The sustainability of supply chains for green hydrogen production is compared from a life cycle point of view: 1) offshore electrolysis with electricity from Dutch wind farms followed by pipeline transport of hydrogen to Rotterdam (Netherlands), 2) onshore electrolysis in Rotterdam with electricity from the same wind farms, 3) electrolysis with electricity from solar PV in Algeria followed by pipeline transport of hydrogen and 4) electrolysis and ammonia production with electricity from solar PV in Saudi Arabia followed by deep sea transport and ammonia cracking. The environmental sustainability is assessed with ReCiPe 2016 and Environmental Footprint 3.0. The Total Cumulative Exergy Loss (TCExL) method is used to calculate the exergetic sustainability. According to the endpoint scores, offshore electrolysis with wind energy is preferred, but the difference between the TCExL scores of both wind energy options is small. The preference order of the other supply chains is undecided. The offshore wind option is also preferred according to the midpoint indicators GWP/climate change, land use and water consumption/use. It is advised that the systems be investigated in more detail before drawing conclusions about the order of preference and that also attention be paid to the economic and social pillars of sustainability.

Purpose: Life cycle assessment (LCA) studies have overlooked the potential range of biochar’s effects on agricultural soils. Only several of the numerous soil effects reported in empirical studies have been included in LCA models. This study aims to establish a consistent lifecycle inventory (LCI) approach to include biochar’s soil effects in LCA and assess the conceptual applicability of LCA to model soil effects. Methods: To exemplify this approach, a case study was conducted, which also provides insight into the environmental implications of biochar’s soil effects and whether LCA results can help guide biochar optimization for greater environmental benefits. For soil effects that met all inclusion criteria, empirical data was selected based on controlling factors and translated into inventory data. The LCI approach was applied to a case study in Aguascalientes, a semi-arid state in central Mexico that suffers from droughts. Results: The combined soil effects have a substantial overall impact across all impact categories, mostly dwarfing upstream biochar production and treatment impacts. This is driven by the persistent soil effects; the transient soil effects contribute far less. Biochar primarily leads to a net environmental benefit in an impact category, strongly depending on the soil effect literature data that is selected. While some soil effects have been researched sufficiently to produce sensible meta-analyses (e.g. crop yield increase), others have only been quantified a handful of times or solely qualitatively assessed (e.g. fire hazard increase). Most soil effects have a non-intermediate impact and can be modelled as intervention or economic flow in some form, with some missing appropriate characterization models. Biochar’s soil effects have a substantial environmental effect and cannot be ignored. A highly accurate inclusion of soil effects in LCA is hindered by several conceptual (non-linearity of soil effect expression, missing characterization models, focus on environmental impact) but mostly data-related (availability of long-term empirical field data) constraints. Conclusion: Although the results varied across scenarios due to differences in model assumptions and uncertainties, they provided in order of magnitude trends that still allowed for informed conclusions on how to tailor biochar in Aguascalientes to maximize environmental benefits while minimizing associated risks (e.g. increasing pyrolysis temperature to reduce PAH content).

Life cycle assessment (LCA) is a reference methodology to evaluate environmental impacts along supply chains of products. Planetary boundaries (PBs) were developed to define the safe operating space (SOS) for humanity. So far, no study has investigated whether wine production and consumption result in crossing the planetary boundary of climate change and no SOS has been calculated for wine production in Greece. Our study applies an LCA according to the European Product footprint environmental category rules to calculate the climate change score of a bottle of 0.75 L of Greek red organic wine in 2021 and 2026, and also applies planetary boundaries to investigate whether the climate change boundary is exceeded. The latter employed the calculation of a SOS based on four partitioning methods: grandfathering principle, economic value, agricultural land area use, and calorific content. The LCA results showed that wine is a carbon emitter. The 2021, 2026-Low yield, and 2026-High yield systems resulted in positive climate change scores between 0.69–1.14 kg CO₂ eq.bottle wine⁻¹. The PBs revealed that carbon emissions of wine production in 2021 exceeded all four SOSs, while carbon emissions of expected wine production in 2026 remained within the SOS of grandfathering, economic value and agricultural land area use partitionings, but exceeded the SOS of the caloric content partitioning. The PB method can be complementary to LCA results in terms of providing context to decision-makers in business and public policy on whether red organic wine production and consumption remain within ecological constraints on human development.

This paper evaluates the potential impacts of introducing low-carbon intensity hydrogen technologies in two oil refineries with different complexity levels, emphasizing the role of hydrogen production in reducing CO₂ emissions. The novelty of this work lies in three key aspects: Comprehensive system analysis of refinery complexity using real site data, integration of low-carbon Hydrogen technologies, long-term and short-term strategies. Two Colombian refineries serve as case studies, with technological solutions adapted to their complexity levels. The methodology involves evaluating different options for hydrogen production, accounting for improvement in technological efficiency over time. The refinery systems were evaluated in a cost-optimization model built in Linny-r. Three different scenarios were considered, Business-As-Usual (BAU), high, and low-ambitions decarbonization scenarios, focusing on the time horizons of 2030 and 2050. When comparing the two case studies, the preferred decarbonization strategy for both facilities involves the substitution of SMR technology with water electrolyzers powered by renewable electricity. Post-2030, biomass-based hydrogen technology is still a costly alternative; however, to achieve CO₂ neutrality, negative emissions storage of biogenic CO₂ emerges as an achievable alternative. Our results indicate the achievability of CO₂ reduction objectives in both refineries. Our results show that achieving long-term CO₂ neutrality requires both refineries to increase renewable electricity production by 5 to 6 times for powering water electrolyzers, steam production by 2 to 2.5 times for CO₂ capture, and supply of dry biomass by 2.6 to 4.5 kt/d. The two most significant factors influencing the refining net margin in the decarbonization scenarios are primarily the CO₂ and the renewable electricity prices. The short-term horizon emerges as the pivotal period, particularly within the high-ambition decarbonization scenarios. In this context, the medium complexity refinery demonstrates economic viability until a CO₂ price of 140 €/t CO₂, while the high complexity refinery endures up to 205 €/t CO₂. The high complexity refinery is better prepared to face the challenges of decarbonization and the impacts generated on the refining margin. Compared to the BAU scenario, the high complexity refinery shows a negative impact on the net margin that corresponds to a 40 % and 5 % reduction in the short and long term, respectively. Meanwhile, for the medium complexity refinery, the impact on net margin amounts to a 52 % reduction in the short term and a 27 % improvement in the long term. Furthermore, our research highlights the significant potential for reducing CO₂ emissions by fully eliminating the use of refinery gas as fuel, providing alternative applications for it beyond combustion.

This research uses system optimization to assess short, medium, and long-term scenarios to achieve the committed CO₂-emission goals of Ecopetrol while minimizing potential adverse impacts such as incremental operational costs and utility demand. Two Colombian refineries are used as a case study: a medium-complexity and a high-complexity refinery. The study explores whether the level of complexity plays a significant role in the results. Potential technologies were ranked using a multi-criteria decision analysis. The system analysis and optimization were done in Linny-R, a mixed integer linear programming software package developed by TU Delft. In the short-term (2030) scenario, the selected technologies include low-carbon H₂ produced from Steam Methane Reformer units with carbon capture and storage and H₂ produced from renewable electricity sources. The medium and long-term (2050) scenario also included biomass gasification, naphtha reforming, and the cracking unit, all with carbon capture and storage. The refineries were modelled using on-site company data. The results indicate that using low-carbon H₂ and carbon capture and storage to flue gases would allow to reach the net zero target. Furthermore, the results show that the level of complexity in a refinery significantly impacts the decarbonization deployment pathways. The high-complexity refineries benefited from using low-carbon H₂ as feedstock while the medium-complexity refinery relied on a combination of carbon capture and low-carbon H₂ as an alternative fuel. This research highlights the potential to achieve substantial CO₂ emissions reductions with less impact on the total operational cost by using the amount of excess refinery gas generated when H₂ is used as fuel in boilers and process furnaces. A significant challenge remains in identifying suitable applications for surplus refinery fuel gas beyond its conventional use in combustion within boilers and furnaces.

Life Cycle Assessment (LCA) is a powerful tool for achieving sustainability. Traditional LCAs analyze well defined and developed industrial systems, but recent developments of LCA focus on analyzing emerging technologies which are not yet optimized with respect to energy and materials. Therefore, LCA results of ex-ante applications can be very different from ex-post applications for the same system. The purpose of this study is to show the different effects of data scales on LCA results regarding global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication potentials. For this purpose torrefaction technology was selected as the case study and assessed based on bench scale data, lab scale data, data derived from process simulations, pilot scale data and commercial scale data. Considered environmental impacts were global warming, fine particulate matter formation, terrestrial acidification and freshwater eutrophication. Results showed that process efficiencies improved significantly between the bench scale system and systems with higher technology readiness levels (TRLs), such as pilot, process simulations and commercial scale systems. Furthermore, process simulations result in scores closer to commercial scale regarding all considered environmental impacts. However, if LCA practitioners focus only on global warming impact, then pilot scale is also a good alternative. Finally, due to torrefaction technology being relatively simple in terms of raw materials input, we suggest more complex chemical systems to be assessed with LCA in various TRLs.

The Netherlands aims at reducing natural gas consumption for heating in the housing sector. Although homeowners are responsible for replacing their heating systems and improving dwelling insulation, they are not always able to make individual decisions. Some projects require group decisions within and between buildings. We use an agent-based modelling and simulation approach to explore how these individual and group decisions would influence natural gas consumption and heating costs in an illustrative neighbourhood, under a set of assumptions. We model individual household preferences over combinations of insulation and heating systems as a lifetime cost calculation with implicit discount rates, and we use quorum constraints to represent group decisions. We model three fiscal policies and a policy to disconnect all dwellings from the natural gas network. Results show that the disconnection policy was the only necessary and sufficient condition to incentivize households to replace their heating systems and that group decisions influenced the alternatives that were chosen. Since results were influenced by group decisions within buildings and by the market discount rate, we recommend further research regarding policies around these topics. Future work can apply our approach to case studies, incorporate new empirical knowledge, and explore group decisions in other contexts.

MSocial Life Cycle Assessment (S-LCA) uses a life cycle perspective to assess social impacts of products, and the S-LCA guidelines describe developing the system boundaries based on a factory-level perspective. However, such a perspective may exclude stakeholders with a negative social performance which are cooperating with a factory but are not directly involved with the product under study, and it can result in a step back on corporate social responsibility (CSR). Our study aimed to align S-LCA with the CSR concept. Therefore, we designed a case study for the manufacturing sector in which we practiced expanding the system boundaries of S-LCA. Our results showed larger social risks after expanding the system boundaries due to subsidiary and supplier companies located in countries with less strict regulations than the Netherlands, which is where the main organizations and parent company existed. We conclude that system boundaries expansion can result in more complete picture of the involved organizations, and lead practitioners to approach S-LCA with the goal of improving social conditions and identify companies which deserve excellent or poor social scores. Its usefulness is mostly expected when S-LCA practitioners aim to identify social hotspots in supply chains in socially sensitive markets.