Search Results (571)

The global atmospheric concentration of carbon dioxide (CO₂) has exceeded 420 ppm. Adsorption-based carbon capture technologies, offer energy-efficient, sustainable solutions. Relying on classical adsorption models like Langmuir to predict CO₂ uptake presents limitations due to the need for case-specific parameter fitting. To address this, the present study introduces a universal machine learning (ML) framework using multiple algorithms—Generalized Linear Model (GLM), Feed-forward Multilayer Perceptron (DL), Decision Tree (DT), Random Forest (RF), Support Vector Machine (SVM), and Gradient Boosted Trees (GBT)—to reliably predict CO₂ adsorption capacities across diverse zeolite structures and conditions. By compiling over 5700 experimentally measured adsorption data points from 71 independent studies, this approach systematically incorporates critical factors including pore size, Si/Al ratio, cation type, temperature, and pressure. Rigorous Cross-Validation confirmed superior performance of the GBT model (R² = 0.936, RMSE = 0.806 mmol/g), outperforming other ML models and providing comparable performance with classical Langmuir model predictions without separate parameter calibration. Feature importance analysis identified pressure, Si/Al ratio, and cation type as dominant influences on adsorption performance. Overall, this ML-driven methodology demonstrates substantial promise for accelerating material discovery, optimization, and practical deployment of zeolite-based CO₂ capture technologies. Full article

This paper presents a numerical simulation study evaluating carbon dioxide capture and storage (CCS) feasibility for the Turceni Power Plant in Oltenia, Romania, using the nearby depleted Bibești-Bulbuceni gas reservoir. A comprehensive reservoir model was developed using Petrel software, integrating geological and reservoir engineering data for the formations of the Bibești-Bulbuceni structure, which is part of the western Moesian Platform. The static model incorporated realistic petrophysical inputs for the Meotian reservoirs. Dynamic simulations were performed using Eclipse compositional simulator with Peng–Robinson equation of state for a CH4-CO₂ system. The model was initialized with natural gas initially in place at 149 bar reservoir pressure, then produced through depletion to 20.85 bar final pressure, achieving 80% recovery factor. CO₂ injection simulations modeled a phased 19-well injection program over 25 years, with individual well constraints of 100 bar bottom-hole pressure and 200,000 Sm³/day injection rates. Results demonstrate successful injection of a 60 Mt CO₂, with final reservoir pressure reaching 101 bar. The modeling framework validates the technical feasibility of transforming Turceni’s power generation into a net-zero process through CCS implementation. Key limitations include simplified geochemical interactions and relying on historical data with associated uncertainties. This study provides quantitative evidence for CCS viability in depleted hydrocarbon reservoirs, supporting industrial decarbonization strategies. The strategy not only aligns with the EU’s climate-neutral policy but also enhances local energy security by repurposing existing geological resources. The findings highlight the potential of CCS to bridge the gap between current energy systems and a sustainable, climate-neutral future. Full article

In the energy sector and in other types of industries (cement, iron/steel, chemical and petrochemical), highly roasted coffee ground residue can be used as a source material for producing bioadsorbents suitable for CO₂ capture. In this study, a bioadsorbent was produced in a two-step process involving biowaste carbonization and biocarbon activation within a KOH solution. The physicochemical properties of the bioadsorbent were assessed using LECO, TG, SEM, BET and FT-IR methods. Investigating the CO₂, O₂ and N₂ equilibrium adsorption capacity using an IGA analyzer allowed us to calculate CO₂ selectivity factors. We assessed the influence of exhaust gas carbon dioxide concentration (16%, 30%, 81.5% and 100% vol.) and adsorption step temperature (25 °C, 50 °C and 75 °C) on the CO₂ adsorption capacity of the bioadsorbent. We also investigated its stability and regenerability in multi-step adsorption–desorption using a TG-Vacuum system, simulating the VSA process and applying different pressures in the regeneration step (30, 60 and 100 mbar_abs). The tests conducted assessed the possibility of using a produced bioadsorbent for capturing CO₂ using the VSA technique. Full article

Ferrocene (Fc) is a redox-active organometallic scaffold whose unique electronic properties, stability, and modularity have enabled a broad range of catalytic and sensing applications. This review critically examines recent advances in Fc-based systems for hydrogen evolution and carbon dioxide (CO₂) conversion, encompassing electrochemical, photochemical, and thermochemical strategies. Fc serves diverse functions: it operates as a reversible redox mediator, an electron reservoir, a ligand framework, and a structural modulator. Each role contributes differently to enhancing catalytic performance, improving selectivity, or increasing operational stability. We highlight how Fc integration facilitates proton-coupled electron transfer in hydrogen evolution, supports selective CO₂ reduction in molecular and hybrid catalysts, and promotes efficient CO₂ fixation and capture within functionalised frameworks. Emerging applications in electrosynthetic organic transformations are also discussed. Together, these findings position Fc as a foundational motif for designing future electrocatalytic and carbon management platforms. Full article

Understanding the adsorption mechanism is essential for developing efficient technologies to capture carbon dioxide from industrial flue gases. In this work, laboratory measurements, density functional theory calculations, and molecular dynamics simulations were employed to study CO₂ adsorption and diffusion behavior in LTA-type zeolites. The CO₂ adsorption isotherms measured in zeolite 5A are best described by the Toth model. Thermodynamic analysis indicates that the adsorption process is spontaneous and exothermic, with an enthalpy change of −44.04 kJ/mol, an entropy change of −115.23 J/(mol·K), and Gibbs free energy values ranging from −9.68 to −1.03 kJ/mol over the temperature range of 298–373 K. The isosteric heat of CO₂ adsorption decreases from 40.35 to 21.75 kJ/mol with increasing coverage, reflecting heterogeneous interactions at Ca²⁺ and Na⁺ sites. The adsorption kinetics follow a pseudo-first-order model, with an activation energy of 2.24 kJ/mol, confirming a physisorption mechanism. The intraparticle diffusion model indicates that internal diffusion is the rate-limiting step, supported by a significant reduction in the diffusion rate. The DFT calculations demonstrated that CO₂ exhibited a −35 kJ/mol more negative adsorption energy in zeolite 5A than in zeolite ITQ-29, attributable to strong interactions with Ca²⁺/Na⁺ cations in 5A that were absent in the pure silica ITQ-29 framework. The molecular dynamics simulations based on molecular force fields indicate that CO₂ diffuses more rapidly in ITQ-29, with a diffusion coefficient measuring 2.54 × 10⁻⁹ m²/s at 298 K, whereas it was 1.02 × 10⁻⁹ m²/s in zeolite 5A under identical conditions. The activation energy for molecular diffusion reaches 5.54 kJ/mol in zeolite 5A, exceeding the 4.12 kJ/mol value in ITQ-29 by 33%, which accounts for the slower diffusion kinetics in zeolite 5A. There is good agreement between experimental measurements and molecular simulation results for zeolite 5A across the studied temperature and pressure ranges. This confirms the accuracy and reliability of the selected simulation parameters and allows for the study of zeolite ITQ under similar simulation conditions. This research provides insights into CO₂ adsorption energetics and diffusion within LTA-type zeolite frameworks, supporting the rational design of high-performance adsorbents for industrial gas separation. Full article

The accurate prediction of carbon dioxide (CO₂) adsorption in metal–organic frameworks (MOFs) is critical for accelerating the discovery of high-performance materials for post-combustion carbon capture. Experimental screening of MOFs is often costly and time-consuming, creating a strong incentive to develop reliable data-driven models. Despite extensive research, most studies rely on standalone models or generic ensemble strategies that fall short in handling the complex, nonlinear relationships inherent in adsorption data. In this study, a novel ensemble learning framework is developed by integrating five distinct regression algorithms: Random Forest, XGBoost, LightGBM, Support Vector Regression, and Multi-Layer Perceptron. These algorithms are combined into four custom ensemble strategies: equal-weighted voting, performance-weighted voting, stacking, and manual blending. A dataset comprising 1212 experimentally validated MOF entries with input descriptors including BET surface area, pore volume, pressure, temperature, and metal center is used to train and evaluate the models. The stacking ensemble yields the highest performance, with an R² of 0.9833, an RMSE of 1.0016, and an MAE of 0.6630 on the test set. Model reliability is further confirmed through residual diagnostics, prediction intervals, and permutation importance, revealing pressure and temperature to be the most influential features. Ablation analysis highlights the complementary role of all base models, particularly Random Forest and LightGBM, in boosting ensemble performance. This study demonstrates that custom ensemble learning strategies not only improve predictive accuracy but also enhance model interpretability, offering a scalable and cost-effective tool for guiding experimental MOF design. Full article

Excessive carbon dioxide (CO₂) emissions represent a critical challenge in mitigating global warming, necessitating advanced separation technologies for efficient carbon capture. Silica-based membranes have attracted significant attention due to their exceptional chemical, thermal, and mechanical stability under harsh operating conditions. In this study, we introduce a novel layered hybrid membrane designed based on amine-functionalized silica precursors, where a distinct affinity gradient is engineered by incorporating two types of amine-functionalized materials. The top layer was composed of high-affinity amine species to maximize CO₂ sorption, while a sublayer with milder affinity facilitated smooth CO₂ diffusion, thereby establishing a continuous solubility gradient across the membrane. A dual approach, combining comprehensive experimental testing and rigorous theoretical modeling, was employed to elucidate the underlying CO₂ transport mechanisms. Our results reveal that the hierarchical structure significantly enhances the intrinsic driving force for CO₂ permeation, leading to superior separation performance compared to conventional homogeneous facilitated transport membranes. This study not only provides critical insights into the design principles of affinity gradient membranes but also demonstrates their potential for scalable, high-performance CO₂ separation in industrial applications. Full article

This study explores innovative strategies for decarbonizing sludge thermal treatments used in electrical power generation, with a focus on integrating sensor technologies and artificial intelligence. Sludge, a carbon-intensive byproduct of wastewater treatment, presents both environmental challenges and opportunities for energy recovery. The paper provides a comprehensive analysis of thermal processes such as pyrolysis, gasification, co-combustion, and emerging methods, including hydrothermal carbonization and supercritical water gasification. It evaluates their carbon mitigation potential, energy efficiency, and economic feasibility, emphasizing the importance of catalyst selection, carbon dioxide capture techniques, and reactor optimization. The role of real-time monitoring via sensors and predictive modeling through artificial intelligence (AI) is highlighted as critical for enhancing process control and sustainability. Case studies and recent advances are discussed to outline future pathways for integrating thermal treatment with circular economy principles. This work contributes to sustainable waste-to-energy practices, supporting global decarbonization efforts and advancing the energy transition. Full article

The acceleration of industrialization and urbanization worldwide has dramatically improved living standards but has also introduced serious environmental and public health challenges. One of the most critical challenges is air pollution, particularly indoors, where individuals typically spend over 90% of their time. Ensuring good Indoor Air Quality (IAQ) is essential, especially in heavily frequented public spaces such as shopping malls. This study focuses on assessing IAQ in a large shopping mall located in Tabuk, Saudi Arabia, covering retail zones as well as an attached underground parking area. Monitoring is conducted over a continuous two-month period using calibrated instruments placed at representative locations to capture variations in pollutant levels. The investigation targets key contaminants, including carbon monoxide (CO), carbon dioxide (CO₂), fine particulate matter (PM_2.5), total volatile organic compounds (TVOCs), and formaldehyde (HCHO). The data are analyzed and compared against international and national guidelines, including World Health Organization (WHO) standards and Saudi environmental regulations. The results show that concentrations of CO, CO₂, and PM_2.5 in the shopping mall are generally within acceptable limits, with values ranging from approximately 7 to 15 ppm, suggesting that ventilation systems are effective in most areas. However, the study identifies high levels of TVOCs and HCHO, particularly in zones characterized by poor ventilation and high human occupancy. Peak concentrations reach 1.48 mg/m³ for TVOCs and 1.43 mg/m³ for HCHO, exceeding recommended exposure thresholds. These findings emphasize the urgent need for enhancing ventilation designs, prioritizing the use of low-emission materials, and establishing continuous air quality monitoring protocols within commercial buildings. Improving IAQ is not only crucial for protecting public health but also for enhancing occupant comfort, satisfaction, and overall building sustainability. This study offers practical recommendations to policymakers, building managers, and designers striving to create healthier indoor environments in rapidly expanding urban centers. Full article

The United Arab Emirates has become increasingly concerned about carbon dioxide emissions due to their impact on climate change and the environment, as it is one of the top ten world oil producers. This reflects its recognition of the need for sustainable development. Therefore, this research aims to study the dynamic impact of economic growth, urbanization, energy consumption, and economic openness on CO₂ emissions, during the period 1975–2022. To capture these effects, a novel dynamic ARDL is employed to separate the impact of each variable separately. The results indicate that the effect of GDP per capita on carbon emissions is negative, as a 1% increase in economic growth leads to a decrease in carbon dioxide emissions by 0.6%. Moreover, the findings confirm that the UAE economy does not apply to the Kuznets curve in developing countries. Furthermore, the impact of energy consumption, urbanization, and trade openness is positive on CO₂ emissions, as a 1% increase in each raises CO₂ by 0.17%, 11.6%, and 1.2%, respectively. These findings are important for decision makers in the environmental field to make decisions to reduce carbon emissions by altering the impact of economic variables and spread awareness towards reducing carbon emissions. Full article

Offshore synthetic fuel production and marine carbon dioxide removal can be enabled by direct ocean capture, which extracts carbon dioxide from the ocean that then can be used as a feedstock for fuel production or sequestered underground. To maximize carbon capture, plants require a variety of low-carbon energy sources to operate, such as variable renewable energy. However, the impacts of variable power on direct ocean capture have not yet been thoroughly investigated. To facilitate future deployments, a generalizable model for electrodialysis-based direct ocean capture plants is created to evaluate plant performance and electricity costs under intermittent power availability. This open-source Python-based model captures key aspects of the electrochemistry, ocean chemistry, post-processing, and operation scenarios under various conditions. To incorporate realistic energy supply dynamics and cost estimates, the model is coupled with the National Renewable Energy Laboratory’s H2Integrate tool, which simulates hybrid energy system performance profiles and costs. This integrated framework is designed to provide system-level insights while maintaining computational efficiency and flexibility for scenario exploration. Initial evaluations show similar results to those predicted by the industry, and demonstrate how a given plant could function with variable power in different deployment locations, such as with wind energy off the coast of Texas and with wind and wave energy off the coast of Oregon. The results suggest that electrochemical systems with greater tolerances for power variability and low minimum power requirements may offer operational advantages in variable-energy contexts. However, further research is needed to quantify these benefits and evaluate their implications across different deployment scenarios. Full article

The European Union views biogas production from landfills as a crucial element in achieving decarbonization goals by 2050. Biogas is primarily composed of methane (CH₄) and carbon dioxide (CO₂), produced through the anaerobic digestion of various residual materials. This study aimed to investigate CH₄ and CO₂ concentrations from municipal solid waste in biogas capture wells in a landfill in Romania between 2023 and 2024. A peak in CH₄ concentrations occurred in the fall of 2024 (P4 well), while the highest CO₂ content was recorded in the summer of 2023 (P3 well). The Aermod View software platform (version 11.2.0) was employed to model the dispersion of pollutants in the surrounding air. A worst-case scenario was applied to estimate the highest ground-level pollutant concentrations. The highest recorded CH₄ concentration was 90.1 mg/m³, while CO₂ reached 249 mg/m³ within the landfill. The highest CH₄ concentrations were found in the southern part of the site, less than 1 km from the landfill, while CO₂ was highest in the northern area. In conclusion, municipal solid waste landfills behave like unpredictable bioreactors, and without proper management and oversight, they can pose significant risks. An integrated system that combines prevention, reuse, and correct disposal is critical to minimizing these negative effects. Full article

This study examines the emissions generated by a tall ship of 81.36 m length under various operating conditions, focusing particularly on carbon dioxide emissions at different navigation speeds. The main purpose of the paper is to establish theoretical and practical methods for calculating and measuring the level of CO₂ emitted by the ship engines. Additionally, this article compares the results of carbon dioxide emission calculations based on theoretical methods with the results of real measurements. The paper verifies and assesses the carbon dioxide emission calculation methods compared to the emissions measured in real conditions for diesel engines. A comparative analysis of several methods for determining CO₂ emissions leads to much more accurate and conclusive results close to reality. The results obtained through empirical and theoretical methods for determining CO₂ emissions from the main engine demonstrate that the difference between these values is more accurate at lower engine loads but shows discrepancies at higher loads due to real-world inefficiencies, combustion variations, and model simplifications. The measured CO₂ emission values for auxiliary engines at 60% load demonstrate consistency and closely reflect real operating conditions, while analytical calculations tend to be higher due to theoretical losses and model assumptions. Stoichiometric values fall in between, assuming ideal combustion but lacking adjustments for real variables. This highlights the efficiency of the diesel generator and the importance of empirical data in capturing actual emissions more accurately. The investigation aims to provide a detailed understanding of CO₂ emission variations based on the ship’s operating parameters, including the study of these emissions at the level of the main diesel propulsion engine as well as the auxiliary engines. By analyzing these methods for determining engine emissions, conclusions can be reached about aspects such as the following: engine wear condition, efficiency losses, or incomplete combustion. This analysis has the potential to guide the implementation of new policies and technologies aimed at minimizing the carbon footprint of a reference ship, considering the importance of sustainable resource management and environmental protection in a viable long-term manner. Full article

India’s revised nationally determined contribution at COP26 set a net-zero target for 2070, but the role of carbon dioxide removal (CDR) in achieving this goal remains unclear. This study quantifies the contribution of land-based CDR—bioenergy carbon capture and storage, biochar, and afforestation—in achieving India’s net-zero goal. Additionally, a stylised scenario explores an accelerated net-zero target by 2050 in India`s climate target. The global emission target is modelled to follow India’s climate ambition in both stylised scenarios. The results show that the ambitious 2050 net-zero pathway requires 56 GtCO₂ of cumulative novel CDR across the century, compared to 47 GtCO₂ under the 2070 scenario, with both requiring around 1 GtCO₂/year at net-zero. A higher ambitious pathway leads to increased economic costs, with a mid-century carbon price of USD 938, compared to USD 174 in the 2070 scenario. Without novel CDR methods, the cost of achieving net zero by 2050 quadruple. The accelerated 2050 net-zero pathway also intensifies land and water trade-offs, reducing land for crop production while increasing water demand for electricity and biomass. Despite these challenges, it limits end-of-century warming to 1.46 °C, compared to 1.79 °C under the 2070 scenario. These findings highlight the importance of clearly defined climate targets, scalable CDR strategies, and integrated resource management to balance climate ambition with sustainable development. Full article

The removal of per- and polyfluoroalkyl substances (PFAS) from global aquatic environments is an emerging issue. However, little attention has been paid to addressing accumulated PFAS through their removal. This study demonstrates the encapsulation of perfluoroalkyl carboxylic acids (PFCAs) within polymer microspheres that dissolve in supercritical carbon dioxide (scCO₂). PFCAs were effectively captured by a hindered amine-supported monomer, 2,2,6,6-tetramethyl-4-piperidyl methacrylate (TPMA), in methanol (MeOH) through a simple acid-base reaction. The PFCA-loaded TPMA underwent dispersion polymerization in MeOH in the presence of poly(N-vinylpyrrolidone) (PVP) as a surfactant, producing microspheres with high monomer conversions. The microsphere size depended on the molecular weight and concentration of PVP, as well as the perfluoroalkyl chain length of the PFCAs. X-ray photoelectron spectroscopy (XPS) revealed that the perfluoroalkyl chains migrated from the interior to the surface of the microspheres when exposed to air. These surface perfluoroalkyl chains facilitated dissolution of the microspheres in scCO₂, with cloud points observed under relatively mild conditions. These findings suggest the potential for managing PFCA-encapsulated microspheres in the scCO₂ phase deep underground via CO₂ sequestration. Full article