This study critically reviews the recent developments and future opportunities pertinent to the conversion of CO2 as a potent greenhouse gas (GHG) to fuels and valuable products. CO2 emissions have reached an alarming level of around 410 ppm and have become the primary driver of global warming and climate change leading to devastating events such as droughts, hurricanes, torrential rains, floods, tornados and wildfires across the world. These events are responsible for thousands of deaths and have adversely affected the economic development of many countries, loss of billions of dollars, across the globe. One of the promising choices to tackle this issue is carbon sequestration by pre- and post-combustion processes and oxyfuel combustion. The captured CO2 can be converted into fuels and valuable products, including methanol, dimethyl ether (DME), and methane (CH4). The efficient use of the sequestered CO2 for the desalinization might be critical in overcoming water scarcity and energy issues in developing countries. Using the sequestered CO2 to produce algae in combination with wastewater, and producing biofuels is among the promising strategies. Many methods, like direct combustion, fermentation, transesterification, pyrolysis, anaerobic digestion (AD), and gasification, can be used for the conversion of algae into biofuel. Direct air capturing (DAC) is another productive technique for absorbing CO2 from the atmosphere and converting it into various useful energy resources like CH4. These methods can effectively tackle the issues of climate change, water security, and energy crises. However, future research is required to make these conversion methods cost-effective and commercially applicable.
Microbial electrosynthesis is a new approach to converting C1 carbon (CO2) to more complex carbon-based products. In the present study, CO2, a potential greenhouse gas, was used as a sole carbon source and reduced to value-added chemicals (acetate, ethanol) with the help of bioelectrochemical reduction in microbial electrosynthesis systems (MES). The performance of MES was studied with varying electrode materials (carbon felt, stainless steel, and cobalt electrodeposited carbon felt). The MES performance was assessed in terms of acetic acid and ethanol production with the help of gas chromatography (GC). The electrochemical characterization of the system was analyzed with chronoamperometry and cyclic voltammetry. The study revealed that the MES operated with hybrid cobalt electrodeposited carbon felt electrode yielded the highest acetic acid (4.4 g/L) concentration followed by carbon felt/stainless steel (3.7 g/L), plain carbon felt (2.2 g/L), and stainless steel (1.87 g/L). The alcohol concentration was also observed to be highest for the hybrid electrode (carbon felt/stainless steel/cobalt oxide is 0.352 g/L) as compared to the bare electrodes (carbon felt is 0.22 g/L) tested, which was found to be in correspondence with the pH changes in the system. Electrochemical analysis revealed improved electrotrophy in the hybrid electrode, as confirmed by the increased redox current for the hybrid electrode as compared to plain electrodes. Cyclic voltammetry analysis also confirmed the role of the biocatalyst developed on the electrode in CO2 sequestration.
This paper presents a fresh understanding of the vigorous connection between inward FDI, renewable energy consumption, economic growth and carbon emission in the Chinese economy employing novel Morlet wavelet analysis. Wavelet correlation, continuous wavelet transform and partial and the multiple wavelet coherence analyses are applied on variables under study for data acquired during the period 1979 to 2017. The outcome of these analyses reveals that the connections among the variables progress over frequency and time. From the frequency domain point of view, the current study discovers noteworthy wavelet coherence and robust lead and lag linkages, although time domain reveals inconsistent associations among the considered variables. The wavelet analysis according to economic point of view supports that inward foreign direct investment (FDI) and renewable energy consumption help to enhance economic condition in Chinese economy. The results also suggested that inward FDI enhances the environmental degradation in medium and long run in China. The results emphasize the significance of having organized strategies by the policymakers to cope with huge environmental degradation occurred for a couple of decades in China.
Photocatalytic conversion of carbon dioxide (CO2) into gaseous hydrocarbon fuels is an auspicious way to produce renewable fuels in addition to greenhouse gas emission mitigation. In this work, non-metals (B, O, P, and S) doped graphitic carbon nitride (g-C3N4) was prepared via solid-state polycondensation of urea for photocatalytic CO2 reduction into highly needed methane (CH4) with water under UV light irradiation. The various physicochemical characterization results reveal the successful incorporation of B, O, P, and S elements in the g-C3N4 matrix. The maximum CH4 yield of 55.10 nmol/(mLH2O.gcat) over S-doped g-C3N4 has been obtained for CO2 reduction after 7 h of irradiation. This amount of CH4 production was 1.9, 1.4, 1.7, and 2.4-folds higher than B, O, P and bare g-C3N4 samples. The doping of S did not enlarge the surface area and photon absorption ability of the g-C3N4 sample, but this significant improvement was evidently due to effective charge separation and migration. The observed results imply that the doping of non-metal elements provides improved charge separation and is an effective way to boost photocatalyst performance. This work offers an auspicious approach to design non-metal doped g-C3N4 photocatalysts for renewable fuel production and would be promising for other energy application.
Recently, supercritical fluid CO2 extraction (SFE) has emerged as a promising and pervasive technology over conventional extraction techniques for various applications, especially for bioactive compounds extraction and environmental pollutants removal. In this context, temperature and pressure regulate the solvent density and thereby effects the yield, selectivity, and biological/therapeutic properties of the extracted components. However, the nature of plant matrices primarily determines the extraction mechanism based on either density or vapor pressure. The present review aims to cover the recent research and developments of SFE technique in the extraction of bioactive plant phytochemicals with high antioxidant, antibacterial, antimalarial, and anti-inflammatory activities, influencing parameters, process conditions, the investigations for improving the yield and selectivity. In another portion of this review focuses on the ecotoxicology and toxic metal recovery applications. Nonpolar properties of Sc-CO2 create strong solvent strength via distinct intermolecular interaction forces with micro-pollutants and toxic metal complexes. This results in efficient removal of these contaminants and makes SFE technology as a superior alternative for conventional solvent-based treatment methods. Moreover, a compelling assessment on the therapeutic, functional, and solvent properties of SFE is rarely focused, and hence this review would add significant value to the SFE based research studies. Furthermore, we mention the limitations and potential of future perspectives related to SFE applications.
The effects of flow rate, different pressures and temperatures on cocoa butter extracted from cocoa nib using supercritical carbon dioxide (scCO2) were investigated. The yield was analyzed for total fat content, triacylglycerol (TG) profile, and fatty acid (FA) profile. Extractions were carried out at pressures of 20 and 35 MPa, temperatures of 50 and 60 °C, and CO2 flow rates of 0.5, 1, 2, 4 mL min(-1). The result shows that the yield of cocoa butter extract increased with increasing pressure, temperature, and flow rate and the optimum conditions for the maximum cocoa butter extraction were 35 MPa, 60 °C and 2 mL min(-1), repectively. TGs and FAs were found to be similar in composition to those of cocoa butter obtained by conventional methods. The lower molecular weight TGs and FAs showed higher selectivity compared to higher molecular weight TGs and FAs.
Polysulfone (PSF) based mixed matrix membranes (MMMs) are one of the most broadly studied polymeric materials used for CO2/CH4 separation. The performance of existing PSF membranes encounters a bottleneck for widespread expansion in industrial applications due to the trade-off amongst permeability and selectivity. Membrane performance has been postulated to be enhanced via functionalization of filler at different weight percentages. Nonetheless, the preparation of functionalized MMMs without defects and its empirical study that exhibits improved CO2/CH4 separation performance is challenging at an experimental scale that needs prior knowledge of the compatibility between the filler and polymer. Molecular simulation approaches can be used to explore the effect of functionalization on MMM's gas transport properties at an atomic level without the challenges in the experimental study, however, they have received less scrutiny to date. In addition, most of the research has focused on pure gas studies while mixed gas transport properties that reflect real separation in functionalized silica/PSF MMMs are scarcely available. In this work, a molecular simulation computational framework has been developed to investigate the structural, physical properties and gas transport behavior of amine-functionalized silica/PSF-based MMMs. The effect of varying weight percentages (i.e., 15-30 wt.%) of amine-functionalized silica and gas concentrations (i.e., 30% CH4/CO2, 50% CH4/CO2, and 70% CH4/CO2) on physical and gas transport characteristics in amine-functionalized silica/PSF MMMs at 308.15 K and 1 atm has been investigated. Functionalization of silica nanoparticles was found to increase the diffusion and solubility coefficients, leading to an increase in the percentage enhancement of permeability and selectivity for amine-functionalized silica/PSF MMM by 566% and 56%, respectively, compared to silica/PSF-based MMMs at optimal weight percentage of 20 wt.%. The model's permeability differed by 7.1% under mixed gas conditions. The findings of this study could help to improve real CO2/CH4 separation in the future design and concept of functionalized MMMs using molecular simulation and empirical modeling strategies.
This study was set up to model and optimize the performance and emission characteristics of a diesel engine fueled with carbon nanoparticle-dosed water/diesel emulsion fuel using a combination of soft computing techniques. Adaptive neuro-fuzzy inference system tuned by particle swarm algorithm was used for modeling the performance and emission parameters of the engine, while optimization of the engine operating parameters and the fuel composition was conducted via multiple-objective particle swarm algorithm. The model input variables were: injection timing (35-41° CA BTDC), engine load (0-100%), nanoparticle dosage (0-150 μM), and water content (0-3 wt%). The model output variables included: brake specific fuel consumption, brake thermal efficiency, as well as carbon monoxide, carbon dioxide, nitrogen oxides, and unburned hydrocarbons emission concentrations. The training and testing of the modeling system were performed on the basis of 60 data patterns obtained from the experimental trials. The effects of input variables on the performance and emission characteristics of the engine were thoroughly analyzed and comprehensively discussed as well. According to the experimental results, injection timing and engine load could significantly affect all the investigated performance and emission parameters. Water and nanoparticle addition to diesel could markedly affect some performance and emission parameters. The modeling system could predict the output parameters with an R2 > 0.93, MSE carbon dioxide, carbon monoxide, nitrogen oxides, and unburned hydrocarbon emission concentrations were found to be 7.26 vol%, 0.46 vol%, 95.7 ppm, and 36.2 ppm, respectively, under the selected optimal operating conditions while the quantity of brake thermal efficiency was found at an acceptable level (34.0%). In general, the applied soft computing combination appears to be a promising approach to model and optimize operating parameters and fuel composition of diesel engines.
The conventional isolation of cellulose nanofibers (CNFs) process involves high energy input which leads to compromising the pulp fiber's physical and chemical properties, in addition to the issue of elemental chlorine-based bleaching, which is associated with serious environmental issues. This study investigates the characteristic functional properties of CNFs extracted via total chlorine-free (TCF) bleached kenaf fiber followed by an eco-friendly supercritical carbon dioxide (SC-CO2) treatment process. The Fourier transmission infra-red FTIR spectra result gave remarkable effective delignification of the kenaf fiber as the treatment progressed. TEM images showed that the extracted CNFs have a diameter in the range of 10-15 nm and length of up to several micrometers, and thereby proved that the supercritical carbon dioxide pretreatment followed by mild acid hydrolysis is an efficient technique to extract CNFs from the plant biomass. XRD analysis revealed that crystallinity of the fiber was enhanced after each treatment and the obtained crystallinity index of the raw fiber, alkali treated fiber, bleached fiber, and cellulose nanofiber were 33.2%, 54.6%, 88.4%, and 92.8% respectively. SEM images showed that amorphous portions like hemicellulose and lignin were removed completely after the alkali and bleaching treatment, respectively. Moreover, we fabricated a series of cellulose nanopapers using the extracted CNFs suspension via a simple vacuum filtration technique. The fabricated cellulose nanopaper exhibited a good tensile strength of 75.7 MPa at 2.45% strain.
This study examines the impact of economic growth, corruption, health, and poverty on environmental degradation for three countries from ASEAN, namely Indonesia, Malaysia, and Thailand using annual data over the period of 1994-2014. The relationship between environmental degradation (pollution) by carbon dioxide (CO2) emissions and economic growth is examined along with some other variables, namely health expenditure, poverty, agriculture value added growth, industrial value added growth, and corruption. The ordinary least squares (OLS) method is applied as an analytical technique for parameter estimation. The empirical results reveal that almost all variables are statistically significant at the 5% level of significance, whereby test rejects the null hypotheses of non-cointegration, indicating that all variables play an important role in affecting the environment across countries. Empirical results also indicate that economic growth has significant positive impact, while health expenditures show significantly negative impact on the environment. Corruption has significant positive effect on environment in the case of Malaysia; while in the case of Indonesia and Thailand, it has insignificant results. However, for the individual analysis across countries, the regression estimate suggests that economic growth has a significant positive relationship with environment for Indonesia, while it is found insignificantly negative and positive in the case of Malaysia and Thailand, respectively, during the period under the study. Empirical findings of the study suggest that policy-makers require to make technological-friendly environment sequentially to surmount unregulated pollution, steady population transfers from rural areas to urban areas are also important, and poverty alleviation and better health provision can also help to improve the environment.
The main purpose of this work is to analyze the impact of environmental degradation proxied by CO2 emissions per capita along with some other explanatory variables namely energy use, trade, and human capital on economic growth in selected higher CO2 emissions economies namely China, the USA, India, and Japan. For empirical analysis, annual data over the period spanning between 1971 and 2013 are used. After using relevant and suitable tests for checking data properties, the panel fully modified ordinary least squares (FMOLS) method is employed as an analytical technique for parameter estimation. The panel group FMOLS results reveal that almost all variables are statistically significant, whereby test rejects the null hypotheses of non cointegration, demonstrating that all variables play an important role in affecting the economic growth role across countries. Where two regressors namely CO2 emissions and energy use show significantly negative impacts on economic growth, for trade and human capital, they tend to show the significantly positive impact on economic growth. However, for the individual analysis across countries, the panel estimate suggests that CO2 emissions have a significant positive relationship with economic growth for China, Japan, and the USA, while it is found significantly negative in case of India. The empirical findings of the study suggest that appropriate and prudent policies are required in order to control pollution emerging from areas other than liquefied fuel consumption. The ultimate impact of shrinking pollution will help in supporting sustainable economic growth and maturation as well as largely improve society welfare.
This study examines the impact of energy consumption, urbanization, and globalization on environmental degradation proxied by carbon emissions (CO2) in the South Asian Association for Regional Cooperation (SAARC) countries, namely Sri Lanka, Pakistan, Maldives, Nepal, Bhutan, Bangladesh, and India using data over the period 1990-2018. The cross-sectional autoregressive distributed lag (CS-ARDL), pooled mean group (PMG), and Dumitrescu and Hurlin (D-H) Granger causality techniques are employed for the empirical analysis. First and second-generation panel unit root tests are used to determine the stationary level of all data series which reveals mixed order of integration. The empirical findings show that urbanization, gross domestic product (GDP) per capita income, energy consumption, industrial growth, globalization, and financial development cause CO2 emissions, while the other variables, namely arable land and innovation, put negative effects on CO2 emissions. Moreover, the D-H heterogeneous test results exhibit that bi-directional relationship exists between CO2 and arable land, urbanization, industrial growth, and financial development, while a unidirectional causality exists between CO2 emissions and GDP per head income. These findings suggest that planned urbanization, investment in renewable energy sources, and effective strategies regarding the economic and financial integration with the global economies are required for a clean and green environment.
BRICS are among the rising nations which drive economic growth by excessive utilization of resources and resulting in environment degradation. Although there is bulk of research on environmental Kuznets curve (EKC), very limited studies explored the scope in context of tourism in BRICS countries. So this research is conducted to explore the association of tourism, renewable energy, and economic growth with carbon emissions by using annual data of BRICS countries from the year 1995 to 2018. By using the recent approach of method of moments quantile regression (MMQR), the finding shows that tourism has stronger significant negative effects from 10th to 40th quantile while the effects are insignificant at remaining quantiles. Furthermore, an inverted U-shape EKC curve is also apparent at all quantiles excluding 10th and 20th quantiles. For renewable energy, the results are found negatively significant across all quantiles (10th-90th) which claim that CO2 emission can be reduced by opting renewable sources. Hence, the empirical results of the current study provide insights for policymakers to consume renewable energy sources for the sustainable economic growth and solution of environmental problems.
This paper assesses the Environmental Kuznets curve based on quantile behavior of the relationship between economic growth, forest area, agriculture production, renewable energy, and environmental degradation. The current literature generally used a single indicator to address environmental issues; however single indicator neither measures overall environmental conditions nor does specify that the environment issue is generally diminishing. Our study is the first one that used ecological footprint (EF) as an indicator to test environmental Kuznets curve (EKC) hypothesis for Pakistan by employing recent approach of quantile autoregressive distributed lag (QARDL) initiated by Cho et al. (J Econ 188(1):281-300, 2015). The result of this study validates the EKC hypothesis for Pakistan and shows quantile-dependent relationship, and in that case, using the conventional methods may somewhat lead to biased results. Moreover, the rejection of the null hypothesis of parameter constancy is also confirmed by Wald test. In the long run, the findings of renewable energy consumption and forest area show significant negative effects on ecological footprints, which indicates that by increasing renewable energy usage and forest area, ecological footprints can be minimized. Interestingly, the short-term effects of agricultural production findings on EF show statistically negative results. This illustrates that EF can also be reduced in the agriculture sector by adopting environment-friendly technologies. In order to create efficient policies for environment deterioration, the empirical findings of the current analysis can be used as a guideline for policy implications.
We employ the new Method of Moments Quantile Regression approach to expose the role of natural resources, renewable energy, and globalization in testing Environment Kuznets Curve (EKC) in MINT panel covering the years 1995-2018. The outcome validates the EKC curve between economic progress and carbon emissions from the third quantile to the extreme highest quantile. The result also shows that natural resources increase CO2 emissions at the lowest quantile and then turn insignificant from the middle to the highest quantiles due to the potential utilization of resources in a sustainable manner. The renewable energy mitigates CO2 emissions at the lower half quantiles. Still, for upper quantiles, the results are unexpected and imply that the countries' total energy mix depends heavily on fossil fuels. As far as globalization is concerned, the significant results from medium to upper quantiles reveal that as globalization heightens due to foreign direct investment or trade, energy consumption also expands, leading to the worst environment quality. Thus, the present study's consequences deliver guidelines for policymakers to utilize natural resources sustainably and opt technologies based on clean energy, which may offset environmental degeneration.
Carbon capture and storage (CCS) involves capturing, transporting and storing CO2 geologically underground permanently. Carbon capture using solvent such as amine and aqueous ammonia has been extensively studied by many researchers. However, this capture technology for CCS scheme is costly. As an alternative, CO2 emission can be cost-effectively captured and stored by utilizing the well-understood natural photosynthetic process of marine cyanobacteria. In contrast, the capturing process using cyanobacteria is very slow compared to the chemical absorption mentioned prior. Hence, this study aimed to investigate carbon capturing and storing process using integrated aqueous ammonia and mutated marine cyanobacteria (Synechococcus PCC 7002 IIUM01). The conditions that can maximize CO2 reduction under various conditions; CO2 flow rate (Lpm), absorption temperature (C) and aqueous ammonia concentrations (% (w/v)) were to be identified. The effectiveness of the mutant cyanobacteria was quantified by measuring the cell concentration, percentage reduction in CO2 concentration and lipid content. Synechococcus PCC 7002 IIUM01 showed it robustness by growing in aqueous ammonia solution at the concentration of 0.5 to 1% (w/v) at which the parent strain was not able to tolerate. The best conditions in maximizing CO2 capture and storage while sustaining growth optimally and being a potential biofuel source was observed at 0.5 Lpm of 15% CO2 gas flow rate, 0.75% (w/v) of ammonia concentration and 33C of absorption temperature. At this specified condition, around 68% of CO2 removal was achieved with 9% (w/w) yield of lipid and more than 13% (w/v) of cell concentration obtained.
In this study, a sustainable NH2-MIL-101(Al) is synthesized and subjected to characterization for cryogenic CO2 adsorption, isotherms, and thermodynamic study. The morphology revealed a highly porous surface. The XRD showed that NH2-MIL-101(Al) was crystalline. The NH2-MIL-101(Al) decomposes at a temperature (>500 °C) indicating excellent thermal stability. The BET investigation revealed the specific surface area of 2530 m2/g and the pore volume of 1.32 cm3/g. The CO2 adsorption capacity was found to be 9.55 wt% to 2.31 wt% within the investigated temperature range. The isotherms revealed the availability of adsorption sites with favorable adsorption at lower temperatures indicating the thermodynamically controlled process. The thermodynamics showed that the process is non-spontaneous, endothermic, with fewer disorders, chemisorption. Finally, the breakthrough time of NH2-MIL-101(Al) is 31.25% more than spherical glass beads. The CO2 captured by the particles was 2.29 kg m-3. The CO2 capture using glass packing was 121% less than NH2-MIL-101(Al) under similar conditions of temperature and pressure.
The aim of this study was to optimize the antioxidant activity of Piper nigrum L. essential oil extracted using the supercritical carbon dioxide (SC-CO₂) technique. Response surface methodology was applied using a three-factor central composite design to evaluate the effects of three independent extraction variables: pressure of 15-30 MPa, temperature of 40-50 °C and dynamic extraction time of 40-80 min. The DPPH radical scavenging method was used to evaluate the antioxidant activity of the extracts. The results showed that the best antioxidant activity was achieved at 30 MPa, 40 °C and 40 min. The extracts were analyzed by GC-FID and GC-MS. The main components extracted using SC-CO₂ extraction in optimum conditions were β-caryophyllene (25.38 ± 0.62%), limonene (15.64 ± 0.15%), sabinene (13.63 ± 0.21%), 3-carene (9.34 ± 0.04%), β-pinene (7.27 ± 0.05%), and α-pinene (4.25 ± 0.06%). The essential oil obtained through this technique was compared with the essential oil obtained using hydro-distillation. For the essential oil obtained by hydro-distillation, the most abundant compounds were β-caryophyllene (18.64 ± 0.84%), limonene (14.95 ± 0.13%), sabinene (13.19 ± 0.17%), 3-carene (8.56 ± 0.11%), β-pinene (9.71 ± 0.12%), and α-pinene (7.96 ± 0.14%). Radical scavenging activity of the extracts obtained by SC-CO₂ and hydro-distillation showed an EC₅₀ of 103.28 and 316.27 µg mL(-1) respectively.
Epiglottic cyst is usually asymptomatic and the commonest presentation is foreign body sensation in the throat. Treatment of epiglottic cysts depends on their size and on the clinical symptoms. Surgery is necessary for large ones. Various modalities of therapy include endoscopic excision, marsupialization and deroofing with or without a carbon dioxide laser. We report our experience of managing a case of a large epiglottic cyst with a carbon dioxide laser.
The well-established emissions-growth debate relies on the symmetric nexus between CO2 emissions and economic growth, thereby ignoring a fundamental component of macro economy in the form of asymmetric relation. This paper considers how CO2 emissions respond asymmetrically to changes in economic growth. While utilizing both linear and nonlinear time series approaches for an environmentally exposed country, Pakistan over the period 1971-2018, we find convincing evidence that CO2 emissions rise more rapidly during negative shocks to economic growth than increase during economic expansions. Thus, contrary to what has previously been reported, the effect is strong as holds both at short run and long run. This is partly due to the increase in informal sector as GDP declines. Our estimated results show that accounting for the shadow economy results a higher magnitude of CO2 emissions due to decrease in economic growth, thus question the traditional symmetric decoupling of economic growth and CO2 emissions. The estimated results are robust to alternative estimators such as fully modified least squares (FMOLS) and dynamic OLS (DOLS). Thus, the findings of this study call for a re-thinking on climate policy design that rarely pays attention to the aforementioned outcomes due to fall in economic growth.