Urban areas are home to most of the world’s population, consume the most energy and are subject to environmental regulations, policies, and, in some cases, legislation to reduce energy consumption and emissions. This means obtaining more energy from renewable sources, improving energy efficiency, and maximizing the use of current energy networks. Energy modeling is often the first tool used to systematically evaluate pathways to a sustainable future. It is important to note that these studies make many assumptions about future conditions that will influence the energy landscape. Furthermore, the scenario-based approach often makes assumptions about the current situation and conditions due to lack of access to data, lack of key data, and lack of interoperability between systems and models. A scenario creates assumptions or a set of assumptions about different components of the space-time system to define a modeled system. Therefore, making comparisons between different models is a complicated task because of the difficulty of ensuring the representation of the same system (input parameters and variables). This article presents a digital framework based on a scenario ontology, called Scenario Management Ontology. The model aims to improve the analysis based on energy models that use the scenario approach by addressing the major challenge of formalizing and governing assumptions in a transparent and formal manner. This approach implements a formal, standardized and transparent characterization of: (1) an energy system, (2) well-defined scenarios, and (3) traceability of the data used for different use cases. The objective of this work is to integrate data and analytical models (energy system modeling and planning tools) to analyze energy strategies for energy planning and analysis. In addition, the framework allows for the management of uncertainty arising from assumptions about the system and data, resulting in a documented, consistent, traceable, and formal approach. This framework is based on the use of energy system domain models. In particular, it makes use of the Common Energy System Modeling Domain (CESDM), which is an ontology for modeling energy systems’ knowledge. In addition, the digital framework aims to integrate different spatial-temporal scales and granularity to homogenize the characterization and references of the modeled system. Finally, the implementation of semantic technologies enables the standardization and linking between different domains, promoting interoperability between system models and analytical tools in the energy field.
Frederiek-Maarten Kerckhof, Norah Benmeridja, Korneel Rabaey, Nico Boon, Jo De Vrieze, Myrsini Sakarika
Microbial protein (MP) is a promising alternative protein source that can be produced using methane as a substrate derived from undervalued resources. Methylococcus capsulatus is one of the most prominent microbial species employed for industrial production, while other potentially suitable methanotrophs remain underexplored. Here, we selected the alternative methanotrophs Methylosinus sp. and Methylomonas methanica with high growth rates and potential for halotolerance and compared them to M. capsulatus. Methylosinus sp. and Methylomonas methanica achieved up to 1.87-fold higher maximum specific growth rates and 2.52-fold higher biomass concentrations, compared to M. capsulatus. When the pH was allowed to acidify below optimum for growth, the protein content of M. methanica (45% ± 5% CDW) was 1.55 times compared to pH-controlled conditions. Cultivation at an increased salt content (20 g NaCl L −1) boosted the protein content of M. methanica to 81% ± 7% CDW, showing its applicability for MP production using saline water. Co-culturing M. methanica with the methylotrophic yeast Komagataella phaffii led to a 1.27-fold higher essential amino acid content, which indicates an improvement in protein quality, while the use of synthetic biogas increased the protein yields up to 1.5-fold, compared to purified methane. In summary, M. methanica co-cultured with selected methylotrophs has the potential to enable more sustainable MP production under saline conditions using biogas, as an alternative to natural gas-based production with M. capsulatus. These strategic upstream choices could bring us closer to a future-proof protein production system.
The decarbonization of energy-intensive industries, particularly in petrochemical refineries, is critical to achieving global net-zero targets. The objective of this study was to develop a structured methodological framework for refinery decarbonization planning under confined industrial data availability. This approach integrates Scope 1 greenhouse gas inventory, emission hotspot identification, technology assessment, and scenario-based transition analysis. A Tier 1 methodology based on the Intergovernmental Panel on Climate Change (IPCC) 2006 Guidelines was applied to quantify direct CO 2 emitted from major process units of a representative Petrochemical Refinery Y in Vietnam. The results identified the residue fluid catalytic cracking (RFCC) (25.95%), electricity and steam generation systems (24.20%), and hydrogen production (20.93%) as the major emission sources, contributing to a total Scope 1 emission of roughly four million tons of CO 2 per year. Based on the quantified emission profile and evaluation of applicable measures, a four-phase strategy toward carbon neutrality by 2050 was constructed to guide the staged deployment of energy efficiency improvements; electrification; renewable integration; carbon capture, utilization, and storage (CCUS); and green hydrogen (GH 2) systems. Scenario analysis indicates that cumulative emission reductions ranging from 80% (conservative) to 90% (optimistic) may be achievable under defined techno-economic assumptions regarding technology deployment and infrastructure development. This work contributes by potentially providing a scalable framework for refinery decarbonization in emerging economies, bridging the gap between emission assessment and transition strategies, while supporting national climate commitments.
Lucas Rodrigues Loyola, Guilherme Barbieri Piski, Francisco Mello Fonseca, Rodrigo Guedes dos Santos, Pedro Rosseto de Faria, José Joaquim Conceição Soares Santos, José Manuel Baranda Moreira da Silva Ribeiro, Márcio Santos
The expansion of biomass, biogas, and waste-to-energy (WtE) technologies is one of the strategies established by the Government of the State of Espírito Santo (Brazil) to increase renewable electricity generation and support decarbonization. In this context, landfill biogas power plants represent an important opportunity for repowering through waste heat recovery (WHR). However, under tropical operating conditions, internal combustion engines commonly operate under derating due to high ambient temperature and humidity while simultaneously rejecting significant amounts of thermal energy through exhaust gases and cooling water. This scenario motivated an R&D Project to investigate integrated WHR alternatives using Organic Rankine Cycle (ORC) and absorption chiller technologies based on a combined energy, exergy, and economic (3E) assessment. Mass, energy, and exergy balances were performed to determine the thermodynamic limits of WHR, using EES software. Two ORC configurations and an absorption cooling system for intake-air and biogas conditioning were simulated using IPSEpro 8.0 software. Using EES software, economic feasibility was evaluated through equipment sizing, parametric cost estimation, and investment indicators, including net present value (NPV), internal rate of return (IRR), and payback period. The results demonstrated that the exhaust-gas-driven ORC is economically feasible, generating an additional 423 kW of electricity, corresponding to approximately 14% of plant repowering. In contrast, the cooling-water-driven ORC was not economically attractive. However, utilizing the same low-grade heat in an absorption chiller for intake-air and biogas conditioning provided an equivalent gain of 452 kW of electricity, which represents approximately 15% of additional repowering. The integrated viable solution requires a total investment of US$ 2.48 million, achieves a discounted payback period of 3.57 years, and increases the overall plant repowering capacity by approximately 29%. These findings demonstrate that matching waste heat sources with recovery technologies according to their thermodynamic quality provides an effective strategy for improving the efficiency and more sustainability of landfill biogas power plants.
Monoclonal antibodies (mAbs) represent one of the largest and fastest-growing classes of biotherapeutics. However, what remains underappreciated is the N-linked glycan on the Fc, a heterogeneous post-translational modification that affects stability, safety, and efficacy. Despite this, glycosylation is still treated as a late-stage critical quality attribute (CQA), characterized and constrained only after a cell line and process are already locked in. I argue that glycosylation should instead be treated as a design variable that enables therapeutic differentiation, a concept framed throughout this perspective as a “mAb glyco-better.” This perspective examines two disciplines central to that shift: Cell line glyco-engineering, which has enabled the directed enrichment of desired glycoform output, and process analytical technology (PAT), which enables near-real-time monitoring of glycosylation. What has not been achieved is their integration. Cell line engineering enables an enriched glycan profile, but a control strategy based on PAT monitoring enables its robust production. Integrating these two technologies will enable next-generation mAbs with enhanced therapeutic functionality by incorporating glycosylation as an intrinsic design parameter.
