Carbon Dioxide Absorption Research Articles

Enhancing soil organic carbon prediction of LUCAS soil database using deep learning and deep feature selection

The main terrestrial carbon (C) fraction is soil organic carbon (SOC), which has a considerable effect on climate change and greenhouse gas emissions through the absorption and sequestration of carbon dioxide (CO2). This has made SOC assessment very important from both economic and environmental viewpoints. The growing count of soil spectral libraries (SSLs) from regional to global scales has brought a tremendous opportunity for the quantification of SOC through developing spectral-based prediction models. Hence, there is a need to take advantage of big data analytics for spectral data processing. The unique ability of deep learning (DL) techniques to leverage important features of high-dimensional large-scale SSLs has made them top-demanding for more sophisticated modeling. The core objective of the present study was to assess the ability of two different DL algorithms, i.e., one-dimensional convolutional neural network (1DCNN) and fully connected neural network (FCNN) coupled with stacked autoencoder (SAE) feature extraction for SOC prediction based on the data from the land use/cover area frame statistical survey (LUCAS) database. SAE extracted the high-level deep features from the visible–near-infrared–shortwave infrared (Vis–NIR–SWIR) spectra of 11441 soil samples, which were then considered as inputs to the 1DCNN and FCNN models for predicting the SOC content. Both SAE-DL feature-selected models yielded higher accuracy than those the DL developed on the entire spectra and a random forest (RF) model was constructed for comparison. The best prediction was achieved by SAE-1DCNN (R2= 0.78, RMSE = 3.94%, RPD = 4.88, RPIQ = 3.91) followed by 1DCNN (R2= 0.73, RMSE = 5.43%, RPD = 3.67, RPIQ = 2.84) proving the superiority of 1DCNN over FCNN in this study. These results supported the applicability of combined deep features extraction and regression methods for predicting SOC using high dimensional large-scale SSLs.

Comparative study of deterministic and stochastic optimization algorithms applied to the absorption of CO2 by alkanolamine solution

Abstract A model based on simulated annealing approach is used with e-UNIQUAC model as well as two other algorithms to study the absorption of carbon dioxide by monoethanolamine solutions. In this work, we propose to compare the performance (through the knowledge of RMSD values) of two stochastic methods, namely the GA (genetic algorithm) and SA (simulated annealing) methods and a deterministic method that is the simplex method. These methods were applied to the absorption of carbon dioxide by an alkanolamine solution using a chemical equilibrium model and a thermodynamic equilibrium model. The latter is based on the use of the modified-UNIQUAC (UNIQUAC-electrolyte) model instead of e-NRTL model for the liquid phase and a fugacity model for the vapor phase. The chemical equilibrium in this work represents the absorption of CO2 by monoethanolamine solution at different temperatures. Solving the coupled system of material and charge balances gives us the carbon dioxide pressure while taking into account the non-ideality of the system. The three-optimization methods show good agreement with the experimental data with a better performance of the simulated annealing method..

Integration of weighted majority voting in machine learning algorithms to enhance pine tree crown mapping on UAV imagery

Abstract. The shape and area of the crown of each tree are among the most influential parameters for identifying and controlling the processes of photosynthesis, respiration, transpiration and its management. In such a way that various physiographic functions, such as carbon dioxide absorption, light energy absorption, oxygen release and transpiration, which are vital for the growth and development of the tree, are done in the crown. In this research, the RGB image of the UAV with a spatial resolution of 2 cm was resampled to three pixel sizes of 10, 30 and 50 cm. Then, each image was classified separately by SVM, ANN and MLC algorithms, which are all part of Ensemble. In the next step, each of the obtained crowns was compared with the digitization of the same crown, and based on the area of the crown obtained from each classification and normalization method, the weight was obtained specifically for the same crown. Finally, by using the weighted majority voting method, classifications were fusioned at the decision level. The results showed that the ANN method gives better results in all pixel sizes compared to MLC and SVM. Also, the combination of different classification methods with the weighted majority voting method based on the weight assigned to the same crown based on each classification method has significantly increased the classification accuracy of the tree crown in all the sizes of the analyzed pixels.

The Recycling of Lithium from LiFePO4 Batteries into Li2CO3 and Its Use as a CO2 Absorber in Hydrogen Purification

The growing adoption of lithium iron phosphate (LiFePO4) batteries in electric vehicles (EVs) and renewable energy systems has intensified the need for sustainable management at the end of their life cycle. This study introduces an innovative method for recycling lithium from spent LiFePO4 batteries and repurposing the recovered lithium carbonate (Li2CO3) as a carbon dioxide (CO2) absorber. The recycling process involves dismantling battery packs, separating active materials, and chemically treating the cathode to extract lithium ions, which produces Li2CO3. The efficiency of lithium recovery is influenced by factors such as leaching temperature, acid concentration, and reaction time. Once recovered, Li2CO3 can be utilized for CO2 capture in hydrogen purification processes, reacting with CO2 to form lithium bicarbonate (LiHCO3). This reaction, which is highly effective in aqueous solutions, can be applied in industrial settings to mitigate greenhouse gas emissions. The LiHCO3 can then be thermally decomposed to regenerate Li2CO3, creating a cyclic and sustainable use of the material. This dual-purpose process not only addresses the environmental impact of LiFePO4 battery disposal but also contributes to CO2 reduction, aligning with global climate goals. Utilizing recycled Li2CO3 decreases the demand for virgin lithium extraction, supporting a circular economy. Furthermore, integrating Li2CO3-based CO2 capture systems into existing industrial infrastructure provides a scalable and cost-effective solution for lowering carbon footprints while securing a continuous supply of lithium for future battery production. Future research should focus on optimizing lithium recovery methods, improving the efficiency of CO2 capture, and exploring synergies with other waste management and carbon capture technologies. This comprehensive strategy underscores the potential of lithium recycling to address both resource conservation and environmental protection challenges.

Modelling of Carbon Dioxide Absorption in Hollow Fiber Membrane Contactor for Different Flow Configurations

Modelling of Carbon Dioxide Absorption in Hollow Fiber Membrane Contactor for Different Flow Configurations

Blue Carbon Potential of Mangrove Ecosystems and Its Management to Promote Climate Change Mitigation in Indonesia

This research aimed to analyze blue carbon potential and mangrove ecosystem management in promoting climate change mitigation in Indonesia. The collected data included mangrove area data obtained through the Indonesian National Ecosystem Monitoring System (SIMONTANA). This research calculated the carbon stock using the global average of mangrove carbon stock. The results showed that the total blue carbon stored in mangrove ecosystems reached 3,267.87 Megaton Carbon (MtC). Papua and Kalimantan regions contributed the most significant potential, with 1,707.22 MtC and 608.17 MtC, respectively. The absorption of carbon dioxide (CO2) reached 11,982.21 MtCO2e. The most significant CO2 gas emissions absorption was observed in the Papua region, amounting to 6,259.80 MtCO2e, followed by Sumatra with 2,118.59 MtCO2e. This high potential value correlated with mangrove ecosystem management policies, such as conservation, restoration, and blue carbon monetization. Mangrove management for climate change mitigation was carried out through national and international cooperation to achieve the 26% to 40% emission reduction target. The existing management model of mangrove ecosystems focused on improving ecological sustainability with less orientation on improving community welfare. Implementing blue carbon monetization at the district level by involving the community as the owners or managers of the mangrove ecosystems is crucial.

Climate Change Implications on Middle Eastern Geography and Stability – A Case Studies of GCC- with a Focus on the Kingdom of Saudi Arabia

The environment constitutes the natural setting where humans reside, secure food sources, and utilize natural resources to fulfill their material and life necessities. Unlike other creatures, humans have not adapted to nature and the surrounding environment; instead, they have manipulated it to their advantage, disrupting the ecological balance. The primary catalyst for this disruption was the Industrial Revolution, which significantly increased pollution rates, harmful emissions, and the extraction of raw materials, thereby intensifying the exploitation of natural resources. The gravest concern is that the damage inflicted upon nature may reach a point of no return, with catastrophic and enduring consequences, such as global warming, ice melting, rising sea levels, and escalation in greenhouse gases, along with severe repercussions of these events, including an increase in mortality rates due to natural disasters. Effective responses necessitate actions at various levels, including cultural and educational initiatives and international measures, particularly in legislation. Such laws must enforce stringent controls on emissions from industrial and automotive sources. Individuals are called upon to conserve electricity and water, and adopting renewable energy sources, such as solar, hydro, wind, and tidal energy, that do not rely on fuel combustion is encouraged. Planting trees, which absorb carbon dioxide as a primary contributor to global warming, is among the most critical measures we can undertake. The Gulf Cooperation Council (GCC) is essential in combating climate change in this arena, and the Kingdom of Saudi Arabia is leading in this. This paper elaborates on the impact of climate change in Middle Eastern countries using a brief case study of the Saudi Green Initiatives. The paper also presents the policy recommendations to the concerned stakeholders of the GCC and the government of Saidi Arabia.

Exploring the potential of biohydrogen as a sustainable energy solution for Pakistan: A review of production processes and policy challenges

Due to growing carbon dioxide emissions and the depletion of fossil-based energy sources, international studies have been focusing more intensely on developing hydrogen as a source of renewable energy. Biohydrogen is an exciting and green alternative energy source with various different benefits. Unlike traditional energy sources, biohydrogen production does not emit pollutants, making it a more environmentally friendly option. Biohydrogen generation, particularly from microalgae and other low-cost biomass feedstocks, so offers the dual benefit of delivering clean electricity while absorbing Carbon Dioxide. This research investigates the possibility of biohydrogen as a sustainable energy solution for Pakistan's climate issue. We examine the current state of biohydrogen generation technologies, such as dark fermentation, photo fermentation, bio photolysis, with a focus on their potential application in Pakistan. The study investigates global advances in biohydrogen research and their significance in Pakistan, demonstrating biohydrogen's potential contribution to Pakistan's energy independence and environmental targets, as well as the practical and policy-related challenges that must be addressed to advance biohydrogen energy generation and wider adoption.

Active near‐infrared laser heterodyne system based on supercontinuum laser source for gas measurement

AbstractThe performance of an active near‐infrared laser heterodyne system using a supercontinuum light source as the light signal for trace species detection is experimentally demonstrated. The characteristics of the supercontinuum light source and the data processing methods used in heterodyne detection are described. The measurement of methane (CH₄) and carbon dioxide (CO₂) absorption spectra was carried out in the laboratory to evaluate the active laser heterodyne system, and high‐resolution absorption spectra of CO₂ and CH₄ were recorded simultaneously. The stability of the active laser heterodyne system is analyzed using Allan variance analysis of long‐term observation data. The active near‐infrared laser heterodyne detection system demonstrated in this paper has great potential for the development of industrial parks' gas monitoring.

Perennial Fodder Crops as a Tool for Soil Carbon Management in Agroecosystems

Carbon sequestration, typically referred to as carbon storage is defined as the “long-term storage of carbon in plants, soils, geologic formations and the ocean, which occurs both naturally and as a result of anthropogenic activities”. With respect to agricultural sector, carbon sequestration is viewed as the capability of agriculture lands to absorb carbon dioxide from the atmosphere. Out of the different ways in play, cultivation of fodder crops turns out to be promising due to its high biomass production, root proliferation, mostly perennial nature, suitability for wastelands and most importantly as the feed for livestock. Restoration of degraded lands, adoption of pasture-based agroforestry systems, inclusion of grasses, sowing of improved forage species, grazing management, nutrient and water management are strategies that aid in improving carbon sequestration in fodder production systems. Perennial fodder grasses and fodder legumes such as alfalfa are excellent for carbon storage as they do not require replanting after each harvest which avoids soil disturbances that usually associate with annual crops. Carbon neutral methods of cultivation is greatly hoped to convert agriculture from a source of carbon to a permanent sink of carbon at a faster pace.

Knowledge Distillation for Urban Tree Image Classification Based on the Diffusion Model

As urban areas continue to emerge as significant contributors to global carbon emissions, the classification of urban street trees has gained increasing importance in carbon sequestration research. By precisely identifying and categorizing different tree species, the carbon absorption capabilities of urban vegetation can be evaluated more accurately. This understanding is essential for addressing the growing environmental challenges posed by carbon emissions, as urban trees play a crucial role in absorbing carbon dioxide and mitigating the effects of climate change. In this study, a Feature Distillation Based on Diffusion Model (FDBD) framework was proposed, utilizing state-of-the-art image classification technology to enhance the accuracy of urban tree species identification. The framework utilized knowledge distillation, a process where a smaller, more efficient “student” model is trained to mimic the performance of a larger, more complex “teacher” model, significantly reducing computational demands while maintaining high accuracy. The model’s effectiveness has been validated through combination experiments with a selected backbone model, achieving promising results. This approach not only enhances the understanding of urban trees’ carbon sequestration potential but also provides crucial insights for policymakers. By facilitating precise tree classification, it empowers urban planners to implement more informed and targeted strategies for carbon reduction, ultimately promoting more sustainable urban environments.

In situ monitoring of CO2$$ {}_2 $$ sorption on polyethylenimine dynamics through broadband dielectric spectroscopy

AbstractChemical reactions between carbon dioxide (CO) and amine have been extensively characterized, however, their influence on the dynamics of polyamines remains largely unexplored. In this work, we compare the dynamics of polyethylenimine (PEI) before and after CO absorption through broadband dielectric spectroscopy (BDS). The molecular processes of bulk PEI are very different from those of thin film PEI, highlighting an interesting interface and nano‐confinement effect. Detailed analyses show CO absorption slows down the PEI dynamics, which is consistent with an elevated glass transition temperature of PEI upon CO absorption from differential scanning calorimetry measurements. Further in situ kinetic measurements demonstrate nonmonotonic changes in relaxation times or dielectric amplitudes of some relaxation processes during CO sorption or desorption, suggesting an intriguing interplay between CO chemisorption and the dynamics of PEI. These results demonstrate that BDS is a powerful platform to resolve the temporal dynamics changes of polyamines for CO capture.

Обобщенные модели фитомассы деревьев ивы (род Salix L.): мета-анализ

Climate change has a negative impact on the environment, including forest ecosystems. However, forests are not only passive objects affected by climate change, but also, due to their ability to absorb and accumulate carbon, they themselves can significantly influence this process. Carbon sequestration by forest ecosystems plays an important role in mitigating the effects of climate change. Therefore, it is necessary to know about the amount of carbon stored in forest phytomass, and it is becoming increasingly important to accurately determine the phytomass of forest trees. Due to the absorption of carbon dioxide during plant growth and its release during wood burning, forests are a carbon-neutral energy source. The idea of using phytomass as an energy source to replace fossil fuels is most promising for fast-growing species. These include willows (genus Salix L.), native to Europe, Asia, America and Africa and found from the tundra to the tropics. Willow is successfully used as fuel in many countries, showing excellent growth and productivity even at juvenile stages and, under certain climatic conditions, having the highest capacity among woody plants to convert solar radiation into phytomass. Short-rotation willow plantations represent an ecologically promising energy resource for reducing greenhouse gas levels. Since the development of phytomass models is a laborious process, so-called “generic meta-models” are used. The aim of this study has been to construct generic models of both aboveground phytomass and phytomass fractions (foliage, branches, stem, roots) of willow trees based on meta-analysis of data. In the course of the work, the models have been constructed for assessing the aboveground phytomass of trees both in diameter at the stem base and in diameter at breast height, the information content of which is close to functional, and the biases are only about 2 %. Since each fraction of phytomass has a specific carbon-sequestering capacity and makes a different contribution to the carbon balance, generic models have been developed to estimate the mass of foliage, branches, stems and roots in relation to the aboveground phytomass of trees, explaining from 82 % (for foliage) to 99 % (for stems and roots) of the total variability of phytomass.

Study on the properties and eco-sustainability of early-age carbonation cured cement paste with recycled concrete slurry waste substitution

The reduced early-age properties of cementitious materials substituted recycled concrete slurry waste (RCSW) hinder its utilisation, which can be further improved via early-age carbonation curing with benefits from sequestering the CO2. This study aims to compressively investigate the effectiveness and environmental impact of early carbonation curing on three replacement ratios and three types of treatments of RCSW including sieving, shearing and ball milling with standard curing. In addition to mechanical properties, hydration properties, microstructure characteristics, and carbon sequestration of the treated-RCSW replaced cement paste after different curing methods were investigated and compared. The results showed that, compared to substitution ratios of 30 % and 45 %, cement paste with a 15 % RCSW substitution ratio exhibited higher strength. Furthermore, compared to standard curing, the carbonation curing method effectively improved the early strength and overall performance of the cement paste, with the early strength under carbonation curing at a 15 % RCSW substitution rate being about 89 % higher than that of standard curing. According to economic and environmental calculations, RCSW substitution could effectively reduce carbon dioxide emissions, and the use of carbonised curing methods enabled the cement paste to effectively absorb carbon dioxide.

Modeling of carbon dioxide absorption into aqueous alkanolamines using machine learning and response surface methodology

This research focuses on modeling CO2 absorption into alkanolamine solvents using multilayer perceptron (MLP), radial basis function network (RBF), Support Vector Machine (SVM), networks, and response surface methodology (RSM). The parameters, including solvent density, mass fraction, temperature, liquid phase equilibrium constant, CO2 loading, and partial pressure of CO2, were used as input factors in the models. In addition, the value of CO2 mass flux was considered as output in the models. Trainlm, trainbr, and trainscg algorithms trained the networks. The results showed that the best number of neurons for MLP with one layer is 16; with two layers, 5 neurons in the first layer and 12 neurons in the second layer; and with three layers, 9 neurons in the first layer, 5 neurons in the second layer, and 1 neuron in the third layer. The best spread in RBF was found to be 2.202 for optimal network performance. Furthermore, statistical data analysis revealed that the trainlm function performs best. The coefficients of determination for RSM, MLP, RBF, and SVM for optimized structures are obtained at 0.9802, 0.9996, 0.9940, and 0.8946, respectively. The results demonstrate that MLP and RBF networks can model CO2 absorption using the trainlm, trainbr, and trainscg algorithms.

Investigating the role of biomass energy consumption and forest products trade on the forest footprint in Finland: an environmental Kuznets curve analysis

AbstractForests are essential in mitigating climate change by absorbing carbon dioxide and maintaining ecosystems, mainly through preserving biodiversity. For this reason, the sustainability of forests is essential for human life. This paper examines the role of biomass energy consumption, forest product trade, and economic growth on Finland’s forest footprint from 1970 to 2018. By employing Fourier-based unit root and cointegration tests, we confirm the Environmental Kuznets Curve (EKC) hypothesis, demonstrating a long-term relationship in which economic growth first raises, then reduces the forest footprint. Biomass energy consumption and forest products trade show an insignificant long-term effect on the forest footprint. We found unidirectional causality from the forest footprint to biomass energy consumption and economic growth. This research fills a gap by focusing on the under-researched forest footprint within the EKC framework, particularly in Finland’s context of stringent forestry policies. Our findings emphasize the need for interdisciplinary collaboration to enhance environmental policy and sustainability practices. We further contribute to the broader literature on sustainable forest management and offer actionable policy recommendations for enhancing Finland’s environmental strategies.

Process Intensification of Gas–Liquid Separations Using Packed Beds: A Review

The gas–liquid multiphase process plays a crucial role in the chemical industry, and the utilization of packed beds enhances separation efficiency by increasing the contact area and promoting effective gas–liquid interaction during the separation process. This paper primarily reviews the progress from fundamental research to practical application of gas–liquid multiphase processes in packed bed reactors, focusing on advancements in fluid mechanics (flow patterns, liquid holdup, and pressure drop) and the mechanisms governing gas–liquid interactions within these reactors. Firstly, we present an overview of recent developments in understanding gas–liquid flow patterns; subsequently we summarize liquid holdup and pressure drop characteristics within packed beds. Furthermore, we analyze the underlying mechanisms involved in bubble breakup and coalescence phenomena occurring during continuous flow of gas–liquid dispersions, providing insights for reactor design and operation strategies. Finally, we summarize applications of packed bed reactors in carbon dioxide absorption, chemical reactions, and wastewater treatment while offering future perspectives. These findings serve as valuable references for optimizing gas–liquid separation processes.

Re-evaluating winter carbon sink in Southern Ocean by recovering MODIS-Aqua chlorophyll-a product at high solar zenith angles

Satellite ocean color observations are extensively utilized in global carbon sink evaluation. However, the valid coverage of chlorophyll-a concentration (Chla, mg m−3) measurements from these observations is severely limited during autumn and winter in high latitude oceans. The high solar zenith angle (SZA) stands as one of the primary contributors to the reduced quality of Chla products in the high-latitude Southern Ocean during these seasons. This study addresses this challenge by employing a random forest-based regression ensemble (RFRE) method to enhance the quality of Moderate Resolution Imaging Spectroradiometer (MODIS) Chla products affected by high SZA conditions. The RFRE model incorporates the color index (CI), band-ratio index (R), SZA, sensor zenith angle (senz), and Rayleigh-corrected reflectance at 869 nm (Rrc(869)) as predictors. The results indicate that the RFRE model significantly increased the MODIS observed Chla coverage (1.03 to 3.24 times) in high-latitude Southern Ocean regions to the quality of standard Chla products. By applying the recovered Chla to re-evaluate the carbon sink in South Ocean, results showed that the Southern Ocean’s ability to absorb carbon dioxide (CO2) in winter has been underestimated (5.9–18.6 Tg C year−1) in previous assessments. This study underscores the significance of improving the Chla products for a more accurate estimation of winter carbon sink in the Southern Ocean.

SEMI-BATCH EXPERIMENTAL STUDY ON MULTIPLE CARBON DIOXIDE BUBBLES ABSORPTION IN SWEETENER SOLUTION UNDER VARYING PRESSURES

Increasing the absorbed carbon dioxide amount in sweetener solution is a new trend to modify soft drinks. This research investigated the optimum increase in absorbed carbon dioxide within the limits of permissible food specifications in the bubble column. Response surface methodology (RSM) utilizing the Box Behnken design (BBD) was used to conduct experiments operating conditions for achieving desired responses within specified ranges of pressure (2-4 bar), temperature (5-25°C), gas flow rate (0.2–0.4 L/min), and absorbent concentration (0–150 g/L). The experimentally obtained results were fitted to a second-order polynomial model—the increase in pressure and gas flow rate results in an increase in absorption yield (YCO2). Also, increasing the gas flow rate and temperature will increase the volumetric mass transfer coefficient (KLa), while, at high pressure and pore size KLa will be reduced. According to the obtained results at optimum conditions, 4 bar, 5°C, gas flow rate 0.4 L/min, sucrose concentration of 0 g/L, and pore diffuser 0.5 μm; The CO2 content (YCO2) was 8.34 g/L. The optimum conditions for combining the effect of high CO2 content (6.125 g/L) and best KLa value (0.1043 L/min) were: 2.83 bar, 5 °C, a gas flow rate of 0.4 L/min, a sucrose concentration of 65.15 g/L, and pore diffuser of 0.5 μm.

Production of low-carbon cement composites using red sandstone: CO2 storage and performance analysis

Carbonation curing is currently one of the most effective methods for reducing carbon and absorbing carbon dioxide in cement-based materials. This study evaluated the macroscopic, microscopic, and thermal properties of red sandstone and limestone with different dosages under different curing methods. The results show that the carbonation rate is higher when 20 % red sandstone is added, and the carbon fixation amount is the highest. The inclusion of red sandstone provides more nucleation sites for the formation of carbonation product silica gel. At 600°C, the strength reduction of the carbonation samples is lower than that of the sealed samples, and the carbonation products are more resistant to high temperatures. Furthermore, the relationship between the microscopic, macroscopic, and thermal properties of red sandstone and limestone under different curing methods is explored. This study provides a new approach to the utilization of red sandstone resources.