Given the persistent energy crisis and the increasing demand for green electricity, the significance of producing green hydrogen is continually rising. The state-of-the-art process for generating green hydrogen is electrolysis which requires large amounts of pre-treated freshwater as the feedstock. This poses challenges for global drinking water supply and demands significant amounts of energy for treatment.

In contrast, the SeaEly project aims to use seawater directly as the feedstock for the electrolysis. This approach leverages the abundance of seawater worldwide and has potential to save substantial amounts of energy that would otherwise be used for water pre-treatment. To achieve the project’s goals, special membranes are being developed to withstand the high salinity of seawater.

A byproduct of this electrolysis process is seawater brine. Current disposal strategies for similar seawater brines, such as those from desalination plants, often involve returning them to the sea, despite the known negative effects on the marine ecosystems.

As part of the SeaEly project, this work provides an in-depth analysis of sustainable and environmentally friendly applications for seawater brine, instead of returning it to the sea. It also includes economic feasibility estimations for mineral extraction and commercialization. Therefore, this approach emphasizes social and environmental responsibility within the supply chain.

In this study separation strategies for the fractionated extraction of various minerals are being developed, considering the abundance of different elements in the Weser River near Bremerhaven. The considered separation strategies include ion exchange, adsorption, liquid-liquid extraction, precipitation/crystallization, and membrane processes.

The economic feasibility of the separation is estimated considering market demands and raw material prices, extraction yields and occurring investment and operating costs. This study concludes that the extracting of chlorine (Cl), sodium (Na), magnesium (Mg), and calcium (Ca) from the resulting brine holds significant economic potential. Over a three-year period, the extraction of Cl, Na, Rb, Mg, and Ca from the brine can yield substantial net revenues ranging from 2 × 10³ , to 80 × 10³ based on the volume of untreated seawater, depending on the method employed and local market conditions.

A SWOT analysis reveals the project's unique strengths, including the production of green hydrogen from an abundant resource and the scalable extraction of raw materials. However, challenges such as complex extraction processes and limited technological adaptability pose internal weaknesses. External opportunities include supplying a variety of raw materials through environmentally favorable byproduct utilization within a circular economy and therefore counteracting existing supply chain risks. Yet, the project faces threats, such as the complex and variable composition of seawater at different locations and uncertainties regarding large-scale implementation necessitate careful consideration of the project's viability.

Many countries around the globe have taken a variety of strategic policies aiming at meeting energy needs more sustainably. Hydrogen energy demand has grown remarkably to support commercial, transport, and residential applications. In this study, we assess the upstream process of the Hydrogen Supply Network (HSC) based on the green hydrogen concept, in which electricity from a renewable energy source such as solar renewable energy is used in the electrolysis technique to break down water into hydrogen and oxygen. Initially, multiple criteria based on geographic, climate, and sun-earth interaction data are collected inclusive of locational area, population density, precipitation level, days with rainfall, air temperature, humidity percentage, wind force, sunshine hours, solar irradiation, and photovoltaic power. Then, these conflicting criteria are modeled using one of the well-known Multiple-Criteria Decision Analysis (MCDA) called the Data Envelopment Analysis (DEA) technique to evaluate the relative efficiency of each investigated regional location for a potential solar energy plant. The DEA technique, in particular, is a linear programming and production theory-based nonparametric approach generally used for efficiency analysis and optimization. The technique thus allows for the measurement of the relative efficiency of alternatives called Decision Making Units (DMUs) simultaneously to capture the interaction between multiple input and output criteria.

Next, given several efficient DMUs, the super-efficiency DEA technique (SDEA) is further used as a basis for ranking efficient DMUs under consideration. The SDEA score, in particular, can be used to measure the proportional increase in the inputs for a DMU that could take place without destroying the ‘efficient’ status of that DMU relative to the efficiency of the remaining DMUs. Thus, the SDEA score can further provide a measure of stability for obtained results. The case study of the state of Saxony-Anhalt in Germany inclusive of eleven districts and three independent cities is further used as DMUs to explore the district/city’s relative efficiency. Our initial DEA analysis suggests that about 57% of all DMUs (i.e., eight DMUs) perform relatively efficient, which are found to be Börde district (BK), Burgenland district (BLK), Harz district (HZ), Mansfeld-Südharz District (MSH), Saalekreis (SK), Salzlandkreis (SLK), City of Halle (Saale) (HAL), and State capital Magdeburg (MD) with all reported 1.00 efficient scores. This result suggests benchmarking locations for solar energy plants in the green HSC. Additionally, the SDEA technique is further used, which enables efficient DMUs to be ranked. That is, the efficiency score in SDEA allows the efficiency score for efficient units to be higher than 100% and thus the efficiency score from the SDEA technique can be taken as a basis for a complete ranking of efficient units. Accordingly, our analysis suggests that the top three efficient locations for solar energy plants in the green HSC based on the SDEA technique are HAL followed by HZ and MD, respectively. We note that this study is the first phase of our ongoing research framework to model and analyze HSC to integrate the upstream, midstream, and downstream operations.

In the discussion of the reduction of greenhouse gas emissions, the use of hydrogen as an energy carrier in the road transportation sector, particularly in freight transportation, is regarded as one option to reduce mobility-based emissions. In this context, the efficient supply of hydrogen refuelling stations is crucial element in the total hydrogen supply chain. Various options for supplying hydrogen refuelling stations from a source, in terms of transportation and storage technologies, already exist, and with advances in research new options continue to emerge. These options, also referred to as pathways, are associated with different costs and also emission characteristics, which strongly depend on the considered scenario. In this paper, a methodology is proposed that allows for flexible modelling and evaluation of hydrogen delivery pathways. The methodology is based on the concept of activity analysis. Delivery pathways are modelled as sequences of activities with all associated material flows and emissions. This allows for both economic and environmental assessment of different hydrogen delivery pathways. The applicability of this approach is demonstrated within a case study for two different use cases. First, we show how different delivery pathways for a specific sourcing option can be evaluated. Second we apply the proposed method for the integrated assessment of different sourcing options, locally procured grey hydrogen and imported green hydrogen. Enabling an economic and environmental evaluation, the methodology allows for the identification of efficient solutions.