CO2 Discharge Research Articles

Energy management optimization of hybrid electric vehicles based on deep learning model predictive control

In this paper, the hybrid electric vehicle (HEV) energy management optimization method is proposed based on deep learning (DL) model predictive control. Through empirical research combined with the questionnaire survey, this article not only provides a new perspective and practical basis but also improves the efficiency and accuracy of the model by improving the relevant algorithms. The study first analyzes the importance of HEV energy management and reviews the existing literature. Then, the optimization method of HEV energy management based on the deep learning model is introduced in detail, including the composition of energy management for hybrid electric vehicles, the structure and working principle of the deep learning model, especially the backpropagation neural network (BPNN) and the convolutional neural network (CNN), and the steps of application of deep learning in energy management. In the experimental part, questionnaire data from 1,500 consumers were used to design the HEV energy management optimization scheme, and consumers’ attitudes and preferences towards HEV energy optimization were discussed. The experimental results show that the proposed model can predict HEV energy consumption under different road conditions (urban roads, highways, mountain areas, suburban areas, and construction sites), and the difference between the average predicted energy consumption and the actual energy consumption is between 0.1KWH and 0.3KWH, showing high prediction accuracy. In addition, the deep learning-based energy management strategy outperforms traditional control strategies in terms of fuel consumption (6.2 L/100 km), battery charge and discharge times (814), battery life, and CO2 emissions, significantly improving the efficiency of HEV energy. These results demonstrate the great potential and practical application value of deep learning models in the optimization of energy management of HEVs, helping to drive the development of more sustainable and efficient transportation systems.

Numerical Simulation of the Dynamics of RF Capacitive Discharge in Carbon Dioxide

In this research, the one-dimensional fluid code SIGLO-rf was used to study the internal parameters of RF capacitive discharge in carbon dioxide, focusing mainly on time-averaged and spatio-temporal distributions of discharge parameters. With the help of this code, in the range of distances between electrodes d = 0.04 – 8 cm, RF frequencies f = 3.89 – 67.8 MHz, and values of carbon dioxide pressure p = 0.1 – 9.9 Torr, averaged over the RF period axial profiles of the density of electrons, positive and negative ions were calculated as well as potential and electric field strength. It is shown that the discharge plasma in CO2 contains electrons, positive ions, as well as negative ions. The negative ions of atomic oxygen are formed by the dissociative attachment of electrons to CO2 molecules. Studies of the spatio-temporal dynamics of plasma parameters (electron density, potential and electric field strength, as well as ionization and attachment rates) in RF capacitive discharge in CO2 showed that during half of the RF period, 1 to 3 ionization bursts are usually observed. They correspond to stochastic heating in the near-electrode sheath and the formation of passive and active double layers near the sheath boundaries. The passive double layer appears in the cathode phase and maintains the discharge plasma. The active layer is formed in the anodic phase and ensures a balance of positive and negative charges escaping to the electrode during the RF period. It was found that when the conditions pd = 2 Torr cm and fd = 27.12 MHz cm are met simultaneously, during half of the RF period, 4 intense ionization peaks are observed: resulting from stochastic heating, passive, active, and additional (auxiliary) double layers. The auxiliary double layer helps bring electrons to the surface of the temporary anode and occurs near its surface inside the near-electrode sheath. Using the similarity law, the conditions for the existence of these 4 ionization peaks in a wide range of RF frequencies, carbon dioxide pressures, and distances between electrodes were verified.

Real-Time Calculation of CO2 Conversion in Radio-Frequency Discharges under Martian Pressure by Introducing Deep Neural Network

In recent years, the in situ resource utilization of CO2 in the Martian atmosphere by low-temperature plasma technology has garnered significant attention. However, numerical simulation is extremely time-consuming for modeling the complex CO2 plasma, involving tens of species and hundreds of reactions, especially under Martian pressure. In this study, a deep neural network (DNN) with multiple hidden layers is introduced to investigate the CO2 conversion in radio-frequency (RF) discharges at a given power density under Martian pressure in almost real time. After training on the dataset obtained from the fluid model or experimental measurements, the DNN shows the ability to accurately and efficiently predict the various discharge characteristics and plasma chemistry of RF CO2 discharge even in seconds. Compared with conventional fluid models, the computational efficiency of the DNN is improved by nearly 106 times; thus, a real-time calculation of RF CO2 discharge can almost be achieved. The DNN can provide an enormous amount of data to enhance the simulation results due to the very high computational efficiency. The numerical data also suggest that the CO2 conversion increases with driving frequency at a fixed power density. This study shows the ability of the DNN-based approach to investigate CO2 conversion in RF discharges for various applications, providing a promising tool for the modeling of complex non-thermal plasmas.

Molar-scale formate production via enzymatic hydration of industrial off-gases

Decarbonizing the steel industry, a major CO2 emitter, is crucial for achieving carbon neutrality. Escaping the grip of CO combustion methods, a key contributor to CO2 discharge, is a seemingly simple yet formidable challenge on the path to industry-wide net-zero carbon emissions. Here we suggest enzymatic CO hydration (enCOH) inspired by the biological Wood‒Ljungdahl pathway, enabling efficient CO2 fixation. By employing the highly efficient, inhibitor-robust CO dehydrogenase (ChCODH2) and formate dehydrogenase (MeFDH1), we achieved spontaneous enCOH to convert industrial off-gases into formate with 100% selectivity. This process operates seamlessly under mild conditions (room temperature, neutral pH), regardless of the CO/CO2 ratio. Notably, the direct utilization of flue gas without pretreatment yielded various formate salts, including ammonium formate, at concentrations nearing two molar. Operating a 10-liter-scale immobilized enzyme reactor feeding live off-gas at a steel mill resulted in the production of high-purity formate powder after facile purification, thus demonstrating the potential for decarbonizing the steel industry.

Spatially resolved TALIF investigation of atomic oxygen in the effluent of a CO2 microwave discharge

A diagnostic setup for one-dimensionally spatially resolved two-photon absorption laser-induced fluorescence (TALIF) detection of ground state oxygen atoms ( 2p43P2,1,0 ) is developed. The goal of this study is to investigate the evolution of temperatures and absolute number densities of oxygen atoms along the effluent of a low-pressure CO2 microwave discharge in order to gain insights into some of the mechanisms governing the post-discharge regime. The plasma source is operated at conditions of 600 W– 1200 W of absorbed power with flow rates of 74 sccm and 370 sccm pure CO2 at pressures between 1.2 mbar and 5 mbar with specific energy inputs up to 111.9 eV/molecule. These operating conditions exhibit high CO2 conversions (up to 90%) at low energy efficiencies (2%–7.4%), due to direct electron impact dissociation driving the conversion process resulting in splitting of CO2 into CO and metastable oxygen atoms. The TALIF measurements yield spatially resolved translational temperatures between 1000 K– 1600 K for most operating conditions and axial positions along the effluent. Reference measurements with xenon 6p′[3/2]2 are used for absolute number density calibration. The resulting axially resolved number density profiles of ground state atomic oxygen increase along the effluent, even at considerable distances of several centimeters from the active discharge, before they reach a maximum between 5×1020 m−3 and 2.2×1021 m−3 depending on the condition, and decrease after that. This behavior indicates the potential significance of quenching of metastable oxygen atoms within the post-discharge regime of the investigated CO2 discharges. The measured spatially resolved number density evolutions are qualitatively consistent with quenching via wall collisions being the dominant deactivation mechanism, underlining the importance of particle-wall interactions.

Mapping the waste heat recovery potential of CO2 intercooling compression via ORC

The goal of the present work is the systematic mapping of the electricity savings potential of waste heat recovery (WHR) from CO2 compression intercoolers via Organic Rankine Cycle (ORC) technology. Α generalized approach covering a broad range of target CO2 discharge pressures from 50 to 500 bar for 3 to up to 8 compression stages is followed. The maximum, theoretical electricity savings based on the exergy of the heat transfer fluid (HTF) used for intercooling range between 10 % and 24 %. Considering the exergy efficiency of optimized air-cooled ORCs operating with alkanes and hydrofluoroolefins for HTF temperatures between 70 °C and 130 °C, the maximum electricity savings ratio (i.e., the electricity savings compared to the total electricity consumption of the compression unit) is about 5 %, while the installed power of the WHR-ORC ranges from about 3 to 23 kWe per kg/s of compressed CO2. Because of the intense variability of CO2 specific heat capacity over a wide range of pressures, there is a very strong dependence of the waste heat potential on the final discharge pressure and number of stages. Through optimized mixing of the HTF streams, the performance of the WHR-ORC can be improved for particular discharge pressure ranges. Proper sizing of the ORC air-cooled condenser for minimizing air-side pressure drop is critical to ensure the feasibility of WHR-ORCs. According to a techno-economic analysis, WHR-ORCs can result in discounted payback periods from 6 to 12 years and 2.5 to 4 years for 4000 and 8000 operating hours, respectively.

Multiple Attribute Group Decision-Making with Neutrosophic Environment for Carbon Emission Prediction on Sustainable Urban Management

Sufficient CO2 is indispensable for vegetation, but space and oceanic vehicles, industrial chimneys and land use tons of extreme CO2 and are typically accountable for global warming, climate variations and greenhouse effect. Owing to COVID19, CO2 discharge was in 2020 at its lower level than first ten years. However, the time taken is not known to decrease, increase or change carbon emissions to an endurable point. Precise predicting of carbon production has real consequences for selecting the optimal ways of decreasing carbon emissions. A pressing necessity to control these carbon emissions is needed. The preliminary step is to precisely recognize the milestones and threat levels. Specific thresholds should be mapped that formulate the maximum levels of CO2 namely – the point of no return, risk point, and so on. This article focuses on the development of Multiple Attribute Group Decision-Making with Neutrosophic Environment for Carbon Emission Prediction (MAGDM-NECEP) method on Sustainable Urban Management. The MAGDM-NECEP architecture proficiently manages the multi-criteria nature of emission calculation, while neutrosophic logic accommodates ambiguity and uncertainty in input dataset. Furthermore, GSO enhances model parameters, improving prediction performance. The MAGDM synergy and neutrosophic logic offer strong decision-making abilities, whereas GSO fine-tuned the model parameter for superior outcomes. Empirical analysis establishes the efficiency of the presented technique in precisely predicting carbon emission, providing valuable insight for the environmentalist and policymaker in developing efficient mitigation strategy

Enhanced methanol selectivity and synthesis in a non-catalytic dielectric barrier discharge (DBD) plasma reactor

Direct utilisation of CO2 to methanol via environmentally friendly gas-to-liquid processes with plasma poses various challenges, such as low methanol selectivity. This study explores the non-catalytic hydrogenation of CO2 and CO gas mixtures in a self-cooling dielectric barrier discharge (DBD) plasma at atmospheric pressure and temperature. Small amounts of N2 and argon were input as auxiliary gases to investigate their effect on methanol production and a probable reaction mechanism was suggested. A H2 + CO2 + CO + N2 mixture minimised methanation and the reverse water–gas shift competitive reactions, thus enhancing methanol selectivity and yield to 86 % and 22.5 %, respectively. Furthermore, N2 helped reduce plasma power requirements, stabilised the discharge, and displayed suitable third-body properties able to tune up plasma reactions yielding a better methanol production rate than argon. Our findings reveal that plasma performance can be enhanced using a suitable reactant composition in combination with gas additives (in this case, N2) to improve methanol synthesis.

Transformation of medical plastic waste to valuable carbon dots: A sustainable recycling of medical waste to efficient fluorescent marker

The dumped medical waste including disposable syringes, gloves and face masks is one of the primary responsible factors causing environmental threats and escalating landfills and CO2 discharges. Thus transforming these medical wastes into worthy carbon-based nanomaterials has offered an effective option for sustainable recycling of medical waste to efficient fluorescent markers. The current work utilizes disposable syringes, gloves and face masks as precursor sources to produce three different types of carbon dots (CDs) by using a simple heating method. The prepared CDs from three different sources have displayed considerable variations in the optical and luminescence properties of CDs. The supremacy of the prepared particles on biocompatibility parameters and the relationships between precursor source and concentration of formed CDs are also discussed via studying the antioxidant and seed germination assay. The outlook of controllable up cycled medical waste derived CDs has further been tested to develop selective and sensitive turn-off sensor for the detection of iron (Fe3+) ions. The corresponding quenching behavior in the presence of Fe3+ ions has further been explored by carrying out the optical and emission as a function of concentration and interference studies. The linear ranges for Fe3+ detection were 50 μM to 30 nM with a limit of detection down to 0.80 nM, 0.42 nM and 0.29 nM for F@CDs, S@CDs and G@CDs generated from face masks, syringes and gloves respectively. This current work presents an effective alternative to the discovery of efficient methodologies for converting disposable medical waste for environmental remediation applications and progressive conclusions for accomplishing lucrative means to manage medical waste to value added products.

Fiscal and Monetary Measures in Achieving Green Ecology: Evidence from Nigeria

Abstract Research background In light of the apparent density of the carbon output in the ecosystems of emerging regions, the United Nations has established a manual that puts an emphasis on carbon taxes as one of the quick fixes to environmental uncleanness in evolving states. Purpose The purpose of this research is to look into the impact of monetary and fiscal policy measures on reducing carbon emissions in the ecosystems of Nigeria. Research methodology The study employs the Autoregressive Distributed Lag (ARDL) co-integration technique or the bound co-integration technique to confirm the existence of long and short term nexus and the influence of selected financial instruments on pollutant reduction. The study spans 1991 to 2021 and relies on World Bank Development Indicators data on inflation and CO2 discharges in millions of metric tons. The statistics on tax earnings is derived from the Central Tax Authority in billions of national currency, but the figures on the state’s outlay and broad money supply are generated from the database of the Apex Bank in the country. Result According to the analysis, financial instruments are not yet being directed toward reducing air pollution and environmental devastation in the country. Further investigation reveals that tax revenue gathering is positively irrelevant, but CO2 has a strong positive effect on its reduction at lag 1, implying that a more eco-friendly financial strategy is required to combat environmental hazards in Nigeria. Novelty A Green financial system is a big issue of contention in the global public discussion about rising temperatures. Presently, there are few studies on the management of pollution using financial instruments in emerging regions. This study will serve as one of the leading investigations to align with the United Nations goal to restore our biodiversity through green fiscal and monetary policies. The study strongly suggests that the Nigerian government should pursue green fiscal and monetary mechanisms that include: issuance of green bonds; potential and cost-effective green payment plans, carbon taxation, and ecologically responsible national budgets and investment opportunities.

Fermatean fuzzy Archimedean Heronian Mean-Based Model for estimating sustainable urban transport solutions

Public transportation frameworks assume a critical role in the metropolitan region, especially in huge urban communities, where they offer a feasible answer for easing gridlock, moderating commotion contamination, and diminishing CO2 discharges. This paper presents some novel Fermatean fuzzy Heronian mean operators based on Archimedean t-norms, specifically the generalized Fermatean fuzzy Archimedean Heronian mean (GFFAHM) and the Fermatean fuzzy Archimedean geometric Heronian mean (FFAGHM). The study investigates different unique instances of these operators while exploring their essential properties. Besides, a powerful multiattribute decision-making (MADM) method is developed using the proposed operators. This approach offers a key asset for handling complex decision-making problems. Overcoming the capabilities of conventional BM operators, the GFFAHM and FFAGHM operators effectively minimize the potential redundancy in interrelationships during the decision-making process. The inclusion of the flexible parameters ρ and ϕ, which have a big impact on the decision-making process’ outcomes, increases the adaptability and resilience of the Archimedean t-based operators. To depict the feasibility of the proposed MADM method, a thorough quantitative model is introduced, outlining its useful execution. Through an exhaustive case study, the predominance of the proposed approach over existing strategies is experimentally established. Remarkably, the study uncovers that reducing fares is the most compelling factor in expanding the public transport framework, subsequently advancing sustainable urban transport. This study’s findings provide useful insights into decision-making processes and practical implications for policymakers, allowing them to make informed and impactful changes to the public transportation system. The proposed MADM method can play a vital role in upgrading the public transport framework, making way for remarkable strategy interventions in urban transport sustainability.

Energetic analysis and performance improvement algorithm of transcritical CO2 heat pump water heater system

Transcritical CO2 heat pump water heaters have been widely studied by researchers for its environmentally friendly nature and energy efficiency. To analyze the impact of various operating parameters on the heating performance of transcritical CO2 heat pump water heater systems, simulation models were developed and their accuracy was verified through experiments. Results indicated that the discharge pressure and CO2 temperature at the gas cooler outlet (Tgc,out) had a significant effect on the system performance, the coefficient of performance (COP) increased notably with higher evaporation temperatures, and the optimal discharge pressure varied depending on the evaporation temperature. The system equipped with intermediate heat exchanger demonstrated a lower optimal discharge pressure and a higher COP compared to the basic system. The inclusion of an intermediate heat exchanger in a system, the maximum COP is 2.99 % to 3.83 % higher than the basic system under the same conditions. It has been observed that the introduction of intermediate heat exchanger significantly improved the system performance when Tgc,out were 35 °C, 40 °C and 45 °C, corresponding to discharge pressures lower than 10.75 MPa, 11.167 MPa and 11.625 MPa. According to the research results, the optimal discharge pressure equation was fitted and an improved algorithm was proposed. Compared to the experimental values, the improved algorithm exhibits a maximum error of 8.81 % and 7.55 % for determining the optimal discharge pressure and temperature, and the improved algorithm is effective in engineering applications. Consequently, the simulation data holds great importance in guiding the design of transcritical CO2 heat pump water heater systems.

New progress of a 2.45 GHz ECR ion source for carbon positive ion mass spectrometry

Positive ion mass spectrometry (PIMS) is a trace element measurement technique based on positive and negative ion conversion, which is contrary to conventional accelerator mass spectrometry (AMS). To precisely measure 14C, interference of molecular isobars (such as 12CH2 and 13CH) need to be suppressed in the ion source by generating multi-charged carbon ions, such as C2+ or C3+. At present, a high-frequency (> 7 GHz) electron cyclotron resonance (ECR) ion source is commonly used to generate C2+ or C3+ ions through CO2 discharge. At Peking University (PKU), we developed a compact permanent magnet 2.45 GHz ECR ion source attempting to produce C2+ ions. In this work, systematical experiments are performed to further improve the performance of the ion source for the application in PIMS. The results show that it can deliver 1.0 emA C2+ ions with an alumina ceramic liner, and its C consumption is about 10∼20 ng/s. Meanwhile, it is also proved that a certain proportion of He and CO2 mixing can improve the production efficiency of C2+ ions, and the consumption of C can be lower. Furthermore, results confirm that this ECR ion source with alumina liner has a lower memory effect, and the influence of original CO2 discharge can be eliminated by Ar plasma cleaning for several minutes. The experimental results show that the 2.45 GHz ECR ion source has the potential to be used in the PIMS system.

Pulsed RF Excitation Inductive Discharge CO2 Laser with the Radiation Energy of 1 J and High Efficiency

Pulsed RF Excitation Inductive Discharge CO2 Laser with the Radiation Energy of 1 J and High Efficiency

Diffusion Characteristics of Airflow and CO in the Dead-End Tunnel with Different Ventilation Parameters after Tunneling Blasting.

After tunnel blasting, a large amount of CO will be produced and accumulated in the dead-end tunnel. If the ventilation discharge is not proper and the entry time into the dead-end tunnel is not appropriate, then it can cause workers to suffer from poisoning, hypoxia, and suffocation. Therefore, to understand the airflow and diffusion characteristics of CO in the dead-end tunnel after excavation and improve the working environment quality of the heading excavation tunnel, this paper uses numerical simulation and on-site verification to study the influence of different ventilation parameters on the airflow and CO diffusion characteristics in the dead-end tunnel after excavation and blasting. The research results show that the higher the air velocity of the duct, the smaller the distance between the duct and the working face, and the higher the hanging height of the duct, the easier it is for CO to be discharged from the dead-end tunnel. The larger the distance between the duct and the side wall, the more vortices there are in the dead-end tunnel and the more difficult it is to discharge CO from the tunnel. This study provides theoretical guidance for the research of the migration law of CO after tunnel blasting and has important value for ensuring a safe working environment and clean production in tunnel excavation.

Cryogenic slab RF discharge CO laser with hybrid waveguide-unstable resonators

Dependences of a cryogenic slab radio-frequency discharge CO laser output power on a distance between mirrors of a hybrid negative-branch waveguide-unstable resonator were experimentally studied. The maximum output power was observed at the resonator length longer than the one calculated by taking into account the mirrors radii of curvature. Optimization of the resonator length made it possible to get the output power increase up to 20%–25%. The results obtained can be used for designing not only slab laser systems with hybrid waveguide-unstable resonators, but also for high-power lasers with full-sized negative-branch unstable ones.

Insight of CO2 and ethanol emission from maize silage: A case study with real-time identification of aerobic and anaerobic microbial respiration using a multi-sensor-fusion method

Silage is produced worldwide for both livestock feeding and biogas production. Sustainable silage production requires characterization and mitigation of potential effects on environmental quality, particularly from greenhouse gas emissions during the production cycle. Ex-situ sampling has demonstrated that major emissions are carbon dioxide (CO2) and ethanol (EtOH). In-situ gas measurements from farm silo and bale silage are rare and may be important to improve our knowledge of the physical and biochemical causes, and constraints on these gas emissions. This study focused on tracking the kinetics of CO2 and EtOH emissions from bale maize silage, with real-time identification, quantification and separation of aerobic and anaerobic respiratory components in the period following opening of the silage. For this, an automatic multi-sensor gas-flux chamber (AMGC) was developed. Three bales (mean weight: 890 kg) of maize silage were tested (n = 3). Oxygen (O2) and temperature (Tsi) sensors were co-located at 10- and 20-cm behind the open face of the bales. Over the two weeks of the experiment we observed: (i) significant initial discharge of CO2 across the open face (1.68–2.55 mol m−2 h−1) and EtOH (0.027–0.034 mol m−2 h−1); (ii) peak CO2 emission occurred when O2 concentration (10 cm depth) was 3∼8% vol., while peak EtOH emission occurred below 2% vol. O2, (iii) dynamic conversion of O2 to CO2 from aerobic respiration; and (iv) the cumulative emission of EtOH during the anaerobic period was 4–6 times greater than that during aerobic plus semi-aerobic periods. These novel measurements provide mechanistic understanding, and may facilitate improved management of silage production to minimize environmental impact and aerobic loss of silage.

On CO2 conversion in discharges in CO2–N2 mixtures

Recent results on the efficiency of CO2 conversion in discharges in CO2–N2 mixtures are discussed. Conditions are considered when the dominating conversion mechanism is dissociation of CO2 molecules in collisions with nitrogen molecules in several electronically excited states. Its efficiency is determined by the values of dissociation yields in these collisions. Knowledge of dissociation yields for various N2 excited states is rather poor. In this paper, the effects of variation of these yields on the conversion efficiency are evaluated. Comparison of the obtained estimates with available experimental data allows ascertaining the yield values.

Removal of endocrine disruptor compounds, CO2 fixation, and macromolecules accumulation in Thermosynechococcus sp. CL-1 cultivation.

Recently, concern on several environmental issues including the pollutant discharge and high concentration of CO2 have gained high interest due to its impact on ecosystem and global warming effect, respectively. Implementation of photosynthetic microorganism carries out numerous advantages including high efficiency of CO2 fixation, the great endurance under extreme conditions and generation of valuable bioproducts. Thermosynechococcus sp. CL-1 (TCL-1), a cyanobacterium, has the ability to perform CO2 fixation and accumulation of various byproducts under extreme conditions like high temperature and alkalinity, presence of estrogen, or even using swine wastewater. This study aimed to assess TCL-1 performance under various endocrine disruptor compounds (bisphenol-A, 17-β-estradiol/E2, and 17-α-ethynilestradiol/EE2), concentrations (0-10mg/L), light intensities (500-2000 µE/m2/s), and dissolved inorganic carbon/DIC levels (0-113.2mM). Addition of E2 content even until 10mg/L carried out insignificant biomass growth interruption along with the improvement in CO2 fixation rate (79.8±0.1mg/L/h). Besides the influence of E2, application of higher DIC level and light intensity also enhanced the CO2 fixation rate and biomass growth. The highest biodegradation of E2 at 71% was achieved by TCL-1 in the end of 12h cultivation period. TCL-1 dominantly produced protein (46.7%±0.2%), however, production of lipid and carbohydrate (39.5±1.5 and 23.3±0.9%, respectively) also could be considered as the potential source for biofuel production. Thus, this study can provide an efficient strategy in simultaneously dealing with environmental issues with side advantage in production of macromolecules.

ICT's impact on CO2 emissions in GCC region: The relevance of energy use and financial development

This study looks into ICT's asymmetrical impact on emissions of carbon dioxide (CO2) controlling energy use and financial development (FD) in GCC countries. It uses panel data covering 1995–2019, employs 2nd generation unit root and Westerlund cointegration tests, and applies panel-pooled “generalized least square (GLS)” techniques. The “pooled mean group (PMG)” method and the “Dumitrescu-Hurlin (D-H)” causality test are employed to verify the robustness of GLS estimation. The bootstrap cointegration test corroborates a long-run cointegration among variables. GLS findings exhibit an asymmetric relation between ICT and CO2 emissions; both the affirmative and negative shocks of ICT and FD are associated with decreased CO2 emissions, while energy use enhances the latter. Hence, promoting ICT is essential to reduce CO2 discharges in the GCC region due to its large negative stimulus on CO2 emissions. The PMG estimation also produces findings similar to those of the GLS outcomes and verifies the GLS outcomes' robustness. The D-H causality check also validates the GLS and PMG outcomes.