Hydrogen has been increasingly recognized as a promising clean energy carrier to support global climate change mitigation efforts. Among various production routes, the utilization of municipal solid waste (MSW), particularly plastic and food waste, offers a dual benefit: reducing the environmental burden of high-volume waste streams and producing a low-carbon energy carrier. Despite growing interest in waste-to-hydrogen technologies, few studies have explored an integrated pathway that simultaneously utilizes both plastic and food waste while incorporating carbon mitigation strategies. This study proposes and assesses, for the first time, a novel MSW-to-hydrogen and combined cooling, heating and power (CCHP) pathway fitted with carbon capture and storage (CCS). Two CCS configurations were examined: a pre-combustion CCS scheme (Scenario 1) and a post-combustion CCS scheme (Scenario 2). Three process cases were designed and evaluated using techno-economic analysis (TEA) and life cycle assessment (LCA) under conditions representative of Indonesia. In Case 1, plastic and food waste are separately processed via plasma gasification and anaerobic digestion, with syngas and biogas subsequently reformed into hydrogen. Case 2 co-processes the waste streams through plasma gasification. Case 3 builds on Case 1 by adding steam methane reforming (SMR) of biogas prior to mixing. For a feedstock of 13.97 kg/s of food waste and 5.0 kg/s of plastic waste, the systems deliver 0.27-0.70 kg/s of hydrogen across all cases and scenarios, with energy and exergy efficiencies of 19-42% and 13-34%, respectively. The levelized cost of hydrogen (LCOH) is estimated at 3.52-13.37 USD/kg, while LCA reveals global warming potentials (GWP) ranging from - 0.159 to 0.048 kgCO2-eq/kg of waste treated. These results demonstrate the technical feasibility and environmental promise of integrating plasma gasification, anaerobic digestion, and CCS for hydrogen production. By valorizing municipal waste while achieving carbon mitigation, this novel multi-integration of plasma gasification, anaerobic digestion, PSA, CCS, CCGT, and ARC represents a compelling and scalable solution for sustainable hydrogen deployment in developing economies.

Previous studies demonstrated the feasibility of vertical axis wind turbine (VAWT)-driven reverse osmosis (RO) units integrated with compressed air energy storage (CAES) to manage renewable energy intermittency. However, an integrated multi-objective strategy for optimal configuration was missing. This study addresses this gap by developing and applying a novel integrated framework coupling multi-objective optimisation with life cycle assessment (LCA) to evaluate technical, economic, and environmental performance. The system was modelled using six design variables, exploring 118,800 configurations to balance annual water production, levelised cost of water (LCOW), and global warming potential (GWP). Machine learning techniques were used to develop surrogate models to identify Pareto-optimal solutions, while a TOPSIS analysis selected four scenarios representing diverse stakeholder priorities. Results revealed that the sizing and number of VAWTs are the dominant factors influencing both LCOW and GWP. The optimisation yielded an LCOW-prioritised scenario that achieved a cost of 1.39 US$/m³, while the GWP-prioritised scenario reached a footprint of 0.70 kg CO₂eq/m³. This work provides a novel methodology for the simultaneous techno-economic and environmental design of off-grid water infrastructure, establishing optimal strategies for renewable desalination to address global water scarcity.

Previous studies demonstrated the feasibility of vertical axis wind turbine (VAWT)-driven reverse osmosis (RO) units integrated with compressed air energy storage (CAES) to manage renewable energy intermittency. However, an integrated multi-objective strategy for optimal configuration was missing. This study addresses this gap by developing and applying a novel integrated framework coupling multi-objective optimisation with life cycle assessment (LCA) to evaluate technical, economic, and environmental performance. The system was modelled using six design variables, exploring 118,800 configurations to balance annual water production, levelised cost of water (LCOW), and global warming potential (GWP). Machine learning techniques were used to develop surrogate models to identify Pareto-optimal solutions, while a TOPSIS analysis selected four scenarios representing diverse stakeholder priorities. Results revealed that the sizing and number of VAWTs are the dominant factors influencing both LCOW and GWP. The optimisation yielded an LCOW-prioritised scenario that achieved a cost of 1.39 US$/m3, while the GWP-prioritised scenario reached a footprint of 0.70 kg CO2eq/m3. This work provides a novel methodology for the simultaneous techno-economic and environmental design of off-grid water infrastructure, establishing optimal strategies for renewable desalination to address global water scarcity.

Biomass will need to play a major role in the transition towards carbon neutrality in the energy sector. The conversion of biomass into syngas through gasification enables its usage in various applications including combined heat and power generation, production of sustainable hydrocarbon fuels and hydrogen generation. The compromise between producing syngas with both a high calorific value and low tar content remains challenging across various gasifier reactors. The rising co-current gasifier presents a novel reactor design that combines the advantages of the fixed and fluidized bed reactors in terms of the biomass conversion efficiency and quality of syngas produced. However, limited research has been conducted on this design, and its capabilities and limitations have not been characterised fully. This study presents an investigation of the performance of a rising cocurrent gasifier with two different feedstocks (wood and miscanthus pellets) over a range of operating conditions. The gasifier achieved an optimum balance between achieving a high magnitude of lower heating value (LHV) and a minimum tar content under different operating conditions. The LHV of syngas varied between 5.0 and 5.5 MJ/Nm3 for both materials, with the wood pellets achieving slightly higher values than the miscanthus. The equivalence ratio (ER) is estimated at 0.283-0.287 for wood pellets and at 0.319-0.339 for miscanthus. The gasifier achieved high cold gas efficiency (CGE) and carbon conversion efficiency (CCE), attaining maximum values of 83.1% and 98.0%, respectively. The H2 content in the syngas had a mean value of approximately 18%, with the H2/CO ratio in the range of 0.8-0.9. A minimum tar content of 14.7 mg/Nm3 of syngas was attained from the wood pellets at an air flow rate of 75 kg/h (ER = 0.285), while the maximum tar content of 163.5 mg/ Nm3, was observed from the gasification of miscanthus pellets at a flow rate of 55 kg/h (ER = 0.319). It is worth highlighting that the gasification of miscanthus pellets imposed the additional challenge of bed agglomeration and the formation of channels in the bed, however fluidization at higher air flow rates can, at least in part, mitigate this problem.

An amine-based CO2 capture plant could mitigate CO2 emissions from a combined-cycle gas turbine (CCGT) plant, but it would require substantial energy. This investigation tackles this issue by assessing the merits of absorber intercooling (AIC) for a CO2 capture plant under the exhaust gas recirculation (50%EGR) and selective exhaust gas recirculation (70%SEGR) flue gas conditions for a CCGT plant, which, to the best of the authors' knowledge, has not been addressed in previous studies. The findings revealed that the greatest benefits of AIC were observed when the bulge temperature peaked at the center of the absorber under the critical lean loading. At the critical lean loading (mol CO2/mol MEA) of 0.35, 0.34, and 0.28 for baseline, EGR, and SEGR, respectively, installing three intercoolers in the absorber can reduce the bulge temperature by approximately 5-9 degrees C. This results in a 22-29% reduction in specific reboiler duty (SRD) across all configurations. In comparison, at the optimal lean loading of 0.20 across all configurations, the advantages of three intercoolers were limited to approximately 1-2 degrees C reductions in bulge temperature and around 7-9% reductions in SRD.

The properties of aviation fuel controlled by specifications, along with fit-for-purpose properties, are essential for ensuring the safety and technical suitability of the entire aircraft system. The complex relationships between these properties and their connection to the chemical composition of aviation fuel can significantly influence system design, emissions, performance, and safety. As an example, fuel density and permittivity are critical for quantification of onboard fuel mass in the aircraft. Variations in hydrocarbon classes and their proportions in synthetic aviation fuels, compared to conventional fuels, could affect fuel gauging systems, which rely on the permittivity-density relationship established for conventional fuels. To address these challenges, a comprehensive dataset of properties for individual chemical fuel constituents, representative of synthetic aviation fuels and categorised by main hydrocarbon classes, is highly desirable. In this study, we combined molecular dynamics (MD) simulations with experimental measurements to construct a detailed dataset of density and permittivity properties for selected hydrocarbon constituents, including normal paraffins, isoparaffins, and cycloparaffins, at a temperature of T = 293.15 K. The simulation results showed good agreement with experimental measurements. Expanding on this validated model, we extended the dataset to include the aforementioned hydrocarbon classes over a wide range of carbon atoms. This generated dataset offers significant potential for constructing structure-property relationships for property prediction, aligning with the scope of aviation fuel pre-screening.

This paper presents findings of demonstration of CO2 capture by rotating packed bed absorber using real biomass flue gases. There are two main objectives of the study presented here: (1) performance assessment of pilot scale rotating packed bed CO2 capture absorber with real biomass flue gases (2) the impact of impurities in biomass flue gases on the solvent. The demonstration was carried out at the waste to energy and CO2 capture facilities at the Energy Innovation Centre of the University of Sheffield. Rotating packed bed (RPB) absorber was used to capture CO2 from biomass flue gas generated by a grate boiler. CO2 loadings and solvent concentrations were measured using Mettler Toledo auto-titrator. Particulates content of the flue gas was measured, and particulates were collected for further analysis at the boiler exit and absorber inlet by Electrical Low Pressure Impactor (ELPI (R)+) manufactured by Dekati (R). The particulate samples were analysed by ICP-OES to investigate the impact of metals in the flue gas coming from the biomass on the solvent degradation. Solvent samples were collected and analysed with ICP-MS and Ion Chromatography to quantify build-up of metals and anions in the solvent over time. There is very limited information on this subject in open literature. The short-term tests presented here can serve as a starting point for further longer-term investigations into the impact of biomass flue gas contaminants on the solvent behaviour and the solvent management requirements during CO2 capture from biomass flue gases.

This paper aims to evaluate whether cofiring hydrogen and natural gas mixtures are suitable as industrial furnace fuels and to identify further characteristics that need more detailed understanding to enable successful implementation of fuel switching. The outcome of this research and further investigations will ensure that the full capability of fuel switching becomes available to energy-intensive process operators. Co-firing natural gas and hydrogen leading to dedicated hydrogen combustion are pathways to decarbonise industrial processes and can enable future hydrogen utilisation and interoperability with fossil fuels. The key observations from pilot-scale industrial furnace trials at the University of Sheffield Energy Innovation Centre included: (1) Radiant heat flux depended primarily upon furnace temperature with no relationship measured with varying fuel composition. (2) The chamber geometry, radiant heat flux from solid surfaces and control temperature achieved were more significant to the furnace heat exchange than the fuel mixture. (3) Firing with natural gas and hydrogen mixtures did not affect furnace temperature or uniformity beyond variations attributable to other process conditions. (4) Gas temperatures and species were distributed uniformly within the fully mixed atmosphere, which represented 2/3 of the chamber volume. (5) Gas temperature and species distributions were not affected by fuel composition, therefore measurements from the centre of the chamber were representative of the mean conditions in the fully mixed atmosphere. (6) CFD modelling of the gas and temperature distributions within the furnace enabled thermodynamic and fluid dynamic characteristics to be understood and afforded confidence in experimental and model outcomes. Co-firing hydrogen with natural gas and dedicated hydrogen firing as an interoperable fuel to substitute for natural gas could be a key means to decarbonise hard to abate foundation industries, whilst making continued use of existing capital assets. This investigation demonstrated that understanding hydrogen firing and co-firing will enable the mitigation of perceived risks arising from decarbonisation of energy-intensive industries with low and zero carbon fuels.

The global transition toward renewable energy has been accelerating in response to climate change. South Korea has increasingly expanded the adoption of renewable energy, especially solar power. Smart farms are one example of renewable energy applications but require both electricity and heat demand. Previous studies have shown that the target smart farm does not achieve 100% energy self-sufficiency rate under current conditions. Therefore, renewable energy-based autonomous energy systems and their operational strategy are required to reduce grid dependency with full energy autonomy. This study proposes a scenario-based energy autonomy framework that integrates life-cycle assessment and techno-economic analysis for smart farms with coupled electricity and heat demands using measured operational data. Analysis results indicated that the proposed energy autonomous scenario could reduce CO2 emissions by up to approximately 92% compared to a centralized grid-based system. It also improved economic viability, lowering the LCOE from $0.435 to $0.287/kWh compared with the existing operating model. Sensitivity analysis identified electricity and wood pellet prices as the most influential economic factors. Consequently, a 60% solar-40% biomass configuration provides the optimal balance between environmental performance and economic efficiency. These findings demonstrate the practical feasibility of applying renewable and low-carbon technologies to smart farms within agricultural systems.

Residential buildings are among the largest energy consumers worldwide. While energy efficiency standards are critical for reducing consumption, approximately 110 countries currently lack mandatory building energy codes. Furthermore, traditional static assessment methods such as degree-day, often miscalculate actual energy demand, leading to significant uncertainties in system sizing. This study proposes a new, structured and holistic framework, based on a transient TRNSYS model, to evaluate the dynamic energy profiles of a typical residential building in temperate climates. The methodology includes the calculation of high-resolution demand profiles for space heating (SH), space cooling (SC), domestic hot water (DHW), and electrical energy (EE). Dynamic simulation results indicate that SH constitutes the largest share of energy demand (5721 kWh), followed by EE (2265 kWh), DHW (1497 kWh), and SC (594 kWh). These findings highlight the dominant role of heating along with the persistent baseload from electrical appliances. The results also provide valuable insights into energy policy and the design of demand-side management strategies. Consequently, this holistic approach offers a useful reference for architects and engineers when determining appropriate system sizing and integrating renewable energy technologies.

Ash-related issues such as slagging and ash deposition in the heat transfer region of the grate boiler have been considered serious problems for safe and efficient operation. These issues must be addressed to avoid any unplanned shutdown due to failure in controlling the agglomeration and slagging during combustion. Various methods have been proposed, such as the injection of chemical additives into the grate boiler to reduce the alkali species in the bottom ash and depositions in the heat transfer region during combustion. However, the impacts of the boiler condition especially the bed conditions of the grate boiler have not been understood well in the past when adding the kaolin. Therefore, the aim of this work is to investigate, both experimentally and theoretically, the effects of blending biomass fuels with kaolin on ash-related issues in a 250 kW field-scale grate boiler. It was found that the kaolin powder performed quite effectively as an absorbent for potassium under firing conditions. The deposition propensity of fly ash was found to reduce by at least 50 % after the addition of the kaolin to the fuel mixtures. However, an increase in the degree of agglomeration was observed in the combustion chamber of the grate boiler when the kaolin was added to the fuel mixtures. High sintering was observed for the virgin wood and the recycled wood fuel blended with the kaolin at any dosages in the grate boiler. According to the elemental analysis by ICP-MS, the most dominant element found in the bottom ash, slag, and coarse fly ash was silica which captured potassium-related species and promoted the formation of slags. This also can be confirmed by the X-ray diffraction (XRD) analysis which shows that a high concentration of silica in crystalline structures were observed in both fuel mixtures. Moreover, according to the XRD analysis and thermodynamic equilibrium model prediction, adding kaolin to the feedstocks significantly influences the crystalline structure formation in the bottom ash such as the formation of Kalsilite, Leucite, Sanidine and many more.

A novel layout of a biogas-based poly-generation system is proposed, designed and techno-economically analysed to satisfy the energy requirements for cooking and other household uses, including lighting, as well as for drying and cooling agricultural produce in rural areas. The integrated system comprises anaerobic digester (AD), internal combustion engine (ICE), absorption chiller, in-bin dryer and CO2 capture unit. The ICEs operate with a high level of flexibility by adjusting their power output according to the power demand variability. The energy demand is modelled based on appliances’ power ratings and usage time windows using an advanced stochastic estimation technique. Under the simulated conditions of a rural unelectrified community in Northern Nigeria, the system can meet approximately 94.6% of the combined cooking and domestic energy requirements. The remaining unmet load is primarily attributed to peak demand periods associated with electric cooking. A supplementary gas burner is integrated to stabilize fluctuations in the ICE energy supply, ensuring a consistent energy supply for both the absorption cooling and the grain drying processes via dedicated heat exchangers. The proposed system provides sufficient thermal energy to achieve a cooling capacity of 160 kW at 7 °C using the absorption chiller whereas the in-bin dryer can dry approximately 1,900 kg/h of maize, decreasing their moisture content from 25% to 13%. Excess biogas stored in the tank is upgraded by removing CO2 via amine scrubbing and liquefied through Linde-Hampsons cycle to produce liquefied biomethane (LBM), to be used for transporting feedstocks to the AD plant over a 90 km distance. The levelized cost of electricity (LCOE) for the proposed system is estimated at $0.055/kWh, with an associated payback period of 8 years.

Decarbonisation of critical hard-to-abate industrial sectors such as the iron and steel industry is crucial for meeting climate targets, with chemical absorption carbon capture identified as a key transitional technology. However, its application is hindered by a significant knowledge gap: the absence of publicly available and transparent performance benchmarks using conventional capture systems under elevated CO2 conditions that are representative of industrial process emissions. An experimental performance campaign was conducted on the chemical absorption pilot plant at the Energy Innovation Centre (EIC) in Sheffield, UK. The study established a novel performance baseline across a wide operating envelope for flue gas concentrations ranging from 10 to 25 mol.% CO2, achieving 90% capture efficiency using a 35 wt.% monoethanolamine (MEA) solvent. In addition, a methodology was developed to quantify solvent regeneration energy and its constituent components, complementing a system energy balance for each capture condition. The results provided experimentally validated insight into the relationship between operating conditions, capture performance, and energy demand at elevated CO2 concentrations. The dataset established a robust baseline for conventional packed-bed systems and improved understanding of regeneration energy contributions under industrially relevant conditions. These findings are scalable for application to the design, operation and optimisation of chemical absorption systems in heavy industries and provide a reliable benchmark for future work on advanced solvents, process intensification and scale-up to commercial deployment.

The aerodynamic behavior of vertical-axis wind turbines (VAWTs), particularly the H-type Darrieus configuration, remains central to renewable energy research due to persistent challenges in self-starting and efficiency at low tip speed ratios (TSRs). This study presents a numerical investigation of a modified NACA0018 aerofoil with chordwise surface openings, termed a J-shaped aerofoil, operating under Darrieus motion. Two-dimensional CFD simulations in ANSYS Fluent evaluated opening ratios of 30%, 60%, and 90% of chord length, focusing on lift, drag, and chordwise force coefficients during dynamic stall. A validated oscillating aerofoil model with user-defined pitching replicated Darrieus kinematics, with systematic variation of TSR and pitch angle. Results show that larger openings enhance lift and delay stall onset in the positive angle of attack phase, improving self-starting potential. However, these gains are offset by increased drag and reduced performance during the negative phase, particularly downstream. The J-shaped aerofoil with 90% opening achieved similar to 30% higher peak lift than the conventional profile, with improved flow reattachment and vortex dynamics observed. Despite elevated downstream losses, the enhanced upstream torque indicates a net advantage for turbine start-up capability. These findings provide insight for optimizing blade design in low-Reynolds-number VAWTs, balancing self-starting improvement against efficiency at higher TSRs.

While the rotating packed bed (RPB) shows good potential for CO2 absorption, it is still not used in large commercial scales largely due to the uncertainty about its real advantages over conventional packed column beds (CPB). In this paper, a large pilot-scale RPB model with an outer packing diameter of 1.2 m has been designed and effectively simulated using the Eulerian porous medium approach for the first time. Various sub-models have been extensively utilized to investigate the CO2 capture processes, including the hydrodynamics, thermodynamics, and mass transfer, within the RPB, comparing it critically with an equivalent CPB. The RPB, which has a much smaller size and footprint, could save 30 % in the liquid flow rate compared to the CPB to achieve the same capture rate using a 50 % MEA solution, coupled with an 80 % reduction in the packed bed volume. The results also show that at higher rotational speeds, increasing the liquid flow sometimes may not consistently improve the capture performance.

The primary challenge in integrating post-combustion CO2 capture (PCC) with natural gas combined cycle (NGCC) is the significant energy consumption and capital costs. The novelty of this paper lies in proposing for the first time an advanced novel configuration that combines lean vapor compression (LVC) for the PCC plant with the NGCC plant incorporating exhaust gas recirculation (EGR) and selective exhaust gas recirculation (SEGR). The simulation results illustrated that implementing 33 % EGR can increase the CO2 level in exhaust gas from a baseline of 4.2 to 6.3 mol%. In comparison, 53 % SEGR increased the CO2 concentration in the flue gas to 8.8 mol %. Among the different configurations examined, SEGR + LVC achieved the highest energy saving for reboiler duty, which was 14 % compared to the baseline. In contrast, the EGR + LVC recorded the highest enhancement in thermal efficiency by 0.7 % points compared to the reference case. The LVC alone resulted in approximately 0.4 % points improvement in thermal efficiency for all configurations evaluated when the gas turbine loads were reduced from 100 to 60 %. This indicates that LVC is effective under partial loads. Finally, SEGR + LVC results in the greatest cost reduction for the PCC plant equipment, lowering the cost by 26 % compared to the baseline. However, the SEGR has the highest total plant cost and total overnight cost due to additional costs for the CO2 membrane separation system.

Accurately modelling the self-starting of vertical-axis wind turbines (VAWTs) requires careful selection and tests of various computational model parameters which is a tedious task. This study applies the Taguchi Design of Experiments (TDE) to evaluate the influence of key numerical parameters such as freestream turbulence intensity, blade boundary layer mesh, time step size, average computational cell size, inner iterations within each time step, etc. The Taguchi study indicated that the time step size and mesh refinement within the rotating domain, particularly in the blade's boundary layer regions, were the most critical factors in the prediction of the self-starting process. Based on the Taguchi analysis, followed by a more detailed sensitivity analysis of these most critical factors on the accuracy of the CFD simulations, a robust CFD approach was successfully developed in order to correctly simulate the dynamic passive self-starting process of a VAWT. The simulation results of the robust model were found to compare well with the experimental measurements. The influence of the computational model settings on the predicted aerodynamics that are critical to the self-starting of the turbine were discussed. Finally, some practical guidelines were provided for building a robust CFD model for self-starting simulations of the VAWT applications.

The growing global population is leading to a surge in waste generation, with plastic waste posing a major pollution challenge due to its resistance to decomposition. Simultaneously, the energy sector is one of the largest contributors to air pollution, which highlights the urgent need for cleaner fuels to mitigate emissions. Innovative solutions, such as converting non-recyclable plastic waste into valuable energy carriers like hydrogen, are crucial to address both issues. This research aims to evaluate the thermodynamic and economic performance of hydrogen production from plastic waste via plasma gasification integrated with a carbon capture and storage plant. To the best of our knowledge, such information is currently unavailable in the literature, and this study represents the first attempt to bridge this gap. The system is modelled using ASPEN Plus software, with mass and energy balances from the simulation used to evaluate performance. Results show that processing 5 kg/s of plastic waste produces 1.20 kg/s of hydrogen, achieving overall energy and exergy efficiencies of 57.40% and 54.12%, respectively. The levelized cost of hydrogen ( LCOH) for economic viability is estimated at 3.3 USD/kgH(2). Monte Carlo simulations indicate a 95% confidence interval for the LCOH, which spans from 2.98 to 4.25 USD/kgH(2).

Waste generation and energy demand are increasing and both require innovative energy symbiosis strategies to meet climate targets. Traditional waste-to-energy processes rely on incineration, but more efficient and sustainable solutions are needed. The aim of the study is to investigate for the first time the feasibility of generating cooling, heating, power (CCHP), and liquid biomethane from plastics and food waste integrated with carbon capture and storage (CCS). The system, modelled in Aspen Plus, consists of a plasma gasifier (PG), anaerobic digester (AD), combined cycle gas turbine (CCGT), absorption refrigeration cooler (ARC), and biomethane liquefier. Two scenarios were analyzed: (1) a standalone CCHP system and (2) its integration with liquid biomethane production. Each scenario includes a baseline (without CCS), pre-combustion CCS, and post-combustion CCS, both with a 95% CO₂ capture fraction. Utilising 5 kg/s of plastic and 13.97 kg/s of food waste, the system generates net power (29.76–85.67 MW), cooling (2.72–4.04 MW), heating (13.99–27.87 MW), and 43.26 MW of liquid biomethane. The highest energy and exergy efficiencies achieved are 49.44% and 41.20%, with carbon emissions ranging from 0.008 to 0.247 kgCO₂/kg waste. The findings of this novel study highlight the potential of integrating several energy systems for an effective waste management strategy that can contribute to the provision of several energy vectors while the inclusion of CCS ensures that significant emission reduction can be attained.

Achieving climate goals demands novel system designs that enable the conversion of municipal waste, such as plastic and food waste into energy and fuels with minimal environmental impact. This study proposes an innovative multi-energy generation system that integrates plasma gasification for plastic waste and anaerobic digestion for food waste, coupled with carbon capture and storage (CCS) technologies. This novel conceptual design aims to maximize energy recovery while reducing lifecycle emissions compared to conventional waste-to-energy (WtE) pathways. Two novel system configurations were assessed: (1) a combined cooling, heating, and power (CCHP) system, and (2) a CCHP system integrated with liquid biomethane production. Each configuration was evaluated under three CCS strategies: no CCS, pre-combustion CCS, and post-combustion CCS. The economic analysis and life cycle assessment (LCA) highlight the economic and environmental trade-offs of each design. Specifically, in Scenario 1, the levelized cost of electricity (LCOE) increases from 0.171 USD/kWh (no CCS) to 0.311 and 0.354 USD/kWh while in Scenario 2, the levelized cost of biomethane (LCObM) rises from 0.176 USD/kWh to 0.314 and 0.374 USD/kWh for pre- and post-combustion CCS, respectively. While CCS raises production costs, they also represent a tangible commitment to reducing emissions and underscore that transitioning to cleaner energy systems often entails higher near-term expenditures. Across both scenarios, the levelized cost of waste treatment (LCOWT) spans 0.081–0.236 USD/kg of waste. Global warming potential (GWP) ranges from −0.191 to 0.662 kgCO2-eq/kg of feedstock for Scenario 1, and 0.123 to 0.746 kgCO2-eq/kg for Scenario 2. This work provides the first integrated assessment of such a hybrid WtE system, offering new insights for sustainable waste valorisation. The proposed novel designs support future detailed engineering studies and inform policymaking for low-carbon waste management.