Averrhoa carambola is a species of tree native to tropical Southeast Asia. It possesses antioxidant and anti-hyperlipidemia effects and has traditionally been used to treat a variety of ailments. However, the presence of oxalic acid in its fruits might restrict its consumption by individuals suffering from kidney disease, and caramboxin can cause neurotoxicity. In this study, we evaluated the acute and sub-chronic toxicity of the methanolic extract of A. carambola leaves (MEAC) in male and female rats. In the acute study, female rats were given a single oral dose of 5000 mg/kg of MEAC and closely examined for distinct indications of toxic effects during the first 4 h, periodically for 48 h, and daily thereafter for 14 days. Rats of both sexes were employed in the sub-chronic investigation for the 28-day repeated dose oral toxicity study. Results of the acute study revealed the safety of MEAC up to a dose of 5000 mg/kg where the rats did not show changes or signs of toxicity. In the sub-chronic toxicity study, MEAC (250, 500, and 1000 mg/kg) administration did not affect the body weight, food, and water consumption, motor coordination, behavior, or mental alertness in the treated rats. In addition, no variations in hematological or biochemical markers were found in MEAC-treated rats. In conclusion, these findings pinpoint the safety of MEAC at doses up to 5000 mg/kg. The leaves of A. carambola could be safely consumed by people with kidney disease to treat other ailments.
Global warming is pressuring policymakers to change climate policies in shifting the global economy onto a net-zero pathway. While financial assets are responsive to policy changes and development, climate change policies are becoming increasingly unpredictable, making policy decision less certain. This study investigates connectedness and spillover effects of US climate policy uncertainty on energy stocks, alternative energy stocks, and carbon emissions futures. We analyzed spillover and connectedness before and after the Paris Agreement. We employed monthly frequency data from August 2005 to March 2021 and applied DY (2012) method and MGARCH approach. We found that world energy stocks and carbon emissions futures are connected to US climate policy uncertainty. Uncertainty in climate policy and world energy stocks act as information transmitters in return spillover, while global alternative energy and carbon market are shock receivers. On volatility spillover, climate policy uncertainty, energy stocks, and carbon emissions future are shocks transmitters, while alternative energy stocks are receivers. We observe increase in connectedness following the Paris Agreement suggesting strengthened global efforts in tackling climate change. DCC and ADCC estimations revealed spillover effects of climate policy on futures returns and volatilities of world energy stocks and carbon emissions futures and the shocks could be transmitted through to the energy sector. During period of uncertainty in US climate policy, carbon allowances can potentially serve as a safe haven for energy stocks and provide downside protection for alternative energy stocks, hence hedging against climate transition risks.
Dispersants are approved for use in many countries (UK, South Korea, Australia, Egypt, France, Greece, Indonesia, Italy, Japan, Malaysia, Norway, Singapore, Spain, Thailand, and several coastal African, South American, and Middle Eastern countries). Here, the protocols of the most advanced (France, Norway, UK, Spain, Greece, Italy, USA, and Australia) are compared for identifying possible harmonization of approval procedures. Pre-toxicity testing, recognized oil datasets, common thresholds, standardized protocols, zoning, and monitoring are some of the aspects that can be discussed between countries.
The treatment of single and binary azo dyes, as well as the effect of the circuit connection, aeration, and plant on the performance of UFCW-MFC, were explored in this study. The decolorization efficiency of Remazol Yellow FG (RY) (single dye: 98.2 %; binary dye: 92.3 %) was higher than Reactive Black 5 (RB5) (single: 92.3 %; binary: 86.7 %), which could be due to monoazo dye (RY) requiring fewer electrons to break the azo bond compared to the diazo dye (RB5). In contrast, the higher decolorization rate of RB5 in binary dye indicated the removal rate was affected by the electron-withdrawing groups in the dye structure. The closed circuit enhanced about 2% of color and 4% of COD removal. Aeration improved the COD removal by 6%, which could be contributed by the mineralization of intermediates. The toxicity of azo dyes was reduced by 11-26% and the degradation pathways were proposed. The dye removal by the plants was increased with a higher contact time. RB5 was more favorable to be uptook by the plant as RB5 holds a higher partial positive charge. 127.39 (RY), 125.82 (RB5), and 58.66 mW/m3 (binary) of maximum power density were generated. The lower power production in treating the binary dye could be due to more electrons being utilized for the degradation of higher dye concentration. Overall, the UFCW-MFC operated in a closed circuit, aerated, and planted conditions achieved the optimum performance in treating binary azo dyes containing wastewater (dye: 87-92%; COD: 91%) compared to the other conditions (dye: 83-92%; COD: 78-87%).
Sand production remains a huge obstacle in many oil and gas fields around the world, but the hazards of contaminants riding on the produced sand are often not emphasised. Improper disposal of the sand could see the toxic leaching into the environment including the food chain, endangering all living organisms. The impending sand production from an oilfield offshore Sabah also suffers from the lack of hazards identification; hence, this study was conducted to assess the contaminant on the produced sand. Sand samples were collected from multiple wells in the area, with the contaminants extracted using n-hexane and subjected to chemical and thermal analyses. FTIR and GC-MS detected traces of harmful pollutants like naphthalene, amine substances, cyclohexanol, and short-chain alkanes. It was discovered that the volatile fraction of the contaminants was able to evaporate at 33 °C, while high energy was needed to remove 100% of the contaminants from the sand. Overall, the produced sand from the oilfield was unsafe and required treatment before it could be dumped or used.
The ecological footprint has currently become a highly popular environmental performance indicator. It provides the basis for setting goals, identifying options for action, and tracking progress toward stated goals. Because the examination of the existence of convergence is important for the climate change protection of the earth, the convergence of ecological footprint and its subcomponents are a major concern for scholars and policymakers. To this end, this study aims to investigate the stochastic convergence of ecological footprint and its subcomponents. We employ the recently developed Hepsag (2021) unit root test that allows nonlinearity and smooth structural change simultaneously to study stochastic convergence in per-capita ecological footprint over the period 1961-2018 for the most polluting countries. The results provide mixed evidence of the presence of stochastic convergence in conventional unit root tests such as ADF, KPSS and Fourier KPSS. According to the Hepsag (2021) unit root test results for all countries, built-up land footprint converges except Australia, Malaysia, Poland, and Turkey. Carbon footprint converges for Indonesia, Malaysia, Mexico, South Africa, Thailand, Turkey, the UK, and the USA. Cropland footprint converges for Australia, Canada, China, France, Indonesia, Italy, Japan, Korea, Malaysia, Mexico, Poland, South Africa, the UK, and Vietnam. Fishing grounds footprint converges in Brazil, France, Germany, Indonesia, Italy, Mexico, South Africa, and Vietnam. Forest product footprint converges in Australia, Canada, France, Germany, India, Korea, Mexico, Poland, Turkey, and Vietnam. Grazing land footprint converges in Canada, France, India, Indonesia, Japan, Korea, Poland, South Africa, Thailand, and Vietnam. And lastly, the total ecological footprint converges in Canada, France, Korea, Malaysia, Mexico, South Africa, the UK, and the USA.
The present study aims to identify the impact of corporate social responsibility on patients' intention to revisit the healthcare industry. Furthermore, mediating the role of patient satisfaction and patient loyalty along with serial mediation through corporate social responsibility = > patient satisfaction = > patient loyalty = > intention to revisit was also tested. The present study is quantitative in nature, while the data for the study was collected using purposive sampling from 321 patients working in eight hospitals in Rawalpindi and Islamabad, Pakistan. For the data analysis, statistical package for the social sciences (SPSS) and structural equation modeling through the partial least square approach (smart-PLS v 3.3.9) were employed. The study results show that corporate social responsibility forms a significantly positive relationship with patient satisfaction, patient loyalty, and patient intention to revisit. Study findings confirmed the mediating role of patient satisfaction and patient loyalty. Furthermore, serial mediation through patient satisfaction and patient loyalty was also confirmed. In the current competitive environment, understanding the direct and indirect effects of CSR activities on patient satisfaction, patient loyalty, and intentions to revisit is of the utmost importance for hospitals. These activities provide hospitals with the opportunity to take certain actions to improve patient satisfaction, and these actions increase their loyalty, which in turn encourages their intention to revisit.
ICTs (information and communication technologies) have emerged as a potent new force. Digitalization, modernization, and automation of the manufacturing process are expected to facilitate ICT adoption, resulting in increased genuine environmental concerns. This research aims to examine the impact of ICTs on environmental quality and the relationship between ICTs, environmental quality, and economic growth. Dynamic panel threshold regression was employed, and the sample countries comprised 69 developing countries from 2010 to 2019. The threshold technique will identify the precise threshold value of ICTs and highlights the impacts of ICTs on the environmental quality nexus when above and below the threshold value in developing countries. Empirical evidence suggests that ICTs positively impact environmental quality (CO2) when above the ICTs threshold value. However, ICTs provide a positive but insignificant impact on environmental quality when below the ICTs threshold value of 4.699. Additionally, ICTs affect the economic growth and environmental quality nexus, with increasing economic growth resulting in a decrease in CO2 emissions in developing countries when ICTs are below the threshold value. Thus, the ICTs threshold value should be used to ensure that ICTs adoption promotes sustainable economic growth and resolves environmental degradation issues in developing nations.
Various empirical studies have examined the nexus between financial markets, but this study focused on the comovement among prominent markets. Our study examines the interrelationship among main financial markets, i.e., stock, oil, and commodity during the recent pandemic. The interconnections among the selected markets are investigated using a battery of wavelet coherence tools and the Granger causality test. From the wavelet coherence analysis, our findings indicate strong co-movements among the VIX, oil volatility, and commodity prices during pandemic and localized in all scales and over the sample period. The dependency strength among the considered economies is noted to increase in pandemic, which implies increased short- and long-term benefits for the investors. Moreover, Our result exhibits a feedback causality between OVIX and crude oil, VIX and S&P 500, and gasoline and VIX. Interestingly, a unidirectional causality exists between VIX and crude oil, S&P 500 and crude oil, Brent and crude oil, gasoline, crude oil, and VIX and OVIX. We advocate that the findings will be helpful for portfolio managers, investors, and officials around the world.
There is strong scientific evidence to suggest that carbon dioxide (CO2) emissions are one of the key drivers of global warming. Rising CO2 emissions across the globe have been traced back to increasing global trade and rapid industrial development powered by fossil fuels. High CO2 emissions have had an adverse effect on the quality of life and economic growth of communities across the globe. In this study, the Granger causality approach is used to examine scientifically some causal relationships between energy consumption, CO2 emissions, economic growth, and key macroeconomic variables (trade openness and foreign direct investment) in the panel of Financial Action Task Force (FATF) countries. FATF countries are signatories to agreements to adhere to good financial practices to ensure sustainable development of their economies. The empirical analysis was conducted for the period 1980 to 2020. Results indicate a strong endogenous relationship between the variables in the short and long run. The analysis suggests that careful co-curation of economic, trade, energy, foreign direct investment, and environmental management policies is needed to ensure sustainable economic development in the FATF countries. Global trade and foreign direct investment policies must foster new environmental-friendly industries and greater use of clean renewable energy among these countries. Note: Arrows indicate direction of possible causal links between the variables.
There are many advantages of geothermal energy as an environmentally friendly resource; however, there are quite a several challenges that need to be overcome to completely harness sustainable and renewable energy that is also natural. The primary aim of this study is to examine what influence geothermal energy will have on land use changes among the considered 27 states in the European Union from the time being 1990 to 2021. The study adopts the auto-regressive distributed lag (ARDL); the findings show that geothermal energy growth could be leveraged to achieve remarkable growth in land use change among the 13 European developing economies than among the 14 EU developed economies. On the other hand, results from analysis further show that a remarkable decrease in land use change could be better attained among the 14 EU developed economies that among the 13 EU developing economies as a result of institutional quality. Furthermore, the result suggests that through economic growth, there could be a remarkable increase in land use change among the 14 EU developed economies than among the 13 EU developing economies. It was further revealed by the study that the level of land use change among the 27 EU nations could be remarkably increased, boosting the level of geothermal energy production that will assist in attaining the aims behind the 2030 energy union. This will eventually help in curbing the incidence of climate change and pollution in the environment; the projected calculations are observed to be valid, as confirmed through the chosen three estimators for this research. The chosen estimators are the pooled mean group, mean group, and dynamic fixed effect. The regulations and governors in 27 European Union countries should give priority to using geothermal in their renewable energy mix to reduce the incidence of changes in land structures. Also, an increased level of efficiency and effectiveness should be made to the generation of geothermal energy by state actors and investors to prompt sustainability and attainability with no further depreciation in agricultural and forest natural states.
In the present work, we prepared MgO-La2O3-mixed-metal oxides (MMO) as efficient photocatalysts for degradation of organic pollutants. First, a series of MgAl-%La-CO3-layered double hydroxide (LDH) precursors with different contents of La (5, 10, and 20 wt%) were synthesized by the co-precipitation process and then calcined at 600 °C. The prepared materials were characterized by XRD, SEM-EDX, FTIR, TGA, ICP, and UV-vis diffuse reflectance spectroscopy. XRD indicated that MgO, La2O3, and MgAl2O4 phases were found to coexist in the calcined materials. Also, XRD confirms the orthorhombic-tetragonal phases of MgO-La2O3. The samples exhibited a small band gap of 3.0-3.22 eV based on DRS. The photocatalytic activity of the catalysts was assessed for the degradation of two dyes, namely, tartrazine (TZ) and patent blue (PB) as model organic pollutants in aqueous mediums under UV-visible light. Detailed photocatalytic tests that focused on the impacts of dopant amount of La, catalyst dose, initial pH of the solution, irradiation time, dye concentration, and reuse were carried out and discussed in this research. The experimental findings reveal that the highest photocatalytic activity was achieved with the MgO-La2O3-10% MMO with photocatalysts with a degradation efficiency of 97.4% and 93.87% for TZ and PB, respectively, within 150 min of irradiation. The addition of La to the sample was responsible for its highest photocatalytic activity. Response surface methodology (RSM) and gradient boosting regressor (GBR), as artificial intelligence techniques, were employed to assess individual and interactive influences of initial dye concentration, catalyst dose, initial pH, and irradiation time on the degradation performance. The GBR technique predicts the degradation efficiency results with R2 = 0.98 for both TZ and PB. Moreover, ANOVA analysis employing CCD-RSM reveals a high agreement between the quadratic model predictions and the experimental results for TZ and PB (R2 = 0.9327 and Adj-R2 = 0.8699, R2 = 0.9574 and Adj-R2 = 0.8704, respectively). Optimization outcomes indicated that maximum degradation efficiency was attained under the following optimum conditions: catalyst dose 0.3 g/L, initial dye concentration 20 mg/L, pH 4, and reaction time 150 min. On the whole, this study confirms that the proposed artificial intelligence (AI) techniques constituted reliable and robust computer techniques for monitoring and modeling the photodegradation of organic pollutants from aqueous mediums by MgO-La2O3-MMO heterostructure catalysts.
The embodied carbon of building materials and the energy consumed during construction have a significant impact on the environmental credentials of buildings. The structural systems of a building present opportunities to reduce environmental emissions and energy. In this regard, mass timber materials have considerable potential as sustainable materials over other alternatives such as steel and concrete. The aim of this investigation was to compare the environment impact, energy consumption, and life cycle cost (LCC) of different wood-based materials in identical single-story residential buildings. The materials compared are laminated veneer lumber (LVL) and glued laminated timber (GLT). GLT has less global warming potential (GWP), ozone layer depletion (OLD), and land use (LU), respectively, by 29%, 37%, and 35% than LVL. Conversely, LVL generally has lower terrestrial acidification potential (TAP), human toxicity potential (HTP), and fossil depletion potential (FDP), respectively, by 30%, 17%, and 27%. The comparative outcomes revealed that using LVL reduces embodied energy by 41%. To identify which of these materials is the best alternative, various environmental categories, embodied energy, and cost criteria require further analysis. Therefore, the multi-criteria decision-making (MCDM) method has been applied to enable robust decision-making. The outcome showed that LVL manufacturing using softwood presents the most sustainable choice. These research findings contribute to the body of knowledge about the use of mass timber in construction.
Social media is playing a vital role in the promotion of green products by reshaping the millennial green purchasing intention and green consumption behaviors, resulting in progressive growth toward sustainable environment and lower carbon emission. Non-organic consumption among humans has increased the carbon emission in contrary risked environment; therefore, consumption behavior and purchasing intention are required to change for better sustainable environment. This study's goal is to determine the effects of social media in molding the consumption behaviors while considering eco-labeling, eco-branding, social norms, and purchase intensions among millennials to promote green consumption and lower carbon emission. It was decided to use a cross-sectional questionnaire survey to get information from the students of different faculties including social sciences, engineering, and bio-sciences. SPSS.V.22 and Smart-PLS were used to analyzed the data. Results indicated that social media has a profoundly good impact on molding and impacting youth behaviors regarding the green consumption, resulting in increasing intention toward sustainable environment which results in lower carbon emission. The results are in line with the predictions and contextual analysis, as the whole world is coming back toward natural life and is working for environmental protection and sustainability specially to lower the carbon emission. Therefore, students are molding themselves toward green consumption. The study recommends that future research may be conducted to study more contextual variables, who has influence on the green consumption among the general public regarding green consumptions and lowering carbon emission and stepping toward the sustainable environment.
The human coronavirus disease (COVID-19) pandemic is caused by a novel coronavirus; the Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV-2). Natural products, secondary metabolites show positive leads with antiviral and immunotherapy treatments using genomic studies in silico docking. In addition, it includes the action of a mechanism targeting the SARS-CoV-2. In this literature, we aimed to evaluate the antiviral movement of the NT-VRL-1 unique terpene definition to Human coronavirus (HCoV-229E). The effects of 19 hydrolysable tannins on the SARS-CoV-2 were therefore theoretically reviewed and analyzed utilising the molecular operating surroundings for their C-Like protease 3CLpro catalytic dyad residues Angiotensin converting enzyme-2 (MOE 09). Pedunculagin, tercatan, and castalin were detected as interacting strongly with SARS-receptor Cov-2's binding site and catalytic dyad (Cys145 and His41). SARS-CoV-2 methods of subunit S1 (ACE2) inhibit the interaction of the receiver with the s-protein once a drug molecule is coupled to the s-protein and prevent it from infecting the target cells in alkaloids. Our review strongly demonstrates the evidence that natural compounds and their derivatives can be used against the human coronavirus and serves as an area of research for future perspective.
In this study, luminescent bio-adsorbent nitrogen-doped carbon dots (N-CDs) was produced and applied for the removal and detection of Hg (II) from aqueous media. N-CDs were synthesized from oil palm empty fruit bunch carboxymethylcellulose (CMC) and urea. According to several analytical techniques used, the obtained N-CDs display graphitic core with an average size of 4.2 nm, are enriched with active sites, stable over a wide range of pH and have great resistance to photobleaching. The N-CDs have bright blue emission with an improved quantum yield (QY) of up to 35.5%. The effect of the variables including pH, adsorbent mass, initial concentration and incubation time on the removal of Hg (II) was investigated using central composite design. The statistical results confirmed that the adsorption process could reach equilibrium within 30 min. The reduced cubic model (R2 = 0.9989) revealed a good correlation between the observed values and predicted data. The optimal variables were pH of 7, dose of 0.1 g, initial concentration of 100 mg/L and duration of 30 min. Under these conditions, adsorption efficiency of 84.6% was obtained. The adsorption kinetic data could be well expressed by pseudo-second-order kinetic and Langmuir isotherm models. The optimal adsorption capacity was 116.3 mg g-1. Furthermore, the adsorbent has a good selectivity towards Hg (II) with a detection limit of 0.01 μM due to the special interaction between Hg (II) and carboxyl/amino groups on the edge of N-CDs. This work provided an alternative direction for constructing low-cost adsorbents with effective sorption and sensing of Hg (II).
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.
Several studies have highlighted the significant impact of climate change on agriculture. However, there have been little empirical enquiries into the impact of climate change on marine fish production, particularly in Bangladesh. Hence, this study aims to investigate the impact of climate change on marine fish production in Bangladesh using data from 1961 to 2019. Data were obtained from the Food and Agriculture Organization, Bangladesh Meteorological Department, the World Development Indicators, and the National Oceanic and Atmospheric Administration. The autoregressive distributed lag (ARDL) model was used to describe the dynamic link between CO2 emissions, average temperature, Sea Surface Temperature (SST), rainfall, sunshine, wind and marine fish production. The ARDL approach to cointegration revealed that SST (β = 0.258), rainfall (β =0.297), and sunshine (β =0.663) significantly influence marine fish production at 1% and 10% levels in the short run and at 1% level in the long run. The results also found that average temperature has a significant negative impact on fish production in both short and long runs. On the other hand, CO2 emissions have a negative impact on marine fish production in the short run. Specifically, for every 1% rise in CO2 emissions, marine fish production will decline by 0.11%. The findings of this study suggest that policymakers formulate better policy frameworks for climate change adaptation and sustainable management of marine fisheries at the national level. Research and development in Bangladesh's fisheries sector should also focus on marine fish species that can resist high sea surface temperatures, CO2 emissions, and average temperatures.
Mining waste that is rich in iron-, calcium- and magnesium-bearing minerals can be a potential feedstock for sequestering CO2 by mineral carbonation. This study highlights the utilization of iron ore mining waste in sequestering CO2 under low-reaction condition of a mineral carbonation process. Alkaline iron mining waste was used as feedstock for aqueous mineral carbonation and was subjected to mineralogical, chemical, and thermal analyses. A carbonation experiment was performed at ambient CO2 pressure, temperature of 80 °C at 1-h exposure time under the influence of pH (8-12) and particle size (
In this study, we are reporting a novel prediction model for forecasting the carbon dioxide (CO2) fixation of microalgae which is based on the hybrid approach of adaptive neuro-fuzzy inference system (ANFIS) and genetic algorithm (GA). The CO2 fixation rate of various algal strains was collected and the cultivation conditions of the microalgae such as temperature, pH, CO2 %, and amount of nitrogen and phosphorous (mg/L) were taken as the input variables, while the CO2 fixation rate was taken as the output variable. The optimization of ANFIS parameters and the formation of the optimized fuzzy model structure were performed by genetic algorithm (GA) using MATLAB in order to achieve optimum prediction capability and industrial applicability. The best-fitting model was figured out using statistical analysis parameters such as root mean square error (RMSE), coefficient of regression (R2), and average absolute relative deviation (AARD). According to the analysis, GA-ANFIS model depicted a greater prediction capability over ANFIS model. The RMSE, R2, and AARD for GA-ANFIS were observed to be 0.000431, 0.97865, and 0.044354 in the training phase and 0.00056, 0.98457, and 0.032156 in the testing phase, respectively, for the GA-ANFIS Model. As a result, it can be concluded that the proposed GA-ANFIS model is an efficient technique having a very high potential to accurately predict the CO2 fixation rate.