This section presents the findings derived from Life Cycle Assessment (LCA) investigations pertaining to various hydrogen production methodologies documented in the scientific literature. The initial phase of data aggregation involved the systematic exploration of the Scopus database utilizing specific search queries: “LCA hydrogen production”, “Life cycle assessment hydrogen production”, “LCA H2”, and “LCA hydrogen”. Out of the initial pool of papers found, the following screening criteria were used to identify the papers to be included in the review. Firstly, the panel was restricted to studies published during the last five years. Secondly, the skimming process was done to include titles related to hydrogen production processes and technologies and, thirdly, a screening of the abstract allowed us to consider only papers related to LCA or a specific environmental index. Finally, we excluded all the works already reported in other reviews, unless it was possible to include significant information previously omitted. So, a total of 21 papers were selected for extracting data.
The following section displays the results of the methodological and technical analysis of the collected papers. Regarding the methodological approach, distinctions and evaluations were done in relation to the publication year, data quality, LCI database, LCIA methods, LCA software, functional unit (FU), system boundaries, impact indicators and allocation methods. The technical analysis primarily concentrated on the impact indicator results, trying to identify the hotspots of the processes whenever data were available. Finally, a statistic analysis of the results is presented.
3.1. Methodological Insight
In a temporal prospective, out of the 21 papers analyzed, 4 were published in 2022, 12 in 2023 and 5 during the first month of 2024. Nine different functional units (FU) were found. Eight are related to the production of 1 kg of H
2 with different specifications of the final pressure, temperature and hydrogen purity grade, while only in one paper was 1 ton of H
2 found as FU. For this latter case, the results were scaled to 1 kg of H
2. Within the first category, one kilogram of hydrogen, without any further specification on the final stage conditions, was adopted in 11 studies. Two papers also specified a final purity grade equal or higher than 99.9%, while the major differences among the rest of the works are related to the final pressure of the produced hydrogen, which was accounted equal to: 25 bar (one paper), 30 bar (one paper), 925 psig (one paper), 80 bar (two papers) and 200 bar (two papers). To enhance comparability, Valente et al., [
21] proposed a harmonization protocol that define the FU that should be used when approaching LCA of hydrogen production methods. The FU consists of 1 kg of H
2 with a purity >99%, final three-stage intercooled compression, a final pressure of 20 MPa, a temperature of 25 °C and 75% efficiency. However, although the choice of 1 kg of H
2 is the most common choice as FU, the final conditions in terms of the purity, final pressure and temperature are not usually adopted, hampering a definitive comparison.
Regarding the data quality, only three papers also considered the primary data from real plant operations or from pilot scale experiments, five used a software simulation to evaluate energy and material consumption, three do not specify the data collection process, while all the rest rely only on secondary data. The major source of secondary data across all the studies is the ecoinvent database (different versions were used, see
Table 1), which was used in 14 works, both as the only data source or to integrate the inventory analysis in the case of a lack of information for specific processes. The sole recourse of the published literature and reports was adopted in two papers, while only one used the database integrated in the GaBi software version 10.5.1.124.
With respect to the software adopted to conduct the LCA, the most used is SimaPro (seven works), followed by GaBi and OpenLCA (three works each), whilst BrightWay was the least common (one works). For the remaining seven papers, no information was provided about the choice of the program.
Five different impact assessment calculation methods (LCIA) were found. The most used are CML 2001 and IPCC 2013 GWP 100a, which were adopted in five papers each, followed by the Environmental Footprint (E.F) and ReCiPe (four papers each). Out of the remaining three studies, one used the Impact 2002+ method, while for the last two, no specific information was provided.
Regarding system boundaries, most of the papers (16) refer to a “cradle-to-gate” approach, although it is not always specified which are the operating conditions in terms of annual production and/or the lifetime of the plant. Three papers limited the studies to “gate-to-gate”, focusing the attention on the production process and excluding the raw material supply. Cradle-to-gate includes mass and energy flows from raw material extraction to the production phase, while gate-to-gate considers only the production steps that occur within the factory. Only one work also included the End-of-Life (EoL) stage by considering material recycling, incineration and landfilling from a water splitting Cu-Cl thermochemical plant powered by a concentrated solar power plant (CSP). Lastly, one paper does not specify the applied boundary condition. All the works refer to attributional LCA. In most cases, with hydrogen being the only output considered from the production process, no allocation was performed. Three papers adopted system expansion to compute the possible environmental benefits of using by-products generated within the plant as alternatives of new products available in the global market. Two papers used the cut-off approach, while mass or economic allocation were considered in one work each.
As can be seen from
Table 1, the methodological choices vary across the studies. The FU, system boundaries and type of data used are the main parameters that can affect the final results, as well as the comparability among the different works. Hence, a common strategy should be implemented to ensure comparability among the different works.
Impacts across more than 20 different indicators were reported in the reviewed papers. However, in the present work, attention is focused only on the global warming potential (GWP), human toxicity (non-cancer), acidification potential and the depletion of abiotic resources (mineral). Three environmental indexes were selected among the recommended impact indicators suggested by the JRC [
18], while human toxicity was chosen to try to evaluate which technology could be less harmful in terms of its direct impact on the population. In
Table 2, the complete list of impact indicators and the number and percentage of papers in which they are used is reported.
From the 21 reviewed papers it was possible to derive a database of 104 different LCAs since, for comparison reasons, each work considers more than one technology at a time. The most investigated technologies are PEM (27 LCAs), SMR (24 LCAs: 14 SMR and 9 SMR + CCS), gasification (14 LCAs) and AE (10 LCAs), while the least investigated is AEM with only 1 LCA. The results were further aggregated according to the hydrogen color classification.
3.2. GHG Emissions
Great variation within the results of the GWP was found among the different technologies and system configurations. An overview of all the results, together with the relative technology adopted, the allocation method, the functional unit and the system boundaries, can be found in
Table 3.
SMR is commonly used as a mature state-of-the-art process that can act as a benchmark to compare new hydrogen production technologies. Out of the 24 case studies evaluated, the GWP index was found to be in the range between of −31.68 kg
CO2eq/kg
H2 and 14.16 kg
CO2eq/kg
H2 [
39]. Both results refer to an SMR process fed by landfill gas, coupled with the gasification of the extracted waste residues from the landfill bioreactor. The only difference between the two results lies in the source of electricity used to run the system, which is supplied either by a hydropower plant (−31.68 kg
CO2eq/kg
H2) or by oil and gas-based fuels (14.16 kg
CO2eq/kg
H2). The authors refer that the negative value is due to the combined effect of using a renewable energy source with a low GWP (hydropower plant), together with a waste-derived feedstock to produce H
2. For this latter aspect, the avoided emissions that would have otherwise arisen from perpetual landfill were considered and entirely allocated to the produced hydrogen. Cho et al. [
37] investigated SMR performance by using real emission data from 33 facilities in the US in a gate-to-gate approach, finding an average GWP of 9.35 kg
CO2eq/kg
H2, mostly due to the direct release of CO
2 during the process. When also considering the emissions coming from the methane supply chain (including leakage during extraction), the final GWP was found to be equal to 11.2 kg
CO2eq/kg
H2. In the same study, a further evaluation accounted for the possible use of landfill gas instead of NG. Conversely to what was previously reported by Wijayasekera et al. [
39], the GWP could be reduced by up to 3.57 kg
CO2eq/kg
H2 thanks to the avoided emissions during biogas production and gas flaring. Weidner et al. [
34] also investigated the achievable emission reduction from now to 2050 considering the decarbonization pathways, finding a decrease of 2.8% and 14% in the GWP, respectively, for SMR and SMR + CCS. When comparing the medium values for SMR and SMR + CCS, the use of a carbon capture and storage system could provide a 50% reduction in the GHG emissions, while when analyzing the single case studies, the range is of 58−60% [
25,
28,
35].
Figure 2 graphically reports the results for the GHG emissions of SMR and SMR + CCS. The x and the horizontal line inside each box represent, respectively, the mean and the median value, while the bottom and the top of the box express the 25th and 75th percentile, respectively. The whiskers extend up to the minimum and maximum value, where these are within the difference between the 75th and 25th percentile multiplied by 1.5. If minimum or maximum are below or above these thresholds, they are represented as point outside the whiskers.
From the values reported in
Table 3, the best and worst results are both associated with PEM electrolysis, with values of −101.12 kg
CO2eq/kg
H2 [
32] and 41.4 kg
CO2eq/kg
H2 [
27], respectively, in the case of using either bioenergy with CCS or the electric grid mix of Creta island. The authors refer to the fact that the negative value associated with PEM with bioenergy is due to the combination of a biogenic carbon energy source (wood chip) together with a CCS system. The cradle-to-gate boundary condition was considered in both studies, while the functional unit differs for the final hydrogen compression stage. The use of grid energy also contributed to a higher GWP in the study of Henrsiksen et al. [
28], which found an increase in emissions from 1.83 kg
CO2eq/kg
H2 to 31.3 kg
CO2eq/kg
H2 when supplying the same PEM stack either with wind or US grid mix energy. In [
24], a PEM stack driven by wind energy or, when unavailable, by the Dutch grid generated 1.79 kg
CO2/kg
H2. Approximately 50% of emissions are due to the production of offshore wind electricity, 40% to the use of Dutch electricity mix, 8% to stack production and 2% to the BoP. The use of PV with PEM produced GHG emissions in the range of 1.19 kg
CO2/kg
H2–9.37 kg
CO2/kg
H2 [
30]. According to both Patel et al. [
29] and Zhang et al. [
30], the largest contribution to the GWP is attributed to solar plant construction, accounting for 96% and 78%, respectively. However, the absolute values differ significantly, accounting, respectively, for 2.4 kg
CO2/kg
H2 and 7.3 kg
CO2/kg
H2. The recourse of a concentrated solar power (CSP) plant led to a total GWP of 8.67 kg
CO2/kg
H2 [
30]. The only work that assesses the use of a hydropower or nuclear plant together with a PEM stack [
32] reports GHG emissions equal to 3.25 kg
CO2eq/kg
H2 and 0.77 kg
CO2eq/kg
H2, respectively. In the graph of
Figure 3, the results of the GHG emission of PEM in relation to the energy sources adopted are reported.
Four papers investigated the eco-profile of Alkaline Electrolysis (AE) for a total of 10 case studies using either photovoltaic, wind or the electric grid as the energy source. While three LCAs refer to an FU of 1 kg
H2, Kolahchian Tabrizi et al. [
22] used the harmonized protocol proposed by Valente et al. [
21]. In [
22], for a baseline scenario with outdated values of efficiency and process production for PV systems, the amount of GHG emissions for mono- and poly-PV AE are, respectively, 4.28 kg
CO2eq/kg
H2 and 3.78 kg
CO2eq/kg
H2. The share of the impact related to the PVs covers almost all the emission (approx. 98%). At the same time, the authors found that when updating the values of PV technologies, impacts can be reduced by 59% and 52%, reaching a total GWP of 1.76 kg
CO2eq/kg
H2 and 1.83 kg
CO2eq/kg
H2 for mono- and poly-PVs, respectively. Higher results were reported by Mio et al. [
25] for an alkaline electrolyzer fed either by a 100% Italian grid mix or by a floating PV plant supported by the grid when the solar source is unavailable. The grid mix was mainly based on the thermoelectric NG plant (44.3%), followed by hydropower energy (19.5%), PV (8.3%), wind (6.2%) and biofuels (5.6%); nuclear energy, coal and oil accounted, respectively, for 4.6%, 4.6% and 3.2%. The results show GHG emissions more than five times higher (23.5 kg
CO2eq/kg
H2 against 4.32 kg
CO2eq/kg
H2) when using a floating PV plant instead of the grid mix. The use of wind energy was evaluated by both Zhang et al. [
23] and Krishnan et al. [
24], considering, respectively, onshore/offshore and baseline/advanced wind farms. For all the cases, the results were between 0.11 kg
CO2eq/kg
H2 [
23] and 2.08 kg
CO2eq/kg
H2 [
24].
Seven LCAs of SOEC systems were collected from three different papers [
23,
28,
33] for cells that operate with energy coming from wind turbines, PV modules, the US grid or nuclear plants. Zhang et al. [
23] reported a GWP of 0.21 kg
CO2eq/kg
H2 and 1.49 kg
CO2eq/kg
H2 for SOEC using electric energy produced, respectively, by onshore or offshore wind power plant, used to satisfy both the electrical and thermal requirements of the system. Henriksen et al. [
28] found GHG emissions of 2.2 kg
CO2eq/kg
H2 and 2.9 kg
CO2eq/kg
H2, respectively, for wind- and PV-driven SOEC systems, with electricity being responsible for 65% and 74% of the emissions. The recourse of electric energy from the US grid raised GHG emissions by approximately one order of magnitude, reaching an overall value of 25.2 kg
CO2eq/kg
H2. Competitive results with wind-driven SOEC were achieved when recurring with nuclear power plant energy [
33]. The work from Ji et al. benefits from the primary data for nuclear fuel production, while for the rest of the inventory, secondary data were used. The calculated GWP was 0.2 kg
CO2eq/kg
H2 and 0.6 kg
CO2eq/kg
H2, respectively, in the case of the absence or presence of nitrogen in the feed stream. The major processes responsible for GHG emission are electrolysis cell manufacturing (27%), power plant construction (23%) and fuel disposal (22%), while the operation phase accounts for approximately 10%.
Five case studies were found about the LCA of water electrolysis, but without further specification of the technology adopted [
34,
35]. All works considered electric energy coming from renewable sources. Weidner et al. [
34] reported the GWP for water electrolysis fed either by an offshore wind power plant or by a PV plant in two different scenarios: a 2019 or 2050 setup, finding that wind energy can ensure GHG emissions between 64% and 74% lower with respect to PV systems (1 kg
CO2eq/kg
H2 against 3.9 kg
CO2eq/kg
H2 for the 2019 scenario and 0.5 kg
CO2eq/kg
H2 against 1.4 kg
CO2eq/kg
H2 for the 2050 scenario). Chisalita et al. [
35] calculated even lower emissions in the case of water electrolysis fed entirely by renewable energy, achieving 0.31 kg
CO2eq/kg
H2.
Hydrogen produced through AEM cells with electricity supplied by the EU grid presents GHG emissions of 2.42 kg
CO2eq/kg
H2 [
31]. From a hotspot analysis, during cell production, almost 90% of the GWP is due to the spraying process (33.99%), end plates (31.46%) and bipolar plates manufactory (23.32%). Within the spraying process, isopropanol is mainly responsible for the emission, accounting for 85% of the overall process. For the end plates, GHG emissions are due to their high mass share and the use of chromium steel that presents intense energy phases during both production and processing.
The results from the water split processes, either through the S-I or Cu-Cl cycle and coupled with a CSP plant, were reported, respectively, by Zhang et al. and by Sadeghi and Ghandehariu [
30,
42]. For the S-I cycle, the calculated GWP is 1.02 kg
CO2eq/kg
H2, mostly due to solar and hydrogen plant construction (0.78 kg
CO2eq/kg
H2 and 0.21 kg
CO2eq/kg
H2, respectively), while impacts associated with the use phase of the hydrogen production plant are almost negligible. Cu-Cl cycles can provide a benefit of 8% lower emissions, reaching 0.94 kg
CO2eq/kg
H2, with a contribution of approximately 91% associated to solar plant construction. Impacts are mostly due to the significant amount of steel, iron, glass and molten salt used for plant manufactory. The operation phase accounts only for 0.041 kg
CO2eq/kg
H2, while hydrogen plant construction and assembly is responsible for 0.14 kg
CO2eq/kg
H2. The partial recycling of different materials of the CSP, with values in the range of 16–35%, allows a negative contribution to the overall GWP of −0.15 kg
CO2eq/kg
H2.
Gasification has been widely investigated for hydrogen production due to the possibility of using different inlet feedstock, both biogenic or not. As the share of hydrogen in the produced gas is not sufficient for direct utilization, usually, a high- and low-temperature water–gas-shift reactor and a pressure swing adsorber are considered at the exit of the gasifier. From the reviewed literature, a great variation of the GWP among the different processes was found, with values ranging from −15.4 kg
CO2eq/kg
H2 [
28] to 59.2 kg
CO2eq/kg
H2 [
39], respectively, in the case of biomass gasification with CCS and for the steam gasification of plastic wastes. The work in [
39] reported a significant variation in the results when using hydropower electricity instead of traditional sources to power the system. In fact, the difference in emissions can be by even up to two orders of magnitude (59.1 kg
CO2eq/kg
H2 against 0.59 kg
CO2eq/kg
H2 in the case of oil and gas or hydropower electricity). Comparing the sole gasification with an integrated pyrolysis + gasification process, the latter scheme can drive to a GWP reduction of between 5% and 19%. GHG emissions for biomass gasification were found to be equal to 5.3 kg
CO2eq/kg
H2 (−15.4 kg
CO2eq/kg
H2 when coupled with CCS) [
28], 1.1 kg
CO2eq/kg
H2 (−13.8 kg
CO2eq/kg
H2 with CCS) [
32] and 1.5 kg
CO2eq/kg
H2 [
40], respectively, when using southern yellow pine, poplar wood, or bio-oil coming from the pyrolysis of sawmill by-products. The latter case is the only that refers to a gate-to-gate approach, not including the energy and material consumption for three cases of cultivation and harvesting, since the feedstock is considered as a by-product of a different system. Waste plastic gasification was studied by Salah et al. [
32] and by Williams et al. [
36] with different gasification agents. In [
36], an equal share of waste plastic and biomass were gasified with either oxygen, air or steam, achieving a total GWP of 16 kg
CO2eq/kg
H2, 24 kg
CO2eq/kg
H2 and 40 kg
CO2eq/kg
H2, respectively. A significantly lower value was calculated in [
32] through the steam gasification of 100% waste polymers, finding GHG emissions of 9.7 kg
CO2eq/kg
H2 and 1.3 kg
CO2eq/kg
H2, respectively, for gasification and gasification + CCS. In this case, the authors considered the avoided landfill or incineration of plastic wastes, accounting it for −2.4 kg
CO2eq/kg
H2, while no specific mentions were found in [
36].
The pyrolysis of methane and/or hydrogen sulfide was also investigated, reporting GHG emissions between 4.5 kg
CO2eq/kg
H2 and 8.1 kg
CO2eq/kg
H2 [
29,
38]. Sole methane pyrolysis, when operated with shipped liquefied NG instead of pipelines NG, produces approximately 37% more CO
2eq emissions, raising them from 5.9 kg
CO2eq/kg
H2 to 8.1 kg
CO2eq/kg
H2.
Promising results were reported for chemical looping technologies either with iron-based (Fe) or copper-based (Cu) oxygen carriers, which, respectively, generates 1.0 kgCO2eq/kgH2 and 1.9 kgCO2eq/kgH2. Since processes rely on NG as a feedstock, 85% and 47% of the emissions are due to the gas supply chain, respectively, for Fe- and Cu-based O2 carrier processes. The second major source of emissions is the hydrogen production section due to CO2 treatment stages (drying and compression), which account for 6.3% and 42.6% of Fe-based and Cu-based O2 carrier processes. The greater share for this latter case is mostly due to the partial decomposition of CaCO3 in the calciner, which directly releases CO2 into the environment.
The combination of biological processes, namely hydrolysis and fermentation, for food wastes (FW)’s conversion into hydrogen, was studied as a possible alternative to landfill disposal [
41]. Out of the 10.1 kg
CO2eq/kg
H2 generated, approximately 57% are due to gas compression, 17% to electricity consumption and 14% to FW transport (considered equal to 100 km with a 32 metric ton EURO5 truck). Avoided landfill contributed with −8.3 kg
CO2eq/kg
H2.
The following
Figure 4 graphically reports the results of the presented studies, grouping the technologies according to the color classification commonly adopted. The average value of the SMR to be used as a reference benchmark to visualize the technologies that could guarantee lower emissions was also included. This latter parameter was calculated as the mean among all the GWP results for the SMR technology presented in
Table 3. Water electrolysis systems were grouped in green, yellow and pink hydrogen, respectively, when coupled with energy coming from renewable sources, an electric grid or nuclear power plants. Blue and turquoise hydrogen refers, respectively, to SMR + CCS and methane pyrolysis. Waste and biomass/biowaste gasification are not included in any color classification, hence they were reported with the process definition name. For each technology, results that are significantly off-scale with respect to the general findings were excluded from the graph.
3.3. Acidification Potential
The concept of the acidification potential refers to the deposition of acidifying agents onto various environmental compartments such as soil, groundwater, surface waters, living organisms, ecosystems and substances. Principal acidifying agents include sulfur dioxide (SO2), nitrogen oxides (NOx) and ammonia (NHx). Acidifying agents instigate a broad spectrum of effects on soil quality, groundwater purity, surface water integrity, organismal health, ecosystem stability and material integrity.
Out of the 12 papers that report results for the acidification potential, two distinct unit measures were found. The most commonly used is kg
SO2eq which was found in 77% of the cases, while the rest adopted molH
+eq/kg
H2. To facilitate a comparison, the results were only expressed as molH
+eq/kg
H2 by using the conversion factor reported in [
43]. The lowest and highest values were of 3.9 × 10
−4 molH
+eq/kg
H2 [
30] and 2.2 × 10
−1 molH
+eq/kg
H2 [
39], respectively, for onshore PEM and SMR with landfill biogas. Regarding water electrolysis, PEM presents values between 3.9 × 10
−4 molH
+eq [
30] and 4.4 × 10
−2 molH
+eq/kg
H2 [
30] when coupled with onshore wind turbines or a CSP plant. From the seven LCAs reporting the AP values of PEM, it resulted in an average emission of 1.8 × 10
−2 molH
+eq/kg
H2. A similar trend was found for AE, with minimum and maximum emissions of 5.4 × 10
−4 molH
+eq/kg
H2 and 1.0 × 10
−1 molH
+eq/kg
H2, respectively, when using electric energy coming from an onshore wind power plant [
23] or floating PV [
25]. The calculated mean value was found equal to 1.8 × 10
−2 molH
+eq/kg
H2. The hotspot analysis reported in [
24] showed that between 45% and 49% of the impacts are related to stack production, while the rest is almost entirely related to the energy supply. Regarding the stack components, the bipolar plate in AE cells is the major source of emissions (52% of the total) due to the high steel and nickel content. SOEC presents fewer scattered results than the other electrolysis technologies, with average emissions of 2.6 × 10
−3 molH
+eq/kg
H2, out of a minimum and maximum value of 7.8 × 10
−4 molH
+eq/kg
H2 and 6.0 × 10
−3 molH
+eq/kg
H2, respectively, when coupled with an onshore or offshore wind power plant [
23]. The only work concerning AEM reports an acidification potential of 2 × 10
−2 molH
+eq/kg
H2 [
31]. From the hotspot analysis of the cell, it results that almost 50% of the impacts are associated with bipolar plates, with the nickel supply being mainly responsible due to the emission of sulfur dioxide during material extraction. This condition can also be found for the emission associated with Ni foam which, despite the reduced mass, accounts for 11.5% of the overall impacts associated with cell components. For PEM technology, the gold in the Porous Transport Layer (PTL) is present in the anode and cathode account for most of the impacts. Zhang et al. [
23] reported also that when coupling electrolysis technologies with wind power systems, PEM can guarantee 40% and 102% lower emissions with respect to AE and SOEC, mostly due to the lower use of copper for cell manufactory and operation. For SOEC cells, Ji et al. [
33] also reported that a significant source of emissions is the manufactory process of ferrochrome and yttrium oxide.
The S-I cycle and Cu-Cl water splitting, respectively powered by nuclear or CSP plants, reported an acidification potential of 1.2 × 10
−3 molH
+eq/kg
H2 [
33] and 1.1 × 10
−2 molH
+eq/kg
H2 [
42], respectively. The results from chemical looping technologies with either Fe- or Cu-based O
2 carriers present AP in the range of 1.4 × 10
−3 molH
+eq/kg
H2 and 3.1 × 10
−3 molH
+eq/kg
H2 [
35].
For SMR, the impacts were in the range between 1.3 × 10
−3 molH
+eq/kg
H2 [
35] and 1.6 × 10
−2 molH
+eq/kg
H2 [
25], while the use of CCS led to an increase of 20%, with a total emission of 1.9 × 10
−2 molH
+eq [
25]. Between one and two orders of magnitude higher values of AP were found for the thermochemical treatment or process gases derived from MSW [
39]. The gasification of bio-oil derived from the pyrolysis of sawmill waste biomass account for 4.2 × 10
−3 molH
+eq/kg
H2, mostly due to the sulfur emission associated with the production and use of the NG used in the reforming process and to the acid gases released during pyrolysis [
40]. Lower emissions (4.0 × 10
−4 molH
+eq/kg
H2) were calculated in relation to the reforming of the biogas produced in an anaerobic digestion plant operating with biological wastes. In fact, the possible application of the digestate material as agricultural soil improver avoids the emission of acid that would have been otherwise generated for the production of fertilizers [
40]. The following
Figure 5 shows the trend in acidification potential for all the different technologies.
3.4. Material Depletion
Material depletion is one of the two categories that are generally included in the Abiotic Depletion Potential (ADP) and it is commonly measured either in kg
Sbeq or in kg
Cueq, according to the impact category assessment method used. Eight papers reported the material depletion potential, six using Antimony as the reference material, while the remaining two refer to Copper. According to Tabrizi et al., AE coupled with a PV power plant resulted in 1 × 10
−4 kg
Sbeq/kg
H2 and 1.1 × 10
−4 kg
Sbeq/kg
H2, respectively, in the case of mono- and polycrystalline PV plants [
22], while Mio et al. refer to 5.1 × 10
−2 kg
Cueq/kg
H2 both in the cases of the energy supplied through a floating PV plant or the EU grid [
25]. The work conducted by Krishnan et al. reported lower impacts when using wind energy, achieving an index of material depletion of 5.6 × 10
−5 kg
Sbeq/kg
H2 [
24]. From the hotspot analysis of the stack components, it resulted that 51.8% of the impacts are associated with the manufactory of the bipolar plate, 33.2% to the anode, while the cathode and end plate accounted, respectively, for 13.1% and 1.2% [
24]. Similarly, also for PEM cells, the highest impacts shared are associated with the production of the bipolar plate (65.6%), followed by the PTL which accounted for 23.4%, while 8.1% are associated with the anode. The cathode and end plate account, respectively, for 2.8% and 0.1% [
24]. As previously reported for AE, and also for PEM, a significant reduction in the impacts (≅50%) can be achieved when passing from the EU grid [
31] to wind energy [
24] (2 × 10
−4 kg
Sbeq/kg
H2 against 9.8 × 10
−5 kg
Sbeq/kg
H2). A critical material assessment conducted by Schropp et al. [
31] reported a more severe condition for PEM, with respect to AEM, mostly due to the use of Iridium and Titanium during cell production. In the same paper, the material depletion for AEM is reported as being equal to 2 × 10
−4 kg
Sbeq/kg
H2, together with an impact repartition in relation to the manufacturing process. On a percentage basis, the highest impact share is due to the bipolar plate (26.8%), despite its lower mass with respect to the end plate, which instead accounts for 25%. Similarly, the NiMo catalyst, although it accounts for less than 1% in its mass share, it is responsible for 10.4% of the final impact, almost entirely due to the presence of the molybdenum.
Two papers also analyzed the ADP for SMR, finding values of 2.5 × 10
−3 kg
Cueq/kg
H2 and 7.8 × 10
−3 kg
Cueq/kg
H2 [
25,
35]. When integrating the system with a CCS, increases in the impacts by 8% and 34% were found. However, the reuse of the sorbent in cement factories could reduce impacts by approximately 13% [
35].
Pyrolysis, gasification and integrated pyrolysis with the gasification of MSW resulted in 3 × 10
−3 kg
Cueq/kg
H2, 4 × 10
−3 kg
Cueq/kg
H2 and 5 × 10
−3 kg
Cueq/kg
H2, respectively, with reactors heated through NG and electric energy coming from a thermoelectric power plant [
39]. Integrated pyrolysis and gasification were also studied by Arfan et al. [
40] using waste biomass derived from a sawmill plant, resulting in 1.1 × 10
−5 kg
Sbeq/kg
H2. The authors report that more than 50% of the impact is related to the reforming process of pyrolysis oil, due to the use of NG. Coupling steam reforming with the anaerobic digestion of biowaste led to a negative impact equal to −1.8 × 10
−5 kg
Sbeq/kg
H2, thanks to the use of digestate that replaces fertilizer production [
40]. These latter results are the only one referring to gate-to-gate system boundaries, while in all the others, it was considered a cradle-to-gate.
3.5. Human Toxicity Non-Cancer
Nine papers evaluated the non-carcinogen human toxicity of different hydrogen production routes. In most of cases (four papers), the authors refer to kg1,4DCBeq.Two further unit measurements were found, expressing the impacts in CTUh and gDCBeq. One paper refers to generic human toxicity potential, without a distinction among carcinogens and non-carcinogens.
When expressing the impacts through CTUh, comparable results were found for wind-driven AE and PEM, reporting, respectively, 3.99 × 10
−8 and 4.05 × 10
−8 CTUh/kg
H2 [
24]. Most of the impacts are associated with the electricity supply, which accounts for 80% and 87%, respectively, for AE and PEM, mostly due to the intensive use of copper. Impacts shared for stack production are in the range of 12–19%. In AE cells, around 50% of stack impacts are related to the bipolar plate, 28% to the anode and 17% to the cathode. In PEM, the anode and bipolar plate account approximately for 35% each, 19% is associated to the PTL and 12% to the cathode. The presence of nickel, and to a lower extent, of steel, in the bipolar plate and electrode, is the major source of impacts. For both technologies, BOP and PE account for less than 1.5%. The use of EU grid electricity instead of wind raises the impacts of PEM by approximately one order of magnitude, resulting in 1.3 × 10
−7 CTUh/kg
H2 [
31]. A similar trend was found for AE with PV energy instead of wind, which turned into an increase in impacts up to 1.5 × 10
−7 CTUh/kg
H2 [
22]. The analysis of AEM coupled with EU grid electricity accounted for 1.3 × 10
−7 CTUh/kg
H2, with more than 95% of the impacts related to electricity production [
31]. Considering only the cell itself, the end plates are responsible for the vast majority of impacts (34.1%), followed by the bipolar plates (26.5%), and the spraying process (22.4%). A better performance can be achieved with SMR, with a human toxicity impact of 2 × 10
−8 CTUh/kg
H2 [
31].
Considering the studies that refers to kg
1,4DCB_eq, a significant discrepancy among the results was found regarding for SMR. The lowest value was found by Cho et al. [
37], reporting a final impact of 1.5 × 10
−3 kg
1,4DCB_eq/kg
H2. Between one and two orders of magnitude higher values were calculated by Chisalita et al. [
35] and Mio et al. [
25] in a cradle-to-gate analysis, finding emissions of 3.2 × 10
−2 kg
1,4DCB_eq/kg
H2 and 9.1 × 10
−1 kg
1,4DCB_eq/kg
H2, respectively. The integration with a CCS system further raised the impacts between 19% and 81%.
Chemical looping with an Fe-based O
2 carrier and sorption-enhanced reforming with Ca-based sorbent, used with or without a copper-based O
2 carrier, reported impacts of 3.5 × 10
−2 kg
1,4DCB_eq/kg
H2, 4.7 × 10
−2 kg
1,4DCB_eq/kg
H2 and 4.8 × 10
−1 kg
1,4DCB_eq/kg
H2, respectively [
35]. For the first case, almost all the impacts are associated with the NG supply chain and wastewater treatment, accounting respectively for 71.6% and 25.5%. For sorption enhanced chemical looping with Cu based O
2 carrier, more than 90% of the final impacts are related to the CuO supply chain, 6% to NG supply, and 2% to the waste water treatment. Negative values were reported by both Arfan et al. [
40] and Wijayasekera et al. [
39], in case of thermochemical processes of either organic or MSW. In [
40], the gate-to-gate analysis resulted in −2.7 × 10
−1 kg
1,4DCB_eq/kg
H2, thanks to the avoided emissions resulting from the use of liquid digestate as an alternative to the production of fertilizers. In fact, the system expansion approach allowed to account for material and energy consumption, as well as harmful emissions (N-compounds, phosphate, or heavy metals), that would had been otherwise associated to the production of biofertilizer. Hence, these impacts were subtracted from the results of the hydrogen production process, comporting negative emission values. The work of Wijayasekera et al. [
39] encompasses 32 different scenarios in cradle-to-gate system boundaries but, considering NG for reactor heating and transportation fuel, together with electricity produced from oil and gas, impacts resulted to be in the range from −4 × 10
−1 kg
1,4DCB_eq/kg
H2 to −1.7 × 10
−1 kg
1,4DCB_eq/kg
H2.
The nuclear-based S-I cycle and SOEC hydrogen production were found to have comparable emissions ranging from 1.1 × 10
−1 kg
1,4DCB_eq/kg
H2 to 1.4 × 10
−1 kg
1,4DCB_eq/kg
H2 [
33]. In both cases, hydrogen plant construction resulted in being the main contributor to the overall impacts. The highest impacts reported in kg
1,4DCB_eq/kg
H2 are related to AE fed wither with Italian grid mix or floating PV which accounted, respectively, for 1.2 × 10
1 kg
1,4DCB_eq/kg
H2 and 1.8 × 10
1 kg
1,4DCB_eq/kg
H2 [
25].