# Cleaner steelmaking using biomass: A novel ironmaking process

Tao Wang, Olivier Mirgaux, Fabrice Patisson

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Tao Wang, Olivier Mirgaux, Fabrice Patisson. Cleaner steelmaking using biomass: A novel ironmaking process. Chemical Engineering Science, 2026, 319, pp.122319. 10.1016/j.ces.2025.122319. hal-05287187

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# Cleaner steelmaking using biomass: A novel ironmaking process

Tao Wang, Olivier Mirgaux, Fabrice Patisson

University of Lorraine, Jean Lamour Institute, Campus Artem, Nancy, France

## ARTICLE INFO

**Keywords:**

Ironmaking

Biomass

Direct reduction

Shaft furnace

Life Cycle Assessment (LCA)

TGA

## ABSTRACT

The iron- and steelmaking industry contributes significantly to greenhouse gas emissions because steel is produced in large quantities, and fossil coal is used as the energy source and reducing agent for this production. Substituting biogenic carbon from biomass for fossil coal could drastically reduce the contribution of the iron- and steelmaking industry to global warming. Based on biomass, we propose a novel, breakthrough ironmaking process (BIORED), in which charcoal lumps and iron ore pellets are loaded at the top of a shaft reactor. CO, the reducing agent that converts iron oxide ore to metallic iron, is produced in situ by charcoal gasification. The exhaust gas mixture (CO–CO₂) is recycled for CO reuse and energy savings. The feasibility of such a process was investigated following a modeling approach that involves laboratory experiments. The results show that charcoal is devolatilized at the top and gasified at the bottom, whereas iron ore is reduced along the shaft, reaching a satisfactory metallization degree at the bottom. A specific experimental protocol was designed for the validation of the model, and the experimental results agreed with the computed results. The environmental performance of the BIORED-based steelmaking route was compared with that of the conventional route via life cycle assessment. The new route emits up to 8 times less CO₂ and has lower impacts on most of the other environmental categories.

## 1. Introduction

The steelmaking industry is responsible for 7 % of global greenhouse gas (GHG) emissions and 10 % of global anthropogenic CO₂ emissions, mostly through the blast furnace (BF)-basic oxygen furnace (BOF) route, which accounts for 70 % of global crude steel production (Iron and steel roadmap International Energy Agency, 2020). Blast furnaces typically emit 1.5 to 1.8 tCO₂ per t of hot metal produced (Wang et al., 2017).

Given the growing energy shortage and greenhouse effect, incorporating renewable energy into existing metallurgical processes has become crucial. Since the coking and sintering processes before BF are considered costly and continue to cause environmental concerns, non blast-furnace-based ironmaking technologies have been developed over the past few decades, among which the direct reduction (DR) of iron ore is considered a promising, lower CO₂-emitting iron production process (Fan and Julio Friedmann, 2021; Sun et al., 2024). In addition, its product (DRI) has the advantages of high iron content and stable composition, which can compensate for the shortage of high-quality scrap as raw material for the electric arc furnace (EAF) process (Yi et al., 2012). Among direct reduction technologies, the gas-based direct reduction process is environmentally friendly, with lower carbon dioxide emissions and lower energy consumption than coal-based DR

processes. DRI production via gas-based shaft furnace DR processes (MIDREX and HYL/ENERGIRON) accounted for approximately 74 % of the global DRI production in 2019 (MIDREX, World steel dynamics, 2019). A possible way to further decrease CO₂ emissions is to use pure green hydrogen instead of the current H₂–CO syngas obtained from fossil natural gas; many projects and publications are reported in this direction (Patisson and Mirgaux, 2020).

An alternative is the use of biomass. Biomass is renewable and widespread, and owing to its short carbon cycle, its biogenic carbon can be considered neutral with respect to climate change if the resource is grown and used in a sustainable manner. Biomass can thus reduce the share of the iron- and steelmaking industry in the context of global warming (Suopajärvi et al., 2017). The applications of biomass in the BF–BOF route have been extensively investigated since the 1970s, including injecting biomass into blast furnaces, mixing coal and biomass in the coking plant or directly replacing coke partially as bed material (MacPhee et al., 2009; Fick et al., 2014; Wang et al., 2015). The benefit in terms of reducing CO₂ emissions remains limited because only a fraction of fossil carbon can be substituted. In addition to the BF–BOF route, interesting basic studies have focused on the reduction behavior of various iron oxide–biomass mixtures at the laboratory scale. Strezov (Strezov, 2006) carried out experiments on iron ore reduction with

<footnote>* Corresponding author.</footnote>

<footnote>E-mail addresses: tao.wang@univ-lorraine.fr (T. Wang), olivier.mirgaux@univ-lorraine.fr (O. Mirgaux), fabrice.patisson@univ-lorraine.fr (F. Patisson).</footnote>
sawdust under an inert atmosphere. With increasing sawdust fraction, the iron ore is better reduced. From 30 wt% biomass, metallic iron is obtained predominantly. Hata et al. (Hata et al., 2009) mixed biotars with three dehydrated ores and heated them to 900 °C under a N₂ atmosphere for the complete reduction of iron oxide with deposited carbon via direct reduction. Zuo et al. (Zuo et al., 2013) analyzed the mechanism of iron ore reduction by biomass char, coal and coke in an argon atmosphere. The reaction temperature of hematite reduced by biomass char was at least 100 K lower, the maximum reaction rate was 1.57 times higher than that of coal, and the final reduction degree was 13 % greater. Bagatini et al. (Bagatini et al., 2014) explored the reduction of mill scale using four different carbonaceous reductants—charcoal, coal char, blast furnace coke, and petroleum coke— among which charcoal appeared to be the best reductant. Furthermore, they concluded that the Boudouard reaction (C + CO₂ = 2 CO) controlled the rate of self-reduction to at least 60 % on the basis of the values of apparent activation energy at different conversions. Guo et al. (Guo et al., 2015; Guo et al., 2017) performed the direct reduction of iron ore/biomass composite pellets under hydrogen gas and simulated biomass-derived syngas. Biomass addition promoted the growth of the pellet porosity and specific surface area, thus increasing the reducibility and reaction rate.

In the present work, we propose a breakthrough option that combines the direct reduction of iron ore by CO with biomass gasification within a single shaft furnace reactor. CO is produced in situ by biomass gasification according to the Boudouard reaction. The exhaust gas, a CO-CO₂ gas mixture, is recycled as feed gas at the bottom of the shaft (Fig. 1). This process provides an advanced utilization opportunity for various biomass resources; it avoids the use of natural gas or hydrogen, of a reformer such as in the MIDREX DR process, of preparing specific blended pellets, and of building a separate gasification reactor. The right-hand side of Fig. 1 shows the shaft furnace itself, which is similar to a usual iron ore DR shaft furnace with cylindrical and conical sections but fed with both iron ore pellets and charcoal lumps. Although different types of biomass (including raw wood) could in principle be used, for simplification, the present study was limited to charcoal. The solids descend by gravity, and the gas flows countercurrently upward. The left part represents the gas loop. The top gas is conditioned to be recycled, i. e., dedusted and reheated. A fraction of the outlet top gas (the volume

flow rate exceeding that of the bustle gas, i.e., the gas injected at the bottom of the cylinder) is burnt to obtain the heat for reheating the rest of the top gas, from typically 400 to 1100 °C. If necessary, a small flow of oxygen is added to further increase the bustle gas temperature. The present paper reports a feasibility study of a new concept; not all the technical details of an actual pilot or industrial unit were investigated.

In the next sections, the mathematical model written to simulate this furnace is presented, followed by a discussion of the results, including a comparison with laboratory experiments. A life cycle assessment (LCA) of this novel process demonstrated its environmental benefits.

## 2. Mathematical model

### 2.1. Background

The mathematical model of the process is derived from a previous model from our research group, namely, the REDUCTOR model. REDUCTOR aims at simulating the operation of a standard, gas-based, iron ore DR furnace. It describes the gas and solid flow, heat transfer and the chemical reactions involved (Patisson and Mirgaux, 2020; Ranzani Da Costa et al., 2013; Hamadeh et al., 2018). Fig. 2 represents the principle of the model. Some adaptations were made to this model in order to simulate the BIORED process: two solids, the iron ore pellets and the charcoal grains, were considered, instead of the pellets only; the chemical reactions related to biomass (devolatilization and gasification) were added, and, for sake of simplicity, the shaft furnace was considered all cylindrical.

The behavior of the iron ore pellets during their reduction was described using the single pellet kinetic model for the reduction reactions developed by Ranzani da Costa et al. (Ranzani Da Costa et al., 2013), which is not recalled here. The model depicting the charcoal grain evolution is illustrated by Fig. 3. When heated, the charcoal grains first experience the loss of volatile matter, producing gases such as CO, CO₂, H₂ and H₂O. Next, the gasification of fixed carbon occurs, consuming CO₂ and releasing CO in the bulk gas.

### 2.2. Main assumptions

The following assumptions, made for REDUCTOR, were also used in

<figure><img src="image_2.png" /><figcaption>**Fig. 1.** Scheme of the biomass-based iron ore direct reduction (BIORED) concept.</figcaption></figure>
<figure><img src="image_3.png" /><figcaption>Fig. 2. Diagram showing the principle of the standard REDUCTOR model (Patisson and Mirgaux, 2020).</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Fig. 3. Evolution of a charcoal grain.</figcaption></figure>

the model of the biomass-based shaft furnace. The model is steady-state and 2-dimensional. The solids descend in plug flow and the gas flows through the porous solid bed. The initial iron ore pellets (diameter 1.5 cm) are composed of dense $Fe_2O_3$ (density 5275 kg/m³) grains (diameter 19 µm), separated by a porosity of 0.33 with an average pore size of 6 µm. The porosity of the bed remains constant (equal to 0.5). The reaction heats are dissipated in the solids, no temperature gradients occur inside the pellets. The reactions R1 to R6 are of first order with respect to the gaseous reactants. Wustite is considered as $Fe_{0.95}O$ (see Table 1 hereafter).

In this first approach to model the BIORED shaft furnace, we make further simplifying assumptions, as follows. The furnace is limited to the

cylindrical zone. There are no direct physical and chemical interactions between charcoal grains and pellets. The initial charcoal grains are of cylindrical shape (diameter 10 mm, length 15 mm) with a density of 750 kg/m³. The proximate analysis of the charcoal is: fixed carbon 74.5 %, volatile matter 25 %, and ash 0.5 %. The volume fractions of both the pellets and charcoal in the bed are constant, as well as their velocities, as a consequence of taking the bed porosity constant throughout. Furthermore, the charcoal grains are assumed not to break or produce fines by attrition. The later assumption is indeed a first-approach simplification. However, the situation is similar (superficial velocity, pressure, particles) to that of the top part of charcoal blast furnaces, which are routinely operated.

<table><caption>**Table 1**
Main reactions considered in the model.</caption><tr><td>R1</td><td>3Fe<sub>2</sub>O<sub>3</sub>(s) + CO(g) → 2Fe<sub>3</sub>O<sub>4</sub>(s) + CO<sub>2</sub>(g)</td></tr><tr><td>R2</td><td>Fe<sub>3</sub>O<sub>4</sub>(s) + <sup>16</sup>/<sub>19</sub>CO(g) → <sup>60</sup>/<sub>19</sub>Fe<sub>0.95</sub>O(s) + <sup>16</sup>/<sub>19</sub>CO<sub>2</sub>(g)</td></tr><tr><td>R3</td><td>Fe<sub>0.95</sub>O(s) + CO(g) → 0.95Fe(s) + CO<sub>2</sub>(g)</td></tr><tr><td>R4</td><td>3Fe<sub>2</sub>O<sub>3</sub>(s) + H<sub>2</sub>(g) → 2Fe<sub>3</sub>O<sub>4</sub>(s) + H<sub>2</sub>O(g)</td></tr><tr><td>R5</td><td>Fe<sub>3</sub>O<sub>4</sub>(s) + <sup>16</sup>/<sub>19</sub>H<sub>2</sub>(g) → <sup>60</sup>/<sub>19</sub>Fe<sub>0.95</sub>O(s) + <sup>16</sup>/<sub>19</sub>H<sub>2</sub>O(g)</td></tr><tr><td>R6</td><td>Fe<sub>0.95</sub>O(s) + H<sub>2</sub>(g) → 0.95Fe(s) + H<sub>2</sub>O(g)</td></tr><tr><td>R7</td><td>CO<sub>2</sub>(g) + C(s, pellets) ↔ 2CO(g)</td></tr><tr><td>R7'</td><td>CO<sub>2</sub>(g) + C(s, charcoal) ↔ 2CO(g)</td></tr><tr><td>R8</td><td>C<sub>0.21</sub>O<sub>0.51</sub>H<sub>1.74</sub> → 0.56H<sub>2</sub>(g) + 0.23H<sub>2</sub>O(g) + 0.06CO(g) + 0.11CO<sub>2</sub>(g) + 0.04CH<sub>4</sub>(g)</td></tr></table>

## 2.3. Chemical reactions

Table 1 lists the main reactions included for the reduction of iron ore pellets and the devolatilization and gasification of the charcoal grains. Both the reduction reactions by CO (R1 to R3) and H₂ (R4 to R6) are considered. However, as the results will show, the later ones remain marginal, limited to the top zone where H₂ is produced by the charcoal devolatilization (R8).

Gasification (Boudouard reaction) (R7 and R7') impacts charcoal and pellets differently. Carbon deposition on the pellet surfaces is prevalent at low temperatures at the top of the reactor, while the direct Boudouard reaction of charcoal serves as the source of CO at high temperatures at the bottom of the reactor. Although marginal, the reduction reactions
involving H₂ (R4 to R6) are also taken into account. The reaction kinetics for these processes are detailed in (Wang, 2022).

## 2.4. Balance equations

The model employs the finite volume method to numerically solve the local conservation equations for mass, energy, and momentum. These equations are detailed in the Appendix.

# 3. Numerical results

Our objective was to simulate the BIORED shaft furnace from both industrial and commercial perspectives. Accordingly, the operating data and shaft dimensions were chosen representative of an industrial DR process. For instance, the solid flow rate corresponds to approximately 1 million tons per year of iron ore pellets treated and 0.72 million tons of DRI produced annually. The main characteristics of the reactor are detailed in Fig. 4. The other input data were obtained after preliminary trial-and-error runs. At the gas inlet, high temperature, high gas flow rate and more CO than CO₂ were found necessary. The simulations involved a mixture of iron ore pellets and charcoal grains fed at room temperature from the top, along with a CO–CO₂ gas mixture introduced at 1100 °C from the bottom. Although the model is two-dimensional, the uniform inlet gas flow at the bottom results in one-dimensional behavior, with uniform values across the radius. The results in the following section illustrate the axial evolution of temperatures and gas composition, as well as the reactions of devolatilization and gasification of charcoal lumps and the reduction of iron ore pellets.

### 3.1. Evolution of temperatures and gas compositions

Fig. 5 displays the temperature profiles of the solid and gaseous phases within the reactor. The temperatures of the gas and solid phases are nearly identical, owing to efficient heat transfer (high gas-solid heat transfer coefficient, over 250 W m⁻² K⁻¹, and low solid-to-gas heat capacity ratio, less than 0.4). The only notable difference occurs in the

<figure><img src="image_5.png" /><figcaption>Fig. 4. Main inlet data.</figcaption></figure>

<figure><img src="image_6.png" /><figcaption>Fig. 5. Profile of temperatures along the shaft furnace.</figcaption></figure>

upper section, where the solid is introduced at room temperature and rapidly heated upon entry. The top gas temperature is 392 °C. Throughout most of the reactor, temperatures remain between 700–800 °C. This range of temperatures is high enough for the reduction of hematite to wustite. It is also low enough for the reduction of wustite to iron, as the last step of reduction is thermodynamically adverse at high temperature (see Fig. 8b below). Gasification takes place at the bottom of the reactor (as shown later), driven by the high temperature of the incoming gas. Due to the endothermic nature of gasification (Δ<sub>h</sub>H = 172 kJ/mol at 293 K), the gas temperature quickly drops to 800 °C within approximately 3 m, despite the reducing gas being introduced at 1100 °C. The observed temperature plateau mirrors the “thermal reserve zone” in the higher part of a blast furnace, where the balance between coke gasification and iron ore reduction maintains a steady temperature.

Regarding the composition of gases (Fig. 6), H₂ and H₂O were not initially present in the reducing gas but are generated through the devolatilization reaction shortly after the solid inlet, where the cold charcoal is heated by the hot gas. The volatile matter constituted 25 wt% of the charcoal, with the pyrolysis gas consisting of 56 vol% H₂ and 23 vol% H₂O. The devolatilization reaction occurs rapidly, leading to a swift release of H₂ and H₂O. The maximum concentration of H₂ reaches approximately 2.6 % of the gas. However, H₂ is oxidized to H₂O during the reduction of hematite to magnetite, so the concentrations of both H₂ and H₂O are influenced by both devolatilization and reduction reactions.

The production of CO and CO₂ through devolatilization is minimal compared to the amounts generated by gasification. The composition of the CO–CO₂ gaseous mixture, which constitutes over 95 % of the gas in the reactor, is primarily influenced by the reduction of iron ore pellets and the reversible Boudouard reaction. The reducing gas mixture is introduced at the bottom, where CO accumulates due to the gasification reaction, which initially proceeds faster than the reduction reaction. However, this accumulation quickly halts as the gasification rate decreases with temperature, leading to a scenario where the reduction of wustite consumes more CO than is produced by gasification. Consequently, after reaching a peak, the CO concentration declines due to the stepwise reduction process. In the upper section of the reactor, a sharp decrease in CO concentration is observed, corresponding to the initial reduction step from hematite to magnetite. At the top, the exhaust gas still contains significant amounts of CO and CO₂, indicating potential for
<figure><img src="image_7.png" /><figcaption>Fig. 6. Profile of the gas compositions along the shaft furnace: (a) H₂ and H₂O, (b) CO and CO₂.</figcaption></figure>

recycling this gas (Fig. 1), even if the top gas composition differs somewhat from that of the bustle gas (CO and CO₂ fractions, small amount of H₂ and H₂O in the top gas). A composition adjustment device (e.g. CO₂ and H₂O abatement) may be considered.

## 3.2. Charcoal lumps

The charcoal lumps considered in our simulations were composed of 25 % volatile matter and 75 % fixed carbon. In the simulated furnace, the temperature of the solid increases to 700 °C within approximately one meter, and the release of volatile matter occurs very rapidly upon heating. Fig. 7 shows that the conversion of charcoal reached 25 % after full devolatilization. Liu et al. (Liu et al., 2004) reported that coal

devolatilization and iron oxide reduction occur simultaneously during the heating of a coal-iron ore mixture. The charcoal was prepyrolyzed, so the formation of bio-oil was not expected to occur. The produced gases are CO₂, CO, H₂, H₂O and CH₄ (Khasraw et al., 2021). Methane is present at too low a concentration to influence the reactor. Nevertheless, H₂ plays a role in the reduction of iron ore pellets because its production cannot be neglected and because the reduction by H₂ is faster than that by CO. The small amounts of CO and CO₂ released via devolatilization merge into the CO–CO₂ atmosphere. Due to the counterflow of gas and solid, devolatilization affects only the first meter of the reactor, after which the gas exits as exhaust.

The gasification of the fixed carbon in the charcoal lumps serves as the primary source of the reducing agent CO. The results indicate that the Boudouard reaction begins effectively around 700 °C in the middle of the reactor and gradually accelerates with increasing temperature. At the bottom, the gasification rate significantly increases due to higher solid temperatures. Compared to devolatilization, gasification proceeds much slower and extends over more than ten meters, with the conversion remaining incomplete at the bottom. Gasification accounts for 98 % of CO production, while devolatilization contributes only to 2 % of CO production.

The charcoal conversion at the bottom is 0.62, meaning that 38 % of the charcoal introduced remains and should be recycled. A possibility for its recovery is to arrange a magnetic separation between the iron pellets and the charcoal downstream from the exit.

The properties of charcoal can vary significantly depending on the type of biomass and the conditions under which it is pyrolyzed. As a result, different charcoals may exhibit varying reactivities during gasification. To better understand how gasification kinetics influence reactor behavior, we conducted a comparison between oak charcoal and other biomass charcoals documented in the literature. This point will be further discussed in the sensitivity analysis section.

<figure><img src="image_8.png" /><figcaption>Fig. 7. Conversion of charcoal along the shaft furnace.</figcaption></figure>

## 3.3. Evolution of iron ore pellets

The pellets are swiftly heated by the hot gas within the first meter of the shaft, initiating the reduction process immediately. The reduction of iron ore pellets proceeds in three stages: Fe₂O₃→Fe₃O₄→FeO→Fe, occurring throughout the entire height of the shaft (Fig. 8a). Liu et al.
<figure><img src="image_9.png" /><figcaption>Fig. 8. Evolution of the composition of the pellets along the shaft furnace (a) and the thermodynamic path in the Chaudron diagram (b).</figcaption></figure>

(Liu et al., 2004) noted that a mixture of coal and iron ore also undergoes this stepwise reduction process.

Hematite is rapidly and fully converted to magnetite within the first meter of the reactor because this initial reduction step with CO is thermodynamically favorable, even at the relatively low temperature of approximately 500 °C. Additionally, the H₂ produced from the devolatilization of charcoal lumps accelerates this reduction process and is entirely consumed in converting hematite to magnetite. The subsequent reduction of magnetite to wustite by CO occurs over the next four meters. This second step is slower than the first. The final reduction step, from wustite to metallic iron, is the slowest and requires the remainder of the reactor to achieve a satisfactory degree of metallization. This highlights the importance of residence time, which should be carefully chosen—through adjustments in solid flow rate or reactor dimensions—to ensure sufficient time for the reduction reactions. However, in the last meter near the exit, the metallic iron undergoes slight reoxidation. As illustrated in the Chaudron diagram (Fig. 8b), the thermodynamic conditions throughout most of the pellets' descent favor the formation of metallic iron. The exception is the final meter, where the pellets enter the wustite stability domain. Therefore, it is crucial to control the CO/(CO + CO₂) ratio to prevent reoxidation at the reactor's end.

### 3.4. Sensitivity analysis

The initial results quickly demonstrated that gasification and reduction occur in separate zones within the reactor. Gasification takes place at the bottom, near the gas inlet, because it requires higher temperatures to proceed at a significant rate. When gasification occurs, it lowers the temperature due to its endothermic nature. Consequently, the most critical operating parameters are the gas inlet temperature and composition. Below, we present the effects of these parameters, along with the impact of the gasification rate. The simulation results discussed previously serve as the reference case, labeled "Ref" while alternative simulations are referred to as "New".

#### 3.4.1. Effect of inlet gas temperature

Fig. 9 illustrates the effect of an increase in the gas inlet temperature from 1100 °C to 1150 °C. Even with a higher gas temperature than the reference case, the cooling effect of gasification led to a similar temperature decrease to approximately 800 °C at the same height within the reactor. At the top, the gas temperatures were identical in both cases (394 vs 392 °C). However, the higher gas temperature at the bottom favored the gasification rate, enhancing CO production and resulting in a higher overall CO content compared to the reference case. This led to a complete reduction from hematite to metallic iron (100 % metallization degree) without reoxidation, requiring only 15 m of the reactor (Fig. 9c), compared to 28 m with minimal reoxidation in the reference case

<figure><img src="image_10.png" /><figcaption>Fig. 9. Effect of the inlet gas temperature on solid temperature (a) profile, the CO profile (b) and the solid mass fractions (c).</figcaption></figure>
(Fig. 8a). This means that a lower reactor could be used.

While it might seem advantageous to use an inlet gas temperature higher than 1100 °C, this is not feasible due to the risk of sticking. At high temperatures, DRI pellets tend to adhere to each other, forming clusters that can obstruct or block the solid flow. Although the precise temperature limit is not clearly defined in the literature, it was set at 1100 °C for this study. Clearly, even if the highest temperatures (above 1000 °C) are only reached over 0.3 m at the bottom of the shaft, the maximum value of the inlet gas temperature should be more precisely specified from further studies.

### 3.4.2. Effect of inlet gas composition

To analyze the influence of the concentration of CO at the reactor inlet, a simulation was conducted with a reduced CO concentration, specifically 63 % CO and 37 % CO₂, instead of 65 % CO and 35 % CO₂ in the reference case. The results of this simulation are presented in Fig. 10. With a CO volume fraction of 63 %, the solid temperatures remained unchanged, indicating that the gasification rate was not significantly affected. However, the lower inlet CO content reduced the driving force for the final reduction step, bringing the reaction closer to thermodynamic equilibrium. As a result, while hematite was reduced to wustite similarly to the reference case, the reduction of wustite to iron was slower, and reoxidation was enhanced due to the lower CO concentration. Consequently, the metallization degree did not exceed 85 %. These findings highlight the importance of a high CO content in the inlet gas to achieve a satisfactory degree of metallization.

### 3.4.3. Effect of charcoal reactivity

Not all types of biomass demonstrate the same level of reactivity in the gasification process. To examine the impact of the gasification rate, we made use of the gasification kinetics reported by Klose and Wölki (Klose and Wölki, 2005) for beach wood char, which are roughly ten times faster than the kinetics measured for our oak charcoal lumps. The results are depicted in Fig. 11. The gasification rate was significantly higher than that of the reference case, leading to an increased production of CO (Fig. 11b) and a sharper drop in temperature, down to 800 °C at a height of 1 m (Fig. 11a). Gasification virtually halted at this point. The trends in CO production and iron ore reduction mirrored those observed earlier for a higher inlet gas temperature (refer to Fig. 9). The greater the CO produced was, the higher the reduction rates. Complete metallization occurred 12 m below the solid inlet without any subsequent reoxidation. According to (Bagatini et al., 2014), besides CO production, the reactivity of the reductants also affects the morphology of the iron generated.

The findings regarding the critical role of charcoal gasification kinetics are quite significant. The oak charcoal employed in our

experiments was not specifically designed for the BIORED system, nor were its pyrolysis conditions optimized for gasification at 1100 °C under CO-CO₂ atmospheres. This suggests that there is potential to select and prepare a charcoal specifically tailored for BIORED, which could demonstrate reactivity levels comparable to, or even exceeding, those reported by (Klose and Wölki, 2005).

## 4. Experimental validation

In the absence of a demonstration or pilot-scale facility to experimentally test the BIORED concept and validate the model results, we opted for indirect validation through thermogravimetric analysis (TGA). The thermobalance was equipped with programmable gas flow controllers for CO and CO₂. We varied the composition and temperature of the reactive gas entering the TGA chamber in accordance with the local conditions that the pellets would encounter during their simulated descent in the furnace. Consequently, the measured mass loss over time from the TGA should correspond to the mass loss of a pellet in the shaft furnace over its residence time within the reactor.

### 4.1. Materials

The iron ore pellets used in the experiment were direct reduction grade pellets sourced from CVRD (Vale) in Brazil, with the composition given in Table 2. These pellets are composed of approximately 95 % hematite, 0.13 % wustite, and around 5 % inert oxides. In the event of complete reduction, the expected mass loss is approximately 28.6 %, which serves as a straightforward indicator for assessing the degree of metallization during the experimental procedures. For simplification purposes, the pellets were considered to be perfect spheres.

The thermobalance used was a SETARAM model TG 96 (Ranzani Da Costa et al., 2013; Hamadeh et al., 2018). The programmable mass flow controllers could deliver up to 0.5 L/min (STP) of CO and 0.36 L/min of CO₂.

### 4.2. Experimental method

Achieving a perfect similarity between the calculated industrial shaft conditions and the experimental conditions in the thermobalance was not possible, primarily due to limitations in the gas flow rate. As a solution, we selected the maximum experimental flow rate, calculated the corresponding gas velocity, and determined the inlet gas flow rate for the validation simulation to match this gas velocity, which ranged between 2 and 9 cm/s. Additionally, the solid flow rate for the simulation needed to be adjusted; it was modified in relation to the bed height to ensure a residence time that corresponded to the duration of the

<figure><img src="image_11.png" /><figcaption>Fig. 10. Effect of the inlet gas composition on temperature (a) profile, the CO profile (b) and the solid mass fractions (c).</figcaption></figure>
<figure><img src="image_12.png" /><figcaption>Fig. 11. Sensitivity analysis of the effect of charcoal reactivity.</figcaption></figure>

<table><caption>**Table 2**
Composition of the iron ore pellets.</caption><thead><tr><th></th><th>Oxides</th><th>Fe<sub>2</sub>O<sub>3</sub></th><th>CaO</th><th>MgO</th><th>SiO<sub>2</sub></th><th>Al<sub>2</sub>O<sub>3</sub></th><th>FeO</th><th>S</th><th>P</th><th>Others</th></tr></thead><tbody><tr><th>Mass %</th><td></td><td>94.93</td><td>2.02</td><td>0.8</td><td>1.4</td><td>0.61</td><td>0.13</td><td>0.004</td><td>0.024</td><td>0.08</td></tr></tbody></table>

experiment (21 h). The main characteristics of the resulting simulated case are summarized in Table 3. In this simulation, no H₂ or H₂O was considered. This is thus a simulation of a virtual DR furnace (not the previous DR furnace nor the TGA furnace) in which a pellet meets the same conditions as in the TGA experiment.

The evolution of gas temperature and composition is illustrated in Fig. 12. On the left side, the modeled temperature, used as the experimental set point, shows a close correlation with the temperature monitored during the experiment. On the right side, the gas composition corresponds to both the simulation results and the composition of the inlet gas mixture used in the experiment. Again, these conditions differ from those of the reference simulation and, as will be discussed, are less favorable for achieving complete conversion.

The sample consisted of a single iron ore pellet weighing approximately 7 g, which was placed in a wired platinum crucible. To ensure the elimination of air, the thermobalance was purged twice before the experiment commenced. The apparatus was then directly supplied with a reactive gas of the same composition than that of the top gas of the simulated shaft. Following this, the furnace was heated, and gas was fed into it in accordance with the temperature and gas composition determined by the simulation results.

Fig. 13 compares the appearance of the pellets used, before (hematite pellet) and after (iron pellet) reduction. Except for the color, no significant differences were noticed.

### 4.2.1. Comparison between simulations and experiments

The mass loss of the pellets recorded by TGA, the calculated mass loss and the calculated fractions of the different iron oxides and metallic iron are shown in Fig. 14. The succession of the three reduction reactions clearly appeared in both the calculated mass fractions and measured mass loss curves and these were in quite good agreement. The calculated

peaks for Fe₃O₄ and FeO coincided with the end of the first and second plateaus of the experimental curve (dotted line). Additionally, the experimental mass losses of approximately 3 % and 8 % correspond to the theoretical mass losses associated with the reductions from Fe₂O₃ to Fe₃O₄ and from Fe₂O₃ to FeO. The comparison between the experimental and calculated mass loss is less satisfactory. First, the end points of the curves diverged, with the experimental mass loss reaching approximately 26 % at the end of the experiment. This value is slightly lower than the theoretical 28.6 %, which corresponds to complete oxygen removal, indicating that the reduction of wustite to iron was not fully achieved. The calculated curves set the end of reduction at about 16 h and the iron mass fraction then further increased from 90 to 96 % owing to the gasification of deposited carbon between 15 h and 19 h, not visible in the experimental curve. The carbon deposit also explains the initial delay in calculated mass loss. Then, the kinetics of the wustite-to-iron reaction in the model were taken from previous work corresponding to reduction by H₂ or H₂-CO mixtures (Hamadeh et al., 2018) and these could be refined for reduction by CO alone. Additional complementary measurements would be valuable to support this refinement.

In conclusion, despite few differences between the experimental results and the simulation results, the overall comparison can be considered satisfactory and indirectly validates the model.

## 5. Environmental assessment of the BIORED process

### 5.1. Methodology

To assess the potential environmental benefits of the BIORED process, a life cycle assessment (LCA) was conducted according to the ISO standards. A LCA is a holistic approach that allows us to assess all the different potential impacts on the environment of a given system throughout its life cycle. It is a well-known and recognized methodology that is widely used in industry and in research. Our study was conducted using the commercial software GaBi™.

#### 5.1.1. Goal and scope

Numerous studies have been conducted on steelmaking processes to assess and compare different existing or potential routes, e.g. (Norgate and Langberg, 2009; Burchart-Korol, 2013; Li et al., 2021). In the present study, we performed an attributional LCA of the BIORED-EAF route,

<table><caption>**Table 3**
Inlet data of the simulation for validation via TGA.</caption><tr><td>Height (m)</td><td>0.45</td></tr><tr><td>Diameter (m)</td><td>3.5</td></tr><tr><td>Solid flow rate (kg/s)</td><td>0.23</td></tr><tr><td>Gas flow rate (mol/s)</td><td>14.68</td></tr><tr><td>Solid temperature (°C)</td><td>20</td></tr><tr><td>Gas temperature (°C)</td><td>1200</td></tr></table>
<figure><img src="image_13.png" /><figcaption>Fig. 12. Experimental conditions for the validation experiment.</figcaption></figure>

<figure><img src="image_14.png" /><figcaption>Fig. 13. Two pellets: (a) before and (b) after reduction.</figcaption></figure>

<figure><img src="image_15.png" /><figcaption>Fig. 14. Comparison between experimental mass loss and simulated solid composition and mass loss.</figcaption></figure>

which was compared to the LCA of the classical BF-BOF route. The LCA is highly dependent on the local context, and the results obtained for a given region cannot be generalized or transposed to other locations. For this reason, it was important to clearly define the potential location for BIORED implantation to conduct the LCA. Given that BIORED relies heavily on biomass, the facility should be situated in an area with ample local biomass resources to ensure sustainability and avoid using imported materials. Additionally, as BIORED converts iron ore to DRI, it would be advantageous to locate the plant nearby an iron mine. Such an option would avoid transportation of the iron ore and could enable the mining company to sell DRI instead of ore. After investigating different locations worldwide, we identified Kiruna, Sweden, as a good candidate. Located north of the polar circle, the Kiruna iron ore mine is the largest in Europe, and the surrounding taiga forests provide sufficient local biomass for the process. For consistency, the same location was used for the BF-BOF scenario. Only key results from this study are presented here; further details can be found in (Wang, 2022).

### 5.1.2. Function and functional unit

The BIORED process produces DRI, which is an intermediate product used to produce steel. To facilitate a comprehensive comparison, we decided to include the transformation of DRI into liquid steel through an electric arc furnace in our study. The same approach was adopted for the BF route, which includes a basic oxygen furnace to convert pig iron to liquid steel. The resulting functional unit is the production of 1 ton of liquid steel.
### 5.1.3. System boundaries

We retained a cradle-to-gate approach, which includes all the steps from the extraction of the raw materials to the gate of the steel shop, which delivers the liquid steel (Fig. 15).

As is commonly assumed in LCAs of large production facilities, the construction phase of the infrastructure was not considered. Regarding the colossal amount of product delivered by the plant throughout its life cycle, the impacts of the construction phase are negligible with respect to those of the use phase.

### 5.1.4. Life cycle inventory

Most LCA studies rely on industrial data or commercial databases to establish inventories. For future processes, for which no plant data or commercial databases are available, models and calculations are good ways to produce missing data. Thus, for the BIORED process, the results from our model were used, whereas the remaining processes were modeled using GaBi™ software. Common processes such as transportation or electricity were obtained from the Ecoinvent database 7.1. The Swedish electricity mix is mainly derived from hydro- and nuclear power plants, with a growing contribution from windmills. More specific processes were modeled from dedicated literature data. When data for Sweden were not available, European data were used.

### 5.1.5. Life cycle impact assessment method

The impact assessment was performed with the ReCiPe v1.08 midpoint indicator method. The different categories of impacts are as follows: climate change (with and without biogenic CO₂), fine particulate matter formation, fossil depletion, freshwater consumption, freshwater eutrophication, freshwater ecotoxicity, human toxicity (cancer and noncancer), terrestrial acidification, ionizing radiation, land use, marine ecotoxicity, marine eutrophication, metal depletion, photochemical oxidant formation (ecosystem and human health), ozone depletion, terrestrial acidification, and terrestrial ecotoxicity.

## 5.2. LCA results

The results of the impact assessment of a BIORED-based steelmaking plant located at the Kiruna mine are reported in Fig. 16. These results are presented as percentages of the total impact in each considered category to best interpret the contributions of the different steps of the route, and the absolute values are also reported on the graph. The category climate

change is presented with or without the consideration of biogenic CO₂ (CO2b), as proposed by the ReCiPe method. In the context of our study, the interest is in the category that excludes biogenic CO₂, as biogenic CO₂ is supposed to have limited effects on climate change.

For most categories, the main impacts are generated by pellet production, a high-temperature process upstream of the shaft furnace. The only exceptions concern the impacts on freshwater eutrophication, climate change and photochemical oxidant formation, which are dominated by the EAF. This can be easily explained by the high consumption of electricity by the EAF, which is supplied by the Swedish mix. In particular, this mixture is highly dependent on hydroelectricity, which has important consequences for freshwater eutrophication. The production of charcoal ranks third for most categories, with the exception of terrestrial ecotoxicity. A stronger influence on land use could have been anticipated because of the massive use of wood for charcoal production. Nevertheless, this category of impact does not reflect the actual surface of land occupation but rather the damage to the ecosystems involved in the utilization of the land. For forest exploitation, this impact is quite low. The shaft furnace (reactor) itself has relatively low impacts in comparison to the other life cycle phases. In particular, as the main emission source is biogenic CO₂, its impact on climate change is limited.

A similar analysis was conducted for the BF-BOF route (Fig. 17). The results show greater variability across the different stages. As expected, the blast furnace is the main emitter of the route for climate change (no biogenic CO₂ here), accounting for almost 60 % of the emissions. For most of the other categories, the coke oven and the agglomeration process are the main emitters.

In Fig. 18, both routes are compared on the same plot for a selection of relevant categories, with the BF-BOF route normalized to unity. This representation clearly shows that for most categories, the BIORED-EAF route has a significantly lower environmental impact than the traditional BF-BOF route. Specifically, in the climate change category, which is of primary concern, the BIORED-EAF route results in 242 kgCO₂eq per functional unit, whereas the BF-BOF route is responsible for 1928 kgCO₂eq (this is consistent with the literature, e.g. (Tanzer et al., 2020). Only for a limited number of categories BIORED exhibit greater impacts, which can be explained by the use of biomass (land use) and electricity (ionizing radiation and freshwater ecotoxicity).

<figure><img src="image_16.png" /><figcaption>Fig. 15. Process tree and system boundaries.</figcaption></figure>
<figure><img src="image_17.png" /><figcaption>Fig. 16. Contribution of the different steps to the total impact in each category for the BIORED-EAF route.</figcaption></figure>

<figure><img src="image_18.png" /><figcaption>Fig. 17. Contribution of the different phases to the total impact in each category for the classical BF-BOF route.</figcaption></figure>

## 5.3. Conclusion of the LCA

The new BIORED-EAF route has the potential to emit up to eight times fewer GHG than the conventional BF-BOF route, making it a promising option for global warming mitigation. However, this estimate is based on an optimal scenario that includes the plant being located near the mine, utilizing local biomass resources, and relying on Sweden's decarbonized energy mix. When considering a higher carbon intensity energy mix, such as that of Spain (kgCO2eq/kWh), which reflects a more typical European situation, the emissions for the BIORED-EAF route increase to 936 kgCO2eq. This result remains highly competitive when compared with that of the BF-BOF route and is also better than that of the MIDREX-EAF route (Tanzer et al., 2020).

## 6. Conclusions and perspectives

A novel ironmaking process was investigated via a modeling approach. The idea is to directly use biomass (charcoal lumps) and iron ore (pellets) to obtain iron (DRI) within a single reactor, which resembles a typical DR shaft furnace but differs in its feed and gas recycling loop.

An existing DR model was adapted to incorporate charcoal as a second solid, along with the reactions of devolatilization and gasification. Simulations based on this enhanced model revealed that using a sufficiently high bustle gas temperatures and a gas mixture rich in CO, it is theoretically feasible to operate such a reactor and achieve high metallization of the produced DRI. The calculated results elucidate the processes of reduction, devolatilization, and gasification occurring within the shaft furnace. Improvements to the process were suggested, including the use of more reactive charcoal types.
<figure><img src="image_19.png" /><figcaption>Fig. 18. Comparison of the routes for selected categories.</figcaption></figure>

A specific experiment was designed to replicate in a thermobalance the thermal and chemical conditions experienced by a pellet as it descends through the shaft furnace. The comparison of the experimental results with the corresponding calculations is satisfactory.

A life cycle assessment was also performed, and the results revealed a dramatic reduction in GHG emissions and fewer impacts on the environment compared to those of the conventional BF-BOF route. The low CO₂ emissions are mostly due to the use of a carbon-neutral reducing agent and, to a lesser extent, low-carbon electricity.

While the current study predominantly employed mathematical modeling, further pilot-scale experiments are recommended to demonstrate the practical feasibility of the BIORED process prior to any industrial application. An important point to check is that of the adequate mechanical behavior of the biomass. Additionally, exploring the use of unprepared raw materials —such as raw woody biomass instead of charcoal and lump iron ore instead of pellets— could lead to further reductions in process impacts.

## Author Contributions

All authors contributed to the study conception and design, and to the modeling work. The experiments, data collection and numerical simulations were carried out by Tao Wang. The supervision was done by Olivier Mirgaux and Fabrice Patisson. The project administration and funding acquisition was ensured by Fabrice Patisson. The first draft of the manuscript was written by Tao Wang and all authors contributed to previous versions of the manuscript. All authors read and approved the final manuscript.

## CRediT authorship contribution statement

**Tao Wang:** Writing – original draft, Software, Methodology, Investigation, Formal analysis, Data curation, Conceptualization. **Olivier Mirgaux:** Writing – review & editing, Validation, Supervision, Methodology, Investigation, Conceptualization. **Fabrice Patisson:** Writing – review & editing, Validation, Supervision, Software, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization.

## Funding

This work was supported by the French government through the program "Investment in the future" operated by the National Research Agency (ANR), France, and referenced by ANR-11-LABX-0008-01 (Labex DAMAS).

## Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

## Acknowledgments

The authors thank Jean-Baptiste Letz for his help during the experiments, and Camille Sitz, Marc Tronet, Amandine Villa for their preliminary LCA.

## Appendix. Local balance equations

The core equations of the model are the local balances of mass, energy, and momentum. These are listed below, and the notation is explained further below.

The gas flow through the porous solid bed is calculated via a combination of the momentum and gas continuity Eq. (A1) and Ergun Eq. (A2):

$$ \nabla \cdot \left( \frac{C_t}{K} \nabla P \right) = r_7 + r_7 + r_8 \quad (A1) $$
$$ \mathbf{u}_g = -\frac{1}{K} \nabla \mathbf{P} \text{ with } K = \frac{150(1 - \varepsilon_s)^2}{\varepsilon_s^3 d_p^2} \mu_g + \frac{1.75(1 - \varepsilon_s)}{\varepsilon_s^3 d_p} \rho_g \mathbf{u}_g \quad (A2) $$

The gas species circulate by both convection and diffusion, which leads to the molar balance for gaseous species i written as:

$$ \nabla \cdot (C_i \mathbf{u}_g \mathbf{x}_i) = \nabla \cdot (C_i D_g \nabla \mathbf{x}_i) + S_{g,i} \quad (A3) $$

Distinct temperatures for the solids and gas are considered, the two phases exchanging heat by convection. Within each phase, the heat transfer is by convection and conduction. For the gas phase, the resulting balance equation is:

$$ \rho_g c_{pg} \left( u_{gr} \frac{\partial T_g}{\partial r} + u_{gz} \frac{\partial T_g}{\partial z} \right) = \frac{1}{r} \frac{\partial}{\partial r} \left( r \lambda_g \frac{\partial T_g}{\partial r} \right) + \frac{\partial}{\partial z} \left( \lambda_g \frac{\partial T_g}{\partial z} \right) + a_b h (T_s - T_g) + \sum_i S_i \int_{T_g}^{T_s} c_{p,i} dT \quad (A4) $$

The solid species descend by convection only. The mass balances for a species i in a pellet (Eq. A(5) or in a charcoal grain are (A6) as follows:

$$ \nabla \cdot (\varepsilon_{s,p} \rho_{s,p} \mathbf{u}_{s,p} \omega_{j,p}) = S_{s,i} \quad (A5) $$

$$ \nabla \cdot (\varepsilon_{s,ch} \rho_{s,ch} \mathbf{u}_{s,ch} \omega_{j,ch}) = S_{s,i} \quad (A6) $$

The energy balance of the solid phase include convection, diffusion, heat exchange and the heat of the reactions:

$$ -\rho_b u_{s,z} c_{ps} \frac{\partial T_s}{\partial z} + \rho_b u_{s,r} c_{ps} \frac{\partial T_s}{\partial r} = \frac{1}{r} \frac{\partial}{\partial r} \left( r \lambda_{eff,r} \frac{\partial T_s}{\partial r} \right) + \frac{\partial}{\partial z} \left( \lambda_{eff,z} \frac{\partial T_s}{\partial z} \right) + a_b h (T_g - T_s) + \sum_n (-v_n \Delta r H_n) \quad (A7) $$

The main notations above are as follows (in alphabetical order): $C_p$: specific heat (J kg⁻¹ K⁻¹); $C_t$: total gas concentration (mol m⁻³); $d$: diameter (m); $D_g$: diffusion coefficient (m² s⁻¹); $h$: heat transfer coefficient (W m⁻² K⁻¹); $i$: a species; $M$: molecular weight (kg mol⁻¹); $P$: pressure (Pa); $r$: radius (m), or reaction rate (mol s⁻¹ m⁻³); $S$: source term (equation-dependent) (mol s⁻¹ m⁻³); $T$: temperature (K); $u$: velocity (m s⁻¹); $x$: volume fraction (–); $z$: height (m); $e$: volume fraction (–); $\lambda$: heat conductivity (W K⁻¹ m⁻¹); $v$: stoichiometric coefficient; $\rho$: density (kg m⁻³); $\omega$: mass fraction (–);

The subscripts are as follows: (g) gas phase; (i) chemical species (gas: CO, CO₂, H₂, H₂O, CH₄ and N₂; solid: volatile matter and fixed carbon in charcoal, and Fe₂O₃, Fe₃O₄, Fe₀.95O, Fe and ash in iron ore pellets); (ch) charcoal; (p) pellets; (n) reaction number; (s) solid phase.

The boundary conditions are solid and gas flow rates, temperatures and compositions known at their respective inlets. The gas pressure is known at the top outlet. Axial symmetry implies no radial derivatives at $r = 0$. The walls are considered impermeable and adiabatic.

## Data availability

The datasets generated during and/or analyzed during the current study are not publicly available due to property reasons but are available from the corresponding author on reasonable request.

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