Electricity Mix Research Articles

Assessing the Carbon Intensity of e-fuels Production in European Countries: A Temporal Analysis

The transport sector heavily relies on the use of fossil fuels, which are causing major environmental concerns. Solutions relying on the direct or indirect use of electricity through e-fuel production are emerging to power the transport sector. To ensure environmental benefits are achieved over this transition, an accurate estimation of the impact of the use of electricity is needed. This requires a high temporal resolution to capture the high variability of electricity. This paper presents a previously unseen temporal analysis of the carbon intensity of e-fuels using grid electricity in countries that are members of the European Network of Transmission System Operators (ENTSO-E). It also provides an estimation of the potential load factor for producing low-carbon e-fuels according to the European Union legislative framework. This was achieved by building on top of the existing EcoDynElec tool to develop EcoDynElec_xr, a python tool enabling—with an hourly time resolution—the calculation, visualisation, and analysis of the historical time-series of electricity mixing from the ENTSO-E. The results highlight that, in 2023, very few European countries were reaching low carbon intensity for electricity that enables the use of grid electricity for the production of green electrolytic hydrogen. The methodological assumptions consider the consumption of the electricity mix instead of the production mix, and the considered time step is of paramount importance and drastically impacts the potential load factor of green hydrogen production. The developed tools are released under an open-source license to ensure transparency, result reproducibility, and reuse regarding newer data for other territories or for other purposes.

Comparative Life Cycle Assessments of Laboratory and Pilot-Scale Mechanochemical Processes for Producing Carbonated Mineral Products as Cement Substitutes.

The use of carbonated mineral products in cement production reduces carbon emissions and enhances durability. This study evaluated the environmental sustainability of using mineral carbonated biomass fly ash (BFA) as a partial cement replacement in European cement production. Laboratory-scale and simulated large-scale scenarios were analysed. Incorporating 20% mineral carbonated BFA showed potential for a 33% reduction in the annual Global Warming Potential (GWP) of cement products. Energy consumption factors, such as ball milling and mineral carbonation processes, were evaluated using a machine learning model and comminution flow sheet model simulations. The machine learning model predicted CO2 absorption and energy requirements for mineral carbonation, showing greater efficiency in large-scale scenarios. Life cycle assessments consistently revealed GWP reductions for OPC-BFA mixtures, with additional emissions reductions when incorporating flow sheet modelling and machine learning data. However, the study's limitations include simplified CO2 flue gas treatment, use of the mean EU electricity mix, exclusion of transportation impacts, and reliance on simulation data. Additionally, the cement mix exhibited reduced compressive strength. This study highlights the potential of mineral carbonated BFA to reduce cement production's environmental impact while emphasising the need for balanced optimisation between sustainability and material performance.

In Search of Energy Security: Nuclear Energy Development in the Visegrad Group Countries

The Visegrad Group, comprising Czechia, Hungary, Poland, and Slovakia, has several common features, including their geographical proximity, membership in the EU and NATO, and similar levels of economic development. However, they also have significant differences. The Russian invasion of Ukraine has exposed new disagreements among them, particularly regarding how to ensure energy security amid a changing geopolitical landscape and the issue of sanctions on Russian energy supplies. Despite these differences, the Visegrad Group countries have shown unity in their approach to nuclear power. Although their use of nuclear technology varies, they have recently aligned their nuclear energy policies. Czechia and Slovakia have a long history with nuclear technology, dating back to the 1970s, while Hungary began its nuclear program in the 1980s. Poland, which had paused its nuclear program after the Chernobyl disaster, has recently resumed its nuclear energy efforts. All four countries aim to expand their nuclear energy capacity to either maintain or increase its share in their electricity mix. This paper provides a comparative analysis of their nuclear energy policies, focusing on the political initiatives driving advancements in this field. It argues that these nations see nuclear energy as crucial for creating a resilient, crisis-resistant, and secure energy sector.

Correction: Balancing cleaner energy and geopolitical interests in the complex transition of the European electricity mix: from Fukushima to the Ukraine war

Correction: Balancing cleaner energy and geopolitical interests in the complex transition of the European electricity mix: from Fukushima to the Ukraine war

PV Module Soiling Detection Using Visible Spectrum Imaging and Machine Learning

During the last decades photovoltaic solar energy has continuously increased its share in the electricity mix and has already surpassed 5% globally. Even though photovoltaic (PV) installations are considered to require very little maintenance, their efficient exploitation relies on accounting for certain environmental factors that affect energy generation. One of these factors is the soiling of the PV surface, which could be observed in different forms, such as dust and bird droppings. In this study, visible spectrum data and machine learning algorithms were used for the identification of soiling. A methodology for preprocessing the images is proposed, which puts focus on any soiling of the PV surface. The performance of six classification machine learning algorithms is evaluated and compared—convolutional neural network (CNN), support vector machine (SVM), random forest (RF), k-nearest neighbor (kNN), naïve-Bayes, and decision tree. During the training and validation phase, RF proved to be the best-performing model with an F1 score of 0.935, closely followed by SVM, CNN, and kNN. However, during the testing phase, the trained CNN achieved the highest performance, reaching F1 = 0.913. SVM closely followed it with a score of 0.895, while the other two models returned worse results. Some results from the application of the optimal model after specific weather events are also presented in this study. They confirmed once again that the trained convolutional neural network can be successfully used to evaluate the soiling state of photovoltaic surfaces.

Production and recycling of blast furnace slag: A life cycle assessment approach in India

AbstractThis article investigated the cradle‐to‐gate environmental impact of granulated blast furnace slag (GBFS) produced in the steel industry and replacement of blast furnace (BF) slag (50%) in place of clinker in Portland slag cement using GaBi software (Indian extension database). In case of GBFS production, maximum burden on the environment is due to BF slag production and the amount of electricity consumed (161 MJ/ton) during the granulation process. The influence of electricity sources on GBFS production was studied via scenario analysis. For investigation, solar and thermal electricity mixes were considered in 50:50 and 75:25 ratios. For the 75:25 ratios, the abiotic depletion potential (fossil), acidification, eutrophication, global warming, and human toxicity potential show a decreasing trend of approximately 45%, 49%, 48%, 46%, and 41%, respectively. The scenario analysis of BF slag transportation (from 100 to 750 km) demonstrates a negative impact due to fuel. The results quantitatively confirm that the addition of GBFS can lower the overall impact for construction and steel industries.

Health benefits of US light-duty vehicle electrification: Roles of fleet dynamics, clean electricity, and policy timing

We present a dynamic perspective to quantify the air quality-related health impacts of the electrification of light-duty vehicles in the United States between 2022 and 2050. Using a fleet turnover model and future electricity generation mix scenarios, we compare ambitious vehicle electrification to fleet renewal relying on newer internal combustion engine vehicles, without electric vehicles. The model includes vehicle-level pollutant emission factors and a reduced complexity air quality and valuation model and covers direct (tailpipe, brake wear, and tire wear) and indirect (production of electricity and liquid fuels) emissions of NOx, SO2, PM2.5, NH3, and VOCs, with a breakdown at the county level to identify geographical disparities in the distribution of health impacts. Short-term health benefits are mostly generated by reductions in NOx emissions from newer gasoline vehicles, while fleet electrification generates further benefits in the long term. The electricity mix plays a crucial role in the success of electrification policies. With continued grid decarbonization, electrification would reduce harmful air quality-related health impacts cumulatively by 84 to 188 billion USD over the study period, compared with fleet renewal without electric vehicles. In contrast, artificially freezing the 2022 grid would make electrification responsible for 32 to 71 billion USD additional health disbenefits compared with fleet renewal. Finally, we show that while fleet electrification achieves most of its benefits over fleet renewal in the long term, delaying the implementation of such policies would sacrifice meaningful cumulative benefits.

Applying trade mechanisms to quantify dynamic GHG emissions of electricity consumption in an open economy - The case of Switzerland

Quantifying greenhouse gas (GHG) emissions from electricity consumption presents a significant challenge due to the variable nature of the generation mix throughout the year and the complex dynamics of cross-border electricity trade. In this paper, we introduce an innovative methodology designed to accurately capture the hourly GHG emissions linked to electricity imports, and thus electricity consumption. Contrary to conventional approaches, our methodology identifies the relevant generation technologies in exporting countries which are activated for export. This selection is based on (i) the classification of the technologies according to their dispatch cost (merit order), and (ii) considers trade mechanisms from economic theory.We apply this methodology to Switzerland, a country characterized by a low-carbon electricity generation mix, which however heavily relies on imports from neighbouring countries, particularly during the winter months. Over the period from 2017 to 2021, we find that 88 % of Switzerland's domestic electricity demand is met by its own generation—primarily hydro and nuclear—while the remaining 12 % is imported, mainly from fossil-fuel-based sources. Consequently, the average annual GHG emission factor for electricity consumption in Switzerland is 98 g-CO2eq/kWh, with 29 % attributed to domestic generation and 71 % to imports. This figure is 40 % higher than the 70 g-CO2eq/kWh estimated using a conventional approach, which typically underestimates the specific impacts of electricity imports.The disparity between these approaches becomes even more pronounced when considering the seasonal and hourly variations in the electricity mix and the resulting emission factors. These insights are particularly crucial in the context of emerging electricity demands, such as heat pumps and electric vehicles, where accurate GHG accounting can significantly influence policy and investment decisions.

Combining expansion turbines, heat pumps, and low-temperature solar heat for enhanced primary energy savings in gas pressure regulating stations

According to previous studies, gas pressure regulating and metering stations (GPRMS) in Germany account for a primary energy consumption between 1.4 and 2.0 TWh/a for the preheating of natural gas flowing through. This work assesses the potential of reducing this consumption through the combined use of expansion turbines, heat pumps, and solar thermal collectors. For this purpose, operation data of 57 GPRMS of a German gas network operator are used to design systems combining in different scenarios two and three of these technologies in each GPRMS. Using an in-house model developed in Python the 57 systems are simulated over one year with an hourly time step. The results show a potential for the installation of expansion turbines with a total capacity of 3.57 MWel, leading, combined with the renewable heating technologies, to a reduction of more than 99 % of the original gas consumption for gas preheating. The results are then extrapolated to the whole country using scaling factors, showing a potential for feeding-in between 510 and 1,140 GWh/a of surplus electricity into the grid, on top of the almost complete elimination of the gas consumption for gas preheating. In total, the use of the complete technical potential available would lead to net primary energy savings between 1,710 and 3,650 GWh/a and net CO2-emission reductions between 470 and 1,010 kt/a. Overall, this work demonstrates that the combination of expansion turbines and heat pumps technically allows an almost complete decarbonation of the operation of GPRMS in Germany. In addition, significant amounts of electricity could be fed into the grid, especially during the winter months, which would contribute to decarbonise the electricity mix of the country. The amount of electricity fed into the grid can be increased with the additional use of low-temperature solar thermal systems. To exploit this potential in the future, current regulations should be adapted and targeted support programmes launched.

Life cycle assessment: Driving strategies for promoting electric vehicles in China

This study employed the Life Cycle Assessment (LCA) method to evaluate the greenhouse gas (GHG) emissions of passenger vehicles across 31 provinces in China. It examined the potential of Battery Electric Vehicles (BEVs), Hybrid Electric Vehicles (HEVs), and Plug-in Hybrid Electric Vehicles (PHEVs) in significantly reducing emissions compared to Internal Combustion Engine Vehicles (ICEVs). The findings revealed that HEVs, PHEVs, and BEVs substantially lower emissions under the national average electricity GHG emissions coefficient, with PHEVs being the most effective, reducing emissions by over 30%. However, disparities exist at the provincial level due to varying electricity structures, with BEVs not fully effective in reducing emissions in about ten provinces, including Liaoning. The study further categorized provinces into six groups using the K-means method to guide the promotion of different types of New Energy Vehicles (NEVs). Sensitivity analysis highlights the critical role of reducing electricity emission coefficients and adjusting PHEV's utility factor in achieving emission reductions. The study also notes that battery replacements in PHEVs and BEVs during their lifecycle could impede emission reduction in most provinces. To maximize the environmental benefits of NEVs, there is a need to move to a greener electricity mix. At the same time, strategies for promoting NEVs should vary for different provinces.

A holistic analysis of environmental impacts and improvement pathways for the Brazilian electric sector based on long-term planning and life cycle assessment

Brazil presents a high share of renewable electricity generation, mainly due to its favorable hydroelectric potential. However, reports estimate that demand will grow substantially in the long term, requiring a significant diversification of the electricity mix. In this context, this paper analyzes how the environmental impacts of electricity generation tend to change over the horizon 2025–2050 in Brazil and identifies improvement opportunities accounting for environmental and economic factors. To do so, the Open Source Energy Modeling System (OSeMOSYS) is applied to estimate the composition of the electricity mix in 2050. Then, life cycle assessment (LCA) is used to evaluate the associated environmental impacts across ten categories. Lastly, hybrid weighted ɛ-constraint multi-objective optimization (MOO) is employed to evaluate which sources can be used to minimize climate change and the levelized cost of electricity while ensuring that other categories are reasonably restrained. The results indicate that the environmental performance of the Brazilian electricity matrix tends to deteriorate substantially, both when analyzing overall impacts and impacts per kWh. Moreover, the proposed MOO approach suggests that some sources, mainly hydropower, onshore wind, and centralized PV present an all-around economic/environmental performance and might be favorable for expanding the power system.

A life cycle assessment of protein production from wheatgrass: Optimization potential of a novel vertical farming system

The global protein demand is expected to keep increasing due to a growing global population, combined with changing social demography and other factors. OrbiPlant®, a novel vertical farming technology developed in Germany, is used to cultivate wheatgrass (Triticum aestivum) as one possible solution for realizing a sustainable protein supply to meet this challenge. The objective of this study was to investigate the environmental impacts of wheatgrass protein concentrate powder produced in the novel vertical farming system and compare it with traditional protein sources (cheese and soy protein). To achieve this, a ‘cradle-to-gate’ life cycle assessment (LCA) was performed using OpenLCA software and Environment Footprint 3.1 method. The results show that wheatgrass protein from vertical farming has lower environmental impacts than cheese protein in terms of terrestrial eutrophication, and land use, similar impacts on freshwater ecotoxicity and particulate matter, but higher impacts in other categories. Due to the high environmental impact of the current Germany electricity mix, the overall environmental performance of wheatgrass protein remains non-competitive to traditional protein sources. By optimizing production, the environmental impact can be reduced to just 57.8 % of the cheese protein. This finding highlights the potential of the investigated wheatgrass protein from vertical farming system to reduce environmental impacts when substituting animal-based protein. Furthermore, it emphasizes the importance of utilizing renewable energy sources.

Advancements in Biological Dosimetry Techniques for Surge Response to Radiation Emergencies in Ghana

The awareness of the use of biodosimetry to estimate external radiation doses received by individuals and in radiation oncology, nuclear medicine, diagnostic, and interventional radiology has gained traction in recent years. At present Ghana is poised to integrate about 1GW of nuclear power into its electricity mix by 2034. The increased awareness of biodosimetry is probably due to increased radiological threats and incidents, medical and forensic applications, the quest to strengthen emergency response to unplanned radiation exposures such as radiological accidents, and the malevolent use of radioactive sources. Biodosimetry capabilities would play an effective role during public health management of radiation emergencies for rapid dose estimation and help to medically categorize the exposures for the purpose of prioritizing treatment of the affected persons. Moreover, it will also serve to provide reassurance and psychological support for the “worried-well”. Biodosimetry methods and infrastructure can also be utilized for various applications, including molecular research, medical cytogenetics, and forensics. This write-up assesses the status of biodosimetry methods and infrastructure capabilities available at the Ghana Atomic Energy Commission (GAEC), which could be leveraged during radiological or allied scenarios.

Environmental Life Cycle Assessment of Innovative Ejectors Plant Technology for Sediment by-Pass in Harbours and Ports

Sedimentation is the natural process of sediment transportation and deposition in quiescent water conditions. Sedimentation can affect the functionality of ports, harbours and navigation channels by reducing water depth, making navigation difficult, if not impossible. Different solutions are available to guarantee infrastructure functionality against sedimentation, with maintenance dredging being the most widely adopted. Alternative technologies for dredging have been developed and tested to reduce the environmental concerns related to dredging operations. Among other solutions, applying a sediment by-pass system based on a jet pump emerged as one of the most promising. While the existing literature covers the techno-economic aspects of sediment by-pass systems, the environmental impacts must be better evaluated and assessed. This paper aims to resolve this gap by evaluating, through the ReCiPe2016 life cycle assessment (LCA) methodology, the environmental impact of an innovative sediment by-pass system called an “ejectors plant”. The LCA results are based on the demonstrator established in Cervia Harbour in Italy, which was extensively monitored for 15 months during its operation. This paper shows how energy consumption during the operation phase highly affects the considered midpoint and endpoint categories. For example, the GWP100 of the ejectors plant, considering the Italian electricity mix, equals 1.75 million tons of equivalent CO2 over 20 years, while under a low-carbon scenario, it is reduced to 0.17. In that case, material consumption in the construction phase becomes dominant, thus highlighting the importance of eco-innovation of ejectors plants to minimise oxidant formation. Finally, this paper compares the ejectors plant and traditional dredging through environmental LCA. The ejectors plant had a lower impact in all categories except for GWP-related categories. The sensitivity analysis showed how such a conclusion may be mitigated by considering different electricity mixes and maintenance dredging working cycles.

Does the electric vehicle promotion policy drive Thailand's passenger transport towards environmental sustainability?

Electric vehicles (EVs) are considered an alternative to internal combustion engine vehicles (ICEVs) for promoting sustainable transport, with environmental benefits depending on many local factors. This study performed a comprehensive life cycle assessment of passenger transport in major urban areas of Thailand, encompassing on-road, metro trains, and inland water transport, to determine the benefits of EV deployment. The findings showed that the vehicle life cycle (manufacture, maintenance, and disposal) was a significant contributor to human health and ecosystem quality impacts when comparing across transport life cycle phases in both ICEVs and EVs. Among private vehicles, with the current electricity mix, EVs had impacts on human health and ecosystem quality comparable to small-size ICEVs. At the projected 2037 electricity mix, the EVs will have lower impacts on human health, ecosystem quality and resource scarcity in comparison with the ICEVs. In scenario analysis, when considering only on-site emissions, it was found that private EV promotion had an environmental cost by about 16–43 % lower than the business-as-usual (BAU) scenario, depending on the rate of EV adoption, while shifting to public electric buses or metro trains had a lower environmental cost by 21 % and 23 % compared to BAU, respectively. If assessing the full transport life cycle, shifting to public electric buses or metro trains had a lower environmental cost (22–23 %) than the promotion of EVs with current electricity mix (14 %). The effectiveness of environmental impact mitigation through deployment of private EVs might increase to a comparable level with public electric bus or metro train shifts when Thailand achieves the electricity mix target with 34 % of renewable energy in 2037.

Cradle to gate life-cycle assessment of battery grade nickel sulphate production through high-pressure acid leaching

The rising global demand for high-purity nickel (Ni) sulphate, primarily used in lithium-ion batteries, is largely met by processing Indonesian laterite ores via hydrometallurgy. However, this supply chain is associated with significant environmental challenges and lack of transparent industrial data. This study uses a cradle-to-gate life cycle assessment (LCA) approach to quantify the greenhouse gas (GHG) emissions and energy use associated with the production of mixed hydroxide precipitate (MHP) from low-grade Indonesian laterites via high-pressure acid leaching (HPAL), which is then refined in China for the production of battery-grade nickel sulphate hexahydrate (NiSO4·6H2O, NSH). Fifteen impact categories are analyzed using established impact assessment and allocation (mass and economic) methods. The analysis reveals that feed preparation/HPAL and purification are the stages that contribute most to environmental impacts and in particular to global warming potential (GWP). Mass allocation results in higher environmental impacts, with 36.8 kg CO2-eq per 1 kg of Ni in NSH for GWP, compared to 33.8 kg CO2-eq per 1 kg of Ni in NSH when economic allocation is used. Sensitivity analysis shows a potential reduction (up to 13 %) in key impact categories if production of NSH is fully integrated in Indonesia or a greener electricity mix is used. Overall, our results indicate that the production of MHP in Indonesia and its refinement to NSH in China has a GWP about two times higher than the global average. Given the limited number of LCA studies for the production of battery-grade nickel, this study highlights major environmental concerns for the NSH production process from Indonesian laterites and identifies opportunities for improvement, towards a more sustainable global battery supply chain.

French economy and clean energy transition: A macroeconomic multi-objective extended input-output analysis

The complexity of a sustainable economy is rooted in its socio-economic and environmental intricacies, particularly in formulating pathways for the harmonious integration of these parameters. This study introduces an extended input-output analysis and a multi-objective optimisation framework designed to discern trajectories for reducing CO2 emissions while simultaneously maximising GDP and employment. The economic alterations are evaluated through metrics facilitating the examination of both direct and indirect consequences stemming from perturbations within the economy. The focus of this research centres on the French economy, concentrating on pivotal sectors where reducing demand could yield the greatest reduction in CO2 emissions with minimal socio-economic ramifications. Additionally, a model is outlined for energy substitution, wherein fossil fuels in the French electricity mix are supplanted with clean energies. The ensuing effects of such a model on emission reduction pathways are scrutinised, followed by a comparison with the baseline case study.

Optimal design of building envelope towards life cycle performance: Impact of considering dynamic grid emission factors

Building-related carbon emissions in the construction and operation stages account for more than one-third of global energy-related emissions. Optimizing during the early design stage is an effective way to reduce building carbon emissions. However, current studies adopt a constant grid emission factor (GEF) to assess the environmental impacts of buildings while ignoring the dynamic changes of the future electricity mix. This will overestimate the operational carbon emissions of the building in the context of the increasing share of renewable energy in power generation. In this study, a dynamic life cycle assessment model based on dynamic GEF is constructed to evaluate the life cycle environmental impacts of buildings. On this basis, a building optimization design framework considering dynamic GEF is proposed, and the impact of considering future variations of GEF on the optimal design of the building envelope is explored. The study is conducted in three steps. First, dynamically changing GEFs are predicted under the future electricity mix based on scenario analysis. Second, a multi-objective optimization framework is established to minimize the life cycle carbon emissions (LCCE) of the building while optimizing its life cycle costs (LCC) and indoor discomfort hours (IDH). Finally, the proposed optimization framework is applied to a prototype office building in Shanghai, and a comparative analysis is conducted for the optimal schemes between a static and two dynamic scenarios. The result reveals that ignoring future variations will lead to overestimating the operational carbon emissions by 49.0%-64.8%, which in turn will result in an over-insulated design of the envelope (i.e., additional material consumption). In addition, compared to the static scenario, consideration of dynamic GEF results in a 38.7%-51.6% reduction in LCCE, a 5.2%-6.1% reduction in LCC, and a 5.3%-9.5% increase in IDH for the optimal solutions. This research illustrates the importance of considering dynamic GEF in identifying the optimal design parameters and can help decision-makers reasonably choose the optimal schemes during early-stage design.

Life Cycle Assessment of CO2-Based and Conventional Methanol Production Pathways in Thailand

Methanol production through carbon capture and utilization technologies offers promising alternatives to traditional natural-gas-based methods, potentially mitigating climate change impacts and improving resource efficiency. This study evaluates four methanol production pathways: CO2 hydrogenation, tri-reforming of methane, electrochemical CO2 reduction, and co-electrolysis of CO2 and water. The analysis covers 19 scenarios, combining three electricity mixes (100% Thai grid mix, 50% Thai grid mix and 50% renewable energy, and 100% renewable energy) with two hydrogen production technologies (alkaline water electrolysis and grey hydrogen). Environmental life cycle assessment results showed that most pathways perform well when using the 100% renewable energy with co-electrolysis (CE-100%) showing the most substantial reductions across all impact categories as compared conventional methanol production. Electrochemical reduction demonstrated the poorest environmental performance for all scenarios. In Thailand, implementing the CE-100% pathway could potentially yield 12.4 million tonnes of methanol annually from the cement industry’s CO2 emissions, with an estimated value of approximately USD 5.4 billion, while reducing emissions from the industrial processes and product use (IPPU) sector by 75%. The findings provide valuable insights for policymakers, industry stakeholders, and researchers, supporting Thailand’s transition towards sustainable methanol production and broader climate goals.

Comparative Life Cycle Assessment of alternative winter salad value chains supplying the United Kingdom

Lettuce is an established food commodity in the UK increasingly facing supply challenges in winter due to adverse weather events and rising energy costs. We investigate whether an agroecologically grown salad mix of lettuce and underutilised leafy greens produced in the Azores, Portugal, could be part of a sustainable solution. We performed a Life Cycle Assessment to compare the environmental impacts of this salad mix with four other value chains for winter salad supply to the UK: conventional open-field lettuce production chains in Spain using (1) current irrigation practices; (2) 100 % desalinated irrigation water; or hydroponic controlled environment agriculture within the UK powered by (3) the national electricity mix; (4) 100 % wind-generated electricity. Results indicated that the leafy-greens agroecological value chain incurred the smallest environmental burdens across 7 to 11 of 16 impact categories studied. Substituting Spanish winter salad supply with agroecological leafy green production in the Azores, if well managed, could reduce many environmental burdens whilst diversifying leafy greens intake. Nevertheless, all winter value chains were associated with larger environmental burdens than conventional open-field production of lettuce in the UK summer, pointing to the importance of seasonal consumption and wider adoption of agroecological techniques to effectively reduce environmental impact.