Asymmetric role of green energy, innovation, and technology in mitigating greenhouse gas emissions: evidence from India.

The primary cause of environmental degradation, which poses a danger to the long-term viability of the ecosystem, is the emission of greenhouse gases (GHG). For this reason, the Glasgow Climate Pact (COP26) established a decarbonization goal in response to this ecological concern, for which all economic players have a responsibility. India is among the participants who have a target set for them to decarbonize their economies by the year 2060 via the use of green energy and the advancement of science and innovation. Nevertheless, the asymmetrical effect of green energy, technology, and innovation on India's decarbonization program was not sufficiently explored in the prior study; hence, this research aims to fill this literature vacuum by considering India's GHG emissions from 1990 to 2020 by leveraging the non-linear autoregressive distributed lag (NARDL) model. The findings reveal the asymmetric influences of variables of interest on GHG emissions during the short and long term and under positive and negative shocks. Regarding the positive shock, long-term findings demonstrate that innovation and technical know-how grow GHG emissions and accelerate environmental degradation. However, a negative shock in innovations and technological know-how is opposed to a positive shock and improving environmental conditions. Further, positive shocks in green energy boost environmental effectiveness by reducing GHG secretions in India. In contrast, the negative shock in green energy deteriorates the environment by triggering GHG releases. These factual findings compel the Indian government to prioritize green technologies in addition to green energy generation to decouple economic growth from greenhouse gas emissions and meet rising energy demands.

Unveiling the impact on corporate social responsibility through green tax and green financing: a PLS-SEM approach.

In today's global business landscape, the concepts of green financing and green tax have become pivotal instruments for fostering environmentally responsible practices. The purpose of 20this study is to comprehensively assess how green financing and green tax collectively influence CSR through various dimensions, including employees, customers, and communities. This research employs a partial least squares structural equation modeling (PLS-SEM) approach, which allows for a rigorous analysis of the complex relationships between the variables involved. Data is collected through surveys, enabling a quantitative evaluation of the impacts and interdependencies. The results indicate that green financing has a positive and significant impact on CSR through customer (ß = 0.609), employee (ß = 0.522), and community (ß = 0.509) dimensions. The results also show that green tax has a positive and significant impact on CSR through customer (ß = 0.183), employee (ß = 0.182), and community (ß = 0.296) dimensions. The findings of this study provide a deeper understanding of how green financing and green tax practices correlate with CSR, both separately and collectively. The implications of this research extend to multiple stakeholders. For businesses, the results offer strategic insights into how environmentally conscious financial practices align with CSR objectives. Policymakers can draw upon the findings to craft effective regulatory frameworks that incentivize sustainable business behavior. Additionally, stakeholders gain valuable insights into how businesses can harmonize economic success with environmental stewardship, promoting engagement with socially responsible entities. This research marks a distinct contribution to the academic landscape by delving into the synergistic impact of green financing and green tax on CSR, particularly within the distinctive context of Bangladesh. In doing so, it successfully addresses a noticeable void within the existing literature, providing fresh insights into the intricate dynamics and opportunities confronting businesses in developing nations.

Challenges Encountered in the Provision of Enteral Nutrition in Pediatric Intensive Care Unit: An Observational Study.

Background Enteral nutrition (EN) represents the preferred modality for nutrient administration in critically ill patients. However, it is fraught with challenges such as delayed initiation and recurrent interruptions, which can significantly impact patient clinical outcomes. A substantial proportion of these interruptions can be mitigated. In the present investigation, our objective was to scrutinize the practice of EN in the Pediatric Intensive Care Unit (PICU). We sought to ascertain the frequency and underlying causes of EN interruptions and assess their ramifications for nutrient delivery. Study design We conducted an observational study within the PICU of Mahatma Gandhi Mission's (MGM) Medical College and Hospital, Aurangabad. The study encompassed children admitted to the PICU for a period exceeding 24 hours who were receiving enteral feeds. We documented the time of commencing EN from the point of PICU admission, instances of enteral feeding interruptions, the number and duration of each interruption episode, and the reasons behind these interruptions. Subsequently, we categorized the causes of feeding interruptions into avoidable and non-avoidable determinants. Results Out of the 100 patients enrolled in this study, only 34% presented with normal nutritional status upon admission. Sixty-five percent of patients had their nutritional support initiated within the first 48 hours of admission to the PICU. The median duration from PICU admission to the initiation of EN was 32.5 hours, with a median interruption duration per patient of 40.96 hours. Common causes of interruptions included radiological procedures, respiratory distress, altered sensorium, presence of gastric aspirates, and surgical procedures. Upon analysis, it was determined that a substantial majority, constituting 74%, of these interruptions were avoidable. Conclusions The primary challenges associated with EN in the PICU encompass delayed initiation of enteral feeds and frequent interruptions. Importantly, a significant proportion of these issues are avoidable.

Does higher energy efficiency growth homogeneously affect carbon emission growth rate across developing Sub-Saharan African nations? The importance of utilizing clean energy.

Establishing a sustainable environment and acquiring a carbon-neutral status require Sub-Saharan African nations to reduce their year-on-year growth rates of carbon emission levels. Thus, this study considers a sample of 38 countries from this region and selects the time period from 2000 to 2020 for analyzing the annual carbon emission growth rate influencing impacts of energy efficiency, clean energy, institutional quality, international trade, and net receipts of foreign direct investment. Overall, for the full sample of Sub-Saharan African nations, the results verify that the enhancing the growth rate of energy efficiency improvement reduces both total and per capita annual carbon emission growth rates. Besides, the results endorse that enhancing renewable energy shares of the final energy consumption profiles and promoting good governance-led betterment of institutional quality also plunge emission growth rates in the long run. More importantly, energy efficiency improvement, renewable energy consumption, and better quality institutions are observed to jointly exert carbon emission growth rate-impeding effects, as well. By contrast, more openness to international trade is not seen to influence the carbon emission growth rates of the Sub-Saharan African nations of concern. Lastly, a greater share of net foreign direct investment receipts in the national output level is evidenced to boost annual carbon emission growth rates across this region; consequently, the pollution haven hypothesis is verified. Furthermore, these above-mentioned findings are found to be heterogeneous across groups of low-income and middle-income Sub-Saharan African nations. Accordingly, in line with the findings, a couple of policies are recommended to the governments of the Sub-Saharan African countries in order to guide them in designing effective environmental sustainability policies that are relevant for tackling climate change-related atrocities in the future.

Towards green economy and sustainable development in Bangladesh: assessing the role of social and environmental indicators.

The evolution towards a green economy integrating social, economic, and environmental concerns has opened a new window to pursue the sustainable development goals (SDGs), especially for emerging nations. Nonetheless, despite being a pressing concern on a global scale, empirical research into the potential for green economy development in the context of Bangladesh has remained notably inadequate. To fill this void, this study is an attempt to evaluate the connection among economic growth, carbon dioxide (CO2) emissions, education, life expectancy, and technology to conclude the ecological and socio-economic repercussions of a green economy in Bangladesh's framework of achieving SDGs. Considering the statistical features of the annual data from 1990 to 2019, the autoregressive distributed lag (ARDL) method has been employed to analyze the connections between the chosen variables. The empirical outcomes show that an upsurge in CO2 is accompanied by a 3.66% increase in GDP over the long term, suggesting a positive and statistically significant relationship between the two variables. In addition, GDP increases by about 4.2% for every 1% increase in life expectancy. However, the relationship between technological innovation and education found an insignificant positive linkage with GDP. The most important takeaway from these findings is that the growth of Bangladesh's economy is occurring at the expense of the environment. Hence, this research recommends that, as a developing nation, Bangladesh should concentrate on environment-friendly alternatives, which can be done through the introduction of a green economy to achieve a sustainably developed economy.

Impact of banking development and renewable energy consumption on environmental sustainability in Germany: Novel findings using the bootstrap ARDL approach.

This study examines the effects of banking development, economic growth and consumption of renewable energy on carbon dioxide (CO2) emissions and load capacity factor (LCF). Previous empirical studies have assessed the interrelationship between banking development and CO2 emissions; however, these studies have ignored supply-side ecological issues. To overcome this issue, this study evaluates the effect of banking development on LCF, which is considered to be one of the most comprehensive ecological proxies to date, including both biocapacity and ecological footprint (EF). Using the bootstrap autoregressive distributed lag model, the study reveals that renewable energy improves ecological quality in Germany. The results of the investigation demonstrate that the environmental Kuznets curve hypothesis is valid in Germany using CO2 emissions and LCF indicators. Furthermore, this study demonstrates that banking growth and renewable energy in Germany correlate with improved environmental quality. These findings provide policymakers with important insights. In this context, the study advises the banking industry and government authorities to leverage banking expansion to support green energy to achieve the national goal of zero CO2 emissions by 2045.

Transitioning towards a sustainable environment: the dynamic nexus between economic complexity index, technological development and human capital with environmental quality in India.

This paper aims to investigate the dynamic nexus between economic complexity index (ECI), technological development (TIN), human capital (HC) and environmental quality in India for transition towards a sustainable environment. This study is based on secondary data covering the period from 1985 to 2018. For empirical analysis, this study applied "Stochastic Impacts by Regression on Population, Affluence, and Technology" (STIRPAT) model framework under the estimation of autoregressive distributed lag (ARDL) model and vector error correction model (VECM) model. The empirical findings of model 1 show ECI, TIN, HC and urbanization (URB) as the helping hands to mitigate the problem of environmental degradation by shrinking the level of EF, whereas for model 2, ECI and TIN failed to influence the CO2 emissions, but HC served as a stimulant for environmental quality enhancement by declining the level of CO2 emissions. In contrast, GDP growth and URB strengthen the CO2 emissions levels. Moreover, in VECM framework, estimated findings reveal that the covariables Granger-cause EF and CO2 emissions, inferring that causality flows asynchronously from its covariables to EF and CO2. Impulse response function (IRF) revealed that the responses in EF and CO2 emissions ascribed to changes in its covariables. The outcome of the study has some implications for environmental policy strategists to prepare sustainable environment policies and other responsible authorities for sustainable development goal (SDGs), academician and scholars. All the stakeholders involved in environmental economics and policymakers can evaluate this study to design proper policy framework with respect to the environment. There are few studies that explore the dynamic nexus between ECI, TIN and HC with environmental quality in the control environment of URB and GDP growth using the STIRPAT model for India.

The role of monetary and fiscal policies in determining environmental pollution: Revisiting the N-shaped EKC hypothesis for China.

The equilibrium between environmental quality and economic growth is one of the contemporary objectives of fiscal and monetary policies in the case of China. In this study, we investigate the extent of the existence of the N-shaped environmental Kuznets curve (EKC) hypothesis and measure the collision of fiscal and monetary policy on carbon emissions within the economic growth perspectives that China is witnessing. This study examines the dynamic nexus between monetary supply, government expenditure, and carbon emissions in China over the spanning from 1980 to 2019. The findings demonstrate that the money supply reduces carbon emissions in the short- and long-run. Precisely, a 1-unit augmentation in monetary policy tool (money supply) will significantly reduce the pressure on the environment by 0.29332 unit in the long-run and 0.79311 unit in the short-run. In contrast, the fiscal policy instrument (government expenditure) contributes to the increase in carbon emissions. Specifically, a 1-unit increase in government expenditure will increase the carbon emission by 0.17835 and 0.48247 units in the long-run and short-run, respectively. Additionally, the result also confirmed the N-shaped EKC hypothesis. Particularly, at the initial stage of economic growth, there are 1.58659 and 4.29197 unit increas in carbon emission in the long-run and short-run, respectively. However, after taking the square of economic growth, this reduces the environmental pollution by 0.3018 and 0.81665 units in the long-run and short-run, respectively. Finally, the cubic form of economic growth shows the 0.01755 and 0.04747 units increase in the pollution level in the long-run and short-run, respectively. Moreover, the study also found the presence of a causality link between government expenditure, economic growth, and carbon emissions. These findings will aid policymakers in implementing fiscal and monetary policies that promote long-term development while lowering carbon emissions.

An autoregressive distributed lag approach for estimating the nexus between CO2 emissions and economic determinants in Pakistan.

Carbon dioxide (CO2) emissions have become a critical aspect of the economic and sustainable development indicators of every country. In Pakistan, where there is a substantial increase in the population, industrialization, and demand for electricity production from different resources, the fear of an increase in CO2 emissions cannot be ignored. This study explores the link that betwixt CO2 emissions with different significant economic indicators in Pakistan from 1960 to 2018 using the autoregressive distributed lag (ARDL) modelling technique. We implemented the covariance proportion, coefficient of determination, the Durbin Watson D statistics, analysis of variance (ANOVA), variance inflating factor (VIF), the Breusch-Pagan test, the Theil's inequality, the root mean quare error (RMSE), the mean absolute percentage error (MAPE), and the mean absolute error (MAE) for the diagnostics, efficiency, and validity of our model. Our results showed a significant association between increased CO2 emissions and increased electricity production from oil, gas, and other sources. An increase in electricity production from coal resources was seen to have resulted in a decrease in CO2 emissions. We observed that an increase in the gross domestic product (GDP) and population growth significantly contributed to the increased CO2 emissions. The increment in CO2 emissions resulting from industrial growth was not significant. The increment in CO2 emissions in the contemporary year is significantly associated with the preceding year's increase. The rate of increase was very alarming, a sign that no serious efforts have been channelled in this regard to reduce this phenomenon. We call for policy dialogue to devise energy-saving and CO2 emission reduction strategies to minimize the impact of climate change on industrialization, population growth, and GDP growth without deterring economic and human growth. Electricity production from different sources with no or minimal CO2 emissions should be adopted. We also recommend rigorous tree planting nationwide to help reduce the concentration of CO2 in the atmosphere as well as environmental pollution.

Impact of technology on the relation between disaggregated energy consumption and CO2 emission in populous countries of Asia.

All around the world, but particularly in developing nations, carbon dioxide emissions are on the rise, and climate change and global warming are brought on by an increase in CO2 emissions. This article provides an overview of the technological effect on energy consumption in the residential, transport, and industrial sector and its ultimate effect on the environment. Using the STIRPAT-Kaya-EKC model for the years 1990 to 2020, this study looked at the threshold impact of technological advancements on the link between disaggregated energy use and CO2 emissions for a panel of 10 Asian countries using the panel threshold regression. Findings demonstrate that the EKC phenomenon is present in the chosen Asian region. Findings also suggest that technology has a threshold influence on the relationship between energy use and carbon emissions; however, this effect varies across sectors.

Investigating the nexus between trade policy uncertainty and environmental quality in the USA: empirical evidence from aggregate and disaggregate level analysis.

Worldwide, environmental sustainability is a hot topic, particularly in industrialized countries due to their higher emission intensity. Environmental conservation and equitable economic growth have been prioritized in economic debate and policy development. Over the past three decades, the USA's emissions of carbon dioxide (CO2e) have risen exponentially, as trade policy uncertainty (TPU). In this circumstance, this paper aims to contribute to the existing literature by exploring the effect of TPU on environmental quality by controlling the energy consumption, economic growth, and population in the USA over the period 1985M1 to 2022M3 employing the augmented ARDL and NARDL procedures in the presence of structural breaks. From our analysis, the results revealed that TPU affects negatively CO2e in the residential sector, and negative changes in TPU positively affect CO2e in the commercial sector both in the long and short run. On the other side, the outcomes show that energy consumption is a crucial key determinant factor in environmental degradation at the aggregate level and in all sectors. Furthermore, our findings clarify that economic growth upsurges the CO2e at the aggregate level precisely in the industrial and residential sectors. Juxtaposing, in the long run, the results indicate that population growth could make additional pressure on environmental quality at the aggregate level, especially in commercial, power generation, and residential sectors. Accordingly, it is clear from our results that the regulations put in place to encourage Americans to buy locally created goods instead of those imported, especially in light of the high levels of TPU, maybe the best option to decrease the long-term impact of international trade on the environment to achieve sustainable development goals (SDGs).

Study on the coupling and coordination degree between urban tourism development and habitat environment in the Yangtze River Delta in China.

By constructing the two evaluation systems of urban tourism development (TD) and habitat environment (HE), the dynamic response relationship between the two systems in the Yangtze River Delta urban agglomeration from 2001 to 2020 is explored by using panel vector autoregression (PVAR) model and coupled coordination degree model. The study unearthed four intriguing findings: (1) the level of TD in the study area has been continuously rising from 2001 to 2020, with an initial slow growth rate and then fast. The level of HE is increasing steadily at an average annual rate of 7.05%. There exists a reciprocal response relationship between the two systems, with a strong shock effect in the short term and a synergistic evolution in the long term. (2) The coupling degree between the urban TD and HE has an increasing trend, and the coupling coordination degree of the two systems has an average annual rate of 4.165%, implying the interaction and promotion effect between the two systems is improving. (3) Most of the cities in the Yangtze River Delta gradually realize the evolution from dysfunctional type to coordinated type, but the overall coordination intensity is low. (4) The barrier degrees of TD system indicators show a small annual increasing trend, while the barrier degrees of HE system indicators show a substantial and continuous decreasing trend. In terms of the barrier degree factors, some important factors that restrict the coupled and coordinated development of the two systems are also reported. This research can provide a useful reference for the synergistic improvement of urban tourism economy and habitat environment.

Risk assessment in livestock supply chain using the MCDM method: a case of emerging economy.

The purpose of the study is to identify and assess the risks related to the livestock supply chain. The major risk related to the livestock supply chain are identified through the comprehensive literature review and finalized with the help of the expert's feedback. Initially, seventeen major livestock supply chain risks are finalized, and these risks are categorized into four major dimensions. Further, analytical hierarchical process (AHP) is used to prioritize these identified major risks based on their severity. Finally, sensitivity analysis is conducted to check the robustness of the risk priorities. The result shows that "input supply risk" is the most significant risk dimension followed by "production risk," "post-harvest risk," and "marketing & price risk." The finding also suggests that "poor quality and under supply of feed and fodder," "lack of proper waste disposal," and "absence of certification for the quality of animals" are the major risks among all seventeen risks. The highest priority risks are input supply risks which require the attention of the livestock supply chain partners. The proposed research framework is used to identify and analyze the livestock supply chain risks. The findings of this research might be beneficial for the farmers and other livestock supply chain stakeholders in developing policies/plans/strategies to control the risk in their livestock supply chain.

Potential antitumour effect of all-trans retinoic acid on regorafenib-treated human colon cancer cell lines.

Introduction: Colorectal cancer (CRC) is a significant contributor to cancer-related mortality worldwide, ranking as the second leading cause of such deaths. Central to the progression of this malignancy is angiogenesis - a complex process orchestrated by vascular endothelial growth factor (VEGF). Regorafenib, a potent multikinase inhibitor, acts as a critical antagonist of multiple kinases involved in angiogenesis, proliferation, and metastasis. Conversely, all-trans retinoic acid (ATRA) has demonstrated compelling antitumour effects across various cancer types. This study aims to comprehensively evaluate the combined antitumour potential of ATRA and regorafenib in human colon cancer cell lines while elucidating the intricate molecular mechanisms that underlie their action. Material and methods: Our investigative approach involved an enzyme-linked immunosorbent assay to meticulously analyse the levels of key players in the VEGF signalling pathway, including VEGF itself, activated protein kinase (AMPK), extracellular signal-regulated protein kinase 1 (ERK1), and nuclear factor kappa B (NF-κB). Additionally, we assessed caspase-3 activity as a fundamental marker of apoptosis. Results: The combined use of ATRA and regorafenib exhibited a remarkable augmentation in both AMPK and caspase-3 activities. This was accompanied by a significant reduction in VEGF, ERK1, and NF-κB levels within human colon cancer cell lines subjected to regorafenib treatment. Conclusions: Our findings underscore the remarkable antiproliferative, antiangiogenic, and proapoptotic effects resulting from the combined use of ATRA and regorafenib in the context of CRC. This modulation of tumourigenic processes is predominantly mediated through the VEGF signalling axis.

Childhood Tuberculosis and Isoniazid Preventive Therapy Among Household Contacts of Sputum Positive Pulmonary Tuberculosis Patients: A Descriptive Observational Study.

Background The prevalence of tuberculosis (TB) disease among household contacts of adult TB patients is very high. Contact screening and isoniazid preventive therapy (IPT) are recommended for household contacts, but their uptake by families and implementation by the national TB program are poor. This study was performed to estimate the yield of tuberculosis disease, risk factors associated with disease development, and coverage of IPT in household contacts of sputum-positive pulmonary tuberculosis patients in the Aurangabad district of Maharashtra. Methods A cross-sectional study was conducted at MGM Medical College Hospital Aurangabad. Sputum-positive adult TB patients were enrolled in the study. Their household contacts were screened for TB disease, and the status of IPT in eligible contacts was studied. Serial screening and follow-up of these contacts were performed for one year. Results A total of 82 contacts of 55 index cases were studied. At the one-year follow-up, 15 (18%) patients developed TB disease. Twelve had pulmonary TB, and three had extrapulmonary TB. The mean age of diseased contacts was 5.5 years. The disease was more common in contacts under six years of age. Sixty-four percent of eligible contacts received IPT. There was a statistically significant association between disease development and noncompliance with IPT (p-value 0.005913). Conclusions The yield of tuberculosis disease is high in children contacts with sputum-positive pulmonary TB cases. IPT implementation is inadequate in child contact.

Analyzing the Asymmetric Effect of Renewable Energy Consumption on Environment in STIRPAT-Kaya-EKC Framework: A NARDL Approach for China.

This study aims to analyze the asymmetric relation between renewable energy consumption and CO2 emissions in China using the STIRPAT-Kaya-EKC framework. To delve into the asymmetric effect of renewable energy consumption on the environment, the non-linear ARDL model is used. The results of this study confirm the asymmetric impact of renewable energy on the environment in the long run as well as in the short run. However, the negative shocks to renewable energy have a greater detrimental influence on the environment than the benign effect due to the positive shock to renewable energy. Population growth affects the environment in the short run, whereas technology only affects environment quality in the long run. Moreover, the study supports the EKC theory in China. This research emphasizes that the administration can improve the economy's lifespan by allocating substantial funds to establish legislation to maintain a clean environment by subsidizing renewable energy infrastructure and research and innovations for low-carbon projects.

Forecasting carbon emissions due to electricity power generation in Bahrain.

Global warming and climate change have become one of the most embarrassing and explosive problems/challenges all over the world, especially in third-world countries. It is due to a rapid increase in industrialization and urbanization process that has given the boost to the volume of greenhouse gases (GHGs) emissions. In this regard, carbon dioxide (CO2) is considered a significant driver of GHGs and is the major contributing factor for global warming. Considering the goal of mitigating environmental pollution, this research has applied multiple methods such as neural network time series nonlinear autoregressive, Gaussian Process Regression, and Holt's methods for forecasting CO2 emission. It attempts to forecast the CO2 emission of Bahrain. These methods are evaluated for performance. The neural network model has the root mean square errors (RMSE) of merely 0.206, while the Gaussian Process Regression Rational Quadratic (GPR-RQ) Model has RMSE of 1.0171, and Holt's method has RMSE of 1.4096. Therefore, it can be concluded that the neural network time series nonlinear autoregressive model has performed better for forecasting the CO2 emission in the case of Bahrain.