# Beyond green hydrogen production: Ground transport within Europe, the hidden environmental impacts

Salma Serghini, Emmanuel Mignard, Stéphanie Muller, Guido Sonnemann

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Salma Serghini, Emmanuel Mignard, Stéphanie Muller, Guido Sonnemann. Beyond green hydrogen production: Ground transport within Europe, the hidden environmental impacts. International Journal of Hydrogen Energy, 2026, 206, pp.153243. 10.1016/j.ijhydene.2025.153243. hal-05468136

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# Beyond green hydrogen production: Ground transport within Europe, the hidden environmental impacts

Salma Serghini<sup>a, *</sup> <sup>†</sup>, Emmanuel Mignard<sup>a, **</sup> <sup>‡</sup>, Stéphanie Muller<sup>b, ‡</sup>, Guido Sonnemann<sup>a, §</sup>

## ARTICLE INFO

Keywords:

- Life cycle assessment
- Renewable hydrogen
- Hydrogen supply chain
- Hydrogen transport
- Hydrogen storage
- Hydrogen leakage

## ABSTRACT

As Europe accelerates its transition to low-carbon energy, renewable hydrogen is expected to play a key role in decarbonizing hard-to-abate industrial sectors. While the environmental impacts of hydrogen production via electrolysis are starting to be well understood, those of its storage and transport remain poorly determined. Yet, they are crucial to overall sustainability. This study presents a comparative Life Cycle Assessment (LCA) of six land-based delivery pathways across Europe for green hydrogen produced via Proton Exchange Membrane (PEM) electrolysis powered by wind energy. The scenarios differ in storage and transport methods—compressed gas (by truck or pipeline), liquefied hydrogen, and three chemical vectors (dibenzyltoluene, ammonia and methanol) transported by truck. While the production phase of green hydrogen shows a low Global Warming (GW) impact, the delivery stages are far from negligible, leading in certain cases to an overall GW impact exceeding that of domestically produced blue or grey hydrogen. These findings are amplified by taking into account hydrogen leaks across the supply chain and their Global Warming Potential. However, results demonstrate that there is no one-size-fits-all hydrogen delivery solution; optimal pathways depend on supply chain parameters, mainly distance and hydrogen demand. Pipeline transport emerges as the most environmentally efficient option for large-scale long-distance hydrogen transportation, whereas compressed gas hydrogen by truck is better suited for small-scale local delivery. Alternative delivery options, such as hydrogen liquefaction or conversion into chemical carriers with higher energy density, can lower transport-related emissions. These advantages often come with environmental trade-offs, as additional conversion steps shift part of the burden to other life-cycle stages and to other impact categories beyond GW, such as acidification and eutrophication. This study highlights the importance of integrating delivery considerations into hydrogen deployment strategies and policies. Finally, while the focus is on intra-European exchanges and ground transport, future work must investigate international hydrogen trade and maritime transport, along with their broader environmental and geopolitical implications.

## 1. Introduction

Global demand for hydrogen is projected to increase 5.5-fold, reaching 500 million tons annually by 2050 [1]. When produced through the electrolysis of water powered by renewable electricity, it is commonly referred to as renewable or green hydrogen, in contrast to grey or black hydrogen derived from fossil fuels. Today, 99 % of hydrogen produced worldwide is derived from fossil fuels and is almost exclusively used in the industrial sector [2]. While new applications of hydrogen are expected to emerge, such as aviation and heavy-duty

mobility, global hydrogen demand by 2050 is still expected to be largely driven by industrial applications, accounting for 45 % of the total demand [3]. In the petrochemical industry—where hydrogen is already used for oil hydrocracking and desulfurization—transitioning to green hydrogen can significantly reduce emissions. Similarly, green hydrogen can serve as a cleaner feedstock for the production of key compounds of methane chemistry such as ammonia and methanol, that are essential for agriculture and chemistry. Green hydrogen can also enable carbon-free steelmaking through direct reduction iron processes, replacing coal or natural gas traditionally used in blast furnaces [4],

<footnote><sup>a</sup> Université de Bordeaux, CNRS, Bordeaux INP, ISM, UMR 5255, Talence, F-33400, France</footnote>

<footnote><sup>b</sup> BRGM, F-45060, Orléans, France</footnote>

<footnote>* Corresponding author.</footnote>

<footnote>** Corresponding author.</footnote>

<footnote>E-mail addresses: salma.serghini@u-bordeaux.fr (S. Serghini), emmanuel.mignard@u-bordeaux.fr (E. Mignard).</footnote>
offering a sustainable solution for industries striving to meet ambitious climate targets. However, beyond these sectoral applications, hydrogen's large-scale deployment still faces significant technical and logistical challenges in production, storage, and transportation [5] and an important implementation gap exists between global hydrogen targets and the actual pace of project realization, underlining the importance of supportive policies and financing frameworks [6].

Producing hydrogen through low-carbon methods like renewable-based electrolysis is only the first step; hydrogen must then be stored, transported, and used efficiently, all of which could introduce potential emissions. A major challenge lies in hydrogen's volumetric energy density of approximately 0.003 kWh/L at 25 °C and 1 bar [7], which results in the need to store it and transport it in large volumes. To enhance its storage properties, hydrogen is typically compressed to pressures up to 900 bars (leading to high-pressure gaseous storage) or liquefied at atmospheric pressure at temperatures below -253 °C (leading to cryogenic liquid storage) [8]. These methods are generally referred to as physical storage. However, even in its liquid state, hydrogen occupies four times the volume of gasoline for the same energy content (low heating value of 8 MJ/L for liquid hydrogen versus 32 MJ/L for gasoline) [9], highlighting the limitations of physical storage and the need for more efficient alternatives. Another option is chemical storage, which involves binding hydrogen to chemical compounds with a better energy density, to enable easier and more efficient storage, handling and transportation. For instance, hydrogen can be stored in Liquid Organic Hydrogen Carriers (LOHCs), which are in liquid form under ambient conditions, can be handled like oil, and offer the advantage of being reusable since the original hydrocarbon carrier is not consumed during the process [10]. Other promising pathways include hydrogen stored in liquid ammonia (NH₃) or methanol (MeOH), which benefit of an established market and an existing global infrastructure [11]. Chemical storage methods therefore have the potential to offer valuable options for hydrogen delivery, namely when hydrogen needs to be transported over long distances between production and end-use sites.

Hydrogen delivery is becoming an increasingly important topic as the hydrogen sector is moving toward globalization, with international trade expected to play a significant role in the future [12]. Countries such as France, Chile, and Morocco are positioning themselves as key producers of green hydrogen, aiming to achieve self-reliance and eventually export their surplus. Meanwhile, nations like Germany, Japan, and South Korea are structuring their energy strategies around importing green hydrogen to meet the domestic demand. As hydrogen production is scaling up and hydrogen global trade turning into reality, storage and distribution challenges are gaining increasing importance. Addressing these challenges is not only about identifying technically feasible or economically viable solutions but also providing a clear understanding of their potential environmental impacts. In 2025, the European Parliament introduced new definitions for hydrogen [13], establishing a clearer distinction between two categories. Low-carbon hydrogen refers to hydrogen derived from non-renewable sources that achieves at least a 70 % reduction in life-cycle greenhouse gas (GHG) emissions compared with fossil fuels, as defined in the Hydrogen and Gas Market Directive (Directive (EU) 2024/1788) [14]. This category includes for example hydrogen produced via Steam Methane Reforming with Carbon Capture and Storage (SMR-CCS) or hydrogen from electrolysis powered by nuclear electricity. In contrast, renewable hydrogen is defined as hydrogen produced from renewable electricity and achieving the same minimum 70 % reduction in GHG emissions, in line with the definition of renewable fuels under the Renewable Energy Directive (RED III) [15]. This 70 % threshold applies regardless of the end-use sector, and is therefore a universal benchmark for hydrogen across different applications. The GHG savings are calculated against the average life-cycle emissions of conventional fossil fuels, set by the European Union (EU) at 94 g CO₂-eq/MJ, which yields the threshold of 3.38 kg CO₂-eq/kg H₂ for renewable and low-carbon hydrogen.

However, although the European Directives [14,15] refer broadly to life-cycle emissions from hydrogen production, methodological annexes that set out the calculation rules explicitly states that storage and transport of hydrogen must also be included in the assessment. It is therefore essential to consider the delivery phase of hydrogen in environmental calculations. Unlike conventional fuels such as oil or natural gas, for which transport-related emissions are marginal compared with those from the production phase, hydrogen involves specific logistical challenges. As a result, the storage and transport stages require meticulous analysis and may critically influence whether the hydrogen ultimately used can genuinely be considered renewable or low-carbon.

In this context, Life Cycle Assessment (LCA) stands out among the available tools for evaluating the environmental impacts of hydrogen delivery systems. With its ISO-standardized methodology (ISO 14040 [16] and 14044 [16]), widespread adoption, and proven reliability, LCA provides a comprehensive framework for assessing environmental impacts across the entire life cycle, including raw material extraction and processing, manufacture, transport, use and end-of-life [17]. The environmental impacts of hydrogen production via electrolysis are becoming increasingly well understood. In a recent review, Wilkinson et al. (2023) identified 99 LCA studies on hydrogen production published between 2015 and 2022, including 19 focusing on electrolysis [18]. However, the environmental impacts of hydrogen storage and transport remain poorly characterized. Applying LCA to hydrogen delivery is essential to ensure that green hydrogen can contribute effectively to industry decarbonization and that its environmental benefits outweigh its impacts. Very few studies have investigated the environmental impacts of hydrogen terrestrial delivery strategies within Europe for industrial applications, making it challenging to draw reliable conclusions. Wulf et al. (2018) examined the economic and environmental performance of hydrogen transported as a LOHC by truck, comparing it to gaseous hydrogen transported either by truck or pipeline to supply refueling stations for hydrogen mobility [19]. The study concluded that while LOHC delivery is more cost-competitive, it demonstrates poorer environmental performance compared to transportation as compressed gas hydrogen. Bano et al. (2018) found that LOHC transportation generates fewer environmental impacts than gaseous hydrogen transport over distances exceeding 365 km [20]. Akhtar et al. (2021) expanded the analysis by including truck-based delivery of hydrogen stored in liquid ammonia, reporting an environmental performance superior to LOHC but still less favorable than compressed gaseous hydrogen [21]. However, these studies remain mainly focused on mobility-related use cases, whereas the industrial sector is and will remain the main consumer of hydrogen worldwide. It is therefore crucial to redirect the analysis towards industrial applications and to consider other relevant delivery vectors such as methanol, which remains underexplored.

In addition, recent studies have raised concerns that hydrogen leakage could lead to indirect Global Warming (GW) by altering the atmospheric composition. Specifically, Warwick et al. (2022) [22] and Sand et al. (2023) [23] suggest that H₂ emissions increase atmospheric water vapor and extend the atmospheric lifetime of methane, which are both potent greenhouse gases. They estimate the 100-year Global Warming Potential (GWP100) of hydrogen to be 12 and 11.6 kg CO₂-eq/kg H₂, respectively. This factor has been overlooked in earlier studies, yet it could become critical in the context of large-scale hydrogen production, storage and transportation.

Furthermore, existing hydrogen delivery assessments often lack comparison with conventional scenarios involving on-site production and consumption of hydrogen, which represents the current practice in the industry. In such cases, hydrogen is produced directly at the industrial site via Steam Methane Reforming (SMR), a fossil-based process that generates significant CO₂ emissions, which is commonly referred to as grey hydrogen. This raises a fundamental question: is transporting green hydrogen produced off-site better than producing grey hydrogen on-site?

The aim of this paper is to determine which strategy represents the
most environmentally performant approach to supply European industries with hydrogen: to continue producing and consuming grey hydrogen locally, or to supply green hydrogen from European countries with a high share of renewables and transport it to industrial sites. An LCA study is performed to compare the environmental impacts of different hydrogen ground delivery strategies: Compressed Gas Hydrogen by Trailer (CGH₂-T) or Pipeline (CGH₂-P), Liquid Hydrogen (LH₂), a LOHC specifically DiBenzylToluene (DBT), liquid ammonia (NH₃), and methanol (MeOH). LH₂, DBT, NH₃, and MeOH are all assumed to be transported by truck in a context where exchanges occur within Europe using terrestrial transport modes. These delivery pathways are also assessed against the conventional strategy, where grey hydrogen is typically produced and consumed on-site via SMR, or through its lower-emission variant with Carbon Capture and Storage (SMR-CCS), also known as blue hydrogen. All strategies are evaluated in light of the European Union's threshold of 3.38 kg CO₂-eq/kg H₂ for renewable and low-carbon hydrogen. Particular attention is given to hydrogen leakage throughout the supply chain and its potential indirect climate implications, which are often overlooked in previous assessments. In addition, this work provides insight into the environmental hotspots and trade-offs associated with hydrogen delivery strategies and investigates the influence of key supply chain parameters that may affect the overall environmental performances. Based on the findings, context-specific recommendations are proposed to guide stakeholders in selecting the most suitable hydrogen delivery option, taking into account their specific constraints and objectives.

To our knowledge, no previous research has conducted such a comprehensive and integrated environmental analysis of multiple hydrogen ground supply strategies within Europe in the context of industrial decarbonization. This study therefore fills an important gap in the literature and aims to inform policymakers, stakeholders, and the public about the environmental implications of hydrogen production, storage, and transportation across the continent.

## 2. Materials and methods

The LCA study conducted in this paper was carried out in accordance with the ISO 14040 [24] and ISO 14044 [16] standards. The applied methodological framework is detailed in the following sections.

### 2.1. Goal and scope

A cradle-to-gate attributional LCA is performed on six delivery scenarios based on green hydrogen stored and transported between its production site and the industrial use-site, as shown in Fig. 1.

These scenarios share the same hydrogen production pathway but differ in the storage and transport mean. Hydrogen is produced through Proton Exchange Membrane (PEM) electrolysis powered by wind-generated electricity. This production route was selected because PEM electrolysis is considered one of the most efficient and flexible technologies for converting renewable electricity into 99.99 % hydrogen [25] and wind energy is currently the most widely represented renewable source in the EU electricity mix. A 100 % wind electricity scenario is not a forecast of a future electricity mix, but a best-case assumption aligned with a prospective EU hydrogen strategy, in which green hydrogen, produced near renewable resources such as wind farms, is transported over long distances to meet demand across Europe. Upon arrival to the consumption site, hydrogen is unloaded and temporarily stored in its conditioned form for three days, and subsequently deconditioned to restore gaseous hydrogen at 200 bars. This delivery pressure is selected as it corresponds to the typical storage pressure used for stationary hydrogen applications, particularly in large-scale industrial contexts where Type I tanks—made of steel and aluminum alloys—are commonly used [26]. While wind electricity is assumed for electrolysis, the energy requirements of all other processes along the supply chain rely on the EU heat and electricity grid.

The GW impact of the delivery scenarios is assessed against three references thresholds. The first one is the EU limit for renewable hydrogen (<3.38 kg CO₂-eq/kg H₂). The other two correspond to existing industrial practices, namely the domestic production and consumption of fossil-based hydrogen, through SMR and SMR-CCS, with no transportation involved. The SMR process is already modeled in existing LCA databases [27]. SMR involves the catalytic conversion of natural gas with steam produce syngas (a mixture of hydrogen and carbon monoxide), followed by a water-gas shift reaction to maximize hydrogen yield. In this study, the process is modeled under European conditions, using the EU electricity mix and the natural gas available in Europe. For carbon capture, a post-combustion methyl diethanolamine (MDEA) technology with a capture efficiency of 90 % is considered. Ravikumar et al. (2020) provide a detailed inventory, excluding the CO₂ transport and storage phases, as their impacts are considered minor compared with those of the capture stage [28]. Under these assumptions, in a European context, producing hydrogen through SMR and SMR-CCS results in 11.72 and 6.43 kg CO₂-eq per kg H₂, respectively.

Since a sensitivity analysis is conducted by varying several key parameters, a reference case study has been defined. The baseline assumptions are described in Table 1. The transport distance is set at 500 km, corresponding to an average distance in the transboundary hydrogen corridors envisioned in the H₂Med European project [29], which aims to establish a dedicated hydrogen pipeline network

<figure><img src="image_3.png" /><figcaption>**Fig. 1.** System boundaries of the hydrogen delivery scenarios assessed in this study. All pathways share common stages from production to delivery (conditioning, storage, land-transport, and deconditioning). Six scenarios are assessed: CGH₂-T (compressed gas hydrogen by truck), CGH₂-P (compressed gas hydrogen by pipeline), LH₂ (liquid hydrogen by truck), DBT (dibenzyltoluene by truck), NH₃ (ammonia by truck), and MeOH (methanol by truck). The functional unit is delivering 1 kg of gaseous H₂ delivered at 200 bars.</figcaption></figure>
<caption>**Table 1**</caption>

Reference use-case adopted for the LCA of hydrogen delivery scenarios, characterized by a transport distance of 500 km, a hydrogen demand at the use site of 15 t/day, and 1000 reuse cycles for the DBT carrier. The 100-year Global Warming Potential (GWP100) of hydrogen emissions is set at 0 kg CO₂-eq/kg H₂. This reference use-case serves as a baseline scenario for the sensitivity analysis, in which parameters are varied one at a time.

<table><tr><td>Transport distance (km)</td><td>500</td></tr><tr><td>Hydrogen demand (t/day)</td><td>15</td></tr><tr><td>Number of reuse cycles of DBT</td><td>1000</td></tr><tr><td>GWP100 H₂ (kg CO₂-eq/kg H₂)</td><td>0</td></tr></table>

interconnecting several European countries. The corridors range from approximately 80 km (e.g., the planned route between Moselle in France and Saarland in Germany) to 860 km (e.g., between Marseille in France and Obergailbach in Germany). Hydrogen demand is fixed at 15 t/day, based on the typical consumption of a medium-scale refinery (e.g., BP's Gelsenkirchen in Germany with a capacity of 265,000 bbl/day) or a small ammonia plant (e.g., Thyssenkrupp Uhde in Herne, Germany, producing around 100 t NH₃/day). Moreover, DBT is assumed to be reused 1000 times. This assumption is supported by previous research as LOHCs can be used repeatedly up to 1000 storage cycles [30] without any noticeable degradation of the carrier [31]. Finally, in the case study used as a reference, fugitive emissions of hydrogen are assumed to have no climate change impact. This parameter will be explored in the sensitivity analysis to evaluate how hydrogen leakage may affect the overall environmental performances.

The functional unit used to ensure a consistent comparison between the different scenarios is: “delivering 1 kg of gaseous hydrogen at 200 bars”. The modeling of background processes relies on the Ecoinvent 3.10 database with cut-off allocation [27], providing a harmonized data framework to support the life cycle inventory. The cut-off model was selected, considering that although electrolysis generates both hydrogen and oxygen, the entire environmental burden is allocated to hydrogen. This choice relies on a forward-looking hypothesis in which, if hydrogen were to be deployed at large scale, oxygen might not be systematically valorized and could instead be treated as a non-valuable by-product.

## 2.2. Technological assumptions and inventory data

Data were consolidated mainly through literature cross-checking, manufacturer notices, and in-house calculations based on mass and energy balances. Infrastructure was considered in all scenarios (among others: electrolysis plant, storage infrastructure, liquefaction plant, ammonia plant). It was modeled in detail when specific datasets were available, and otherwise represented using generic background processes. A preliminary study showed that infrastructure-related impacts in the hydrogen sector are negligible compared to those of the operational phase. Therefore, modeling efforts were focused on the most impactful operational stages. The main data sources and underlying assumptions are specified in the following sections. Detailed inventory is available in the Supplementary Materials. Data was processed using SimaPro 9.6 LCA software.

### 2.2.1. Compressed gas hydrogen

To transport hydrogen as compressed gas by trailer, storage at 700 bar is generally considered the most viable option, offering a density of approximately 40 g/L at 20 °C [32], corresponding to a volumetric energy density of 1.33 kWh/L. Theoretically, the electricity required to compress hydrogen isothermally from 20 to 700 bar is estimated at 1.36 kWh/kg H₂ [33]. However, industrial partners cited in that reference observed energy requirements of 2.85 and 3.02 kWh/kg H₂. In this work, an average electricity demand of 2.9 kWh/kg H₂ is assumed to compress hydrogen from 20 to 700 bar at 20 °C. This value corresponds

to the performance of a small-scale reciprocating compressor, operating at typical flow rates of around 1000 kg/day of hydrogen. It should nevertheless be noted that compression energy demand can vary depending on the target pressure, compressor technology, and installation scale. The chosen value should therefore be regarded as a representative order-of-magnitude assumption rather than a precise benchmark.

At high pressures rates, high-pressure storage vessels are required. Type IV vessels are lightweight and highly resistant tanks, characterized with a composite cylinder, mainly carbon fiber, wrapped with a polymer liner [34]. The technology readiness level (TRL) of hydrogen compression is currently assessed at 9, while that of gaseous hydrogen transport by truck reaches TRL 11 [35]. These values indicate that the solutions are mature, although improvements are still required for compression to maintain competitiveness.

In comparison, the transport of gaseous hydrogen through dedicated pipelines is assessed at TRL 10 [35], meaning that the technology is commercially available, but further efforts are needed for large-scale integration into energy infrastructures. The H₂Med European project indicates that pipelines are expected to operate at pressures up to 100 bar [29]. In addition, recompression is needed every 250 km to maintain the required pressure. The modeling of hydrogen pipeline transport in this study is initially based on the Ecoinvent 3.10 datasets for natural gas pipelines, which are then modified and tailored to reflect the specific requirements of hydrogen. The inventory data are primarily drawn from Wulf et al. (2018) [19], who adapted multiple sources from the literature. The main modifications include adjusting the pipeline diameter and incorporating a special internal coating made of an aluminum-zinc-silicon alloy to reduce hydrogen diffusion.

### 2.2.2. Liquid hydrogen

Liquefying hydrogen enables a significant increase in storage density compared to CGH₂, reaching 70.8 g/L at -253 °C and atmospheric pressure [36] corresponding to a volumetric energy density of 2.36 kWh/L. Although the theoretical minimum energy requirement for liquefaction is 3.9 kWh/kg H₂ [33], modern liquefaction plants—employing advanced techniques such as magnetic regenerative liquefiers—typically require between 6.4 and 7 kWh/kg H₂ of electricity [37]. An average liquefaction electricity need of 6.7 kWh/kg H₂ was considered in this study. LH₂ must be stored in cryogenic tanks with highly effective insulation at low pressures (<10 bar), making large-scale, high-density energy storage systems feasible [38]. However, complete heat insulation is impossible, hydrogen boil-off must be taken into account, with a typical value around 1 wt% per day [39]. Finally, the energy required for LH₂ vaporization is 447 kJ/kg H₂ [40]. Hydrogen liquefaction and vaporization processes are considered relatively mature (TRL 7-9), with commercially available solutions, but improvements can still be achieved to enhance competitiveness and large-scale integration [35,41]. In contrast, the transport of liquid hydrogen by truck remains at an early conceptualization stage, with TRLs estimated between 2 and 3 [35]. Significant efforts are required, particularly to achieve near zero atmospheric release of boil-off gas, to extend delivery distances up to 2000 km and beyond, and to ensure long-term operational reliability.

### 2.2.3. Dibenzyltoluene

LOHCs have emerged as a promising solution for energy-efficient, scalable, and safe long-distance hydrogen transportation and storage [42]. In LOHC systems, hydrogen is stored in a hydrocarbon compound through a hydrogenation process and is later released through the reverse dehydrogenation process. In this study, DBT is used due to its high potential as an LOHC by offering a hydrogen storage capacity of 6.2 wt% [43]. DBT is also favored over other LOHC candidates such as toluene because of its more advantageous properties in terms of flammability, vapor pressure, and toxicity. DBT synthesis data is sourced from Cho et al. (2024) [44], who described different routes of
production, including the conventional process with toluene and chlorine facilitated by an iron III chloride catalyst. Electricity needs for the DBT hydrogenation and dehydrogenation processes are based on the work of Wulf et al. (2018) [19]. However, the TRL of DBT transformation processes (hydrogenation and dehydrogenation) is considered medium, ranging from 5 to 7, which corresponds to advanced prototyping under real-life conditions [35]. In particular, ongoing research focuses on improving the overall efficiency of DBT by developing advanced catalysts that enable dehydrogenation at lower temperatures. As for the transport of DBT, this process is already mature, as it can be handled like oil under ambient temperature and pressure [10].

### 2.2.4. Ammonia

Using liquid NH₃ (atmospheric pressure and temperature of -33 °C) as a hydrogen storage medium is an attractive solution due to its high hydrogen density of 17.7 wt% [45]. Hydrogen can be efficiently converted into ammonia by reacting with nitrogen (N₂) through the well-established Haber-Bosch process and using a catalyst composed of iron, potassium hydroxide and alumina [46]. Low-cost nitrogen can be extracted from the atmosphere using cryogenic air separation technology, which is a mature technology well-suited for large-scale uses [47]. The total electricity consumption for atmospheric nitrogen extraction and ammonia production is in a range of 0.6-1.1 kWh/kg NH₃ [48], while the electricity need for ammonia liquefaction is neglectable, not exceeding 0.03 kWh/kg H₂ [49]. An average value of 4.83 kWh/kg H₂ was considered in this work. Although the Haber-Bosch process itself is highly mature, its integration with renewable hydrogen produced via electrolysis is assessed at a TRL of 8, indicating that first-of-a-kind, full-scale commercial demonstrations are beginning to be deployed [35]. Then hydrogen can be recovered through ammonia cracking process, in which liquid NH₃ is heated between 800 and 1000 °C and atmospheric pressure, and passed over a nickel-based catalyst that facilitates its dissociation into H₂ and N₂. The heat required for ammonia cracking is supplied by combusting part of the ammonia itself along with a fraction of the off-gas. Previous studies have reported the use of a combustible molar mixture consisting of approximately 70 % NH₃ and 30 % H₂ [50,51]. The energy required for the cracking process is estimated at an average value of 8.5 kWh/kg H₂ [46,52-54]. Its current TRL is estimated at 4, corresponding to early prototyping under test conditions [35].

### 2.2.5. Methanol

Methanol is one of the most widely used chemical throughout the world and is traditionally produced either from natural gas or coal [55]. The synthesis of methanol directly from CO₂ and H₂ requires only minimal modifications to existing infrastructure, a pathway that has already been commercialized, notably in Iceland at the George Olah Renewable Methanol Plant [48]. Just like ammonia, methanol is a promising hydrogen storage option as it is liquid at ambient conditions, has a hydrogen content of 12.6 wt%, benefits from existing storage and transport infrastructure, and offers broad application potential [56]. In this work, methanol is produced through catalytic hydrogenation of captured CO₂ with electrolytic hydrogen. CO₂ and H₂ react over a Cu/ZnO/Al₂O₃ catalyst to form methanol and water. The inventory data for methanol production and reforming was taken respectively from Rosental et al. (2020) [57] and manufacturer's data from Caloric Anlagenbau GmbH [58]. The TRL of methanol production from captured CO₂ and electrolytic hydrogen is currently assessed at 7 [35]. In contrast, methanol reforming remains at an early prototyping stage, with individual components still under testing and major improvement needed in catalyst deactivation, achieving high conversion and selectivity at lower temperatures, and ensuring cost-effective and scalable pathways [59].

### 2.2.6. Transportation

Transportation requirements are directly linked to the end-user's hydrogen daily demand. Specifically, for a given hydrogen flow rate (t/

<caption>**Table 2**</caption>

Effective truck loading capacities expressed in kilograms of hydrogen transported per 32-ton truck for the different delivery scenarios.

<table><thead><tr><td>Scenario</td><td>kg H<sub>2</sub> transported per 32-ton truck</td></tr></thead><tbody><tr><td>CGH<sub>2</sub>-T</td><td>1100</td></tr><tr><td>LH<sub>2</sub></td><td>4300</td></tr><tr><td>DBT</td><td>2000</td></tr><tr><td>NH<sub>3</sub></td><td>5700</td></tr><tr><td>MeOH</td><td>4000</td></tr></tbody></table>

day), the number of trucks required to ensure the delivery depends on the effective payload capacity of the truck, which in turn is determined by the density of the physical or chemical storage medium used. In other words, relatively dense hydrogen carriers, such as NH₃ or MeOH, allow a larger amount of hydrogen to be transported per truck, thereby reducing the number of round trips needed. Conversely, low-density options like CGH₂ necessitate a higher number of deliveries to supply a same quantity of hydrogen. Ecoinvent transportation datasets [27], notably "transport, freight, lorry >32 metric ton, EURO 6", are based on average truck loading capacities. In this study, the Ecoinvent transportation model was refined to account for the effective hydrogen load, which varies depending the transported compound and its density. Table 2 summarizes the truck loading capacities considered for each scenario. The values are derived from DOE Multi-Year Research, Development and Demonstration Plan (2014) [60] for CGH₂, LH₂, and calculated in-house for DBT, NH₃ and MeOH. For a 32-ton truck with a volume of 50 m³, the amount of hydrogen that can be transported was determined from the carrier density and its hydrogen storage capacity. All truck scenarios assume transportation by EURO 6 diesel-powered engines.

### 2.2.7. Supply chain losses

Losses can occur at various stages of the hydrogen supply chain. It is essential to account for them accurately, as they are released into the ecosphere and contribute to environmental impacts. The nature and magnitude of the losses vary depending on the delivery scenario and the physical or chemical form in which hydrogen is stored and transported. For example, CGH₂ has a very high diffusivity, making it prone to leakage and LH₂ leaks through boil-off due to the extremely low storage temperature of -253 °C. By contrast, DBT, is liquid at ambient conditions, making it more stable and easier to handle. Table 3 summarizes the losses considered in this study for each delivery scenario. However, loss rates are not consistently reported in the literature. To address this variability and ensure consistency across scenarios, average values were defined by cross-referencing multiple data sources [21,30,37-39,60,61]. The loss rates presented in this work do not account for loss recovery systems, as their effectiveness strongly depends on specific operational practices and is not systematically documented in the literature.

## 2.3. Life cycle impact assessment (LCIA)

The inventory data were processed into environmental impact indicators using SimaPro 9.6 LCA software and the ReCiPe 2016 Midpoint (H) impact assessment method. This method allows the calculation of up

<caption>**Table 3**</caption>

Hydrogen losses along the supply chain, expressed as weight percentage. Values correspond to the losses assumed for each delivery scenario, depending on the carrier considered.

<table><thead><tr><td></td><td>(De)conditioning (wt%)</td><td>Storage (wt%/day)</td><td>Transport (wt%/day)</td></tr></thead><tbody><tr><td>CGH<sub>2</sub>-T</td><td>0.3</td><td>0.18</td><td>0.18</td></tr><tr><td>CGH<sub>2</sub>-P</td><td>0.3</td><td>0.3</td><td>0.3</td></tr><tr><td>LH<sub>2</sub></td><td>0.5</td><td>1</td><td>1</td></tr><tr><td>DBT</td><td>0.1</td><td>-</td><td>-</td></tr><tr><td>NH<sub>3</sub></td><td>0.6</td><td>0.015</td><td>0.015</td></tr><tr><td>MeOH</td><td>0.2</td><td>0.0003</td><td>0.0003</td></tr></tbody></table>
<table><caption>**Table 4**

Environmental impact categories considered in the study, with abbreviations and units.</caption><thead><tr><th>Global Warming</th><th>GW</th><th>kg CO<sub>2</sub>.eq</th></tr></thead><tbody><tr><td>Stratospheric Ozone Depletion</td><td>SOD</td><td>kg CFC11-eq</td></tr><tr><td>Terrestrial Acidification</td><td>TA</td><td>kg SO<sub>2</sub>.eq</td></tr><tr><td>Freshwater Eutrophication</td><td>FE</td><td>kg P-eq</td></tr><tr><td>Human Carcinogenic Toxicity</td><td>HCT</td><td>kg 1,4-DCB</td></tr><tr><td>Fossil Resource Scarcity</td><td>FRS</td><td>kg oil-eq</td></tr></tbody></table>

to 18 indicators, offering a comprehensive overview of potential environmental burdens. Although the full set of environmental impact categories was assessed, only a subset of 6 indicators is presented and discussed in this paper, as summarized in Table 4. GW was selected as it is one of the most widely monitored and regulated environmental indicators. The other categories were chosen because they are considered the most relevant to the systems under investigation. Fossil Resource Scarcity (FRS) and Terrestrial Acidification (TA) were selected due to their high sensitivity to fuel consumption, which is a key factor when assessing ground transport-based systems. In addition, TA can also be exacerbated by the use and handling of ammonia-based compounds, as is the case in one of the scenarios studied. The same applies to Freshwater Eutrophication (FE), since nitrogen-based substances are known to contribute to aquatic nutrient enrichment. Stratospheric Ozone Depletion (SOD) was considered relevant given its potential contribution from industrial processes, particularly those involving solvents, refrigeration, and air conditioning technologies, which are central in the modeled supply chains. Finally, Human Carcinogenic Toxicity (HCT) was selected due to its links with the production and handling of chemical substances, as well as emissions related to the construction sector, which may reflect the background infrastructure required for the studied scenarios. Detailed LCIA results for remaining impact categories are provided in the Supplementary Materials.

### 3. Results and discussion

This section begins with a comparative LCA of the six hydrogen delivery scenarios across several environmental impact categories. The discussion then turns to the contribution of the different life cycle stages to the overall GW impact of each scenario. Finally, a set of sensitivity analyses explores how variations in key parameters—including the

number of reuse cycles of dibenzyltoluene, transport distance, hydrogen demand, and the GWP100 of hydrogen leakage—affect the relative performance of the delivery scenarios.

#### 3.1. Environmental impact assessment

Fig. 2 compares the environmental impacts of the six green hydrogen delivery scenarios, covering the entire pathway from the production site to the point of use, for the baseline use case described in Table 1. In addition, a reference scenario is included, representing hydrogen produced locally via SMR, without transportation involved. Because the environmental impact categories have different units, the results are expressed as relative values to facilitate visual comparison. Each impact category is normalized to the scenario with the highest impact within each category.

First, it can be observed that the domestic hydrogen production via SMR ranks highest in the GW and FRS impact categories, with respective values of 11.72 kg CO₂-eq and 4.43 kg oil-eq per kg of hydrogen. This result is expected, as SMR is a fossil-fuel-based process, which naturally leads to higher impacts in these categories. It is worth noting that the GW impact of the local SMR scenario is between 1.3 and 5 times higher than that of the long-distance delivery scenarios of green hydrogen produced off-site, while its FRS impact is 2.5–7 times higher. For the remaining impact categories, the local SMR scenario shows almost exclusively the lowest impact values, ranking behind the long-distance delivery scenarios. This indicates the dominance of transport-related contributions in these categories.

Now, when focusing exclusively on the scenarios that involve hydrogen transport between the production and consumption sites (thus excluding the local SMR case), it can be observed that scenarios relying on the physical storage of hydrogen in its gaseous form exhibit the best environmental performance in most categories. In particular, CGH₂-P underscores the lowest impact in four out of six categories, making it the most environmentally favorable transport option in this case study. For the delivery of 1 kg of hydrogen, CGH₂-P results in 2.36 kg CO₂-eq for GW, 9.06 × 10⁻⁷ kg CFC-11-eq for SOD, 8.76 × 10⁻³ kg SO₂-eq for TA, and 0.64 kg oil-eq for FRS, proving its efficiency across multiple dimensions. However, a burden shift is observed toward other impact categories. While CGH₂-P reduces impacts related to road transportation, it increases impacts in FE and HCT, likely associated with the material and infrastructure requirements for pipeline construction, which offset the benefits of lower emissions during the operational

<figure><img src="image_4.png" /><figcaption>**Fig. 2.** Environmental impact comparison of six green H₂ delivery scenarios of 1 kg of H₂. The comparison covers all life cycle stages defined in the system boundaries, including production, conditioning, storage, transport, and deconditioning. A reference scenario is also included, representing locally produced hydrogen via SMR, without any transportation involved. Results are expressed as relative values, normalized to the highest-impact scenario within each impact category, with the corresponding absolute value indicated. The impact categories considered are Global Warming, Stratospheric Ozone Depletion, Terrestrial Acidification, Freshwater Eutrophication, Human Carcinogenic Toxicity, and Fossil Resource Scarcity. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>
phase. More specifically, $\text{CGH}_2$-P reaches $1.70 \times 10^{-3}$ kg P-eq/kg H$_2$ for FE and ranks as the fourth-best performer in HCT with 3.52 kg 1,4-DCB-eq/kg H$_2$.

The $\text{CGH}_2$-T scenario also emerges as a promising solution for green H$_2$ storage and transportation. Although it ranks as the best performer in only two categories, FE and HCT, it consistently ranks second best option across all other impact categories, closely following $\text{CGH}_2$-P. The differences between $\text{CGH}_2$-T and $\text{CGH}_2$-P remain relatively small, with a maximum increase of only 1.5 times, notably in the FRS category. This suggests that $\text{CGH}_2$-T offers a balanced environmental profile with limited trade-offs, making it a robust alternative when pipeline infrastructure is unavailable.

The DBT scenario ranks second or third best performer for four impact categories out of six, namely HCT, SOD, TA, and FE, but exhibits a burden shift towards higher impacts in FRS and GW, with values 2.8 and 2.3 times higher than those of $\text{CGH}_2$-P, respectively. This is due to the specific logistics of the DBT transportation. Unlike other truck-scenarios where the lorry returns empty, DBT trucks return carrying the dehydrogenated liquid carrier. The heavier load during the way back increases fuel consumption, thereby resulting in a greater fossil resource use and associated greenhouse gas emissions.

The $\text{NH}_3$ scenario exhibits heterogeneous results. While it ranks as the third-best performer in three out of six categories (GW, HCT, FRS), it shows the highest impacts for TA and SOD. Specifically, the $\text{NH}_3$ pathway presents TA and SOD impacts that are 5.8 and 3.2 times higher, respectively, than those of the $\text{CGH}_2$-P scenario. The elevated TA impact is mainly due to the release of nitrogen oxides (NO and $\text{NO}_2$) throughout the supply chain, particularly during ammonia cracking, where the heat required for the process is generated by the combustion of $\text{NH}_3$ and part of the off-gas. NO and $\text{NO}_2$ play a key role in acid deposition processes, thereby intensifying acidification effects on terrestrial ecosystems. Regarding SOD, the high impact is primarily associated with the use of refrigerants during the liquefaction and storage of ammonia (liquid $\text{NH}_3$ stored at -33 °C under ambient pressure [45]). The $\text{NH}_3$ scenario also exhibits elevated FE impact, about 1.8 times higher than those of $\text{CGH}_2$-P. These impacts can be attributed to the intrinsic nature of ammonia as a storage medium. During both the ammonia synthesis and cracking stages, nitrogen compound, particularly nitrates, can leach into aquatic environments, contributing to nutrient enrichment, promoting excessive algae growth, and thus causing eutrophication. For instance, ammonia losses during the Haber-Bosch synthesis process are estimated at approximately 9 mg $\text{NH}_3$ per kg H$_2$ input [62]. Detailed loss estimates along the $\text{NH}_3$ supply chain are provided in the Supplementary Materials.

Finally, the LH$_2$ and MeOH scenarios are the least favorable options across nearly all impact categories, never ranking above fourth place. LH$_2$ is positioned second-to-last or last in three categories: OD, FE and HCT. This can be explained by the liquefaction process, which relies on industrial refrigerants that are harmful to the ozone layer, aquatic ecosystems, and human health. MeOH ranks second-to-last for TA, FE and FRS, and last for GW. The most pronounced gap is observed for GW, where MeOH exhibits an impact 3.6 times higher than that of $\text{CGH}_2$-P. This underperformance is primarily attributed to the high energy demand of the methanol reforming process, as well as the generation of carbon dioxide as a reaction by-product.

To summarize, for the specific use case described in Table 1, local hydrogen production via SMR—without long-distance transport—shows the highest impacts GW and FRS. These impacts are up to 5 and 7 times higher, respectively, than those of off-site green hydrogen produced and transported over 500 km to the point of use. However, this improvement comes with trade-offs in other impact categories. When excluding local SMR production and considering only the transport-based scenarios ($\text{CGH}_2$-T, $\text{CGH}_2$-P, LH$_2$, DBT, $\text{NH}_3$, and MeOH), the pathways relying on the physical storage of hydrogen in gaseous form demonstrate the most favorable environmental performance, with $\text{CGH}_2$-P ranking first, closely followed by $\text{CGH}_2$-T. In contrast, the LH$_2$ and MeOH scenarios

exhibit the highest environmental burdens among the different impact categories. The DBT and $\text{NH}_3$ pathways show heterogeneous results, reflecting clear trade-offs across impact categories. The DBT scenario performs poorly in GW and FRS, which directly reflects its emission-intensive transport profile. However, it achieves relatively good performance in the remaining impact categories, consistently ranking among the top three delivery options. Conversely, the $\text{NH}_3$ scenario shows low impacts in GW and FRS, indicating a relatively clean transport stage, but this comes at the expense of higher impacts in TA, SOD and FE. These elevated impacts are directly linked to the intrinsic nature of ammonia as a hydrogen carrier, which involves nitrogen-related emissions ($\text{NO}_x$, nitrates, and $\text{NH}_3$) during the transformation and storage phases of ammonia, contributing to secondary forms of pollution. Overall, these findings should be interpreted in the context of the specific use case described in Table 1 and may vary under different assumptions or system conditions.

## 3.2. Contribution to Global Warming

This section focuses specifically on the GW impact that is prioritized due to its central role in climate-related regulations and decarbonization strategies. Fig. 3 shows the contribution of each life cycle stage to the overall GW impact. The aim is to examine the environmental hotspots and explore potential optimization levers.

Among all the hydrogen supply strategies assessed, only two achieve a GW impact compatible with the EU limit for renewable hydrogen (3.38 kg $\text{CO}_2$-eq/kg H$_2$): those involving transporting hydrogen as compressed gas, either via truck or pipeline. For the $\text{CGH}_2$-T scenario, the GW impact amounts to 3.28 kg $\text{CO}_2$-eq/kg H$_2$. The impact is almost evenly distributed across three life cycle stages: hydrogen production via PEM electrolysis (33 %), conditioning to compress hydrogen to 700 bars for transportation purposes (30 %), and road transportation by truck (37 %). The storage phase (either at the production site while awaiting delivery, or upon arrival at the use site) is neglectable, accounting for less than 1 % of the total impact. Shifting to pipeline transport ($\text{CGH}_2$-P scenario) reduces GW to 2.36 kg $\text{CO}_2$-eq/kg H$_2$. Carbon savings are primarily observed in the conditioning phase, which accounts for 18 % of the total impact, due to lower compression requirements for pipeline delivery (100 bars). Transport-related emissions are also significantly reduced, contributing only 17 % of the GW impact, highlighting the superior efficiency of pipeline transport over trucks for distances of 500 km. The deconditioning phase, where hydrogen is compressed to reach 200 bars, represents 18 % of the overall impact. Ultimately, the impact is dominated by the green hydrogen production phase, which contributes to 46 % of the impact, equivalent to 1.01 kg $\text{CO}_2$-eq/kg H$_2$.

The GW impact of the LH$_2$ scenario reaches 4.49 kg $\text{CO}_2$-eq/kg H$_2$, thus exceeding the EU threshold of 3.38 kg $\text{CO}_2$-eq/kg H$_2$. However, the impacts remain 2.6 and 1.4 times lower than that of grey and blue hydrogen, respectively, when produced and consumed on-site. In LH$_2$ scenario, the conditioning phase alone accounts for more than half of the total GW impact (54 %), reflecting the significant energy demand required to liquefy hydrogen at cryogenic temperatures. Hydrogen production also contributes substantially (26 %), while storage, transport, and deconditioning represent minor contributions, accounting for 2 %, 9 %, and 11 %, respectively. These results underline that, although carbon savings can be achieved during the transport phase, they are insufficient to offset the highly energy-intensive nature of the liquefaction process.

Similarly, the DBT scenario yields a GW impact of 5.42 kg $\text{CO}_2$-eq/kg H$_2$, exceeding the EU renewable hydrogen limit, but still below the values associated with grey and blue hydrogen produced via SMR and SMR-CCS. Unlike LH$_2$, which significantly reduces the transport-related impact, the transport phase in the DBT scenario accounts for nearly one-quarter of the total GW impact. The main contributor is the deconditioning phase (47 %), due to the high energy demand required to dehydrogenate dibenzyltoluene and recover hydrogen at the use site. It
<figure><img src="image_5.png" /><figcaption>**Fig. 3.** Contribution of life-cycle stages to the Global Warming impact of the six hydrogen delivery scenarios: CGH₂-T, CGH₂-P, LH₂, DBT, NH₃, and MeOH. Results include all life cycle stages defined in the system boundaries (green H₂ production, conditioning, storage, transport, and deconditioning). The delivery scenarios are benchmarked against three reference thresholds: renewable H₂ according to the EU threshold, grey hydrogen from Steam Methane Reforming, and blue hydrogen from Steam Methane Reforming with Carbon Capture and Storage, both produced locally without transportation. Results are expressed in kg CO₂-eq per kg H₂ delivered. (For interpretation of the references to colour in this figure legend, the reader is referred to the Web version of this article.)</figcaption></figure>

is worth noting that this scenario assumes the DBT is reused for 1000. This assumption may strongly influence the results and will be examined further in the sensitivity analysis. The remaining GW impact contributions stem from green hydrogen production (20 %), conditioning phase to hydrogenate the LOHC (9 %), and storage at the production and use site (0.2 %).

The NH₃ scenario results in a GW impact of 3.74 kg CO₂-eq per kg H₂, slightly exceeding the EU threshold. The main contributors are hydrogen production via PEM electrolysis (31 %) and hydrogen conditioning for ammonia synthesis through the Haber–Bosch process (46 %). Although the absolute emissions from each of these stages remain below 1.7 kg CO₂-eq/kg H₂, their relative contribution is amplified by the minor contribution of the transport and deconditioning phases. Ammonia has a high hydrogen storage capacity, and both its storage and transport are well-established industrial processes, resulting in low transport-related emissions. In the deconditioning stage, the thermal energy required for ammonia cracking is supplied internally by combusting part of the ammonia and a fraction of the off-gas hydrogen, making the process energetically optimized. Supplying external energy for this step would likely have significantly altered the results of this scenario.

Finally, the MeOH pathway results in carbon emissions exceeding the EU threshold for renewable hydrogen with its emissions amounting to 8.60 kg CO₂-eq/kg H₂. Also, while this strategy performs better than the local SMR scenario, it remains less favorable than local SMR-CCS. The impact is dominated by the deconditioning phase, with ~97 % of it arising from CO₂ released during methanol reforming. In this process, methanol reacts with water to produce hydrogen and CO₂, the latter being emitted to the atmosphere and thereby increasing the GW impact of this pathway. This effect is partially offset by negative emissions during the conditioning phase (−3.59 kg CO₂-eq/kg H₂), where captured CO₂ and green H₂ are used to synthesize methanol. Therefore, if the supply chain were to end at the delivery of green methanol rather than green hydrogen recovery, this pathway could potentially be classified as renewable and even result in net-negative emissions.

A key insight across all delivery scenarios between the production and use sites is that the GW impact contribution from green hydrogen production remains relatively modest, consistently around 1.10 kg CO₂-eq/kg H₂. In contrast, the delivery-related stages, namely conditioning, transportation, and deconditioning, collectively represent the majority of the total impact, contributing at least 54 % in every case. This finding raises important questions about the sustainability of transporting

hydrogen over long distances. It suggests that using green hydrogen directly at its production site, or alternatively producing hydrogen closer to the point of use, could substantially reduce environmental impacts by avoiding the burdens associated with transport and transformation processes. However, if green hydrogen must be transported overland across a distance of 500 km, pathways based on the physical storage of hydrogen in its gaseous form (CGH₂-T and CGH₂-P) and the ammonia-based route (NH₃) exhibit the best GW performance. Among these, only CGH₂-T and CGH₂-P comply with the EU definition of renewable hydrogen (3.38 kg CO₂-eq/kg H₂), while the NH₃ pathway slightly exceeds this threshold. The LH₂ and DBT scenarios, however, largely exceed the EU threshold but still result in lower impacts compared to local production of grey or blue hydrogen via SMR or SMR-CCS. On the other hand, the MeOH pathway, while significantly reducing transport-related impacts, suffers from a major burden shift toward the deconditioning phase, where hydrogen is recovered from the chemical carrier. As a result, under the studied conditions, producing blue hydrogen locally (via SMR-CCS) appears preferable to importing green methanol and reconverting it to hydrogen at the consumption site. This study focuses on hydrogen ground delivery within Europe and does not include cases where chemical carriers are directly supplied. Nevertheless, the MeOH pathway may offer advantages when final reversion to hydrogen can be avoided, for instance when supplying industries capable of directly using green methanol as a feedstock to support their decarbonization efforts.

Finally, it can be observed that DBT dehydrogenation, NH₃ thermal cracking, and MeOH reforming are the least mature technologies, currently at early to advanced prototyping development stages [35,59]. Among these, DBT dehydrogenation and MeOH reforming represent environmental hotspots. Although these environmental burdens cannot be attributed solely to the current lack of technological maturity, future technological developments could nonetheless reshape the environmental profile of different solutions.

### 3.3. *Sensitivity analysis*

A sensitivity analysis is conducted to assess how key supply chain parameters influence the environmental performance of the different hydrogen delivery strategies. In each case, only one parameter is varied at a time, while all others are held constant.
### 3.3.1. Number of reuse cycles of dibenzyltoluene

In the reference use case presented earlier, the DBT carrier was assumed to be reused up to 1000 times. This means that once hydrogen is released through the dehydrogenation process, the carrier returns to the production site and is reused for subsequent delivery cycles. Although this assumption is supported by previous research, which reports that LOHCs can undergo up to 1000 storage cycles without noticeable degradation of the carrier [30,31], such a value should be regarded as optimistic. In real-world operation, not only material degradation or contamination but also logistical constraints associated with the return and handling of the carrier may limit the achievable number of reuse cycles. For this reason, a sensitivity analysis is conducted to evaluate how GW impact results vary as a function of DBT number of reuse cycles.

Fig. 4 illustrates the evolution of the GW impact for the DBT scenario as a function of the number of reuse cycles of the LOHC. For a single-use, the GW impact increases drastically to 251 kg CO₂-eq/kg H₂, making this option clearly unsustainable and to be avoided. It becomes environmentally viable after approximately 40 reuse cycles, reaching 11.75 kg CO₂-eq/kg H₂, almost equivalent to the SMR scenario. Beyond 300 cycles, it becomes more favorable than the SMR-CCS scenario, with a GW impact of 6.30 kg CO₂-eq/kg H₂. The GW impact then reaches an optimal performance from 500 cycles onward, stabilizing around 5.42 kg CO₂-eq/kg H₂.

### 3.3.2. Transport distance

Fig. 5 shows how the transport distance between the production site and the use site influences the GW impact of the different hydrogen delivery pathways. As expected, GW increases with distance for all scenarios. However, the increase rate differs across pathways. The least sensitive pathways to distance are CGH₂-P, LH₂, NH₃, and MeOH, with a GW increasing less than 0.30 kg CO₂-eq/kg H₂ every 250 km. In contrast, the CGH₂-T scenario exhibits a more important sensitivity, with GW rising by approximately 0.59 kg CO₂-eq/kg H₂ for every 250 km. It is primarily due to the low energy density of compressed gas hydrogen, which requires a larger number of trucks to deliver the same quantity of hydrogen compared to carriers with higher energy density (Table 2). As a result, the emissions associated with transport are amplified in proportion to the number of vehicles needed. The DBT scenario represents a particular case. Although it partially mitigates the energy density issue by using a liquid organic carrier, the DBT is assumed to be reused. Consequently, the return trip is not empty: trucks carry the dehydrogenated DBT back to the production site. This return load increases diesel consumption compared to other scenarios, and thus contributes to additional transport-related emissions. The GW increase rate for DBT is approximately 0.65 kg CO₂-eq/kg H₂ for every 250 km traveled.

That being said, for short distances, the most environmentally advantageous option remains CGH₂-P, followed closely by CGH₂-T and

<figure><img src="image_6.png" /><figcaption>Fig. 4. Influence of the number of reuse cycles of dibenzyltoluene on the Global Warming impact of the DBT delivery scenario. Results are expressed in kg CO₂-eq per kg H₂ delivered.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Fig. 5. Influence of transport distance on the Global Warming impact of the six hydrogen delivery scenarios (CGH₂-T, CGH₂-P, LH₂, DBT, NH₃, and MeOH). Results are expressed in kg CO₂-eq per kg H₂ delivered.</figcaption></figure>

then NH₃. However, certain transport distances represent critical turning points beyond which the relative performance shifts: solutions that were previously environmentally competitive become less favorable. For instance, the NH₃ and LH₂ scenarios become more advantageous than compressed gaseous hydrogen transported by truck (CGH₂-T) at distances exceeding 800 km and 1250 km, respectively. Likewise, beyond 2250 km, the MeOH pathway outperforms DBT in terms of GW impact performance.

### 3.3.3. Hydrogen demand

Hydrogen demand at the consumption site is a key parameter that can influence environmental impact results of hydrogen supply chains. Indeed, for a given hydrogen demand (in t/day), the number of trucks required to meet the demand directly depends on the useable capacity of the truck, which is determined by the hydrogen delivery vector (e.g., CGH₂, LH₂, DBT, NH₃, MeOH). High-density vectors such as ammonia or methanol allow for larger quantities of hydrogen to be transported per truck, thereby reducing the number of trucks needed. In contrast, low-density carriers such as compressed gas hydrogen require significantly more trucks to deliver the same amount of useable hydrogen. For instance, delivering 2 t/day of hydrogen requires two trucks with the CGH₂-T scenario, but only one with NH₃. The greater the number of trucks required, the more round trips are needed, leading to higher diesel consumption and consequently higher CO₂ emissions. Beyond the number of trucks, their payload also matters: the heavier the load, the higher the average fuel consumption of each truck, and thus the higher the associated CO₂ emissions. A detailed analysis is therefore required to capture the effect of hydrogen demand on the environmental performance of the overall delivery chain. Additionally, plant and pipeline sizing with hydrogen demand was not considered in the following sensitivity analysis, as the focus was placed on operational processes rather than infrastructure.

In the reference case study, hydrogen demand was set at 15 t/day and distance at 500 km. A preliminary analysis showed that for short transport distances, GW impact results are only marginally sensitive to demand variations. For this reason, the sensitivity analysis was further explored under long-distance conditions (3000 km). GW impact results are presented in Fig. 6 and are expressed per functional unit of 1 kg of H₂.

The CGH₂-P scenario, which involves pipeline transport, shows an asymptotic decrease in GW as hydrogen demand increases. At low demand, impacts are high (e.g., 40.36 kg CO₂-eq/kg H₂ at 0.5 t/day), as emissions embodied in pipeline construction dominate when flow rates are low. Under these conditions, 94.6 % of the CGH₂-P impact is attributable to pipeline construction, corresponding to 38.18 kg CO₂-eq/kg H₂. As demand rises, these emissions are distributed across larger amounts of hydrogen, thereby reducing the GW impact per kilogram of hydrogen delivered. The system reaches near-optimal performance above 8 t/day, where construction-related emissions are effectively
<figure><img src="image_8.png" /><figcaption>**Fig. 6.** Influence of hydrogen demand at use site on the Global Warming impact of the six hydrogen delivery scenarios (CGH₂-T, CGH₂-P, LH₂, DBT, NH₃, and MeOH). Results are expressed in kg CO₂-eq per kg H₂ delivered.</figcaption></figure>

amortized. For example, at 15 t/day, the GW impact decreases to 5.54 kg CO₂-eq/kg H₂, with pipeline construction representing only 20 % of the impact.

For all truck-based scenarios, GW decreases with higher demand but in a discontinuous, stepwise manner. This trend arises because impacts are expressed per kg of H₂: as demand grows, the share of emissions attributed to 1 kg decreases. However, each time demand exceeds the capacity of the existing fleet and an additional truck is required, GW temporarily rises before decreasing again as the new truck is fully utilized. This stepwise pattern continues until the curves stabilize, reflecting a near-optimal state where further increases in demand no longer significantly influence results for 1 kg of hydrogen. For instance, in the CGH₂-T scenario, GW decreases from 17.31 kg CO₂-eq/kg H₂ at 0.5 t/day to 9.14 kg CO₂-eq/kg H₂ at 1.1 t/day (corresponding to one full truck). It then increases to 12.32 kg CO₂-eq/kg H₂ at 1.5 t/day when a second truck is required, before dropping again to 9.14 kg CO₂-eq/kg H₂ at 2.2 t/day, when both trucks are fully loaded.

Another observation for truck-based transport is that pathways relying on chemical carriers (e.g., DBT, NH₃, and MeOH) are the most sensitive to demand variations. They exhibit very high GW values at low demand, but allow for stronger optimization at higher demand levels. For instance, in the case of NH₃ pathway, GW impact values can reach 26.00 kg CO₂-eq/kg H₂ at low demand (0.5 t/day) and stabilize around 5.32 kg CO₂-eq/kg H₂ at higher demands (15 t/day), corresponding to a potential improvement of 20.68 kg CO₂-eq/kg H₂. In contrast, truck pathways based on physical storage show a smaller optimization potential, with a delta of only 8.17 kg CO₂-eq/kg H₂ between maximum and minimum values for CGH₂-T. Therefore, for small-scale hydrogen demands, chemical carriers appear less suitable for truck transportation.

### 3.3.4. Global Warming Potential of hydrogen leakage

Warwick et al. (2022) [22] and Sand et al. (2023) [23] suggest that hydrogen may have an indirect GW effect, due to its influence on atmospheric chemistry—specifically, by increasing tropospheric water vapor and extending the atmospheric lifetime of methane. To evaluate the implications of this, a sensitivity analysis was conducted assuming a hydrogen GWP100 of 12 kg CO₂-eq/kg H₂ emitted. The other parameters are fixed: transport distance of 500 km, a daily hydrogen demand of 15 t/day, and in the case of DBT, a reuse cycle of 1000 times. As expected, all delivery pathways show an increase in their GW impact when the GWP100 of hydrogen emissions is considered (Table 5). However, the extent of this increase varies significantly across the scenarios. The largest relative increase in the GW impact is observed for the LH₂ pathway (+21.7 %), followed by CGH₂-P (+11.2 %) and CGH₂-T (+6.0 %). By contrast, pathways based on chemical carriers such as DBT, NH₃, and MeOH exhibit much smaller increases—respectively +5.6 %, +4.7 %, and +1.3 %. These differences can be explained by the varying degrees of hydrogen leakage along the supply chain (Table 3), depending on the vector considered. For LH₂, total hydrogen losses throughout the

<caption>**Table 5**</caption>

The total hydrogen losses throughout the supply chain vary according to the carrier and are expressed in mg of H₂ emitted per kg of H₂ delivered. Influence of the 100-year Global Warming Potential (GWP100) of hydrogen emissions on the overall GW impact of the six delivery scenarios (CGH₂-T, CGH₂-P, LH₂, DBT, NH₃, and MeOH). Two values of GWP100 are considered: 0 and 12 kg CO₂-eq/kg H₂, with the corresponding relative change (Δ) between the two cases.

<table><thead><tr><th></th><th>H₂ losses (mg H₂ emitted/kg H₂ delivered)</th><th>GW impact (GWP100 = 0 kg CO₂-eq/kg H₂)</th><th>GW impact (GWP100 = 12 kg CO₂-eq/kg H₂)</th><th>Relative Δ</th></tr></thead><tbody><tr><td>CGH₂-T</td><td>16.31</td><td>3.28</td><td>3.48</td><td>+6.0 %</td></tr><tr><td>CGH₂-P</td><td>22.04</td><td>2.36</td><td>2.63</td><td>+11.2 %</td></tr><tr><td>LH₂</td><td>81.00</td><td>4.49</td><td>5.47</td><td>+21.7 %</td></tr><tr><td>DBT</td><td>25.37</td><td>5.42</td><td>5.73</td><td>+5.6 %</td></tr><tr><td>NH₃</td><td>15.00</td><td>3.74</td><td>3.92</td><td>+4.7 %</td></tr><tr><td>MeOH</td><td>9.06</td><td>8.60</td><td>8.71</td><td>+1.2 %</td></tr></tbody></table>

supply chain are nearly five times higher than those of CGH₂-T (81.00 mg versus 16.31 mg of H₂ emitted per kg of H₂ delivered). This is primarily due to the significant boil-off that occurs when hydrogen is stored and transported in its liquid form, which strongly amplifies the GW impact of the LH₂ scenario when a non-zero GWP100 is applied for hydrogen emissions. Pathways including compressed gaseous hydrogen (CGH₂-T and CGH₂-P) are also affected by hydrogen losses, though to a lesser extent. Losses mainly result from the diffusivity of hydrogen, which can cause permeation through materials and minor venting events during compression and storage. In contrast, chemically-bound hydrogen in molecules such as dibenzyltoluene, ammonia, and methanol is far more stable, which leads to minimal losses during storage and transportation. However, additional conditioning and deconditioning steps introduce extra hydrogen losses. These losses partially offset the advantages gained during storage and transportation, resulting in total supply-chain losses that are comparable in order of magnitude to those of CGH₂-T and CGH₂-P. For example, the DBT pathway, shows very low leakage rates during storage and transport, as dibenzyltoluene is a liquid organic carrier that can be handled like oil under ambient conditions. However, relatively significant losses occur during the transformation steps—hydrogenation and dehydrogenation—resulting in an overall GW impact increase rate of 5.6 %. The detail of hydrogen losses for each life cycle step are detailed in the Supplementary Materials.

In this specific case study, although the sensitivity to hydrogen's GWP100 does not alter the overall ranking of the hydrogen delivery solutions, it does narrow the differences between them, particularly between LH₂ and DBT, which now present similar impact levels: 5.47 vs. 5.73 kg CO₂-eq/kg H₂ respectively. Moreover, the CGH₂-T pathway, which was previously considered a renewable option under the EU classification, exceeds the threshold of 3.38 kg CO₂-eq/kg H₂ when hydrogen's indirect climate impact is taken into account, reaching 3.48 kg CO₂-eq/kg H₂. Currently, hydrogen's indirect climate effects are not included in the EU definition of renewable and low-carbon hydrogen, as laid down in the Hydrogen and Gas Market Directive (Directive (EU) 2024/1788) [14] and the Renewable Energy Directive (RED II/III) [15]. This omission highlights a regulatory gap: while the current framework establishes a standard threshold based on direct life-cycle emissions, accounting for the indirect climate impacts of hydrogen leakage could alter conclusions regarding the sustainability of certain hydrogen production and transport pathways. In addition, to date, relatively few studies have rigorously quantified the indirect GWP100 of hydrogen, and current estimates remain subject to scientific uncertainty. This analysis shows that hydrogen's climate profile can significantly alter the environmental performance of hydrogen delivery pathways, under-scoring the need for dedicated measurement campaigns and the development of standardized methods to better characterize hydrogen's atmospheric effects. A more precise understanding is essential not only to refine life cycle assessments, but also to inform technological choices
and guide policy decisions toward truly climate-compatible hydrogen value chains.

## 4. Conclusion

This paper presents a comparative life cycle assessment of several land-based hydrogen delivery strategies designed to supply European industrial sites. Rather than identifying a universal best option, the results reveal a series of context-dependent trade-offs that underscore the need for a case-by-case approach in the design of hydrogen supply chains.

The results of this work should be interpreted within the boundaries of the considered case study. Depending on the use cases that are being developed or that could be developed in future decarbonized hydrogen projects, the choice of transport and storage methods is far from trivial.

Across all scenarios, more than half of the GW impact arises from the delivery-related stages themselves, namely conditioning, transportation, and deconditioning. This raises critical questions about the environmental viability of long-distance hydrogen transport. Our work shows that whenever feasible, producing green hydrogen close to its consumption site is preferable, provided that water, electricity, and financial resources are locally available.

Pathways relying on physical storage of hydrogen in its gaseous form (CGH₂-T, CGH₂-P) generally offer the best environmental performance. Among them, pipeline transport (CGH₂-P) emerges as the most environmentally robust option, especially for long-distance transportation. However, for small hydrogen demands, CGH₂-P pathway no longer qualifies as renewable under the EU definition (GW impact >3.38 kg CO₂-eq/kg H₂), and even on-site production of grey hydrogen (via SMR) is more environmentally favorable. This is explained by the emissions embodied in pipeline construction, which are not amortized at low flow rates. For small-scale applications, CGH₂-T is the most suitable option, but only for short transport distances. At distances greater than 800 km, it becomes more emissive than the NH₃ scenario, and after 1250 km, its impact also surpasses that of LH₂. Beyond 2000 km, even locally produced blue hydrogen (via SMR-CCS) offers better environmental performance.

Alternative storage and transport pathways such as LH₂, DBT, NH₃, and MeOH offer higher energy densities and often greater logistical flexibility. However, these benefits come with notable environmental trade-offs, as each option introduces specific impact hotspots along the supply chain. LH₂, for instance, shows relatively low transport-related emissions but remains one of the least favorable options overall due to the energy-intensive liquefaction process and the use of industrial refrigerants, which strongly affect SOD, FE and HCT impact categories. The MeOH pathway exhibits a GW impact exceeding both the EU threshold for renewable hydrogen and that of locally produced blue hydrogen (via SMR-CCS), largely due to the energy requirements of the deconditioning stage. Nonetheless, green methanol could still play a strategic role when directly used in the chemical industry rather than as a hydrogen carrier. For DBT, the environmental viability strongly depends on the reuse rate of the carrier, with substantial improvements observed only beyond 500 cycles. The DBT pathway is also highly sensitive to transport distance, as its GW impact exceeds that of on-site blue hydrogen (via SMR-CCS) beyond 800 km, and even on-site grey hydrogen (via SMR) beyond 3000 km. The NH₃ pathway presents heterogeneous results. Its GW impact is relatively low compared to other options (only slightly exceeding the EU renewable hydrogen threshold), reflecting its good transport efficiency. However, this pathway generates significant environmental burdens during ammonia synthesis and cracking, showing some of the highest impacts in TA, SOD and FE impact categories. These impacts are mainly attributed to nitrogen oxide emissions from the combustion of ammonia used to supply the heat required for the cracking process, as well as nitrogen compound releases into aquatic environments and the use of refrigerants for ammonia liquefaction and storage. In addition, technological advances, particularly in chemical storage pathways (e.g., DBT dehydrogenation, NH₃

cracking, MeOH reforming), which are currently less mature than physical storage options, could shift the balance in their favor as efficiency and performance improve.

Overall, while the GW impact of green hydrogen production is significantly lower (~1 kg CO₂-eq/kg H₂), the impacts associated with its transformation, transport and storage along the supply chain can become, at best, non-negligible and, at worst, environmentally detrimental. This contrasts with fossil fuels, for which transport and storage generally represent a minor share of the total emissions compared to the production stage. Depending on parameters such as transport distance or delivered quantity, no single technical solution emerges as universally optimal. Stakeholders and decision-makers should therefore move beyond static comparisons and integrate key contextual factors. Furthermore, for real-world industrial H₂ project implementation, a more detailed LCA is recommended to capture site-specific conditions, processes and requirements. Several additional factors—such as safety considerations and hydrogen purity—may influence both environmental impacts and practical feasibility, particularly for mobility applications. We recommend that future research explicitly address these and other context-specific factors in order to refine the accuracy and applicability of hydrogen supply chain assessments.

From a methodological standpoint, this study highlights the urgent need to improve the quantification of hydrogen leakage and its atmospheric effects, as this parameter can significantly alter the environmental profile of delivery pathways and may even cause a pathway previously considered renewable to fall outside the scope of EU renewable hydrogen regulations. Future measurement campaigns and methodological developments are therefore recommended to improve the assessment of hydrogen leakage impacts. In parallel, greater transparency and granularity in LCA datasets are essential, given the current lack of high-quality, standardized data. Moreover, current European policy frameworks for renewable and low-carbon hydrogen do not account for indirect climate impacts from hydrogen leakage. They also place only limited emphasis on transport-related emissions of hydrogen. This represents a critical policy gap that should be addressed in future revisions if regulatory thresholds are to fully capture the true climate performance of hydrogen value chains.

Finally, while this analysis focuses on intra-European hydrogen ground transportation, our ongoing work now explores global trade scenarios involving maritime transport and international supply chains. Maritime shipping was deliberately excluded from the present scope, but it represents an important component of future European hydrogen logistics. Its potential impacts are multidimensional: while long-distance routes would increase absolute transport emissions, the large payload capacity of vessels compared to trucks could reduce emissions per unit of hydrogen delivered. Other aspects must also be considered, including air pollutant emissions from marine fuels—or conversely, the potential use of hydrogen itself as a fuel—as well as the need for important port and storage infrastructure. Beyond environmental performance, international maritime trade also raises strategic questions regarding resource sovereignty and geopolitical dependencies, since Europe will likely rely on imports and may not have full control over its hydrogen supply. Future research should address hydrogen ground-based transportation alongside maritime options in order to develop a comprehensive understanding of the sustainability of future European hydrogen supply chains.

### CRediT authorship contribution statement

**Salma Serghini:** Writing – original draft, Visualization, Methodology, Investigation, Formal analysis, Data curation. **Emmanuel Mignard:** Writing – review & editing, Supervision, Project administration, Funding acquisition, Conceptualization. **Stéphanie Muller:** Writing – review & editing, Supervision, Conceptualization. **Guido Sonnemann:** Writing – review & editing, Supervision, Funding acquisition.
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 acknowledge Master students Edgar Latour, Veronica E. Chavez and Edwin F. Memirieki for their help in consolidating the lMC, as well as Dr. Philippe Loubet for his technical advices.

This work benefited aid from the French state, managed by the French National Research Agency (ANR) under the France 2030 program, with the reference ANR-22-PEHY-0019.

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