Search Results (486)

The main advantage of using biomass for energy generation is the reduction in carbon dioxide emissions. For a fast reduction effect, it is important to use biomass characterised by an annual growth cycle. These may be fallen leaves. The fuel properties of the leaves can change during the growth period. These changes can result from both the natural growth process and environmental factors—particulate matter adsorption. The main objective was to determine changes in the characteristics of leaves and needles during the growth period (from May to October). Furthermore, to determine the effect of adsorbed particulate matter, the washing process was carried out. Studies were carried out for three tree species: Norway maple, horse chestnut and European larch. Proximate and ultimate analysis was performed and mercury content was determined. During the growth period, beneficial changes were observed: an increase in carbon content and a decrease in hydrogen and sulphur content. The unfavourable change was a significant increase in ash content, which caused a decrease in calorific value. The increase in ash content was caused by adsorbed particulate matter. They were mostly absorbed by the tissues of the needle and leaves and could not be removed by washing the surface. Full article

This study presents the synthesis, characterization, and application of magnetic magnetite–zirconium dioxide (Fe₃O₄–ZrO₂) nanoparticles as an efficient nanoadsorbent for fluoride removal from water. The nanoparticles were synthesized using a wet chemical co-precipitation method with Fe/Zr molar ratios of 1:1, 1:2, and 1:4, and characterized using Fourier-transform infrared (FTIR) spectroscopy, scanning electron microscopy (SEM), X-ray diffraction (XRD), and energy-dispersive X-ray spectroscopy (EDS). FTIR analysis confirmed the presence of Fe₃O₄ and ZrO₂ functional groups, while XRD showed that increased Zr content led to a dominant amorphous phase. SEM and EDS analyses revealed quasi-spherical and elongated morphologies with uniform elemental distribution, maintaining the designed Fe/Zr ratios. Preliminary adsorption tests identified the Fe/Zr = 1:1 (M1) nanoadsorbent as the most effective due to its high surface homogeneity and optimal fluoride-binding characteristics. Adsorption experiments demonstrated that the material achieved a maximum fluoride adsorption capacity of 70.4 mg/g at pH 3, with the adsorption process best fitting the Temkin isotherm model (R² = 0.987), suggesting strong adsorbate–adsorbent interactions. pH-dependent studies confirmed that adsorption efficiency decreased at higher pH values due to electrostatic repulsion and competition with hydroxyl ions. Competitive ion experiments revealed that common anions such as nitrate, chloride, and sulfate had negligible effects on fluoride adsorption, whereas bicarbonate, carbonate, and phosphate reduced removal efficiency due to their strong interactions with active adsorption sites. The Fe₃O₄–ZrO₂ nanoadsorbent exhibited excellent magnetic properties, facilitating rapid and efficient separation using an external magnetic field, making it a promising candidate for practical water treatment applications. Full article

Population growth has led to an increased volume of wastewater from industrial, domestic, and municipal sources, contaminating aquatic bodies in the state of Veracruz. This study aimed to assess the efficacy of a water treatment system incorporating a DAF stage, followed by the cultivation of a microalgal consortium to eliminate pollutants from the blended effluent. The cultivation of Nannochloropsis oculata in wastewater entailed the assessment of a single variable (operating pressure) within the DAF system, in conjunction with two supplementary variables (residence time and F:M ratio), resulting in removal efficiencies of 70% for CODt, 77.24% for CODs, 78.34% for nitrogen, and 77% for total organic carbon. The water sample was found to contain elevated levels of organic matter and pollutants, beyond the permitted limits set forth in NOM-001-SEMARNAT-2021. The obtained removal percentages indicate that the suggested physicochemical–biological process (DAF-microalgae) is a suitable method for treating mixed wastewater. This approach reduces atmospheric pollution by sequestering greenhouse gases such as carbon dioxide through the photosynthetic activity of N. oculata cells, so facilitating the production of oxygen and biomass while limiting their accumulation in the atmosphere. Full article

Understanding the trends and drivers of greenhouse gases (GHGs) is vital to making effective climate mitigation strategies and benefiting human health. In this study, we investigate carbon dioxide (CO₂) trends in the top three emitting states in the U.S. (i.e., Texas, California, and Florida) using column-averaged CO₂ concentrations (XCO₂) from the Greenhouse Gases Observing Satellite (GOSAT) from 2010 to 2022. Annual XCO₂ enhancements are derived by removing regional background values (XCO_{2, enhancement}), and their interannual changes (ΔXCO_{2, enhancement}) are analyzed against key influencing factors, including population, gross domestic product (GDP), nonrenewable and renewable energy consumption, and normalized vegetation difference index (NDVI). Overall, interannual changes in socioeconomic factors, particularly GDP and energy consumption, are more strongly correlated with ΔXCO_{2, enhancement} in Florida. In contrast, NDVI and state-specific environmental policies appear to play a more influential role in shaping XCO₂ trends in California and Texas. These differences underscore the importance of regionally tailored approaches to emissions monitoring and mitigation. Although renewable energy use is increasing, CO₂ trends remain primarily influenced by nonrenewable sources, limiting progress toward atmospheric CO₂ reduction. Full article

Biogas is a renewable energy source produced by anaerobic digestion of organic waste. It can be upgraded to bio-methane by removing carbon dioxide, water and impurities. The present work focuses on carbon dioxide removal using both physical and chemical absorption in a micromixer. The absorption efficiency in the micromixer was studied under various conditions of co-current gas–liquid flow. With physical absorption, 25% of carbon dioxide could be removed from the biogas stream (with a liquid flowrate of 40 mL/min and a gas flowrate of 25 mL/min). In absorption with a chemical reaction, up to 88% of the carbon dioxide was eliminated with a catalyst concentration of 77.4 mol·m⁻³. In both cases, the space time was below 3 s. Liquid-side mass transfer coefficients as large as 3.5 s⁻¹ were achieved, which is at least two orders of magnitude higher than those reported in conventional absorbers. 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

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

This study investigated carbon dynamics in a peach orchard subjected to three treatments with a mixed compost amendment (MCA, 35% organic content): a control with no amendment (A0), a full dose (A1, 10 t ha⁻¹), and a half dose (A2, 5 t ha⁻¹). The sustainability of MCA was assessed in terms of (i) potential and (ii) actual soil respiration, (iii) soil carbon and physical properties and (iv) fruit quality and yield. Carbon dioxide (CO₂) emissions were measured both in the laboratory, by incubating soil samples without root removal, and in the field using static chambers. Observations spanned three growing seasons (2021–2023). A correlation was found between actual and potential soil respiration, with emission peaks occurring near the time of MCA application. Cumulative actual CO₂ emissions amounted to 5.6, 12.0 and 9.4 t CO₂ ha⁻¹ for A0, A1 and A2, respectively. MCA application (i) increased microbial respiration, (ii) reduced soil physical characteristics, such as bulk density and water-filled pore space, and (iii) slightly improved fruit quality, although the yield was not significantly affected. Furthermore, the MCA enhanced soil organic carbon and total nitrogen content compared to the control. These results suggest that high organic content amendments, such as MCA, could represent a strategy to maintain or increase soil organic matter in a sustainable way, although MCA does not improve carbon emission efficiency. 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

Hydrogen sulfide (${\mathrm{H}}_2$S) and carbon dioxide (${\mathrm{CO}}_2$) can cause various damages that degrade the quality of natural gas before it reaches end users and contribute to environmental pollution. Therefore, it is crucial to eliminate these contaminants to ensure effective usage and prolong equipment lifetime. An acid gas removal unit (AGRU) is a well-known type of equipment for removing ${\mathrm{H}}_2$S and ${\mathrm{CO}}_2$ from natural gas. Forty-six recent research papers have focused on the landscape of the AGRU process and its optimization strategies through experimental and simulation methods, which rely heavily on mathematical approaches. These techniques are often costly and time-consuming. Conversely, discussions on data-driven approaches as optimization techniques for AGRUs are limited. Therefore, this review highlights the potential advancements of data-driven strategies toward AGRU performance. Numerous predictive models of AGRU-related parameters, including ${\mathrm{H}}_2$S and ${\mathrm{CO}}_2$, operating parameters, and material discovery, are discussed in detail. Furthermore, predictive models of fault detection and its prevention are also examined. The literature confirms that data-driven approaches exhibit effective capabilities to enhance the operational performance of AGRUs. This could help industry operators and stakeholders maintain reliable operation and optimize the AGRU’s performance. Full article

Computational fluid dynamics (CFD) models have been widely used to evaluate the hydrodynamic and gas exchange performances of oxygenators, which are crucial in supporting patients with lung diseases or failure. However, while CFD models have been effective in analyzing oxygen transfer, they have not adequately addressed the experimentally demonstrated effects of varying sweep gas flow rates on CO₂ removal. This is a critical gap, as sweep gas flow directly influences the CO₂ transfer efficiency in oxygenators. To fill this gap, we extend our previously developed 1D mathematical model into a 3D computational framework to predict both blood pressure drops and the rates of oxygen and CO₂ transfers in oxygenators. The comparison between our model predictions and experimental data validates the model’s capability in capturing the overall trends in CO₂ transfer/removal rates under different sweep gas flow rates. The results also demonstrated that our model can predict CO₂ removal more accurately, particularly in scenarios where adjusting the sweep gas flow rate is essential for optimizing the oxygenator performance. Full article

Natural gas with a high carbon dioxide (CO₂) content presents significant operational and environmental challenges when used as a fuel. A high CO₂ content lowers the calorific value of natural gas, reducing its fuel efficiency and increasing the risk of corrosion in pipelines and processing equipment. Consequently, such natural gas must be purified to reduce the CO₂ content to acceptable levels before it can be effectively used as a fuel. Various technologies for natural gas purification are currently employed, primarily focusing on CO₂ removal. This research explores an innovative approach where highly contaminated natural gas is utilized to synthesize hydrogen for subsequent methanol production. Methanol synthesis necessitates both hydrogen and CO₂, integrating the use of by-products effectively in the production chain. Following the production of methanol, it is then converted into dimethyl ether (DME), a compound with considerable value as a clean fuel alternative due to its lower emissions when burnt. The open-source COCO simulator was used to model and simulate these processes, allowing for the creation of a detailed process flowsheet. The simulation covered four main stages: (1) purification of the natural gas to remove excess CO₂, (2) production of hydrogen, (3) synthesis of methanol using the hydrogen and captured CO₂, and (4) conversion of methanol to DME. This integrated approach mitigates the issues associated with high CO₂ content in natural gas and leverages this component as a valuable feedstock, demonstrating a comprehensive use of all extracted compounds. The proposed process illustrates a promising route for utilizing highly contaminated natural gas, potentially transforming an environmental liability into valuable chemical commodities. Full article

Our society is facing serious challenges from global warming and environmental degradation. Scientists have identified carbon dioxide as one of the causes. Our society is embracing carbon offset as a way to field the challenges. The purpose of carbon offset is trying to cancel out the large amounts of carbon dioxide by investing in projects that reduce or remove emissions elsewhere. Examples of carbon offset projects are planting trees, renewable energy projects, and capturing methane from landfills or farms. Not all carbon offset projects are equally effective. In stock markets, investors eagerly pursue carbon offset. Namely, investors favor carbon offset in addition to risk and return when investing. Therefore, investors supervise risk, return, and carbon offset. Investors’ pursuits raise the question of how to model carbon offset for investments. The traditional answer is to adopt carbon offset screening and engineer portfolios by stocks with good carbon offset ratings. However, Nobel Laureate Markowitz emphasizes portfolio selection rather than stock selection. Moreover, carbon offset is composed of multiple components, ranging from business, social, economic, and environmental aspects. This multifaceted nature requires more advanced models than carbon offset screening and portfolio selection. Within this context, we systematically formulate multiple-objective portfolio selection models that include carbon offset. Firstly, we extend portfolio selection and treat carbon offset as a whole. Secondly, we separate carbon offsets into different components and build models to monitor each component. Thirdly, we innovate a model to monitor each component’s expectation and mitigate each component’s risk. Lastly, we optimize the series of models and prove the models’ properties in theorems. Mathematically, this paper makes theoretical contributions to multiple-objective optimization, particularly by proving the consistency of efficient solutions during objective classification and model evolution, describing the structure of properly efficient sets for multiple quadratic objectives, and elucidating the optimization’s sensitivity analyses. Moreover, by coordinating the abstract objective function, our formulation is generalizable. Overall, this paper’s contribution is to model carbon offset investments through multiple-objective portfolio selection. This paper’s methodology is multiple-objective optimization. This paper’s achievements are to provide investors with greater precision and effectiveness than carbon offset screening and portfolio selection through engineering means and to mathematically prove the properties of the model. Full article

Carbon mineralization has attracted great interest as a promising strategy to achieve a decarbonized pathway by 2050. Despite the significant environmental and economic promise associated with using industrial solid waste for carbon mineralization, the scale-up application of this approach is limited due to its low reactivity and relatively high cost. A clear understanding of the detailed mechanisms governing various carbonation techniques is needed to achieve high CO₂ conversion efficiency. This review can provide valuable insight into carbon mineralization pathways, advantages and challenges, and potential feedstocks. Factors affecting reaction kinetics, and thereby carbonation efficiency, are also discussed. Then, we focus on the research progress of the most representative industrial solid wastes for CO₂ mineralization, process conditions, and their carbonation potential. Lastly, a market analysis of the precipitated carbonate products is provided to assess economic feasibility for practical applications. Full article

This study investigates a sustainable approach to the photocatalytic degradation of Congo red (CR) dye using titanium dioxide (TiO₂) under simulated solar radiation, with a specific focus on the UV-A component of the radiation. The aim was to optimize reaction conditions to maximize dye removal efficiency while promoting environmentally friendly wastewater treatment practices. A central composite design (CCD) was implemented, and results were analyzed using analysis of variance (ANOVA). The key factors examined included TiO₂ concentration, UV-A radiation intensity, CR dye concentration, and suspension depth. The optimal conditions determined were 222.37 mg/L TiO₂, 20 W/m² UV-A irradiation, 25 µmol/L CR dye concentration, and a suspension depth of 29 mm. Under these conditions, decolorization was achieved with the lowest absorbance (0.367 at 498 nm) and total organic carbon (0.805 mg/L) values, indicating effective dye degradation. The findings confirm that TiO₂-assisted photocatalysis is a green and promising method for wastewater treatment. The potential use of natural solar radiation could reduce operational costs, making the process more sustainable. However, challenges such as photocatalyst recovery, aggregation, and the impact of the real wastewater matrices need further investigation. Full article