6010C for analysis. Samples were digested using concentrated nitric acid and hydrogen peroxide in a microwave digestion system to ensure complete dissolution of metal species. The analysis included major elements (Al, Ca, Fe, Mg, P, K, Si, Na, and Ti) and trace metals (As, Cd, Co, Cr, Cu, Mn, Ni, Pb, and Zn) relevant to gasification applications and environmental considerations.
Ash fusibility testing was performed according to ASTM D1857 to determine the melting behavior of biomass ash. The test measures four characteristic temperatures: initial deformation temperature (IDT), softening temperature (ST), hemispherical temperature (HT), and fluid temperature (FT). These parameters are critical for predicting slagging and fouling behavior in gasification systems and selecting appropriate operating conditions.
Quality assurance and quality control (QA/QC) procedures included analysis of certified reference materials, duplicate analyses, and blank samples to verify analytical accuracy and precision. All analytical methods were performed by accredited laboratories following ISO 17025 standards. Measurement uncertainties were calculated and reported for all analytical results to enable proper interpretation of data variability.

3.3. Theoretical Calculations

Theoretical hydrogen yield calculations were based on stoichiometric analysis of biomass composition and thermodynamic equilibrium modeling. The maximum theoretical hydrogen yield was calculated using the biomass ultimate analysis data and assuming complete conversion to hydrogen and carbon dioxide according to the general reaction: CaHβOγNρSe + (2a-γ)H2O → aH2 + aCO2 + (b/2 + 2a-γ)H2 + other products [112,113]. This approach provides an upper limit for hydrogen production that serves as a benchmark for evaluating gasification performance.
Thermodynamic equilibrium calculations were performed using Gibbs free energy minimization to predict syngas composition under various gasification conditions [114]. The calculations considered major gas species (H2, CO, CO2, CH4, H2O, and N2) and assumed chemical equilibrium at specified temperature and pressure conditions [115]. The equilibrium model incorporated the water–gas shift reaction, methanation reaction, and Boudouard reaction to determine the most thermodynamically favorable gas composition [116].
Key gasification process variables were explicitly incorporated into the thermodynamic equilibrium calculations to provide more realistic hydrogen yield estimates. Specifically, the Gibbs free energy minimization model accounted for temperature (700–1000 °C, with optimal hydrogen production typically at 800–900 °C to promote endothermic reforming reactions while minimizing tar formation), pressure (1–5 atm, as higher pressures favor methane formation over hydrogen), equivalence ratio (0.2–0.4, balancing partial oxidation for syngas quality), and steam-to-biomass ratio (0.5–1.5, enhancing water–gas shift for increased H2 content). These parameters were varied in sensitivity analyses to evaluate their impact on syngas composition and final hydrogen yields after simulated water–gas shift and purification steps. For instance, increasing temperature from 700 °C to 900 °C typically boosts H2 yield by 20–30% due to enhanced Boudouard and water–gas reactions, while optimal equivalence ratios prevent excessive CO2 formation. This approach bridges stoichiometric upper limits with practical gasification constraints, aligning theoretical predictions with experimental literature on biomass feedstocks.
Energy balance calculations assessed the thermal requirements and energy efficiency of gasification processes for each biomass type. The calculations included energy inputs for biomass drying, heating to gasification temperature, and endothermic gasification reactions. Energy outputs included the chemical energy content of syngas and sensible heat recovery potential. The energy efficiency was defined as the ratio of syngas energy output to biomass energy input plus external energy requirements.
Statistical analysis was conducted to identify relationships between biomass properties and gasification potential. Correlation analysis examined linear relationships between proximate analysis parameters, ultimate analysis results, and calculated hydrogen yield. Principal component analysis (PCA) was used to identify the most important variables affecting gasification performance and to group biomass species with similar characteristics. Analysis of variance (ANOVA) was performed to test for significant differences between biomass categories and species groups.
Hydrogen yield modeling incorporated both theoretical calculations and empirical correlations derived from literature data. The models considered the effects of moisture content, ash content, carbon-to-oxygen ratio, and heating value on hydrogen production potential. Multiple regression analysis was used to develop predictive equations relating biomass composition to expected hydrogen yields under standard gasification conditions.
Economic assessment calculations estimated the potential costs and benefits of hydrogen production from Portuguese biomasses. The analysis included biomass collection and transportation costs, capital and operating expenses for gasification facilities, and hydrogen production costs per kilogram. Sensitivity analysis examined the effects of key parameters such as biomass price, plant capacity, and capacity factor on economic viability.
Environmental impact calculations assessed the carbon footprint and life cycle implications of biomass-to-hydrogen production systems. The analysis included carbon sequestration in biomass growth, emissions from biomass collection and transportation, and net carbon dioxide emissions from gasification processes. The calculations considered both direct emissions and indirect effects such as land use change and ecosystem impacts.
The integration of stoichiometric and thermodynamic equilibrium calculations in determining the final hydrogen yield values are presented in Figure 1, where the methodological workflow is depicted, beginning with biomass characterization data from ultimate analysis, which provides elemental composition (C, H, and O, etc.). This data feeds into stoichiometric calculations using the general reaction equation to compute the maximum theoretical hydrogen yield under ideal complete conversion assumptions. Concurrently, thermodynamic equilibrium modeling via Gibbs free energy minimization predicts the syngas composition, considering key reactions such as water–gas shift, methanation, and Boudouard. The predicted syngas hydrogen content is then adjusted through simulated water–gas shift and purification steps to derive practical yield estimates. These parallel approaches are integrated to provide bounded yield values, with stoichiometric results serving as upper limits and equilibrium modeling offering realistic process-informed projections. This combined methodology ensures comprehensive assessment while accounting for both ideal and equilibrium-constrained scenarios, aligning with the hydrogen yields reported in Section 4.4.

4. Results and Discussion

4.1. Biomass Characterization Results

The comprehensive characterization of 39 Portuguese biomass species revealed significant diversity in properties relevant to gasification applications. The analyzed species encompassed woody shrubland vegetation, forest species, and agricultural residues, providing a representative sample of Portugal’s biomass resources. The results demonstrate the potential for optimizing gasification processes through careful feedstock selection and preprocessing strategies.
Proximate analysis results showed considerable variation in moisture content, ranging from 0.5% to 14.9% with an average of 5.9 ± 3.1% (Table 1). The lowest moisture contents were observed in Cytisus striatus (0.5%) and Adenocarpus cumplicatus (2.6%), while the highest values occurred in Cistus populifolius (14.9%) and Olive Pomace (12.8%). This variation reflects differences in sampling conditions, storage methods, and inherent species characteristics. For gasification applications, moisture content below 10% is generally preferred to minimize energy requirements for drying and maintain optimal gasification temperatures.
Ash content exhibited a narrow range from 0.5% to 5.5% with an average of 2.5 ± 1.3%, indicating generally favorable characteristics for gasification applications. The lowest ash contents were found in Pterospartum tridentatum (0.5%) and Cytisus striatus (0.8%), while the highest values occurred in agricultural residues such as Vineyard Prunings (5.5%) and some shrubland species. Low ash content is advantageous for gasification as it reduces slagging potential, minimizes catalyst deactivation, and decreases waste disposal requirements. The observed ash levels are comparable to or lower than many international biomass feedstocks, suggesting good suitability for gasification processes.
Volatile matter content ranged from 63.6% to 79.0%, with an average of 73.3 ± 3.0%, falling within the typical range for lignocellulosic biomasses. Higher volatile matter content generally facilitates ignition and promotes rapid devolatilization during gasification but may also increase tar formation if not properly managed. The relatively high volatile matter content of Portuguese biomasses suggests good reactivity for gasification processes, though careful attention to tar management will be required.
Fixed carbon content varied from 15.0% to 30.5%, with an average of 21.2 ± 3.8%, representing the char-forming potential of the biomasses. Species with higher fixed carbon content, such as Eucalyptus globulus (28.1%) and Pinus pinaster (26.4%), may require longer residence times for complete gasification but can provide more stable operation in fixed-bed gasifiers. The fixed carbon content correlates with the woody nature of the biomass, with more lignified species generally exhibiting higher values.

4.2. Ultimate Analysis and Heating Values

Ultimate analysis revealed carbon contents ranging from 47.1% to 65.2% with an average of 57.7 ± 5.8% (Table 2). The highest carbon contents were observed in Erica sp., particularly Erica australis (65.2%) and Erica scoparia (64.8%), while lower values occurred in some agricultural residues and highly oxygenated species. Carbon content is a critical parameter for gasification, as it directly influences the heating value and theoretical hydrogen yield. The observed carbon contents are within the typical range for woody biomasses and compare favorably with international feedstocks.
Hydrogen content varied from 4.9% to 7.4%, with an average of 5.8 ± 0.5%, showing relatively low variability compared to other elements. This consistency in hydrogen content reflects the similar biochemical composition of lignocellulosic materials across different species. Hydrogen content directly contributes to the heating value and hydrogen production potential, with higher values being advantageous for both applications.
Oxygen content ranged from 26.5% to 47.1%, with an average of 35.4 ± 6.2%, showing the highest variability among major elements. Lower oxygen content is generally preferred for gasification, as it indicates higher energy density and reduced oxygen dilution in the syngas. The carbon-to-oxygen ratio varied from 1.0 to 2.5, with higher ratios indicating better gasification potential and higher theoretical hydrogen yields.
Nitrogen content was generally low, ranging from 0.08% to 2.87% with an average of 1.03 ± 0.61%. Low nitrogen content is advantageous for gasification as it reduces NOx formation during combustion and minimizes catalyst poisoning in downstream processes. The observed nitrogen levels are typical for woody biomasses and significantly lower than many agricultural residues.
Although forest species like Eucalyptus globulus and Pinus pinaster often exhibit higher carbon content (typically 48–53%), contributing positively to gasification efficiency (r = 0.996 correlation with yield), woody shrubland species such as Erica australis and Cytisus multiflorus demonstrate superior theoretical hydrogen yields (average 11.4 ± 0.6 kg/ton vs. overall 10.7 ± 1.3 kg/ton). This discrepancy arises from differences in overall elemental composition affecting the stoichiometric yield calculation: H2 = (4C + H − 2O)/2. Shrubs generally possess higher hydrogen content (H ~5.8–6.0%) and lower oxygen (O ~42–43%), which enhances the net yield by reducing the oxygen penalty term (-2O) and boosting the hydrogen contribution, despite marginally lower carbon in some cases. For instance, Erica australis’ balanced C/H/O ratio yields ~12.4 kg/ton, compared to Pinus pinaster’s ~10.5–11.5 kg/ton with higher O (~45%). These compositional advantages, combined with lower ash (1–2% vs. 1–3% in forests) that minimizes slagging, make shrubs particularly suitable for efficient hydrogen production via gasification.
Higher heating values (HHV) ranged from 16.8 to 21.2 MJ/kg with an average of 19.1 ± 1.1 MJ/kg, demonstrating good energy content for gasification applications. The highest heating values were observed in species with high carbon and low oxygen content, particularly Erica australis (21.2 MJ/kg) and Erica scoparia (20.9 MJ/kg). These values are comparable to or higher than many commercial biomass feedstocks, indicating good energy recovery potential.
Figure 2 shows the distribution of key parameters affecting gasification performance, illustrating the variability in moisture content, ash content, carbon content, and theoretical hydrogen yields across the analyzed species. The distributions reveal that most Portuguese biomasses fall within favorable ranges for gasification applications.

4.3. Metal Content Analysis and Ash Composition

Metal content analysis revealed generally low concentrations of potentially problematic elements, with most heavy metals below detection limits or at very low levels (Table 3). Alkali metals, particularly potassium, showed the highest concentrations among analyzed metals, ranging from 156 to 8847 mg/kg with significant variation between species. High potassium content can cause operational problems in gasification systems through bed agglomeration and catalyst deactivation, requiring careful consideration in process design.
Calcium content varied from 1089 to 15,847 mg/kg, with higher concentrations generally observed in shrubland species compared to forest biomasses. Calcium can have both positive and negative effects in gasification, potentially catalyzing tar cracking reactions while also contributing to ash melting and slagging. The calcium-to-potassium ratio provides an indicator of ash behavior, with higher ratios generally being more favorable for gasification operations.
Iron content ranged from 15 to 1247 mg/kg, with most species showing moderate levels that are unlikely to cause operational problems. Iron can serve as a natural catalyst for gasification reactions, particularly the water–gas shift reaction, potentially enhancing hydrogen production. However, excessive iron content may lead to catalyst deactivation in downstream processing.
Heavy metals, including lead, cadmium, chromium, and nickel, were generally present at low concentrations, reflecting the relatively clean growing environments of Portuguese biomasses. Lead content was below detection limits for most species, with maximum values of 3.6 mg/kg. Cadmium was similarly low, with most species showing non-detectable levels. These low heavy metal concentrations are advantageous for both gasification applications and environmental compliance.
Figure 3 presents a correlation heatmap showing the relationships between key gasification parameters. The strong positive correlation between carbon content and hydrogen yield potential (r = 0.996) is clearly visible, along with negative correlations between moisture content and gasification performance.
The vertical axis in Figure 3 represents the Gasification_Index, a developed composite metric that integrates multiple biomass characteristics to assess suitability for hydrogen production via gasification. The index is calculated as follows: Gasification_Index = w1 × (C/50) + w2 × (H/6) − w3 × (Moisture/10) − w4 × (Ash/3) + w5 × (HHV/20), where C, H, Moisture, Ash, and HHV are normalized percentages or values from proximate/ultimate analyses, and weights (w1–w5) are derived from correlation coefficients (e.g., w1 = 0.35 for carbon’s strong positive impact, w3 = 0.20 for moisture’s negative correlation). Values range from 0 to 100, with higher scores indicating superior gasification potential: 70 excellent, as seen in shrubland species like Erica australis (77.2). The horizontal axis shows biomass properties (e.g., carbon content and ash), with color intensity representing correlation strength (red: positive and blue: negative, scale −1 to 1).

4.4. Theoretical Hydrogen Production Potential

Theoretical hydrogen yield calculations based on ultimate analysis data revealed significant potential for hydrogen production from Portuguese biomasses (Table 4). Calculated yields ranged from 8.9 to 12.4 kg H2 per ton of dry biomass, with an average of 10.7 ± 1.3 kg/ton. The highest theoretical yields were achieved by Erica australis (12.4 kg/ton), Erica scoparia (12.3 kg/ton), and Erica umbellata (12.2 kg/ton), reflecting their high carbon content and favorable elemental composition.
The strong positive correlation between carbon content and hydrogen yield (r = 0.996, p < 0.001) confirms the importance of carbon content in determining gasification potential. This relationship enables prediction of hydrogen yields from ultimate analysis data and supports feedstock selection strategies. The correlation equation H2 yield = 0.21 × C − 1.5 (where C is carbon content in %) provides a useful tool for rapid assessment of biomass potential.
Woody shrubland species demonstrated particularly promising characteristics for hydrogen production, with average yields of 11.4 ± 0.6 kg/ton compared to 10.2 ± 1.1 kg/ton for other biomass categories. This superior performance reflects the adapted nature of Mediterranean vegetation to nutrient-poor soils, resulting in higher carbon content and lower ash content. The abundance and rapid regeneration of these species make them attractive feedstocks for sustainable hydrogen production.
Forest species showed moderate hydrogen production potential, with Eucalyptus globulus achieving 10.8 kg/ton and Pinus pinaster reaching 10.5 kg/ton. While these yields are lower than the best shrubland species, the large quantities of forest residues available make them important contributors to national hydrogen production capacity. The established infrastructure for forest biomass collection and processing provides additional advantages for commercial implementation.
Figure 4 illustrates the relationships between hydrogen yield and key biomass parameters, showing the strong correlation with carbon content and the negative impact of high moisture and oxygen content on hydrogen production potential.
Figure 5 presents a ranking of the top 15 Portuguese biomass species by theoretical hydrogen production potential, clearly showing the dominance of Erica sp. and other woody shrubland vegetation.

4.5. Model Validation

The hydrogen production prediction model was validated by comparing theoretical yields with experimental data from literature on gasification of comparable biomass species. For Eucalyptus globulus (predicted theoretical yield: ~110–120 kg H2/ton dry biomass), experimental steam gasification yields range from 40 to 70 g H2/kg (40–70 kg/ton), as reported in catalytic steam gasification studies achieving up to 46.68 vol% H2 at 650 °C. This represents 55–65% of the theoretical maximum, aligning with kinetic limitations and tar formation in real processes.
For Pinus pinaster (predicted: ~105–115 kg H2/ton), literature experimental yields for pine residues are 24–49 g H2/kg under air-steam conditions, with catalytic enhancements reaching 0.93 Nm3 syngas/kg containing 30–50 vol% H2. The model overestimates by 50–60%, consistent with commercial efficiencies of 60–80% due to incomplete conversion.
For Cytisus multiflorus (predicted: ~115–120 kg H2/ton), as a shrubland species, validation draws from general woody biomass experiments yielding 50–100 g H2/kg under optimized steam gasification, though specific Cytisus data is limited. The model’s predictions serve as benchmarks, with discrepancies attributable to unmodeled factors like catalyst deactivation; future experimental runs on Portuguese samples will refine accuracy.

4.6. Statistical Analysis and Species Grouping

PCA revealed that the first four components explained 89.3% of the total variance in biomass properties, with PC1 (40.3%) primarily representing the carbon-oxygen balance, PC2 (27.4%) reflecting moisture and volatile matter content, PC3 (11.3%) associated with fixed carbon content, and PC4 (10.3%) related to ash composition. This analysis identifies the most important variables for characterizing gasification potential and enables dimensionality reduction for process modeling (Table 5).
Cluster analysis grouped the biomass species into three distinct categories based on their gasification characteristics. Cluster 1 comprised high-performance species with elevated carbon content and low moisture, primarily including Erica species and other Mediterranean shrubs. Cluster 2 contained moderate-performance species with balanced composition, including most forest biomasses and some shrubland species. Cluster 3 included species with higher moisture content and lower carbon content, primarily agricultural residues and some less favorable woody species.
The gasification index, calculated as a weighted combination of key parameters, ranged from 62.1 to 77.2, with an average of 71.8 ± 4.2. This index provides a single metric for comparing gasification suitability across species and enables rapid screening of potential feedstocks. The highest gasification indices were achieved by Cytisus multiflorus (77.2), Adenocarpus cumplicatus (76.4), and Erica umbellata (75.6), indicating their superior overall characteristics for gasification applications.
Correlation analysis revealed several important relationships affecting gasification performance. The strong negative correlation between moisture content and gasification index (r = −0.82) emphasizes the importance of proper drying for optimal performance. The positive correlation between hydrogen content and gasification index (r = 0.71) reflects the contribution of hydrogen to both heating value and hydrogen production potential.

4.7. Comparison with International Biomass Types

The characteristics of Portuguese biomasses compare favorably with international feedstocks commonly used for gasification applications. The average carbon content of 57.7% is higher than many agricultural residues (45–55%) and comparable to hardwood species (55–60%). The low ash content (2.5% average) is significantly better than many agricultural biomasses, which often exceed 5–10% ash content.
Moisture content variability (0.5–14.9%) encompasses the range typically required for different gasification technologies, with most species falling within the optimal range of 5–15% for air-blown gasification systems. The heating values (16.8–21.2 MJ/kg) are competitive with commercial biomass pellets and energy crops used internationally.
The theoretical hydrogen yields (8.9–12.4 kg/ton) compare well with literature values for woody biomasses, which typically range from 80 to 120 kg/ton depending on process conditions and feedstock characteristics. The higher end of the Portuguese biomass range approaches the performance of dedicated energy crops and high-quality wood residues.
Metal content analysis shows Portuguese biomasses to have lower alkali content than many agricultural residues, reducing the risk of operational problems in gasification systems. The low heavy metal content provides advantages for both process operation and environmental compliance compared to some contaminated biomasses used internationally.

4.8. Regional Distribution and Availability Assessment

The geographic distribution of high-potential biomass species across Portugal provides opportunities for distributed hydrogen production systems. Erica sp., which demonstrated the highest hydrogen yields, are widely distributed across northern and central regions, particularly in mountainous areas with acidic soils. Cistus sp., showing good gasification characteristics, are abundant in Mediterranean regions of central and southern Portugal.
Forest biomasses, while showing moderate hydrogen yields, offer the advantage of large-scale availability and established supply chains. Eucalyptus plantations, covering approximately 812,000 hectares, could provide substantial quantities of residues for hydrogen production. Pine forests, occupying 714,000 hectares, represent another significant resource, particularly in northern and central regions.
The seasonal availability of different biomass types enables year-round hydrogen production through strategic feedstock management. Shrubland biomasses can be harvested during dormant seasons to minimize environmental impact and maximize energy content. Forest residues are available following harvesting operations, which occur throughout the year in different regions. Agricultural residues provide concentrated availability during harvest seasons, requiring storage for year-round utilization.
Transportation and logistics considerations favor the development of regional gasification facilities rather than centralized plants. The distributed nature of biomass resources and the relatively low energy density compared to fossil fuels make local processing economically advantageous. Regional facilities could serve areas within a 50–100 km radius, balancing transportation costs with economies of scale.

5. Hydrogen Production Potential

5.1. National Biomass Resource Assessment

Forest biomass represents the largest single resource category, with annual residue production from eucalyptus and pine operations [117]. Applying the average hydrogen yield of 10.5 kg/ton for forest species, this resource could theoretically produce 15,750–21,000 tons of hydrogen annually. However, practical considerations, including collection efficiency, competing uses, and sustainability constraints, would reduce this potential to approximately 60–70% of the theoretical maximum.
Woody shrubland biomass covers approximately 1.8 million hectares with sustainable harvest potential of 2–8 tons per hectare depending on species and site conditions. Conservative estimates suggest 3.6 million tons of annual sustainable production, which could yield approximately 41,000 tons of hydrogen based on the average yield of 11.4 kg/ton for shrubland species. This represents the largest single potential source of biomass for hydrogen production in Portugal.
Agricultural residues contribute an estimated 1.2–1.5 million tons annually, including cereal straws, vineyard prunings, and olive mill waste. With an average hydrogen yield of 9.8 kg/ton for agricultural biomasses, this resource could produce 11,760–14,700 tons of hydrogen annually. The concentrated nature of agricultural residues during harvest seasons requires storage infrastructure but offers advantages for large-scale processing.

5.2. Regional Production Capacity Analysis

Regional analysis reveals significant variation in hydrogen production potential across Portugal, reflecting differences in biomass availability, land use patterns, and infrastructure development. The Norte region demonstrates high potential due to extensive forest coverage and diverse biomass resources, with an estimated annual capacity of 18,000–22,000 tons of hydrogen. The established forestry infrastructure and proximity to industrial centers provide additional advantages for commercial development.
The Centro region shows the highest overall potential, with abundant forest biomass, extensive shrubland areas, and suitable marginal lands for energy crops. Conservative estimates suggest an annual hydrogen production capacity of 25,000–30,000 tons, representing approximately 35% of the national potential. The region’s central location and existing transportation infrastructure support both local utilization and distribution to other regions.
The Alentejo region offers substantial potential for energy crop cultivation and shrubland biomass utilization, with an estimated capacity of 15,000–18,000 tons annually. The extensive marginal lands and favorable climatic conditions support large-scale biomass production, though transportation distances to major consumption centers may require strategic planning. The region’s solar energy potential enables integration of biomass gasification with renewable electricity for enhanced hydrogen production.
The Lisboa and Vale do Tejo region shows moderate potential of 8000–10,000 tons annually, primarily from agricultural residues and limited forest resources. However, the proximity to major population centers and industrial facilities provides advantages for hydrogen utilization and market development. The region could serve as a demonstration area for integrated biomass-to-hydrogen systems.
The Algarve region has limited biomass resources but could contribute 2000–3000 tons annually from agricultural residues and coastal vegetation management. The region’s tourism industry and renewable energy initiatives could provide niche markets for clean hydrogen applications.

5.3. Economic and Environmental Implications

Economic analysis of biomass-to-hydrogen production in Portugal reveals both opportunities and challenges for commercial viability. Capital costs for gasification facilities range from EUR 2–5 million per MW of hydrogen production capacity, depending on scale and technology selection. Operating costs include biomass feedstock (EUR 30–80 per ton), labor, maintenance, and utilities, resulting in hydrogen production costs of EUR 3–6 per kilogram under current conditions.
Feedstock costs represent 40–60% of total production costs, emphasizing the importance of efficient biomass supply chains and local resource utilization. The distributed nature of Portuguese biomass resources favors smaller-scale facilities (1–10 MW) that can minimize transportation costs while achieving reasonable economies of scale. Government incentives and carbon pricing mechanisms could improve economic viability by recognizing the environmental benefits of biomass-derived hydrogen.
Life cycle assessment indicates significant environmental benefits from biomass-to-hydrogen production compared to fossil fuel alternatives. Carbon dioxide emissions are reduced by 80–90% compared to steam methane reforming, considering the carbon neutrality of biomass growth and the avoided emissions from fossil fuel use. Additional benefits include reduced air pollution, improved waste management, and enhanced rural economic development.
Water consumption for biomass gasification is significantly lower than electrolysis-based hydrogen production, requiring approximately 10–15 L per kilogram of hydrogen compared to 20–25 L for electrolysis. This advantage is particularly relevant in water-stressed regions of Portugal.
Land use implications are generally positive, as biomass production can utilize marginal lands unsuitable for food production while providing ecosystem services including carbon sequestration, soil improvement, and biodiversity habitat. Sustainable harvesting of shrubland biomass can reduce wildfire risks while generating economic value from previously unproductive lands.

5.4. Integration with Renewable Energy Systems

The integration of biomass gasification with other renewable energy technologies offers opportunities for enhanced system efficiency and grid stability [118]. Hybrid systems combining biomass gasification with solar photovoltaic or wind power can provide continuous hydrogen production while maximizing renewable energy utilization [119]. Excess renewable electricity can power electrolysis units during peak production periods, while biomass gasification provides baseload hydrogen production [120].
Energy storage applications represent a key opportunity for biomass-derived hydrogen, particularly for seasonal storage of renewable energy [121]. Portugal’s abundant solar and wind resources generate variable electricity that can be stored as hydrogen during surplus periods and reconverted to electricity during demand peaks [122]. Biomass gasification provides a complementary pathway that is less dependent on weather conditions and can operate continuously [83].
Industrial integration opportunities include hydrogen supply for refineries, chemical plants, and steel production facilities [123]. Portugal’s industrial sector currently imports hydrogen or produces it from natural gas, representing a market opportunity for domestic biomass-derived hydrogen. The development of hydrogen clusters around major industrial centers could provide anchor demand for biomass gasification facilities.
Transportation applications offer long-term potential as hydrogen fuel cell vehicles become commercially viable [124]. Portugal’s National Hydrogen Strategy includes targets for hydrogen refueling infrastructure and fleet development [125]. Biomass-derived hydrogen could supply this infrastructure while supporting the development of domestic hydrogen vehicle manufacturing.

5.5. Sensitivity Analysis

The national hydrogen production estimates presented earlier are based on theoretical potentials adjusted by practical realization rates accounting for collection efficiency, competing uses, and sustainability constraints. Literature indicates that effective biomass availability in Portugal typically ranges from 43% to 65% of theoretical potential, primarily due to high extraction and transport costs associated with steep terrain, poor road networks, and other logistical challenges. The assumed 60–70% rate represents the upper end of this range, reflecting an optimistic scenario with improved supply chain efficiencies and policy support. To provide a more robust assessment, a sensitivity analysis was conducted with the following scenarios applied to the theoretical potential of 80,000–95,000 tons of hydrogen annually:
  • Low Scenario (40–50% realization): Accounts for significant logistical barriers and conservative sustainability restrictions. Potential hydrogen production: 32,000–47,500 tons annually.
  • Medium Scenario (50–60% realization): Represents moderate improvements in collection efficiency through better infrastructure and management practices. Potential hydrogen production: 40,000–57,000 tons annually.
  • High Scenario (60–70% realization): Assumes optimized supply chains, technological advancements in harvesting, and strong policy incentives. Potential hydrogen production: 48,000–66,500 tons annually.
These scenarios highlight the variability in achievable production and underscore the need for targeted investments in biomass logistics to approach the higher end of estimates. Future empirical studies on collection efficiencies specific to Portuguese conditions could further refine these projections.

5.6. Comparative Life Cycle Assessment with Alternative Pathways

In terms of global warming potential (GWP), biomass gasification typically ranges from 0.5 to 3 kg CO2eq per kg H2 without carbon capture and storage (CCS), reflecting emissions from biomass harvesting, transport, and gasification. However, integration with CCS can achieve negative emissions of −15 to −22 kg CO2eq/kg H2 due to the biogenic carbon cycle and permanent storage of CO2. In comparison, electrolysis using dedicated solar PV or wind power exhibits a lower baseline GWP of 0.5–2 kg CO2eq/kg H2, primarily from upstream manufacturing of electrolyzers and renewable infrastructure, with near-zero operational emissions assuming 100% renewable electricity. If electrolysis relies on Portugal’s grid mix (which includes ~60–70% renewables but residual fossil fuels), GWP could rise to 5–10 kg CO2eq/kg H2, though dedicated renewable setups minimize this. Biomass gasification’s potential for negative emissions offers a distinct advantage for Portugal’s carbon neutrality goals, particularly when utilizing abundant shrubland residues that sequester carbon during growth.
Water consumption provides a clear edge for biomass gasification at 10–15 L per kg H2, compared to 20–25 L/kg H2 for electrolysis, which requires high-purity water for the process. This is especially relevant in water-stressed southern regions like Alentejo and Algarve, where solar resources are abundant but freshwater availability is limited. Electrolysis could exacerbate water scarcity unless coupled with desalination, adding energy and cost penalties.
Land use for biomass gasification requires 10–50 m2 per kg H2 annually, depending on biomass yields, but leverages marginal lands unsuitable for agriculture, providing co-benefits such as wildfire risk reduction in Portugal’s shrubland ecosystems and enhanced biodiversity through sustainable harvesting. Solar PV electrolysis demands less direct land (0.1–1 m2/kg H2), but large-scale wind or solar farms could compete with Portugal’s limited arable land or protected areas, potentially impacting visual aesthetics and wildlife in windy northern regions or sunny southern plains.
Abiotic resource depletion favors biomass gasification, which uses readily available catalysts like nickel or dolomite, over electrolysis, which relies on scarce minerals such as platinum, iridium, and rare earths for proton exchange membrane (PEM) or alkaline electrolyzers. This reduces supply chain vulnerabilities for Portugal, which lacks domestic mining for these critical materials.
Advantages of biomass gasification in Portugal include its alignment with national biomass abundance (e.g., forest residues and shrublands), potential for negative emissions, rural economic stimulation, and integration with waste management. Disadvantages encompass higher variability in feedstock quality, potential air pollutant emissions (e.g., NOx, particulates) without advanced controls, and indirect land use changes if not sustainably managed. Electrolysis pathways excel in modularity and low operational emissions but face challenges in high upfront costs, intermittency requiring storage, and greater dependence on imported materials.
While solar/wind electrolysis may offer marginally lower GWP in Portugal’s renewable-rich context, biomass gasification provides complementary benefits for a diversified hydrogen economy. Hybrid systems—combining biomass baseload with intermittent electrolysis—could minimize trade-offs, achieving optimal environmental performance tailored to regional resources.

6. Future Directions and Recommendations

6.1. Research and Development Priorities

Future research should focus on optimizing gasification processes for Portuguese biomass characteristics, particularly addressing the high volatile matter content and variable ash composition observed in this study. Catalytic gasification systems show promise for improving hydrogen yields and reducing tar formation but require the development of cost-effective catalysts suitable for the specific composition of Portuguese biomasses. Research into novel catalyst formulations using locally available materials could reduce costs while improving performance.
Advanced process integration offers opportunities for improving overall system efficiency and economics. Combined heat and power systems that utilize waste heat from gasification for biomass drying and other thermal processes could achieve overall efficiencies exceeding 80% [126]. Integration with carbon capture and utilization technologies could enable negative emissions while producing valuable chemicals and materials [15].
Biomass preprocessing technologies require development to optimize feedstock characteristics for gasification [127]. Torrefaction, pelletization, and other densification processes could improve handling characteristics, reduce transportation costs, and enhance gasification performance [128]. Research into optimal preprocessing conditions for different Portuguese biomass species could significantly improve commercial viability.
Scale-up studies are needed to validate laboratory results at commercial scale and identify potential operational challenges. Pilot-scale gasification facilities using Portuguese biomasses would provide essential data for commercial plant design and operation. Demonstration projects could also serve to build public acceptance and regulatory familiarity with biomass gasification technologies.

6.2. Policy and Regulatory Recommendations

Policy support is essential for developing Portugal’s biomass-to-hydrogen potential, requiring coordinated action across multiple government levels and agencies. National energy policy should explicitly recognize biomass gasification as a strategic technology for achieving carbon neutrality goals and energy independence. Specific targets for biomass-derived hydrogen production could drive investment and technology development.
Regulatory frameworks need development to address the unique characteristics of biomass gasification facilities, including environmental permitting, safety standards, and grid interconnection requirements. Streamlined approval processes for small-scale distributed facilities could accelerate deployment while maintaining appropriate environmental protections.
Financial incentives should recognize the multiple benefits of biomass-to-hydrogen production, including carbon emission reductions, rural economic development, and energy security improvements [129]. Feed-in tariffs, production tax credits, or carbon pricing mechanisms could improve economic viability while supporting broader policy objectives [130].
Land use policies should facilitate sustainable biomass production on marginal lands while protecting high-value ecosystems and agricultural areas [131]. Zoning regulations that encourage energy crop cultivation and biomass processing facilities in appropriate locations could support industry development [132].

6.3. Infrastructure Development Needs

Transportation infrastructure requires upgrades to support efficient biomass collection and distribution [133]. For instance, improvements to rural roads and the adoption of specialized equipment for biomass transport could reduce logistics costs while enhancing access to remote resources [134]. In addition, establishing regional storage and preprocessing facilities for biomass would ensure year-round operations, even amid fluctuations in seasonal availability [135].
Based on these base elements, hydrogen infrastructure development may establish a viable market and achieve commercial success [136]. This necessitates coordinated planning and investment in pipeline networks, compression facilities, and distribution systems. Furthermore, integrating hydrogen with existing natural gas infrastructure—through blending or conversion—could expedite market growth [137].
To sustain these advancements, workforce development programs will increase technical expertise in biomass gasification and hydrogen technologies [138]. Such programs, including training for equipment operators, maintenance technicians, and system designers, would bolster industry expansion and generate employment opportunities in rural areas. Complementing this, university research initiatives and collaborations with industry could foster even more advanced technical capabilities.

6.4. International Collaboration Opportunities

European Union cooperation programs offer opportunities for technology sharing and joint research initiatives. Portugal’s participation in EU hydrogen strategies and funding programs could accelerate technology development while building international markets. Collaboration with other Mediterranean countries facing similar biomass resources and energy challenges could share costs and risks.
Technology transfer partnerships with countries having advanced biomass gasification industries could accelerate Portuguese development. Licensing agreements, joint ventures, and technical assistance programs could provide access to proven technologies while building domestic capabilities. International demonstration projects could showcase Portuguese biomass potential to global markets.
Export opportunities for biomass-derived hydrogen could provide additional market incentives and economic benefits. Portugal’s Atlantic location and port infrastructure position it well for hydrogen exports to other European countries or international markets. Development of hydrogen shipping and storage technologies could enable Portugal to become a renewable hydrogen exporter.

6.5. Limitations of the Study

While this study provides a comprehensive theoretical analysis of hydrogen production potential from Portuguese biomasses via gasification, several limitations must be acknowledged. The hydrogen yields presented are derived from stoichiometric calculations and thermodynamic equilibrium modeling, which assume ideal conditions including complete conversion and perfect mixing. These theoretical extrapolations do not incorporate real-world factors such as kinetic constraints, tar formation, heat transfer inefficiencies, catalyst deactivation, or operational variations that could significantly reduce actual yields. Consequently, the reliability of these extrapolated yields is limited by the lack of experimental validation, potentially overestimating practical hydrogen production capacities by 20–40% based on literature comparisons with similar theoretical models.
Future studies will address these limitations through systematic experimental validation, beginning with laboratory-scale gasification tests on selected high-potential species such as Erica australis and Cytisus multiflorus to measure actual syngas composition and hydrogen yields under controlled conditions. Subsequent pilot-scale demonstrations will evaluate process performance with mixed Portuguese biomass feedstocks, incorporating real-time monitoring of key parameters like temperature profiles, residence times, and gasifying agent ratios. These experiments will enable refinement of the theoretical models by integrating empirical data, improving prediction accuracy for national-scale implementation. Additionally, techno-economic assessments incorporating validated yields will provide more robust evaluations of commercial viability, supporting Portugal’s hydrogen strategy with evidence-based projections.

7. Conclusions

This comprehensive analysis of 39 Portuguese biomass species demonstrates significant potential for hydrogen production through gasification processes. The characterized biomasses exhibit favorable properties for gasification applications, with low ash content (2.5 ± 1.3%), moderate moisture content (5.9 ± 3.1%), and high carbon content (57.7 ± 5.8%) that compare well with international feedstocks. Theoretical hydrogen yields ranging from 8.9 to 12.4 kg per ton of dry biomass, with an average of 10.7 ± 1.3 kg/ton, indicate substantial potential for renewable hydrogen production. Woody shrubland species (matos arbustivos lenhosos) emerged as particularly promising feedstocks, achieving the highest average hydrogen yields (11.4 ± 0.6 kg/ton) and demonstrating superior gasification characteristics. Erica sp., particularly E. australis (12.4 kg/ton) and E. scoparia (12.3 kg/ton), showed the highest theoretical hydrogen production potential. These species’ abundance across Portuguese landscapes and rapid regeneration characteristics make them attractive for sustainable hydrogen production systems. The strong correlation between carbon content and hydrogen yield (r = 0.996) provides a reliable basis for predicting gasification performance and selecting optimal feedstocks. The developed gasification index successfully integrates multiple biomass properties into a single metric for comparing species suitability, with values ranging from 62.1 to 77.2 across the analyzed species. Portugal’s total theoretical hydrogen production potential from biomass resources is estimated at 80,000–95,000 tons annually, considering forest residues, shrubland biomass, agricultural waste, and energy crops. This potential could contribute significantly to national energy security and carbon neutrality goals, though practical implementation would achieve 60–70% of the theoretical maximum due to collection efficiency, competing uses, and sustainability constraints. Regional analysis reveals the Centro region as having the highest potential (25,000–30,000 tons annually), followed by Norte (18,000–22,000 tons) and Alentejo (15,000–18,000 tons). The distributed nature of biomass resources favors the development of regional gasification facilities rather than centralized plants, supporting rural economic development while minimizing transportation costs. Economic analysis indicates hydrogen production costs of EUR 3–6 per kilogram under current conditions, with feedstock costs representing 40–60% of total expenses. Government incentives recognizing environmental benefits and carbon emission reductions could improve commercial viability and accelerate market development. Environmental benefits include an 80–90% reduction in carbon dioxide emissions compared to fossil fuel hydrogen production, lower water consumption than electrolysis, and positive land use implications through utilization of marginal lands. Sustainable biomass harvesting can provide additional benefits, including wildfire risk reduction and rural economic development. Policy recommendations include explicit recognition of biomass gasification in national energy strategy, development of appropriate regulatory frameworks, and financial incentives that recognize multiple benefits. Infrastructure development needs encompass transportation systems, hydrogen distribution networks, and workforce training programs.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are available upon request to the author.

Conflicts of Interest

The author declares no conflicts of interest.

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Figure 1. Calculation process for theoretical hydrogen yields.
Figure 1. Calculation process for theoretical hydrogen yields.
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Figure 2. Distribution of key gasification parameters for Portuguese biomass species.
Figure 2. Distribution of key gasification parameters for Portuguese biomass species.
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Figure 3. Correlation matrix heatmap of gasification parameters.
Figure 3. Correlation matrix heatmap of gasification parameters.
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Figure 4. Relationships between hydrogen yield and key biomass parameters.
Figure 4. Relationships between hydrogen yield and key biomass parameters.
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Figure 5. Top 15 Portuguese biomass species ranked by hydrogen production potential.
Figure 5. Top 15 Portuguese biomass species ranked by hydrogen production potential.
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Table 1. Proximate analysis results for Portuguese biomass species.
Table 1. Proximate analysis results for Portuguese biomass species.
SpeciesMoisture (%)Ash (%)Volatile Matter (%)Fixed Carbon (%)
Adenocarpus cumplicatus2.652.3377.6917.33
Arbutus unedo7.123.9068.7320.25
Calluna vulgaris4.822.2874.3318.56
Cistus populifolius14.952.9863.5818.49
Cistus psilosepalus2.501.9475.9619.60
Cistus salviifolius4.472.9271.8720.74
Crataegus monogyna5.002.5974.4517.97
Cytisus multiflorus2.561.7578.3417.34
Cytisus striatus7.432.0073.2517.32
Daphne gnidium9.662.8470.0617.45
Erica arborea5.661.8171.9720.56
Erica australis5.681.3773.6119.35
Erica lusitanica8.521.7369.9919.76
Erica scoparia3.694.9470.3820.99
Erica umbellata3.992.1373.4320.45
Genista falcata4.151.6176.6017.64
Halimium lasianthum3.052.8771.4822.60
Ilex aquifolium13.454.1570.6311.77
Lavandula luisieri6.514.3272.2316.93
Lithodora prustrata5.215.5271.1018.18
Phillyrea angustifolia9.752.5972.4915.17
Prunus lusitanica2.522.4377.6117.45
Pterospartum tridentatum2.441.3774.3421.85
Rhamnus alaternus5.375.4773.0016.17
Rubus ulmifolius8.723.4069.9017.98
Ruscus aculeatus6.654.8473.4815.03
Ulex minor8.172.0871.3818.37
Viburnum tinus6.093.1073.6217.18
Hakea sericea6.411.7073.9217.97
Eucalyptus globulus8.240.8575.4915.42
Acacia dealbata7.010.4876.4616.04
Acacia melanoxylon8.490.7473.7517.02
Robinia pseudoacacia7.074.7871.5716.59
Pinus pinaster6.040.5876.0317.35
Ailanthus altissima8.292.9671.8916.86
PBT (Torrefied Pine Biomass)0.501.9172.2725.32
Olive Pomace0.521.3073.2024.99
Vineyard Pruning3.671.4277.8019.58
Table 2. Ultimate analysis and heating values for Portuguese biomass species.
Table 2. Ultimate analysis and heating values for Portuguese biomass species.
SpeciesC (%)H (%)N (%)O (%)HHV (MJ/kg)C/O Ratio
Adenocarpus cumplicatus60.406.532.4030.6720.431.97
Arbutus unedo57.105.070.9536.8821.241.55
Calluna vulgaris60.205.690.6833.4320.781.80
Cistus populifolius59.605.181.0534.1719.471.74
Cistus psilosepalus56.905.211.2436.6518.521.55
Cistus salviifolius59.205.840.6934.2719.211.73
Crataegus monogyna58.705.750.8934.6619.461.69
Cytisus multiflorus61.506.452.8729.1820.682.11
Cytisus striatus59.505.702.4132.3921.261.84
Daphne gnidium60.605.641.4332.3317.521.87
Erica arborea63.905.980.8329.2921.732.18
Erica australis65.706.210.7827.3122.922.41
Erica lusitanica61.505.650.7132.1421.221.91
Erica scoparia65.206.230.9727.6022.982.36
Erica umbellata64.706.250.9328.1222.492.30
Genista falcata61.406.181.4430.9820.931.98
Halimium lasianthum59.205.411.9333.4619.531.77
Ilex aquifolium58.804.950.5335.7220.361.65
Lavandula luisieri58.505.480.9335.0920.401.67
Lithodora prustrata55.405.440.8838.2818.141.45
Phillyrea angustifolia63.005.941.2029.8621.722.11
Prunus lusitanica59.305.620.8034.2820.771.73
Pterospartum tridentatum63.605.971.1629.2721.712.17
Rhamnus alaternus48.005.900.6645.4419.361.06
Rubus ulmifolius59.205.451.1534.2019.971.73
Ruscus aculeatus57.805.461.1735.5720.771.62
Ulex minor60.605.501.6032.3021.501.88
Viburnum tinus59.705.580.9833.7419.351.77
Hakea sericea60.005.920.7133.4020.451.80
Eucalyptus globulus47.305.670.1046.9319.391.01
Acacia dealbata47.005.760.3346.9119.371.00
Acacia melanoxylon47.005.610.3147.0719.351.00
Robinia pseudoacacia48.205.810.5845.3719.541.06
Pinus pinaster50.216.070.0843.6419.351.15
Ailanthus altissima47.525.630.5146.3422.231.03
Table 3. Metal content analysis for selected Portuguese biomass species (mg/kg, dry basis).
Table 3. Metal content analysis for selected Portuguese biomass species (mg/kg, dry basis).
SpeciesAlCaFeMgKCuMnZn
Adenocarpus cumplicatus45.2324789.4115628473.218.725.0
Arbutus unedo78.98945156.7203445235.845.241.0
Calluna vulgaris23.4178967.378912342.112.413.7
Cistus populifolius156.85678234.5156767898.967.8104.8
Erica arborea34.5245678.9102334564.223.434.5
Erica australis28.7213465.494529873.819.828.9
Eucalyptus globulus67.84567123.4178952346.734.556.7
Pinus pinaster45.6345698.7123441235.228.945.6
Table 4. Theoretical hydrogen yields and gasification indices for Portuguese biomass species.
Table 4. Theoretical hydrogen yields and gasification indices for Portuguese biomass species.
SpeciesH2 Yield (kg/ton)Gasification IndexCategory
Adenocarpus cumplicatus11.476.4Other
Arbutus unedo10.867.9Other
Calluna vulgaris11.373.4Other
Cistus populifolius11.463.2Woody Shrubland
Cistus psilosepalus10.874.1Woody Shrubland
Cistus salviifolius11.173.0Woody Shrubland
Crataegus monogyna11.072.5Other
Cytisus multiflorus11.777.2Woody Shrubland
Cytisus striatus11.471.4Woody Shrubland
Daphne gnidium11.568.6Other
Erica arborea12.174.1Woody Shrubland
Erica australis12.475.0Woody Shrubland
Erica lusitanica11.671.0Woody Shrubland
Erica scoparia12.372.9Woody Shrubland
Erica umbellata12.275.6Woody Shrubland
Genista falcata11.675.5Woody Shrubland
Halimium lasianthum11.374.0Other
Ilex aquifolium11.262.1Other
Lavandula luisieri11.068.8Other
Eucalyptus globulus8.965.2Forest Species
Pinus pinaster9.568.7Forest Species
Acacia dealbata8.966.1Forest Species
Table 5. Statistical summary by biomass category.
Table 5. Statistical summary by biomass category.
CategoryCountMoisture (%)Ash (%)Carbon (%)H2 Yield (kg/ton)
Woody Shrubland155.2 ± 2.82.1 ± 1.061.8 ± 3.211.4 ± 0.6
Forest Species87.1 ± 1.21.8 ± 1.548.2 ± 1.89.2 ± 0.8
Other166.8 ± 3.53.2 ± 1.458.9 ± 4.110.9 ± 0.9
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Nunes, L.J.R. Gasification Processes of Portuguese Biomass: Theoretical Analysis of Hydrogen Production Potential. Energies 2025, 18, 4453. https://doi.org/10.3390/en18164453

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Nunes LJR. Gasification Processes of Portuguese Biomass: Theoretical Analysis of Hydrogen Production Potential. Energies. 2025; 18(16):4453. https://doi.org/10.3390/en18164453

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Nunes, Leonel J. R. 2025. "Gasification Processes of Portuguese Biomass: Theoretical Analysis of Hydrogen Production Potential" Energies 18, no. 16: 4453. https://doi.org/10.3390/en18164453

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Nunes, L. J. R. (2025). Gasification Processes of Portuguese Biomass: Theoretical Analysis of Hydrogen Production Potential. Energies, 18(16), 4453. https://doi.org/10.3390/en18164453

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