Marcello De Falco

Carbon capture could support deep decarbonisation only if the energy required for separation, regeneration, compression and refrigeration is supplied with low lifecycle emissions. This review approaches low-carbon and renewable energy integration into carbon-capture processes from the point of view of the technologies, integration problems and energy vectors encountered when entering the capture boundary: renewable heat (RH-CC), renewable electricity (RE-CC) and renewable or recovered cryogenic energy (CR-CC). For RH-CC, indirect solar heat (ISH) is the most retrofit-compatible route, whereas thermal or solvent storage improves flexibility, and direct solar solvent regeneration (DSSR) offers greater process intensification but remains largely model-based. For RE-CC, direct electric heating is the simplest option but retains the intrinsic regeneration duty. High-temperature heat pumps (HTHPs) and mechanical vapour recompression (MVR) show the strongest near-term potential through heat recovery and upgrading, whereas electrochemically and mechanically assisted pathways must be scaled up and require complete energy balances. CR-CC can combine renewable-powered refrigeration, recovered cold energy and liquid–air energy storage (LAES) in high-efficiency multi-purpose solutions, although multi-product boundaries complicate comparison. Across all pathways, promising solutions of low-carbon energy penetration and high separation performance have been identified and classified; although full development depends on resource quality, temporal matching, host–process integration and electricity carbon intensity in site-specific solutions.

This study evaluates the economic feasibility of flexible, renewable ammonia production in Italy through a comprehensive sensitivity analysis of the levelized cost of ammonia (LCOA). Ammonia is produced through Haber–Bosch synthesis from green hydrogen and nitrogen coming from alkaline electrolysis and cryogenic air separation, respectively. The analysis examines the impact of key parameters such as renewable source peak power, Haber–Bosch reactor flexibility, energy mix, electrochemical and hydrogen storage, on the final production cost. The location considered for the PV and wind power output is Southern Italy. The results show that a wind-driven system with minimal battery storage and a flexibility factor (ratio between the minimum operating capacity and the nominal capacity of the plant) of 20% offers the most cost-effective solution, but production is scaled down to 64 tpd. With the 2030 cost structure, battery storage offers better integration with wind systems and flexible operation, even at low levels of turndown. For different combinations of process design choices and flexibility, the optimal LCOA for a green ammonia production is approximately 0.59 USD/kgNH₃ in 2050. This cost of production could be competitive with grey ammonia, provided that a carbon emission allowance of USD 0.12/kgCO₂ is applied.

Wastewater treatment plants (WWTPs) currently represent one of the main sources for microplastics (MPs) and other emerging contaminants entering the environment. Coagulation is a longstanding and cost‐effective process designed to enhance the removal of colloidal particles and proved to be efficient in the abatement of MPs. The present study investigates the feasibility of a progressive replacement of ferric chloride (FeCl ₃ ) with chitosan (CT) and sodium alginate (SA), starting from their use as coagulant aids. Coagulations tests were carried out to assess the performance of FeCl ₃ ‐CT and FeCl ₃ ‐SA systems in the removal of polystyrene (PS) microbeads, polyethylene (PE) and polyethylene terephthalate (PET) fragments with sizes lower than 500 μm. Results from experiments have shown that both CT and SA are useful to enhance the removal performance of conventional coagulation by improving the settling characteristics of flocs. The use of CT allows a reduction of coagulant dosage for removing PS and PE particles, while it turned out to be detrimental for the removal of PET fragments. Instead, SA at a concentration of 0.2 mg L ⁻¹ proved to be useful both to achieve higher removal rate at a medium dosage of coagulant and to improve the efficiency of the process at lower dosages.

In the past two decades, advancements in thermochemical technologies have improved biomass gasification for distributed power generation, enhancing efficiency, scalability, and emission control. This study aims to optimize syngas production from biomass gasification by comparing two computational models: a quasi-equilibrium thermodynamic model implemented in Aspen Plus and an artificial neural network (ANN) model. Operating at 850 °C with varying steam-to-biomass (S/B) ratios, both models were validated against experimental data. Results show that hydrogen concentration in syngas increased from 19.96% to 43.28% as the S/B ratio rose from 0.25 to 0.5, while carbon monoxide concentration decreased from 24.6% to 19.1%, consistent with the water–gas shift reaction. The ANN model provided rapid predictions, showing a mean absolute error of 3% for hydrogen and 2% for carbon monoxide compared to experimental data, though it lacks thermodynamic constraints. Conversely, the Aspen Plus model ensures mass and energy balance compliance, achieving a cold gas efficiency of 95% at an S/B ratio of 0.5. A Multivariate Statistical Analysis (MVA) further clarified correlations between input and output variables, validating model reliability. This combined modelling approach reduces experimental costs, enhances gasification process control and offers practical insights for improving syngas yield and composition.

Biomass gasification has obtained great interest over the last few decades as an effective and trustable technology to produce energy and fuels with net-zero carbon emissions. Moreover, using biomass waste as feedstock enables the recycling of organic wastes and contributing to circular economy goals, thus reducing the environmental impacts of waste management. Even though many studies have already been carried out, this kind of process must still be investigated and optimized, with the final aim of developing industrial plants for different applications, from hydrogen production to net-negative emission strategies. Modeling and development of process simulations became an important tool to investigate the chemical and physical behavior of plants, allowing raw optimization of the process and defining heat and material balances of plants, as well as defining optimal geometrical parameters with cost- and time-effective approaches. The present review paper focuses on the main literature models developed until now to describe the biomass gasification process, and in particular on kinetic models, thermodynamic models, and computational fluid dynamic models. The aim of this study is to point out the strengths and the weakness of those models, comparing them and indicating in which situation it is better to use one approach instead of another. Moreover, theoretical shortcut models and software simulations not explicitly addressed by prior reviews are taken into account. For researchers and designers, this review provides a detailed methodology characterization as a guide to develop innovative studies or projects.

Biomass gasification acquired great interest over the past decades as an effective and trustable technology to produce energy and fuels with net-zero carbon emissions. Moreover, using biomass waste as feedstock enables to recycle organic wastes and to fit the circular economy goals thus reducing the environmental impacts of waste management. Even if many studies have been already carried on, this kind of process must still be investigated and optimized with the final aim to develop industrial plants for different applications, from the hydrogen production to net-negative emission strategies. Modeling and developing of process simulations became an important tool to investigate the chemical and physical behavior of the plant, allowing to make a first raw optimization of the process and to define heat and material balances of the plant as well as to define optimal geometrical parameters with cost and time effective approaches. The present review paper focuses on the main literature models developed until now to describe biomass gasification process, and in particular on kinetic models, thermodynamic models, and computational fluid dynamic models. The aim of this study is to point out the strengths and the weakness of those models, comparing them and indicating in which situation is better to use an approach instead of another. Moreover, theoretical shortcut models and software simulations, not explicitly addressed by prior reviews, are taken into account. For researchers and designers this review provides a detailed methodology characterization as a guide to develop innovative study or project.

Global warming, along with increasing global energy demands, has led to the need for a sustainable and low-carbon-based energy economy. In addition to renewable energy technologies, such as biomass, solar, hydro, and wind, another possible strategy to mitigate climate change is the capture/conversion and recycling of CO₂. In recent years, many methods for both CO₂ capture (mainly adsorption, absorption, and membrane) and conversion (many electrolysis, catalyst, and plasma) have been investigated. Conversion technology is less studied but seems to be very promising. Within that, non-thermal plasma technology has received much interest because it works at low temperatures and atmospheric pressure, and there is no need for high temperature and high electricity consumption, which are typical of the catalyst and electrolysis conversion processes, respectively. Therefore, in order to optimize this emerging technology, simulative kinetic models have been developed with the aim of maximizing both energy efficiency and CO₂ conversion. In the present paper, an overview of the most common non-thermal plasma technologies was carried out to highlight the advantages and disadvantages of each method. Then, an overview of the most significant kinetic models available in literature was carried out to point out the main reactions occurring during CO₂ conversion and also the parameters that most affect the performance of a plasma reactor during CO₂ conversion. Then, a brief recap of the literature available on economic studies of the plasma process is given.

Carbon Capture Utilization and Storage (CCUS) is a set of technologies aimed at capturing carbon dioxide (CO₂) emissions from point-source emitters to either store permanently or use as a feedstock to produce chemicals and fuels. In this paper, the potential benefits of CCUS integration into the energy supply sector are evaluated from a Life Cycle Assessment (LCA) perspective by comparing two different routes for the CO₂ captured from a natural gas combined cycle (NGCC). Both the complete storage of the captured CO₂ and its partial utilization to produce dimethyl ether are investigated. Moreover, the assessment is performed considering the region-specific features of two of the largest CO₂ emitters in Europe, namely Italy and Poland. Results shows that the complete storage of the captured CO₂ reduces Global Warming Potential (GWP) by ~89% in Italy and ~97%, in Poland. On the other hand, the partial utilization of CO₂ to produce dimethyl ether leads to a decrease of ~58% in Italy and ~68% in Poland with respect to a comparable reference entailing conventional dimethyl ether production. A series of environmental trade-offs was determined, with all the investigated categories apart from GWP showing an increase, mainly connected with the higher energy requirements of CCUS processes. These outcomes highlight the need for a holistic-oriented approach in the design of novel implemented configurations to avoid burden shifts throughout the value chain.