Environmental Performance of the Sewage Sludge Gasification Process Considering the Recovered CO₂

Abstract

An advanced gasification module (AGM) for green hydrogen production involves a small-scale biomass gasification process owing to the low energy density of biomass. Therefore, significant heat loss and the endothermic nature of gasification system require additional fossil fuel heat, increasing CO₂ emissions. This study focuses on bioenergy conversion with carbon capture and utilization (BECCU), where carbon-neutral CO₂ from biomass gasification is captured and reused as a gasifying agent to reduce the greenhouse gas intensity of green hydrogen. BECCU is expected to achieve negative emissions and enhance gasification efficiency by promoting conversion of char and tar through CO₂ gasification. To evaluate the effectiveness of BECCU in the AGM, we conducted a sensitivity analysis of the reformer temperature and S/C ratio using process simulation combined with life cycle assessment. In both sensitivity analyses, the GWP for CO₂ capture was lower compared with conventional conditions, considering recovered CO₂ from purification and the additional steam generated through heat recovery. This suggests improved hydrogen yields from enhanced char and tar conversion. Consequently, the GWP was reduced by more than 50%, demonstrating BECCU’s effectiveness in the AGM. This represents a step toward operating biomass gasification systems with lower environmental impact and contributing to sustainable energy production.

1. Introduction

Hydrogen (H₂), which can be produced from various sources such as water, coal, natural gas, and renewable energy, is a next-generation energy source with a low environmental impact that does not emit CO₂ when used [1,2]. The global demand for H₂ is projected to increase approximately five-fold by 2050, compared to 2022 levels, to achieve carbon neutrality [3]. In particular, the production of green H₂ from renewable sources such as solar and wind power is expected to expand as numerous nations announce roadmaps for H₂ production [4]. In this study, we focused on biomass gasification to produce green H₂. Biomass is carbon-neutral and can be stably obtained in various regions, unaffected by weather conditions. Additionally, gasification offers advantages over water electrolysis in terms of energy and exergy efficiency [5]. Our research group has focused on a small-scale biomass gasification process, the advanced gasification module (AGM), which enables the synthesis of H₂ and is characterized by higher gasification and reforming efficiencies. The AGM employs an indirect pyrolysis gasification process in which syngas is produced through the circulation of heat carriers (HCs) heated by external fuel gas generated from the combustion of fossil fuels and off-gas. However, this implies that the consumption of fossil fuels may be attributed to heat loss in small-scale plants, consequently worsening specific CO₂ emissions.

Additionally, biomass feedstock has a lower energy density and calorific value than fossil fuels [6,7]. As a result, the feedstock must be collected from a wider area, leading to increased specific CO₂ emissions and higher economic costs during transportation [8]. Therefore, mitigating CO₂ emissions through the recycling or sequestration of CO₂ gas is necessary [9]. Furthermore, the utilization of recovered CO₂ has been widely applied across various fields to address energy shortages and ecological environmental challenges, such as in rock fracturing technology and CO₂ fixation in algae cultivation for next-generation bioenergy [10,11]. In this context, we focus on bioenergy conversion with carbon capture and utilization (BECCU), which involves capturing CO₂ generated from biomass gasification and reusing it as a gasifying agent for CO₂ gasification.

Considering BECCU, the following advantage can be obtained: negative emissions to capture and utilize CO₂ gas, corresponding to carbon neutrality [12]. Bioenergy conversion with carbon capture and storage (BECCS) has garnered significant interest as a large-scale carbon-negative technology [13]. However, upgrading waste CO₂ into valuable products, such as in BECCU, is a promising complementary approach that improves the carbon balance and provides additional economic value [14]. Current BECCU strategies include biocatalytic approaches, such as biotransformations using algae and biological Sabatier processes, which focus on chemical transformations [12]. Most of these strategies use CO₂ not to produce the primary product, but as a feedstock for producing by-products. However, in all these studies, BECCU has been applied to produce by-products, and it has not yet been implemented to produce the main products in H₂ production plants via gasification.

Investigating the eco-burden on BECCU is necessary to implement a life cycle assessment (LCA) [15]. In a previous study, Kuroda et al. conducted an LCA evaluation assuming a BECCU for a plant where H₂ was produced through gasification [16]. In their research, the captured CO₂ was considered available for carbon dioxide fertilization in the plant factory, leading to its fixation. As a result, the BECCU was not counted as an emission to the atmosphere, and the global warming potential (GWP) was reduced by more than half compared to the conventional case. Maran et al. conducted a consequential LCA to evaluate the environmental impacts of a scenario in which the BECCU was integrated into the HTL to produce biocrude and methanol, introducing flexible BECCU operations [17]. BECCU enabled the CO₂ supply in this study, thereby reducing the required biomass feedstock. However, as the external energy input for by-product production increased, the environmental impacts in many categories were higher compared to a scenario without BECCU integration. This suggests that using BECCU to produce by-products can generate another valuable energy source, but it also requires additional energy for by-product production.

Based on these concepts, we suggest that the 2-step pressure swing adsorption (PSA) method developed by our research team is effective for CO₂ recovery in BECCU [18]. A notable feature of this system, which divides the H₂ purification process into two steps, is that it enables low-pressure operation by adsorbing and separating CO₂ from syngas in the first step and purifying H₂ in the second step. As a result, this method reduces the auxiliary power consumption compared with conventional PSA and reduces the environmental impact. The 2-step PSA is effective for BECCU because it enables purification with a low environmental impact and makes it possible to utilize the recovered CO₂ effectively. Therefore, this study introduces 2-step PSA into the AGM to recover CO₂ for the BECCU.

Finally, the CO₂ recovered by 2-step PSA was utilized as a gasifying agent in the AGM reformer. It is known that adding CO₂ to the reformer improves the gasification efficiency. Renganathan et al. evaluated the gasification performance of a reformer using CO₂ and steam as gasifying agents through simulation [9]. The results showed that cold gas efficiency (CGE) improved as the conversion of char increased with increasing CO₂ flow rate and temperature. Additionally, as the amount of steam added increased, the required amount of CO₂ for char conversion and the CO₂ reaction rate decreased. Li et al. experimented with toluene as a model component of biomass tar to study the effects of temperature and CO₂ flow rate on gasification [19]. Their results indicated that as temperature and CO₂ flow rate increased, the tar conversion rate improved, and the yields of H₂, CO, and syngas also increased.

Based on the above background, this study proposes a BECCU that utilizes CO₂ recovered by the 2-step PSA as a gasifying agent for a reformer in the same H₂ production AGM. The introduction of CO₂ recovery helps reduce CO₂ emissions. Furthermore, using CO₂ as a gasifying agent improves the gasification efficiency and increases H₂ production. Consequently, the CO₂ emission intensity of the AGM was reduced. In this study, we evaluated the impact of introducing BECCU on the CO₂ emission intensity at the AGM plant scale using LCA.

This study represents a significant step toward establishing biomass gasification systems that operate with significantly lower environmental impacts. By integrating CO₂ recovery and utilization technologies such as BECCU, this work contributes to advancing sustainable energy production and addressing the global need for hydrogen production with low environmental impact [3]. Our approach will contribute to progress toward a cleaner energy future.

2. Materials and Methods

This study aimed to introduce BECCU at the AGM plant scale and evaluate its effectiveness in reducing CO₂ emission factors by considering CO₂ recovery and recycling. To achieve this, a process simulation was used to conduct a sensitivity analysis of the effects of reformer temperature and steam/carbon ratio (S/C) when recovered CO₂ was used as a gasifying agent in addition to the conventional gasifying agent, steam. An increase in the reformer temperature and S/C ratio is expected to enhance the reaction rate between char, tar, and the gasifying agent, resulting in increased H₂ production. Although both factors are anticipated to increase CO₂ emissions due to higher combustion in the reformer, this can be considered an increase in negative emissions by introducing BECCU, contributing to a reduction in CO₂ emission intensity. Additionally, the CO₂ mitigation effect of auxiliary power in the H₂ purification process, achieved by 2-step PSA, was also considered. Next, sewage sludge (SS) was used as the feedstock for the AGM. Co-locating an AGM with a wastewater treatment plant offers advantages such as a stable collection route and reduced transportation distances.

Furthermore, tar condensation in the gasification process can cause issues such as pipe blockages and reduced heat exchange efficiency, whereas decomposition through gasification can increase H₂ production [20]. To gain a deeper understanding of the decomposition behavior during tar reforming in a reformer under various conditions, gasification experiments were conducted using tar collected from an AGM plant [21]. Process simulations were designed using the tar gasification rate equations estimated from preliminary experiments. Finally, an LCA was conducted using the inventory data obtained from the simulations.

2.1. Preliminary Experiments: Estimation of Gasification Rate Equation for Sewage Sludge Tar

Based on the advantages of the captured CO₂, the reaction of tar with CO₂ was considered in this study.

In the experiments, the SS-derived tar collected from the pyrolizer of the AGM was used as the sample (Figure 1a,

Table 1. Properties of sewage sludge tar.

C * [wt.%]	72.37
H * [wt.%]	7.07
N * [wt.%]	9.08
O *,** [wt.%]	11.49
S * [wt.%]	0.00
Cl * [wt.%]	0.00
Higher heating value (HHV) [kJ/kg]	30,711

* Dry basis, ** O = 1 − (C + H + N + S + Cl + Ash).

). Tar is composed of numerous compounds, making it difficult to represent accurately in the process simulation used in this study. Therefore, in the simulations described in the later sections, tar was modeled solely as benzene (C₆H₆) and naphthalene (C₁₀H₈). The properties in Table 1 are provided only to describe the experimental samples, and only the gasification rate equation obtained from experiments using these samples was applied in the process simulation. Therefore, the elemental properties, such as C, H, N, O, S, and Cl, were not considered as influencing factors in the gasification process (see Table 1). During the experiment, the sample was dried to a constant weight and heated to a specified temperature in an argon atmosphere. Once the target temperature was reached, the sample was held isothermally under a gasifying agent atmosphere, during which the mass change of the sample was measured as it underwent decomposition. These experimental results were used to determine the reaction rate constant, frequency factor, and activation energy in the gasification reaction rate equation between the sample and the gasifying agent. The experimental conditions are listed in

Table 2. Experimental conditions.

Gasifying Agent	CO2, Steam
Temperature [K]	1173, 1273, 1373
Heating rate [K/min]	30
Sample particle size [mm]	≤1
Sample weight [mg]	10

. CO₂ and steam were used as the gasifying agents. Isothermal temperatures were selected at three points where the tar decomposition of each gasifying agent could be easily observed.

Regarding the heating rate, with reference to our previous study as a guide for the experimental method, it was confirmed through preliminary gasification experiments that the gasification rate expression for the samples used in this study is independent of heating rates between 10 and 30 K/min [22]. Therefore, setting the heating rate within this range does not affect the results, and based on this premise, the experiments in this study were conducted at 30 K/min. To ensure that variations in gasifying agent concentration did not affect the decomposition rate of the sample, each experiment was conducted at sufficiently high concentrations of gasifying agents. Because the sample sizes within the furnace were not uniform, the particle size was not standardized. However, samples smaller than approximately 1 mm were used, with approximately 10 mg used per experiment. Thermogravimetric analysis (TGA; TGA-51, SHIMADZU; Figure 1b) was employed for the measurements, and the experimental setup was configured to obtain the data (Figure 1c).

To obtain a detailed understanding of the reactions in the reformer through process simulations, a kinetic model defined by the frequency factor and activation energy for each reaction was used. Using the data obtained from the above method, the frequency factor and activation energy in the reaction rate equation for reformer design were estimated through the analytical method described below.

The sample was a nonporous material, such as coal particles, and the reaction progressed centripetally from the surface to the interior of the solid particles. Based on this observation, the gasification rate was considered proportional to the surface area; therefore, the unreacted core model was applied. The reaction rate constants were determined using Equations (1) and (2) [23].

$${\displaystyle \frac{dX}{dt}}={k\left(1-X\right)}^n,$$

(1)

$$kt={\displaystyle \frac{\left({\left(1-X\right)}^{1-n}\right)-1}{n-1}},$$

(2)

where $k$ [1/s] is the reaction rate constant, $t$ [s] is time, $X$ is the conversion rate, and $n$ [-] is the reaction order. Note that $n$ is 2/3, which is assumed to be proportional to the surface area according to the unreacted core model. Regarding the assumption of nonporosity in the unreacted core model used for kinetic analysis, the experimental sample, sewage sludge tar, was treated as nonporous because, when comparing reaction orders, the case assuming a nonporous material (reaction order of 2/3) provided a better fit to the experimental data than the case assuming a porous material (reaction order of 1/3) [23]. This justifies the use of the unreacted core model in this study.

A potential limitation of this model is that, for truly porous reactants where the reaction gas can penetrate into the interior, the unreacted core model may not be applicable [24]. In such cases, the estimated reaction rate constant could be influenced by heat and mass transfer effects, and a more detailed model reflecting the actual reaction mechanism would be required.

The reaction rate constants obtained from Equations (1) and (2) follow the Arrhenius correlation. Therefore, an Arrhenius plot, as defined by Equation (3), can be used to determine the frequency factor and activation energy (Figure 2).

$$\mathit{ln}k=\mathit{ln}A-{\displaystyle \frac{E}{RT}},$$

(3)

where $A$ [1/s] is the frequency factor, $E$ [kJ/mol] is the activation energy, $R$ [J/(K·mol)] is the gas constant, and $T$ [K] is the temperature.

The frequency factor and activation energy of each gasifying agent were statistically determined by calculating the slope and intercept from the estimated equations of the plotted graphs (

Table 3. The kinetics parameters.

Gasifying Agent	$\mathit{A}$ [1/s]	$\mathit{E}$ [kJ/mol]
CO2	$1.09\times {10}^2$	$1.32\times {10}^2$
Steam	$6.31\times {10}^2$	$1.49\times {10}^2$

). In Table 3, the frequency factor ranges from 10² to 10⁵ s⁻¹, and the activation energy is approximately 93–125 kJ/mol, indicating reasonable results [25,26].

2.2. Design of Process Simulation

To evaluate the effects of reformer temperature and S/C ratio on CO₂ emission reduction when recycling recovered CO₂ for gasification, a process simulation of the AGM plant was designed. The simulation was performed using the AVEVA Process Simulation (Version 8.0.0.2238, AVEVA Group, Cambridge, UK) under steady-state conditions (Figure 3). In addition, the stream data table for the most common operating condition of the AGM—reformer temperature of 1173 K and S/C ratio of 1.4—is shown in

Table 4. Stream data table.

	Units	1	2	3	4	5	6	7	8	9	10	11	12	13	14	15	16	17	18	19
Pressure	kPa	101.3	101.3	101.3	104.0	106.0	106.0	106.0	106.0	106.0	106.0	106.0	105.0	102.0	109.0	101.0	101.0	106.0	106.0	106.0
Temperature	K	298.2	298.2	298.2	423.2	298.2	957.7	303.6	307.6	423.2	1173.2	1173.2	623.2	630.1	303.2	303.2	313.2	315.1	298.2	1273.2
Mass Flows	kg/s	0.1995	0.0349	0.0000	0.3318	0.0083	0.0074	0.0002	0.0068	0.0054	0.0009	0.0188	0.0187	0.0187	0.0054	0.0145	0.0004	0.0073	0.1716	0.1789
Mole Flows	mol/s	11.5739	2.4367	0.0000	11.4453	0.9853	0.3411	0.0047	0.1764	0.2995	0.0749	0.8781	0.8744	0.8744	0.2995	0.6438	0.2244	0.2430	5.9474	6.1745
C	mol/s	0.2674	0.2674	0.0000	0.0000	0.2674	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
H	mol/s	0.4711	0.4711	0.0000	0.0000	0.4711	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
N	mol/s	0.0241	0.0241	0.0000	0.0000	0.0241	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
O	mol/s	0.1213	0.1213	0.0000	0.0000	0.1213	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
S	mol/s	0.0019	0.0019	0.0000	0.0000	0.0019	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Cl	mol/s	0.0002	0.0002	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
H2	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0330	0.0000	0.0000	0.0000	0.0000	0.1660	0.1660	0.2872	0.0000	0.2872	0.2244	0.0628	0.0000	0.0000
CO	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0176	0.0000	0.0000	0.0000	0.0000	0.1417	0.1417	0.0206	0.0000	0.0206	0.0000	0.0206	0.0000	0.0000
CO2	mol/s	0.0000	0.0000	0.0000	0.3221	0.0000	0.0506	0.0000	0.1764	0.0000	0.0000	0.1810	0.1810	0.3021	0.0000	0.3021	0.0000	0.1257	0.0389	0.2770
CH4	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0414	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
C2H4	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0017	0.0000	0.0000	0.0000	0.0000	0.0014	0.0014	0.0014	0.0000	0.0014	0.0000	0.0014	0.0000	0.0000
C2H6	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0286	0.0000	0.0000	0.0000	0.0000	0.0237	0.0237	0.0237	0.0000	0.0237	0.0000	0.0237	0.0000	0.0000
N2	mol/s	0.0000	0.0000	0.0000	8.8841	0.0000	0.0088	0.0000	0.0000	0.0000	0.0000	0.0088	0.0088	0.0088	0.0000	0.0088	0.0000	0.0088	4.7703	4.7791
C6H6	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0051	0.0000	0.0000	0.0000	0.0000	0.0016	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
C10H8	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0006	0.0000	0.0000	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
H2O	mol/s	10.6878	1.5506	0.0000	0.2062	0.0749	0.0749	0.0000	0.0000	0.2995	0.0000	0.3517	0.3517	0.2306	0.2995	0.0000	0.0000	0.0000	0.0000	0.1922
H2S	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0017	0.0000	0.0000	0.0000	0.0000	0.0017	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
O2	mol/s	0.0000	0.0000	0.0000	2.0330	0.0000	0.0000	0.0047	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	1.1244	0.9262
HCl	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
C-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0610	0.0000	0.0000	0.0000	0.0593	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
H-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0113	0.0000	0.0000	0.0000	0.0108	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
O-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0013	0.0000	0.0000	0.0000	0.0013	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
N-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0032	0.0000	0.0000	0.0000	0.0032	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
S-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0002	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Cl-CHAR	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
Ash	mol/s	0.0000	0.0000	0.0000	0.0000	0.0243	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000
PROPANE	mol/s	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0000	0.0139	0.0000

. The stream data table includes pressure, temperature, flow rate, and composition. Details of the process are described below.

In the simulation, the design scope was limited to the process downstream of the drying furnace within the AGM, specifically from pyrolysis to PSA. Upstream processes before the pyrolizer, such as dewatering and drying, were not included in the simulation because the process simulation software used in this study cannot design these units. The eco-burdens of the auxiliary power of the dehydrator and drying furnace were accounted for in the LCA. Furthermore, the primary focus of this study is on the BECCU system, particularly the section between the reformer and the 2-step PSA, which plays a key role in CO₂ recovery and utilization. For the upstream processes, we referred to the detailed studies by Kobayashi et al. [27] and Nakakubo [28], which specifically investigated dewatering and drying operations for sewage sludge. Their findings were used to estimate the performance and energy requirements of these processes, thereby ensuring the validity and consistency of the overall system analysis.

The AGM can be divided into the following four steps.

First, the feedstock SS was fed into the pyrolizer at a rate of 720 kg/d, corresponding to a feed rate of 0.00833 kg/s for the simulation calculations. In the demonstration AGM plant, the sewage sludge feedstock fed into the pyrolizer is operated with a particle size of 10 mm or less, and this study also assumes a particle size of 10 mm or less. The results of the property analysis of SS during feeding are listed in

Table 5. Properties of sewage sludge and sewage sludge char.

	Sewage Sludge	Sewage Sludge Char
C * [wt.%]	46.0	41.7
H * [wt.%]	6.80	1.30
N * [wt.%]	4.84	5.15
O *,** [wt.%]	27.8	2.36
S * [wt.%]	0.860	0.340
Cl * [wt.%]	0.100	0.0500
Ash * [wt.%]	13.6	49.1
HHV [kJ/kg]	17,220	14,644

* Dry basis, ** O = 1 − (C + H + N + S + Cl + Ash).

. In the pyrolizer, the indirect pyrolysis of SS occurs at 873 K using HCs heated in the preheater by combustion heat in the combustor. Note that in a 1473 K combustor, off-gas and supplementary propane are consumed during combustion. The composition of the syngas after pyrolysis was estimated based on the properties of the SS and SS char (Table 5), as reported by Hamazaki et al. [29] for the pyrolysis product distribution, which is presented in

Table 6. Pyrolysis composition of sewage sludge at 873 K.

H2 [wt.%]	0.797
CO [wt.%]	5.92
CO2 [wt.%]	26.7
CH4 [wt.%]	7.96
C2H4 [wt.%]	0.566
C2H6 [wt.%]	10.3
N2 [wt.%]	2.97
C6H6 [wt.%]	4.77
C10H8 [wt.%]	0.904
H2O [wt.%]	16.2
H2S [wt.%]	0.690
O2 [wt.%]	0.00
HCl [wt.%]	0.0753
C-Char [wt.%]	8.79
H-Char [wt.%]	0.274
N-Char [wt.%]	1.09
O-Char [wt.%]	0.497
S-Char [wt.%]	0.0716
Cl-Char [wt.%]	0.0105
Ash [wt.%]	11.4
Total [wt.%]	100

. As biomass-derived tar consists of many hydrocarbon species, it was simplified by assuming that it comprises two relatively well-studied components: benzene (C₆H₆) and naphthalene (C₁₀H₈). The heat remaining in the HC after preheating was directed to a drying furnace.

Second, the syngas and char obtained after pyrolysis were sent to the reformer, where they underwent conversion through three main reactions: partial oxidation, steam reforming, and CO₂ reforming (

Table 7. Reactions in the reformer.

Partial oxidation	C-Char + 1/2O2 → CO
	CO + 1/2O2 → CO2
	H2 + 1/2O2 → H2O
	H-Char + 1/2O2 → H2O
	CH4 + 1/2O2 → CO + 2H2
	C2H4 + O2 → 2CO + 2H2
	C2H6 + O2 → 2CO + 3H2
Primary water gas	C-Char + H2O → CO + H2
Tar steam reforming	C6H6 + 6H2O → 6CO + 9H2
	C10H8 + 10H2O → 10CO + 14H2
Boudouard	C-Char + CO2 → 2CO
Tar dry reforming	C6H6 + 6CO2 → 12CO + 3H2
	C10H8 + 10CO2 → 20CO + 4H2
Dry reforming of methane	CH4 + CO2 → 2CO + 2H2
Methane reforming	CH4 + H2O ↔ CO + 3H2
Water–gas shift	CO + H2O ↔ H2 + CO2

). In this study, it was expected that the addition of CO₂ would promote Boudouard and tar dry reforming. Additionally, the dry reforming of methane, in which methane reacts with CO₂, is likely to occur at high temperatures [30]. The frequency factor and activation energy of the tar gasification reaction rate equation were used in the design. To promote these reactions, O₂ (298 K), steam (500 K), and CO₂ (298 K) were added as gasifying agents. O₂ was externally generated and added to reach the target temperature. Steam was generated through heat exchange with hot gas from the reformer and added at S/C = 1.4 in conventional operation. CO₂ was added from the separated and recovered amount using 2-step PSA.

Third, two shift reactors were installed: a high-temperature shift (HTS) reactor with an inlet temperature of 623 K and a low-temperature shift (LTS) reactor with an inlet temperature of 513 K to produce H₂-rich gas through water–gas shift reactions [16]. For the removal of H₂S contained in the reformed gas, a desulfurizer was installed between the reformer and the HTS unit, which is an earlier stage than the 2-step PSA, referencing Nakayama et al. [18]. In addition, fuel cells intended to use hydrogen produced by the AGM degrade in performance if the hydrogen fuel contains more than 1 ppm of H₂S [31]. Therefore, the desulfurizer must remove H₂S to less than 1 ppm. Kitayama et al. of our research team have demonstrated that neutralized sediments, a mining waste, can be used as an H₂S adsorbent and can remove H₂S down to 0 ppm [32]. Accordingly, in this study, it was assumed in the calculations that H₂S was completely removed.

Finally, the 2-step PSA, which reduces auxiliary power, separated CO₂ from the other gases in the first step and purified H₂ in the second step. From 2-step PSA, CO_2, and off-gas, in addition to purified H₂, were recovered. 2-step PSA is more advantageous than conventional PSA because of its lower operating pressure and higher purification performance [18]. According to Kuroda et al., the purity of recoverable CO₂, depending on the gas composition, was 98.4% and the recovery rate was 58.4% [16]. This study assumed that the purity of CO₂ was 100% and that the purity of the purified H₂ was 98.2%, with a recovery rate of 78.14%.

2.3. LCA

In this study, an environmental impact assessment was conducted using LCA. The functional unit for the evaluation was set to 1 MJ of H₂, which corresponds to the produced gas. The system boundary followed the well-to-gate approach, encompassing six defined subsystems from the collection of the SS feedstock onward: dehydrator (SS1), drying furnace (SS2), combustor (SS3), pyrolizer, reformer, HTS, and LTS (SS4), 2-step PSA (SS5), and BECCU (SS6) (Figure 4). In the impact analysis, only the GWP was selected because it is a technology for capturing and utilizing CO₂.

Kobayashi et al. assumed that SS1 utilized screw press dewatering to reduce the moisture content of the sewage sludge from 96.5% to 80.0% [27]. The electricity consumption for this process was reported as 5.8 kWh/t of dewatered sludge.

Next, the sewage sludge was dried from a moisture content of 80.0% to 16.2% using a kiln dryer. The electricity required for this process was 85 kWh/t of dewatered sludge [28]. The heat necessary for moisture evaporation was calculated using Equation (4) (SS2). Any shortfall in the required heat was assumed to be provided by propane combustion (LHV = 46.6 MJ/kg).

$$\begin{array}{c}Q=\left\{M_{H_{2}O}\times c\times \left(373\mathrm{K}-298\mathrm{K}\right)+M_{H_{2}O}\times L\right\}/\eta ,\end{array}$$

(4)

where $Q$ [kJ] is the total heat required for drying; $M_{H_{2}O}$ [kg] is the amount of water to be removed; $c$ [kJ/(kg·K)] is the specific heat of water; $L$ [kJ/kg] is the latent heat of evaporation of water; and $\eta$ [%] is the drying efficiency (i.e., the ratio of energy required for evaporation to the energy consumed). According to Kobayashi et al., $\eta$ was set to 60% [27].

Propane was supplied to provide the necessary heat for heating the heat HCs, and the electricity consumption of the air supply pump required for combustion was also accounted for (SS3).

The power required to produce oxygen for the reformer, the electricity consumption of the pumps supplying the gasifying agents (oxygen and CO₂), and the power needed to supply water for heat exchange with high-temperature gas after reforming were all included (SS4).

Finally, based on a study by Kuroda et al., the energy required for the 2-step PSA was assumed [16]. The operating performance of the 2-step PSA generally depends on the composition and flow rate of the supplied syngas, so a detailed process simulation would be necessary for precise evaluation. However, because the primary focus of this study was to conduct an LCA for the entire process, reference values were used for simplicity. Regarding CO₂ accounting in the BECCU system, the CO₂ recovered by the 2-step PSA and added to the reformer was subtracted from the total CO₂ emissions (SS6). Any CO₂ not recovered by the 2-step PSA, which became off-gas, was considered to have zero emissions due to its carbon neutrality. The intensities of electricity, propane, oxygen production, water, and the 2-step PSA used in the LCA calculations described above are summarized in

Table 8. Intensity used in LCA calculations.

Item	Intensity	Unit	Reference
Electricity	0.574	kg-CO2/kWh	[33]
Propane (production)	0.508	kg-CO2/Nm3	[33]
Propane (combustion)	0.0499	kg-CO2/MJ	[33]
Oxygen production	0.350	kWh/Nm3	[34]
Water	0.000366	kg-CO2/L	[33]
2-step PSA (Auxiliary power)	2.83	MJ/kg-CO2	[16]

.

2.4. Evaluation Method

The effects of BECCU, as determined by the above method, were evaluated using the following indicators: GWP, H₂ production, syngas composition, auxiliary power, CGE, recycled CO₂/C, and reaction rates of char and tar. The H₂ production was defined as the amount of H₂ that could be produced from 1 kg of SS feedstock, and the auxiliary power was defined as the power consumed per second to produce 1 MJ of H₂. The syngas composition consisted of four components –H₂, CO, CO₂, and CH₄ after reforming, and LTS was used to observe the effect of CO₂ addition on the reactions. The CGE is defined as follows:

$$\begin{array}{c}\mathrm{CGE}={\displaystyle \frac{{\mathrm{L}\mathrm{H}\mathrm{V}}_{\mathrm{p}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}{\mathrm{H}}_2}+{\mathrm{L}\mathrm{H}\mathrm{V}}_{\mathrm{o}\mathrm{f}\mathrm{f}-\mathrm{g}\mathrm{a}\mathrm{s}}}{{\mathrm{L}\mathrm{H}\mathrm{V}}_{\mathrm{f}\mathrm{e}\mathrm{e}\mathrm{d}\mathrm{s}\mathrm{t}\mathrm{o}\mathrm{c}\mathrm{k}}}}.\end{array}$$

(5)

The CO₂ recovered and added in 2-step PSA was defined as recycled CO₂. The amount of recycled CO₂ was defined as follows:

$$\begin{array}{c}{\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{d}\mathrm{C}\mathrm{O}}_2/\mathrm{C}={\displaystyle \frac{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}{\mathrm{C}\mathrm{O}}_2\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{o}\mathrm{v}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{d}}{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{c}\mathrm{a}\mathrm{r}\mathrm{b}\mathrm{o}\mathrm{n}\mathrm{i}\mathrm{n}\mathrm{f}\mathrm{u}\mathrm{e}\mathrm{l}}}.\end{array}$$

(6)

The following equation defines the reaction rates of char and tar with CO₂. Additionally, the CO₂ was divided into pyrolysis CO₂ and recycled CO₂ to examine the effects of recycled CO₂.

$$\mathrm{C}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}={\displaystyle \frac{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{c}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{p}\mathrm{y}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{s}{\mathrm{C}\mathrm{O}}_2+\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{d}{\mathrm{C}\mathrm{O}}_2+\mathrm{o}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{s}}{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{c}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{r}}}.$$

(7)

$$\mathrm{T}\mathrm{a}\mathrm{r}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}\mathrm{r}\mathrm{a}\mathrm{t}\mathrm{e}={\displaystyle \frac{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{p}\mathrm{y}\mathrm{r}\mathrm{o}\mathrm{l}\mathrm{y}\mathrm{s}\mathrm{i}\mathrm{s}{\mathrm{C}\mathrm{O}}_2+\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{d}{\mathrm{C}\mathrm{O}}_2+\mathrm{o}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{s}}{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{t}\mathrm{a}\mathrm{r}\mathrm{b}\mathrm{e}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{r}}}.$$

(8)

$$\text{*Tar}={\text{C}}_6{\text{H}}_6+{\text{C}}_{10}{\text{H}}_8$$

The amount of recycled CO₂ consumed in the reaction between the char and tar is defined by the following equation:

$$\begin{array}{c}\mathrm{recycled}{\mathrm{C}\mathrm{O}}_2\mathrm{reaction}\mathrm{rate}={\displaystyle \frac{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}{\mathrm{C}\mathrm{O}}_2\mathrm{r}\mathrm{e}\mathrm{a}\mathrm{c}\mathrm{t}\mathrm{e}\mathrm{d}\mathrm{w}\mathrm{i}\mathrm{t}\mathrm{h}\mathrm{c}\mathrm{h}\mathrm{a}\mathrm{r}\mathrm{a}\mathrm{n}\mathrm{d}\mathrm{t}\mathrm{a}\mathrm{r}}{\mathrm{m}\mathrm{o}\mathrm{l}\mathrm{e}\mathrm{s}\mathrm{o}\mathrm{f}\mathrm{r}\mathrm{e}\mathrm{c}\mathrm{y}\mathrm{c}\mathrm{l}\mathrm{e}\mathrm{d}{\mathrm{C}\mathrm{O}}_2\mathrm{a}\mathrm{d}\mathrm{d}\mathrm{e}\mathrm{d}\mathrm{t}\mathrm{o}\mathrm{t}\mathrm{h}\mathrm{e}\mathrm{r}\mathrm{e}\mathrm{f}\mathrm{o}\mathrm{r}\mathrm{m}\mathrm{e}\mathrm{r}}}.\end{array}$$

(9)

In this study, the GWP was used as a quantitative indicator of the synergistic effect of direct CO₂ recovery and improved gasification efficiency. The GWP was calculated using the following equation:

$$\begin{array}{c}\mathrm{GWP}[{\mathrm{g}\text{-}\mathrm{C}\mathrm{O}}_2\mathrm{eq}./{\mathrm{M}\mathrm{J}\text{-}\mathrm{H}}_2]={\displaystyle \frac{{\sum }_{\mathrm{i}=1}^5\mathrm{S}\mathrm{S}\mathrm{i}-\mathrm{S}\mathrm{S}6}{1\mathrm{M}\mathrm{J}\mathrm{o}\mathrm{f}{\mathrm{H}}_2\mathrm{p}\mathrm{r}\mathrm{o}\mathrm{d}\mathrm{u}\mathrm{c}\mathrm{t}\mathrm{i}\mathrm{o}\mathrm{n}}}.\end{array}$$

(10)

Here, SS1 to SS5 represent the CO₂ emissions from each process step involved in producing 1 MJ of H₂, and SS6 represents the amount of CO₂ recovered and recycled within the system. Increasing the quantity of CO₂ recovered and recycled in SS6 directly reduces the GWP.

In addition, the reuse of the recovered CO₂ enhances the gasification efficiency, thereby increasing H₂ production. This increase in H₂ output results in a relative decrease in the total CO₂ emissions from SS1 to SS5 per unit of H₂ produced. Consequently, the reduction in GWP is the combined result of (i) direct CO₂ removal from the system boundary and (ii) the indirect effect of improved process efficiency. This combined mechanism constitutes the “synergistic effect” referred to in the manuscript.

Furthermore, the calculation accounts for energy penalties, including heat losses occurring during heat exchange in the dryer and heat exchanger units, ensuring that the GWP values reflect realistic process performance.

3. Results

3.1. Sensitivity Analysis Results

3.1.1. Effect of Reformer Temperature

A sensitivity analysis of the reformer temperature was conducted in the range from 973 K, where carbon deposition is unlikely to occur, to 1373 K, which is the heat-resistance temperature of the furnace [35]. The S/C ratio was set to 1.4, as under conventional operating conditions.

Figure 5a and

Table 9. Simulation results.

Reformer temperature [K]	973	1073	1173	1273	1373
GWP [g-CO2 eq./MJ-H2]
SS1	2.70	2.48	2.14	1.58	1.46
SS2	84.1	74.9	67.0	61.3	58.3
SS3	7.94	7.09	6.30	5.63	5.34
SS4	0.313	0.551	0.92	1.28	2.03
SS5	122	119	111	89.5	85.8
BECCU	−157	−153	−143	−116	−111
Total	59.3	50.2	43.8	43.4	41.9
H2 production [MJ-H2/kg-SS]	5.17	5.62	6.51	8.83	9.59
CGE [%]	60.9	64.1	67.3	71.4	74.2
Auxiliary power [kW/MJ-H2]
SS1	16.9	15.6	13.4	9.9	9.1
SS2	263	243	209	155	142
SS3	27.4	25.2	21.7	15.9	14.6
SS4	1.68	3.19	5.51	7.9	12.6
SS5	762	744	693	562	538
Total	1072	1030	943	750	717
recycled CO2 [%]	57.6	61.0	66.0	72.4	75.4
Char reaction rate [%]
recycled CO2	0.00546	0.0444	0.225	0.627	1.60
pyrolysis CO2	0.00179	0.0137	0.0646	0.164	0.402
others	0.0773	0.505	2.47	7.23	19.2
Total	0.0846	0.563	2.76	8.02	21.2
Tar reaction rate [%]
recycled CO2	9.81	18.9	24.9	24.4	24.6
pyrolysis CO2	3.22	5.85	7.13	6.38	6.17
others	10.0	23.5	36.0	44.1	52.6
Total	23.0	48.3	68.0	74.9	83.4

show that increasing the reformer temperature results in a significant reduction in the GWP. Specifically, increasing the temperature from 973 to 1373 K reduced the GWP from 59.3 g-CO₂ eq./MJ-H₂ to 41.9 g-CO₂ eq./MJ-H₂, representing a reduction of approximately 29%. This result demonstrates that BECCU, which utilizes CO₂ derived from biomass and recovered through a 2-step PSA process as a gasifying agent within the same process, effectively reduces the CO₂ intensity of green H₂ production.

The reduction in GWP can be attributed to the synergistic effect of reusing recovered CO₂ as a gasifying agent and high-temperature operation, both of which improve gasification efficiency and increase H₂ production. The reuse of CO₂, which was not utilized in the conventional process, as a gasifying agent promoted the decomposition of char and tar. As the reformer temperature increased, the total char reaction rate rose significantly from approximately 0% to 21.2%, and the total tar reaction rate increased from 23.0% to 83.4% (Table 9).

In this gasification process, although the overall reaction with steam predominates, as shown in Figure 5d, the contribution of recycled CO₂, central to this study, increases significantly with increasing temperature.

The reason for this is the increase in CO₂ concentration during the process. As shown in Figure 5b, CO at the reformer outlet is converted to CO₂ in the subsequent HTS and LTS processes. Therefore, as the reformer temperature increases and more char and tar are decomposed, a greater amount of CO₂ is generated and recovered throughout the process. The recycled CO₂ was reused as a gasifying agent, creating a positive cycle that promoted the decomposition of char and tar. Regarding methane reforming, steam reforming was the dominant process because of the presence of steam in the atmosphere, whereas dry reforming occurred only minimally. This improvement directly increased gasification efficiency, leading to higher H₂ production per unit of feedstock. As shown in Table 9 and Figure 5a, H₂ production increased approximately 1.9 times, from 5.17 MJ/kg-SS (973 K) to 9.59 MJ/kg-SS (1373 K). Because more H₂ can be produced from the same amount of feedstock, the relative environmental impact per MJ of H₂, that is, the GWP, was significantly reduced.

Additionally, the improvement in gasification efficiency resulted in enhancements in CGE and auxiliary power. The CGE increased from 60.9% to 74.2% as the reformer temperature increased (Table 9 and Figure 5c). This indicates that the chemical energy of the feedstock was converted more efficiently into H₂ and CO at high temperatures. In contrast, the 2-step PSA, which is central to the BECCU, remains the primary source of power consumption, accounting for approximately 70% of the entire process (Table 9). In this simulation, the overall power consumption increased due to higher H₂ production, driven by the larger volume of processed syngas. However, when considering energy consumption per purified H₂, the total auxiliary power required to produce 1 MJ of H₂ decreased from 1072 kW at 973 K to 717 kW at 1373 K (Figure 5c).

From the above, it can be concluded that the introduction of BECCU and the increase in reformer temperature are effective in reducing the GWP in AGM plants. However, operating above the furnace’s heat-resistance temperature may cause damage to the furnace and shorten its lifespan [36]. In practice, in the demonstration plant of the AGM, SUS304 was used as the furnace material, with a maximum heat-resistance temperature of 1673 K; however, during actual operation, the operating temperature was reduced to below 1273 K. Furthermore, furnaces capable of withstanding higher temperatures generally incur increased costs. Therefore, it is necessary to select furnace materials and designs while considering the trade-offs between operating temperature requirements, durability, and economic factors.

3.1.2. Effect of S/C

A sensitivity analysis of the S/C ratio was conducted within the range from 1.4, which is the conventional operating condition, to 4.0, which can be generated through heat exchange with the hot gas after the reformer. The S/C ratio of less than 1.4 was not considered because carbon deposition may occur [37]. The reformer temperature was set to 1173 K under conventional operating conditions.

As shown in Figure 6a and

Table 10. Results of the simulation.

S/C ratio	1.4	2.0	3.0	4.0
GWP [g-CO2 eq./MJ-H2]
SS1	2.14	2.06	2.01	2.00
SS2	67.0	65.0	63.6	63.0
SS3	6.30	6.10	5.96	5.91
SS4	0.915	0.721	0.566	0.492
SS5	111	114	116	117
BECCU	−143	−148	−151	−152
Total	43.8	40.3	37.9	37.0
H2 production [MJ-H2/kg-SS]	6.51	6.78	6.94	6.98
CGE [%]	67.3	67.6	67.9	68.1
Auxiliary power [kW/MJ-H2]
SS1	13.4	12.9	12.6	12.5
SS2	209	201	197	195
SS3	21.7	20.8	20.3	20.2
SS4	5.51	4.19	3.03	2.38
SS5	693	674	675	675
Total	943	913	907	905
recycled CO2 [%]	66.0	71.0	74.0	74.9
Char reaction rate [%]
recycled CO2	0.225	0.178	0.116	0.0772
pyrolysis CO2	0.0646	0.0474	0.0296	0.0195
others	2.47	2.86	3.21	3.32
Total	2.76	3.09	3.35	3.42
Tar reaction rate [%]
recycled CO2	24.9	18.4	10.64	6.33
pyrolysis CO2	7.13	4.91	2.72	1.60
others	36.0	45.9	57.1	63.2
Total	68.0	69.2	70.4	71.1

, increasing the S/C from 1.4 to 4.0 reduced the GWP from 43.8 g-CO₂ eq./MJ-H₂ to 37.0 g-CO₂ eq./MJ-H₂. This reduction in GWP is attributed to the gradual increase in H₂ production from 6.51 MJ/kg-SS to 6.98 MJ/kg-SS. Thus, increasing the S/C ratio was found to be an effective means of reducing GWP.

The primary reason for the increase in H₂ production is the promotion of the water–gas shift reaction (WGS). An increase in the amount of steam input caused the WGS equilibrium to shift significantly toward the product side (right side). This promoted the conversion of CO to H₂, resulting in an improved final H₂ yield. This is supported by the increase in H₂ concentration after LTS, accompanied by an increase in the S/C ratio, as shown in Figure 6b.

However, the gasification reaction pathways of char and tar differed from those at the reformer temperature. As shown in Figure 6d, increasing the S/C ratio reduced the contribution of gasification by recycled CO₂. This is believed to be because the abundant steam competes with CO₂ in the gasification reaction with char and tar, exerting a dominant effect. In other words, it can be suggested that H₂ production under these conditions relied more on the conventionally known “gasification by steam” and “WGS reaction” than on “gasification by CO₂,” which is the core mechanism of BECCU.

Additionally, their effects on the CGE and auxiliary power are limited. The CGE improved slightly from 67.3% to 68.1%; however, the total auxiliary power required to produce 1 MJ of H₂ decreased slightly from 943 kW to 905 kW (Figure 6c). This is believed to be due to the limited increase in H₂ production and the increased load on the 2-step PSA resulting from the higher CO₂ production caused by the WGS.

Based on the above, although the reduction in GWP from increasing the S/C ratio is primarily due to the promotion of WGS rather than the effect of BECCU, it has proven to be an effective strategy in AGM plants; it reduces GWP through increased H₂ production and negative emissions resulting from CO₂ recovery. In particular, increasing the S/C ratio is effective because it enables the efficient utilization of waste heat after reforming. However, H₂ production and GWP tend to converge, and excessive steam addition leads to a drop in the reformer temperature, resulting in the combustion of H₂ and CO, which in turn increases the GWP. In addition, the amount of steam that can be generated through heat exchange with the hot gas after reforming is limited. Using external fossil energy to generate supplementary steam would damage the GWP.

3.2. Effectiveness of 2-Step PSA

To demonstrate the effectiveness of the BECCU system proposed in this study, which utilizes CO₂ recovered through a 2-step PSA process in the same H₂ production gasification process, three different scenarios were considered (see

Table 11. 2-step PSA effectiveness comparison.

Case	Case 1	Case 2	Case 3 (This Study)
	AGM + PSA	AGM + 2-Step PSA	AGM + 2-Step PSA + Reuse As a Gasifying Agent
GWP [g-CO2 eq./MJ-H2]	156	140	43.8
H2 production [MJ-H2/kg-Feedstock]	6.39	6.75	6.51
CGE [%]	65.4	65.4	67.3
Auxiliary power [kW/MJ-H2]	759	556	943

). Their performances were compared and evaluated under identical conditions: a reformer temperature of 1173 K and an S/C ratio of 1.4, ensuring a fair comparison. The schematics of the process and stream data tables for Case 1 and Case 2 are provided in the Appendix A. The schematic of the process and stream data table for Case 3 are shown in Figure 3 and Table 4, respectively.

Case 1 represents the conventional AGM configuration, in which a single-step PSA is used only for H₂ purification. As a result, the auxiliary power due to gas compression becomes very large. In addition, CO₂ is not recovered, and all off-gas containing CO₂ other than H₂ is sent to the combustor. The PSA is operated at high pressure, and according to the report by Nakayama et al. [18], the auxiliary power is 4.17 kW/kg-H₂ and the H₂ recovery efficiency is 74.0%.

Case 2 introduces a 2-step PSA system that divides the purification process into two stages. This enables low-pressure operation, thereby reducing the auxiliary power consumption (from 759 to 556 kW/MJ-H₂). CO₂ is recovered as a single high-purity stream, which is assumed to be used externally (for example, as a growth agent in agricultural facilities). Since this utilization occurs outside the system boundary, CO₂ is regarded as carbon neutral in the LCA, and no negative emission credit is applied in the GWP calculation.

The focus of this study, Case 3, is based on Case 2 but features the reuse of recovered CO₂ as a gasifying agent within the same H₂ production AGM process. This increases the CO₂ inflow to the 2-step PSA, resulting in higher auxiliary power (943 kW/MJ-H₂). However, the reused CO₂ promotes the decomposition of char and tar, improving both the cold gas efficiency (CGE) and H₂ yield. Furthermore, because the reused CO₂ is derived from biomass, it is counted as a negative emission in the LCA, directly contributing to a significant reduction in GWP.

Cases 1 and 2 have lower auxiliary power than Case 3 and almost the same CGE, but the remarkable reduction in GWP in Case 3 (down to 43.8 g-CO₂ eq./MJ-H₂) results from the combination of two advantages: improved PSA efficiency through the 2-step PSA and the negative emission effect from CO₂ reuse. This synergistic effect maximizes both environmental and process performance, enabling Case 3 to outperform the other two cases.

At the current stage, a conventional PSA system performs hydrogen separation and recovery in a single step at an adsorption pressure of approximately 1.0 to 2.0 MPa, resulting in a high auxiliary power requirement. In light of this issue, this study examined the two-step PSA as an alternative technology. The two-step PSA divides the separation and recovery into two steps, enabling operation at lower compression pressures and thereby reducing auxiliary power consumption. Furthermore, it can recover CO₂ as a high-purity gas, making it suitable for reuse in the BECCU system. In this study, the effectiveness of the BECCU system was evaluated by reusing the recovered CO₂ as a gasifying agent in the H₂ production process, which enhances gasification efficiency while maximizing the GWP reduction effect. It should be noted that, as the amount of recovered CO₂ increases, the internal power consumption of the two-step PSA also rises; strategies to further reduce this power consumption will be addressed in future work.

The above comparison demonstrates that BECCU, in the same H₂ production process using 2-step PSA, not only recovers and utilizes CO₂ with a low environmental impact but also maximizes the environmental impact reduction by reusing it as a gasifying agent to promote gasification. This is due to the synergistic effect of two mechanisms: direct GWP reduction through CO₂ recovery and indirect GWP reduction through improved gasification efficiency. Therefore, BECCU, which reuses recovered CO₂ as a gasifying agent for H₂ production in AGM, can be considered effective in reducing CO₂ emissions per unit of energy.

4. Conclusions

In this study, we focused on BECCU, which utilizes CO₂ recovered by 2-step PSA as a gasifying agent to reduce the CO₂ intensity of H₂ production in the AGM. To evaluate the effectiveness of the BECCU in AGM, we conducted a sensitivity analysis of the reformer temperature and S/C ratio using process simulation and LCA, incorporating the results from tar gasification experiments.

Sensitivity analysis revealed that increasing the reformer temperature is a highly effective strategy for reducing the GWP. This improvement is attributed to the enhanced gasification of char and tar, particularly through the reuse of recycled CO₂ as a gasifying agent, which improves the overall process efficiency, such as the CGE and auxiliary power. Increasing the S/C also reduced the GWP, but this effect was primarily due to the promotion of the WGS reaction rather than the CO₂ gasification central to the BECCU concept.

Furthermore, a comparative analysis demonstrates the superiority of the proposed in-process BECCU system (Case 3), which achieved the lowest GWP. By considering this BECCU system, the GWP can be reduced by more than 50% compared with the conventional process. Its effectiveness stems from a synergistic effect: (1) direct GWP reduction by capturing carbon-neutral CO₂ using a low-environmental-impact 2-step PSA, and (2) indirect GWP reduction by improving the gasification efficiency of char and tar by reusing the captured CO₂ as a gasifying agent.

Therefore, this study concludes that implementing a BECCU system with in-process CO₂ recycling, especially when combined with high-temperature operation, is a promising and practical approach for significantly reducing the environmental impact of green H₂ production in AGM plants.

In this study, to simplify the calculations, the heat required for drying the sewage sludge and the auxiliary power for the 2-step PSA were estimated using theoretical values and constants. However, the actual heat required for drying varies depends on factors such as the method of supplying hot air, the surface area of the feedstock, and the auxiliary power for the 2-step PSA, which also depends on the flow rate and composition of the process gas. Currently, the GWP of the entire AGM process is primarily driven by the drying process and the power consumption of the 2-step PSA. Therefore, future work will focus on conducting a more detailed analysis of these factors and proposing specific methods to further reduce GWP from an LCA perspective.