Conference Agenda

This study presents a comprehensive approach to optimizing a sustainable aviation fuels (SAF) supply chain network (SAFSCN) with an initial focus on the Chechia Republic. Utilizing a Mixed-Integer Linear Programming (MILP) framework, the research decomposes into two distinct modelling scenarios: decentralized and centralized Hydrodeoxygenation (HDO) plants. In the second scenario, the centralized case, the final upgrading of the pyrolysis oil occurs at the HDO plants located within existing refineries in the examined country.

In the present study, the feedstock selected is wheat straw for the production of SAF to replace Jet A-1, which is included in the Renewable Energy Directive (REDII Annex IX) and is characterized as a bio-based feedstock and low-cost waste material.

The objective function aims to minimize total costs constrained by the mass balance, seasonality, feedstock storage, demand satisfaction, solar panel area, pyrolysis plant capacity, and final HDO plant costs (for the centralized case). Total costs encompass feedstock, transportation, storage, operation, and capital expenditure costs for pyrolysis plants, offset by biochar revenue.

Both scenarios account for revenue from biochar (a by-product) production and the satisfaction of Jet A-1 supply/demand for three time periods, today, in 2030, and 2050, considering both potential outcomes: a mixture (up to 50%) or a drop-in fuel.

Finally, the two scenarios are compared by assessing their respective advantages and disadvantages to determine the most economically feasible (sensitivity analysis) and efficient option for an EU country to start to decouple from oil production and imports. This approach facilitates informed decision-making in the evolution of sustainable aviation fuels produced from agricultural residues, providing a strategic roadmap for policy reforms and supply chain development. This ensures alignment with existing legislation across EU countries, aiding in achieving EU legislative targets.

Hydrothermal liquefaction (HTL) has proven to be a practical approach for converting sewage sludge into a valuable resource for renewable energy generation. This study focuses on a prospective analysis of various scenarios for sewage sludge-to-fuel pathway design configurations via HTL, co-located with a wastewater treatment plant, in support of a circular economy. The circular economy emphasizes evaluating the environmental performance and economic feasibility of emerging technologies, which has gained significant attention recently. Integrated assessment models (IAMs), such as the REMIND model combined with shared socio-economic pathways (SSPs), are used to develop globally consistent future scenarios. This approach supports the development of three prospective scenarios aligned with the Paris Agreement’s climate targets: REMIND-SSP2-Base (projecting a 3.5°C temperature rise by the end of the century), PKBudg1150 (aiming to limit the rise to below 2°C), and PKBudg500 (targeting a cap below 1.5°C) for 2030, 2040, and 2050. The core part of this study is the use of prospective assessment for a process that serves circular economy targets to identify the most suitable production pathway by considering the economic balance between operating costs, the future market value of products, and the externality costs associated with GHG emissions.

The P-graph model is used as an effective decision support tool. To Identify optimal and near-optimal solutions for addressing trade-offs between future socio-economic policies and practical implementation for 2030, 2040, and 2050, which are often difficult to monetize. This study includes four foreground scenarios for sewage sludge-to-fuel conversion. Scenario 1 uses natural gas in both the HTL unit for biocrude production and the biocrude upgrading unit, with hydrogen produced via steam reforming. Scenario 2 utilizes onsite-produced biomethane for both biocrude production and the upgrading system. Scenario 3 involves using natural gas for the HTL unit while producing hydrogen through electrolysis. Scenario 4 employs biomethane for the HTL process and uses electrolysis for the biocrude upgrading system. The objective of this study is to maximize profit by accounting for credits from avoided GHG emissions, the market value of recovered products, while subtracting operational costs and GHG emission penalties incurred during the biocrude production and upgrading processes. The P-graph model is employed to solve the superstructure problem using branch and bound approach while also provide a graphical representation, which is a key strength of the method (p-graph studio). This visual approach makes the model more accessible for stakeholders without a mathematical optimization background. The potential profit is 810 euro per ton of sewage sludge for Pkbudg500 under scenario 4 by 2040 and near optimal solution 696 and 676 euro per ton of sewage sludge for Pkbudg1150 and Pkbudg500 under scenario 4 by 2050 respectively. The P-graph approach shows that HTL treatment of sewage sludge provides an alternative production pathway within the circular economy concepts.

A country's energy consumption is linked to its economic growth. Despite efforts to reduce greenhouse gas emissions by integrating green technologies to meet energy needs, energy consumption remains largely reliant on fossil fuels. On a global scale, oil and gas production is projected to increase by 27% and 25% by 2030 (McKinsey & Company, 2022). Nonetheless, current geopolitical conflicts highlight the urgent need to reduce dependency on fossil fuels. As the global energy transition accelerates, and the push to fund clean energy projects intensifies, biogas and hydrogen emerge as strong energy vectors due to the extensive research into their production technologies, versatility, and non-intermittency. Hydrogen production is currently dominated by steam methane reforming (SMR) using natural gas. Since SMR is a well-established technology, using methane obtained from biogas offers an attractive alternative for hydrogen production. Furthermore, using biomass for methane and hydrogen production fosters a circular economy by reincorporating waste into the value chain.

However, several challenges exist due to the direct competition between using methane and other byproducts from biogas versus hydrogen production. Most research on the supply chain of these two products either caters to biogas demand¹, hydrogen demand, or power-to-gas concepts². This study aims to identify the synergies and trade-offs between hydrogen and biogas production within a shared biomass supply chain, regarding economic and environmental performance. Two hydrogen sectors in Mexico are identified: the steel industry and the heavy-duty transport sector, while biogas is intended to replace natural gas in domestic applications. The supply chain model considers biomass obtention, biogas production and upgrading. Hydrogen is produced from the resulting biomethane using SMR, considering its storage through the liquefaction and regasification stages until the refuelling stations, as the final node for the supply chain.

The mathematical model for the supply chain consists of steady-state mass balances, formulated as a mixed-integer linear program, in GAMS (General Algebraic Modeling Language) environment, through a deterministic approach. A single-objective optimization approach, focusing on maximizing profit using fixed and variable costs along each node of the supply chain was performed. The optimization is approached as an allocation problem, with production divided between the methane and the hydrogen demand markets. Hydrogen allocation was gradually increased from 10% to 90% of hydrogen production, obtaining a production yield of 2,072 tons per year, and a levelized cost of hydrogen of 14 € per kg, a value expected to drop with higher production yields, while the levelized cost of biogas returned a value of 0.98€ per kg. Preliminary results highlight the importance of integrating environmental objectives to evaluate the trade-offs between these energy vectors and promote the decarbonization of key economic sectors. Therefore, life cycle assessment will be employed to pinpoint the impacts of each of the products along the supply chain.

[1] Díaz-Trujillo L, Nápoles-Rivera, F. (2019). Optimization of biogas supply chain in Mexico considering economic and environmental aspects. Renewable energy, 139, 1227-1240.

[2] Carrera, E., Azzaro-Pantel, C. (2021). Bi-objective optimal design of Hydrogen and Methane Supply Chains based on Power-to-Gas systems. Chemical Engineering Science, 246, 116861.

Sugarcane bioenergy is a reality in Brazil, comprising the production of bioethanol (partially displacing fossil gasoline consumption) and bioelectricity (partially displacing fossil electricity generation). As sugarcane bioethanol can reduce around 68% of greenhouse gas (GHG) emissions of displaced gasoline, there is an opportunity to almost double this reduction taking into account that around 80% of Brazilian light vehicles fleet are able to run with any blend of ethanol or gasoline (the so-called flex-fuel cars). On the other hand, there are concerns about the possible implications caused by the expansion of sugarcane production on indirect land use change, especially when this expansion takes place on pasture land for livestock activity. A promising strategy to enlarge sugarcane bioenergy in Brazil without compromising the pasture industry is to integrate both activities, converting extensive livestock into an intensive one. In 2020, the Brazilian government joined the UNFCCC (United Nations Framework Convention on Climate Change) Race to Zero call announcing the commitment to reduce its GHG emissions in 2050 by zero. The objective of this study is to compare and evaluate socioeconomic (such as activities output level, Gross Domestic Product - GDP, and employment) and environmental (such as Greenhouse Gases - GHG emissions) impacts in two scenarios, both of them including the effects of indirect land use change. The first scenario, referred to Business as Usual (BAU), consists of sugarcane bioenergy and extensive livestock production without integration. The second scenario, Integrated Sugarcane-Bioenergy and Livestock (ISBL) in Brazilian agriculture, considers the same amount of sugarcane bioenergy and livestock production obtained in BAU scenario, but given the integration between activities projected land use is half of the BAU scenario. To achieve this goal, a computable general equilibrium (CGE) model was implemented, in which (i) for the BAU scenario an optimized pasture activity and sugarcane bioenergy industry were introduced separately as single sectors and (ii) for the ISBL scenario an optimized integrated sugarcane bioenergy and livestock sector was considered. For both scenarios in the model, based on the results obtained from an optimization model (in economic and environmental terms) the respective direct technical coefficients were estimated taking into consideration a choice of intermediate consumption and use of primary factors of production that maximize their profitability and minimize the GHG emissions. The Brazilian input-output matrix (main data for the model) was estimated for 2021, admitted as the first recovered economic year after the Covid-19 crisis in 2020. Model’s results show that the ISBL scenario is economically more efficient, as fewer jobs and higher output level activity were obtained. Even considering that the integration of sugarcane bioenergy and livestock production took place just in these activities, the positive socioeconomic impacts were noticed in all sectors of the economy.

To improve the sustainability of the transport sector, there is a global tendency to promote more environmentally friendly modes of transportation, in alignment with the Sustainable Development Goals (SDGs), particularly SDG 13, which focuses on climate action. This shift is essential given that the transport sector is one of the largest contributors to greenhouse gas emissions globally, and transitioning to cleaner transportation options is a critical step toward mitigating climate change. Electric vehicles (EVs) have emerged as a promising solution due to their potential to reduce emissions significantly when powered by renewable energy sources. In response to these developments, many countries are implementing policies and incentives to encourage the adoption of EVs, including subsidies for EV purchases, investments in charging infrastructure, and stringent emission standards for conventional vehicles. This trend has led to a surge in EV adoption, which may reduce the reliance on traditional fuel stations in the future. However, the existing network of fuel stations, strategically located and familiar to consumers, offers a unique opportunity to support the EV transition. Retrofitting these fuel stations into EV charging stations not only leverages their advantageous locations and existing infrastructure but also facilitates a smoother transition for consumers who are accustomed to using these sites for refuelling (Ghosh et al., 2022).

In this work, we propose an optimization model based on the set-covering problem to determine which fuel stations are best suited for retrofitting and to evaluate the impact of this conversion on economic and environmental objectives compared to a baseline scenario with no retrofitting. The set-covering approach ensures that the retrofitted stations can adequately serve EVs within a specified radius, addressing the limited range issue of current electric vehicles.

The proposed methodology is applied to a case study in Spain, utilizing a comprehensive dataset of all existing fuel stations. Given the NP-hard nature of the set-covering problem, an initial filtering step is employed to reduce the problem’s complexity. Subsequent optimization is performed under various assumptions, such as the source of electricity and local population density, using bi-objective optimization techniques. The model aims to minimize economic costs and CO₂ equivalent emissions, employing a life-cycle assessment (LCA) framework (Azapagic, 1999).

The results indicate that retrofitting a relatively small fraction (approximately 10%) of the fuel stations can satisfy the set-covering constraints, ensuring sufficient coverage for EV users. This optimal solution for the supply chain includes factors such as electricity sourcing and demand of travel distances for EVs. Although the economic costs increase, the environmental benefits are significant, demonstrating that strategic retrofitting of gas stations can play a crucial role in achieving sustainability goals while supporting the growth of electric mobility.

References

Azapagic, A., 1999. Life cycle assessment and its application to process selection, design and optimisation. Chemical Engineering Journal 73, 1–21. https://doi.org/10.1016/S1385-8947(99)00042-X

Ghosh, N., Mothilal Bhagavathy, S., Thakur, J., 2022. Accelerating electric vehicle adoption: techno-economic assessment to modify existing fuel stations with fast charging infrastructure. Clean Techn Environ Policy 24, 3033–3046. https://doi.org/10.1007/s10098-022-02406-x